Nov 12, 2018 | Volume 8 - Issue 4
Jeffrey M. Warren, Leslie A. Locklear, Nicholas A. Watson
This study explored the relationships between parenting beliefs, authoritative parenting style, and student achievement. Data were gathered from 49 parents who had school-aged children enrolled in grades K–12 regarding the manner in which they parent and their child’s school performance. Pearson product-moment correlation coefficients and multiple regression modeling were used to analyze the data. Findings suggested that parent involvement, suspension, and homework completion significantly accounted for the variance explained in grade point average. Authoritativeness was positively and significantly related to both rational and irrational parenting beliefs. Irrational parenting beliefs were positively and significantly related to homework completion. School counselors are encouraged to consider the impact of parenting on student success when developing comprehensive programming.
Keywords: student achievement, homework completion, irrational parenting beliefs, authoritative parenting, school counseling
There are many indicators of success as students matriculate through elementary, middle, and high school. Student success is generally defined by the degree to which students meet or exceed a predetermined set of competencies (York, Gibson, & Rankin, 2015). These competencies are often academic in nature and align with state curriculum. Data collected at numerous points (i.e., formal and informal assessment) throughout an academic year are used to monitor student performance. Student achievement data, including end-of-grade tests and grade point average (GPA), are key determinants of student outcomes such as promotion or retention (Schwerdt, West, & Winters, 2017). Although both are distal data points that measure achievement, GPA is a cumulative measure of student performance based on mental ability, motivation, and personality demonstrated throughout the course of a school year (Imose & Barber, 2015; Spengler, Brunner, Martin, & Lüdtke, 2016).
Numerous factors are related to and impact student achievement. According to Hatch (2014), these factors include discipline referrals, suspension, homework completion, and parental involvement. Research suggests that these factors are good indicators of distal or long-term academic success (Kalenkoski & Pabilonia, 2017; LeFevre & Shaw, 2012; Noltemeyer, Ward, & Mcloughlin, 2015; Roby, 2004). Although it is a challenge to determine student progress based on GPA alone, these variables can be monitored across the school year for a real-time snapshot of student success (Hatch, 2014).
The American School Counselor Association (ASCA; 2012) has suggested that school counselors work to promote student success by operating across three distinct areas or domains: academic, social and emotional, and career development. As such, school counselors play an integral role in developing, delivering, and evaluating programs that promote academic achievement. School counselors are challenged to determine the direct impact of services on student achievement. Student achievement–related data can be measured to understand the impact of school counseling interventions. For example, a study skills curriculum such as SOAR® (SOAR Learning Inc., 2018) may increase homework completion by 20%. School counselors can infer that the intervention will lead to increases in student achievement; literature suggests homework completion is positively correlated with GPA (Kalenkoski & Pabilonia, 2017).
Although school counselors often work directly with students, they also can engage in efforts to promote student achievement through work with parents and families. For example, Ray, Lambie, and Curry (2007) suggested school counselors can offer parenting skills training to promote positive parenting practices. Other authors have advocated to strengthen the partnerships with and involvement of parents, which are factors related to student achievement (Bryan & Henry, 2012; Epstein, 2018). In developing interventions that aim to build partnership and increase involvement, it is important for school counselors to understand the values, assumptions, beliefs, and behaviors of parents (Bryan & Henry, 2012). During the initial stages of partnering with families, school counselors should address any biases and assumptions that may impede the partnership (Warren, 2017). Furthermore, strategies and interventions should be data-driven and aim to promote student achievement (Hatch, 2014). In the current study, researchers examined the relationships between parenting beliefs, authoritative parenting style, and student achievement. School counselors who understand the relationships between these factors are best positioned to meet the needs of all students.
Parenting Beliefs
The beliefs parents maintain are especially pertinent to the overall wellness and success of their children (Warren, 2017). At times, parents may place unreasonable demands on themselves, their children, or the practice of parenting in general. For example, a parent may think, “My child should always do what I say, and I cannot stand it otherwise.” This belief can have a detrimental impact on the parent–child relationship and family unit as well as the psychosocial development of the child (Bernard, 1990).
Rational emotive behavior therapy (REBT), developed by Ellis (1962), emphasizes two main types of thoughts pertinent to the beliefs of parents: rational and irrational. Rational thoughts are flexible and preferential in nature. These thoughts lead to healthy emotions and functional behaviors. Alternatively, irrational beliefs are rigid and dogmatic and stem from demands placed on the self, others, and life. “Life should always treat me fairly and it is horrible when it does not,” is an example of an irrational belief. This belief can lead to unhealthy emotions (e.g., anger, depression) and result in unhelpful or dysfunctional behavior.
A central goal of REBT is to advance acceptance of the self, others, and life in general. In turn, individuals are encouraged to abstain from global evaluations or rating the self, others, or life as totally bad. When striving toward acceptance, individuals are happier and more successful in life (Dryden, 2014). Researchers have studied REBT and associated constructs among various populations, including children (Gonzalez et al., 2004; Sapp, 1996; Sapp, Farrell, & Durand, 1995; Warren & Hale, 2016), teachers (Warren & Dowden, 2012; Warren & Gerler, 2013), college students (McCown, Blake, & Keiser, 2012; Warren & Hale, in press), and parents (Terjesen & Kurasaki, 2009; Warren, 2017). Literature suggests a strong correlation between irrational beliefs and dysfunction, regardless of the measure used or sample under investigation.
Findings from Hamamci and Bağci (2017) have suggested that a relationship exists between family functioning and the degree to which parents hold irrational expectations about their children. Emotional support and responsiveness of parents deteriorate with an increase in irrational beliefs. Additionally, child behavior issues are more prevalent when parents think irrationally. Hojjat et al. (2016) found that children are more susceptible to substance abuse when their parents maintain irrational beliefs and unrealistic expectations. Parenting styles that advance unrealistic or irrational academic expectations may stifle academic success and promote the development of irrational beliefs and unhealthy negative emotions (e.g., anxiety) in children (Kufakunesu, 2015).
Parenting Styles
Parenting style is most often used to broadly describe how parents interact with their children. In 1966, Diana Baumrind presented three major parenting styles: authoritarian, authoritative, and permissive. Later, Maccoby and Martin (1983) identified a fourth style of parenting: neglectful. Parenting styles are defined by collections of attitudes and behaviors expressed to children by their parents (Darling & Steinberg, 1993) and are often based upon the degree of demandingness/control and responsiveness. Parents who maintain an authoritarian parenting style are highly demanding, yet emotionally unresponsive, while authoritative parents exude high demands, but are communicative and responsive (Baumrind, 1991). Permissive parents, on the other hand, are responsive, yet lack firm control of their children; neglectful parenting involves a lack of emotional support as well as little control (Pinquart, 2016).
The manner in which parents parent can impact their child’s success in school. Of the four parenting styles described, research findings suggested that models of parenting aligning with the authoritative parenting style are most closely linked to student achievement (Carlo, White, Streit, Knight, & Zeiders, 2018; Castro et al., 2015; Kenney, Lac, Hummer, Grimaldi, & LaBrie, 2015; Masud, Thurasamy, & Ahmad, 2015). Additionally, the impact of parenting style on student success seems to vary little across culture. A meta-analysis conducted by Pinquart and Kauser (2018) suggested that children across the world may benefit academically from authoritative parents. Although a plethora of evidence supporting this relationship exists, a meta-analysis conducted by Pinquart (2016) found a small effect size, suggesting the relationship between authoritative parenting and student achievement is minimal. Regardless, the manner in which parents interact with their children impacts many aspects of child development, including their ability to succeed in school.
Purpose of the Study
This article explores the relationships between parenting beliefs, styles, and student achievement. Ellis, Wolfe, and Moseley (1981) suggested parents’ behaviors stem from their thoughts and emotions. These beliefs impact the manner in which parents interact with their children. For example, parents who hold rigid or extreme beliefs may respond to their children more negatively than parents who maintain a flexible belief system. As such, parenting beliefs may impact parenting style, and therefore the success of students. However, the literature is scant when exploring the relationships between parenting beliefs, parenting style, and student achievement.
In order to work effectively with parents, it is important that school counselors understand parenting beliefs and styles and their impact on student achievement. Several research questions guided this study, including: (a) Is there a relationship between student achievement and parental involvement, homework completion, discipline referrals, and suspensions?; (b) Is authoritative parenting related to student achievement?; and (c) Are parenting beliefs related to student achievement? Based on these research questions and existing literature, the following hypotheses were generated: Hypothesis #1: A significant relationship exists between GPA and student achievement–related variables. Hypothesis #2: Rational, irrational, and global evaluation parenting beliefs are predictive of authoritative parenting. Hypothesis #3: Authoritative parenting is significantly positively related to student achievement. Hypothesis #4: Parenting beliefs are significantly related to student achievement–related variables.
Method
Participants
This study included parents living in the southeastern United States (N = 49) who self-reported having children enrolled in elementary, middle, or high school. Of the participants, 96% (n = 47) were mothers, while 4% (n = 2) were fathers. Regarding race and ethnicity, 45% (n = 22) identified as White, 41% (n = 20) identified as American Indian, 8% (n = 4) identified as African American, and 6% (n = 3) identified as Hispanic/Latino. The mean age of the participants’ children was 11 years old; ages ranged from 5 to 18. All grade levels (K–12) across elementary (n = 28), middle (n = 6), and high school (n = 15) were represented, with second grade represented most frequently.
G*Power 3.1, developed by Faul, Erdfelder, Lang, and Bucher (2007), was utilized during an a priori power analysis. The author conducted the power analysis to ascertain the minimum number of participants needed to reach statistical significance, should it exist among the variables under investigation. With statistical power set at .80 and alpha level set at .05, the analysis produced a minimum sample size of 40. This sample size was large enough to detect a medium effect size
(f2 = .35). As a result, the sample size was sufficient to explain the relationships between the predictor and criterion variables.
Instruments
The parents who participated in this study completed a demographic questionnaire and two surveys. The demographic questionnaire, developed by the first author, captured race/ethnicity and gender of the parent in addition to the level of involvement in their child’s schooling. Student achievement–related questions also were asked to capture the age of the participant’s child, grade level, GPA, homework completion percentage, and number of discipline referrals and suspensions. Participants responded to questions such as, “What percentage of your child’s homework is completed on a weekly basis?” Other surveys utilized in this study include the following.
Parental Authority Questionnaire–Revised (PAQ-R; Reitman, Rhode, Hupp, & Altobello, 2002). The PAQ-R is a 30-item self-report measure of parenting style. The PAQ-R is a revision of the Parental Authority Questionnaire (PAR; Buri, 1991) and is grounded in the work of Baumrind (1971). Three subscales, Authoritarian, Authoritative, and Permissive, comprising 10 items each, assess the degree to which parents exhibit control, demand maturity, and are responsive and communicative with their child. Participants indicate their level of agreement with statements such as, “I tell my children what they should do, but I explain why I want them to do it” using a 5-point Likert-type scale ranging from strongly disagree (1) to strongly agree (5).
Findings from a study conducted by Reitman et al. (2002) suggested that the PAQ-R is a reliable measure of authoritarian, authoritative, and permissive parenting styles when considering respondents’ demographic characteristics such as socioeconomic status or race. The Authoritarian (r = .87), Authoritative, (r = .61), and Permissive (r = .67) subscales of the PAQ-R have good test-retest reliability at one month. The Authoritarian (r = .25) and Authoritative (r = .34) subscales were positively correlated with the Communication subscale of the Parent-Child Relationship Inventory (Gerard, 1994), suggesting convergent validity. Across three distinct samples of parents, coefficient alphas ranged from .72 to .76 for Authoritarian, .56 to .77 for Authoritative, and .73 to .74 for Permissive, demonstrating internal consistency (Reitman et al., 2002).
In the current study, only the Authoritative subscale was used. The demographic characteristics of participants in Sample A in a study conducted by Reitman et al. (2002) most closely aligned with the sample in the present study. Factor loadings for Sample A were identical to the Authoritative subscale of the original PAR and therefore used in this study. For the present study, the Authoritative subscale has an internal consistency of .69.
Parent Rational and Irrational Belief Scale (PRIBS; Gavita, David, DiGiuseppe, & DelVecchio, 2011). The PRIBS was used in this study to assess participants’ beliefs related to their child’s behavior and parenting roles. The self-report instrument contains a total of 24 items; four are control items. Three subscales, Rational Beliefs (RB), Irrational Beliefs (IB), and Global Evaluation (GE), comprise the remaining 20 items. The RB subscale contains 10 items and assesses the degree to which preferential and realistic thoughts related to parenting are maintained. The IB subscale includes six items and evaluates the demands parents place on themselves and their child. The GE subscale comprises four items and assesses the degree to which parents globally rate themselves or their children.
A 5-point Likert-type scale ranging from strongly disagree (1) to strongly agree (5) is used to respond to items such as, “My child must absolutely respect and obey me.” Scores on the PRIBS generally range from 39 (very low) to 60 (very high). The PRIBS and its subscales are significantly correlated with other measures of irrationality and negative emotion, including the General Attitudes and Beliefs Scale-Short Form (Lindner, Kirkby, Wertheim, & Birch, 1999) and the Parental Stress Scale (Berry & Jones, 1995). Gavita et al. (2011) suggested the PRIBS is a reliable measure of parent irrationality; test-retest reliability (r = .78) for the full scale was acceptable after two months. Internal consistency for the PRIBS was .73. The coefficient alphas for RB, IB, and GE were .83, .78, and .71, respectively. For the current study, an internal consistency coefficient of .46 was found for the PRIBS. Additionally, coefficient alphas for the subscales are .62 (RB), .80 (IB), and .43 (GE). All PRIBS subscales were used in this study.
Procedure
A review of literature was conducted in an effort to identify the measures for use in this study. Additionally, a brief demographic instrument was developed to obtain relevant parent and child demographic information. Qualtrics survey software was utilized to prepare the survey packet (i.e., informed consent, demographic questionnaire, and surveys) for electronic dissemination. An application to complete the study then was submitted for review to the institutional review board (IRB) at the researchers’ university. Upon IRB approval, the researchers disseminated an electronic message containing a link to the research packet via a graduate counseling student listserv. An email also was distributed to staff who worked in the School of Education at the researchers’ university. The email contained a request for parents of K–12 students to participate in the study; recipients also were asked to forward the email to family, friends, and colleagues. The email was disseminated on three occasions across two weeks. Participants who completed the study were entered into a drawing for a chance to win $50.
Results
Preliminary Analyses
In order to gain a better understanding of the student achievement–related data collected during this study, initial analyses were conducted. Prior to analysis, GPA was calculated using a letter grade–GPA conversion table; parents reported letter grades on the survey. As such, grades of A+, A, and A- equated to GPAs of 4.33, 4.0, and 3.67, respectively. The student achievement–related variables included in the initial analyses were parental involvement, discipline referrals, suspensions, and homework completion.
Pearson product-moment correlation coefficients and multiple regression analyses were used to test the hypothesis that GPA is related to and predicted by these student achievement–related variables. The degree of parental involvement and homework completion were positively and significantly related to GPA. Suspensions were negatively and significantly related to GPA. Discipline referrals were not significantly related to GPA. The descriptive statistics and correlations for these variables are offered in Table 1.
Prior to additional analysis, basic assumptions of multiple regression analysis were tested and satisfied. Standardized residual plots and Q-Q plots were inspected; bivariate correlations also were examined. Next, a multiple regression analysis including parent involvement, suspensions, and homework completion as predictors was conducted with GPA as the criterion variable. Discipline referrals were not included in the regression analysis. A significant regression equation was found: F(3, 45) = 11.539, p < .001. The model with these three predictors explained a significant amount of the variance in GPA (R2 = .435). Significant contributions were made to the model by each of the three predictor variables: parent involvement (β = .284, p < .05), suspensions (β = -.369, p < .05), and homework completion (β = .273, p < .05).
Main Analyses
A multiple linear regression was used to test the hypothesis that authoritative parenting is predicted by parenting beliefs. Authoritative parenting served as the criterion variable. RB, IB, and GE were predictor variables. A combination of these predictor variables yielded a significant regression equation: F(3, 38) = 14.536, p < .000. The model explained a significant portion of variance (53%) in authoritative parenting (see Table 2). Additionally, RB (β = .38, p < .05) was positively and significantly related to authoritative parenting. IB (β = .46, p < .001) also was positively and significantly correlated with authoritative parenting. GE did not contribute significantly to the model (β = -.25 p > .05).
A simple linear regression was performed to test the hypothesis that authoritative parenting predicts student achievement. Based on prior research findings that suggest authoritative parenting is related to positive student achievement, authoritative parenting served as a predictor variable; the criterion variable was GPA. Output from the analysis revealed that authoritative parenting did not predict GPA for this sample of parents: F(1, 40) = .642, p > .05.
Finally, the hypothesis that parenting beliefs predict student achievement–related variables was tested using multiple linear regression modeling. IB, RB, and GE were predictor variables and parent involvement, suspension, and homework completion were criterion variables. A combination of these predictor variables yielded a non-significant regression equation when parental involvement was the criterion variable: F(3, 37) = 1.773, p = .169. Suspensions were not predicted by RB, IB, or GE: F(3, 37) = 1.232, p = .312. Finally, a combination of these predictor variables yielded a non-significant regression equation when homework completion was the criterion variable: F(3, 37) = 2.382, p = .085. Although this model did not explain variance in homework completion, IB was positively and significantly related to homework completion: t(39) = 2.34, p = .025; β = .357.
Discussion
The hypotheses put forth based on previous research and literature were supported and refuted in various instances based on the analyses of the data collected. In regard to the first hypothesis, all student achievement–related factors except discipline referrals were significantly related to GPA. This finding is consistent with research that explores the relationships of proximal student achievement–related factors and distal student achievement outcomes. Parental involvement in their child’s schooling, homework completion, and suspensions are predictors of GPA. Each of these variables contributed to the overall model for predicting student achievement. This finding demonstrates the value of parental involvement and homework completion in the success of students. Additionally, the negative impact of suspension on the academic achievement of students is highlighted. This outcome signals the importance of fostering safe and inviting schools and establishing policies that offer alternatives to suspension unless absolutely necessary.
The second hypothesis purported that authoritative parenting is significantly related to RB, IB, and GE. This hypothesis was supported; combined, RB, IB, and GE predicted authoritative parenting. Research findings suggest that authoritative parenting is related to student achievement, so it is counterintuitive that both RB and IB are positively related to authoritativeness. IB typically lead to dysfunction rather than positive outcomes such as student achievement (Terjesen & Kurasaki, 2009). However, according to Reitman et al. (2002) and others, authoritative parents are demanding, yet supportive of their children. The demandingness described in this parenting style may be a derivative of irrational thinking, as evidenced by the significant contribution of IB to the model. As suggested by Bernard (1990), parents who place rigid demands on their children may be less supportive; effective communication also may fluctuate. It is likely that an acceptable balance of demands, free of unrealistic, rigid expectations, coupled with support, is most effective when considering the role of authoritative parenting on student achievement. Excessive or unrealistic demands may lead to increases in student achievement, but at the expense of the parent–child relationship as well as mental health. In turn, these demands may serve as a barrier to home and school success (Terjesen & Kurasaki, 2009; Warren, 2017).
Closely tied to the second hypothesis, the third hypothesis suggested that authoritative parenting is significantly positively related to student achievement. Based on the data set analyzed, this hypothesis was not supported. This finding is inconsistent with previous research, which stated that the authoritative parenting style correlates to positive student achievement. In a meta-analysis conducted by Pinquart (2016), a small effect size was found in the relationship between authoritativeness and student achievement. It is possible that a significant relationship exists, yet was not found in this study because of a small sample size. Alternatively, authoritative parenting was not related to student achievement, a finding contrary to Pinquart (2016). Demographic variables such as race/ethnicity of participants (e.g., 40.8% American Indian) were not accounted for in this study and also may have implications for the findings.
The final hypothesis indicated that parenting beliefs are significantly related to student achievement–related variables; this hypothesis was partially supported. Although parenting beliefs were not predictive of parental involvement or suspensions, IB were significantly related to homework completion. Students who consistently complete their homework appear to have parents who maintain IB. Although homework completion is important and leads to academic achievement (Kalenkoski & Pabilonia, 2017), according to REBT, irrational thinking is unproductive and leads to unhealthy negative emotion and dysfunctional behaviors (Dryden, 2014). In some instances, it is possible that parents model unhelpful psychosocial processes (e.g., irrational thinking, anger, yelling) when facilitating the completion of their child’s homework. This may lead to rifts in the parent–child relationship and a general disdain for doing homework, especially that which is difficult or challenging. As such, it is important for parents to set realistic, high expectations for homework completion. These expectations should be based on the child’s strengths and weaknesses, clearly communicated, and consistently followed. Parents are encouraged to hold their children accountable without placing demands on themselves, their child, or the homework process in general (Warren, 2017).
Overall the data from this study presented interesting findings related to authoritative parenting style, beliefs, and student achievement. Certain factors such as homework completion and parental involvement were positively related to GPA; school suspension had a negative impact on GPA. Although these findings are not novel, consideration for the relationships between authoritativeness, parent beliefs, and student achievement in this investigation is noteworthy. Although homework completion was positively related to GPA, it also was correlated with IB. In combination, these findings provide an interesting perspective on the ways in which authoritativeness is related to parenting beliefs, which, in turn, appear to influence homework completion, a key determinant of positive distal student achievement outcomes. Although limitations exist, this study can help to facilitate the development of additional research and offers practical implications for school counselors.
Limitations
As suggested, there are several limitations of this study. When considering the generalizability of these results and potential implications for practice, readers should account for the method of data collection and the sample used in this study. First, data were gathered using self-report measures. Because of the nature of the questions asked on the survey, parents participating in this study may have provided socially desirable responses rather than indicating their actual parenting beliefs and behaviors. Additionally, the sample size was small, yet it was sufficiently sized to detect moderate effects. A convenience sample was used and likely is not representative of the general population. Students and faculty affiliated with a university listserv were contacted and asked to participate and disseminate the study information to their family and friends. A larger sample size would have increased the generalizability of these results and yielded greater power, including the ability to detect smaller effect sizes among the variables.
Future Research
Research investigating parenting styles, beliefs, and student achievement variables such as discipline referrals, suspension, and homework completion is sparse. This study offers a foundation for future empirical and action-based research in this area. Researchers initially are encouraged to replicate this study using a larger, more representative sample of parents with school-aged children. Replication may shed additional light on the strengths of the relationships of the variables explored in this study. Given the achievement gap, including the disproportionate suspension rates that exist in K–12 schools among students of color, it is especially important for researchers to explore the impact of parenting styles and beliefs on the achievement of students from historically underrepresented backgrounds. The American Indian population, specifically, is largely absent in research that explores factors of K–12 student success, yet over 500,000 American Indian students are enrolled in schools across the nation (Snyder, de Brey, & Dillow, 2018). This lack of research is a barrier for school counselors and other educators who seek to better support and understand American Indian families and students. Research that explores these relationships within and across specific racial/ethnic groups, including African American, Hispanic/Latino, and American Indian, can serve as a catalyst for school counselors to enhance service delivery and meet the needs of all students.
Researchers also are encouraged to explore the effects of targeted parenting interventions, such as rational emotive-social behavioral (RE-SB) consultation (Warren, 2017) on parenting and student achievement. School counselors can implement large group, small group, or individual RE-SB consultation with parents to address IB and promote student success (Warren, 2017). School counselors, in collaboration with researchers, can play a central role in the development, delivery, and evaluation of parenting interventions that aim to promote student success; these efforts also can further establish evidence-based practice in school counseling.
Implications for School Counselors
According to the ASCA National Model (ASCA, 2012), school counselors play an integral role in supporting the academic, social-emotional, and career development of all students through work with various stakeholders, including students, teachers, and parents. The findings of this study offer insight into the connection between parenting and student success. Operating in the academic domain, school counselors can deliver direct and indirect services to support the success of all students. The recommendations provided below serve to guide school counselors in identifying and delivering targeted programming that yields positive student outcomes.
A broad strategy for promoting academic success involves the establishment of a comprehensive school counseling program that includes interventions that aim to increase homework completion, decrease suspension rates, and increase parental involvement. As the findings of this study suggest, these factors have a direct impact on student achievement. Therefore, school counselors should leverage their roles as leaders, advocates, and consultants to ensure students are adequately supported by parents and positioned by their teachers to meet the daily expectations of school.
As educational leaders, school counselors are encouraged to engage parents, teachers, administrators, and students in ongoing, critical discussion about the relationships between student achievement–related factors and GPA. Classroom guidance, staff development sessions, and parent workshops are viable opportunities to disseminate this information and engage stakeholders. School counselors can involve teachers and administrators in discussions surrounding classroom and school policies and procedures that impact homework completion, suspension, and parent involvement. Leveraging student and school data during these conversations are more likely to lead to classroom and school policy revisions that accommodate all students and their families. When school counselors collaborate with teachers and administrators, innovative strategies and support structures to promote homework completion and alternatives to suspension will emerge.
School counselors also can use the findings of this study to increase their awareness of the values and beliefs of parents. Used within the context of culture, these findings can offer school counselors additional insights that may be useful when working with parents. For instance, when working with American Indian families, school counselors should consider how customs and traditions impact the manner in which parents engage with their children (Castagno & Brayboy, 2008). By understanding the culture of students and families while considering parenting styles and beliefs, school counselors can partner with parents in intentional ways in an effort to promote student achievement. It is especially important to consider strategies to engage parents who may experience barriers to visiting school. School counselors can seek community resources and partnerships that can be leveraged to increase parental involvement. Using asset mapping as promoted by Griffin and Farris (2010), school counselors can help parents connect to school via the workplace, church, or community centers.
School counselors are encouraged to work closely with parents to establish programming that best supports parents’ efforts to help their children succeed. RE-SB consultation, as described by Warren (2017), is a viable service to educate parents about parenting styles and the impact of their thoughts on emotions and behaviors. For example, school counselors can hold a workshop for parents during a PTA event to promote rational thinking. “Rational reminders” disseminated via the school’s social media account also can be useful for parents not familiar with REBT who are attempting to set realistic expectations and provide optimal support to their children. Interventions such as these can increase parents’ self-awareness of the influence they have on their children and lead to positive student outcomes.
Finally, school counselors should explore strategies that foster social-emotional development for all students and especially those with little parental support. Establishing support systems among students can increase their academic success (Sedlacek, 2017). Mentoring programs that resemble or simulate the parent–child relationship and model rational thinking may yield academic success, given the findings of this study. School counselors also can develop programming that aligns with non-cognitive factors as promoted by Warren and Hale (2016). Students who have a positive self-concept, realistically appraise themselves, are involved in the community, take on leadership roles, have experience in a specific field, and have a support network are better positioned to succeed in school and in life (Sedlacek, 2017). These efforts may position students for school success by neutralizing or reducing the negative impact a lack of parental involvement has on achievement.
Conclusion
School counselors play a critical role in today’s schools. Serving as leaders, advocates, collaborators, and consultants with an aim of promoting student success, school counselors work with many stakeholders, including teachers, administrators, and students and their parents. This study sheds light on the impact of suspension, homework completion, and parental involvement on student achievement. The relationships between parent beliefs and authoritativeness and student achievement also are explored. The authors hope the findings of this study foster awareness and lead school counselors to further consider the impact parents have on student achievement. An understanding of parenting style and beliefs and their impact on student achievement affords school counselors the opportunity to develop targeted programs that increase parent involvement, strengthen the school–parent partnership, and promote academic success.
Conflict of Interest and Funding Disclosure
The authors reported no conflict of interest
or funding contributions for the development
of this manuscript.
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Jeffrey M. Warren, NCC, is an associate professor and Chair of the Counseling Department at the University of North Carolina at Pembroke. Leslie A. Locklear is the FATE Director at the University of North Carolina at Pembroke. Nicholas A. Watson is a graduate student at the University of North Carolina at Pembroke. Correspondence can be addressed to Jeffrey Warren, 1 University Drive, Pembroke, NC 28372, jeffrey.warren@uncp.edu.
Nov 10, 2018 | Volume 8 - Issue 4
Zachary D. Bloom, Victoria A. McNeil, Paulina Flasch, Faith Sanders
Empathy plays an integral role in the facilitation of therapeutic relationships and promotion of positive client outcomes. Researchers and scholars agree that some components of empathy might be dispositional in nature and that empathy can be developed through empathy training. However, although empathy is an essential part of the counseling process, literature reviewing the development of counseling students’ empathy is limited. Thus, we examined empathy and sympathy scores in counselors-in-training (CITs) in comparison to students from other academic disciplines (N = 868) to determine if CITs possess greater levels of empathy than their non-counseling academic peers. We conducted a MANOVA and failed to identify differences in levels of empathy or sympathy across participants regardless of academic discipline, potentially indicating that counselor education programs might be missing opportunities to further develop empathy in their CITs. We call for counselor education training programs to promote empathy development in their CITs.
Keywords: empathy, sympathy, counselor education, counselors-in-training, therapeutic relationships
Empathy is considered an essential component of the human experience as it relates to how individuals socially and emotionally connect to one another (Goleman, 1995; Szalavitz & Perry, 2010). Although empathy can be difficult to define (Konrath, O’Brien, & Hsing, 2011; Spreng, McKinnon, Mar, & Levine, 2009), within the counseling profession there is agreement that empathy includes both cognitive and affective components (Clark, 2004; Davis, 1980, 1983). When discussing the difference between affective and cognitive empathy, Vossen, Piotrowski, and Valkenburg (2015) described that “whereas the affective component pertains to the experience of another person’s emotional state, the cognitive component refers to the comprehension of another person’s emotions” (p. 66). Regardless of specific nuances among researchers’ definitions of empathy, most appear to agree that “empathy-related responding is believed to influence whether or not, as well as whom, individuals help or hurt” (Eisenberg, Eggum, & Di Giunta, 2010, p. 144). Furthermore, empathy can be viewed as a motivating factor of altruistic behavior (Batson & Shaw, 1991) and is essential to clients’ experiences of care (Flasch et al., in press). As such, empathy is foundational to interpersonal relationships (Siegel, 2010; Szalavitz & Perry, 2010), including the relationships facilitated in a counseling setting (Norcross, 2011; Rogers, 1957).
Rogers (1957) intuitively understood the necessity of empathy in a counseling relationship, which has been verified by the understanding of the physiology of the brain (Badenoch, 2008; Decety & Ickes, 2009; Siegel, 2010) and validated in the counseling literature (Elliott, Bohart, Watson, & Greenberg, 2011). In a clinical context, empathy can be described as both a personal characteristic and a clinical skill (Clark, 2010; Elliott et al., 2011; Rogers, 1957) that contributes to positive client outcomes (Norcross, 2011; Watson, Steckley, & McMullen, 2014). For example, empathy has been identified as a factor that leads to changes in clients’ attachment styles, treatment of self (Watson et al., 2014), and self-esteem development (McWhirter, Besett-Alesch, Horibata, & Gat, 2002). Moreover, researchers regularly identify empathy as a fundamental component of helpful responses to clients’ experiences (Beder, 2004; Flasch et al., in press; Kirchberg, Neimeyer, & James, 1998).
Although empathy is lauded and encouraged in the counseling profession, empathy development is not necessarily an explicit focus or even a mandated component of clinical training programs. The Council for Accreditation of Counseling and Related Educational Programs (CACREP; 2016) identifies diverse training standards for content knowledge and practice among master’s-level and doctoral-level counselors-in-training (CITs), but does not mention the word empathy in its manual for counseling programs. One of the reasons for this could be that empathy is often understood and taught as a microskill (e.g., reflection of feeling and meaning) rather than as its own construct (Bayne & Jangha, 2016). Yet empathy is more than a component of a skillset, and CITs might benefit from a programmatic development of empathy to enhance their work with future clients (DePue & Lambie, 2014).
The application of empathy, or a counselor’s use of empathy-based responses in a therapeutic relationship, requires skill and practice (Barrett-Lennard, 1986; Truax & Carkhuff, 1967). Clark (2010) cautioned, for example, that counselors’ empathic responses need to be congruent with the client’s experience, and that the misapplication of sympathetic responses as empathic responses can interfere in the counseling relationship. In regard to sympathy, Eisenberg and colleagues (2010) explained, “sympathy, like empathy, involves an understanding of another’s emotion and includes an emotional response, but it consists of feelings of sorrow or concern for the distressed or needy other rather than merely feeling the same emotion” (p. 145). Thus, researchers call for counselor educators to do more than increase CITs’ affective or cognitive understanding of another’s experience, and to assist them in differentiating between empathic responses and sympathetic responses in order to better convey empathic understanding and relating (Bloom & Lambie, in press; Clark, 2010).
With the understanding that a counselor’s misuse of sympathetic responses might interrupt a therapeutic dialogue and that empathy is vital to the therapeutic alliance, researchers call for counselor educators to promote empathy development in CITs (Bloom & Lambie, in press; DePue & Lambie, 2014). Although there is evidence that some aspects of empathy are dispositional in nature (Badenoch, 2008; Konrath et al., 2011), which might make the counseling profession a strong fit for empathic individuals, empathy training in counseling programs can increase students’ levels of empathy (Ivey, 1971). However, the specific empathy-promoting components of empathy training are less understood (Teding van Berkhout & Malouff, 2016). Overall, empathy is an essential component of the counseling relationship, counselor competency, and the promotion of client outcomes (DePue & Lambie, 2014; Norcross, 2011). However, little is known about the training aspect of empathy and whether or not counselor training programs are effective in enhancing empathy or reducing sympathy among CITs. Thus, the following question guided this research investigation: Are CITs’ levels of empathy or sympathy different from their academic peers? Specifically, do CITs possess greater levels of empathy or sympathy than students from other academic majors?
Empathy in Counseling
Researchers have established continuous support for the importance of the therapeutic relationship in the facilitation of positive client outcomes (Lambert & Bergin, 1994; Norcross, 2011; Norcross & Lambert, 2011). In fact, the therapeutic relationship is predictive of positive client outcomes (Connors, Carroll, DiClemente, Longabaugh, & Donovan, 1997; Krupnick et al., 1996), accounting for about 30% of the variance (Lambert & Barley, 2001). That is, clients who perceive the counseling relationship to be meaningful will have more positive treatment outcomes (Bell, Hagedorn, & Robinson, 2016; Norcross & Lambert, 2011). One of the key factors in the establishment of a strong therapeutic relationship is a counselor’s ability to experience and communicate empathy. Researchers estimate that empathy alone may account for as much as 7–10% of overall treatment outcomes (Bohart, Elliott, Greenberg, & Watson, 2002; Sachse & Elliott, 2002), making it an important construct to foster in counselors.
Despite the importance of empathy in the counseling process, much of the literature on empathy training in counseling is outdated. Thus, little is known about the training aspect of empathy; that is, how is empathy taught to and learned by counselors? Nevertheless, early scholars (Barrett-Lennard, 1986; Ivey, 1971; Ivey, Normington, Miller, Morrill, & Haase, 1968; Truax & Carkhuff, 1967) posited that counselor empathy is a clinical skill that may be practiced and learned, and there is supporting evidence that empathy training may be efficacious.
In one seminal study, Truax and Lister (1971) conducted a 40-hour empathy training program with 12 counselor participants and identified statistically significant increases in participants’ levels of empathy. In their investigation, the researchers employed methods in which (a) the facilitator modeled empathy, warmth, and genuineness throughout the training program; (b) therapeutic groups were used to integrate empathy skills with personal values; and (c) researchers coded three of participants’ 4-minute counseling clips using scales of accurate empathy and non-possessive warmth (Truax & Carkhuff, 1967). Despite identifying statistically significant changes in participants’ scores of empathy, it is necessary to note that participants who initially demonstrated low levels of empathy remained lower than participants who initially scored high on the empathy measures. In a later study modeled after the Truax and Lister study, Silva (2001) utilized a combination of didactic, experiential, and practice components in her empathy training program, and found that counselor trainee participants (N = 45) improved their overall empathy scores on Truax’s Accurate Empathy Scale (Truax & Carkhuff, 1967). These findings contribute to the idea that empathy increases as a result of empathy training.
More recent researchers (Lam, Kolomitro, & Alamparambil, 2011; Ridley, Kelly, & Mollen, 2011) have identified the most common methods in empathy training programs as experiential training, didactic (lecture), skills training, and other mixed methods such as role play and reflection. In their meta-analysis, Teding van Berkhout and Malouff (2016) examined the effect of empathy training programs across various populations (e.g., university students, health professionals, patients, other adults, teens, and children) using the training methods identified above. The researchers investigated the effect of cognitive, affective, and behavioral empathy training and found a statistically significant medium effect size overall (g ranged from 0.51 to 0.73). The effect size was larger in health professionals and university students compared to other groups such as teenagers and adult community members. Though empathy increased as a result of empathy training studies, the specific mechanisms that facilitated positive outcomes remain largely unknown.
Although research indicates that empathy training can be effective, specific empathy-fostering skills are still not fully understood. Programmatically, empathy is taught to counselors within basic counseling skills (Bayne & Jangha, 2016), specifically because empathy is believed to lie in the accurate reflection of feeling and meaning (Truax & Carkhuff, 1967). But scholars argue that there is more to empathy than the verbal communication of understanding (Davis, 1980; Vossen et al., 2015). For example, in a more recent study, DePue and Lambie (2014) reported that counselor trainees’ scores on the Empathic Concern subscale of the Interpersonal Reactivity Index (IRI; Davis, 1980) increased as a result of engaging in counseling practicum experience under live supervision in a university-based clinical counseling and research center. In their study, the researchers did not actively engage in empathy training. Rather, they measured counseling students’ pre- and post-scores on an empathy measure as a result of students’ engagement in supervised counseling work to foster general counseling skills. Implications of these findings mirror those described by Teding van Berkhout and Malouff (2016), namely that it is difficult to identify specific empathy-promoting mechanisms. In other words, it appears that empathy training, when employed, produces successful outcomes in CITs. However, counseling students’ empathy also increases in the absence of specific empathy-promoting programs. This begs the question: Are counseling programs successfully training their counselors to be empathic, and is there a difference between CITs’ empathy or sympathy levels compared to students in other academic majors? Thus, the purpose of the present study was to (a) examine differences in empathy (i.e., affective empathy and cognitive empathy) and sympathy levels among emerging adult college students, and (b) determine whether CITs had different levels of empathy and sympathy when compared to their academic peers.
Methods
Participants
We identified master’s-level CITs as the population of interest in this investigation. We intended to compare CITs to other graduate and undergraduate college student populations. Thus, we utilized a convenience sample from a larger data set that included emerging adult college students between the ages of 18 and 29 who were enrolled in at least one undergraduate- or graduate-level course at nine colleges and universities throughout the United States. Participants were included regardless of demographic variables (e.g., gender, race, ethnicity).
Participants were recruited from three sources: online survey distribution (n = 448; 51.6%), face-to-face data collection (n = 361; 41.6%), and email solicitation (n = 34; 3.9%). In total, 10,157 potential participants had access to participate in the investigation by online survey distribution through the psychology department at a large Southeastern university; however, the automated system limited responses to 999 participants. We and our contacts (i.e., faculty at other institutions) distributed an additional 800 physical data collection packets to potential participants, and 105 additional potential participants were solicited by email. Overall, 1,713 data packets were completed, resulting in a sample of 1,598 participants after data cleaning. However, in order to conduct the analyses for this study, it was necessary to limit our sample to groups of approximately equal sizes (Hair, Black, Babin, & Anderson, 2010). Therefore, we were limited to the use of a subsample of 868 participants. Our sample appeared similar to other samples included in investigations exploring empathy with emerging adult college students (e.g., White, heterosexual, female; Konrath et al., 2011).
The participants included in this investigation were enrolled in one of six majors and programs of study, including Athletic Training/Health Sciences (n = 115; 13.2%); Biology/Biomedical Sciences/Preclinical Health Sciences (n = 167; 19.2%); Communication (n = 163; 18.8%); Counseling (n = 153; 17.6%); Nursing (n = 128; 14.7%); and Psychology (n = 142; 16.4%). It is necessary to note that students self-identified their major rather than selecting it from a preexisting prompt. Therefore, the researchers examined responses and categorized similar responses to one uniform title. For example, responses of psych were included with psychology. Further, in order to attain homogeneity among group sizes, we included multiple tracks within one program. For example, counseling included participants enrolled in either clinical mental health counseling (n = 115), marriage and family counseling (n = 24), or school counseling (n = 14) tracks. Table 1 presents additional demographic information (e.g., age, race, ethnicity, graduate-level status). It is necessary to note that, because of the constraints of the dataset, counseling students consisted of master’s-level graduate students, whereas all other groups consisted of undergraduate students.
Table 1
Participants’ Demographic Characteristics
| Characteristic |
|
n
|
Total %
|
|
| Age |
18–19 |
460
|
52.4
|
|
|
20–21 |
155
|
17.9
|
|
|
22–23 |
130
|
15.0
|
|
|
24–25 |
58
|
6.7
|
|
|
26–27 |
36
|
4.1
|
|
|
28–29 |
27
|
3.1
|
|
| Gender |
Female |
692
|
79.7
|
|
|
Male |
167
|
19.2
|
|
|
Other |
8
|
0.9
|
|
| Racial |
Caucasian |
624
|
71.9
|
|
| Background |
African American/African/Black |
101
|
11.6
|
|
|
Biracial/Multiracial |
65
|
7.5
|
|
|
Asian/Asian American |
40
|
4.6
|
|
|
Native American |
3
|
0.3
|
|
|
Other |
25
|
2.9
|
|
| Ethnicity |
Hispanic |
172
|
19.8
|
|
|
Non-Hispanic |
689
|
79.4
|
|
| Academic |
Undergraduate |
709
|
81.7
|
|
| Enrollment |
Graduate |
152
|
17.5
|
|
|
Other |
5
|
0.6
|
|
| Academic Major |
Athletic Training/Health Sciences |
115
|
13.2
|
|
|
Biology/Biomedical Sciences/Preclinical Health Sciences |
167
|
19.2
|
|
|
Counseling |
153
|
17.6
|
|
|
Communication |
163
|
18.8
|
|
|
Nursing |
128
|
14.7
|
|
|
Psychology |
142
|
16.4
|
|
Note. N
= 868.
Procedure
The data utilized in this study were collected as part of a larger study that was approved by the authors’ institutional review board (IRB) as well as additional university IRBs where data was collected, as requested. We followed the Tailored Design Method (Dillman, Smyth, & Christian, 2009), a series of recommendations for conducting survey research to increase participant motivation and decrease attrition, throughout the data collection process for both web-based survey and face-to-face administration. Participants received informed consent, assuring potential participants that their responses would be confidential and their anonymity would be protected. We also made the survey convenient and accessible to potential participants by making it available either in person or online, and by avoiding the use of technical language (Dillman et al., 2009).
We received approval from the authors of the Adolescent Measure of Empathy and Sympathy (AMES; Vossen et al., 2015; personal communication with H. G. M. Vossen, July 10, 2015) to use the instrument and converted the data collection packet (e.g., demographic questionnaire, AMES) into Qualtrics (2013) for survey distribution. We solicited feedback from 10 colleagues regarding the legibility and parsimony of the physical data collection packets and the accuracy of the survey links. We implemented all recommendations and changes (e.g., clarifying directions on the demographic questionnaire) prior to data collection.
All completed data collection packets were assigned a unique ID, and we entered the data into the IBM SPSS software package for Windows, Version 22. No identifying information was collected (e.g., participants’ names). Having collected data both in person and online via web-based survey, we applied rigorous data collection procedures to increase response rates, reduce attrition, and to mitigate the potential influence of external confounding factors that might contribute to measurement error.
Data Instrumentation
Demographics profile. We included a general demographic questionnaire to facilitate a comprehensive understanding of the participants in our study. We included items related to various demographic variables (e.g., age, race, ethnicity). Regarding participants’ identified academic program, participants were prompted to respond to an open-ended question asking “What is your major area of study?”
AMES. Multiple assessments exist to measure empathy (e.g., the IRI, Davis, 1980, 1983; The Basic Empathy Scale [BES], Jolliffe & Farrington, 2006), but each is limited by several shortcomings (Carré, Stefaniak, D’Ambrosio, Bensalah, & Besche-Richard, 2013). First, many scales measure empathy as a single construct without distinguishing cognitive empathy from affective empathy (Vossen et al., 2015). Moreover, the wording used in most scales is ambiguous, such as items from other assessments that use words like “swept up” or “touched by” (Vossen et al., 2015), and few scales differentiate empathy from sympathy. Therefore, Vossen and colleagues designed the AMES as an empathy assessment that addresses problems related to ambiguous wording and differentiates empathy from sympathy.
The AMES is a 12-item empathy assessment with three factors: (a) Cognitive Empathy, (b) Affective Empathy, and (c) Sympathy. Each factor consists of four items rated on a 5-point Likert scale with ratings of 1 (never), 2 (almost never), 3 (sometimes), 4 (often), and 5 (always). Higher AMES scores indicate greater levels of cognitive empathy (e.g., “I can tell when someone acts happy, when they actually are not”), affective empathy (e.g., “When my friend is sad, I become sad too”), and sympathy (e.g., “I feel concerned for other people who are sick”). The AMES was developed in two studies with Dutch adolescents (Vossen et al., 2015). The researchers identified a 3-factor model with acceptable to good internal consistency per factor: (a) Cognitive Empathy (α = 0.86), (b) Affective Empathy (α = 0.75), and (c) Sympathy (α = 0.76). Further, Vossen et al. (2015) established evidence of strong test-retest reliability, construct validity, and discriminant validity when using the AMES to measure scores of empathy and sympathy with their samples. Despite being normed with samples of Dutch adolescents, Vossen and colleagues suggested the AMES might be an effective measure of empathy and sympathy with alternate samples as well.
Bloom and Lambie (in press) examined the factor structure and internal consistency of the AMES with a sample of emerging adult college students in the United States (N = 1,598) and identified a 3-factor model fitted to nine items that demonstrated strong psychometric properties and accounted for over 60% of the variance explained (Hair et al., 2010). The modified 3-factor model included the same three factors as the original AMES. Therefore, we followed Bloom and Lambie’s modifications for our use of the instrument.
Data Screening
Before running the main analysis on the variables of interest, we assessed the data for meeting the assumptions necessary to conduct a one-way between-subjects MANOVA. First, we conducted a series of tests to evaluate the presence of patterns in missing data and determined that data were missing completely at random (MCAR) and ignorable (e.g., < 5%; Kline, 2011). Because of the robust size of these data (e.g., > 20 observations per cell) and the minimal amount of missing data, we determined listwise deletion to be best practice to conduct a MANOVA and to maintain fidelity to the data (Hair et al., 2010; Osborne, 2013).
Next, we utilized histograms, Q-Q plots, and boxplots to assess for normality and identified non-normal data patterns. However, MANOVA is considered “robust” to violations of normality with a sample size of at least 20 in each cell (Tabachnick & Fidell, 2013). Thus, with our smallest cell size possessing a sample size of 115, we considered our data robust to this violation. Following this, we assumed our data violated the assumption for multivariate normality. However, Hair et al. (2010) stated “violations of this assumption have little impact with larger sample sizes” (p. 366) and cautioned that our data might have problems achieving a non-significant score for Box’s M Test. Indeed, our data violated the assumption of homogeneity of variance-covariance matrices (p < .01). However, this was not a concern with these data because “a violation of this assumption has minimal impact if the groups are of approximately equal size (i.e., largest group size ÷ smallest group size < 1.5)” (Hair et al., 2010, p. 365).
It is necessary to note that MANOVA is sensitive to outlier values. To mitigate against the negative effects of extreme scores, we removed values (n = 3) with standardized z-scores greater than +4 or less than -4 (Hair et al., 2010). This resulted in a final sample size of 868 participants.
We also utilized scatterplots to detect the patterns of non-linear relationships between the dependent variables and failed to identify evidence of non-linearity. Therefore, we proceeded with the assumption that our data shared linear relationships. We also evaluated the data for multicollinearity. Participants’ scores of Affective Empathy shared statistically significant and appropriate relationships with their scores of Cognitive Empathy (r = .24) and Sympathy (r = .43). Similarly, participants’ scores of Cognitive Empathy were appropriately related to their scores of Sympathy (r = .36; p < .01). Overall, we determined these data to be appropriate to conduct a MANOVA. Table 2 presents participants’ scores by academic discipline.
Table 2
AMES Scores by Academic Major
|
Scale
|
Mean (M)
|
SD
|
Range
|
| Athletic Training |
|
|
|
|
Affective Empathy
|
3.20
|
0.80
|
4.00 |
|
Cognitive Empathy
|
3.80
|
0.62
|
3.33 |
|
Sympathy
|
4.34
|
0.55
|
2.67 |
| Biomedical Sciences |
|
|
|
|
Affective Empathy
|
3.12
|
0.76
|
4.00 |
|
Cognitive Empathy
|
3.66
|
0.59
|
3.00 |
|
Sympathy
|
4.30
|
0.61
|
2.00 |
| Communication |
|
|
|
|
Affective Empathy
|
3.18
|
0.87
|
4.00 |
|
Cognitive Empathy
|
3.80
|
0.62
|
2.67 |
|
Sympathy
|
4.27
|
0.69
|
3.00 |
| Counseling |
|
|
|
|
Affective Empathy
|
3.32
|
0.60
|
3.33 |
|
Cognitive Empathy
|
3.83
|
0.48
|
4.00 |
|
Sympathy
|
4.32
|
0.54
|
2.00 |
| Nursing |
|
|
|
|
Affective Empathy
|
3.37
|
0.71
|
3.67 |
|
Cognitive Empathy
|
3.80
|
0.59
|
2.67 |
|
Sympathy
|
4.46
|
0.49
|
2.00 |
| Psychology |
|
|
|
|
Affective Empathy
|
3.28
|
0.78
|
4.00 |
|
Cognitive Empathy
|
3.86
|
0.59
|
2.67 |
|
Sympathy
|
4.35
|
0.65
|
2.67 |
Note. N
= 868.
Results
Participants’ scores on the AMES were used to measure participants’ levels of empathy and sympathy. Descriptive statistics were used to compare empathy and sympathy levels between counseling students and emerging college students from other disciplines. CITs recorded the second highest levels of affective empathy (M = 3.32, SD = .60) and cognitive empathy (M = 3.83, SD = 0.48), and the fourth highest levels of sympathy (M = 4.32, SD = 0.54) when compared to students from other disciplines. Nursing students demonstrated the highest levels of affective empathy (M = 3.37, SD = .71) and sympathy (M = 4.46, SD = .49), and psychology students recorded the highest levels of cognitive empathy (M = 3.86, SD = 0.59) when compared to students from other disciplines. The internal consistency values for each empathy and sympathy subscale on the AMES were as follows: Cognitive Empathy (α = 0.86), Affective Empathy (α = 0.75), and Sympathy (α = 0.76).
We performed a MANOVA to examine differences in empathy and sympathy in emerging adult college students by academic major, including counseling. Three dependent variables were included: affective empathy, cognitive empathy, and sympathy. The predictor for the MANOVA was the 6-level categorical “academic major” variable. The criterion variables for the MANOVA were the levels of affective empathy (M = 3.24, SD = .76), cognitive empathy (M = 3.80, SD = .58), and sympathy
(M = 4.34, SD = .60), respectively. The multivariate effect of major was statistically non-significant:
p = .062, Wilks’s lambda = .972, F (15, 2374.483) = 1.615, η2 = .009. Furthermore, the univariate F scores for affective empathy (p = .139), cognitive empathy (p = .074), and sympathy (p = .113) were statistically non-significant. That is, there was no difference in levels of affective empathy, cognitive empathy, or sympathy based on academic major, including counseling. Thus, these data indicated that CITs were no more empathic or sympathetic than students in other majors, as measured by the AMES.
We also examined these data for differences in affective empathy, cognitive empathy, and sympathy based on data collection method and educational level. However, we failed to identify a statistically significant difference between groups in empathy or sympathy based on data collection method
(e.g., online survey distribution, face-to-face data collection, email solicitation) or by educational level (e.g., master’s level or undergraduate status). Thus, these data indicate that data collection methods and participants’ educational level did not influence our results.
Discussion
The purpose of the present study was to (a) examine differences in empathy (i.e., affective empathy and cognitive empathy) and sympathy levels among emerging adult college students, and (b) determine whether CITs demonstrate different levels of empathy and sympathy when compared to their academic peers. We hypothesized that CITs would record greater levels of empathy and lower levels of sympathy when compared to their non-counseling peers, because of either their clinical training from their counselor education program or the possibility that the counseling profession might attract individuals with strong levels of dispositional empathy. Participants’ scores on the AMES were used to measure participants’ levels of empathy and sympathy. We conducted a MANOVA to determine if participants’ levels of empathy and sympathy differed when grouped by academic majors. CITs did not exhibit statistically significant differences in levels of empathy or sympathy when compared to students from other academic programs. In fact, CITs recorded levels of empathy that appeared comparable to students from other academic disciplines. This finding is consistent with literature indicating that even if empathy training is effective, counselor education programs might not be emphasizing empathy development in CITs or employing empathy training sufficiently. We also failed to identify statistically significant differences in participants’ AMES scores when grouping data by collection method or participants’ educational level. Thus, we believe our results were not influenced by our data collection method or by participants’ educational level.
Implications for Counselor Educators
The results from this investigation indicated that there was not a statistically significant difference in participants’ levels of cognitive or affective empathy or sympathy regardless of academic program, suggesting that CITs do not possess more or less empathy or sympathy than their academic peers. This was true for students in all majors under investigation (i.e., athletic training/health sciences, biology/biomedical sciences/preclinical health sciences, communication, counseling, nursing, and psychology), regardless of age and whether or not they belonged to professions considered helping professions (i.e., counseling, nursing, psychology). Although students in helping professions tended to have higher scores on the AMES than their peers, these differences were not statistically significant.
One might hypothesize that students in helping professions (especially in professions in which individuals have direct contact with clients or patients, such as counseling) would have significantly higher levels of empathy. However, counseling programs may not attract individuals who possess greater levels of trait empathy, or training programs might not be as effective in training their students as previously thought. Although microskills are taught in counselor preparation programs (e.g., reflection of content, reflection of feeling), microskill training might not overlap with material that is taught as part of an empathy training or enhance such training. Thus, microskill training might not be any more impactful for CITs’ development of empathy and sympathy than material included in training programs of other academic disciplines (e.g., athletic training, nursing).
Another potential reason for the lack of recorded differences between CITs and their non-counseling peers could be that counseling students are inherently anxious, skill-focused, self-focused, or have limited self-other awareness (Stoltenberg, 1981; Stoltenberg & McNeill, 2010). We wonder if CITs might not be focused on utilizing relationship-building approaches as much as they are on doing work that promotes introspection and reflection. Another inquiry for consideration is whether CITs potentially possess a greater understanding of empathy as a construct that inadvertently leads CITs to rate themselves lower in empathy than their non-counseling peers. Further, it is possible that CITs potentially minimize their own levels of empathy in an effort to demonstrate modesty, a phenomenon related to altruism and understood as the modesty bias (McGuire, 2003). Future research would be helpful to better understand various mitigating factors. Nevertheless, we suggest that counseling programs might be able to do more to foster empathy-facilitating experiences in counselors by being more proactive and effective in promoting empathy development in CITs. Through a review of the literature, we found support that empathy training is possible, and we wonder if there is a missed opportunity to effectively train counselors if counselor education programs do not intentionally facilitate empathy development in their CITs.
Counselor training programs are not charged to develop empathy in CITs; however, given the importance of empathy in the formation and maintenance of a therapeutic relationship, we propose that counseling training programs consider ways in which empathy is or is not being developed in their specific program. As such, we urge counselor educators to consider strategies to emphasize empathy development in their CITs. For example, reviewing developmental aspects of empathy in children, adolescents, and adults might fit well in a human development course, and the subject can be used to facilitate a conversation with CITs regarding their experiences of empathy development.
Similarly, because empathy consists of cognitive and affective components, CITs might benefit from work that assists them in gaining insight into areas of strengths and limitations in regard to both cognitive and affective aspects of empathy. Students who appear stronger in one area of empathy might benefit from practicing skills related to the other aspect of empathy. For example, if a student has a strong awareness of a client’s experience (i.e., cognitive empathy) but appears to have limitations in their felt sense of a client’s experience (i.e., affective empathy), a counselor educator might utilize live supervision opportunities to assist the student in recognizing present emotions or sensations in their body when working with the client or in a role play. Alternatively, to assist a student with developing a greater intellectual understanding of their client’s experience, a counselor educator might employ interpersonal process recall when reviewing their clinical work to help the student identify what their client might be experiencing as a result of their lived experience. To echo recommendations made by Bayne and Jangha (2016), we encourage counselor educators to move away from an exclusive focus on microskills for teaching empathy and to provide opportunities to teach CITs how to foster a connecting experience through creative means (e.g., improvisational skills).
Furthermore, the results from this study indicated that CITs possess higher levels of sympathy than of both cognitive and affective components of empathy. We recommend that counselor educators facilitate CITs’ understanding of the differences between empathy and sympathy and bring awareness to their use of sympathetic responses rather than empathic responses. It is our hope that CITs will possess a strong enough understanding between empathy and sympathy to be able to choose to use either response as it fits within a counseling context (Clark, 2010). We also encourage counselor educators to consider recommendations made by Bloom and Lambie (in press) to employ the AMES with CITs. The AMES could be a valuable and accessible tool to assist counselor educators in evaluating CITs’ levels of empathy and sympathy in regard to course assignments, in response to clinical situations, or as a wholesale measure of empathy development. As Bloom and Lambie encouraged, clinical training programs might benefit from using the AMES as a tool to programmatically measure CITs’ levels of empathy throughout their experience in their training program (i.e., transition points) as a way to collect programmatic data.
Limitations
Although this study produced important findings, some limitations exist. It is noted that the majority of participants from this study attended universities located within the Southeastern United States. As a result, the sample might not be representative of students nationwide. Similarly, demographic characteristics of the present study including the race, age, and gender composition of the sample limit the generalizability of the findings.
This study also is limited in that the instrument used to assess empathy and sympathy was a self-report measure. Although self-report measures have been shown to be reliable and are widely used within research, these measures might result in the under- or over-reporting of the variables of interest (Gall, Gall, & Borg, 2007). It is necessary to note that we employed the AMES, which was normed with adolescents and not undergraduate or graduate students. Although we recognize that inherent differences exist between adolescent and emerging adult populations, we believed the AMES was an effective choice to measure empathy because of Vossen and colleagues’ (2015) intentional development of the instrument to address existing weaknesses in other empathy assessment instruments. Nonetheless, it is necessary to interpret our results with caution.
Recommendations for Future Research
We recommend future researchers address some of the limitations of this study. Specifically, we recommend continuing to compare CITs’ levels of empathy with students from other academic disciplines, but to include a more diverse array of academic backgrounds. Similarly, we suggest future researchers not limit themselves to an emerging adult population, as both undergraduate and graduate populations include individuals over the age of 29. Further, researchers should aim to collect data from students across the country and to include a more demographically diverse sample in their research designs.
Additionally, it is necessary to note that limitations exist to using self-report measures (Gall et al., 2007), and measures of empathy are vulnerable to a myriad of complications (Bloom & Lambie, in press; Vossen et al., 2015). Thus, we encourage future researchers to consider using different measures of empathy that move away from a self-report format (e.g., clients’ perceptions of cognitive and affective empathy within a therapeutic relationship; Flasch et al., in press). Another area for future research is to track counseling students’ levels of empathy as they enter the counseling profession after graduation. It is possible that as they become more comfortable and competent as counselors, and as anxiety and self-focus decrease, their ability to empathize increases.
There is agreement in the counseling profession that empathy is an important characteristic for counselors to embody in order to facilitate positive client outcomes and to meet counselor competency standards (DePue & Lambie, 2014). Yet scholars have grappled with how to identify the necessary skills to foster empathy in counselor trainees and remain torn on which approaches to use. Although empathy training programs seem effective, little is known about which aspects of such programs are the effective ingredients that promote empathy-building, and we lack understanding about whether such programs are more effective than simply engaging in clinical work or having life experiences. Thus, we encourage researchers to explore if counseling programs are effective at teaching empathy to CITs and to further explore mechanisms that may or may not be valuable in empathy development.
Conflict of Interest and Funding Disclosure
The authors reported no conflict of interest
or funding contributions for the development
of this manuscript.
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Zachary D. Bloom is an assistant professor at Northeastern Illinois University. Victoria A. McNeil is a doctoral candidate at the University of Florida. Paulina Flasch is an assistant professor at Texas State University. Faith Sanders is a mental health counselor at Neuropeace Wellness Counseling in Orlando, Florida. Correspondence can be addressed to Zachary Bloom, 5500 North St. Louis Avenue, Chicago, IL 60625, z-bloom@neiu.edu.
Nov 9, 2018 | Volume 8 - Issue 4
Jennifer Barrow, Stanley B. Baker, Lance D. Fusarelli
The purpose of this grounded theory study was to understand and explain how training and work setting experiences influence readiness of professional school counselors for serving gang members in schools. A purposeful sample consisted of secondary school counselors (n = 5) and school leaders (n = 7) in a southeastern metropolitan school district. Blended themes from the counselors and leaders were: (a) professional development attitudes, (b) actual and potential roles when working with students in gangs, and (c) counselors’ collaborative role in discipline process. The Collaborative C.A.R.E. theory that emerged from the thematic analysis highlighted the absence of collaboration between school counselors and leaders. Specific findings identified reasons for the lack of collaboration and led to recommendations for practice and further research.
Keywords: gang members, school counselors, grounded theory, Collaborative C.A.R.E, discipline
On a daily basis, professional school counselors (PSCs) are expected to engage in a variety of functions in order to enhance the academic, career, personal, and social development of all students (American School Counselor Association [ASCA], 2012b, 2014). Serving all students can be very challenging given the disproportionate number of PSCs to students in the United States and the number of non-counseling functions often imposed on PSCs (Lambie & Williamson, 2004). ASCA (2012a) recommends a counselor-to-student ratio of 1:250. Despite this recommendation, findings have indicated that the accurate ratio is closer to 1:491 (ASCA, n.d.). Responding to the “serve all students” expectation can be even more challenging when attempting to serve gang members, who are considered members of marginalized populations that are excluded from the social, economic, cultural, and political mainstream (McCluskey, Baker, & McCluskey, 2005).
Research on the PSC’s role was conducted in the late 1990s and early 2000s, and much of the research is generalized to include the role of the PSC (both perceived and actual) with little consideration for the contextual differences in jobs (e.g., elementary, middle, high school; Brott & Myers, 1999; Lambie & Williamson, 2004). A paucity of data exists in recent research examining the role of PSCs with specific groups of students based on cultural and environmental contexts, and their role since the introduction of the ASCA National Model. Gang members are students with norms related to language, rituals, and membership (Gibbs, 2000). The presence of gangs in schools reflects a need to examine the role of the PSC in serving this culturally marginalized population.
Gang members are often viewed as outsiders associated with “outlaw organizations” engaged in deviant behaviors (Gibbs, 2000, p. 73). On the other hand, from the inside, members find structure, ritual, and norms specific to their gang structure. This study was designed to attempt to fill these gaps by examining the role of the PSC with a contemporary, marginalized population.
According to the National Gang Intelligence Center (2011), there are approximately 1.4 million active gang members representing more than 33,000 gangs in the United States. This represents a 40% increase compared to data collected in 2009. The data support an assumption that there is an increasing presence of gangs in both rural and urban communities (Brinson, Kottler, & Fisher, 2004). Unfortunately, there are several negative outcomes associated with the presence of gang members in the schools, including harassment, vandalism, aggressive recruitment of new members, irregular attendance, decreased motivation to succeed in school, and criminal activities. Consequently, gang presence can adversely affect the school environment, lower levels of academic achievement, and negatively influence perceptions of safety (Brinson et al., 2004). In and of itself, gang membership is not a crime, and gang members who are enrolled in public schools are eligible for all of the services that other students are receiving, including those offered by PSCs (Kizer, 2012).
As gang membership increases nationally, the presence of gang members will continue to expand in the schools and surrounding communities (Coggeshall & Kingery, 2001; Kingery, Coggeshall, & Alford, 1998). A recent survey of 12- to 18-year-old students indicated that 18% stated there were gangs in their schools (Robers, Kemp, Truman, & Snyder, 2013). This phenomenon will increase the exposure of PSCs to gang activity (Gündüz, 2012; Skovholt & McCarthy, 1988). Because of their training, PSCs appear to be in a unique position conceptually to offer services to gang members and to the schools where gang members are present. Potential resources include individual and group counseling competencies; core curriculum programming knowledge and skills; availability for providing helpful consultations; and the overlying quest to enhance the academic, career, personal, and social development of all students (ASCA, 2012b, 2014).
The first author’s exposure to gangs increased in her role as a PSC. Perceived lack of training and preparation to work with gang members and an absence of professional literature on the role of PSCs with gangs motivated the first author to conduct a preliminary investigation. Participants in the pilot study were PSCs in a southeastern urban public school setting. The pilot study consisted of two phases of inquiry consistent with the grounded theory methodology. Grounded theory generates data based on “participant experiences” (Hays & Singh, 2012, p. 288).
The first phase of the pilot study was a focus group of PSC participants with data being transcribed by the researcher, hand-coded, and analyzed. The second phase consisted of individual interviews completed at the respective job sites of three practicing PSCs. The interviews and observations from the second phase provided further evidence, more variation, and a greater understanding of the role of the PSC working with students in gangs across elementary, middle, and high school settings.
The preliminary investigation suggested further research in the school counseling domain. The participating PSCs appeared to experience ambiguity and lack of decision-making authority related to working with students who are gang members. Decisions on professional development opportunities and the PSC’s role were influenced by school-based leaders, such as principals, whose views tended to focus on disciplinary issues rather than academic, career, personal, and social development with regard to gang members. Consequently, the pilot study revealed a need to further explore the PSC’s role in working with gang members based on perceived and ideal roles, their professional development needs, and the influence of their educational administrators and supervisors.
Although uniquely positioned to offer something of value, there are impediments to fulfilling that role. Developing and defining the role for PSCs continues to be a challenge for PSCs, their school leaders (SLs), and national professional organizations that offer recommended roles for PSCs (Foxx, Baker, & Gerler, 2017; Griffin & Farris, 2010; Shoffner & Williamson, 2000). Some SLs determine the tasks that define the role of their PSCs with little to no input from counselors (Zalaquett & Chatters, 2012). These decisions are not aligned with ASCA’s PSC role recommendations and indicate misunderstandings about how their counselors were trained and failure to collaborate on PSC role definitions (Kirchner & Setchfield, 2005). Collaboration between PSCs and SLs is essential in the development of comprehensive counseling programs designed to support the academic goals of the school (Armstrong, MacDonald, & Stillo, 2010; Foxx et al., 2017; Zalaquett & Chatters, 2012).
An additional challenge is a lack of professional development related to working with gang members after one’s graduate training program. Caldarella, Sharpnack, Loosli, and Merrell (1996) found that many PSCs do not feel adequately trained or equipped to deal with gang activity and gang members in their schools, and almost half of the sample had no training related to gangs. Relatedly, our preliminary investigation found PSCs were trained to recognize the presence of gangs yet knew very little about how to engage with gang members and offer their services. Believing that one is unprepared and not competent to deliver counseling services to gang members may cause feelings of helplessness, apathy, and little or no desire to serve them (Ibrahim, Helms, & Thompson, 1983). As a marginalized population, students in gangs compound the unique challenges PSCs face, including role ambiguity (Burnham & Jackson, 2000), constant changes in student and school characteristics and needs (Reising & Daniels, 1983), and disconnects between training and practice (Brott & Myers, 1999; Lambie & Williamson, 2004).
The purpose of the present grounded theory study was to further understand and explain how training, perceived roles, and work setting experiences (e.g., professional development, working with students in gangs) influenced the readiness of PSCs in a large urban school district to serve gang members. Given the challenges PSCs experience related to serving gang members, the following research questions were derived in order to attempt to explain a conceptual linkage via a grounded theory based on understanding perspectives of a sample of PSCs and SLs via the interplay of context, conditions, and the PSC’s role (Hays & Singh, 2012): How do PSCs and SLs describe perceived and actual roles of PSCs regarding services to gang members? How do PSCs and SLs describe previous training related to working with gang members? and How do PSCs and SLs describe circumstances that influence opportunities PSCs have for serving gang members?
Method
Participants
A total of 12 participants were included in this study. Five participants were PSCs and seven were SLs. Of the PSCs, four were female and one was male; four were White and one was African American. All of the PSCs had master’s degrees and school counseling licenses. The mean age of the PSCs was 52 (SD = 8.57), and the mean years of counseling experience was 14.8 (SD = 7.69). All of the seven SLs were male. Six were White and one was African American. Four had master’s degrees in educational leadership, one had a bachelor’s degree in science, and two had doctoral degrees in education. Two of the seven SLs were based in the school district’s central office. The mean age of the SLs was 42 (SD = 7.23), and the average years of experience was 10.4 (SD = 3.26). Each participant is represented by a pseudonym in the findings.
Consistent with grounded theory, stratified purposeful sampling was used to identify PSCs and SLs serving at the same school to voluntarily participate (Corbin & Strauss, 2008; Hays & Singh, 2012). PSCs possessed state professional licenses in their fields and were employed in secondary school settings. Specific criteria for the SLs were that they be assistant principals, principals, or central office staff members. SLs possessed state professional licenses in their fields. An additional advantage of this approach was being able to triangulate data sources by acquiring data from different perspectives, including central school office members.
Instrumentation
Demographic questionnaire. Information related to age, ethnicity, education, and experience was collected from PSC and SL participants via a brief demographic questionnaire that asked identical questions.
Interview questions for participants. Two sets of open-ended questions were developed for semi-structured individual interviews. Topical areas addressed in the current study included role perception, professional development, and barriers to serving students in gangs. The following questions were presented to the PSC participants: (a) What factors determine the role you play in your school? (b) Who is involved in determining your professional role? (c) In your opinion, what role do professional school counselors currently play in identifying gang presence and providing intervention in your school? (d) Tell me what role you think counselors may play in identifying and providing interventions for students currently involved in a gang or considering gang membership. (e) What role has the school or school district played in providing professional school counselors with training specific to gang activity in the schools? (f) During your graduate school training, were you provided any opportunities to learn about gangs in schools? (g) Since graduate school, have you been provided or sought out opportunities to learn about gangs in schools? (h) In your own words, describe your work with students in gangs. (i) What barriers exist impacting your effectiveness in working with students in gangs? (j) In what ways do you seek out information to inform your work as a professional school counselor? (k) How might the ASCA National Model support your efforts to prevent or intervene with students in gangs? and (i) Is there anything you care to add?
The following questions were presented to the SL participants: (a) What factors determine the role school counselors play in your school? (b) Who is involved in determining their professional role? (c) In your opinion, what role do professional school counselors currently play in identifying gang presence and providing intervention in your school? (d) Tell me what role you think counselors may play in identifying and providing interventions for students currently involved in a gang or considering gang membership. (e) What role has the school or school district played in providing professional school counselors and school faculty with training specific to gang activity in the schools? (f) During your graduate school training, were you provided any opportunities to learn about the role of the school counselor? (g) Since graduate school, has your perception of the role of the school counselor changed? How so? (h) In your own words, describe your work with students in gangs. (i) How might the ASCA National Model support your school’s efforts to prevent or intervene with students in gangs? and (j) Is there anything you care to add?
Interviewer/Investigator. The first author was an insider who worked for the school district as a PSC. At the time of the study, she was working full-time and was a doctoral student in a counselor education program accredited by the Council for Accreditation of Counseling and Related Educational Programs. She was a 37-year-old White female with nine years of school counseling experience. She is a licensed school counselor, licensed professional counselor, and a National Certified Counselor (NCC). She had access to data that would not be available to an outsider. An advantage was her familiarity with the participants.
Subjectivity statement. On the one hand, the first author lacked personal gang awareness and was sensitive to the participants’ lack of knowledge (Corbin & Strauss, 2008). On the other hand, she had observed disruptive incidents created by gang members in her schools and was conflicted about how to deal with gang members as a professional. This led to a preliminary literature review that suggested ideas about how PSCs may serve gang members in their schools via both responsive services and core curriculum responses. The potential biases were role ambiguity and professional development. These biases were addressed during the data collection and analysis through the use of a journal to record immediate reactions to completed interviews.
Reflectivity during data collection is a valuable tool and is “considered essential to the research process” (Corbin & Strauss, 2008, p. 31). A journal housed field notes after each interview regarding participants’ body language, physical environment, and interviewer’s immediate thoughts and impressions. Journaling allowed for the constant comparison of data, looking for more data, and initial coding of collected data (Corbin & Strauss, 2008).
Procedure
Data collection. Established university research policies for the protection of human subjects and the research policies of the school district were followed in order to gain access to schools and participants. After receiving institutional review board approval from the first author’s affiliated university and the school district’s research department, data collection was completed via interviewing participants, journaling, and reviewing documents. The primary source of data was individual semi-structured interviews using an open-ended questions approach and an interview guide (Patton, 2002). Observations of the school setting, participants, and reflections of each interview were noted by the first author/researcher in her journal (Corbin & Strauss, 2008). In addition to journaling, policy manuals and public relations documents were accessed from the school district’s website for the triangulation process (Patton, 2002). The school district’s documents informed the researcher of existing procedures and policies and potential access to related training opportunities.
Participants were provided the interview questions in the moments immediately preceding the beginning of the interviews, giving them the opportunity to view questions and consider answers or emerging thoughts as needed. They were offered an opportunity to answer all questions. In order to enhance the analysis of the role of the PSC, interviews were conducted with SLs and PSCs working at the same schools. The interviews were conducted at the jobsites of the PSCs and SLs or at mutually agreeable locations. A digital voice recorder was used to record all interviews.
Data analysis. The recorded interviews were played and reviewed immediately after face-to-face interviews, allowing for constant comparisons (Schwandt, 2001). Each individual audio-recorded interview was transcribed by a professional transcriptionist. Following transcription, the interviews were read twice by the first author before themes were highlighted and noted in the margins. Interview data were individually read for all PSCs with themes noted in the margins. Then, interview data were individually read for all SLs with themes noted in the journal. Finally, interview data were reviewed for each PSC and their corresponding SL with themes of each pairing noted by the researcher. Hand-coding was used to analyze data gathered from transcribed interviews with a focus on capturing essential concepts (Bogdan & Biklen, 2007). The process of hand-coding involved deriving codes and the emerging themes to be organized into discrete categories leading to theory development (Corbin & Strauss, 2008). In the first or open coding stage, large general conceptual domains were identified in the reflective journal. Then, the researcher searched for relationships among the domains during the axial coding stage. Finally, the selective coding stage involved: (a) explaining story lines, (b) relating subsidiary categories around the core categories by means of paradigms, (c) relating categories at the dimensional levels, (d) validating the relationships against the raw data, and (e) filling in the categories that may need further development (Corbin & Strauss, 2008).
Triangulation was used as a means to increase the trustworthiness in the present study (Creswell & Miller, 2000; Patton, 2002). Four data sources were used to inform theory development: interviews with PSCs, interviews with SLs, a reflective journal, and related school district documents (e.g., discipline policies, in-service training programs). Grounded theory is built upon the cyclical and constant analysis of data (Hays & Singh, 2012). The use of multiple data sources in this study enhanced the development of codes, categories, and theory, and strengthened the trustworthiness of the study’s findings (Merriam, 2002). The transcribed interviews were reviewed by the researcher to ensure that professional jargon was accurate. A reflective research journal was kept throughout the entire study. Each participant was offered an opportunity to member check the transcribed data (Creswell & Miller, 2000). In addition, an audit was conducted to attempt to reduce the potential for personal biases influencing the data analysis. The auditor was a White female with a doctorate in educational leadership and previous work experience as a PSC. The auditing process consisted of quality control: (a) assuring ethical concerns were addressed, including the use of pseudonyms to protect participants; (b) reviewing the data to insure the study proposed and conducted matched data reported; and (c) proofreading, including clarifying professional jargon. Data saturation was achieved after the eighth interview; however, to affirm category development, complete interview pairings, and ensure triangulation of data sources, the interviews continued through 12 participants. As stated in the introduction, the purpose of the present study was to construct a grounded theory based on the data.
Findings
Grounded theory study data analyses provide central categories that bring all of the codes together (Corbin & Strauss, 2008). The central thematic categories in the present study were: (a) professional development attitudes, (b) actual and potential roles when working with students in gangs, and (c) PSCs’ collaborative role in the discipline process. An integration of the three central categories caused a Collaborative C.A.R.E. theory to emerge. Collaboration was the category both present and notably absent in the stories of the PSCs and the SLs. The C.A.R.E. acronym emerged out of the categories that developed during the axial coding process. The categories revealed a lack, or the presence, of communication with community stakeholders. The data suggested a need for PSCs working in secondary school settings to advocate for policies, procedures, programming, and educational opportunities to clarify their role in providing responsive services for students in gangs. What follows are excerpts of the data in the voices of the participants presented via the three central themes.
Professional Development Attitudes
PSCs are increasingly overwhelmed by their day-to-day responsibilities, leading them often to not engage in professional development that may take them away from campus. In addition, the interview data revealed that PSCs were not engaging in professional development related to working with gang members because of a lack of interest in working with this population, a concern for personal safety, unclear counseling roles, and the cost of professional development.
Beth (PSC) noted in her time as a PSC that different initiatives drive the training offered in the local district. She recalled a “push” four or five years previously to identify the presence of gangs at her school, but since that training she noted, “It’s not an interest of mine” and she will look to other staff members to “handle that stuff.” Beth’s response demonstrated a lack of engagement as a result of a lack of interest.
As noted, Beth expected other staff members, primarily SLs, to address the needs of students in gangs. In contrast, Sasha’s (PSC) gang awareness training at the school level had occurred in other counties. She noted that the school district in the present study “maybe has had something,” but “I don’t think the school has provided anything.” She went on to say, “I don’t think I’ve done anything in this district.” Sasha added that possessing knowledge of gangs in schools is “just not the highest on the list of priorities.”
Sasha’s supervising SL, Joe, noted the training from the district is “probably limited, to be honest.” Joe stated as an SL: “I don’t receive training for gangs or gang-related activity. Most of what I know is either self-taught or stuff that we pick up along the way because we’re placed into that position as administrators.” Joe elaborated that much of what he had picked up was reactive: “Unfortunately it’s reactive, but that’s also predicated upon the levels that we deal with here, which is not very much . . . so some of that [training] is from our SRO [school resource officer].”
Beyond having experienced awareness training, the PSCs expressed repeated concerns about their lack of intervention tools. Sasha said she was in need of “strategies” to work with gangs. She asked, “Are you working on trying to get them out of a gang or are you working on how do you cope with being part of a gang?” She followed with an insight: “it’s . . . how it’s affecting them in the school and so, generally, it leads to academics and attendance and if there are discipline issues or . . . . But it still has to have the school slant to . . . work with them.” Judy (PSC) concurred that training had “been mostly awareness and information,” and a lack of urgency to learn more left her deficient in skills and techniques to intervene.
Although awareness training appeared to be somewhat useful, specific prevention and intervention strategies were lacking in any of the training in which PSCs had previously participated. Stacey (PSC) stated that the limited training she received had been “one or two instances” consisting of “signs or signals.” Sasha noted she had not been trained to intervene, and she believed part of the problem was the nature of gangs because they may be “generational, and I don’t think anybody really knows how exactly [to] intervene. ” When speaking about the role of training, Judy quite frankly stated, “If you’re going to provide . . . training, does that imply that I then own the problem . . . if you’re training me, you’re giving me the problem and how am I supposed to solve it?”
Actual and Potential Roles When Working With Students in Gangs
The perceived and actual role of working PSCs has been studied extensively. Recommendations for serving students representing specific populations may vary (e.g., different ethnic groups, various exceptional populations, sexual minorities). On the other hand, ASCA (2014) is explicit in its petitioning provision of services to all students to address long-term goals and “demonstrate personal safety skills” (p. 2). The findings in this study suggest a possible actual role and provide ideas for a potential role for serving gang members.
Beth’s SL, Stan, said, “I would say they [PSCs] don’t really have a specific role in identifying gang presence” and “it wouldn’t be something that I would put under their job description.” Beth also noted that interactions with students in gangs were limited to an awareness that students may be involved with a gang because any intervention or interaction was something “that the assistant principals work with.” Stan’s comments mirrored those of his PSC. He stated, “If it’s a discipline issue, then it [the student issue] would stick with the administration.” Stan’s PSCs would be involved if the student needed “more of a counseling-type component where the student needs assistance or is seeking help from . . . the school.”
Sasha said she worked with students in gangs, but their gang affiliation was “not what we’re working on.” Beth agreed: “The thing is . . . if a kid is coming to you with a specific problem, you help them with that specific problem whether he’s a gang member or not.” Beth stated her actual role as a PSC limited her ability to interact because in her opinion, “if a kid was deeply entrenched in a gang, we’re not going to be able to get them out of that gang.” Derek (SL) agreed that the degree of involvement complicates the intervention because “once they reach a certain point, it is going to be very difficult—I’m not going to say impossible—but it’s going to be very difficult to get [them] back.”
Because the immediate need for a student to seek a PSC’s assistance was rarely, if ever, gang-related, Beth noted her form of intervention was about helping the students obtain their diplomas. Beth went on to say, “If he is here and attempting to get an education, behaving himself and not fighting . . . then my role would be to help him get what he needs from the school system as long as he is playing by our rules.” Her view of services for gang members seemed focused primarily on academic counseling.
PSCs’ Collaborative Role in Discipline Processes
Jake (SL) identified collaboration as a function in the PSC’s role when working with students in gangs, although he noted that the level of collaboration would be limited by the degree of the student’s gang involvement and its impact on the school environment. Jake stated, “I don’t know that they play a role in identifying gang issues unless somebody comes to them with a situation.”
Stacey, a PSC at Jake’s school, concurred with his assessment when she noted, “We don’t do a lot in identifying the gang presence . . . administration and the resource officer tend to be the ones dealing with that.” Stacey went on to say that addressing students in gangs was handled by administrators, and there was no communication with the PSCs about those students that may be involved in gangs. Communications related to students in gangs among SLs, PSCs, and teachers did not exist at Stacey’s school. She explained, “I can’t remember anyone here ever talking about making that kind of referral.”
Like Stacey, Trevor (PSC) did not expect referrals related to gang membership coming to him from teachers. The PSC participants reported that those students violating school policy were referred to administrators. Most referrals for confirmed concerns related to gang members based on attire or language were directed to the administrative teams if they came to the counseling office first. As a counterpoint, Trevor’s SL, Frank, stated, “I can’t say I’ve ever met a counselor I would trust to even give me that type of information.” He went on to say, “So I’m not very trusting of that [information coming from PSCs] at this point. I don’t think they’re [PSCs] involved.”
The degree of collaboration in the actual role of PSCs was mentioned frequently. There seemed to be a lack of collaboration and shortage of referrals from SLs to PSCs, especially when the student gang members had committed infractions leading to disciplinary consequences. When SLs disciplined gang members, there often was no follow-up with PSCs. The SLs in this sample seemed not to view PSCs as contributors to their disciplinary and safety maintenance functions. Because of their focus on safety and discipline issues when thinking about gang members, it seemed not to occur to the SLs that PSCs could contribute to the academic, career, personal, and social development of gang members via their traditional professional functions.
Limitations
Given the impact of the school calendar and its restricted timeline on data collection, it is possible the researcher was dependent upon acquiring participants from a limited population of busy professionals. Rather than relying on power analyses to determine the sample, qualitative researchers rely on evidence of data saturation, which may not have occurred in this study, to ensure sample sizes are sufficient. Further, qualitative researchers continue interviewing if repeated themes or codes are not present in the interviewing and follow emerging themes (Corbin & Strauss, 2008; Creswell & Miller, 2000; Marshall, Cardon, Poddar, & Fontenot, 2013). In the present study, the sample size was smaller than some sources recommend for grounded theory studies. Fortunately, obvious signs of saturation were noted after the eighth participant was interviewed.
Racial diversity was limited to one African American in each sub-sample. Gender diversity was not achieved in the SL sub-sample. Consequently, the voice of a female SL’s perspective was not present in this study because there were only five female site-based SLs in a district with 25 high schools. The lack of diversity might have impacted the lens by which they led or worked with marginalized populations. Meeting the age diversity selection criterion also was a challenge. The average age of the PSCs indicated that the views and experiences of younger professionals were understated. The extent of the participating PSCs’ exposure to the ASCA National Model (2012a) was not assessed in the demographic questionnaire. Consequently, recommendations promoted in the National Model such as serving all students; offering comprehensive school counseling programs; enhancing the academic, career, and personal/social development of students; and collaboration with stakeholders, may have been limited, therefore impacting their perceived and actual roles accordingly. Participants may have self-censored responses as a result of being interviewed by a school system colleague or by knowing that a colleague in their school with more power was also being interviewed. Utilizing a researcher without ties to the school district might have enhanced the responses. Having colleagues from the same school participate was an important component of the study, a limitation that had to be accepted in addition to the population and sample being limited to one school district.
Discussion
The perceived and ideal role of PSCs has been extensively studied; however, a search of the professional literature demonstrated a paucity of research on the role of PSCs with specific, marginalized student populations (e.g., exceptional children, homeless), and the present study was designed to address the work of PSCs with one such group (i.e., students in gangs). The researcher attempted to understand the participants’ perspectives related to how participating PSCs and SLs described their actual roles, their previous training, and opportunities for further training with regard to serving gang members.
Consistent with previous research (Burnham & Jackson, 2000; Ibrahim et al., 1983; Lambie & Williamson, 2004), the findings revealed a perceived role for the PSCs’ work with students in gangs as academically focused and reactive. PSC participants noted not knowing what counseling strategies to employ in order to assist students in gangs, implying there is no ideal role for PSCs within that domain. A lack of engagement in professional development, concerns for personal safety, unclear or absent roles for working with students in gangs, and, notably, a limited role imposed by SLs, negatively impacted their potential for working with gang members constructively.
Insights Based on the Circumstances That Led to the Study
As stated in the introduction, motivation to conduct the study was based on the first author’s limited previous professional experience with gang members, suggestions from a literature search, and results of a pilot study. The first author reported having observed the influence of disruptive gang members in her schools, leading to conflicted thoughts about how to serve them. Consistent with previous literature on role confusion (Burnham & Jackson, 2000; Lambie & Williamson, 2004), PSCs in the present study also seemed conflicted about serving student gang members, and SLs seemed to consider the role of PSCs from a limited perspective. The perspectives of the two sets of professionals were somewhat different because their respective broad professional goals differed. Although SLs were more likely to focus on maintaining order and ensuring safety for all students, PSCs were more likely to focus primarily on their own safety and secondarily on providing limited responsive services to gang members (Sindhi, 2013).
Consequently, when SLs considered the role of PSCs, their perspectives were narrowly focused on safety and disciplinary issues, and PSCs were not viewed as being expected or able to contribute to those goals. They were not prompted to consider the PSC’s role from a broader professional perspective, nor did they think of it (Cobb, 2014). It seemed as if most of the PSCs also responded from a safety perspective, feeling unprepared and unwilling to be involved in that kind of role, especially if it would involve discipline or attempting to get students to leave their gangs. Two PSCs (Sasha and Beth) mentioned providing limited responsive services if requested (i.e., personal issues and academic counseling) and if the students were behaving themselves. This finding also mirrored those of the pilot investigation that prompted this study.
Related contributions to the professional literature indicated dissonance about the perceived and actual roles of PSCs (Brott & Myers, 1999; Burnham & Jackson, 2000; Ibrahim et al., 1983; Lambie & Williamson, 2004). The findings in the present study were quite similar to those of Caldarella et al. (1996) almost two decades ago—that is, the PSCs did not feel adequately trained to work with gang members. And the attitudes expressed by the PSC participants in the findings mirrored the apathy about and disinterest in serving gang members reported by Ibrahim et al. (1983) over 30 years ago. Unfortunately, the findings highlighted apparently limited potential for PSCs to address the academic, career, personal, and social development needs of students in gangs in the targeted school district because of their current settings and frames of mind.
Implications for Professional School Counseling
Limited range of counselor services. Implementation of the ASCA National Model (2012b)throughout the school system represented in the present study apparently had little influence on the role PSCs played in serving gang members. Considerable interview content from PSCs and SLs seemed focused on safety and discipline issues rather than on the academic, career, personal, and social development of student gang members. Mention of providing academic services came from two of the PSCs. Limiting counseling services to academics alone does not fit into the proactive, “serve all students” framework supported by ASCA (2012b). The perception that PSCs are solely academic counselors may cause them to feel boxed in professionally, therefore limiting their ability to advocate for counseling services for students in gangs and causing them to determine over the course of their professional careers that their role is fixed and rigidly academically focused (Lambie & Williamson, 2004).
Insufficient training. Three of the PSCs reported lacking sufficient training as a barrier to their working with students in gangs. Four of the five PSCs had not received training related to working with students in gangs during their master’s degree programs. Two of the five reported attending workshops after graduate school, and the remaining three had not sought training. Training provided by the school district on gangs in schools was limited to enhancing awareness, and there was no coverage of counseling-based techniques designed to reach students in gangs. A significant obstacle to training was time away from work and the cost of attending training. Although obstacles to training were reported, there seemed to be an underlying sense of frustration about the training that had been offered. The training from the district and from professional conferences was designed to make school personnel aware of the presence of gangs in the schools. This perceived lack of training designed to intervene and engage in counseling services for students in gangs is consistent with Brott and Myers’ (1999) work noting the need for experiential learning to enhance professional autonomy. The participants reported not knowing what to do with students in gangs and wondering what the goals of the counseling relationships would be if students were involved with gangs. This limited response model appears to have negatively impacted the way that PSCs viewed gang members. Neither the PSCs nor the SLs wanted PSCs involved in a discipline-focused mode.
PSC collaboration and advocacy. The Collaborative C.A.R.E. grounded theory presented at the beginning of the findings section suggests that PSCs respond to the challenges presented above via collaborating with others in their educational communities to advocate for policies, procedures, programs, and educational opportunities designed to clarify their role in providing responsive services to students in gangs. Although PSCs will benefit from more informed policies and richer educational opportunities, they also have advocacy competencies acquired in their training programs that should be of value when serving all students, including gang members. It appears as if the best way to serve students in gangs is through targeted responsive services designed to remove barriers and promote equitable access to counseling services (Trusty & Brown, 2005). Fortunately, most PSCs will not have to work differently in order to work with students in gangs via these approaches. Therefore, it appears as if the major changes needed are attitudinal. Believing that students in gangs deserve their services and advocacy efforts and can be served through existing services and competencies is essential. Overcoming safety concerns seems to be a very important goal. Students in gangs are members of a unique cultural group and equally worthy of positive regard and empathy. Becoming familiar with the nuances of this culture also seems to be an important goal for PSCs.
PSCs are challenged to be able to approach counseling sessions with student gang members in the same way as any other student client. Sasha noted she had not been trained to intervene with gang members; however, she likely is capable of building empathic relationships and aiding in goal setting and future planning for all student clients. The challenge might be to accept gang members as they are and attempt to help them focus on something of value that they want to be in their future and attempt to help them achieve those goals.
Recommendations for Practice and Research
Training preparation recommendations. The role of the PSC is continuously evolving via numerous influences, such as changing school policies and new initiatives at the local, state, and federal levels. Over their professional careers, PSCs may see a shift in the issues their students bring to the counseling relationship. For example, 15 years ago, PSCs were not dealing with cyberbullying. Cultural and economic shifts lead to changes in the issues students are forced to address, and changes in the lives of the students challenge PSCs to expand their expertise in order to be more effective practitioners. PSCs should be offered and encouraged to attend training based on a variety of issues impacting their work with 21st-century students, including enhancing the academic, career, personal, and social development of gang members.
As PSCs prepare to respond to evolving issues and shifting demographics, graduate training programs are challenged to provide instruction to prepare future PSCs for the realities of school settings and the diverse populations served. By no means can graduate training programs prepare graduate-level students for all of the nuances of practicing in a school; however, a careful review of the populations being served in 21st-century schools may guide the development of training modules designed to work with unique populations, including students in gangs. A training module of this type also can be developed and implemented in school districts in order to provide professional development for practicing PSCs.
Research recommendations. The paucity of research related to students in gangs and school counseling provides rich opportunities for future studies that might include examining the professional development needs of PSCs, addressing personal safety concerns, and exploring the impact of school-based stakeholders on the self-efficacy of PSCs. Until PSCs feel secure in the role they were trained to fill, they may continue to accept the non-counseling roles often expected by SLs and experience low levels of self-efficacy in working with diverse populations, including students in gangs (Dahir, Burnham, & Stone, 2009).
Responsive services address the immediate needs and concerns of students and incorporate both direct and indirect service modes (ASCA, 2012b). Further research involving responsive services may address the following questions: How is role development impacted by existing procedures and policies? How is the role of PSCs different in districts with procedures for addressing the needs of students in gangs versus districts lacking the same procedures? How effective are PSCs who collaborate with their communities when working with gang members?
Of all the research needs regarding students in gangs, knowledge acquired from the gang member’s perspective seems most needed. Without gang members as participants, the voice of students in gangs will continue to be silent. Studying students in gangs in order to understand how school staff can enhance their development may provide valuable information for both responsive and core curriculum services that can be provided by PSCs.
Conclusion
ASCA’s National Model (2012b) advocates for comprehensive school counseling programs designed to serve all students. Gang members are a unique student culture to be included within the “all students” framework and can benefit from school-based counseling services designed to enhance their academic, career, personal, and social development. Unfortunately, the findings in the present study revealed that there are impediments preventing PSCs from serving gang members. It seems as if the PSCs in the present study lacked role clarity in working with students in gangs, and there was a lack of intervention-based professional development. Not serving students in gangs led PSCs to believe they have nothing to offer those students through traditional counseling services, and this lack of efficacy may impact their role as advocates. Although this study was limited to one school district, the experiences and perceptions of PSCs and SLs in this study might not be unique. PSCs are uniquely trained and strategically located in school settings to provide valuable services to gang members that can help them feel accepted for who they are at the moment, while also helping them to focus on finding a meaningful pathway to their futures.
Conflict of Interest and Funding Disclosure
The authors reported no conflict of interest
or funding contributions for the development
of this manuscript.
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Jennifer Barrow, NCC, is an assistant professor at North Carolina Central University. Stanley B. Baker is a professor at North Carolina State University. Lance D. Fusarelli is a professor at North Carolina State University. Correspondence can be addressed to Jennifer Barrow, 700 Cecil Street, Durham NC 27707, jbarrow4@nccu.edu.
Oct 21, 2018 | Volume 8 - Issue 4
Vernell Deslonde, Michael Becerra
This study utilized a qualitative dominant crossover mixed analysis that examined why school counselors (N = 38) choose or do not choose to use Naviance—an online college, career, and financial planning tool. The study further explored whether school counselors’ acceptance and use of Naviance enhances counseling practices, job productivity, and efficiency. The Technology Acceptance Model (TAM) was used for the theoretical framework. TAM is comprised of four constructs: perceived ease of use, perceived usefulness, attitudes, and actual behaviors. Bandwidth, training, and connectivity influenced some counselors’ attitudes toward usage and productivity; however, overall attitudes toward Naviance were positive. Future research should explore the connection between counselor usage and the number of hours trained on Naviance.
Keywords: school counselors, Technology Acceptance Model, TAM, Naviance, qualitative dominant crossover mixed analysis
New technologies are pervasive in the counseling profession. School counselors are experiencing a growing field of technologies that include virtual counseling platforms, smartphone applications, and learning management systems that provide the ability to see students face-to-face, quickly access information through an application, and offer high school students resources and information, ultimately assisting in the school-to-work transition. Additionally, the value of integrating new technologies into practice to support counselor growth as well as student outcomes is recognized in the education field. Many researchers believe that online technologies are effective educational tools (Serdyukov, 2017; Sung, Chang, & Liu, 2016; Tarhini, Hone, & Liu, 2015; Teo, 2011).
According to the Condition of Education 2017 report, in 2013–2014, K–12 schools spent $634 billion integrating technology to support academic achievement (National Center for Education Statistics, 2017). The bulk of the cost has been on purchasing equipment, integrating hardware and software, and training staff personnel. Despite the promise and financials spent, the lack of user acceptance is a barrier to the success of integrating new technologies (Blanchard, Prior, Barton, & Dawson, 2016; Davis, 1993; Tarhini et al., 2015; Teo, 2011). Without user acceptance, the value of the technology diminishes. Alternatively, increased technology acceptance can enable educators, including school counselors, to become effective with transferring knowledge, preparing and advancing student outcomes (Hu, Clark, & Ma, 2003), and enhancing counseling practices (Hayden, Poynton, & Sabella, 2008; Steele, Jacokes, & Stone, 2014).
Numerous theoretical models have been developed to investigate users’ acceptance of new technologies. The most widely researched model on user acceptance that investigates why a user chooses to use or not to use technology is the Technology Acceptance Model (TAM; Davis, 1993; Nair & Das, 2011; Tarhini et al., 2015; Teo, 2011). TAM predicts the level of technology acceptance and usage. Few studies exist on TAM within the context of K–12 schools and even fewer on the school counseling profession (Tri Anni, Sunawan, & Haryono, 2018). Utilizing TAM as a guiding framework, this research extends and advances knowledge on factors that influence school counselors’ acceptance and use of technologies, specifically Naviance, an online college, career, and financial planning counseling platform.
School Counselors’ Technology Acceptance
Perceived Ease of Use
Research has indicated that individuals are more likely to accept and use new technology if they perceive the technology as easy to use (Davis, 1993; Nair & Das, 2011; Saade & Bahli, 2005). Perceived ease of use is determined when a user believes that using a system is free of effort (Nair & Das, 2011;
Tarhini et al., 2015). Previous studies reveal common themes of perceived ease of use of certain technologies in the school counseling profession. For example, many school counselors perceive that sending email communication, creating multimedia presentations and webpages, developing newsletters, and retrieving information from schools’ student information systems are relatively easy functions (Carey & Dimmitt, 2004; Carlson, Portman, & Bartlett, 2006; Kozlowski, Mikesina, & Genova, 2015; Loague, Alexander, & Reynolds, 2010; Steele et al., 2014; Van Horn & Myrick, 2001). Today, many school counselors find it easy to retrieve counseling-related information from the internet and create targeted presentations for students. Further, school counselors perceive that delivering counseling curriculum, disseminating information, and administering needs and career assessments require minimal effort (Hayden et al., 2008; Holcomb-McCoy, Gonzalez, & Johnston, 2009; Loague et al., 2010; Millsom & Bryant, 2006; Steele et al., 2014).
School counselors have found certain types of technology easier to use. For example, in a quantitative study, Carlson et al. (2006) investigated how school counselors use technology and their comfort level. The results indicated that counselors felt comfortable or somewhat comfortable (92.7%) utilizing certain types of technology and software, such as desktop computers, VCRs and monitors, overhead projectors to create visual presentations, and Microsoft Word and Microsoft PowerPoint, as additional resources. However, most school counselors (76.9%) experienced low comfort levels and felt anxious or somewhat anxious using new software.
Perceived Technology Usefulness
Technology acceptance also is influenced by perceived usefulness. Perceived usefulness is determined by a user’s belief that a type of technology enhances job performance (Tarhini et al., 2015). Although a
reasonable amount of literature exists on how school counselors use technology in the counseling profession (Carlson et al., 2006; Hayden et al., 2008; Steele et al., 2014), little exists on perceived usefulness (Tri Anni et al., 2018). Tri Anni et al. (2018) surveyed school counselors in Indonesia and found that counselors who perceived that technology was easy to use were more likely to determine that the technology was useful. However, Tri Anni et al.’s study did not focus on a specific type of technology such as Naviance to determine whether such a tool enhances job effectiveness.
In another study, Steele et al. (2014) surveyed school counselors and found that many (45%) remained neutral when asked whether the advantages of online communication in their counseling practice outweighed the disadvantages. Furthermore, 61% felt slightly or not comfortable at all using online technology to perform counseling duties. When asked specifically about using Skype and other synchronous online communication technologies, researchers found a positive correlation among counselors’ level of training and comfort.
Attitudes Toward Technology Use
Guzman and Nussbaum (2009) argued that merely acquiring the hardware or software is insufficient to integrate technologies and therefore stressed the importance of the user’s attitude. The more positive the attitude about technology, the higher the actual usage (Teo, 2011). Several researchers have found school counselors’ attitudes toward the use of technology to be mostly positive, but lower when new technologies are introduced (Carlson et al., 2006; Rainey, Mcglothlin, & Miller, 2008; Steele et al., 2014).
It is important to note that there are external forces that shape a person’s perceived ease of use and usefulness of technology, and these forces may negatively affect attitudes. Such barriers include limited training on new software, age of the user, bandwidth challenges, slow data access, time delays in downloading content, and limited equipment (Carlson et al., 2006; Guzman & Nussbaum, 2009; Hu et al., 2003; Lederer, Maupin, Sena, & Zhuang, 2000; Steele et al., 2014). Moreover, large counselor caseloads might be a barrier to perceived ease of use and usefulness. For example, counselors working in states with higher caseloads may perceive that learning new technological software while managing higher caseloads and trying to capture large amounts of student information can be difficult.
Naviance: An Online College Career and Financial Planning Tool
Although many school counselors and students have used Naviance for more than a decade, a Google Scholar search revealed only one study in which the authors explored the relationship between the number of times that students visit Naviance and increased college application rates (Christian, Lawrence, & Dampman, 2017). Naviance is an online college and career readiness tool developed by Hobsons (Hobsons, 2017). According to Hobsons’ website, “more than 10 million students rely on Naviance to achieve key readiness milestones and answer critical questions such as: Who am I? What do I want to be? How will I get there? and Will I be successful?” (Hobsons, 2017). From a college and career counseling perspective, Naviance is used by middle and high school counselors and personnel to support and track student progress. Some of the features in Naviance include course planning; postsecondary planning; career inventories; career and college searches; college majors; college applications; test preparation (SAT, ACT, and Advanced Placement); college enrollment; and 28 curriculum lessons in college, career, and financial planning.
TAM
Technology acceptance and adoption is well documented in the literature. Although several factors influence the acceptance and use of technologies, TAM, grounded in Fishbein and Ajzen’s (1975) research on beliefs, attitudes, and behaviors, indicates that perceived usefulness and perceived ease of use predict attitudes and actual behaviors (Davis, 1993; Nair & Das, 2011). Essentially, TAM captures the user’s overall attitude toward online technologies.
Davis (1993) hypothesized that one’s attitude toward using technology is a function of two beliefs: perceived ease of use and perceived usefulness. Perceived ease of use is the degree to which a person believes that using the system would require minimal effort, whereas perceived usefulness is the extent to which the information system enhances job performance (Lederer et al., 2000). Two other constructs of TAM are a person’s attitude toward the use of the system (which is the user’s desire to employ the system) and behavioral intention (which is the likelihood that a person will use the system; Davis, 1993; Lederer et al., 2000). Scholars have argued that perceived ease of use of the technology and perceived usefulness determines one’s attitude toward a new technology (Davis, 1993; Padmavathi, 2016; Teo, 2011), such as Naviance.
Purpose of the Study
The purpose of this study was two-fold. First we sought to investigate if school counselors utilized Naviance. Second, we examined how Naviance usage enhances middle and high school counselors’ practices, productivity, and efficiency. Although many school counselors integrate technology into their practice (Kozlowski et al., 2015; Reljic, Harper, & Crethar, 2013; Steele et al., 2014), few studies address whether school counselors accept new technologies, as well as examine attitudes and actual usage. TAM provides the theoretical framework to understand school counselors’ acceptance and use of Naviance. To shed light onto the phenomenon, the following research questions guided this study: (a) Do school counselors choose to use or not choose to use Naviance; and (b) how does Naviance acceptance and usage enhance school counseling practices in terms of productivity and efficiency?
Methods
Data sources collected for this qualitative dominant crossover mixed analysis study included a survey questionnaire, face-to-face semi-structured interviews, and Naviance staff usage and engagement reports. According to Onwuegbuzie and Teddlie (2003), the benefits of a crossover mixed analysis include the ability to compare, correlate, and integrate quantitative and qualitative findings to describe the phenomenon. This type of qualitative dominant crossover mixed analysis takes into consideration a qualitative stance with quantitative data that provides additional detail to the study (Frels & Onwuegbuzie, 2013; Onwuegbuzie, Leech, & Collins, 2011). Ross and Onwuegbuzie (2010) grouped quantitative analyses according to difficulty, starting at the basic, descriptive level 1, and reaching as high as level 8, which includes multidirectional and multilevel analyses like multilevel structural equation modeling. In this study, the researchers used a level 1 quantitative analysis, which includes descriptive data taken from usage and engagement reports, and percentages from the questionnaire to determine productivity and efficiency.
Participants
A purposeful and convenience sample was utilized for this study. Purposeful sampling is used to identify and select individuals who are knowledgeable about a phenomenon (Palinkas et al., 2015), whereas convenience sampling is beneficial when participants are easily accessible and in close geographic proximity (Etikan, Musa, & Alkassim, 2016). The first researcher purposefully sought out middle and high school counselors who worked in close proximity and use Naviance in their role, from 14 public schools within the southwestern part of the United States. The first researcher sent an email to 48 potential participants. Of the 48 participants contacted, 38 school counselors agreed to participate, of which 10 were male and 28 were female. Twelve counselors worked at the middle school level and 26 at the high school level. All participants held a master’s degree and Pupil Personnel Service credential. Counselors ranged in age from 25 to 51. The age range for 55% of the school counselors was 25–44 years, whereas the remaining 45% age range was 45–51 years.
School District and Research Team
The school district implemented Naviance in 2014. The Naviance technology was given a low to medium priority, with the expectation that school counselors would at least minimally use the technology. The Naviance implementation occurred over a 3-year period. In the first year, two middle and two high schools implemented Naviance. In the second year, three additional high schools, two alternative high schools, and two additional middle schools launched Naviance, and during the final year, the remaining three middle schools rolled out the technology tool. Also in the third year, all Advanced Placement (AP) teachers were trained on Naviance AP test prep at each high school. Counselors and select school personnel received two full-day trainings on Naviance during each implementation year and Webex trainings were offered quarterly to those who needed a refresher on Naviance features and functionalities. In addition, professional development was offered to counselor groups upon request.
The first researcher works at the district office and provides monthly professional development to school counselors; however, the first researcher does not supervise the school counselors. Further, there are multiple layers of supervision that remove the first researcher from the day-to-day interactions of school counselors; the first researcher does not sign the performance evaluations of counselors, thereby preventing the first researcher from being able to use knowledge obtained from this study to negatively affect the participants. The second researcher works at a university in Texas as an adjunct faculty member. The first researcher identifies as African American and the second as Afro-Latino, with a mean age of 45. The first researcher is female and the second is male. Neither researcher has received financial assistance to conduct this study from Hobsons or its affiliates.
Instruments
Survey questionnaire. The TAM electronic questionnaire, first developed by Davis (1993) and validated in different contexts by several researchers (Nair & Das, 2011), consisted of 17 questions, of which 13 were on a 5-point Likert-type scale questionnaire, with the scale ranging from 1 (strongly agree) to 5 (strongly disagree). Also included in the survey questionnaire was demographic information (questions 1–3). To explore the research question, survey questions 4–15 asked about the extent to which Naviance was easy to use (4 questions); whether Naviance enhanced middle and high school counselors’ counseling practices, job productivity, and efficiency (4 questions); if Naviance was useful (2 questions); and attitudes toward using Naviance (2 questions). Question 16 was open-ended and regarded counselors’ overall attitude toward using Naviance, and the last question asked participants to indicate the frequency that they use Naviance (1 = daily, 2 = weekly, 3 = monthly, 4 = at least every other month, or 5 = not at all). Validation of the survey questions was established through a school counseling professional, who is a researcher, university faculty, and a retired school counselor of 30 years. Both researchers had combined experience of more than 30 years in counseling.
Interviews. Face-to-face, semi-structured interviews were another source of data for this study to help answer both research questions. The researchers used TAM and the survey questionnaire to construct 10 interview questions. The 10 interview questions centered on usefulness, ease of use, attitudes, and whether Naviance helped to enhance school counseling practices, job productivity, and efficiency. To ascertain ease of use, the first two interview questions focused on which of the functionalities in Naviance were the easiest to navigate and which data visualization features were easy to decipher. Questions 3 and 4 investigated how Naviance enhanced the role of school counselors and the benefits of using Naviance to engage multiple stakeholders. Interview questions 5–8 examined the ways that Naviance increases job effectiveness, efficiency, and productivity. The remaining questions explored whether Naviance was worthwhile and integration challenges.
Validation of the interview questions were by an expert panel of doctoral-level professionals in the fields of education and school counseling. Two members of the panel have been school principals and district personnel for more than 20 years combined. The third expert panelist is a university faculty member and retired school counselor. The first researcher sent the interview questions to the expert panel via email and requested feedback. One of the experts suggested that the researchers add a definition for perceived ease of use and perceived usefulness for the participants as part of interview questions two and three, which the first researcher subsequently incorporated. The second expert suggested that the researchers incorporate the language middle and high school counselor as part of the purpose of the study in the interview script rather than school counselor, which the first researcher included. The third expert did not offer additional suggestions.
Archival materials. To further help address the second research question, the researchers used the Naviance staff usage and engagement reports as a secondary data source. Specifically, the staff usage report showed the number of times that school counselors had accessed Naviance since implementation. In addition, the engagement reports showed the features in Naviance school counselors use to support the academic, college, and career development of students.
Procedure
The first researcher sent an email invitation along with a Qualtrics link for the TAM questionnaire to 48 middle and high school counselors to participate in this study. The survey remained open for 10 business days. Within that timeframe, 38 middle and high school counselors consented to participate in this study. After the survey closed, the first researcher sent an email to all 48 counselors inviting those who completed the survey to participate in face-to-face interviews. Of the 38 counselors who completed the study, 10 consented (three middle and seven high school counselors) to participate in the face-to-face interviews. The first researcher told participants that the interviews would be digitally recorded, they could withdraw any time, and their demographic information and personal identities would remain confidential. The first researcher conducted 10 separate interviews, which lasted on average 33 minutes.
After transcription of the interviews by rev.com, an online transcription company, each participant received a copy of the transcript to review and offer feedback within five business days. At the close of the five business days and with no changes suggested from participants, the first researcher deleted information that could identify participants and emailed the interview and Naviance staff and engagement data, which was retrieved at the district level, to the second researcher. The use of video conference calls as a virtual workspace was useful in collectively reading over transcripts, developing and comparing coding, and discussing themes.
Trustworthiness Procedures
To ensure trustworthiness and credibility of the study, the researchers used the process of triangulation and member checking to strengthen construct validity during the data collection process. The selection of triangulation allowed the researchers to collect data using a combination of sources to incorporate multiple perspectives on technology use and integration. Although archival materials (e.g., school counselor usage and engagement reports) did not require insight from the participants to increase the researchers’ understanding because of their pre-existing nature (Yin, 2014), the materials were instrumental in authenticating information from the interviews and were determined to be a valued data source. Another method used to strengthen trustworthiness was member checking. The first researcher separately emailed each participant, asking them to review the interview transcriptions to check for accuracy and offer feedback. Each participant replied within the 5-day timeframe indicating no corrections or feedback were necessary.
Data Analysis
The process of thematic analysis guided this study, which involved identifying patterns, insights, or concepts in the data that help to explain why those patterns are there (Bernard & Ryan, 2010). Both researchers used the process of open and axial coding, which involved breaking apart each data source, and deductive coding, which uses a top-down approach making connections and categorizing themes under TAM (i.e., perceived ease of use, perceived usefulness, attitudes, and actual usage). After reviewing themes from both researchers, there was absolute agreement about themes and codes.
The researchers followed the six phases of thematic analysis described by Clarke and Braun (2013), which included (a) familiarization of the data; (b) generation of initial codes; (c) identification of themes; (d) review themes; (e) define and name themes; and (f) produce the report. First, the researchers read through each line of the transcript several times to become familiar with content and understand perceptions regarding the usefulness, ease of use in using Naviance, and attitudes. Second, the researchers generated initial codes. Open coding allowed the researchers to break apart and group the data, and axial coding allowed the researchers to make connections to the data once it was categorized (Bernard & Ryan, 2010).
Next, the researchers categorized themes according to TAM from the transcribed interviews. TAM served as a priori themes, which related to the research questions as well. Themes capture important data about the research questions (Clarke & Braun, 2013) and explore patterns (Alhojailan, 2012). To help sort through the data to identify potential themes and the relationship between the codes, the first researcher established a codebook to assist in analyzing the data. Then, the researchers defined and named the themes based on TAM. Next, the researchers connected the narrative to the themes, named each theme according to the model, and generated themes. The last step of the data analysis process was to produce a concise, non-repetitive account of the story related to the research questions (Clarke & Braun, 2013).
Results
Perceived Ease of Use
Drawing from the survey questionnaire, 79% of the middle and high school counselors (n = 30) strongly or somewhat agreed that Naviance has a friendly interface for students and counselors, requires minimal effort, and was easy to use, while 5% (n = 2) neither agreed nor disagreed and 16% (n = 6) somewhat disagreed. Similarly, when asked whether Naviance was clear and understandable, 79% (n = 30) strongly or somewhat agreed, while 3% (n = 1) neither agreed nor disagreed, and 18% (n = 7) somewhat or strongly disagreed.
During the interviews, the counselors reported that the Naviance data platform layout made it easy to view and use all the pertinent data required for advising students on academic performance, college readiness, and social and emotional development. Specifically, some of the layout features discussed by counselors included Quick Links (i.e., application manager, transcript manager, journal dashboard, curriculum, and test prep) and counseling tabs (i.e., students, planner to help assign tasks and discuss goals, course planner, scholarships, colleges, careers, and a new feature, analytics). Other areas described by counselors that contributed to the ease of use of Naviance was data visualization of college applications submitted by students on the home page, and outcome images (i.e., overall percentage of students that applied and were accepted to at least one college and overall percentage that applied to and were accepted to a 4-year college).
Another feature reported by middle and high school counselors that they believed was easy to use was the reports and analytics functionality. At the middle school level, counselors indicated that they were able to run reports on whether students completed their career inventories or curriculum assignments. If a student failed to complete an assignment, counselors mentioned that sending an electronic reminder to their student via Naviance was seamless. One middle school counselor stated, “I run various queries in Naviance, which are extremely helpful. I like the feature where it allows me to automatically generate a weekly status report on all of my students.”
One high school counselor described Naviance’s academic, college, and career online resources: “Naviance is the best setup I’ve seen in my 20-plus years of being a counselor. It’s a one-stop shop and really simple to use.” Two other high school counselors described the ability to cross-share information with other Naviance counselors nationwide. For instance, a male high school counselor stated, “I no longer need to create student surveys! Other counselors who use Naviance in other states have created a battery of surveys across entire grade levels that I can export and electronically use with my students.”
Overall, most of the middle and high school counselors reported that Naviance was easy to use; however, some school counselors somewhat disagreed. For example, one high school counselor mentioned, “When Naviance is working correctly and the students can complete the activities, Naviance is easy to use. As a counselor, Naviance feels like busy work [record keeping, student follow-up, having groups of students logging in to a system], especially when there are issues with connectivity.” Another counselor reported, “Naviance is not user-friendly at the high school level. It’s too cumbersome and time consuming.”
Perceived Usefulness
On the survey questionnaire, when asked whether Naviance increases job-related effectiveness and productivity, in both instances most school counselors (79%, n = 30) strongly or somewhat agreed, while some were neutral (5%, n = 2) or somewhat disagreed (16%, n = 6). When asked whether Naviance enhances counseling practices, 84% of school counselors (n = 32) strongly or somewhat agreed, while 16% somewhat disagreed (n = 6). When asked whether Naviance was useful 92% of school counselors agreed (n = 35), while 8% (n = 3) somewhat or strongly disagreed.
During the interviews, eight of the 10 middle and high school counselors reported that the Naviance system is a comprehensive counseling solution that allows for the collection and quick retrieval of information that shows measurable results of their work, which increases their job effectiveness and productivity. For instance, school counselors identified the ability to retrieve overall assessment results, graduation status, academic progress, individual and small group tracking, pre- and post-outcomes, analysis on college application and acceptance rates (i.e., 2- and 4-year acceptances), field trip numbers, PSAT/SAT/ACT historical data, and more. The collection, analysis, and reporting of data from Naviance was perceived by school counselors as a useful strategy that supported their effort in becoming more data-driven, with data needed for school counselors to establish credibility in their role, evaluate their impact, and demonstrate program accountability that promotes student outcomes. The perception by many middle and high school counselors was that the Naviance system facilitated evidence-based practices. One high school counselor put it this way, “administrators understand data, and if we want to demonstrate our value to stakeholders, we must show how our work impacts student outcomes.” A middle school counselor stated, “Presenting survey data and responses from students after each presentation or field trip shows teachers, administrators, and parents the effect of our efforts.”
When asked whether Naviance enhances their counseling practice, one middle school counselor stated, “I think that Naviance makes our jobs a lot easier. . . . Naviance has helped to streamline the college, career, and academic process and make it very clear. Everything about our job as counselors is more fluid.” Another middle school counselor stated, “I think Naviance is very beneficial to my role. I can track student progress, communicate to teachers about relevant meetings, quickly deliver services, and actively engage to find digital resources to address needs.” A counselor at the high school level stated, “The more I used Naviance, the more I saw the many benefits, possibilities, and connections to the work that I do every day. Naviance has become a really important tool in my arsenal.” A high school counselor commented that Naviance helps capture whether students are on or off track to graduate and is a source to share electronic resources for students needing Tier 2 supports. Another high school counselor reported that Naviance was helpful in saving time when completing tasks and gathering student information. She stated, “Using Naviance makes me a better counselor; I’m more productive throughout my day, and I can tackle other more pressing issues students might have instead of working late to update my Excel spreadsheet.”
Although there were more counselors who found Naviance useful in their role, one middle school counselor and one high school counselor did not agree that Naviance enhanced their counseling practice. The high school counselor stated, “Naviance is yet again another system to use to support students that might go away when there is no more funding, so why learn it.” The same counselor went on to add that she has students who are “dealing with anger, drug addiction, pregnancy, suicide, and anxiety, and Naviance does not offer curriculum on those topics.” She further stated, “I can upload resources into Naviance, but it’s not useful because my role also includes helping students in the areas of social and emotional development.”
The middle school counselor described her experience using Naviance and added, “Naviance is good for kids, but I honestly do not see how it makes me a better counselor or my job more efficient or productive.” The same counselor added, “My job is about building trust, establishing relationships, advocating, and guiding students through middle school. Naviance is a tool that can help facilitate that process, but it does not enhance my counseling skills.”
Attitudes
When asked whether counselors like using Naviance and whether they have a generally favorable attitude toward it, in both instances the results were mixed. Twenty-eight (72%) of the 38 school counselors strongly or somewhat agreed that they liked using Naviance, four counselors (10%) neither agreed nor disagreed, and seven (18%) somewhat disagreed or strongly disagreed. When asked about having a favorable attitude toward Naviance, 23 (61%) strongly or somewhat agreed, 5 (13%) neither agreed nor disagreed, and 10 (26%) disagreed or strongly disagreed. Twenty-three school counselors (61%) reported on the open-ended survey question that Naviance was desirable to use for academic and related counseling purposes. Several counselors indicated that multiple training opportunities contributed to comfort level and positive attitudes. However, one high school counselor whose attitude was less than positive stated, “I would prefer to use Californiacolleges.edu, which is a free program that essentially offers the same activities for our students instead of Naviance. Plus, the system specifically caters to counselors and students in California, unlike Naviance.”
Two challenges identified by several school counselors that interfered with having a positive attitude about Naviance related to bandwidth issues and access to schools’ computer labs. Counselors expressed frustration by the slow internet connection at their schools, which they reported was due to limited bandwidth capacity. One counselor commented, “due to bandwidth limitations, Naviance does not always work.” Another challenge identified that interfered with overall satisfaction of Naviance was limited access to computer labs. One high school counselor stated, “Computer labs are scarce and accessibility to use Naviance with students is difficult.”
Actual Usage
Drawing from the Naviance usage and engagement reports, actual Naviance usage and engagement among school counselors was high. Since the implementation of Naviance, school counselor usage has increased each year (see Table 1). Counselor-supported engagement within Naviance is highest among high school counselors (see Table 2).
Table 1
Actual Usage of Naviance Since Implementation
| Descriptors |
Year 1
(2014–2015)
|
Year 2
(2015–2016)
|
Year 3
(2016–2017)
|
| Middle and High School |
1,295
|
3,277
|
5,574
|
Note.
Number of times school counselors used or accessed Naviance from 2014–2017.
Table 2
Counselor Engagement Support Provided to Students
| Descriptors |
Naviance Guidance Curriculum
|
ACT/SAT/ AP Study Plans
|
College Planning
|
Career Planning
|
Academic Planning
|
| Middle School |
12,887
|
0
|
599
|
10,735
|
32
|
| High School |
22,366
|
153,000
|
11,623
|
508
|
497
|
Note.
Number of times Naviance was used to engage students in 2016–2017.
On the survey, middle and high school counselors were asked the frequency of Naviance usage. Most school counselors used Naviance daily, followed by weekly usage. Sixty-six percent (n = 25) reported using Naviance daily, whereas 24% (n = 9) indicated using Naviance weekly, and 5% (n = 2) reported monthly use. Finally, 5% (n = 2) reported not using Naviance at all. Table 3 shows the frequency of Naviance usage.
Table 3
Naviance Frequency of Use by School Counselors
|
Descriptors
|
Daily
|
Weekly
|
Monthly
|
At Least Every Other Month
|
Not At All
|
| Middle School |
10
|
2
|
0
|
0
|
1
|
| High School |
15
|
7
|
2
|
0
|
1
|
Note.
Frequency in which school counselors used Naviance during the
2016–2017 academic year.
Discussion
Implementing technology in school counseling is a call to action from past counseling researchers (Casey, Bloom, & Moan, 1994; Creamer, 2000; Dahir, 2009; Granello, 2000) to move the profession into the future (Dahir, 2009). When school counselors adopt and integrate technology into their practices, they can be effective in their role (Hu et al., 2003). The first research question, whether school counselors choose to use or not use Naviance, was answered by most of the counselors, who indicated that the ease of use and the overall usefulness influenced their decision to use the Naviance platform or not. Barriers identified that interfered with ease of use and usefulness were bandwidth issues within schools and school counselors’ ability to connect to the resource tool.
The second research question, how Naviance acceptance and usage enhance school counseling practices, productivity, and efficiency, was answered by most of the school counselors in this study, who stated that the use of Naviance positively enhanced their job productivity, efficiency, and counseling practices. Particularly, the ability to introduce college-related material to help students develop individual education plans, identify courses, provide social and emotional resources, and advise on graduation status and college eligibility, was positive. In addition, more school counselors used Naviance as a vehicle to share information with teachers, administrators, and parents.
Limitations
There were several limitations. The results of this study indicated that school counselors had positive attitudes toward the integration and usage of Naviance; however, the findings were limited to middle and high school counselors who work in a specific public school district located in the southwestern part of the United States, which prevented the inclusion of experiences and expertise of other public and private school counselors throughout the country. The addition of other Naviance users in small public and private schools might have produced other results. Another limitation was that the first researcher has used Naviance for the past 10 years in various roles as a district administrator. To prevent bias, the first researcher did not make assumptions based on what participants chose to share or attempt to present answers. In contrast, the second researcher has never used Naviance, which allowed for an unbiased viewpoint when writing the analysis. Further, a school counselor educator, familiar with Naviance, reviewed and read over this study prior to publication to minimize researcher technology bias.
Finally, Naviance generally provides district offices and schools with reports on engagement activities and staff and student usage. Although researchers used the Naviance engagement reports to speak to overall usage in subcategories such as college planning, career planning, guidance curriculum, and test preparation, multiple school engagement reports were combined to differentiate middle and high school engagement activities. In addition, Naviance provides reports on staff usage; therefore, the first researcher retrieved data at the school site level to determine counselor usage rather than usage by staff, such as teachers and administrators, during data analysis.
Implications for Counselors
One of the benefits of using an online platform such as Naviance is that it can bring value to the practices of school counselors when helping to introduce and prepare students for college. For instance, such a tool can support dissemination of critical student-related information, data collection, tracking and analysis, customization of 4-year graduation plans, and communication between multiple stakeholders, to name a few.
The knowledge generated from this study is useful to school counselors in several ways. First, understanding the intricacies and impact of Naviance could offer school counselors additional ways to support their students’ academic development, college preparedness, and readiness efforts, and to share and provide social and emotional resources to students. Second, knowing which features in Naviance influence career and college-related outcomes at the middle and high school level can improve engagement and communication efforts between school counselors, parents, and teachers. Third, exposing students early to the numerous college readiness features and functionalities in Naviance can increase graduation and college application rates of high school students, which is consistent with literature findings. Fourth, capturing college- and career-related data can help school counselors communicate, gather, analyze, and synthesize information required to meet state accountability standards and evaluate the effectiveness of counseling programs.
Recommendations and Future Research
Given the benefits of integrating Naviance into the daily practice of school counselors, two recommendations for future practice include leveraging the reports and analytic features to emphasize programmatic effectiveness and student outcomes, and infusing the college-related curriculum into subject matter classes. Although the high school counselor is the primary interpreter of the college preparation, application, and enrollment sources, incorporating college-related information into classroom instruction could be used as a springboard to deliver information on college and career readiness and support the understanding of the relationship between academic performance and college eligibility. This practice could free up time for the high school counselor to have more meaningful and deliberate conversations with students to support their understanding of college norms and expectations and effectively facilitate the college enrollment process.
The findings indicate a need to extend TAM by exploring other external factors that influence user acceptance of Naviance. For example, future research could explore the connection between counselor usage and the number of hours trained on Naviance. Low counselor usage could be the result of insufficient training or differences in age. In addition, as many schools, particularly those located in urban settings, focus on increasing college eligibility, future studies should be conducted on Naviance test prep (i.e., ACT, SAT, AP) and student outcomes.
Conclusion
Research into school counselors’ technology integration and usage has been a focus in the counseling profession since the 1980s and continues to be an important area for investigation today. Most school counselors suggested that Naviance was useful in their role as a school counselor in providing academic, career, college, and personal counseling to students and that actual usage enhanced their job performance, productivity, and proficiency. In addition, many expressed that Naviance was a tool that required minimal effort, if usage was ongoing. Lastly, perceived usefulness and perceived ease of use was connected to school counselors’ positive attitude regarding Naviance.
Conflict of Interest and Funding Disclosure
The authors reported no conflict of interest
or funding contributions for the development
of this manuscript.
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Sep 28, 2018 | Volume 8 - Issue 3
Anthony Hartman, Hope Schuermann, Jovanna Kenney
Despite efforts to boost mental health treatment-seeking behaviors by combat veterans, rates have improved relatively little since 2004. Previous work suggests that trust and confidence in the mental health community may be a significant factor. This study explored how professional titles may impact trust and confidence among active-duty U.S. Army soldiers (n = 32). Consistent with previous research, eight vignettes were used to solicit ordinal (ranked) trust and confidence scores for mental health professionals. Highest confidence and trust were seen in clinical psychologists and licensed professional counselors, followed by psychiatrists, licensed clinical social workers, and marriage and family therapists; however, deviations were seen for each individual vignette and the manifested symptoms depicted. Scores for trust and confidence were strongly correlated and both appear to impact soldiers’ treatment-seeking decisions.
Keywords: soldiers, mental health professionals, licensed professional counselors, trust, confidence
The U.S. Army Medical Command’s Department of Behavioral Health provides the following vision: “Our efforts in education, prevention, and early treatment are unprecedented. Our goal is to ensure that every deployed and returning soldier receives the health care they need” (U.S. Army Medical Department, 2016). In 2004, a landmark study by Hoge and colleagues found that only 13–27% of soldiers meeting screening criteria for mental health disorders sought treatment from a mental health professional in the previous year. The researchers concluded that the primary reason for such underutilization was perhaps “concern about how a soldier will be perceived by peers and by the leadership” (Hoge et al., 2004, p. 20). Subsequently, the Army has taken significant actions to reduce negative perceptions toward mental health care and increase confidentiality for those seeking treatment.
Despite substantial efforts to reduce negative stigmas, the number of soldiers seeking mental health care seems to remain significantly low. In a population of soldiers with probable post-traumatic stress disorder (PTSD) or major depression, Schell and Marshall (2008) found that “only 30 percent had received any type of minimally adequate treatment” (p. 101). Specifically, only 18% received minimally adequate talk therapy treatment. Of a sample population of National Guard and Reserve service members reporting psychological problems, Britt et al. (2011) found that only 42% had sought treatment. Most recently, Britt, Jennings, Cheung, Pury, and Zinzow (2015) found that only 40% of soldiers who acknowledged having a mental health issue sought treatment in the last year. Although the percentages of soldiers seeking treatment seem to be improving, the current literature continues to show less than half of those in need seek even a first visit with a mental health care provider. Thus, other significant deterrents to seeking treatment remain beyond the perceptions of leadership and peers.
Research studies indicate that one possible reason for this underutilization of mental health care services could be soldiers’ lack of trust or confidence in the quality of their providers or treatments. When surveyed, one in four soldiers recently returning from deployment indicated a lack of trust in mental health care practitioners (Kim, Britt, Klocko, Riviere, & Adler, 2011). Similarly, in a different sample of soldiers and Marines screening positively for mental health disorders, 38% indicated a lack of trust in mental health providers, while one in four of the same sample indicated a belief that mental health treatments were not effective (Hoge et al., 2004). Further hinting at a lack of trust for mental health care professionals and confidence in treatment, many soldiers would prefer to address their mental health issues with family, friends, or clergy (Schell & Marshall, 2008). Recently, the statement “Marines don’t trust mental health professionals” was rated as one of the top perceptions that mark barriers to care by a sample of enlisted Marine Corps leaders (VanSickle et al., 2016, p. 1022). Ultimately, there seems to be a trend of distrust and a lack of confidence in mental health care treatments and professionals among military populations.
Mental Health Practitioners and Military Treatment
Considering that there are numerous types of mental health professionals (e.g., psychiatrists, mental health counselors), it is possible that soldiers’ perceptions and knowledge of mental health professionals may vary depending on the specific type of provider. This study aims to distinguish soldiers’ perceptions between distinct mental health professionals: psychiatrists, clinical psychologists, licensed clinical social workers (LCSWs), licensed marriage and family therapists (LMFTs), and licensed professional counselors (LPCs). Psychiatrists are distinct in that they must have earned a doctorate in medicine (i.e., MD or DO) and have the nearly exclusive privilege of prescribing pharmaceutical medications for the treatment of mental disorders. Clinical psychologists also must be educated at the doctoral level (i.e., PhD or PsyD) and maintain a licensure in order to practice, but they cannot prescribe medications in most states. LCSWs, LMFTs, and LPCs are educated at least at the master’s level by an institution accredited for their respective field, and must complete respective licensing requirements that include supervised clinical experience following degree completion.
While the educational experience and licensing protocol can easily be distinguished, the mental health professions also have evolved somewhat distinct professional identities in terms of their approaches to mental health treatment. While psychiatrists are trained in various psychotherapeutic modalities, trends indicate the majority of current and future psychiatrists plan to rely more heavily on pharmacological treatments than on talk therapies (Clemens, Plakun, Lazar, & Mellman, 2014; Zisook et al., 2011). As for clinical psychologists, a review of 50 years of literature surrounding this occupation revealed trends around specializing in one particular aspect of the field (i.e., psychotherapy, assessment, research) and one or two treatment modalities (e.g., psychodynamic therapy, cognitive-behavioral therapy), and a prevalence of cognitive therapies (Norcross & Karpiak, 2012). Generally speaking, LCSWs are likely to conduct therapy from a holistic approach that heavily considers the social impacts on a person while pursing social justice and equality agendas, such as helping underprivileged groups (Bradley, Maschi, O’Brien, Morgen, & Ward, 2012). While LMFTs are often exposed to or trained in a wide variety of therapeutic paradigms and techniques, they are likely to emphasize a collective rather than individual treatment approach, often marked by working with families and couples to identify and improve systemic or transactional issues between the members (Imber-Black, 2014). As LPCs’ professional identity continues to develop and stabilize (Mellin, Hunt, & Nichols, 2011; Reiner, Dobmeier, & Hernández, 2013), professional counselors train in a variety of treatment modalities and provide a variety of services in the mental health field, including “the diagnosis and treatment of mental and emotional disorders, including addictive disorders; psychoeducational techniques aimed at the prevention of such disorders; consultation to individuals, couples, families, groups, and organizations; and research into more effective therapeutic treatment modalities” (American Counseling Association, 2011, para. 4).
Although the average client may not know or fully understand the distinctions between mental health professionals, the literature suggests clients do exhibit some bias when selecting mental health professionals. Over the past 30 years, researchers have shown a consistent trend of professional titles or education levels impacting perceptions of mental health professionals. Warner and Bradley (1991) and Wollersheim and Walsh (1993) established that both perceptions of and confidence in mental health therapies were impacted by the title and education level of the mental health professional; generally, participants in these studies indicated a lack of confidence and knowledge about clinical psychologists and a preference for treatment from counselors. In a study examining public confidence in mental health professionals, Fall, Levitov, Jennings, and Eberts (2000) found significant differences in confidence based upon their title as well as their education level (i.e., master’s vs. doctoral level); participants mostly favored doctoral-level education and preferred counselors, except when presented with “serious psychiatric disorders” (p. 122). This study was repeated in 2005 with an African American sample that provided similar findings (Fall, Levitov, Anderson, & Clay, 2005). While specific attitudes and perceptions may have changed or evolved over the past three decades, these studies show that distinct perceptions or even biases toward professional titles do exist among civilian populations. This led the researchers to question if similar trends exist in military populations, which may be influencing the treatment-seeking decisions of service members.
To summarize, soldiers’ confidence in treatment for and trust in mental health professionals might be significantly impacting treatment-seeking decisions. In multiple studies, service members have repeatedly indicated relatively low levels of trust and confidence in mental health providers and treatments. Also, researchers have consistently shown that a professional title can impact patient or public perceptions with respect to general confidence in the professional’s abilities. To date, no known research is published on military members’ perceptions and levels of confidence or trust with differing mental health professionals. Thus, the purpose of this study was to explore soldiers’ relative levels of trust for and confidence in mental health professionals based solely upon their title and a presenting issue, in an effort to better understand what may be influencing treatment-seeking decisions among U.S. Army soldiers.
Method
The researchers for this study received approval from the Institutional Review Board of their university, and the survey was approved for distribution to active-duty soldiers by Army public affairs representatives. Sample size was determined by following similar confidence in mental health professional studies that used Friedman non-parametric tests (e.g., Fall et al., 2000; Fall et al., 2005). Participants were surveyed via the online metrics program Qualtrics, ensuring anonymity.
Participants
Active-duty soldiers serving in the U.S. Army were recruited using snowball sampling initiated by public affairs representatives at various Army installations. Each potential participant received a generalized email invitation that included an information sheet about the research and a link to complete an online survey. Participants were encouraged to forward the invitation to others who also met the inclusion criteria, which limited participation to those currently serving on active duty in the U.S. Army with more than 2 years of active-duty service or the National Guard/Army Reserve equivalent. Upon completion of the survey, participants were offered the opportunity to enroll in a raffle drawing to win one of two prizes: a $100 or a $50 gift card.
The sample included 32 active-duty soldiers, 26 males and six females, between the ages of 25 and 50 years (M = 33.3, SD = 7.0). Ethnic identities included 25 non-Hispanic Whites, two Hispanic or Latinos, one African American, one Filipino, one Native American, one White/Korean, and one White/Hispanic. Most of the participants (26) were married, while three were divorced and three had never married. Nearly two-thirds of the sample indicated current responsibility for children in their homes; there was an average of 1.85 children (SD = 1.5) reported by these 20 participants. Thirteen of the soldiers had seen at least one mental health professional (MHP) prior to completing the survey; respondents had seen all five MHPs included in this study. Participants were allowed to list multiple MHPs if applicable, and the MHPs were identified as follows: clinical psychologist, seven times; psychiatrist, five times; LPC, four times; LCSW, three times; LMFT, three times; and “other” or “unsure,”five times.
Regarding military experience, the sample included 18 officers, 11 non-commissioned officers, and three junior-enlisted (i.e., rank of E1–E4) soldiers. Twenty participants had a military occupational specialty (MOS) considered as Combat Arms in the U.S. Army. In the military, not all service members are equally likely to fight in combat; certain MOSs are combat-related while others are supportive in nature (e.g., administrative personnel, mechanics, logisticians). Of our 32 qualifying participants, we had a good mix of combat and non-combat MOSs. To the reader, this may seem to be either irrelevant or not particularly noteworthy information; however, this data can be quite important when forming conclusions about the study. On average, military service was 11.4 years (SD = 7.2), with 17 months (SD = 11.5) deployed to either Iraq or Afghanistan; only two participants had not been deployed to these countries. Seventy-five percent of the sample reported direct exposure to combat, and 59% reported having never seen an MHP for even one visit throughout their life.
Materials
Demographic questionnaire. In order to provide some description of the sample population, a demographics survey of 15 questions regarding age, sex, ethnicity, marital background, parental status, military rank, deployment and combat experience, and previous experience with mental health care providers was collected from participants. Most questions were multiple-choice but offered the options to not respond or provide a unique response if desired. The remaining questions were free-response.
Vignettes. Brief vignettes were used to depict the selected mental health diagnoses or mental health issues of eight fictional soldiers recently returning from a combat deployment. The vignettes were limited in length to approximately half of a standard printed page and were written with the goal of depicting diagnostic criteria in a manner that one might see them manifested by the soldier in the vignette. Authors specifically avoided using the exact clinical terms that an MHP may use while ensuring that enough diagnostic criteria were included to suggest the intended diagnoses may be warranted.
Each vignette was followed immediately by two questions. These questions asked the participant to rank the five MHPs in order according to the participant’s preference for (1) confidence in the MHPs in providing treatment for the soldier in the vignette, and (2) their own personal trust for the professionals if they were experiencing the symptoms described in the vignette. Because both questions were worded similarly, keywords such as trust and confident were bolded or underlined in order to highlight the intent of the question.
Development and validation of the vignettes.
The vignettes and questions were originally drafted by the lead researcher to explore how soldiers may rank MHPs under the two stated conditions (i.e., confidence and trust questions). The four mental health diagnoses selected were PTSD, anxiety disorders, depression, and substance use disorders, as these were identified by Seal, Bertenthal, Miner, Sen, and Marmar (2007) to be the most prevalent for soldiers returning from Iraq. The four common issues were suicide, marital problems, parenting difficulties, and sleep problems; these were selected from the Military Health System’s “After Deployment” (2015) website because they were depicted as common problems faced by soldiers and contributed to the breadth of issues explored in the study. Vignettes were modeled after previous studies using similar metrics to measure populations’ trust of MHPs (e.g., Fall et al., 2000; Fall et al., 2005).
After review and editing within the research team, faculty with extensive clinical and teaching expertise in the area of diagnosis reviewed the vignettes. Based on their recommendations, specific diagnostic labels, such as PTSD and depression, were removed in order to reduce the impact of these labels on participants’ responses, and the keywords trust and confidence were included and bolded in the survey questions. Their input also resulted in the refining of the vignettes to more accurately depict the intended issues based upon their clinical experience and expertise.
Procedures
From January to June of 2017, surveys were administered via Qualtrics software on an electronic device of the participant’s choosing. Respondents were requested to complete the surveys at a location and time presenting minimal distractions. After being provided information about the study and consenting to continue, participants were presented with the demographics survey followed by the vignettes. The survey would not advance to the next page unless a response was recorded to all questions on the previous page. Upon completion of the demographics portion, participants advanced to the vignettes depicting soldiers facing issues upon returning from a combat deployment.
During the vignette portion of the survey, respondents ranked the list of mental health practitioners for both the confidence and trust conditions; see the Appendix for the vignettes presented to participants. The survey would not allow duplicate ranks (i.e., MHPs could not “tie”) for either condition. The vignettes were randomized, with both the trust and confidence questions presented together on the same screen, and the listed order of the MHPs was randomized for each vignette as well.
Analysis
Data analysis focused on three main themes: the mean ranks for trust of the MHPs across the vignettes, the mean ranks for confidence in the MHPs across the vignettes, and potential correlation between trust and confidence. Consistent with the Fall et al. (2005) analysis, Friedman non-parametric tests and Wilcoxon matched-pairs tests were used to determine significant findings in the mean ranks for MHPs in each vignette with respect to both the confidence and trust conditions separately. These tests were completed 16 times—once for each of the eight vignettes for both the trust and confidence questions. Afterward, the data was aggregated separately for both the trust and confidence questions to allow an overall assessment of the mean ranks for each MHP without concern for the particular vignette presented. Both the Friedman and Wilcoxon tests were completed again on the aggregated data. Finally, a Goodman and Kruskall’s gamma test was used to determine the correlation between trust and confidence ranking for each MHP.
Results
For all eight vignettes, significant differences (n = 32, df = 4, p <= .002) were found for mean rankings in both confidence and trust conditions. Subsequently, Wilcoxon matched-pairs tests identified statistically significant differences within groups for each of the 16 conditions; see Table 1 for specific results. Figures 1 and 2 display inverted mean rankings for each MHP by vignette for the confidence and trust questions respectively; higher scores indicate a more favorable ranking.
In both the confidence and trust conditions, the data from each vignette allowed for the separation of the five MHPs into either two or three distinct groups in terms of their rankings. In some instances, some MHPs could be grouped with both the higher- and lower-ranking adjacent MHP; in this case, the MHP was placed in both groups. For example, in Table 1 under the Aggregate Rank column for the confidence condition, there was no significant difference between LPCs and psychiatrists (N = 256, p = .202), or LPCs and psychologists (N = 256, p = .336), but there was a significant difference between psychologists and psychiatrists (N = 256, p = .011).
Lastly, scores from all eight vignettes were aggregated for each MHP to allow an overall measure of the MHP’s ranking for both confidence and trust. Table 1 includes the associated statistically significant grouping, and Figure 3 depicts the aggregated inverted mean ranking for both conditions for each MHP. Using a Goodman and Kruskall’s gamma test on the aggregated data, a strong positive correlation was found between confidence and trust ratings for all five MHPs with G values ranging from 0.72 to 0.88 (N = 256, p < .0005).
Figure 1. Inverted Mean Ranks for Confidence Question Plotted by Type of Mental Health Professional and Vignette. Higher mean rank equates to higher confidence.
Figure 2. Inverted Mean Ranks for Trust Question Plotted by Type of Mental Health Professional and Vignette. Higher mean rank equates to higher trust.
Figure 3. Aggregated Inverted Mean Ranks for Mental Health Professionals for Confidence and Trust Questions. Higher mean rank equates to higher confidence or trust. Error bars indicate standard error based on standard deviation from the mean; they do not indicate statistical significance.
Discussion
This study was designed to explore active-duty Army soldiers’ perceptions toward various mental health care providers with respect to trust and confidence in the MHP. Overall, the sample population of soldiers appears to have the highest confidence and trust in clinical psychologists and LPCs, while LCSWs and LMFTs are significantly less preferred (as seen in Table 1). Psychiatrists seem to be somewhere between each of these two groups, as they appear in both the highest and second-highest preferred groups depending on the condition (i.e., confidence or trust). The statistically significant stratification into these groups suggests that the title of available MHPs may influence a soldier’s decision to seek services. Undoubtedly, other factors are involved, but the title, and perhaps the certifications of the available professional, is likely impacting treatment-seeking behaviors in military communities.
At the heart of this study is the notion that each of the MHPs included could treat any of the soldiers in the vignettes; however, the results suggest that soldiers would seek out different professionals based on the context of the presenting symptoms rather than the type or potential efficacy of the treatment to be received. For example, the marital problems vignette (see Appendix) could arguably have been treated more effectively by a psychiatrist than an LMFT; perhaps the declining relationship was itself a symptom of biochemical issues such as vitamin or neurotransmitter deficiencies, which may be more aptly treated with medicine. Or, it also is possible that an experienced LPC or LCSW could have effectively brought to the surface some other underlying issue in the course of individual therapy rather than the marriage, couple, and family-oriented approach taken by an LMFT. Similar arguments could be made for each of the other vignettes, but the results suggest that soldiers are likely making treatment decisions based upon professional title and presumably the associated reputation. If the Army’s goal is to boost rates of treatment-seeking behaviors, professional titles and perceptions of trust and confidence should not be ignored.
Results also show a strong correlation between trust and confidence across all of the vignettes. This can best be seen by comparing the LMFTs’ rankings for the marital problems and parenting issues vignettes with their consistently lower scores on the other vignettes. The jump in scores was consistent across both conditions, demonstrating that trust and confidence for MHPs are strongly linked. Although less likely, it also is possible that the respondents might have been biased or influenced to provide similar ranks for each professional across both conditions because the survey design allowed them to see their scores for the confidence question while completing the trust question. Regardless of whether trust influences confidence or vice versa, the two should be considered in the quest to boost treatment-seeking rates among soldiers.
Implications for Service Provision
With further validating and corroborating research, the Army may be able to improve treatment-seeking rates among those in need of mental health care by adjusting services based on the perceptions of soldiers. Although LPCs were consistently favored more than LCSWs, the Army currently allows LCSWs to serve as commissioned officers in behavioral health clinics providing individual therapy to soldiers, while the LPC license does not qualify an MHP to commission and serve as an officer (U.S. Department of the Army, 2007). This means soldiers have fewer chances of seeing an LPC without some type of insurance referral because the uniformed personnel initially available will not be LPCs. This study provides evidence that LPCs may be more appropriate and effective in this role by boosting treatment-seeking rates, so it could be beneficial to make treatment with LPCs more accessible to soldiers. Likewise, incorporating the services of LMFTs following deployments could help military families, as they had the highest average trust and confidence ratings of any professional in any vignette in the study when they were the preferred MHP. Perhaps they could advocate for temporary positions following deployments or increased advertisement of their services in military communities with units returning from overseas.
Limitations and Future Research
Future research is certainly needed to further confirm the results of this study. Investigators could explore what drives trust and confidence perceptions in military communities and how prior personal experiences influence the soldiers’ views of MHPs. Studies like this one could be conducted with other branches of the military and include National Guard and Reserve forces. Exploratory qualitative research could seek to identify specific factors that build trust and confidence in the mental health community as a whole. Future studies also should continue to update the disorders or issues selected to accurately represent the issues faced by targeted populations at the time.
Limitations to this study include the sample size, delivery of the survey, and lack of consideration for gender biases. While 32 respondents can provide initial insights, a much larger sample should be surveyed before any significant policy decisions are considered. The research team also recommends administering the surveys in person rather than online with the belief that many soldiers—and people in general—may not complete the digital surveys as earnestly as a paper version following a personal interaction with the research team or a recruiter. With regards to gender, it was not considered how the names of the soldiers in the vignettes may influence the respondents’ rankings; it is possible that the scores could have varied if the soldier in the vignette was of a specific gender.
Future researchers should be cautious to ensure that voluntary participation is not influenced by environmental pressures. In military communities, the researchers recommend seeking a sample population that includes personnel from multiple units, locations, and MOSs, as culture and attitudes can be vastly different among these variables.
Although this study has limitations, the researchers believe it highlights one of the key reasons that soldiers may not seek mental health services when in need: lack of trust and confidence in the resources available. Although the military has significantly addressed other identified issues, such as the associated stigma or impact to a service member’s career, treatment-seeking rates for those in need have changed very little, which indicates other issues are contributing to the decision not to visit with an MHP. The researchers hope the results of this study are built upon and examined for alternative approaches to boost treatment-seeking rates among the military.
Conflict of Interest and Funding Disclosure
The authors reported no conflict of interest
or funding contributions for the development
of this manuscript.
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Appendix
Vignettes Used to Depict Mental Health Diagnoses and Issues
Post-Traumatic Stress Disorder Vignette
Joe returned from deployment to Afghanistan 4 months ago. He was personally involved in combat with enemy insurgents on multiple occasions and was exposed to disfigured, dead bodies of both enemy combatants and fellow soldiers as well. He has often mentioned bad dreams about one of these times in particular and seems obviously distressed (e.g., fidgeting, faster breathing, and sometimes even sweating) whenever he speaks about it. However, when his fellow soldiers from the deployment bring up the event, he seems unwilling to participate in the conversation and has on a few occasions become angry about it. Based on these behaviors, you believe he may be struggling with traumatic experiences.
Anxiety Disorder Vignette
John returned from a combat deployment 9 months ago. Since returning, his family and coworkers have noticed changes in his behavior. He is often restless (or “on edge”), irritable, or physically tense in common, everyday situations. Plus, he has claimed poor or unsatisfying sleep for several months. These symptoms seem to be impairing his work performance and damaging personal relationships with loved ones. When asked, he hasn’t mentioned any particular traumatic events or worries that are bothering him. He simply seems much more anxious and it is affecting his well-being.
Depression Vignette
Jane returned from a combat deployment 3 months ago and has generally seemed a little bit down since coming home. Nearly every day over the past 2 weeks she has seemed to be sad or gloomy throughout the day and has shown very little interest in doing things she used to enjoy. She is clearly tired throughout the day and has mentioned feeling worthless to those around her. It seems like she is suffering greatly based on her unhappy and sad moods.
Substance Abuse Disorder Vignette
Jim returned from a combat deployment 12 months ago. Upon returning, he seemed to seamlessly reintegrate with his family, friends, and former social life. However, he soon began drinking alcohol more heavily than ever before, often binge drinking until passing out on weekdays and weekends. Although never caught in the act, he has even gone to work intoxicated and driven while drunk on multiple occasions. On two distinct occasions, he attempted to reduce his alcohol consumption but failed after only a week or two. Alcohol abuse is beginning to disrupt his work performance, family life, and physical well-being.
Sleep Problems Vignette
Joan returned from a combat deployment 4 months ago. She seems to have reintegrated very successfully into her family, social, and work environments. However, her sleep patterns have become very irregular and unsatisfactory. She rarely gets more than 4 hours of sleep consecutively and often uses her weekends to recover from a week of sleepless nights. Although her family and coworkers haven’t noticed anything wrong, Joan fears her sleep problems will soon begin disrupting her life.
Suicide Risk Vignette
James returned from a combat deployment 6 months ago. Since returning, he has outwardly seemed to have successfully reintegrated into his family, work, and social life. Although he appears to have been changed by his combat experiences, he does not seem to be generally troubled in any way (e.g., depressed, anxious, abusing drugs). However, he has jokingly mentioned “blowing his brains out” to colleagues at work and mentioned a specific plan to take his own life with his pistol. During a conversation with two friends, he has mentioned “ending it all” because he is feeling hopeless. You think James may be at risk for suicide.
Marital Problems Vignette
Jon returned from a combat deployment 5 months ago. He has rejoined his wife of 6 years, but their relationship has changed. While they used to feel very close and connected, they now both feel very distant. They do not enjoy activities together which they used to, such as hiking and dancing. They rarely hold good conversations with each other and are also less physically intimate. Jon and his wife both want their marriage to work but fear that they are nearing divorce. They are facing the most significant period of marital problems they have ever experienced.
Parenting Issues Vignette
Jerry returned from a combat deployment 10 months ago. He rejoined his wife of 16 years, their 13-year-old daughter, and their 5-year-old son. Since returning, Jerry has experienced some difficulty reassuming his role as a parent. His daughter seems to want very little to do with him. Although he thinks this is typical of a 13-year-old, it still causes him distress and he complains that he doesn’t feel like he has any influence in her life. With their son, Jerry often disagrees with his wife on discipline issues, and he can’t seem to find ways to connect with the 5-year-old. His son seems to have little interest in playing anything besides video games and always runs to his mother when Jerry attempts to discipline him. These parenting issues are significantly affecting Jerry’s mental and emotional well-being.
Anthony Hartman is a medical student at UT-Health San Antonio. Hope Schuermann is a clinical assistant professor at the University of Florida. Jovanna Kenney is a therapist at Genesis Psychiatric Center in San Antonio, TX. Correspondence can be addressed to Anthony Hartman, 7703 Floyd Curl Drive, San Antonio, TX 78229, hartmanaj@livemail.uthscsa.edu.
Sep 28, 2018 | Volume 8 - Issue 3
Jennifer L. Rogers, Dennis D. Gilbride, Brian J. Dew
This conceptual article provides a counselor-oriented overview of the origins and consequences of the current opioid epidemic in the United States. After a thorough review of Bronfenbrenner’s ecological perspective on human development, this article presents a case conceptualization model aimed at providing counselors with a tool and strategy to better understand how systemic complexities impact opioid-dependent clients and their communities. A detailed composite case study is used to demonstrate the influence of multiple ecological variables on a specific client. Individual, micro-, meso-, exo-, macro-, and chronosystem stimuli are explored, and the role of advocacy as inherent in systemic conceptualization and treatment planning is discussed.
Keywords: opioid epidemic, ecological, Bronfenbrenner, opioid-dependent, case conceptualization
Alarming national headlines related to opioid addiction highlight a public and mental health emergency across America. Overdoses and opioid-related deaths are skyrocketing (Rudd, Seth, David, & Scholl, 2016; Skolnick, 2018; Suzuki & El-Haddad, 2017), and the lifespan of many Americans, especially in rural areas, is declining for the first time in generations due in part to maladaptive use of narcotics (Katz, 2017a). Opioid painkillers are the most frequently prescribed class of drugs in the United States (Skolnick, 2018). Misuse of these drugs often leads to the use of heroin, a cheaper and more potent alternative to prescription painkillers (Skolnick, 2018). Heroin is increasingly cut with the synthetic opioid fentanyl (50–100 times stronger than morphine) and its various analogs, such as carfentanil (a veterinary drug used to rapidly immobilize wild animals; Suzuki & El-Haddad, 2017), contributing to the recent dramatic rise in overdose deaths (Katz, 2017b; Suzuki & El-Haddad, 2017). The opioid epidemic also is associated with increases in a host of other negative outcomes, including rates of HIV and hepatitis C, arrests and incarcerations, and neonatal abstinence syndrome (Skolnick, 2018).
Addictions, mental health, rehabilitation, and school counselors are challenged to find better ways to understand and assist users, families, and communities being ravaged by this public health crisis. Clinicians and researchers have developed multiple individual and community-based strategies to assist clients with substance abuse, but current circumstances have underscored the need for members of the counseling profession to take a more comprehensive and ecological approach to both understanding and addressing the needs of people struggling with opioid addiction (Dasgupta, Beletsky, & Ciccarone, 2018; Hewell, Vasquez, & Rivkin, 2017; Keyes, Cerdá, Brady, Havens, & Galea, 2014; Kolodny et al., 2015). In subsequent sections, details of this public and mental health crisis are described, and an ecological case conceptualization model that utilizes eco-mapping to assist counselors in better understanding and developing systemic treatment plans is presented. A case study allowing for the application of the model is provided, and implications for counselors are explored.
An Opioid Overview
Mental and public health officials have long recognized the popularity and uniquely addictive potential of substances classified as opioids. Use of opium and morphine first became a problem in America during the late 1800s (Kolodny et al., 2015). Morphine was used to treat a variety of chronic and acute ailments, including diarrhea and injuries sustained in battle. Smoking opium recreationally became popular in some circles, and physicians also inadvertently addicted their patients by prescribing opioid treatments. As medicine and public health advanced, more diseases could be avoided, cured, or treated without the use of highly addictive opioids, and their use fell out of favor by 1919 (Kolodny et al., 2015). In the second half of the 20th century, heroin addiction intermittently rose to epidemic levels among disadvantaged urban populations, especially in the large cities of the northeast and west coast of the United States (Kolodny et al., 2015; McCoy, McGuire, Curtis, & Spunt, 2005). More recently, the introduction of synthetic prescription opiates (e.g., Vicodin, Percocet) in the 1980s and the approval of sustained-release oxycodone (brand name OxyContin) in 1996 brought pain relief to millions of users, but has contributed to high levels of abuse and dependence nationwide (Van Zee, 2009).
Opioid Effects
To understand the addictive nature of opioids, counselors must account for the acute effects of their use (e.g., relief from physical and psychological pain), unique side effects (e.g., opioid-induced pain sensitivity, painful withdrawal symptoms), ease and speed with which tolerance is established, and potential resulting impairments in daily functioning (Kosten & George, 2002). When opiates bind with neural opioid receptors in the brain, spinal cord, gastrointestinal tract, and other organs, they inhibit the release of pain signals, blocking the user from experiencing both physical and emotional suffering. Some people are naturally more vulnerable to developing opioid tolerance (taking more drug for the same effect) and dependence (drug required to avoid withdrawal; Kosten & George, 2002). Susceptibility is influenced by a variety of biopsychosocial factors (e.g., brain structures, cellular differences, context of use, stress). In a study examining opioid prescribing patterns, 25% of patients who had a new opioid prescription progressed to receiving additional prescriptions episodically or chronically (Hooten, St. Sauver, McGree, Jacobson, & Warner, 2015). Nicotine addiction, overall poor health, psychiatric diagnosis, and history of substance abuse were found to increase the likelihood of ongoing opioid use. Withdrawal symptoms lasting three to five days—including nausea, muscle cramping, body aches, anxiety, and inability to sleep—can compel users to obtain immediate symptom relief via the use of additional opioids (Kosten & George, 2002). In an attempt to avoid debilitating withdrawal symptoms, users become reliant on the drug to function at a normative, baseline state.
Current Opioid Epidemic
Although the pathway to opioid abuse and addiction is not new, a culmination of ecological factors over the last 20 years has led to what is now commonly referred to as a national epidemic (Kolodny et al., 2015; Skolnick, 2018). These factors include changes in prescribing patterns, increased supply, rampant growth of illicit use, the progression to intravenous heroin use among chronic users, and the lethal contamination of heroin and fake prescription pills with highly potent synthetic opioids like fentanyl, as well as broader systemic variables such as poverty and access to health care (Dasgupta et al., 2018).
The dramatic increase in the availability of prescription opioids in the early 21st century stemmed, in part, from changes in medical attitudes and policies (Kolodny et al., 2015; Skolnick, 2018). Spearheaded by the American Pain Society’s advocacy efforts to have pain recognized as a fifth vital sign (along with temperature, pulse, respiration rate, and blood pressure) in the mid-1990s, the Joint Commission and the Veterans Health Administration formally endorsed patients’ rights to pain assessment management in 2000 (Kolodny et al., 2015; Skolnick, 2018). Helping patients avoid physical pain thus became a primary focus of medical care. During the same time period, Purdue Pharma provided financial contributions to multiple medical and patient organizations (e.g., the American Pain Society, the Joint Commission, the Federation of State Medical Boards) and lobbied to allay concerns regarding long-term use of prescription opioids in the treatment of chronic non-cancer pain (Kolodny et al., 2015). Methodologically questionable research studies were widely cited to minimize the perceived risks associated with long-term use and addiction. Sales of Purdue Pharma’s doggedly promoted, non-generic OxyContin grew from $48 million in sales in 1996 (316,000 prescriptions) to almost $3 billion (more than 14 million prescriptions) in 2001–2002 (Van Zee, 2009). Though the time-release formula was touted as a deterrent for misuse, users discovered the pills could be crushed and then snorted or injected. In 2000, Purdue released a 160 milligram tablet (up from the previous high dose of 80 milligrams) approved for use by patients who had developed opioid tolerance, further increasing OxyContin’s draw as a drug of abuse (Van Zee, 2009).
An increase in opioid supply via both unwitting and unscrupulous prescribers was quickly followed by the rapid acceleration of opiate abuse across the country (Van Zee, 2009). Unlike other illicit substances (e.g., cocaine, methamphetamine, ecstasy), these pain-killing medications were prescribed by medical professionals and therefore assumed to be safe. Prescription opiates were accessible through doctors, family, friends, the internet, and on the black market. Long-term use of prescription opiates can lead to tolerance and eventual physical dependence, requiring a continuous supply of drugs and financial resources to purchase them. Users of prescription opiates have increasingly turned to heroin (Skolnick, 2018) as a cheaper, more readily available option to keep painful withdrawal symptoms at bay. With increased availability and visibility, many people now report that their opioid use started with heroin rather than prescription drugs (Dasgupta et al., 2018).
The rise of the presence of illegally manufactured fentanyl in opioids available on the illicit market has had increasingly deadly consequences, with fentanyl-related deaths in the United States up 540% between 2013 and 2016 (Katz, 2017b). Average life expectancy is now declining among some segments of the population—unusual except in times of war (Dasgupta et al., 2018). Unlike other U.S. drug use crises that have disproportionately affected minority populations (e.g., crack cocaine), there has been a focus in this crisis on over-prescribing as the root cause, rather than the moral failings of individual users. This broader view may help destigmatize the current situation, but it is imperative to recognize that complex factors lead to susceptibility to all such crises. For instance, in areas particularly affected by the opioid crisis, mortality associated with alcoholism, drug overdoses, and suicide (known as “diseases of despair”) has increased as local economies have declined (Dasgupta et al., 2018).
The devastation of individual lives, families, and communities resulting from this epidemic is clear, and the complexity of the issues it has engendered requires counselors to expand treatment strategies and interventions. In the next section, we review Bronfenbrenner’s (1979, 1994) ecological systems theory and present a strategy designed to help counselors both understand and intervene with clients and communities battling this challenge.
Ecological Perspective
Bronfenbrenner’s foundational work, The Ecology of Human Development (1979), described how a child develops within a series of interrelated systems. He posited that human development processes are influenced by individual characteristics, as well as features in one’s immediate and more distant environments. Over the course of a lifetime, development progresses through a series of increasingly complex and reciprocal interactions between an individual and the people, things, and symbols in their environment. Research designed to investigate this developmental progression is described as aligning with a process-person-context model (Bronfenbrenner, 1994) and is endemic in our current understanding of psychological health and illness.
Drawing upon Lewin’s (1935) theory of psychological fields (as cited in Bronfenbrenner, 1979), the ecology of a developing person is described as a set of nested structures, one inside the other (see Figure 1). The innermost system, called the microsystem, was defined by Bronfenbrenner as the pattern of personal interactions and activities that occur face-to-face with a person in their immediate environment (Bronfenbrenner, 1979, 1994). These interactions include an individual’s family, friends, schoolmates, teachers, neighbors, and colleagues. The proximal processes occurring between family members in the microsystem are among the most frequently studied in the psychological literature (Bronfenbrenner, 1994). These close relationships have extraordinary power to normalize or stigmatize behaviors and to support or hinder optimal individual development. Examples of behaviors that may be supported or discouraged within a microsystem include child-rearing practices, therapeutic or recreational use of prescription medication, pursuit of educational or occupational goals, religious practices, and encouragement of relationships with persons or groups outside the immediate microsystem.
Figure 1. Bronfenbrenner’s Ecological Model
The mesosystem includes the processes and connections occurring between two or more environments in which an individual exists, or the system of microsystems in a person’s life (Bronfenbrenner, 1979, 1994). Interactions between a person’s home, school, workplace, neighborhood, place of worship, or medical providers are described as occurring within the mesosystem. Examples of mesosystem processes include how the closing of a manufacturing plant where an individual was employed could lead to a decline in the condition of his or her neighborhood, or how patients of a local physician who frequently prescribes pain medication may experience an increase in the off-market availability of such medication within his or her neighborhood, family, or peer group.
The exosystem is comprised of processes occurring between two or more environments, at least one of which does not include the individual of interest (Bronfenbrenner, 1979, 1994). Even though a person may not exist within a certain setting, outside events can indirectly influence that person’s immediate environment. Examples of exosystem processes include how a new local company’s practice of only hiring college-educated workers influences less educated workers in a nearby neighborhood, or how decisions by legislators regarding health care policy influence local hospitals and family decisions about medical care.
The macrosystem represents the patterns, policies, laws, values, and trends that comprise the broad cultural, political, economic, and societal/environmental backdrop of an individual’s life (Bronfenbrenner, 1979, 1994). Macrosystems include mega factors such as advances in technology and the rapid transition into the information age, the precipitous move away from manufacturing in the United States, the increasing need for a college education to obtain a salary that can sustain a middle-class lifestyle, changes in how health care is funded and delivered, the decline in membership in organized religious institutions, and a growing cultural emphasis on individualism. Other trends include changes in how information is delivered and consumed, and the increasing gulf between rural and urban communities.
The chronosystem describes changes in an environment over time related to each of the other systems (Bronfenbrenner, 1994)—the normal growth and development of a person or family, the effect of a move or migrations of families or groups, and the effects of large historic events such as wars, natural disasters, and recessions. The chronosystem highlights that along with living within nested or interacting systems, a person also lives within the history of their own life—as well as within the history of their family, community, state, nation, and world (Bronfenbrenner, 1994).
Ungar, Ghazinour, and Richter (2013) expanded Bronfenbrenner’s model in their studies of resilience to include a focus on the success of individuals and groups to secure resources leading to healthy development, even in adverse circumstances. Ungar and colleagues’ model describes systems as reciprocal rather than hierarchical. The effect of a systemic variable is not just related to its proximity to an individual (per Bronfenbrenner’s nested model as described above and in Figure 1), but rather on its importance to a particular person at a specific point in time. For example, a war and its related geo-politics (a macrosystem issue) may be much more salient than school (a mesosystem issue) for a particular child living under siege in Syria.
An Ecological Conceptualization of Opioid Addiction
A social-ecological perspective is tacit in many popular journalistic efforts focused upon the opioid use epidemic, including books (e.g., Hillbilly Elegy; Vance, 2016), documentaries (e.g., Warning: This Drug May Kill You; Peltz, 2017), and investigative news reports (e.g., Talbot, 2017). In these long-form examinations, a multitude of distal and proximal variables influencing opioid use patterns among individuals are described. Recent scholarly publications outside of the counseling literature have utilized implied (Dasgupta et al., 2018; Kolodny et al., 2015) and overt ecological (Hewell et al., 2017; Keyes et al., 2014) lenses to examine this problem. Keyes and colleagues (2014) undertook a large ecological synthesis of the extant empirical literature related to the opioid crisis in rural America. They identified the following risks in their analyses: (1) increased availability and access; (2) lower perceptions of harm; (3) self-medicating for pain; (4) more increased availability in rural rather than urban areas; (5) out-migration of young people (rural economic declines, and via selection effect, young adults remaining in economically depressed areas may have a greater number of risk factors); (6) differences between urban and rural social and kinship networks (importance of community investment, family ties, work over education, and local social capital in rural areas); and (7) structural stressors of modern rural living (unemployment and economic deprivation).
In their qualitative inquiry about systemic and individual factors in medication-assisted treatment for opioid abuse, Hewell and colleagues (2017) reported findings supporting the construct of recovery capital (including personal recovery capital, family and social recovery capital, and community recovery capital), as well as suggesting the interactional relationship of such resources. They advised practitioners to be educated about multiple ecological influences and to be flexible in their approaches so as to utilize ever-changing sources of recovery capital available to their clients.
Ecological Conceptualization and Treatment Planning
The proposed counseling, teaching, and intervention strategies are an extension and elaboration of the eco-webbing model proposed by Williams, McMahon, and Goodman (2015). The authors described a strategy designed to facilitate more critical consciousness thinking in their students by creating visual representations of the factors and forces that may be affecting a client’s life and situation. Concept mapping strategies have been found to be powerful tools in creating visual representations of key factors affecting a client’s health and treatment needs (Gul & Boman, 2006) and in enhancing critical thinking.
In Phase 1 of Williams and colleagues’ (2015) model, they ask counseling students to brainstorm all the variables related to a client’s problem. In the present model, we expand and structure this phase to include a systematic analysis of each of the system levels identified by Bronfenbrenner (1979, 1994) in order to create an eco-map. Phase 2 of the Williams’ et al. model (2015) involves the distillation of information and themes. We address this phase by utilizing Ungar et al.’s (2013) concept of differential impact. Ungar and colleagues assert that although Bronfenbrenner’s systemic levels are often visually represented as nested and hierarchal (i.e., levels closer to the center where the individual is more important), this structuring is merely a heuristic device, and that it is more useful to understand various systems and subsystems as reciprocal, having differential impacts at various moments and in various contexts. In the present model, we address Phase 2 by visually prioritizing different systemic issues and factors. As indicated in Figure 2, key factors from each of Bronfenbrenner’s systemic levels are illustrated by circles in the eco-map rather than in the traditionally nested manner. Based upon the client and counselor’s joint evaluation, many variables are included in the eco-map, with their current importance to the client represented by both relative size and distance from the center of the map.
The final phase of the eco-webbing process, as described by Williams and colleagues (2015), calls for reflection upon the central issue and the multiple eco-systemic factors, and how these may inform the counseling process. Reflection upon the eco-webbing process itself is also encouraged. Our model expands upon these steps by using the information visually represented in the eco-map to structure and develop a formal treatment plan including both individual and systemic variables in the order and priority of their current effect on the client. Over the course of counseling, the eco-map can be revisited and restructured to represent the shifting centrality of various factors. For example, in an initial eco-map, access to a detox treatment center may be largest and at the center, while 6 months later, labor market or family relationship issues may enlarge and move toward the center.
Figure 2. Eco-map for Jason
In the following sections, we present a client case study, suggest an ecological approach to understanding our client, and offer treatment strategies based upon our ecological conceptualization.
Case Study: Jason
Jason is a 37-year-old White male who lives in a southwest West Virginia town with a population of 30,000. Jason’s father and grandfather were both coal miners who worked hard, made a good living, and were active in the local community as church members and volunteer firemen. Jason had a happy childhood with no remarkable adverse events. He was a star of the high school football team. Having seen his grandfather die from black lung disease and his father suffer from emphysema, Jason vowed to never work in the mines. By the time he graduated high school, there were few mining jobs available. Jason began work for a concrete company, pouring concrete for residential and commercial projects. He was popular among his coworkers and relished working outdoors. At age 21 he married a young woman he had known since childhood and within 3 years they had two sons.
After 10 years on the job, Jason was laid off because of the lack of new development in his town. Jason moved his young family to a larger town in Ohio to do concrete work for a commercial construction company. The working environment was very different, and Jason was required to take orders from contractors, rather than being in charge of each job as he had become accustomed to back home. Jason’s wife was very unhappy living away from their friends and family. After a few months, she and the children moved back to live with her parents. Jason visited on the weekends, but the arrangement strained their marriage, and within 2 years his wife filed for divorce. Around the same time, his father died from lung cancer.
Jason had a number of back injuries over the years while working, but when he fell at home while moving a piece of heavy furniture, he herniated three discs and was restricted from many physical activities because of continuous pain. Because this debilitating injury occurred at home, Jason did not qualify for worker’s compensation benefits. He had surgery on his back and returned home with a prescription for narcotic pain medication. He did not comply with his doctor’s orders regarding physical therapy because as an hourly laborer, he could not afford any more time off work. Though the surgery did alleviate some of his pain initially, after a year it was clear that the operation did not fully repair his spine, and his pain again became unbearable. His doctor prescribed Percocet for him to take in the evenings when his pain was the worst, but over time, the medication became less effective. He visited a pain clinic near his apartment and received a prescription for OxyContin, which was stronger and long-acting. Jason noticed he felt less lonely and discouraged after taking the pills, which he began to do more often. Soon, Jason was not himself at work—making mistakes, forgetting things, and having conflicts with his supervisors. He was fired from his job.
With no savings, outstanding medical bills, and being unable to work in his field, Jason returned home to live in a small house on his mother’s property. He applied for disability benefits and began receiving prescription opioids through a pain clinic in town. As his tolerance for opioids increased, he tried various strategies to avoid the horrific withdrawal symptoms he experienced when his supply of opiates ran out: crushing and snorting pills for a stronger effect, “borrowing” medication from family and friends, and buying additional pills from dealers. Nine months ago, the high street cost of pills led Jason to begin snorting heroin, which was cheaper, but more potent. Within 2 months, he began using heroin intravenously on a daily basis. Acquiring and using heroin became his primary endeavor, increasingly isolating him from his family and his group of lifelong friends. After showing up to church several times late and disheveled, Jason’s mother told him he was no longer welcome to join her in the family’s regular pew on Sundays. Last Friday, he met his ex-wife and younger son to attend his elder son’s first varsity football game as a family. In an effort to avoid becoming ill during the long game, Jason shot heroin in the parking lot and was visibly high when he entered the stadium. The evening ended with his ex-wife enraged, his younger son in tears, and his elder son saying he could not wait to go far away to college and never see Jason again. Two days ago, Jason’s mother found him unresponsive in his truck and called 911. EMTs administered naloxone (branded as Narcan), which restored his breathing after an accidental heroin/fentanyl overdose. He was taken to the hospital and referred to an outpatient community addiction and mental health clinic upon release. With no one in his family willing to pick him up from the hospital, and his mother saying she is unsure if she wants him to continue living on her property, Jason used a hospital bus pass to travel directly to a local substance abuse treatment facility.
Treatment Planning Implications by Ecological Level: The Case of Jason
Individual: Traditional treatment focus. Assuming a disease model of addiction, a counselor would view Jason’s opioid dependence as primary, chronic, progressive, and potentially fatal (Angres & Bettinardi-Angres, 2008). As such, many substance abuse professionals would advocate that Jason’s addiction is the primary presenting problem and must be addressed first, before tackling other concerns and challenges. A treatment plan including goals and objectives focused upon enhancing his ability to remain abstinent from opioids and all other mood-altering substances should be developed, implemented, and monitored from the outset of treatment.
It is essential for Jason to reduce his isolation by developing a social network supportive of his recovery efforts. Specific objectives to meet this goal might include attending daily 12-step meetings for a minimum of 90 days, obtaining a sponsor who has a minimum of 5 years in recovery, and reestablishing relationships with non-using childhood friends.
An additional individual-level concern that must be addressed is Jason’s chronic pain from multiple herniated disks. During the first week of substance abuse treatment, Jason’s plan should include a complete physical examination with an emphasis on assessing pain level and spinal functioning, as well as HIV and hepatitis screening. Throughout his substance abuse treatment, Jason should receive psychoeducation via group work, lectures, reading materials, and videos or other media in order to enhance his understanding of the cyclic nature of pain disorders and opioid addiction. Jason also should make an appointment and establish a relationship with a medical specialist who is knowledgeable in both pain management and addictive disorders. Jason and this medical professional can develop an action plan to address his chronic back pain while minimizing his risk of opiate relapse.
Acute fiscal concerns and the accompanying stress associated with lack of financial resources were identified as primary risk factors for relapse. Individual-level interventions should include connecting Jason with vocational rehabilitation counselors who will assist him in identifying personal and employment strengths, acknowledging limitations in the current job market, and assisting him in finding employment. Finally, in order to enhance the likelihood of success in his recovery, Jason should address issues of shame resulting from his drug use and loss of family, employment, health, and identity. While in treatment, he should receive extensive psychoeducation as to the meaning and significance of shame in the recovery process. Jason should be encouraged to discuss, in individual and group counseling, the complex nature of his drug use and related intra- and interpersonal consequences.
Microsystem: Face-to-face interactions between individual and environment. Primary face- to-face interactions impacted by Jason’s addiction to opiates include communications with his ex-wife, sons, and mother. Although Jason’s marriage was negatively impacted by the family’s moving to Ohio, his use of prescription opioids following the move hurt his ability to communicate, restricted his interactions with his wife and children through gradual withdrawal from family events, and transferred parenting responsibilities to his wife. These changes in functioning within his nuclear family caused further alienation from others, including but not limited to his mother, friends, neighbors, fellow church members, and extended family. As a result of his opiate use, he no longer attended parent–teacher conferences at school and only sporadically appeared at his children’s baseball and football games.
Having grown up in a small town, Jason was well known and well liked by many in his community. While working at the local concrete company in his home town, he had developed a tight-knit group of close friends, many of whom he knew from childhood. Upon his return to West Virginia following his loss of employment and injury while in Ohio, Jason no longer reached out to this group of friends. Instead, his primary focus became finding, paying for, and using opioids in order to avoid painful withdrawal symptoms. His social circle was nearly replaced by his drug dealer and occasional fellow heroin users with whom he would shoot up and share needles.
It should be noted that all of the individual-level treatment concerns involve microsystem-level interactions between Jason and his environment. Jason’s counselor should be aware that achieving these goals will depend upon Jason’s pursuit or avoidance of interactions with various individuals, groups, and settings (i.e., the microsystem). This ecological awareness will increase the counselor’s understanding of the magnitude of Jason’s task, allowing for both deeper empathy and better planning. By highlighting the microsystem interactions required to pursue treatment goals, the counselor can help Jason become aware of the many variables in the environment he may not be able to control, thus emphasizing the importance of remaining steadfast regarding those elements of his treatment and life in which he does have power and choice.
Mesosystem: Interactions between two or more environments where an individual exists. In Jason’s West Virginia and Ohio communities, there were several changes in economic and medical systems that impacted his use of opiates. The shutting down of coal mines and businesses associated with the coal industry (housing, rail transportation, and facility maintenance provision) made a significant economic impact on communities and extended to multiple industries outside of mining. New houses were not being constructed, and local small businesses began to struggle and disappear. As a result, the need for concrete diminished and Jason’s boss was forced to lay off workers. Families like Jason’s were faced with a difficult choice: remain in a community in which they and multiple generations before them had lived and hope jobs would one day return or uproot their families in search of employment opportunities elsewhere. Many families chose the latter—which left the small town void of human resources and an adequate tax base from which to provide municipal and human services.
Jason’s long-term treatment provider should take into account employment opportunities within the community and assess if Jason has adequate training for today’s workforce. Vocational rehabilitation counseling is recommended to assess his skills and to determine if further education is needed. All of the local helping service providers (e.g., medical, addictions, mental health, vocational, and school professionals) in Jason’s town are overwhelmed because of high needs and dwindling financial resources. As such, Jason’s counselor must be aware of mesosystem-level obstacles; these interactions between microsystems may be fraught because of the challenges being experienced in each system. For example, the process of one facility making a referral to another can be difficult because of high demand and a lack of resources in either system. For clients like Jason, already struggling with shame and disenfranchisement, a mesosystem-level challenge might be taken personally and be potentially triggering. A counselor working with Jason through an ecological lens could engage with him regarding such an obstacle, and draw parallels to other system-to-system interactions that have affected him (e.g., how decline of coal is impacting other economic opportunities in his town; how the influx of cheap heroin is impacting hospitals, treatment centers, and neighborhoods). As mentioned above, increasing a client’s awareness as a person in a system may help create more accurate assessments of the forces at play within the respective environments.
Exosystem: Interactions between two or more environments, at least one of which does not include the individual. In addition to the economic shifts noted in the previous section, important changes in the way pharmaceutical companies marketed prescription opioids to both consumers and medical providers impacted the availability of these narcotics in the communities where Jason lived. Jason was told by physicians that the drugs he was prescribed carried a very low risk of addiction and was given documentation supporting the effective and safe use of Oxycontin as a treatment for pain (Van Zee, 2009). Jason was not aware that his physician had attended an all-expenses-paid pain management conference at a Florida resort, hosted by Purdue Pharma, or that his doctor had been invited to become a speaker for the company. He also was not aware that his physician was being tracked by Purdue as a frequent prescriber of OxyContin and thus receiving increased attention and gifts from their regional sales representative, who was eagerly pursuing an annual sales bonus that could more than double her salary.
These distal variables had a profound effect on Jason as an individual, along with many other examples in the mesosystem: his Ohio boss’s enforcement of company policies regarding drug use and addiction; health care policies about prescription opiates, addictions treatment (including medication-assisted therapies), and insurance for people with pre-existing conditions; drug traffickers contaminating heroin with fentanyl and pushing an influx of heroin into Jason’s vulnerable community; and state and local policy regarding the availability and administration of naloxone—which likely saved Jason’s life. If Jason’s counselor views Jason and the helping process through an ecological lens including such variables, both counselor and client will be better prepared to co-construct a treatment narrative around the past, present, and future that draws upon Jason’s strengths and recognizes his limitations within the realities of a complex system.
Macrosystem: Cultural, political, economic, societal backdrop. Jason’s current circumstances have unfolded against a multifaceted socio-political backdrop, influencing many clinically salient factors in his treatment. The economic decline of his hometown is not isolated, but rather part of global trends related to the urbanization of wealth and resources. There has been a marked decline in well-paying blue-collar jobs with benefits, overall economic dislocation due to automation, and an increasing need for advanced education in order to be competitive for open positions. Technology has increased the breadth and depth of information available to the average American, and those who cannot afford access to technology fall further and further behind. With access to information about opportunities available elsewhere, young adults from small rural communities increasingly leave areas their families may have resided in for multiple generations. Religious authority and institutions have declined, and the purpose and services churches traditionally provided in rural areas have also eroded. State- and federal-level health care policy, pharmaceutical industry regulations, scientific progress in the fields of pain management and addiction, and changing norms in our cultural understanding of addiction, treatment, and outcomes are all at play in the macrosystem.
As part of Jason’s long-term treatment, psychoeducation and client-centered processing regarding these and other macrosystem variables can support multiple treatment goals, particularly those related to issues of shame. Placed within a broad ecological context, Jason’s feelings of anger and shame can be normalized while facilitating a shift from a personalized focus (e.g., “I am bad,”) to a broader perspective (e.g., “These are difficult times, and new skills I never had the chance to learn before are needed for survival”).
Chronosystem: Historical context and changes in environments over time. In developing a comprehensive treatment plan, along with the systems already outlined, the ecologically sensitive counselor should help Jason plan for challenges that are likely to occur over time as a result of his developmental process, along with the historical moment in which Jason lives. He is 37 years old and still in the first half of his working life. He has adolescent children who will be growing into young adulthood; they may look toward him for guidance or choose to challenge and reject him. This moment in time is a developmentally critical one for Jason’s family.
At the time of writing this article, the United States is in the midst of a number of policy debates that will have an enormous effect on Jason’s life and health (Kessler, 2018). Long-term funding and access to health care is a contentious and unsettled issue. Ecologically aware counselors should both monitor and engage in the unfolding policy debates related to the funding of substance abuse treatment and other ongoing services Jason and clients like him need now and in the future. Furthermore, economic trends toward clean energy, globalization, technology, urbanization, and higher education continue to accelerate; the world is already a different place than when Jason first started working, or when he first started using drugs as a means to cope with pain. Jason and those seeking to help him must have accurate, up-to-date knowledge of how industry trends are impacting local and regional sectors, and devise strategies to engage and compete in the current economic environment.
Although vital, it is not enough for Jason’s counselor to help him survive only in the present moment. The counselor should anticipate future challenges Jason will confront and assist him in mapping out a sustainable, long-term plan. Such a plan will normalize the influence of both individual- and systems-level variables, emphasizing the importance of multiple sources of support, maintenance of his sobriety, and the inevitability of confronting both developmental and historical challenges. Just as a person with progressive multiple sclerosis needs to anticipate their future medical and assistive technology needs, so does Jason need to identify and plan for his future health, wellness, and economic needs within our rapidly changing society. An ecologically sensitive counselor understands both Jason’s personal development and larger historical trends, and is thus able to advocate for Jason’s preparation to survive and thrive over time.
Advocacy as an Inherent Element of Ecologically Informed Treatment
Over the past few decades, the counseling profession has increasingly recognized that advocacy is a vital component of the counselor’s role (Chang, Barrio Minton, Dixon, Myers, & Sweeney, 2012; Ratts, Toporek, & Lewis, 2010). Counselors are ethically required to understand their clients in a deeply contextualized manner and have a responsibility to try and reduce social and ecological barriers that may be blocking their clients’ growth, development, and flourishing, and exacerbating their clients’ mental and physical health challenges. Understanding the pivotal role ecological factors play in clients’ health, relationships, and careers has long been central to the field of rehabilitation counseling (Parker & Patterson, 2012). Issues such as accessibility and universal design were recognized as central to the success of people with disabilities, just like evidence-based treatments. For example, if a client who uses a wheelchair is seeking to participate in a program or obtain a job requiring access to a particular building, and that building lacks accessible parking or public transportation, curb cuts, and an accessible entrance and bathroom, the client is likely going to be blocked from reaching goals. Such systemic, advocacy-oriented thinking can be applied to the current opioid crisis.
As described in the previous sections, using Bronfenbrenner’s ecological model and creating an eco-map as a tool in the client conceptualization process led to the identification of a wide range of variables related to Jason’s treatment and recovery. Counselors need both awareness of and knowledge about factors affecting their clients at multiple systemic levels. Advocacy as understood within this model includes understanding labor market trends and participating in public policy discussions concerning support for workers displaced by globalization and automation. It means working to obtain more medical resources and treatment centers for clients struggling with addiction, striving to change laws to emphasize treatment over incarceration, and providing more access to life-saving medications such as naloxone. In short, the pursuit of social justice and counselors’ roles as advocates are intrinsic in this model of conceptualization and intervention, highlighting the clinical and societal relevance of a broad range of systemic variables and public policy debates.
One area in which counselors can advocate for the improved access to services for those struggling with opioid use is through supporting programs, such as the Mental Health Facilitator program (Hinkle, 2014), aimed at training laypersons with the basic skills to identify, briefly intervene with, and refer people in their communities who are experiencing a mental health crisis. The increased presence of persons with such skills in the microsystem—in schools, hospitals, faith communities, businesses, and neighborhoods—creates opportunities for detection, referrals to treatment, and life-saving emergency interventions, particularly among underserved populations. Mental Health First Aid is an international, evidence-based, 8-hour training course that teaches community members steps they can take if they encounter a person who is having an emergency, such as having suicidal ideation, a panic attack, or an overdose. Mental Health First Aid has recently added opioid-specific overdose training and naloxone administration to their curriculum (Pellitt, 2018).
Conclusion
Ecological thinking is a powerful skill, and one we argue is necessary for clinically competent counseling. The ecological conceptualization and treatment planning process outlined in this article is designed to provide a structured and systematic template for helping counselors identify clients’ complex needs, as well as the many influential variables at play in the past, present, and future. Engaging from an ecological perspective requires counselors to understand their clients as embedded in multiple systems. Further, it calls upon counselors to develop a deep understanding of the social, economic, and political contexts in which their clients live, and to develop systemic intervention skills. Utilizing this model in clinical settings could enrich the lives of clients, who may come to embrace a more nuanced and inclusive way of conceptualizing themselves and their environment.
Counselors-as-advocates are inherent in this model, and those professionals who espouse ecological thinking cannot ignore the multitude of powerful forces that either enhance or impede our clients’ well-being. Clinicians who understand and engage with their clients through this lens may find that ecological psychoeducation can lead to clients-as-advocates as well. Clients who come to understand themselves and others as people in environments may find their individual-level goals are supported and enhanced by goals associated with learning about and eventually acting upon systems-level variables in their lives, thus increasing the recovery capital (Hewell et al., 2017) available to them within their own environments. Attention to the American opioid epidemic is increasing based on advocacy by citizens, journalists, public servants, and health professionals. As focus and resources are directed to this complex problem, ecologically informed interventions by stakeholders in all of the interconnected systems are advised to both save and improve lives now and in the future.
Conflict of Interest and Funding Disclosure
The authors reported no conflict of interest
or funding contributions for the development
of this manuscript.
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Sep 28, 2018 | Volume 8 - Issue 3
M. Ann Shillingford, Seungbin Oh, Amanda DiLorenzo
Natural disasters over the past few decades have necessitated mass migration of Haitian immigrants to the United States. Haitians residing in the United States have experienced significant cultural and social challenges. Recent political deportation mandates have increased the systemic challenges that Haitian students and their families are currently facing in the United States. These systemic barriers have fostered an increase in stressors affecting the mental wellness of Haitian students and their families. This article introduces school counselors to the culturally focused, multiphase model of psychotherapy, counseling, human rights, and social justice as a framework to assist Haitian students and their families.
Keywords: Haiti, immigrant, school counseling, human rights, social justice
There has been a growing trend in the counseling profession to provide culturally relevant services to all clients. In fact, most recently, Ratts, Singh, Nassar-McMillan, Butler, and McCullough (2016) proposed the Multicultural and Social Justice Counseling Competencies to support the evolving need for multiculturally competent counselors to support today’s diverse populations and their varying mental health needs. One diverse group that has caught the attention of counseling professionals is the Haitian population. A long history of political unrest, coupled with grievous damage from natural disasters over the past few decades, has snowballed the migration of Haitian families into the United States. With mass migrations come challenges with cultural identity, social and academic obstacles, and psychological impairment. This article highlights the role of school counselors as social justice advocates and introduces the multiphase model of psychotherapy, school counseling, human rights, and social justice as a framework for offering services to Haitian students and their families. The authors present literature underlining the experiences of the Haitian population both within the context of their home country and also as immigrants in the United States.
Effects of Natural Disasters on Haitian Migration
Over the past few decades, the small nation of Haiti has suffered tremendously from natural disasters. In January 2010, a major 7.1-magnitude earthquake shook the island’s core, killing close to 300,000 men, women, and children. An equal number of individuals were injured and at least 1.5 million were displaced. Among the damage and destruction were almost 4,000 schools (CNN, 2017). Six years later, Hurricane Matthew swept through the south side of the island, killing over 900 citizens and leaving severe devastation in its tracks (BBC News, 2016). A year after that, Haiti, already crippled economically by previous natural disasters, was hit by Hurricane Irma, a Category 5 storm. Cook (2017) reported that homes, bridges, and housing already weakened by previous disasters were destroyed. Not only were homes destroyed, but the country’s ability to rebuild also was diminished.
Each natural disaster in Haiti has meant a struggle for regrowth. Between 2015 and 2016, it was reported that the economic growth in Haiti was down to a staggering 2% (U.S. Department of State, 2018). Damage from natural disasters, drought conditions, governmental unrest, and a significant decrease in the country’s currency were identified as contributors to the financial stagnation (U.S. Department of State, 2018). Migration trends portrayed a parallel between decreased stability in Haiti and increased migration to the United States and other more secure territories. In fact, over the years, the United States has been the recipient of thousands of immigrants seeking security and a better future for their families. Stepick and Stepick (2002) reported that in the 20th century, the number of Haitian immigrants to the United States reached an all-time high. By 2010, there were approximately 587,000 Haitians living in the United States, and that number rose to almost 700,000 by 2015 (Migration Policy Institute, 2017). The distribution of Haitian immigrants varies from state to state, with Florida having the largest population (46%), followed by New York (25%), New Jersey (8%), Massachusetts (7%), Georgia (2%), and Maryland (2%). These numbers may continue to rise as the outlook for the island of Haiti remains bleak.
Prior to the January 2010 earthquake, Haitian migration to the United States was considered high due to unemployment, low socioeconomic stability, poverty, violence, and political instability on the island (Cone, Buxton, Lee, & Mahotiere, 2014). Presently, Haiti is considered the economically poorest country in the Western hemisphere (Coupeau, 2008; Mendelson-Forman, 2006). Haiti also has been notorious for its high number of orphans, with at least 380,000 before the earthquake and a significantly increased number of displaced and homeless children after the earthquake (Little, 2010). Concern exists for the well-being of Haiti’s survivors of natural disasters, particularly the children. According to Potocky (1996), in the past years many Haitian children and their families who fled Haiti due to hardships and entered the United States as refugees often suffered from post-traumatic stress disorder (PTSD; Potocky, 1996).
The U.S. Department of State (2018) estimated that Haiti has received nearly $5.1 billion in aid from the United States since the earthquake. Assistance offered included increasing the number of officers on the police force to increase security, increasing basic health care through development of new clinics, construction of a mega power plant to provide electricity, and support for farmers to increase crop development. Even so, Haitians continue to struggle and have sought immigration support from the United States. Reports have suggested that as many as 55,000 Haitians applied and have been granted visas to the United States since the earthquake, and as many as 500 orphaned children have been allowed travel documents for adoption by U.S. families (Zissis, 2010).
To support Haiti over the past decade, U.S. Homeland Security has offered Temporary Protected Status (TPS) to large numbers of Haitians affected by the debilitating conditions caused by natural disasters as well as political unrest. TPS is offered to individuals from foreign countries where it may be unsafe or where resources are inadequate to support the citizens. TPS may be granted to individuals who are already in the United States or those still in their native country. TPS allows recipients to remain in the United States and secure travel and employment authorization (U.S. Department of State, 2018). As such, TPS has been granted to an estimated 60,000 Haitian citizens following the destruction from the 2010 earthquake. Outside of Haitians who have entered the United States through the TPS program, it has been reported that at least 40,000 more Haitians have entered the United States seeking refuge following Hurricane Matthew (Fifield, 2016). It appears that with each natural disaster the number of Haitian immigrants in the United States has increased.
Impact of Migration on Haitian Students and Families
Migration to a new country may come with difficulties for families, particularly children. Haitian children experience multiple layers of challenges in the American educational system and society at large. To better support Haitian students, counselors need to understand the impact of these hardships on various aspects of Haitian students’ lives and needs. The following sections provide a review on the complications facing these students and their unique needs.
Research suggests that traumatic events affect the physiological, psychological, and social welfare of immigrant students (Bean, Derluyn, Eurelings-Bontekoe, Broekaert, & Spinhoven, 2006). Haitian families may experience household stress due to separation of family members between the United States and their homeland (Desrosiers & St. Fleurose, 2002). Additional stressors include cultural misunderstanding and isolation in the school setting (Chhuon, Hudley, Brenner, & Macias, 2010); differences in educational policies, pedagogical practices, and teaching styles; and overall differences in school culture and climate (Cone et al., 2014). These challenges, particularly in the school setting, may be problematic for Haitian students and parents trying to acculturate to the American system.
Haitian students experience significant social difficulties. In a study exploring stressors experienced by immigrants to the United States, Haitian parents and children reported the highest number of stressors among immigrants from the Caribbean islands (Levitt, Lane, & Levitt, 2009). In addition, it has been reported that Haitian immigrants have a 20–30% higher chance of living in poverty-stricken conditions in the United States than people who are White (Hernandez, Denton, & Mcartney 2009). Douyon, Marcelin, Jean-Gilles, and Page (2005) indicated that students in highly populated Haitian communities—such as the Miami-Dade, Florida, area—may be surviving in not only poor health conditions, but also hostile territories where education appears to be futile and a life of crime is more appealing. Those social problems may add stress to the Haitian household, which may compound existing economic problems (Chierici, 2004). Indeed, migration disrupts the familial and social networks as well as the behavioral norms and cultural values of new immigrants. It places responsibility on counselors and other educators to meet the needs of these students academically, socially, and culturally (Asner-Self & Marotta, 2005). Thus, it is imperative for schools to help provide both supportive relationships to foster resiliency and additional resources for Haitian immigrant students.
Social and Cultural Needs
Haitian students face potential cultural difficulties, such as language barriers, cultural identity, and acculturation, particularly in the school setting. Haitian students and their families may primarily speak Haitian Creole, yet few interpreters are available to assist with standardized test explanations (Kretsedemas, 2005), student code of conduct reviews, and other pertinent information that may affect students’ academic functioning. In comparison to Spanish, which is taught in American schools, Haitian Creole is spoken only within the Haitian culture (Phelps & Johnson, 2004). Although Haitian Creole is based on the French language, it has syntactical influences from West African languages. It should be noted that it is not a dialect of French, but is its own independent language (Solano-Flores & Li, 2006).
Along with sensitivity to language barriers, Haitian students may encounter challenges in developing their cultural identity. As reported by Doucet (2005), Haitian students who may be struggling between their own cultural identity and the American culture might encounter school-related problems such as suspensions, truancy, academic failure, and eventual school dropout. Cone and colleagues (2014) reported the results of a qualitative study and emphasized the difficulty in identity formation that Haitian students experience in the United States. Identity formation was influenced by three factors: differences in pedagogical approaches to teaching between Haiti and the United States; differences in disciplinary approaches between teacher groups; and pressure from peers to become Americanized. To counter the stigma associated with being and looking different, Cone and colleagues noted that Haitian students may accede to their peers and hide any indication of their Haitian heritage. Consequently, these practices may foster added stress within the family network and community at large. Struggles with cultural identity formation can cause Haitian students to feel anxiety, confusion, fear, helplessness, and homesickness (Bachay, 1998), which may ultimately lead to increased risk of PTSD.
To further compound psychological distress experienced by Haitian families living in the United States, in November 2017, U.S. President Donald Trump declared an end to TPS for Haiti and several other countries (Park, 2018). This means that at least 60,000 Haitians currently residing legally in the United States through TPS can be deported by January 2019 (Daugherty, 2018). Additionally, deportation holds on Haitian citizens activated following the 2010 earthquake are being released, increasing the number of Haitians being deported. Deportation is destructive to family units, especially children. Children are affected by the knowledge of deportation of individuals within their community, even when that individual is unrelated to them. When a family member is deported, the rest of the family, including children, may suffer from poverty, reduced access to food and health care, and limited educational opportunities (Wiley, 2013). Thus, the already fragile academic, social, and cultural experiences of some Haitian students and families currently residing in the United States might be further aggravated by political mandates and changing policies. Therefore, culturally relevant support is warranted from those who serve this population, including school counselors and other stakeholders.
School Counselors’ Role in Supporting the Haitian Students
According to the American School Counselor Association (ASCA; 2012) National Model, professional school counselors are to develop a comprehensive school counseling program that addresses the social, personal, academic, and career needs of students. Several approaches have been introduced to provide school counselors a pathway to supporting immigrant students, including parenting workshops for Jamaican parents (Morrison, Smith, Bryan, & Steele, 2016); community outreach programs on college preparation for first-generation Latinx students, families, and friends (Tello & Lonn, 2017); and a comprehensive, multilevel system of support that includes school–family–community partnerships for adolescent immigrants (Suárez-Orozco, Onaga, & de Lardemelle, 2010). A thorough search of the literature, particularly school counseling literature, yielded a dearth of information on working with Haitian students and their families. In light of the numerous challenges that this population faces, the scarcity of research support is disappointing. Therefore, the authors provide a guideline for school counselors to support their Haitian clients by using the Multiphase Model of Psychotherapy, Counseling, Human Rights, and Social Justice (MPM; Chung & Bemak, 2012). The MPM was developed by counselor educators as a culturally responsive intervention to support individuals from marginalized groups. The MPM is psychoeducational in nature and consists of “affective, behavioral, and cognitive interventions and prevention strategies that are rooted in cultural foundations and relate to social and community process and change” (Chung & Bemak, 2012, p. 2).
Multiphase Model of Psychotherapy, Counseling, Human Rights, and Social Justice (MPM)
The MPM was developed by Chung and Bemak (2012), who expertly recognized the need for a culturally sensitive approach to supporting refugees globally. Chung and Bemak indicated that an effective counselor is one who understands the importance of refugees’ historical, sociopolitical, cultural, and psychological context when dealing with displacement, loss, and trauma. The MPM was constructed as a trauma-based model that integrates humanistic trauma therapy, exposure therapy, stress inoculation approach, and cognitive behavior therapy, and is framed by the multicultural counseling competencies (Arredondo et al. 1996). According to Chung and Bemak, the MPM includes five phases: (a) mental health education; (b) group, family, and individual psychotherapy; (c) cultural empowerment; (d) indigenous healing; and (e) social justice and human rights. Each phase can be used independently of the other and can be adjusted based on the needs of the client. The following section expands on the five phases and incorporates practical interventions for school counselors.
Phase One: Mental Health Education
Mental health education focuses on defining the counseling process for the client. Haitian immigrant students might not have had exposure to counseling in the past; therefore, it is important for school counselors to thoroughly explain what counseling is about, what the expectations are, and the expected outcomes of counseling. Chung and Bemak (2012) also noted the importance of discussing the meaning of confidentiality in both the context of the U.S. counseling community and in the client’s native community. Confidentiality is an ethical consideration supported by ASCA as an obligation for school counselors (ASCA, 2014). Lazovsky (2008) remarked on the fact that laws and regulations regarding confidentiality may differ internationally, so it is important for the counselor to explain the meaning and objectives of using confidentiality as it relates to family and school. During this phase, school counselors should pay close attention to the experiences of marginalization and trauma that these students and their families may have faced and the psychological distress related to potential deportation. Mistrust of Americans may be an essential part of the Haitian family’s survival mechanism (Stepick, Stepick, & Kretsedemas, 2018); therefore, school counselors should be cautious in this phase to be culturally sensitive to the fears and anxiety that the student and family may be experiencing.
Phase Two: Group, Family, and Individual Psychotherapy
The second phase is focused on providing culturally relevant counseling techniques and strategies. To do so, the school counselor needs to understand the contextual background of the student. What have their experiences been either while in Haiti or within the United States? How has that student and the family been affected by natural disasters and sociopolitical experiences? Based on this information, the school counselor needs to decide on the most appropriate culturally relevant interventions for the student. Surveys and questionnaires are an ideal format for gathering information about the experiences of Haitian students and their families (Ekstrom, Elmore, Schafer, Trotter, & Webster, 2004). However, school counselors should be mindful of language barriers and provide surveys that have been translated in both English and Haitian Creole. Additionally, individual and group counseling sessions need to be adapted to meet the cultural needs of the Haitian student. For instance, singing, dancing, and spiritual guidance are an integral part of the Haitian culture (Marcus, 2010). School counselors should consider the collectivist cultures of the Haitian population, which may influence their decision to engage the students in small groups as opposed to individual counseling. By utilizing culturally relevant counseling approaches, school counselors might find small group expressive techniques to be beneficial for developing trust, while assessing the psychological needs of the student.
Phase Three: Cultural Empowerment
Cultural empowerment extends support for client needs beyond the counseling setting to community resources. This phase incorporates collaborating with multiple agencies. Examples of such agencies include housing services, social services, and health services. The school counselor can choose to develop a team approach with the school’s social worker and other school stakeholders and serve as the facilitator of services. The objective during this phase is to serve as an advocate and guide for the student and their family to reduce their levels of stress and anxiety as well as meet their basic needs. In fact, Chung and Bemak (2012) surmised that cultural empowerment goes beyond in-office counseling to the greater community, with helpers rallying for services and resources to meet the families’ basic needs. Finally, cultural empowerment may mean providing adequate interpretation services for students and families (Kretsedemas, 2005) so that all stakeholders fully understand each other and the processes that are at work. In fact, school counselors and educators have a civic obligation to provide interpretive services to students and parents with limited English proficiency (Office for Civil Rights, 2015).
Phase Four: Indigenous Healing
From the American viewpoint, counseling, therapy, medicine, and health care are considered important aspects of holistic healing. However, within the Haitian culture, indigenous healing has been noted as a longstanding cultural practice. It is not uncommon for individuals from the Haitian population to seek help from spiritual healers, herbal specialists, and midwives rather than more formalized Westernized therapy. In fact, many Haitians hold extreme faith in natural healing and may be hesitant to pursue counseling in the context of the United States. Furthermore, Haitian individuals often believe that illness is caused by supernatural forces (Nicolas, DeSilva, Grey, & Gonzalez-Eastep, 2006); therefore, it is not unusual for families to pursue help from family healers, spiritual healers, or folk medicine in seeking the supernatural cause of illnesses. Nicolas and colleagues (2006) noted that common beliefs may attribute illnesses to evil spirits, a poor relationship with God, or offending the Lwa, a deity associated with the voodoo religion. Although not all Haitians hold these indigenous views, there may be a general mistrust of mental health services. Counselors working with Haitian clients should be cautious to embrace culturally sensitive practices that combine Westernized practices with indigenous healing. Seeking consultation from a Haitian spiritual healer might be a first step in formulating an effective counseling approach. Nicolas and colleagues (2006) suggested seeking these healers through Haitian community centers and through communication with family members of the clients. Counselors should avoid assumptions and initiate conversations with Haitian clients to understand their beliefs and practices.
Phase Five: Social Justice and Human Rights
The final phase of the multiphase model focuses on counselors advocating for the rights of their clients. Haitian immigrants in the United States experience political discrimination. For example, recent threats of deportation and the termination of TPS protection can be discriminatory. At this phase, it is vital that counselors examine their own worldviews, community relations, and the role of politics and political policies in counseling, as well as the impact of social injustices (e.g., discrimination, oppression, racism) on the well-being of their clients (Chung & Bemak, 2012). Griffin and Steen (2011) mentioned nine steps that school counselors can employ as social justice advocates: develop cultural competence; use data to support work, particularly educational inequalities; gain allies, recognizing that the work cannot be done alone; speak up at school, at town hall meetings, and at board meetings, and write to state legislators; educate and empower parents and families; stay politically engaged and know what is happening in the current political environment; be bold and confident in beliefs; be persistent, understanding that systemic barriers may stand in the way of progress; and conduct research to demonstrate the needs for justice, equity, equality, and fairness. School counselors are inundated with multiple roles and as such may not have the time and/or resources to cover all nine steps mentioned. However, knowledge of these practical strategies may be helpful in their ethical decision making and development of a culturally sensitive, comprehensive school counseling program. Essentially, school counselors should be leading agents of change, seeking to provide culturally relevant services to their immigrant students.
Summary
Haitian children face various systemic challenges adjusting to the U.S. educational system and society. Given their unique challenges and needs, Haitian children require specialized, culturally responsive school counseling programs. To provide such programs, school counselors need practical strategies on how to provide culturally appropriate interventions that address the multiple systemic challenges to Haitian students’ well-being. However, school counselors may find it difficult to find such information given the dearth of school counseling literature concerning Haitian students. Therefore, this article provides practical guidelines using the MPM that may strengthen school counselors’ approach to providing culturally responsive services to Haitian students and their families.
Using the MPM, school counselors will be in a better position to explore the benefits of counseling with their Haitian families. The model encourages school counselors to assess the unique needs of the children and families within a cultural context. Moreover, by using this model, school counselors are encouraged to actively engage in collaborative partnerships with multiple agencies and professionals to meet the practical needs of Haitian families. Lastly, school counselors need to work beyond the structure of the office setting and integrate social justice advocacy work for systemic changes to maximize therapeutic changes for Haitian students and their families. The authors hope that this guideline will help school counselors to better understand the multiple layers of challenges for Haitian students, as well as how to provide culturally relevant support.
Conflict of Interest and Funding Disclosure
The authors reported no conflict of interest or funding contributions for the development of this manuscript.
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articles/haitian-migration-debate
- M. Ann Shillingford is an associate professor at the University of Central Florida. Seungbin Oh, NCC, is a doctoral candidate at the University of Central Florida. Amanda DiLorenzo is a doctoral student at the University of Central Florida. Correspondence can be addressed to M. Ann Shillingford, P.O. Box 161250, Orlando, FL 32816, Dr-S@ucf.edu.
Sep 28, 2018 | Volume 8 - Issue 3
Nancy E. Thacker, Jillian M. Blueford
Counselors are becoming more involved with clients pursuing physician-assisted death (PAD) as legislation for legalization increases. PAD may present complex values-based conflicts that can challenge counselors to maintain ethical practice in counseling. When conflicts arise, counselors must engage in ethical decision making that considers systemic influences on personally held beliefs and values. The authors merge ecological systems theory with the counselor values-based conflict model to offer a holistic approach to resolving values-based conflicts surrounding PAD. In this article, the authors review PAD and counselors’ roles in the hastened death process, discuss sources and impacts of personal and professional values through an ecological systems lens, and provide an applied method of managing values-based conflicts with PAD through a case illustration.
Keywords: physician-assisted death, hastened death, values-based conflict, ethical decision making, ecological systems
Individuals with terminal illnesses encounter difficult end-of-life decisions amidst experiencing physical and emotional distress (Daneker, 2006). Currently in six U.S. states and Washington, DC, terminally ill individuals have a legal right to end their lives via physician-assisted death (PAD). As legislation for legalization of PAD increases, more terminally ill patients can consider PAD as an option (Miller, Hedlund, & Soule, 2006). As a result, the need for mental health professionals to assist individuals dealing with these end-of-life decisions is on the rise.
The topic of death presents complex questions about the meaning of life and death and evokes reflections on one’s personal beliefs and values surrounding death and dying (Yalom, 2009). Terminally ill individuals may confront their personal beliefs about a morally just or good death, explore feelings about the process of dying, and consider their levels of personal control or power in their processes of dying (Laakkonen, Pitkala, & Strandberg, 2004; Yalom, 2008). Religion and spirituality often contribute to terminally ill individuals’ beliefs and values surrounding death and dying and can influence end-of-life decisions (Reiner, 2007). Each personal belief and value is influenced by systemic factors, cultural experiences, and cultural customs or expectations that play a role in end-of-life decision making (Laakkonen et al., 2004; Neimeyer, Klass, & Dennis, 2014).
Counselors will confront their beliefs and values about death and dying as terminally ill individuals who are contemplating PAD (PAD clients) seek counseling to explore end-of-life decisions (Werth & Crow, 2009). If counselors’ beliefs and values conflict with PAD clients’ beliefs and values, or PAD itself, then it may present an ethical dilemma that challenges the quality of care counselors provide (Heller Levitt & Hartwig Moorhead, 2013). Although not all counselors may experience a value conflict related to PAD, those who do experience a conflict may look to the American Counseling Association’s (ACA) Code of Ethics (2014) and an ethical decision-making model that accurately addresses the values-based nature of the ethical dilemma at hand.
Multiple scholars have discussed the need to explore values related to personal conflicts to maintain ethical practice in counseling (Cottone & Tarvydas, 2016). However, few sources have yet to provide direction for counselors on how to resolve personal values-based conflicts regarding PAD. There is an added layer of difficulty with PAD clients because of the multifaceted nature of personal and professional values at play. Counselors are grounded on the ethical principles of promoting client autonomy and respecting cultural differences in decisions (ACA, 2014), but hastening death conflicts with the counseling profession’s inherent stance to “first do no harm” and to maintain client safety and preserve life when clients desire to end their lives (Cohen, 2001). Even though hastening death is legal in certain states, values surrounding the decision to end life do not simply cease because there is justified reasoning for a decision. Thus, counselors face a challenging dichotomy between law and values in their practice with PAD clients.
Recent changes in the counseling profession’s ethical code also contribute to the potential challenge of maintaining ethical practice with PAD clients. The ACA Code of Ethics (2005) included codes that addressed counseling practice with clients considering end-of-life options. Section A.9 in the ACA Code of Ethics (2005) provided guidelines about the quality of care counselors should uphold for clients facing the end of their life, including the counselor’s role in assisting clients with end-of-life decisions. Counselors were tasked with the responsibility to reflect upon personal values and morals regarding end-of-life to ensure competent and ethical care. Although the revised ACA Code of Ethics (2014) includes considerations for confidentiality, legal concerns, and client safety during end-of-life care, there is no longer a designated section for the end-of-life care of terminally ill clients, and explicit codes regarding PAD are absent. The ACA Code of Ethics (2014) included guidelines for counselors regarding methods to maintain client autonomy and seek continuing education to address the holistic needs of clients, along with giving clients the tools necessary to make the most appropriate decisions for their care. However, lack of explicit codes about PAD and few guidelines related to end-of-life care might cause ambiguity when values-based ethical dilemmas about PAD arise.
In summary, consideration for counselors’ personal and professional values, along with the ethical and legal implications at hand, creates unique potential for a values-based conflict surrounding PAD unlike other sources of values-based conflicts. Values are influenced by numerous factors in multiple settings and contexts (Heller Levitt & Hartwig Moorhead, 2013). Therefore, resolving value conflicts related to PAD warrants a unique systemic perspective that considers the multiple influential sources that shape values about death and grief in personal and professional realms (Neimeyer et al., 2014).
The authors of this article review PAD, counselors’ roles in the hastened death process, and an applied method of managing values-based conflicts with PAD through a values-based ethical decision-making model and ethical bracketing. The impacts of personal and professional values will be described through an ecological systems lens. It is important for counselors to understand PAD in the context of various systems, as individuals’ decisions concerning PAD are influenced by multiple sources that contribute to their beliefs and values related to death and dying.
Physician-Assisted Death
PAD is currently legal in six U.S. states: California, Colorado, Montana (by court ruling), Oregon, Vermont, and Washington, as well as Washington, DC (Death with Dignity, 2018). Hawaii will become the seventh state to legalize PAD when their legal statute takes effect in January 2019 (Death with Dignity, 2018). PAD has been a topic of debate throughout American society and health care for decades (Werth & Holdwick, 2000). Many have voiced opposition to PAD as a legalized option (Werth & Holdwick, 2000), and previous “standards of mental health practice [have treated] all suicides as products of mental illness” (Cohen, 2001, p. 279). However, health care advocates of PAD, such as Dr. Jack Kevorkian, have fought for individual rights to choose dignified death when faced with terminal illness (Kevorkian, 1991). As the legalization of PAD emerged in the aforementioned states, the topic of debate shifted from the right to choose hastened death toward the policies that guide health care professionals to assist terminally ill individuals in hastening their deaths (Werth & Holdwick, 2000).
Language within each state statute slightly varies, but requirements to legally hasten death are similar across states. There are no formal requirements for PAD in Montana, because a law permitting PAD does not exist in that state; however, there is a legal precedent that protects physicians from prosecution as long as there is written consent from the patient (Baxter v. Montana, 2009). For all other states, patients must be over the age of 18, permanent residents of the state, have been determined by an attending and consulting physician to be suffering from a terminal illness, and carry a life expectancy of under 6 months to be eligible to legally hasten their deaths. Patients must voluntarily express their wishes to die orally, make a written request for medication to end their lives in a humane and dignified manner, and be deemed mentally competent to make end-of-life decisions by a licensed psychiatrist or psychologist. In addition, there is typically a 15-day waiting period between the initial request and when the physician provides a written prescription for medication to end life (Death with Dignity, 2018).
In the legal requirements of each state and district statute, there is no mandate for counseling services beyond an assessment of competency. However, PAD clients and their families often work with mental health professionals throughout the process of considering hastened death and implementing PAD (Fulmer, 2014). As more states move toward legislation to legalize PAD, counselors are becoming more involved in the interdisciplinary teams of health professionals working to meet the needs of this population. Interdisciplinary teams may be comprised of medical physicians, psychiatrists, psychologists, social workers, palliative care nurses and specialists, occupational therapists, and mental health counselors (O’Connor & Fisher, 2011). Clients pursuing PAD have physical, social, emotional, spiritual, and practical needs as they deal with the process and experience of dying (Daneker, 2006). Helping professionals’ roles can be blurred as the interdisciplinary team works together to meet PAD clients’ needs (O’Connor & Fisher, 2011). Physical needs include keeping clients comfortable in their final months of life when all other treatment options are exhausted. Practical needs include making arrangements for after death and navigating the legal processes to hasten death, including the competency assessment a psychiatrist or psychologist must conduct to ensure that PAD clients are stable and well-informed enough to decide to hasten their death (O’Connor & Fisher, 2011). Clients’ social, emotional, and spiritual needs will vary depending on the nature of the terminal illness, individual contexts, and familial and cultural contexts; counselors are trained to address such biopsychosocial needs within clients’ individual and cultural contexts (Peruzzi, Canapary, & Bongar, 1996; Werth & Crow, 2009).
A counselor’s primary role is to address how clients’ medical diagnoses are impacting their biopsychosocial well-being, including their decision-making processes to hasten death (O’Connor & Fisher, 2011; Peruzzi et al., 1996; Werth & Crow, 2009). Counselors build a unique therapeutic relationship that provides professional emotional support, and they help clients reflect on the factors that have led them to make this life-ending decision. They may explore what hastened death means to clients’ families or communities. Counselors also seek to understand how clients’ spiritual beliefs and emotional needs influence their well-being and decision making. Counselors recognize that spirituality and religious practices can be significant to clients when discussing dying, death, and grief (Altmaier, 2011). Addressing these factors allows counselors to be intentional in creating a safe setting for difficult discussions.
Standards of Counseling Practice With Dying Clients
The ACA Code of Ethics (2014) not only serves as a guide to ethical practice in counseling, but also provides an understanding of the goals and mission of the counseling profession. Counselors are committed to engaging in “a professional relationship that empowers diverse individuals, families, and groups to accomplish mental health [and] wellness” (ACA, 2014, p. 3). In order to engage in such a relationship with ethical integrity, counselors consider the six principles of ethical behavior: autonomy, nonmaleficence, beneficence, justice, fidelity, and veracity (ACA, 2014). These principles are foundational to the ways in which counselors practice ethically across diverse client groups and settings. Counselors working with PAD clients should review relevant ethical codes concerning end-of-life issues, personal value conflicts, and confidentiality concerns pertinent to fulfilling the needs of terminally ill clients. Of these relevant issues, one specific code includes guidance in managing personal values in counseling:
Counselors are aware of—and avoid imposing—their own values, attitudes, beliefs, and behaviors.
Counselors respect the diversity of clients . . . and seek training in areas in which they are at risk
of imposing their values onto clients, especially when the counselor’s values are inconsistent with
the client’s goals or are discriminatory in nature. (ACA, 2014, A.4.b)
As counselors confront the socioemotional and spiritual needs of PAD clients, regulating personal values related to PAD is of utmost importance for the well-being of a dying client (Werth, 1999).
Values and PAD
Personal values exist at individual, professional, and societal levels. Counselors develop and mold their values in multiple contexts and through various experiences in their lifetime. Thus, counselors’ values surrounding death, dying, and PAD are multifaceted and influenced by multiple factors. Counselors’ views and values surrounding death may be impacted by age, race, gender, religion or spiritual beliefs, phase of life, family structure and influence, cultural identity (e.g., individualistic vs. collectivistic), and education (Bevacqua & Kurpius, 2013; Harrawood, Doughty, & Wilde, 2011; Kemmelmeier, Wieczorkowska, Erb, & Burnstein, 2002). How these factors are interwoven into personal views and values depends on counselors’ perceptions of their experiences and influences from their surrounding environments.
Because personal values are constructed and influenced by a multitude of factors and environments (Heller Levitt & Hartwig Moorhead, 2013), a systemic perspective can be used to appropriately explore and understand how personal values may form and influence counselors. Bronfenbrenner (1979) established the ecological model to describe an individual’s development within four ecosystems: the microsystem, mesosystem, exosystem, and macrosystem. In 1994, Bronfenbrenner revised the ecological model to include the chronosystem, which considers the influence of time and history as individuals develop. Each ecosystem interacts with the others and influences how each ecosystem forms and impacts the developing individual. The ecosystems can be understood as “a set of nested structures, each inside the next, like a set of Russian dolls” (Bronfenbrenner, 1979, p. 3). Next to the chronosystem, the outermost system, the macrosystem encompasses one’s culture, societal norms, and traditions. The exosystem lies within the macrosystem and represents the interactions between environments that may or may not directly affect an individual’s daily interactions. An example of this system would be a parent having trouble at work, and that stressor then affecting the relationship with the child. Within the exosystem is the mesosystem. The mesosystem includes the interactions between the individual’s microsystem and has direct effects on the individual. Lastly, the microsystem involves the individual’s immediate settings and relationships. Relationships can include family and caregivers among others in the environment. Each of these ecosystems and the interactions between them impact the developing individual’s behaviors (Bronfenbrenner, 1979).
Within a systemic ecological perspective, beliefs and values can be viewed as forming and ensuing through layers of influence first from the macrosystem and filtered down through the exosystem, mesosystem, and microsystem (Bronfenbrenner, 1979). The chronosystem includes a history of culture that influences development over time, but the cultural expressions of such influence play out in the macrosystem (Bronfenbrenner, 1994). The macrosystem, the most external of systemic influence, can include societal norms of death and dying and a religious or spiritual belief system. These norms and belief systems influence the exosystem, where laws and regulations exist (e.g., the right for individuals to hasten death in legalized states). Events that occur in the exosystem might not directly include counselors, but they impact the ways in which counselors interact with their lower systems (e.g., news reports of terminally ill patients miraculously overcoming illness).
Through the mesosystem structure, counselors directly engage with multiple settings that influence their beliefs surrounding death and dying (e.g., work and family). Counselors’ interactions with two settings, such as workplace and family, will shed light onto how beliefs, values, and behaviors about death and dying are experienced in each setting. Counselors’ values are subsequently influenced by the interactions between the two settings. Finally, direct experiences in counselors’ immediate settings, the microsystem, impact the unique views and values counselors espouse. Although values filter through larger systems with influence from external factors that impact multiple people, counselors will form distinct perceptions of their experiences that inform their intrapersonal reactions to death and dying (Werth & Crow, 2009).
As counselors consider each layer of the surrounding environment that informs their personal values, they face the values of the counseling profession in the mesosystem. The ACA Code of Ethics (2014) highlighted five fundamental professional values:
- enhancing human development throughout the lifespan;
- honoring diversity and embracing a multicultural approach in support of the worth, dignity,
potential, and uniqueness of people within their social and cultural contexts;
- promoting social justice;
- safeguarding the integrity of the counselor–client relationship; and
- practicing in a competent and ethical manner. (p. 3)
These values provide a foundation for counselors’ ethical behaviors and decisions and inform the collective identity of the counseling profession.
Counselors first encounter professional values in their training programs and are continually exposed to new expressions of professional values throughout their careers. Counselors are nurtured throughout their development to integrate their personal attributes with professional factors as they form an identity congruent with the counseling profession (D. M. Gibson, Dollarhide, & Moss, 2010; Post & Wade, 2009). The ways in which counselors integrate professional values and develop their identities depends on the culture of their training programs, professional work settings, experiences in those settings, and individual perceptions that form from those experiences (Francis & Dugger, 2014). As a result, counselors may vary in their level of support for PAD, personal conflicts related to PAD, and general beliefs and values about death and dying. Therefore, counselors must evaluate their values at a personal and professional level as they work through value conflicts and ethical dilemmas with PAD clients (Johnson, Hayes, & Wade, 2007).
Ethical Decision Making and Bracketing
Counselors’ abilities to resolve value conflicts are determined through ethical decision making (Cottone & Tarvydas, 2016; Kocet & Herlihy, 2014). The ACA Code of Ethics (2014) serves as a guide to counselors to uphold equitable standards of care across client populations when ethical dilemmas and value conflicts arise. According to ACA:
When counselors are faced with ethical dilemmas that are difficult to resolve, they are expected to
engage in a carefully considered ethical decision-making process, consulting available resources as
needed. Counselors acknowledge that resolving ethical issues is a process; ethical reasoning
includes consideration of professional values, professional ethical principles, and ethical
standards. (ACA, 2014, p. 3)
Becoming an ethical decision maker is most effectively done through practice in intentional decision-making processes (P. A. Gibson, 2008). There are many ethical decision-making models that are relevant to maintaining ethical integrity during a variety of dilemmas (Cottone & Tarvydas, 2016). Counselors most often use practice-derived models that are produced from counselors’ experiences and are intended to provide a step-by-step guide for practice (Cottone & Tarvydas, 2016). Although each model is distinct in its step-by-step process, there are common elements throughout them that highlight a standard of practice for ethical decision making. Significant commonalities include gathering information; considering the context of the situation; reviewing codes, standards, and laws; evaluating the counselor’s values or biases; consultation; developing a plan; and executing the plan. For counselors working with PAD clients, their decision-making processes will require a more in-depth exploration of the context of the situation, counselors’ values and biases, and the counseling profession’s values (Heller Levitt & Hartwig Moorhead, 2013; Kurt & Piazza, 2012). Thus, a decision-making model that carefully considers values-based conflicts is needed.
Using a practice-derived framework, Kocet and Herlihy (2014) developed the counselor values-based conflict model (CVCM) to specifically address ethical dilemmas stemming from value conflicts. The model includes five steps: (1) determine nature of values-based conflict (personal or professional); (2) explore core issues and potential barriers to providing appropriate standard of care; (3) seek assistance/remediation for providing appropriate standard of care; (4) determine and evaluate possible courses of action; and (5) ensure that proposed actions promote client welfare (Kocet & Herlihy, 2014). Each step includes consideration for potential personal and professional values that may arise for counselors.
A key part of resolving values-based conflicts is avoiding imposing one’s values onto the client. To address this key issue, Kocet and Herlihy (2014) also introduced the term ethical bracketing. Ethical bracketing in qualitative research is “a reflexive process [that] enables [researchers] to bracket or set aside their own experiences and assumptions when they interact with their participants and thus accurately capture their participants’ voices” (Kocet & Herlihy, 2014, p. 182). To apply this concept to counseling, Kocet and Herlihy stated that ethical bracketing
is defined as the intentional separating of a counselor’s personal values from his or her
professional values or the intentional setting aside of the counselor’s personal values in order to
provide ethical and appropriate counseling to all clients, especially those whose worldviews,
values, belief systems, and decisions differ significantly from those of the counselor. (p. 182)
Counselors can engage in ethical bracketing by seeking supervision, consultation, continuing education, and personal counseling (Kocet & Herlihy, 2014). This bracketing technique allows counselors to confront their values and establish awareness of how their values may be impacting their views and interactions with clients. Counselors may more easily recognize the unique worldviews of clients through this process, thereby respecting the diversity of clients in their cultural contexts. Such recognition protects the welfare of clients as counselors strive to work from the client’s worldview rather than their own (ACA, 2014). The CVCM, along with ethical bracketing, can be used as a guiding ethical decision-making framework for counselors to explore the systemic nature of their values and resolve values-based conflicts with PAD.
Values-Based Ethical Decisions and Bracketing With PAD
The CVCM is designed to assist counselors in managing personal conflicts related to values that may arise when working with clients (Kocet & Herlihy, 2014). The model begins with a prompt for counselors to determine if the nature of the conflict is personal or professional and ensues with steps that align with the nature of the conflict. However, considering the systemic makeup of individual values, particularly related to PAD, counselors must be mindful of the influences that stem from the profession’s values in the formation and modification of their personal values. Personal and professional values are interwoven and will consequently impact the ethical decision-making process related to values-based conflicts with PAD (Heller Levitt & Hartwig Moorhead, 2013). As a result, adding a systemic lens to the process of resolving values-based conflicts using the CVCM and ethical bracketing is important to maintaining ethical practice with PAD clients.
The systemic sources of values related to PAD are important to consider in the second step of the CVCM; this step includes a prompt for counselors to “explore core issues and potential barriers to providing appropriate standard[s] of care” (Kocet & Herlihy, 2014, p. 184). Gathering awareness about counselors’ personal views related to death, dying, and PAD is the crux of working through this step in the model. As previously discussed, counselors must engage in reflective practice to examine influential factors throughout each ecosystem. Each system contributes to counselors’ personal views and beliefs, and reflecting will bring awareness to not only the sources of counselors’ values, but also potential barriers to overcoming values-based conflicts (Bronfenbrenner, 1979; Cottone & Tarvydas, 2016; Kocet & Herlihy, 2014).
Beginning with the macrosystem, societal norms and religious and spiritual views of death and dying will influence the exosystem. Legislation that gives clients legal freedom in certain states to decide to end their lives is situated in the exosystem. As the decision to engage in PAD is legalized, it then trickles down into the mesosystem where groups, such as work colleagues and family, hold beliefs and values about PAD. These beliefs and values influence counselors in new ways and impact the intrapersonal reactions counselors have in their microsystem of experience. Counselors must examine the interactions between settings and the messages they receive in those settings. Then, they may more readily discover how their values and beliefs about PAD are formed and either reinforced or undermined. Increased awareness will help counselors identify the ecosystem that is the most salient source of their value conflict with PAD (Bronfenbrenner, 1979). Identifying the salient source may then lead to increased potential for counselors to be more specific in the ways they strategize to bracket their values.
As counselors foster awareness about the sources of their value conflicts, they can move into the third step and engage in ethical bracketing as a strategy to seek necessary assistance to resolve value conflicts. In addition to referring to the ACA Code of Ethics (2014), counselors may consult with other counselors to explore individualized strategies to engage with PAD clients without imposing personal beliefs and value systems. Consultation with other professionals will shed light onto professional standards of care for PAD clients, while also serving as a mirror for further self-exploration about the sources and nature of value conflicts with PAD. It is important to note that counselors should “identify ways to maintain personal/religious/moral beliefs while still providing effective counseling” (Kocet & Herlihy, 2014, p. 184). Ethical bracketing is not designed to push counselors to give up their beliefs or values; rather, counselors simply “set aside their own experiences and assumptions” to effectively step into the client’s worldview (Kocet & Herlihy, 2014, p. 182). Seeking supervision, consultation, and personal counseling can provide guidance for counselors to determine their needs to maintain their personal beliefs and deliver ethical care for PAD clients (Cottone & Tarvydas, 2016; Kocet & Herlihy, 2014).
Next, counselors shift into the fourth step to “determine and evaluate possible courses of action” (Kocet & Herlihy, 2014, p. 184). Using ethical bracketing as a strategy may provide distinct options to consider in this step. Once counselors are aware of the intricacies of their values-based conflict with PAD, they may be more readily able to bracket their values. The guidelines for use of the CVCM in the fourth step note client referral; however, counselors may only refer when they “lack the competence to be of professional assistance to clients,” and their rationale is not the result of personal bias (ACA, 2014, A.11.a.). If counselors lack competence, they may seek appropriate continuing education and supervision to expand their competency in the future. However, in the case of personal value conflicts, referral is not ethical. There is no statement in the ACA Code of Ethics (2014) “that [indicates] referral can be made on the basis of counselor values” (Kaplan, 2014, p. 144). Self-evaluation and consultation is essential to maintain ethical practice surrounding this topic. Once a course of action has been determined as ethical and effective, counselors engage in the fifth step to “ensure that proposed actions promote client welfare” (Kocet & Herlihy, 2014, p. 184). In order to more fully conceptualize resolving values-based conflicts with PAD through this model, a specific example is provided in the following section.
Case Study Application
The following case study explores a counselor’s values-based conflict related to PAD for illustrative purposes. Although many sources may contribute to potential values-based conflicts, personally held religious beliefs are often influential to views and values about PAD (Bevacqua & Kurpius, 2013; Burdette, Hill, & Moulton, 2005; Reiner, 2007). Therefore, personal religious beliefs are explored for the purposes of this case study. Considering a systemic view of counselors’ values, the CVCM and ethical bracketing are used to generate potential conflict resolutions that ensure ethical practice and protect the welfare of the client.
Vignette
Amy is a licensed professional counselor in the state of Washington. She works for an agency that receives referrals from a local hospital. Amy identifies as a religious person and has connections and support through her religious community. Her personal religious views do not endorse hastening one’s death, even under extreme circumstances like a terminal illness. Amy also has two young children.
Amy has been meeting with Frankie, a 40-year-old woman, for about four months. Frankie was diagnosed with leukemia about six months ago and began treatment shortly thereafter. Frankie recently found out that the leukemia is not responding to treatment and her treatment options are exhausted. Frankie’s oncologist has estimated a five- to six-month life expectancy. Frankie has expressed to Amy that she wants to pursue PAD so that she does not have to be in pain for 6 more months. Frankie has a husband and 6-year-old daughter.
Amy is initially shocked to hear Frankie’s desire to hasten her death. Amy is unsure how to proceed in her work with Frankie because she feels Frankie’s decision conflicts with her religious beliefs. Amy also is wondering if Frankie has considered how her family feels and if they would be okay with Frankie’s decision. Recognizing she needs to process her thoughts and feelings, Amy seeks out a helpful colleague in order to proceed in her work with Frankie.
Discussion
Beginning with the first step of the CVCM, Amy appears to be dealing with a complex values-based conflict. The nature of Amy’s conflict is primarily personal, but she is faced with some professional conflicts as well. Amy’s religious beliefs and values are personally driven, but the countertransference she is experiencing related to Frankie’s seeming lack of concern for her family can become a professional issue if Amy considers making professional decisions that emphasize family values over Frankie’s requests (Heller Levitt & Hartwig Moorhead, 2013). Furthermore, Amy’s personal religiously driven value conflict intertwines with the counseling profession’s value and ethical standard to respect clients’ worldviews and not impose personal beliefs onto clients (ACA, 2014, A.4.b). Understanding both personal and professional implications allows counselors to move into the second step of the CVCM.
The development and context of Amy’s values may be explored through a systemic ecological lens in the second step. Beginning with the macrosystem, Amy may consider how her religious culture views death and what messages she has internalized to form her understanding of morality and autonomy (Burdette et al., 2005; Johnson et al., 2007). She also could explore how society at large influences her religious beliefs and practices and subsequently how she believes her religion views the practice of hastened death. The interaction between Amy’s religious culture and society is situated in the exosystem. Amy’s interactions with her religious community, which are a part of her mesosystem, also will play a role in her beliefs and actions. She might think about how her immediate community impacts her beliefs and influences her perceptions of hastened death; Amy’s individual perceptions and direct engagement with her religious practices play out in her microsystem. As each ecosystem is explored, Amy can develop a clear understanding of the sources of her value conflict. The same process should be repeated for her values-based conflict about Frankie’s family. Amy may value collective family decisions and could potentially struggle to meet Frankie with acceptance if she believes an isolated decision is improper.
Once Amy has explored the systemic sources of her values, she is ready to seek assistance to ethically move forward with Frankie in the third step of the CVCM. Using ethical bracketing, Amy can reach out to her colleagues to consult about the issues at hand. Exploring her values with a trusted professional may enable her to bracket her values to approach Frankie’s differing beliefs and values. Amy must review the ACA Code of Ethics (2014) before creating a plan of action. Again, Code A.4.b, regarding personal values and biases, is central to an ethical course of action; the profession’s value of client autonomy and Code A.1.a, to protect the welfare of the client, also are important to consider here (ACA, 2014). Attending to legal implications, Amy should keep in mind that Frankie has a legal right in the state of Washington to decide to hasten her death. Lastly, Amy should consider ways she can maintain her own values without compromise while still providing effective care and assistance to Frankie in her decision-making process (Kocet & Herlihy, 2014). Amy may pursue personal counseling or supervision and connect with trusted individuals in her religious community to maintain her personal beliefs and values while providing ethical care (Cottone & Tarvydas, 2016; Johnson et al., 2007).
Moving into the fourth step of the CVCM, referral is an option only if Amy lacks competence to provide Frankie with effective care. According to the CVCM, when a counselor is determining action plans, the choice to refer a client is decided after careful consideration of ethical guidelines, rationale for the referral, and in-depth consultation (Kocet & Herlihy, 2014). Referral based on personal values is not ethical according to the ACA Code of Ethics (2014); therefore, Amy cannot ethically refer Frankie, considering the source of her conflict is related to personal values.
Finally, in the fifth step, Amy can ensure her constructed course of action considers both legal and ethical implications. The rationale for Amy’s action plan should be based on professional competency, not personal bias (ACA, 2014, A.11.a). Amy’s ability to effectively bracket her values will be dependent on her depth of self-exploration, understanding of ethical practice in counseling, willingness to consult and seek appropriate resources, and ability to ensure client welfare as the priority. It is essential for Amy to seek consultation from her professional peers, who can provide insight into maintaining ethical boundaries with clients. Also, Amy can receive permission to speak with Frankie’s lawyer and the primary doctors involved with her decision to hasten her death. By increasing involvement with Frankie’s interdisciplinary team, Amy is ensuring holistic care and attending to the systemic nature of end-of-life decision making surrounding PAD.
Implications for Counseling Practice
The interplay between PAD and the values of counselors and the counseling profession is complex and warrants depth of exploration for counselors to effectively meet the needs of this population. Values-based conflicts do not occur in isolation; instead, multiple systems that impact individuals in varying ways influence the formation and expression of such conflicts (Heller Levitt & Hartwig Moorhead, 2013). No one specific cultural identity, belief, or value can predict a counselor’s conflicts with PAD, but it is crucial to explore values through a systemic lens to successfully manage values-based conflicts with PAD. The CVCM, along with ethical bracketing, can serve as an appropriate framework to confront and resolve values-based conflicts with PAD. Counselors will be better equipped to provide care to PAD clients as they willingly and openly explore their values related to death, dying, and hastening death through an ethical decision-making model (ACA, 2014). Counselors’ effectiveness in self-reflection and ethical practice is reliant in part on counselor education.
Counselor Education
As state laws change, counselor educators need to recognize that counselors will play a larger role in caring for potential PAD clients. It can be beneficial to learn about the role of value bracketing in regard to discussing the possibility of a client exploring the option of PAD. It is difficult for counselor educators to prepare counselors-in-training (CITs) for every potential ethical dilemma. However, with a better understanding of PAD, novice counselors can feel more equipped to effectively address concerns their clients may have without interference of their personal beliefs and values. PAD is a topic that will continue to expand. Introducing PAD during training may allow counselors to feel more prepared should a value conflict arise. As counselor educators facilitate conversations with CITs about their personal and professional beliefs toward PAD, CITs can implement their value bracketing skills under the supervision of their faculty. Being in a safe environment can encourage CITs to explore their authentic feelings concerning PAD and evaluate their value bracketing skillset. Addressing concerns and potential red flags during training can prevent harm to future clients and unethical clinical judgment and behaviors.
There is a potential challenge in maintaining consistency in training about end-of-life issues, including PAD, because of the nature of accreditation standards for counseling programs. There is no specific standard of learning in the 2016 Council for Accreditation of Counseling and Related Educational Programs (CACREP) standards regarding end-of-life counseling issues (CACREP, 2016). Counselor educators are tasked to meet learning standards related to human growth and development “across the lifespan,” but they have discretion over what they include and highlight throughout their curriculum (CACREP, 2016, p. 10). Counselor educators should consider the importance and advantages of including specific instruction on end-of-life issues in their curriculum (Servaty-Seib & Tedrick Parikh, 2014).
In addition to educating CITs, more research is needed to further understand counselors’ developing roles with clients pursuing PAD. With more states legalizing this procedure, it is only a matter of time before counselors are face-to-face with a client that needs a counselor’s experience and competency to assist with this life-changing decision. Although data is available concerning grief and loss counseling, literature directly related to counselors’ roles in working with PAD is sparse. Future research should incorporate counselors’ emerging roles with PAD clients and needs for training to prepare CITs. With stronger research in this area, counselor educators may feel more equipped to teach and support CITs
to become aware of and potentially bracket their values about death, dying, and PAD.
Conclusion
Counselors must be knowledgeable about the legal and ethical standards surrounding PAD in order to work effectively and ethically with PAD clients. Counselors also need to be aware of their personal beliefs and values about death and dying and be able to manage values-based conflicts. This article highlighted personal and professional values relevant to counselors working with PAD clients through an ecological systems lens. Considering the values at play, counselors can use the CVCM with ethical bracketing as an integrated method to resolve value conflicts with PAD (Kocet & Herlihy, 2014). Increased knowledge regarding ethical decision making surrounding PAD can encourage counselors to provide care for PAD clients with competence and confidence. Further research on counselors’ roles with PAD clients and needs for training may enhance counselors’ knowledge and competency with this client population.
Conflict of Interest and Funding Disclosure
The authors reported no conflict of interest or funding contributions for the development of this manuscript.
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Nancy E. Thacker, NCC, is a doctoral candidate at the University of Tennessee, Knoxville. Jillian M. Blueford, NCC, is a doctoral candidate at the University of Tennessee, Knoxville. Correspondence can be addressed to Nancy Thacker, 501 BEC, 1122 Volunteer Blvd, Knoxville, TN 37996-3452, nthacke2@vols.utk.edu.
Sep 27, 2018 | Volume 8 - Issue 3
Christopher T. Belser, M. Ann Shillingford, Andrew P. Daire, Diandra J. Prescod, Melissa A. Dagley
The United States is facing a crisis with respect to filling job vacancies within science, technology, engineering, and math (STEM) industries and with students completing STEM undergraduate degrees. In addition, disparities exist for females and ethnic minorities within STEM fields. Whereas prior research has centered on disparities in STEM fields, retention rates, and some intervention programs, researchers have not given much attention to the role of career development initiatives within STEM recruitment and retention programming. The purpose of the present study was to incorporate demographic variables, math performance, and career development–related factors into predictive models of STEM retention with a sample of undergraduate students within a STEM recruitment and retention program. The resulting two models accurately predicted first-year to second-year retention with 73.4% of the cases and accurately predicted first-year to third-year retention with 70.0% of the cases. Based on the results, the researchers provide a rationale for STEM career programming in K–12 and higher education settings and for the inclusion of career development and career counseling in STEM education programming.
Keywords: STEM, retention, career development, career counseling, undergraduate student
The United States lacks an adequate number of workers to keep up with the demand for trained workers in science, technology, engineering, and mathematics (STEM) fields (National Center for Science and Engineering Statistics [NCSES], 2017; National Science Board, 2018; Sithole et al., 2017). Researchers have pointed to the overall stagnancy of undergraduate students declaring and completing STEM degrees (Carnevale, Smith, & Melton, 2011; Doerschuk et al., 2016; Sithole et al., 2017). Additionally, underrepresentation is a problem for racial and ethnic minorities and females in STEM fields (NCSES, 2017). Because of these disparities, universities have developed programs centered on recruitment and retention of STEM undergraduates (Bouwma-Gearhart, Perry, & Presley, 2014; Dagley et al., 2016; Schneider, Bickel, & Morrison-Shetlar, 2015) and both government and private entities invest billions of dollars annually toward STEM initiatives at the K–12 and higher education levels (Carnevale et al., 2011). However, many of these endeavors have failed to incorporate components centered on career development or career planning.
The National Career Development Association (2015) defined career development as “the sequence of career-related choices and transitions made over the life span” (p. 4) and career planning as a structured process through which a person makes decisions and plans for a future career. Career development activities, such as structured career planning courses, have shown efficacy with general undergraduate populations (Osborn, Howard, & Leierer, 2007; Reardon, Melvin, McClain, Peterson, & Bowman, 2015) but have been studied less commonly with STEM-specific undergraduate populations (Belser, Prescod, Daire, Dagley, & Young, 2017, 2018; Prescod, Daire, Young, Dagley, & Georgiopoulos, in press). In the present study, researchers examined a STEM recruitment and retention program that did include a career planning course. More specifically, the research team sought to investigate relationships between demographics (e.g., gender, ethnicity), math scores, and various aspects of the undergraduate STEM program and student retention in the first 2 years of college.
Gender, Ethnicity, and STEM
Gender disparities are a common sight within STEM degree programs and the larger STEM workforce (NCSES, 2017). Females who are interested in math and science are more likely to be tracked into non-diagnosing health practitioner fields, such as nursing (ACT, 2018; NCSES, 2017). Some researchers have pointed to the K–12 arena as the root of these gender disparities that permeate undergraduate programs and STEM professions (Mansfield, Welton, & Grogan, 2014), whereas others have identified specific problems, such as differences in math and science course completion over time (Chen & Soldner, 2013; Riegle-Crumb, King, Grodsky, & Muller, 2012), stereotype threat (Beasley & Fischer, 2012), and STEM confidence (Litzler, Samuelson, & Lorah, 2014). As a result, existing predictive models typically indicate a lower likelihood of females completing a STEM degree compared to male students (Cundiff, Vescio, Loken, & Lo, 2013; Gayles & Ampaw, 2014).
Similarly, disparities in STEM degree completion and STEM job attainment exist between ethnic groups (NCSES, 2017; Palmer, Maramba, & Dancy, 2011). Although progress has been made in degree attainment in certain STEM areas, other areas have stagnated or are declining in participation by ethnic minority students (Chen & Soldner, 2013; NCSES, 2017). Foltz, Gannon, and Kirschmann (2014) identified protective factors for minority students in STEM, such as receiving college-going expectations from home, establishing connections with STEM faculty members (particularly those of color), and developing connections with other minority students in STEM majors; however, the disparities in STEM programs help perpetuate a cycle of many students not being exposed to these protective factors. The intersectionality of ethnicity and gender in STEM fields has become a topic producing interesting findings (Riegle-Crumb & King, 2010). In addition to observing disparities across ethnic groups, researchers have observed disparities within ethnic groups based on gender (Beasley & Fischer, 2012; Cundiff et al., 2013; Riegle-Crumb & King, 2010). Specifically with males of color, predictive models have been inconclusive, with some showing a higher likelihood of completing a STEM degree (Riegle-Crumb & King, 2010) and others showing a lower likelihood (Cundiff et al., 2013; Gayles & Ampaw, 2014).
Mathematics and STEM
The SAT is one of the most widely used college admissions tests (CollegeBoard, 2018). Researchers have correlated the math sub-score with undergraduate math and science classes within the first year, indicating that higher SAT math scores indicate a higher probability of higher course grades in math and science courses (Wyatt, Remigio, & Camara, 2012). Additionally, researchers have identified SAT scores as predictors of academic success and university retention (Crisp, Nora, & Taggart, 2009; Le, Robbins, & Westrick, 2014; Mattern & Patterson, 2013; Rohr, 2012). Despite its wide use in higher education admissions, the SAT may not be free from bias. Numerous scholars have highlighted potential test bias, particularly against ethnic minorities (Dixon-Román, Everson, & McArdle, 2013; Lawlor, Richman, & Richman, 1997; Toldson & McGee, 2014). Nevertheless, its wide use makes it a prime instrument for research.
In addition to the SAT scores, researchers also have demonstrated that taking higher-level math courses and having higher math self-efficacy translate to better outcomes within STEM majors (Carnevale et al., 2011; Chen & Soldner, 2013; Nosek & Smyth, 2011). Specifically, taking calculus-based courses in high school correlated with retention in STEM majors (Chen & Soldner, 2013). Nosek and Smyth (2011) found connections between gender and internalized math variables, such as warmth for math, identification with math, and self-efficacy; females across the life span showed lower levels of each of these variables, but the authors did not test these against retention outcomes in STEM majors. However, one could hypothesize that having lower levels of warmth toward math and not being able to identify with math would likely impact one’s career decisions, particularly related to math and science fields.
Career Interventions and STEM
Career theory can provide for understanding one’s interest in STEM fields (Holland, 1973), one’s exposure to STEM fields (Gottfredson, 1981), and one’s beliefs or expectations about the process of choosing a STEM field (Lent, Brown, & Hackett, 2002; Peterson, Sampson, Lenz, & Reardon, 2002). However, career interventions, such as a career planning class, are more likely to make a direct impact on career outcomes with undergraduates. In one review of research on undergraduate career planning courses, more than 90% of the courses produced some measurable positive result for students, such as increased likelihood of completing a major, decreased negative career thinking, and increased career self-efficacy (Reardon & Fiore, 2014). Other researchers have reported similar results with generic undergraduate career planning courses (Osborn et al., 2007; Saunders, Peterson, Sampson, & Reardon, 2000).
Researchers have studied structured career planning courses specific to STEM majors with much less frequency. In one such study, Prescod and colleagues (in press) found that students who took a STEM-focused career planning course scored lower on a measure of negative career thinking at the end of the semester. In a similar study, STEM-interested students in a STEM-focused career planning course had lower posttest scores on a measure of negative career thinking than declared STEM majors at the end of the same semester (Belser et al., 2018). Additionally, in a pilot study, Belser and colleagues (2017) found that greater reductions in negative career thinking predicted higher odds of being retained in a STEM major from the first to second year of college; in this same study, the authors found that students who participated in a STEM-focused career planning course were more likely to be retained in a STEM major than students in an alternative STEM course. Researchers have not given ample attention to determining how career planning and other career variables fit into predictive models of retention in STEM majors.
Statement of the Problem and Hypotheses
As previously noted, prior researchers have paid limited attention to developing predictive models that incorporate career development variables along with demographics and math performance. Developing effective predictive models has implications for researchers, career practitioners, higher education professionals, and the STEM workforce. To this end, the researchers intend to test two such models related to retention in STEM majors using the following hypotheses:
Hypothesis 1: First-year to second-year undergraduate retention in STEM majors can be predicted by ethnicity, gender, initial major, math placement–algebra scores, SAT math scores, STEM course participation, and Career Thoughts Inventory (CTI) change scores.
Hypothesis 2: First-year to third-year undergraduate retention in STEM majors can be predicted by ethnicity, gender, initial major, math placement–algebra scores, SAT math scores, STEM course participation, and CTI change scores.
Methods
In this study, researchers examined multi-year retention data for students in a STEM recruitment and retention program at a large research university in the Southeastern United States and utilized a quasi-experimental design with non-equivalent comparison groups (Campbell & Stanley, 1963; Gall, Gall, & Borg, 2007). Because this study was part of a larger research project, Institutional Review Board approval was already in place.
The COMPASS Program
The COMPASS Program (Convincing Outstanding Math-Potential Admits to Succeed in STEM; Dagley et al., 2016) is a National Science Foundation–funded project that seeks to recruit and retain undergraduate students in STEM majors. To enter the program, students must have a minimum SAT math score of 550, an undeclared major at the time of applying to the university and program, and an expressed interest in potentially pursuing a STEM degree. However, some students accepted to the COMPASS Program declare a STEM major between the time that they are accepted into the COMPASS Program and the first day of class, creating a second track of students who were initially uncommitted to a major at the time of application. Students in both tracks have access to math and science tutoring in a program-specific center on campus, are matched with undergraduate mentors from STEM majors, have access to cohort math classes for students within the program, and can choose to live in a residence hall area designated for COMPASS participants. Depending on which COMPASS track students are in, they either take a STEM-focused career planning course or a STEM seminar course during their first semester.
COMPASS participants who started college without a declared major take a STEM-focused career planning class in their first semester. The activities of this course include a battery of career assessments and opportunities to hear career presentations from STEM professionals, visit STEM research labs, and attend structured career planning activities (e.g., developing a career action plan, résumé and cover letter writing, small group discussions). The first author and fourth author served as instructors for this course, and both were counselor education doctoral students at the time.
Participants who had declared a STEM major between the time they were accepted into the COMPASS Program and the first day of class took a STEM seminar course instead of the career planning class. The structure of this course included activities designed to help students engage with and be successful in their selected STEM majors, including presentations on learning styles and strategies, time management, study skills, professional experiences appropriate for STEM majors, and strategies for engaging in undergraduate research. Guest speakers for the class focused more on providing students with information about how to be successful as a STEM student. The course did not include career planning or career decision-making activities specifically geared toward helping students decide on a major or career field. A science education doctoral student served as the instructor of record for the course, with graduate students from various STEM fields serving as teaching assistants.
Participants
The university’s Institutional Knowledge Management Office provided demographic data on program participants. Table 1 displays descriptive data for participants, organized by second-year retention data (i.e., retention from the first year of college to the second year of college, for Hypothesis 1) and third-year retention data (i.e., retention from the first year of college to the third year of college, for Hypothesis 2). The frequencies for the subcategories were smaller for the third-year retention data (Hypothesis 2) because fewer participants had matriculated this far during the life of the project. Table 1 also breaks down each subset of the data based on which students were retained in a STEM major and which were not retained.
Table 1
Descriptive Statistics for Categorical Variables
|
Second-Year Retention Descriptives |
Third-Year Retention Descriptives |
| Variables |
Retained |
Not Retained |
Total |
Retained |
Not Retained |
Total |
|
n |
%a |
n |
%b |
n |
%c |
n |
%a |
n |
%b |
n |
%c |
| Gender |
|
|
|
|
|
|
|
|
|
|
|
|
| Male |
159 |
58.9 |
74 |
46.5 |
233 |
54.3 |
72 |
55.8 |
65 |
44.8 |
137 |
50.0 |
| Female |
111 |
41.1 |
85 |
53.5 |
196 |
45.7 |
57 |
44.2 |
80 |
55.2 |
137 |
50.0 |
| Total |
270 |
100.0 |
159 |
100.0 |
429 |
100.0 |
129 |
100.0 |
145 |
100.0 |
274 |
100.0 |
| Ethnicity |
|
|
|
|
|
|
|
|
|
|
|
|
| Caucasian/White |
147 |
54.4 |
100 |
62.9 |
247 |
57.6 |
66 |
51.2 |
85 |
58.6 |
151 |
55.1 |
| African Am./Black |
31 |
11.5 |
16 |
10.1 |
47 |
11.0 |
16 |
12.4 |
18 |
12.4 |
34 |
12.4 |
| Hispanic |
57 |
21.1 |
34 |
21.4 |
91 |
21.2 |
29 |
22.5 |
32 |
22.1 |
61 |
22.3 |
| Asian/Pacific Islander |
24 |
8.9 |
4 |
2.5 |
28 |
6.5 |
10 |
7.8 |
5 |
3.4 |
15 |
5.5 |
| Other |
11 |
4.1 |
5 |
3.1 |
16 |
3.7 |
8 |
6.2 |
5 |
3.4 |
13 |
4.7 |
| Total |
270 |
100.0 |
159 |
100.0 |
429 |
100.0 |
129 |
100.0 |
145 |
100.0 |
274 |
100.0 |
| Course |
|
|
|
|
|
|
|
|
|
|
|
|
| Career Planning |
137 |
50.7 |
120 |
75.5 |
257 |
59.9 |
76 |
58.9 |
112 |
77.2 |
188 |
68.6 |
| STEM Seminar |
133 |
49.3 |
39 |
24.5 |
172 |
40.1 |
53 |
41.1 |
33 |
22.8 |
86 |
31.4 |
| Total |
270 |
100.0 |
159 |
100.0 |
429 |
100.0 |
129 |
100.0 |
145 |
100.0 |
274 |
100.0 |
| Initial Major |
|
|
|
|
|
|
|
|
|
|
|
|
| Undeclared |
130 |
48.1 |
72 |
45.3 |
202 |
47.1 |
65 |
50.4 |
63 |
43.4 |
128 |
46.7 |
| STEM |
124 |
45.9 |
40 |
25.2 |
164 |
38.2 |
55 |
42.6 |
39 |
26.9 |
94 |
34.3 |
| Non-STEM |
16 |
5.9 |
47 |
29.6 |
63 |
14.7 |
9 |
7.0 |
43 |
29.7 |
52 |
19.0 |
| Total |
270 |
100.0 |
159 |
100.0 |
429 |
100.0 |
129 |
100.0 |
145 |
100.0 |
274 |
100.0 |
Note. a = percentage of the Retained group. b = percentage of the Not Retained group. c = percentage of the Total group.
Gender representation within the two samples was split relatively evenly, with female participants represented at a higher rate in the sample than in the larger population of STEM undergraduates and at a higher rate than STEM professionals in the workforce. Both samples were predominantly Caucasian/White, with no other ethnic group making up more than one-fourth of either sample individually; these ethnicity breakdowns were reflective of the university’s undergraduate population and somewhat reflective of STEM disciplines. The students who took the STEM-focused career planning course accounted for a larger percentage of both total samples and also of the not-retained groups. Regarding initial major, the largest percentage of students fell within the initially undeclared category, with the next largest group being the initially STEM-declared group (these students officially declared a STEM major but were uncommitted with their decision).
The researchers conducted an a priori power analysis using G*Power 3 (Cohen, 1992; Faul, Erdfelder, Lang, & Buchner, 2007), and the overall samples of 429 and 271 were sufficient for the binary logistic regression. With logistic regression, the ratio of cases in each of the dependent outcomes (retained or not retained) to the number of independent variable predictors must be sufficient (Agresti, 2013; Hosmer, Lemeshow, & Sturdivant, 2013; Tabachnick & Fidell, 2013). Following Peduzzi, Concato, Kemper, Holford, and Feinstein’s (1996) rule of 10 cases per outcome per predictor, the samples were sufficient for all independent variables except ethnicity, which had multiple categories with fewer than 10 cases. However, Field (2009) and Vittinghoff and McCulloch (2006) recommended having a minimum of five cases per outcome per predictor, which the sample achieved for all independent variables.
Variables and Instruments
The analysis included 10 independent variables within the logistic regression models. The university’s Institutional Knowledge Management Office (IKMO) provided data for the four categorical variables displayed in Table 1 (gender, ethnicity, course, and initial major). Four of the independent variables represented the participants’ total and subscale scores on the CTI, which students completed in either the career planning course or the STEM seminar course. The other two independent variables were participants’ scores on the SAT math subtest and the university’s Math Placement Test–Algebra subscale; the IKMO provided these data as well.
Career Thoughts Inventory (CTI). The CTI includes 48 Likert-type items and seeks to measure respondents’ levels of negative career thinking (Sampson, Peterson, Lenz, Reardon, & Saunders, 1996a, 1996b). To complete the CTI, respondents read the 48 statements about careers and indicate how much they agree using a 4-point scale (strongly disagree to strongly agree). The CTI provides a total score and scores for three subscales: (a) Decision Making Confusion (DMC); (b) Commitment Anxiety (CA); and (c) External Conflict (EC). Completing the instrument yields raw scores for the assessment total and each of the three subscales, and a conversion table printed on the test booklet allows respondents to convert raw scores to T scores. Higher raw scores and T scores indicate a higher level of problematic thinking in each respective area, with T scores at or above 50 indicating clinical significance. For the college student norm group, internal consistency alpha coefficients were .96 for the total score and ranged from .77 to .94 for the three subscales (Sampson et al., 1996a, 1996b). With the sample in the present study, the researchers found acceptable alpha coefficients that were comparable to the norm group. The researchers used CTI change scores as predictors, calculated as the change in CTI total and subscale scores from the beginning to the end of either the career planning class or the STEM seminar class.
SAT Math. High school students take the SAT as a college admissions test typically in their junior and/or senior years (CollegeBoard, 2018). Although the SAT has four subtests, the researchers only used the math subtest in the present study. The math subtest is comprised of 54 questions or tasks in the areas of basic mathematics knowledge, advanced mathematics knowledge, managing complexity, and modeling and insight (CollegeBoard, 2018; Ewing, Huff, Andrews, & King, 2005). In a validation study of the SAT, Ewing et al. (2005) found an internal consistency alpha coefficient of .92 for the math subtest and alpha coefficients ranging from .68 to .81 for the four math skill areas. The researchers were unable to analyze psychometric properties of the SAT math test with the study sample because the university’s IKMO only provided composite and subtest total scores, rather than individual item responses.
Math Placement Test–Algebra Subtest. The Math Placement Test is a university-made assessment designed to measure mathematic competence in algebra, trigonometry, and pre-calculus that helps the university place students in their first math course at the university. All first-time undergraduate students at the university are required to take the test; when data collection began, the mandatory completion policy was not yet in place, so some earlier participants had missing data in this area. The test is structured so that all respondents first take the algebra subtest and if they achieve 70% accuracy, they move to the trigonometry and pre-calculus subtests. Similar to the SAT, the researchers were unable to analyze psychometric properties of the test because the IKMO provided only composite and subtest total scores.
Procedure
Because the dependent variables (second-year retention and third-year retention) were dichotomous (i.e., retained or not retained), the researchers used the binary logistic regression procedure within SPSS Version 24 to analyze the data (Agresti, 2013; Hosmer et al., 2013; Tabachnick & Fidell, 2013). The purpose of binary logistic regression is to test predictors of the binary outcome by comparing the observed outcomes and the predicted outcomes first without any predictors and then with the chosen predictors (Hosmer et al., 2013). The researchers used a backward stepwise Wald approach, which enters all predictors into the model and removes the least significant predictors one by one until all of the remaining predictors fall within a specific p value range (Tabachnick & Fidell, 2013). The researchers chose to set the range as p ≤ .20 based on the recommendation of Hosmer et al. (2013).
Preliminary data analysis included identifying both univariate and multivariate outliers, which were removed from the data file; conducting a missing data analysis; and testing the statistical assumptions for logistic regression. There were no missing values for categorical variables, but the assessment variables (CTI, SAT, and Math Placement Test) did have missing values. Results from Little’s (1988) MCAR test in SPSS showed that these data were not missing completely at random (Chi-square = 839.606, df = 161, p < .001). The researchers chose to impute missing values using the Expectation Maximization procedure in SPSS (Dempster, Laird, & Rubin, 1977; Little & Rubin, 2002). The data met the statistical assumptions of binary logistic regression related to multicollinearity and linearity in the logit (Tabachnick & Fidell, 2013). As previously discussed, the data also sufficiently met the assumption regarding the ratio of cases to predictor variables, with the exception of the ethnicity variable; after removing outliers, the Asian/Pacific Islander subcategory in the non-retained outcome had only four cases, violating the Peduzzi et al. (1996) and Field (2009) recommendation of having at least five cases. However, because the goal was to test the ethnicity categories separately rather than collapsing them to fit the recommendation, and because Hosmer et al. (2013) noted this was a recommendation and not a rule, the researchers chose to keep the existing categories, noting the potential limitation when interpreting this variable.
Results
The sections that follow provide the results from each of the hypotheses and interpretation of the findings.
Hypothesis 1
Hypothesis 1 stated that the independent variables could predict undergraduate STEM retention from Year 1 to Year 2. As stated previously, the backward stepwise Wald approach involved including all predictors initially and then removing predictors one by one based on p value until all remaining predictors fell within the p ≤ .20 range. This process took five steps, resulting in the removal of four variables with p values greater than .20: (a) CTI Commitment Anxiety Change, (b) CTI External Conflict Change, (c) Gender, and (d) CTI Decision Making Confusion Change, respectively. The model yielded a Chi-square value of 91.011 (df = 10, p < .001), a -2 Log likelihood of 453.488, a Cox and Snell R-square value of .198, and a Nagelkerke R-square value of .270. These R-square values indicate that the model can explain between approximately 20% and 27% of the variance in the outcome. The model had a good fit with the data, as evidenced by the Hosmer and Lemeshow Goodness of Fit Test (Chi-square = 6.273, df = 8, p = .617). The final model accurately predicted 73.4% of cases across groups; however, the model predicted the retained students more accurately (89.6% of cases) than the non-retained cases (45.8% of cases).
Table 2 explains how each of the six variables retained in the model contributed to the final model. The odds ratio represents an association between a particular independent variable and a particular outcome, or for this study, the extent that the independent variables predict membership in the retained outcome group. With categorical variables, this odds ratio represents the likelihood that being in a category increases the odds of being in the retained group over the reference category (i.e., African American/Black participants were 1.779 times more likely to be in the retained group than White/Caucasian students, who served as the reference category). With continuous variables, odds ratios represent the likelihood that quantifiable changes in the independent variables predict membership in the retained group (i.e., for every unit increase in SAT math score, the odds of being in the retained group increase 1.004 times). The interpretation of odds ratios allows them to be viewed as a measure of effect size, with odds ratios closer to 1.0 having a smaller effect (Tabachnick & Fidell, 2013).
Table 2
Variables in the Equation for Hypothesis 1
|
|
|
|
|
95% C.I. for O.R. |
| Variable |
B |
S.E. |
Wald |
O.R. |
Lower |
Upper |
| Ethnicity |
|
|
10.319* |
|
|
|
| Ethnicity (African American/Black) |
.576 |
.393 |
2.148 |
1.779 |
.823 |
3.842 |
| Ethnicity (Hispanic) |
.068 |
.290 |
.054 |
1.070 |
.606 |
1.889 |
| Ethnicity (Asian/Pacific Islander) |
1.889 |
.637 |
8.803** |
6.615 |
1.899 |
23.041 |
| Ethnicity (Other) |
.258 |
.714 |
.131 |
1.295 |
.320 |
5.246 |
| Initial Major |
|
|
35.824*** |
|
|
|
| Initial Major (Declared STEM) |
.412 |
.265 |
2.422 |
1.511 |
.899 |
2.539 |
| Initial Major (Declared Non-STEM) |
-1.944 |
.375 |
26.905*** |
.143 |
.069 |
.298 |
| STEM Seminar (Non-CP) |
.850 |
.258 |
10.885** |
2.340 |
1.412 |
3.879 |
| SAT Math |
.004 |
.002 |
2.411 |
1.004 |
.999 |
1.008 |
| Math Placement–Algebra |
.002 |
.002 |
2.080 |
1.002 |
.999 |
1.005 |
| CTI Total Change |
.017 |
.007 |
5.546* |
1.017 |
1.003 |
1.032 |
| Constant |
-2.994 |
1.378 |
4.717 |
.050 |
|
|
Note: B = Coefficient for the Constant; S.E. = Standard Error; O.R. = Odds Ratio; * p < .05; ** p < .01; *** p < .001.
With logistic regression, the Wald Chi-square test allows the researcher to determine a coefficient’s significance to the model (Tabachnick & Fidell, 2013). Based on this test, Initial Major was the most significant predictor to the model (p < .001). Students in the initially Declared STEM category were 1.511 times more likely to be in the retained group than those in the initially Undeclared category (the reference category); the odds of being in the retained group decreased by a factor of .143 for students in the initially Declared Non-STEM group. The STEM course was the predictor with the second most statistical significance (p < .01), with students in the STEM seminar class being 2.340 times more likely to be in the retained outcome than those in the career planning class. The CTI Total Change score was statistically significant (p < .05), indicating that for every unit increase in CTI Total Change score (i.e., the larger the decrease in score from pretest to posttest), the odds of being in the retained group increase by a factor of 1.017. Ethnicity was a statistically significant predictor (p < .05), with each subcategory having higher odds of being in the retained group than the White/Caucasian group; however, the researchers caution the reader to read these odds ratios for ethnicity with caution because of the number of cases in some categories. SAT Math and Math Placement–Algebra were not statistically significant, but still fell within the recommended inclusion range (p < .20).
Hypothesis 2
Hypothesis 2 stated that the independent variables could predict undergraduate STEM retention from Year 1 to Year 3. As stated previously, the backward stepwise Wald approach involved including all predictors initially and then removing predictors one by one based on p value until all remaining predictors fell within the p ≤ .20 range. This process took six steps, resulting in the removal of five variables with p values greater than .20: (a) CTI Commitment Anxiety Change, (b) CTI Decision Making Confusion Change, (c) Gender, (d) CTI External Conflict Change, and (e) CTI Total Change, respectively. The model yielded a Chi-square value of 55.835 (df = 9, p < .001), a -2 Log likelihood of 307.904, a Cox and Snell R-square value of .191, and a Nagelkerke R-square value of .255. These R-square values indicate that the model can explain between approximately 19% and 26% of the variance in the outcome. The model had a good fit with the data, as evidenced by the Hosmer and Lemeshow Goodness of Fit Test (Chi-square = 9.187, df = 8, p = .327). The model accurately predicted 70.0% of cases across groups. In this analysis, the model predicted the non-retained students more accurately (72.7% of cases) than the retained cases (66.9% of cases).
Table 3 explains how the variables within the model contributed to the final model. Based on the Wald test, Initial Major was the most significant predictor to the model (p < .001). Students in the initially Declared STEM category were 1.25 times more likely to be in the retained group than those in the initially Undeclared category (the reference category); the odds of being in the retained group decreased by a factor of .167 for students in the initially Declared Non-STEM group. The Math Placement–Algebra variable was statistically significant (p < .05), and the odds ratios indicated that for every unit increase in Math Placement–Algebra test score, the odds of being in the retained group are 1.005 higher. The STEM course variable was slightly outside the statistically significant range but fell within the inclusion range, with students in the STEM seminar class being 2.340 times more likely to be in the retained outcome than students in the career planning class. SAT Math was not statistically significant but still fell within the recommended inclusion range (p < .20). Ethnicity also was not a statistically significant predictor but fell within the inclusion range, with each subcategory having higher odds of being in the retained group than the White/Caucasian group; however, the researchers caution the reader to read these odds ratios for ethnicity with caution because of the number of cases in some categories.
Table 3
Variables in the Equation for Hypothesis 2
|
|
|
|
|
95% C.I. for O.R. |
| Variable |
B |
S.E. |
Wald |
O.R. |
Lower |
Upper |
| Ethnicity |
|
|
6.445 |
|
|
|
| Ethnicity (African American/Black) |
.542 |
.448 |
1.467 |
1.719 |
.715 |
4.134 |
| Ethnicity (Hispanic) |
.243 |
.349 |
.484 |
1.275 |
.643 |
2.528 |
| Ethnicity (Asian/Pacific Islander) |
1.636 |
.698 |
5.494* |
5.137 |
1.307 |
20.185 |
| Ethnicity (Other) |
.403 |
.684 |
.347 |
1.497 |
.391 |
5.725 |
| Initial Major |
|
|
17.362** |
|
|
|
| Initial Major (Declared STEM) |
.223 |
.328 |
.460 |
1.250 |
.656 |
2.379 |
| Initial Major (Declared non-STEM) |
-1.792 |
.468 |
14.664** |
.167 |
.067 |
.417 |
| STEM Seminar (Non-CP) |
.588 |
.323 |
3.327 |
1.801 |
.957 |
3.389 |
| SAT Math |
.004 |
.003 |
2.536 |
1.004 |
.999 |
1.010 |
| Math Placement–Algebra |
.005 |
.002 |
5.449* |
1.005 |
1.001 |
1.009 |
| Constant |
-2.994 |
1.378 |
4.717 |
.050 |
|
|
Note: B = Coefficient for the Constant; S.E. = Standard Error; O.R. = Odds Ratio; * p < .05; *** p < .001.
Discussion
The researchers sought to determine the degree to which a set of demographic variables, math scores, and career-related factors could predict undergraduate retention in STEM majors. Based on descriptive statistics, the participants are remaining in STEM majors at a higher rate than other nationwide samples (Chen & Soldner, 2013; Koenig, Schen, Edwards, & Bao, 2012). The sample
in this study was quite different based on gender than what is commonly cited in the literature; approximately 46% of the study’s sample was female, whereas the NCSES (2017) reported that white females made up approximately 31% of those in STEM fields, with minority females lagging significantly behind. The present study’s sample was more in line with national statistics with regard to ethnicity (NCSES, 2017; Palmer et al., 2011).
With Hypothesis 1, the researchers sought to improve on a pilot study (Belser et al., 2017) that did not include demographics or math-related variables. Adding these additional variables did improve the overall model fit and the accuracy of predicting non-retained students, but slightly decreased the accuracy of predicting retained students, as compared to the Belser et al. (2017) model. In addition to improving the model fit, adding in additional variables reversed the claim by Belser et al. (2017) that students in the STEM-focused career planning class were more likely to be retained than the STEM seminar students. In the present study, the STEM seminar students, who declared STEM majors prior to the first day of college, were more likely to be retained in STEM majors, which is in line with prior research connecting intended persistence in a STEM major to observed retention (Le et al., 2014; Lent et al., 2016).
With Hypothesis 2, the researchers sought to expand on the Belser et al. (2017) study by also predicting retention one year farther, into the third year of college. In this endeavor, the analysis yielded a model that still fit the data well. However, this model was much more accurate in predicting the non-retained students and was slightly less accurate in predicting the retained students, with the overall percentage of correct predictions similar to Hypothesis 1. This finding indicates that the included predictors may provide a more balanced ability to predict long-term retention in STEM majors than in just the first year. The initial major and STEM course variables performed similarly as in Hypothesis 1, and as such, similarly to prior research (Le et al., 2014; Lent et al., 2016).
Although sampling issues warrant the reader to read ethnicity results with caution, ethnicity did show to be a good predictor of retention in STEM majors with both Hypotheses 1 and 2. More noteworthy, the African American/Black and Hispanic students had higher odds of being retained. This is inconsistent with most research that shows underrepresented minorities as less likely to be retained in STEM majors (Chen & Soldner, 2013; Cundiff et al., 2013; Gayles & Ampaw, 2014); however, at least one study has previously found results in which ethnic minority students were more likely to be retained in STEM majors (Riegle-Crumb & King, 2010).
Gender was removed as a predictor from both models because of its statistical non-significance. Prior research has shown that females are less likely to be retained in STEM majors (Cundiff et al., 2013; Gayles & Ampaw, 2014; Riegle-Crumb et al., 2012), which separates this sample from prior studies. However, the COMPASS sample did have a larger representation of females than typically observed. Moreover, the COMPASS Program has been mindful of prior research related to gender and took steps to address gender concerns in program development (Dagley et al., 2016).
The continuous variables retained in the models showed only a mild effect on predicting STEM retention. The SAT Math and Math Placement–Algebra scores did perform consistently with prior research, in which higher math scores related to higher odds of retention (CollegeBoard, 2012; Crisp et al., 2009; Le et al., 2014; Mattern & Patterson, 2013; Rohr, 2012). The CTI variables that were retained in the models performed in line with the Belser et al. (2017) pilot study specific to STEM majors and with prior research examining negative career thoughts in undergraduate retention in other majors (Folsom, Peterson, Reardon, & Mann, 2005; Reardon et al., 2015).
Limitations and Implications
The present study has limitations, particularly with regard to research design, sampling, and instrumentation. First, the researchers used a comparison group design rather than a control group, and as such, there were certain observable differences between the two groups. Not having a control group limits the researchers’ ability to make causal claims regarding the predictor variables or the STEM career intervention. The researchers also only included a limited number of predictors; the inclusion of additional variables may have strengthened the models. Although the sample size was sufficient based on the a priori power analysis, the low number of participants in some of the categories may have resulted in overfitting or underfitting within the models. Finally, the researchers were not able to test psychometric properties of the SAT Math subtest or the Math Placement–Algebra subtest with this sample because of not having access to the participants’ item responses for each. The researchers attempted to mitigate limitations as much as possible and acknowledge that they can and should be improved upon in future research.
Future research in this area would benefit from the inclusion of a wider variety of predictor variables, such as math and science self-efficacy, outcome expectations, and internal processes observed with gender and ethnic minority groups (e.g., stereotype threat; Cundiff et al., 2013; Litzler et al., 2014). The researchers also recommend obtaining a larger representation of ethnic minority groups to ensure an adequate number of cases to effectively run the statistical procedure. Future researchers should consider more complex statistical procedures (e.g., structural equation modeling) and research designs (e.g., randomized control trials) to determine more causal relationships between predictors and the outcome variables.
Because the results of this study indicate that a more solidified major selection is associated with higher odds of retention in STEM majors, university career professionals and higher education professionals should strive to develop programming that helps students decide on a major earlier in their undergraduate careers. Structured career development work, often overlooked in undergraduate STEM programming, may be one such appropriate strategy. Additionally, any undergraduate STEM programming must be sensitive to demographic underrepresentation in STEM majors and the STEM workforce and should take steps to provide support for students in these underrepresented groups.
Similar to work with undergraduates, this study’s results provide a rationale for school counselors to engage students in STEM career work so that they can move toward a solidified STEM major prior to enrolling in college. The industry-specific career development work discussed within this study is just as important, if not more important, for students in K–12 settings. Moreover, school counselors, through their continued access to students, can serve as an access point for researchers to learn more about the STEM career development process at an earlier stage of the STEM pipeline. All of these endeavors point to the need for counselor educators to better prepare school counselors, college counselors, and career counselors to do work specifically with STEM and to become more involved in STEM career research.
In the present study, the researchers built upon prior research in the area of STEM retention to determine which variables can act as predictors of undergraduate STEM retention. The binary logistic regression procedure yielded two models that provide insight on how these variables operate individually and within the larger model. Finally, the researchers identified some key implications for counselors practicing in various settings and for researchers who are interested in answering some of the key questions that still exist with regard to STEM career development and retention.
Conflict of Interest and Funding Disclosure
Data collected in this study was part of a dissertation study by the first author. The dissertation was awarded the 2018 Dissertation Excellence Award by the National Board for Certified Counselors.
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Christopher T. Belser, NCC, is an assistant professor at the University of New Orleans. M. Ann Shillingford is an associate professor at the University of Central Florida. Andrew P. Daire is a dean at Virginia Commonwealth University. Diandra J. Prescod is an assistant professor at Pennsylvania State University. Melissa A. Dagley is an executive director at the University of Central Florida. Correspondence can be addressed to Christopher Belser, 2000 Lakeshore Drive, Bicentennial Education Center Room 174, New Orleans, LA 70148, ctbelser@uno.edu.
Sep 1, 2018 | Volume 8 - Issue 3
Nayoung Kim, Glenn W. Lambie
To prevent school counselors from experiencing feelings of burnout, identifying relevant factors is important. The purpose of this article is to review studies investigating the constructs of burnout and occupational stress in school counseling samples. Eighteen published research articles fit the inclusion criteria for this review. The researchers identified external and internal variables relating to school counselor burnout, as well as protective and risk factors. The review identified that school counselors’ higher level of burnout correlated with having non-counseling duties, being assigned large caseloads, working in schools that did not meet adequate yearly progress (AYP) status, experiencing a lack of supervision, possessing greater emotion-oriented stress coping scores, providing fewer direct student services, and having greater perceived stress. In contrast, feelings of burnout among school counselors were mitigated when counselors received supervision, possessed higher task-oriented stress coping strategies, scored at higher levels of ego maturity, reported greater occupational support at their schools, had greater grit scores, and worked in schools that met AYP.
Keywords: burnout, occupational stress, school counselors, non-counseling duties, coping strategies
There are multiple definitions of burnout (e.g., Burke & Richardson, 2000; Stalker & Harvey, 2002); however, the primary consistent aspect of burnout is that it is a psychological phenomenon associated with job-related stress (Maslach, 2017). Burnout occurs when professionals are unable to meet their own needs, as well as their clients’ needs, in a high-pressure environment (Maslach, 2017). Freudenberger (1990) identified common symptoms of burnout, including negative changes in individuals’ (a) attitudes and decision making; (b) physiological states; (c) mental, emotional, and behavioral health; and (d) occupational motivation. Burnout has significant consequences, including compromised physical health, increased risk of mental health disorders (e.g., depression, substance abuse), poor job performance, absenteeism, occupational attrition, and low self-esteem (Maslach & Leiter, 2016). Burnout can also cause symptoms such as fatigue, exhaustion, and insomnia (Armon, Shirom, Shapira, & Melamed, 2008).
Burnout in School Counseling
Morse, Salyers, Rollins, Monroe-DeVita, and Pfahler (2012) identified that 21% to 67% of mental health professionals reported experiencing high levels of burnout, possibly because of dealing with high client caseloads (Ducharme, Knudsen, & Roman, 2007) or overall job effectiveness (Stalker & Harvey, 2002). In addition, Oddie and Ousley (2007) found that 21% to 48% of mental health workers reported experiencing high levels of emotional exhaustion. School counselors specifically are at risk for experiencing feelings of burnout because of their multiple job demands, including paperwork, parent conferences, school-wide testing, large caseloads, and requests from administrators (McCarthy & Lambert, 2008), and other factors such as role ambiguity and limited occupational support (Young & Lambie, 2007). The school counseling job environment, where “the demands of the work are high, but the resources to meet those demands are low” (Maslach & Goldberg, 1998, pp. 63–64), increases susceptibility to experiencing feelings of burnout (e.g., average student-to-counselor ratio being 491-to-1; National Center for Education Statistics, 2016). Stephan (2005) found that within a national sample of school counselors, 66% of middle school counselors scored at moderate to high levels of emotional exhaustion. Further, Wachter (2006) found that 20% of the school counselors in her investigation (N = 132) experienced feelings of burnout; 16% scored at moderate levels of burnout, and 4% scored at severe levels of burnout. Thus, many school counselors experience feelings of burnout that may influence their ability to provide ethical and effective counseling services to the students they serve.
School counselors may experience chronic fatigue, depersonalization, or feelings of hopelessness and leave their jobs because of the rigidity of school systems and limited support (Young & Lambie, 2007). In fact, counselors experiencing significant feelings of burnout provide reduced quality of service to their clientele because burnout relates to lower productivity, turnover intention, and a lowered level of job commitment (Maslach, Schaufeli, & Leiter, 2001). Because of the importance of preventing the burnout phenomenon, the American School Counselor Association’s (ASCA; 2016) ethical standards note that school counselors are responsible for maintaining their health, both physically and emotionally, and caring for their wellness to ensure their effective practice. The American Counseling Association’s (2014) ethical standards also state that school counselors have an ethical responsibility to monitor their feelings of burnout and remediate when their feelings potentially influence their ability to provide quality services to their stakeholders. To monitor burnout, counselors need to understand the symptoms of burnout and prevent it from happening, while maintaining their psychological well-being.
School counselors face challenges with their significant job demands (McCarthy, Van Horn Kerne, Calfa, Lambert, & Guzmán, 2010), such as large caseloads (Lambie, 2007) and extreme amounts of non-counseling duties (Moyer, 2011). In fact, school counselors report job stress and dissatisfaction when they are required to complete non-counseling duties, hindering their ability to work with their students (McCarthy et al., 2010). Examples of non-counseling duties include clerical tasks, such as scheduling students for classes; fair share, such as coordinating the standardized testing program; and administrative duties, such as substitute teaching (Scarborough, 2005). School counselors with large caseloads and high student-to-counselor ratios are more likely to experience increased feelings of burnout (Bardhoshi, Schweinle, & Duncan, 2014). Although ASCA (2015) recommends a student-to-counselor ratio of 250-to-1, the U.S. average student-to-counselor ratio is almost double the recommended proportion (491-to-1; National Center for Education Statistics, 2016).
Insufficient resources for school counselors and negative job perception increase their likelihood of experiencing feelings of burnout. Lower levels of principal support and lack of clinical supervision raise school counselors’ occupational stress (Bardhoshi et al., 2014; Moyer, 2011). For instance, school counselors with higher levels of role ambiguity are likely to experience burnout (Wilkerson & Bellini, 2006). School counselors experience role ambiguity when their responsibilities or the expected level of performance is not clearly identified (Coll & Freeman, 1997). As a result, school counselors report increased levels of stress (Culbreth, Scarborough, Banks-Johnson, & Solomon, 2005), leading to burnout and attrition from the profession (Wilkerson & Bellini, 2006). ASCA (2016) dictated that school counselors’ responsibilities include providing counseling services to students to support their development, which distinguishes them from other school personnel. With the importance of preventing burnout in school counseling, the purpose of this review is twofold: (a) to present identified factors influencing school counselors’ levels of burnout and (b) to offer strategies to assist school counselors in mitigating the feelings of burnout.
Research Examining Burnout in School Counseling
We began by conducting a formal search of electronic databases—PsycINFO, ERIC (EBSCOhost), and Academic Search Premiere—relating to school counselor burnout. The search term burnout was first used to analyze the research trend in the field. Both the search terms burnout and school counselors OR school counseling were used to collect any articles on the topic of school counselor burnout published between 2000 and 2018. An additional search was conducted with the terms occupational stress and school counselors OR school counseling to identify potential studies related to the topic in the same type of literature.
The following inclusion criteria were applied for our review: (a) investigations of school counselor burnout and occupational stress, (b) sample participants were school counselors in the United States, (c) the primary topic of the investigation was burnout and/or occupational stress, (d) articles were written in English, (e) articles were published in refereed journals, and (f) articles were published between 2000 and 2018. In addition, our review excluded literature reviews, editorials, and rejoinders. The abstracts of the articles meeting the criteria were examined and confirmed in order to be included in our review.
Our literature search based on the inclusion criteria produced 51 articles. As not all articles from the search satisfied the criteria, the articles were reviewed manually to evaluate whether they met the criteria, resulting in 35 articles not meeting criteria (e.g., conceptual articles, studies related to teachers) and 16 articles meeting all criteria. An additional literature search yielded two more studies meeting the inclusion criteria, identifying 18 studies in total. None of the identified research articles examined prevention or treatment interventions for burnout in school counselors. The 18 investigations had school counselor burnout or occupational stress as the constructs of interest. The research findings identified the positive relationships between school counselors’ burnout or occupational stress scores and the following factors: (a) non-counseling duties, (b) large caseloads, (c) not meeting adequate yearly progress (AYP) status (i.e., the expected amount of students’ academic growth per year based on the No Child Left Behind mandate [Minnesota House of Representatives, 2003]), (d) lack of supervision, (e) emotion-oriented stress coping scores, (f) grit, and (g) perceived stress.
Fourteen out of 18 articles provided information related to school counselor burnout (see Table 1 for quantitative studies and Table 2 for qualitative studies), and the other four studies investigated school counselors’ occupational stress (see Table 3). Occupational stress refers to the strain a person experiences when the perceived stress in a workplace outweighs their ability to cope (Decker & Borgen, 1993). Quantitative research methods were employed in 15 of the investigations, two used mixed-methods, and one study utilized a qualitative approach. For all 18 articles, the participants were current school counselors, and the number of participants ranged from 3 to 926. Effect sizes were categorized depending on the analysis into three groups (i.e., small, medium, and large) based on the effect size matrix from Sink and Stroh (2006), offering a better understanding of the results. Specifically, the effect size from independent samples t-test (2 groups; Cohen’s d) is interpreted as small for 0.2, medium for 0.5, and large for 0.8. For the effect size of other analyses listed in this review, including paired-samples t-tests (η2), multiple regression (R2), and analysis of variance (ANOVA; η2), 0.01 is considered as small, 0.06 as medium, and 0.14 as large.
Table 1
Summary of Quantitative/Mixed Studies Related to Professional School Counselor (PSC) Burnout
| Study |
Sample |
Variables |
Findings |
| Bain, Rueda, Mata-Villarreal, & Mundy (2011) |
PSCs in rural districts of South Texas
(N = 27)
Convenient Sampling |
Mental health awareness, the amount of time spent on academic advising
|
Feelings of burnout were reported by the majority of the PSCs (89%) in the study and many of them spent the greatest amount of time on administrative duties and the least on counseling. |
| Bardhoshi, Schweinle, & Duncan (2014) |
PSCs
(N = 212)
Random Sampling |
Non-counselor duties, school factors, five subscales of the CBI |
Non-counseling duties and school factors were associated with PSC burnout. Non-counseling duties explained the variance of the three burnout subscales: Exhaustion (11%; medium effect size), NWE (6%; medium effect size), and DPL (8%; medium effect size). Non-counseling duties and other factors (e.g., caseload, principal support) explained the variance of the four burnout subscales: Exhaustion (21%; large effect size), Incompetence (9%; medium effect size), NWE (49%; large effect size), and DPL (17%; large effect size). |
| Butler & Constantine (2005) |
PSCs
(N = 533)
Random Sampling |
Collective self-esteem, burnout, demographics |
Collective self-esteem explained 3% of the variance of PSC burnout (small effect size). In particular, PRCS (2%) and PUCS (1%) accounted for PA (both small effect sizes), and IICS explained 1% of feelings of DP and PA (both small effect sizes). Higher collective self-esteem was associated with lower PSC burnout. PSCs working in urban settings tended to have higher levels of burnout than the counterparts in other environmental settings. PSCs with experience of 20–29 years reported higher levels of burnout than the counterparts with 0–9 years of experience. PSCs with experience of 30 or more years reported higher levels of burnout than those with less experience. |
| Gnilka, Karpinski, & Smith (2015) |
PSCs
(N = 269)
Convenient Sampling |
Five subscales on the CBI |
Effect size differences were found between PSCs and other professionals in the counseling fields (Exhaustion, d = .26, small effect size; DC, d = -.50, medium effect size). Effect size differences were noted between PSCs and sexual offender and sexual abuse therapists (Exhaustion, d = .27, small effect size; DPL, d = -.23, small effect size; DC, d = -.82, large effect size). |
| Lambie (2007) |
PSCs
(N = 218)
Random Sampling
|
Ego maturity, three subscales on the MBI-HSS
|
PSCs with greater levels of ego maturity tended to have a higher level of PA than those with lower ego maturity. Ego maturity predicted PA (3.3%; small effect size). Occupational support and the subscales of burnout were correlated. Reported occupational support predicted EE (16%; large effect size), DP (12%; medium effect size), and PA (7.2%; medium effect size). |
| Limberg, Lambie, & Robinson (2016-2017) |
PSCs
(N = 437)
Random Sampling/
Purposive Sampling |
Altruistic motivation, altruistic behavior, burnout |
PSCs with greater levels of altruism had lower levels of EE and higher feelings of PA. PSC altruism explained 31.36% of the variance in EE (large effect size), and 29.16% of the variance in PA (large effect size). Self-Efficacy accounted for 14.4% of the variance in EE (large effect size) and 9% of the variance in PA (medium effect size). |
| Moyer (2011) |
PSCs
(N = 382)
Convenient Sampling |
Non-guidance activities, supervision, student-to-counselor ratios, five subscales of the CBI |
Non-guidance–related duties and clinical supervision were significant predictors of PSC burnout. Non-guidance duties (7.3%; medium effect size) and supervision (9%; medium effect size) predicted burnout.
|
| Mullen, Blount, Lambie, & Chae (2017) |
PSCs
(N = 750)
Random Sampling |
Perceived stress, burnout, job satisfaction |
Perceived stress predicted burnout positively (large effect size) and job satisfaction negatively (large effect size). Perceived stress and burnout predicted job satisfaction (large effect size). Burnout mediated the relationship between perceived stress and job satisfaction. |
| Mullen & Crowe (2018) |
PSCs
(N = 330)
Convenient Sampling |
Grit, stress, burnout |
Grit was negatively related to burnout (small effect size) and stress (small to medium effect size). |
| Mullen & Gutierrez (2016)
|
PSCs
(N = 926)
Random Sampling
|
Burnout, perceived stress, direct student services
|
Burnout attributed to direct counseling activities (12%; medium effect size), direct curriculum activities (5%; small to medium effect size), and percentage of time at work providing direct services to students (6%; medium effect size). |
| Wachter, Clemens, & Lewis (2008) |
PSCs
(N = 249)
Random Sampling |
Demographics, stakeholder involvement, lifestyle themes, burnout |
Burnout and lifestyle themes were associated. Perfectionism subscale was negatively related to burnout, and the Self-Esteem subscale was positively related to PSC burnout. About 15.1% of the variance in burnout was accounted for by the lifestyle themes of Self-Esteem and Perfectionism (large effect size). |
| Wilkerson & Bellini (2006)
|
PSCs in northeastern U.S.
(N = 78)
Systematic Random Sampling
|
Demographics, intrapersonal, and organizational factors; three subscales on the MBI-ES |
Demographic (age, counseling experience, supervision, and student/counselor ratio), intrapersonal, and organizational factors significantly accounted for the amount of the variance in each subscale of burnout, including EE (45%; large effect size), DP (30%; large effect size), and PA (42%; large effect size). |
| Wilkerson (2009)
|
PSCs
(N = 198)
Random Sampling |
Demographic and organizational stressors and individual coping strategies; three subscales on the MBI-ES |
Demographic factors (years of experience and student/counselor ratio), organizational stress, and coping styles explained the variance of each subscale of burnout including EE (49%; large effect size), DP (27%; large effect size), and PA (36%; large effect size).
|
Table 2
Summary of Qualitative/Mixed Studies Related to Professional School Counselor Burnout
| Study |
Sample |
Topic |
Identified Themes |
| Bain, Rueda, Mata-Villarreal, & Mundy (2011) |
PSCs in rural districts of South Texas (N = 27)
Convenient Sampling |
Helpful ways to better provide mental health services at school |
Having access to additional staff and additional education and awareness in terms of helpful ways to provide mental health services at their school. |
| Bardhoshi, Schweinle, & Duncan (2014) |
PSCs
(N = 252)
Random Sampling |
a) Their experience of burnout
b) The meaning of performing non-counseling duties |
a) Lack of time, budgetary constraints, lack of resources, lack of organizational support, etc.
b) Adverse personal/professional effects, a reality of the job, reframing the duties within the context of the job. |
| Sheffield & Baker (2005) |
Female PSCs
(N = 3)
Purposive Sampling |
Burnout experience |
Important beliefs, burnout feelings, burnout attitude, (lack of) collegial support. |
Table 3
Summary of Quantitative Studies Related to Professional School Counselor Occupational Stress
| Study |
Sample |
Variables |
Findings |
| Bryant & Constantine (2006) |
Female PSCs
(N = 133)
Random Sampling |
Role balance, job satisfaction, satisfaction with life, demographics |
Multiple role balance ability and job satisfaction positively predicted overall life satisfaction. Role balance and job satisfaction explained the variance of life satisfaction (41%; large effect size). |
| Culbreth, Scarborough, Banks-Johnson, & Solomon (2005) |
PSCs
(N = 512)Stratified Random Sampling |
Role conflict, role ambiguity, role incongruence, demographics |
Perceived match between the job expectations and actual experiences predicted role-related job stress, including role conflict (7.6%; medium effect size); role incongruence (19.7%; large effect size); and role ambiguity (8.3%; medium effect size). |
| McCarthy, Van Horn Kerne, Calfa, Lambert, & Guzmán (2010) |
PSCs in Texas
(N = 227) Convenient Sampling |
Demographics, job stress, resources and demands |
Job stress was different between the resourced, balanced, and demand groups. The effect sizes were large in the differences between the demand group and the resourced group (1.62; large effect size) and the balanced group (0.70; large effect size).
|
| Rayle (2006) |
PSCs
(N = 388)Convenient Sampling |
Demographics, mattering, job-related stress |
Thirty-five percent of the variance in overall job satisfaction was explained by mattering to others at work and job-related stress (large effect size). Mattering to others (19.36%; large effect size) and job-related stress (16.81%; large effect size) explained the variance in overall job satisfaction. |
Three instruments were used to measure levels of school counselor burnout, including: (a) the Maslach Burnout Inventory (MBI; Maslach, Jackson, & Leiter, 1996), (b) the Counselor Burnout Inventory (CBI; S. M. Lee et al., 2007), and (c) the Burnout Measure Short Version (BMS; Malach-Pines, 2005). Maslach and Jackson (1981) defined burnout with three dimensions: Emotional Exhaustion (EE), Depersonalization (DP), and reduced Personal Accomplishment (PA). Emotional exhaustion is to exhaust one’s capacity to continuously involve with clients (R. T. Lee & Ashforth, 1996). Not being able to respond to clients’ needs may cause counselors to distance themselves from their job emotionally and cognitively, which is defined as depersonalization. Lastly, having a lower sense of effectiveness may reduce feelings of personal accomplishment (Maslach et al., 2001). Four studies used the MBI-Education Survey (MBI-ES), which was designed for the education population, and another study utilized the MBI-Human Services Survey (MBI-HSS), in which the word students from the MBI-ES is substituted with recipients in a third of the items (Sandoval, 1989).
Four studies used the CBI, which is a 20-item instrument with five subscales, including:
(a) Exhaustion, (b) Incompetence, (c) Negative Work Environment (NWE), (d) Devaluing Client (DC), and (e) Deterioration in Personal Life (DPL). Exhaustion is the condition of being physically and emotionally exhausted by the duties of a counselor, and incompetence focuses on counselors’ feelings of being incompetent. While negative work environment refers to the stress caused by the working environment, devaluing client is related to being unable to establish emotional connectedness with clients. Finally, deterioration in personal life assesses the level of deterioration in a counselor’s personal life. Sample items include “I feel exhausted due to my work as a counselor,” and “I feel I have poor boundaries between work and my personal life.” The internal consistency of the CBI ranged from .73 to .85 (S. M. Lee et al., 2007). In addition, three studies used the BMS (Malach-Pines, 2005), a 10-item scale in which participants rate their answers to the question “When you think about your work overall, how often do you feel the following?” in seven prompts, including: “Trapped,” “Hopeless,” and “Helpless.” The BMS is adapted from the original version of the Burnout Measure (Pines & Aronson, 1988). The internal consistency of the BMS ranged from .85 to .87 (Malach-Pines, 2005).
Researchers investigated different factors relating to school counselor burnout within the 18 published articles. One of the studies provided descriptive statistics of school counselor burnout, comparing school counselors to other mental health professionals and showing how burnout symptoms may emerge (N = 269; Gnilka, Karpinski, & Smith, 2015). School counselors had greater levels of Exhaustion (d = .26; small effect size) and lower levels of DC (d = -.50; medium effect size) than mental health professional participants. Furthermore, school counselors had greater levels of Exhaustion (d = .27; small effect size) and lower levels of DC (d = -.82; large effect size) compared to the mental health professional participants working with sex offenders and clients that have been sexually abused. Therefore, school counselors score higher in exhaustion as compared to other mental health professionals and score lower on devaluing their clients.
Individual Factors Related to Burnout
The two categories of individual factors relating to school counselor burnout were (a) psychological constructs and (b) demographic factors. The psychological constructs included ego maturity (Lambie, 2007), collective self-esteem (Butler & Constantine, 2005), altruism (Limberg, Lambie, & Robinson, 20162017), lifestyle themes (Wachter, Clemens, & Lewis, 2008), coping styles (Wilkerson, 2009), perceived stress (Mullen, Blount, Lambie, & Chae, 2017), and grit (Mullen & Crowe, 2018). The definitions of these psychological constructs related to school counselor burnout follow.
Ego maturity refers to the fundamental element of an individual’s personality, encompassing components of self, social, cognitive, character, and moral development (Loevinger, 1976). When individuals’ egos develop, they become more individualistic, autonomous, and highly aware of themselves (Loevinger, 1976). Collective self-esteem is individuals’ perception of their identification with the social group they belong to (Bettencourt & Dorr, 1997). Altruism is the behavior driven by values or goals individuals possess or their concerns for others, aside from external rewards (Eisenberg et al., 1999). A lifestyle is an individual’s way of perceiving self, others, and the world (Mosak & Maniacci, 2000), and lifestyle themes refer to common patterns people possess in relation to their lifestyles (Mosak, 1971). Coping is defined as cognitive and behavioral efforts to deal with specific demands that take up or exceed individuals’ resources (Lazarus & Folkman, 1984), and coping styles refer to individuals’ relatively stable patterns in handling stress (Heszen-Niejodek, 1997). Perceived stress represents the extent to which individuals evaluate their situations as stressful (Cohen, 1986). Grit is “perseverance and passion for long-term goals” (Duckworth, Peterson, Matthews, & Kelly, 2007, p. 1087). Specifically, grit refers to efforts to achieve a goal despite challenges. In addition to psychological constructs, the demographic factors category included years of experience in school counseling (Butler & Constantine, 2005; Wilkerson, 2009; Wilkerson & Bellini, 2006) and age (Wilkerson & Bellini, 2006).
Psychological constructs. Seven studies identified that psychological constructs relate to school counselors’ feelings of burnout. Five of seven factors had large effect sizes, including ego maturity, altruism, lifestyle themes, coping styles, and grit, and three of the factors with large effect sizes were associated with Emotional Exhaustion (EE) among the MBI (Maslach et al., 1996) subscale scores (i.e., ego maturity, altruism, and coping styles).
Specifically, Lambie (2007) examined the directional relationship between school counselors’
(N = 218) burnout and ego maturity, identifying that those counselors with higher levels of ego maturity were likely to have greater feelings of Personal Accomplishment (PA; R2 = .033). The researcher also investigated the relationship between the school counselors’ reported occupational support and their MBI burnout subscales scores (Maslach & Jackson, 1996), identifying that each MBI subscale relates to the participants’ levels of reported occupational support; EE (large effect size; R2 = .167); DP (medium effect size; R2 = .120); and PA (medium effect size; R2 = .072). The results indicated that school counselors scoring at higher ego maturity levels had lower feelings of burnout, and counselors experiencing high levels of occupational support had significantly lower burnout scores.
The relationship between burnout and collective self-esteem was investigated within a sample of school counselors (N = 533; Butler & Constantine, 2005). The Collective Self-Esteem Scale has four subscales (Luhtanen & Crocker, 1992), including (a) Private Collective Self-Esteem (PRCS), (b) Public Collective Self-Esteem (PUCS), (c) Membership Collective Self-Esteem (MCS), and (d) Importance to Identity Collective Self-Esteem (IICS). These subscales measure individuals’ perception of social groups they belong to, including how they feel about the group (PRCS), how they perceive others feel about the group (PUCS), how they perceive themselves being a good member of the group (MCS), and how important their social group is to their self-concept (IICS). These four Collective Self-Esteem Scale subscales explained 3% of the variance in the burnout subscales (Pillai’s trace = .08, F [12, 1584] = 3.48, p < .001, η2M = .03; Maslach & Jackson, 1986).
In general, higher collective self-esteem relates to lower levels of burnout, and different dimensions of collective self-esteem relate to different components of burnout. Higher PRCS was associated with higher feelings of PA (η2 = .02), and higher PUCS was related to lower levels of EE (η2 = .01). The school counselors’ IICS subscale scores were related to their lower feelings of DP (η2 = .01) and greater feelings of PA (η2 = .01). Although a small amount of variance in burnout scores (.01–.02) was explained by the components of collective self-esteem, the positive relationship between higher PRCS and higher feelings of PA identified that positive perceptions of the group school counselors belong to might reduce their feelings of burnout. For instance, having a sense of pride as a school counselor by observing other school counselors’ hard work and good relationships with students may promote their sense of PRCS, which may lead to higher feelings of PA. Taken together, promoting school counselors’ collective self-esteem may decrease their feelings of burnout.
Limberg and colleagues (2016–2017) investigated the directional relationship between school counselors’ (N = 437) levels of altruism and burnout. The school counselors with greater levels of altruism had lower levels of EE and higher feelings of PA. Specifically, the altruism subscales of Positive Future Expectation (PFE) and Self-Efficacy from the Self-Report Altruism Scale (Rushton, Chrisjohn, & Fekken, 1981) and two subscales of burnout (MBI) correlated (χ2 = 403.611, df = 216, χ2 ratio = 1.869, p < .001). PFE and Self-Efficacy accounted for 31.36% of the variance in the EE subscale (large effect size), and 29.16% of the variance in the PA subscale (large effect size). The Self-Efficacy subscale, which involves individuals’ perceived competence in a certain skill, explained 14.4% of the variance in EE subscale scores (large effect size), and 9% of the variance in PA subscale scores (medium effect size). Therefore, the results identified that school counselors’ levels of altruism negatively contribute to their burnout scores.
Burnout was related to lifestyle themes among school counselors (N = 249; Wachter et al., 2008). Two subscales of lifestyle themes from the Kern Lifestyle Scale (Kern, 1996), Self-Esteem and Perfectionism, accounted for 15.1% of the variance in burnout (large effect size; R2 = .151). Specifically, the Perfectionism subscale was negatively related to school counselor burnout scores (Burnout Measure: Short Version; BMS; Malach-Pines, 2005), and the Self-Esteem subscale was positively related to school counselor burnout. As a result, these findings identified school counselors’ personality factors relating to their risk of burnout, supporting that higher levels of perfectionism and lower levels of self-esteem may increase the likelihood of experiencing burnout.
Two studies employed hierarchical regression analyses to examine what factors may predict burnout subscale scores of the MBI, and one of the predicting variables was coping styles (Wilkerson, 2009; Wilkerson & Bellini, 2006). Wilkerson (2009) used four-step hierarchical regression models that included demographics, organizational stressors, and coping strategies, such as task-oriented, emotion-oriented, and avoidance-oriented coping (N = 198). The models with large effect sizes explained all three MBI burnout subscales. Specifically, 49% of the variance in the EE subscale was explained (large effect size; R2 = .49); 27% of the variance in the DP subscale was accounted for (large effect size; R2 = .27); and 36% of the variance of the PA subscale was explained (large effect size; R2 = .36). The results identified school counselors’ stressor scores both at the individual and organizational levels; intrapersonal coping strategies contributed to feelings of burnout with large effect sizes in the final model. In other words, demographic factors (e.g., more school counseling experience), coping styles (e.g., more emotion-oriented and less task-oriented coping strategies), and organizational variables (e.g., lack of decision-making authority, role ambiguity, role incongruity, and role conflict) positively predicted the level of burnout among school counselors.
Wilkerson and Bellini (2006) used three-step hierarchical regression models including demographic, intrapersonal, and organizational factors to examine the relationship between the variables and burnout among school counselors (N = 78). The school counselors’ demographic data (e.g., age, counseling experience, supervision, and student/counselor ratio), and intrapersonal (i.e., coping strategies) and organizational factors (e.g., role conflict, role ambiguity, and counselor occupational stress) significantly accounted for the variance in their burnout subscale scores on the MBI. Specifically, 45% of the variance in the EE subscale was explained (large effect size; R2 = .45), 30% of the variance in the DP subscale was accounted for (large effect size; R2 = .30), and 42% of the variance in the PA subscale was explained (large effect size; R2 = .42) by the final three-step model with the variables (i.e., counselor demographics, intrapersonal factors, and organizational factors). The findings indicated that school counselors’ emotion-oriented coping style predicted their three MBI subscale scores, supporting the importance of utilizing helpful strategies (i.e., task-oriented coping) to mitigate counselors’ feelings of burnout.
Another study examined how school counselors’ perceived stress and job satisfaction relate to burnout (Mullen et al., 2017). Specifically, perceived stress measured by the Perceived Stress Scale (Cohen, Kamarck, & Mermelstein, 1983) explained 52% of the variance in burnout (F (1, 749) = 808.55, p < .001; R2 = .52) and 25% of the variance in job satisfaction (F (1, 749) = 243.36, p < .001; R2 = .25). When both perceived stress and burnout were examined in order to test the relationship with job satisfaction, they explained 40% of the variance in job satisfaction (F (2, 747) = 246.48, p < .001; R2 = .40). In addition, the results indicated that burnout mediated the relationship between perceived stress and job satisfaction (z = -21.47, p < .001), and burnout (rs = .99) predicted job satisfaction better than perceived stress (rs = .79). Overall, perceived stress predicted burnout positively (large effect size) and job satisfaction negatively (large effect size). Both perceived stress and burnout predicted job satisfaction (large effect size).
Finally, Mullen and Crowe (2018) investigated the relationship between grit, burnout, and stress among school counselors (N = 330). The researchers found that grit was negatively correlated with burnout (r = -.22, p < .001) and stress (r = -.28, p < .001). Specifically, perseverance of effort, one of the subscales from the Grit-S (Duckworth & Quinn, 2009), was negatively related with burnout (r = -.12,
p < .05) and stress (r = -.19, p < .001). Therefore, school counselors’ level of grit may be a protective factor for burnout and stress.
Demographic factors. School counselors’ individual factors, such as age (Wilkerson & Bellini, 2006) and years of experience (Butler & Constantine, 2005; Wilkerson, 2009), correlate with feelings of burnout. Age was negatively correlated to the DP subscale (r = -.19, p < .05); therefore, older school counselors were less likely to experience burnout as compared to younger counselors (Wilkerson & Bellini, 2006). Nevertheless, the correlation between school counselors’ years of experience and burnout was inconsistent. Wilkerson and Bellini (2006) indicated that years of experience negatively correlated with the EE (r = -.26, p < .01), and DP (r = -.24, p < .05) subscales, while Butler and Constantine (2005) identified that school counselors with more years of experience scored at higher levels of burnout (MBI scores). Specifically, school counselors with 20–29 years of experience had greater DP subscale scores than those with 0–9 years of experience (F (3, 529) = 3.38, p < .05); and counselors with 30 years or more of experience had lower PA subscale scores than those with less than 20 years of experience (F (3, 529) = 3.39, p < .05). Furthermore, Wilkerson (2009) also reported that the years of experience positively correlated with the EE (ß = .21, p < .01) and DP (ß = .26, p < .01) MBI subscales in the hierarchical regression models whose variables included counselor demographics and organizational and intrapersonal variables to explain the variance of the burnout scores. Possible reasons behind the incongruent results may relate to school counselors’ role ambiguity, as counselors with less experience may experience or perceive large workloads compared to more experienced counselors. The conflicting results also may be related to other school counselor factors, such as the level of social support counselors experience at their schools. The findings identified the need for more inquiry to increase our understanding of the relationship between school counselors’ years of experience and their feelings of burnout.
Organizational Factors Relating to School Counselors Levels of Burnout
Eight organizational factors appear to correlate with school counselors’ levels of burnout, including (a) workplace (Butler & Constantine, 2005), (b) non-counseling duties such as administrative and clerical tasks (Bardhoshi et al., 2014; Moyer, 2011), (c) caseloads (Bardhoshi et al., 2014), (d) AYP (Bardhoshi et al., 2014), (e) level of principal support (Bardhoshi et al., 2014), (f) clinical supervision (Moyer, 2011), (g) student-to-counselor ratio (Wilkerson, 2009; Wilkerson & Bellini, 2006), (h) perceived work environment (Wilkerson & Bellini, 2006), and (i) direct student services (Mullen & Gutierrez, 2016). We categorize these organizational factors into two domains: (a) job responsibilities and
(b) work environment factors.
Job responsibilities. Two studies examined the relationship between school counselors’ non-counseling duties and their burnout scores. First, Bardhoshi and colleagues (2014) examined school counselors’ (N = 212) non-counseling duties and identified a significant relationship between three of the CBI subscales: (a) 11% of the variance in Exhaustion was explained (medium effect size; R2 = 0.11); (b) 6% of the variance in NWE was explained (medium effect size; R2 = 0.06); and (c) 8% of the variance in DPL was explained (medium effect size; R2 = 0.08). Taken together, the results identified that school counselors’ non-counseling duties positively predict their burnout scores.
Moyer (2011) examined how school counselors’ (N = 382) non-counseling duties (non-guidance duties) were correlated to their levels of burnout as measured by the CBI. School counselors’ non-counseling duties accounted for 7.3% of the variance in the burnout score (medium effect size; R2 = .073, ß = .27, p < .01). Receiving supervision accounted for additional variance in school counselors’ burnout scores after controlling the variance explained by non-counseling activities (medium effect size; R2 = .09, ß = -.14, p < .01). As a result, school counselors with more non-counseling duties and less clinical supervision had higher burnout scores. The findings identify the importance of clinical supervision to reduce burnout among school counselors, helping them improve their quality of counseling, which in turn may increase their sense of competence in the workplace.
Bain and colleagues (2011) investigated the mental health of school counselors in a rural setting and their percentage of workweek spent on counseling and administrative duties in South Texas (N = 27). Within this sample of school counselors, 89% had experienced feelings of burnout at least sometimes when trying to provide mental health services; specifically, 41% reported feelings of burnout, and 48% sometimes experienced burnout when providing mental health services to their students. School counselors also reported that they spent the greatest amount of time completing administrative duties and the least amount of time providing counseling services. About 48% of the counselors used more than 50% of their time completing administrative duties, such as organizing facts to report to administrators and preparing for assessments of knowledge and skills, and more than 70% of the participants spent less than 50% of their time providing counseling services. The sample size for this study was small; nevertheless, the results identified that approximately 90% of the school counselors experienced some levels of burnout and spent less time providing counseling services to their students and other stakeholders than completing administrative duties.
Finally, Mullen and Gutierrez (2016) investigated the relationship between burnout and direct student services of school counselors (N = 926). The results indicated that burnout negatively contributed to the frequency of direct counseling activities (ß = -.35, p < .001), direct curriculum activities (ß = -.22, p < .001), and percentage of time at work providing direct services to students (ß = -.24, p < .001). The findings suggest that school counselors experiencing feelings of burnout are likely to have lower numbers of direct counseling activities and curriculum activities, and spend less time offering direct services to students.
Work environment factors. School counselors’ levels of burnout may be different depending on the location of their workplace (Butler & Constantine, 2005). Specifically, school counselors working in urban settings scored higher on the EE subscale as compared to counselors in suburban, rural, and other settings (F (3, 529) = 24.66, p < .001). In addition, counselors in urban settings had higher DP subscale scores than those in other environmental settings (F (3, 529) = 13.67, p < .001). The results may relate to unique stressors school counselors in the urban settings face, including their expected proficiency in working with diverse students (Constantine et al., 2001). Overall, school counselors in urban settings were likely to experience greater feelings of burnout than those counselors in other settings, suggesting that more research is warranted to better understand possible contributors to these educators having higher MBI scores.
Factors relating to school counselors’ work correlating with their feelings of burnout include counselors’ caseloads, AYP status, principal support, and non-counseling duties. Specifically, school-related factors for counselors explained the variance of four burnout subscales of the CBI (Bardhoshi et al., 2014): (a) 21% of the variance in Exhaustion scores was explained (large effect size; R2 = 0.21, p < .001); (b) 9% of the variance in Incompetence scores was explained (medium effect size; R2 = 0.09, p < .01); (c) 49% of the variance in NWE scores was explained (large effect size; R2 = 0.49, p < .001); and (d) 17% of the variance in DPL scores was explained (large effect size; R2 = 0.17, p < .001). As a result, both school counselors’ work-related factors, such as caseloads and non-counseling duties, and their school environment (support from school staff and AYP status) correlate to their feelings of burnout. Therefore, providing sufficient support for school counselors, meeting the AYP, and reducing caseloads and non-counseling duties might mitigate feelings of burnout among school counselors.
Student-to-counselor ratio (Wilkerson, 2009) and perceived work environment (e.g., role conflict; Wilkerson & Bellini, 2006) were identified as predictive factors for school counselor burnout. Wilkerson (2009) found that the hierarchical regression models with variables of demographic data (e.g., years of experience), organizational stressors (e.g., counselor–teacher professional relationships), and coping strategies (e.g., task-oriented coping) explained all three subscale scores of the MBI in a sample of school counselors (N = 198): EE (R2 = .49; large effect size), DP (R2 = .27; large effect size), and PA (R2 = 36; large effect size). Similarly, Wilkerson and Bellini (2006) identified that school counselors’ demographic, intrapersonal, and organizational factors accounted for variance in all three MBI subscale scores, including the EE, DP, and PA subscales (45%, 30%, and 42%, respectively; all large effect sizes). The findings from these studies support that environmental factors relate to school counselor burnout.
Identified Themes From Qualitative Studies
One qualitative study and two mixed-methods studies explored themes relating to school counselor burnout and ways to improve their service, which may offer ways to prevent burnout. Bardhoshi and colleagues (2014) examined how school counselors experienced burnout. Specifically, the emergent themes identified for school counselors’ feelings of burnout organized around four areas including (a) lack of time, (b) budgetary constraints, (c) lack of resources, and (d) lack of organizational support. When school counselors were asked about the meaning of performing non-counseling duties, they stated adverse personal and professional effects, the realities of practice, and reframing the duties within the context of the job. One participant described burnout stating, “It means that I am no longer helpful to my students. I feel like I’m extremely tired and overworked and consequently my effectiveness as a school counselor is negatively impacted” (p. 437).
These themes aligned with existing qualitative research examining school counselors’ feelings of burnout (N = 3; Sheffield & Baker, 2005), including (a) important beliefs, (b) burnout feelings, (c) burnout attitude, and (d) lack of collegial support. One of the participants stated, “I didn’t think I was doing any good for anybody . . . I just can’t go on this way” (p. 181). Another participant stated, “You get to the point where it is no longer fun coming to work or when you are just tired [and] don’t want to deal with anyone” (p. 182). Finally, Bain and colleagues (2011) explored helpful ways to better provide mental health services at school with 27 school counselors in rural districts of South Texas. The results identified that having access to more staff and additional education and awareness of mental health services at their school was needed. Overall, these studies identified common themes of school counselors’ need for collegial support and resources, such as a school climate encouraging collaboration, and identifying gaps in the needs and realities of school counselors (Bardhoshi et al., 2014), as well as reducing the amount of stressful, non-counseling–related work they perform.
Occupational Stress
Researchers examined which factors may influence school counselors’ job stress or job satisfaction, including (a) counselors’ perceived match between job expectations and their actual experiences (Culbreth et al., 2005), (b) the amount of resources in their work environment (McCarthy et al., 2010), (c) mattering to others (Rayle, 2006), and (d) role balance ability (Bryant & Constantine, 2006). Perceived match between initial expectations of the job and actual experiences as a school counselor was the most significant predictor of lower role stress demonstrated by each subscale score of the Role Questionnaire (N = 512; Culbreth et al., 2005): role conflict (medium effect size; R2 = .076); role incongruence (large effect size; R2 = .197); and role ambiguity (medium effect size; R2 = .083). School counseling students reported not feeling trained enough because of the significant amount of non-counseling–related duties, which increased their sense of role conflict.
Graduating from a program accredited by the Council for Accreditation of Counseling and Related Educational Programs accounted for 1.2% of the variance in school counselors’ perceived readiness for the job (small effect size; r = .111, p < .05; Culbreth et al., 2005). School counselors’ balance between job demand and resources was another important factor for their job stress. Moreover, McCarthy and colleagues (2010) identified that perceived job stress and work environment in terms of demands and resources were correlated (N = 227; F (2, 206) = 44.77, p < .001). School counselors with resources, such as other counselors in general or as mentors, and support from administrators scored lower on levels of job stress. The effect size for the difference between the demand and the resourced groups was 1.62 (large effect size), and between the demand and balanced groups was 0.70 (large effect size). In other words, school counselors with more work-related resources were likely to experience lower levels of job stress.
Several factors are related to job satisfaction for school counselors. Rayle (2006) investigated the relationship between school counselors’ (N = 388) mattering to others at work scores and job-related stress scores, and their overall job satisfaction scores. The School Counselor Mattering Survey developed for this study included seven items asking participants to rate their perceived mattering to others, including their students, administrators, and the parents and teachers they worked with. School counselors’ mattering to others at work scores and job-related stress scores explained 35% of the variance in their overall job satisfaction (large effect size; ηp² = .62). Specifically, school counselors’ job satisfaction correlated with mattering to others at work scores (large effect size; r = .44, p < .001) and their job-related stress scores (large effect size; r = -.41, p < .001). In addition, school counselors’ mattering to others scores were negatively associated with their job-related stress scores (r = -.54, p < .001; large effect size). The findings suggest that school counselors’ perceived mattering to others at work and job-related stress predict their overall job satisfaction, and mattering to others at work relates to their job-related stress.
In addition, Bryant and Constantine (2006) investigated the relationship between female school counselors’ (N = 133) role balance, job satisfaction, and life satisfaction. After controlling for demographic information (age, years of school counseling experience, and location of school), role balance and job satisfaction scores correlated with their satisfaction with life scores (large effect size; R2 = .41). As a result, school counselors’ multiple role balance ability and job satisfaction scores positively predicted their overall life satisfaction scores. In sum, these findings identified factors related to school counselors’ job satisfaction, including mattering to others at work, job-related stress, and life satisfaction.
Discussion
Because of the dearth of literature examining school counselor burnout or occupational stress, we reviewed 18 investigations based on the inclusion criteria and included articles focusing on the topic that were published between 2000 and 2018 in refereed journals and identified internal and external factors relating to the phenomena. Specific factors were identified relating to school counselor burnout or stress and their environment, including responsibilities not related to counseling, large caseloads, AYP status, and role confusion. The findings suggest the importance of school counselors asserting themselves to focus on mandated tasks (i.e., counseling) in order to experience less burnout. In addition, it is imperative to train school counseling students to understand the reality of practice, such as other job responsibilities and school climates, and inform them on the necessity of counselors advocating for themselves in order to overcome role confusion and avoid large caseloads. Furthermore, several resources were identified to mitigate burnout among school counselors. Clinical supervision from a competent supervisor is essential for school counselors to get support and learn how to intervene with their clients effectively. In addition, peer supervision or consultation from colleagues may benefit school counselors in sharing their difficulties and gaining other professionals’ perspectives (Butler & Constantine, 2005). Task-oriented coping skills which can be learned in the school counseling programs were also related to a reduced level of burnout among school counselors.
Limitations
Our review needs to be interpreted with some caution, as it is limited to the 18 published studies meeting the inclusion criteria. Therefore, additional research investigating school counselor burnout is needed to further our understanding of this significant construct that may influence the services school counselors provide to their stakeholders. In addition, the reviewed studies include methodological limitations (e.g., sample size, self-report data), further supporting the need for increased research examining the construct of burnout in school counseling. Moreover, no research was identified examining interventions to possibly reduce counselor feelings of burnout.
Implications for School Counseling
Although no studies were identified that investigated treatments for school counselor burnout, research from other similar professions may provide insight for developing coping strategies for school counselors addressing their feelings of burnout. Awa, Plaumann, and Walter (2010) reviewed 25 intervention studies for burnout prevention whose participants included employees from diverse occupations. Seventeen out of 25 studies employed person-directed interventions and indicated the positive effects of the interventions, including cognitive behavioral training (Gorter, Eijkman, & Hoogstraten, 2001), psychosocial skill training (Ewers, Bradshaw, McGovern, & Ewers, 2002), and recreational music making (Bittman, Bruhn, Stevens, Westengard, & Umbach, 2003). Two studies used organization-directed interventions, and one of the studies reduced burnout by using cognitive behavioral techniques, management skill training, and social support (Halbesleben, Osburn, & Mumford, 2006). The other six investigations explored the effects of combined (person- and organization-directed) interventions in reducing burnout. The examples of combined interventions to mitigate counselors’ feeling of burnout include professional supervision (Melchior et al., 1996); work schedule reorganization and lectures (Innstrand, Espnes, & Mykletun, 2004); and participatory action research, communication, social support, and coping skills (Le Blanc, Hox, Schaufeli, Taris, & Peeters, 2007). Overall, Awa and colleagues (2010) identified positive impacts of burnout intervention programs, suggesting potential benefits of these treatment programs for school counselors.
In addition, Krasner and colleagues (2009) reported the effectiveness of their continuing medical education program for physicians to reduce burnout, which involves mindfulness, self-awareness, and communication skills. Educating for mindfulness strategies, self-awareness, and communication skills also may be helpful for school counselors. Providing a supportive environment and acknowledging school counselors’ work may help them increase their sense of matter in their workplace. Lacking empirical studies identifying treatment outcomes for burnout in school counselors, research on decreasing the level of school counselor burnout should be examined both deeply and extensively. Furthermore, intervention programs to prevent and intervene with school counselors’ burnout and occupational stress at the individual and organizational levels are warranted. The efforts to prevent burnout may lead to school counselors providing better quality of services, benefitting the counselors and the students they serve.
Our review indicated that school counselors’ responsibilities, such as non-counseling duties and dealing with large caseloads, hindered counselors from maintaining their wellness. Additionally, experiencing role conflict and employing emotion-oriented coping skills increased their feelings of burnout. Therefore, school counselor preparation programs need to incorporate into their curriculum the characteristics of their future work environment that may involve potential risk factors for burnout. Furthermore, developing school counselors’ own strategies and practicing beneficial skills such as task-oriented coping skills may be helpful for them in decreasing their likelihood of experiencing burnout.
Conclusion
Preventing and reducing school counselors’ feelings of burnout is important to ensure counselors’ ability to provide ethical and effective services to their stakeholders. Failure to address work-related stress in school counselors may cause reduced quality of their service and increased counselor attrition from the profession. Although more investigations examining burnout in school counselors are warranted, this manuscript is the first systematic review of burnout in school counseling, offering increased insight into this significant job-related psychological phenomenon.
Conflict of Interest and Funding Disclosure
The authors reported no conflict of interest
or funding contributions for the development
of this manuscript.
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