Access to School Counseling and the Connection to Postsecondary STEM Outcomes

Dana L. Brookover

 

Access to school counseling services leads to access to college-readiness counseling initiatives, including science, technology, engineering, and mathematics (STEM) education–focused counseling for students. School counselor caseload and percentage of time spent on college-readiness counseling were analyzed in relation to longitudinal STEM postsecondary outcomes of students in a nationally representative sample. Access to school counselors who spend 21% or more of their time on college-readiness counseling predicted persistence and attainment of a STEM postsecondary degree. The current results offer implications for school counselors, counselor educators, and future researchers, including the need for STEM self-efficacy interventions, unbiased curriculum, and professional development on STEM counseling for school counselors; and the call for a more nuanced understanding of this topic.

Keywords: STEM, school counseling, college-readiness counseling, longitudinal, self-efficacy

 

College and career readiness are key outcome targets of school systems across the United States (Malin et al., 2017; U.S. Department of Education, 2010). Science, technology, engineering, and mathematics (STEM) initiatives are also a national priority (The White House, Office of Science and Technology Policy, National Science and Technology Council, 2018). School counselors play an integral role in their students’ college readiness through providing college-readiness counseling (Gilfillan, 2017). This includes the important role school counselors perform in educating students on the possibilities in STEM at the college level (Cabell et al., 2021; Schmidt et al., 2012).

STEM Education
     STEM education has been described by Tsupros and colleagues (2009) as an interdisciplinary approach to learning science, technology, engineering, and mathematics that includes understanding and knowledge of science and math concepts, computers, and problem-solving skills. There have been long-standing calls for a more STEM-literate workforce, a more diverse STEM workforce, and more individuals interested in working in the STEM fields in general (Mohr-Schroeder et al., 2015).

STEM education attainment and persistence is an emerging topic in the career development and counseling profession, but there are differing opinions on what constitutes the “STEM crisis” (Xue & Larson, 2015). Some researchers have indicated that the demand for STEM workers in the United States will not be met because of a lack of qualified and interested individuals to step into these positions. Another viewpoint emphasizes that research has indicated there are both shortages and surpluses of STEM workers, depending on the particular job market segment (Xue & Larson, 2015). Still, the data is clear that there is a “STEM crisis” in terms of inequities in who is matriculating into and persisting in STEM majors (National Science Foundation [NSF], 2021).

Despite the great growth in traditionally underrepresented students persisting in STEM majors in college (NSF, 2021) and the potential for career development initiatives to increase retention in STEM for minority groups (Belser et al., 2018), there are still disparities in STEM college major attainment and persistence by gender, race and ethnicity, socioeconomic status (SES), and first-generation college student (FGCS) status (Chen, 2013). This is an equity issue, as the choice to enroll in a STEM postsecondary program may also lead to higher pay and the potential for positive job marketability given the projected growth in available positions (Cataldi et al., 2014; Vilorio, 2014). Hence, school counselors are called upon to address STEM education disparities in their work, as the American School Counselor Association (ASCA; 2019) emphasizes the role of the school counselor in working to ensure equitable postsecondary opportunities and outcomes for all students.

College-Readiness Counseling and STEM Education
     High school counselors are in a unique position to provide career-readiness counseling, including college-readiness counseling for those students who aim to attend college after high school. College-readiness counseling involves developmentally appropriate counseling that engages students in (a) creating postsecondary goals and expectations, (b) building an awareness of interests and abilities, and (c) receiving information and support for their college access and success (Savitz-Romer, 2012). School counselors can focus on STEM education with students in each of these tasks.

Research has shown that students’ intent to pursue a STEM career already varies by populations as early as the ninth grade. Girls and students in minority racial groups, in a nationally representative sample, were less likely to expect to work in a STEM discipline at the age of 30 as compared to boys and White students (Mau & Li, 2018). Students’ SES also predicted STEM career aspirations, in that a student with higher SES was more likely to aspire to a STEM career (Mau & Li, 2018). There are multiple potential reasons for the opportunity gaps in STEM higher education, including lack of engagement in higher-level STEM coursework in high school, the time it takes to complete STEM programs, and a student’s lack of financial ability to do so, as well as attitudinal factors, such as motivation and confidence. These factors can lead to less matriculation into a STEM major and more attrition (Chen, 2013). There may also be a lack of support and encouragement and even direct discouragement from educators for underrepresented minorities and women to engage in STEM coursework, starting in adolescence (Grossman & Porche, 2014). This was echoed in a qualitative study in which high school counselors said that a barrier in their work supporting underrepresented students in STEM was a lack of anti-racist curricula in STEM classes and inconsistencies in anti-racist practice by teachers (Cabell et al., 2021). The importance of college-readiness counseling focused on STEM education is known.

Existing STEM Education–Focused College-Readiness Counseling Research
     Emerging research is developing on the school counselor’s role on students’ STEM self-efficacy and students’ pursuit of postsecondary STEM education (Cabell et al., 2021; Falco, 2017; Falco & Summers, 2019; Schmidt et al., 2012). Falco (2017) provided a conceptual framework with the goal of helping school counselors better support STEM career development for all students and especially those from underrepresented groups. Falco suggested school counselors can encourage students to take advanced-level math and science courses, provide classroom instruction on the benefits of engaging in STEM, ensure balanced gender and racial/ethnic ratios in STEM classes, and organize a peer mentoring program or conduct small group counseling on relevant skills.

Cabell and colleagues (2021) interviewed high school counselors about their work with underrepresented students and STEM education. The participants were actively engaging in college-readiness counseling focused on STEM education with students, but there were barriers to their ability to support underrepresented students’ STEM interests, including lack of time, in part from administrative tasks, and large caseloads (Cabell et al., 2021). This is related to previous research suggesting that the percentage of time spent on college-readiness counseling differs by school characteristics. For example, private school counselors typically spend more time on it than public school counselors, and school counselors with more students on free-and-reduced lunch tend to spend less time (Clinedinst & Koranteng, 2017). Smaller caseloads have also been associated with school counselors spending more than half their time on college-readiness counseling (Engberg & Gilbert, 2014). Further, smaller caseloads show improved college outcomes, including higher rates of 4-year college enrollment (Engberg & Gilbert, 2014; Hurwitz & Howell, 2014).

Schmidt and colleagues (2012) also provided suggestions for school counselors to “expand their repertoire” through STEM-focused career development. Key impact areas include academic and career counseling, and leadership and advocacy. The researchers acknowledged how school climate and the large administrative demands (i.e., duties inappropriate for counselors) placed on school counselors may restrict their ability to engage in career-related and STEM course discussions with students. However, there is no data to shed light on the long-term impacts of this barrier and how their suggested key impact areas influence student outcomes.

Research has found that self-efficacy is an important pathway to students’ STEM major persistence (Lent et al., 2016; Rittmayer & Beier, 2009). Self-efficacy is an individual’s belief in their ability to influence and control the events of their life to obtain desired performances (Bandura, 1994). As an example, when students believe they can achieve desired results in science through their abilities and actions, this is considered high science self-efficacy. Researchers have detailed the results of a career group intervention that incorporated the sources of self-efficacy and addressed perceived career barriers with the goals of improving the career decision self-efficacy and STEM self-efficacy for adolescent girls (Falco & Summers, 2019). Components of the intervention included a group counseling structure, career psychoeducation, journaling, constructing a timeline of successful previous performances, progressive muscle relaxation, vicarious learning, and verbal persuasion by the leader. Results showed significantly different improvements in career decision self-efficacy and STEM self-efficacy. The results of this intervention are promising, especially as it is one of the few empirical studies on self-efficacy counseling interventions and STEM career outcomes with adolescents. The sample was all female with half of the sample identifying as Latina (Falco & Summers, 2019).

It follows that there needs to be access to school counseling services for engagement in college counseling that can effectively bolster students’ STEM aspirations. Given the potential for high school STEM interventions to make a great impact in student’s STEM self-efficacy and education outcomes, the inability of school counselors to provide college counseling, and specifically STEM-focused college counseling, is troubling (Falco & Summers, 2019). To move forward in advocating for school counseling access to promote student outcomes in the STEM pipeline, a theory-driven, longitudinal approach to investigating the impact of school counseling access on this outcome was initiated in the current study. Given the importance of considering student characteristics, environmental inputs, and self-efficacy in STEM matriculation, attainment, and persistence, social cognitive career theory (Lent et al., 1994) served as a logical base for the theoretical framework for this investigation.

Social Cognitive Career Theory
     Social cognitive career theory (SCCT) was developed from Albert Bandura’s (1986) social cognitive theory to create a unifying theory of career and academic interest, choice, and performance (Lent et al., 1994). SCCT accounts for the cyclical nature of making a career choice through accounting for people receiving information from contextual influences that fuel feedback loops (Lent, 2004). These external influences can be contextual supports or barriers (Lent et al., 2000). It is also important to note that one’s perception of barriers moderates the relationship between interests and career choices (Brown & Lent, 1996). Hence, underrepresented and underserved students’ perceptions of barriers in obtaining a STEM degree can impact career choice and development. Moreover, other background environmental influences, person inputs, and behaviors interact in this feedback loop as well. One influence of utmost importance in the theory is self-efficacy. Thus, SCCT can account for external factors, otherwise known as proximal environmental influences (e.g., school counseling access), and individual characteristics (e.g., demographics and self-efficacy) within long-term career development formation.

Purpose of the Study
     The current study was built upon previous SCCT school counseling and STEM attainment and persistence studies. The goal was to investigate the long-term impacts of school counseling access, in relation to student characteristics, on STEM outcomes. The research question guiding the study was: Do school counselor caseload and percentage of time spent on college-readiness counseling predict STEM major attainment and persistence?

Method

Using a multivariate, quantitative, longitudinal research design to answer the research question was well-suited to the purpose of the study. Longitudinal research designs allow for gathering and analyzing data on development over time (Lavrakas, 2008). As the research question was focused on prediction in a sample of students and the outcome was measured quantitatively, this research design was employed. I followed the process of secondary analysis of existing data (Cheng & Phillips, 2014), utilizing the High School Longitudinal Study of 2009 (HSLS:09), developed by the National Center for Education Statistics (NCES; 2020a). The HSLS:09 dataset followed a sample of high school students throughout their secondary education career into postsecondary years (NCES, 2020b).

Participants and Sampling
     The HSLS:09 is a longitudinal study of over 23,000 ninth graders from 944 schools (Ingels & Dalton, 2013; NCES, 2020b). Stratified random sampling ensured a nationally representative sample. Approximately 900 high school counselors were surveyed for the study to provide information on their school counseling departments, including school counselor caseload and percentage of time spent on college-readiness counseling. School counselors in the study were not randomly selected; rather, they were either the lead counselor or the counselor deemed most knowledgeable about the ninth graders at the time of the baseline data collection (Ingels & Dalton, 2013). The baseline data was collected in 2009, then the study had a first follow-up survey with student participants in 2012; there was a brief 2013 update survey and a second follow-up in 2016 (Duprey et al., 2018).

Data Selection
     Cheng and Phillips’s (2014) steps for secondary analysis of existing data under the research question–driven approach guided the data collection procedures for the current study. Thus, I determined which variables in the existing dataset to use to answer the research question. This was done through using SCCT to guide the model creation. Then, I became acquainted with the coding patterns of variables. This led to the transformation of distributions of select variables to meet assumptions of the model to be used in analysis when necessary, as detailed below.

Constructs and Variables
     The HSLS:09 variables (NCES, 2020a) included in the current study both cover the research question and fit within the theoretical framework (i.e., SCCT; Lent et al., 1994). First, there are demographic variables, also known as person inputs and background environmental influences, within SCCT. Data on variables to represent self-efficacy constructs were also selected. Two variables measured school counselor caseload and school counselor percentage of time spent on college-readiness counseling. Finally, the outcome variable was STEM major attainment and persistence.

First-Generation College Student Status
     The FGCS status variable was constructed as a variable detailing the highest level of education achieved by either parent/guardian in the sample member’s home in the HSLS:09 dataset. This was created from two composite variables within the dataset: highest education level of Parent 1 and highest education level of Parent 2. In its original categorical form, there are seven categories for parent highest level of education, but for the current study, it was recoded into a dichotomous/dummy variable; either the student had a parent in the home who has a bachelor’s degree or a more advanced degree, or the student did not have a parent in the home who has a bachelor’s or a more advanced degree.

Race/Ethnicity
     Race/ethnicity information was provided through dichotomous race/ethnicity composites based on data from the student questionnaire, if available. If not available from the student questionnaire, they were based on, in order of preference: data from the school-provided sampling roster or data from the parent questionnaire. The designations included in the HSLS:09 and the current study are: (a) American Indian or Alaskan Native; (b) Asian; (c) Black (African American); (d) Hispanic, no race specified; (e) Hispanic, race specified; (f) more than one race; (g) Native Hawaiian/Pacific Islander; and (h) White. For the current study, the two Hispanic categories were combined.

Sex
     This variable was categorical and referred to the sex of the sample member (male or female) and was provided by the student if possible, and if not, the parent or school roster. The labels male and female have held and continue to hold “powerful associations” (Lips, 2020, p. 3), and not all people identify into a gender binary of female and male (Lips, 2020). There is a gender variable assessed in the HSLS:09 study; however, it is only available in the restricted use dataset, so the sex variable was utilized in the current study.

Socioeconomic Status
     SES was a composite variable consisting of five components obtained from the parent/guardian questionnaire and aligned with previous NCES longitudinal study methods for calculating SES: (a) the highest education among parents/guardians in the two-parent family of a responding student, or the education of the sole parent/guardian; (b) the education level of the other parent/guardian in the two-parent family; (c) the highest occupational prestige score among parents/guardians in the two-parent family of a responding student, or the prestige score of the sole parent/guardian; (d) the occupation prestige score of the other parent/guardian in the two-parent family; and (e) family income. This was a standardized value set to 0; hence, values ranged from −1.82 to 2.57.

Self-Efficacy Variables
     This data was collected at the baseline. SCCT asserts that learning experiences and prior accomplishments are an integral part of forming self-efficacy; hence STEM grade point average (GPA) was included under self-efficacy (Lent et al., 1994). GPA information was collected at the 2013 update.

     Math Self-Efficacy. Math self-efficacy is a continuous variable, with higher values representing higher math self-efficacy. The information was assessed through a scale consisting of four items (e.g., “can do excellent job on math tests”). The variable was created through principal components factor analysis and was standardized to a mean of 0 and standard deviation of 1. Only respondents who provided a full set of responses were assigned a scale value. The coefficient of reliability (demonstrated by alpha) for the scale is .65 (NCES, 2020c).

     Science Self-Efficacy. Science self-efficacy is also a continuous variable, with higher values representing higher science self-efficacy, and was also created through principal components factor analysis and standardized to a mean of 0 and standard deviation of 1. There were four items on the scale (e.g., “can master skills in science course”). Only respondents who provided a full set of responses were assigned a scale value. The coefficient of reliability (indicated by alpha) for the scale is .65 (NCES, 2020c).

STEM GPA
     STEM GPA, an interval variable, was computed during the 2013 update through high school transcript composites. STEM GPA values range from 0.25 to 4, in increments of 0.25.

School Counselor Caseload
     Information for this continuous variable was assessed through one item on the school counselor questionnaire: “On average, what is the caseload for a counselor in this school? Students per counselor.” Students per counselor ranged from 2 to 999 (NCES, 2020c). The variable was recoded into a dichotomous variable, with 0 indicating a school counselor caseload of 250 or less, and 1 indicating a school counselor caseload of 251 or more. The ASCA-recommended caseload number for school counselors is 250:1.

School Counselor Percentage of Time Spent on College-Readiness Counseling
     This was assessed through one item on the school counselor questionnaire that read, “Last school year (2008–2009), what percentage of work hours did your school’s counseling staff spend assisting students with college readiness, selection, and applications?” Responses were reported according to the following categories: 5% or less, 6%–10%, 11%–20%, 21%–50%, and more than 50%. This was recoded to a dichotomous variable—20% or less time spent on college-readiness counseling or 21% or more time spent on college-readiness counseling—reflecting a cut-off of the national average of time spent on college-readiness counseling by school counselors at 21% (Clinedinst & Koranteng, 2017).

Outcome Variable: STEM Major Attainment and Persistence
     This was a dichotomous variable (either Not STEM or STEM) and was collected in the second follow-up study in 2016 (i.e., approximately 3 years post–high school graduation). It referred to how the respondent declared or decided upon their degree and whether that undergraduate degree or certificate is in a STEM field of study.

Data Analysis

Continuing to follow Cheng and Phillips’s (2014) steps for secondary analysis of existing data, the first step in data analysis was to run preliminary analyses of descriptive statistics and bivariate correlations. Then, I assessed missing data patterns. When deemed necessary, the HSLS:09 developers did utilize imputation of values (Ingels & Dalton, 2013). Imputation allows the use of all study respondent records in an analysis, affording more power for statistical tests. Additionally, if the imputation procedure is effective, then the analysis results can be less biased than if there were missing data unaccounted for (Ingels & Dalton, 2013). Value imputation occurred in place of missing responses for select variables identified from the student and parent questionnaires through single-value imputation (Duprey et al., 2018; Ingels & Dalton, 2013). Further, the NCES provides analytic weighted variables and replication weights associated with those main sampling weights. The analytic weights make estimates from the sample data representative of the target population (i.e., ninth grade students in 2009–2010). These analytic weights account not only for differential selection probabilities, but also for differential patterns of response and nonresponse—in other words, nonresponse bias (Duprey et al., 2018). In addition to the analytic weight variables accounting for stratified sampling and nonresponse bias, replication weight variables address standard error concerns. Standard error calculation ensures appropriate standard errors based on the differences between the estimates of the full sample and a series of replicates (Duprey et al., 2018). These replication weights are done with the balanced repeated replication method and help account for the possibility of artificially low standard errors due to clustering in sampling (Duprey et al., 2018).

Prior to running the sequential logistic regression, assumptions testing was completed. Logistic regression analyses allow the use of criterion measures on a binary outcome (Meyers et al., 2017). The result of a logistic regression is the impact of each variable on the probability of the observed event of interest (Sperandei, 2014). Sequential logistic regression allows the researcher to specify the entry order of predictor variables into the model (Tabachnick & Fidell, 2013).

Model 1, the baseline model, represented person inputs and background environmental influences in SCCT. It included the following variables: FGCS status, race/ethnicity, sex, and SES. Model 2 represented self-efficacy, after controlling for person inputs and background environmental influences. Self-efficacy variables included math self-efficacy, science self-efficacy, and STEM GPA. Model 3 examined school counseling access, after controlling for the variables in the previous two models. School counseling access variables were school counselor caseload and school counselor percentage of time spent on college-readiness counseling. Table 1 displays the model steps and variables.

Table 1

Logistic Regression Model Steps

Results

The aim of the current study was to examine the predictors of STEM major attainment and persistence, including school counselor caseload ratio and percentage of time spent on college-readiness counseling. First, preliminary analysis included running descriptive statistics and a correlation matrix.

Preliminary Analysis
     Frequencies and percentages on the variables’ unweighted, valid data (i.e., data before weights were applied and not including missing data) are reported in this section. First, descriptive statistics on person inputs and background environmental influences (i.e., student demographics) were collected. A total of 56.4% (n = 9,468) of the valid sample were FGCS, and 43.6% (n = 7,314) were non-FGCS. A total of 50.9% (n = 11,973) of the sample were identified as female, and the remaining 49% (n = 11,524) as male. The continuous SES variable ranged from −1.93 to 2.88, with a mean score of 0.05 (SD = 0.78). For information on participants’ race/ethnicity, see Table 2.

Table 2

Participant Race and Ethnicity Variable Percentages and Frequencies

Math self-efficacy scores ranged from −2.92 to 1.62 (M = 0.0421, SD = 0.96). Science self-efficacy scores ranged from −2.91 to 1.83 (M = .0372, SD = 0.99). In terms of STEM GPA, the range was 0.25 through 4.00, reported in intervals of 0.25 (M = 2.43, SD = 0.93).

The school counselor caseload in the current study had a mean score of 347.65 students (SD = 130), ranging from 2–999. The median was 350. The school counselor percentage of time spent on college-readiness counseling scores ranged from 1–5 (M = 3.37, SD = 0.95). A total of 2.3% (n = 484) chose 5% or less, and 16.2% (n = 3,389) of the sample chose 6%–10%. A total of 33.8% (n = 7,094) indicated 11%–20%, followed by 37.5% (n = 7,867) choosing 21%–50%. Finally, 10.2% (n = 2,132) of the sample chose the more than 50% option.

For the STEM major persistence and attainment variable, 23% (n = 2,658) of the valid sample were enrolled as a STEM major or had attained a STEM degree as of February 2016, and 77% (n = 8,902) were neither enrolled as a STEM major nor had attained a STEM degree as of February 2016.

Bivariate Correlations
     A bivariate correlational analysis of interval and ratio variables in the study allowed for preliminary examination of collinearity and provided information on relationships between the variables of interest. The bivariate correlation matrix indicated no concerns regarding multicollinearity. The correlations contain indications of relationships to school counseling access. For example, school counseling caseload and percentage of time spent on college-readiness counseling were inversely related (r = −.181, p < .01). School counselor caseload was negatively significantly correlated to SES, STEM GPA, and math self-efficacy. School counselor percentage of time spent on college-readiness counseling was positively significantly correlated with SES, STEM GPA, math self-efficacy, and science self-efficacy. See Table 3 for the full results of the bivariate correlations.

Table 3

Bivariate Correlations

Primary Analysis
     Next, the results of the sequential logistic regression are presented (see Table 4). The outcome variable is a dichotomous variable of STEM major persistence and attainment and indicated if a student either is or is not enrolled as a declared STEM major in a postsecondary institution or has or has not attained a degree in a STEM field from a postsecondary institution.

Statistical assumptions of the model were assessed. Tolerance (0.26) and VIF values (mean VIF = 1.34) indicated no concerns regarding multicollinearity. The Box-Tidwell test indicated the assumption of a linear relationship between continuous predictors and the logit transform of the outcome variable was met, with nonsignificant p values. Utilizing the balanced repeated replication variance estimation method, 16,007 observations were included in the regression model, with a population size of 1,540,118 and 192 replications.

Table 4

Logistic Regression Model Predicting STEM Major Attainment and Persistence

Note. Model 1 = person inputs and background environmental influences (first-generation college student [FGCS], race/ethnicity, sex, socioeconomic status [SES]), without any controls; Model 2 = person inputs and background environmental influences, and self-efficacy variables (math self-efficacy, science self-efficacy, and STEM grade point average [GPA]); Model 3 = person inputs and background environmental influences, self-efficacy variables, and proximal environmental influences (school counselor caseload and percentage of time spent on college-readiness counseling). Reference categories: FGCS = non-FGCS; Sex = male; Race/ethnicity = White; STEM GPA = 3.0–4.0; Percentage of time spent on college-readiness counseling = less than 21%.
*p < .05. **p < .01. ***p < .001.

 

Model 1 was significant, F(9, 189) = 12.49, p < .001. McFadden’s R Square was 0.0506, indicating that the model explains 5.06% of the variance outcomes. This model indicated that SES significantly predicted STEM major attainment and persistence (β = 0.22, p < .001). In addition, female students were less likely than males to report STEM major attainment and persistence (β = −0.94, p < .001). Asian students were significantly more likely than White students to report STEM major attainment and persistence (β = 0.91, p < .001).

Model 2 was significant, F(12, 185) = 19.03, p < 0.001, McFadden’s R Square = 0.0966. STEM GPA significantly predicted STEM major attainment and persistence, with students with GPAs ranging from 0.25–2.75 being significantly less likely to report STEM attainment and persistence compared to students with GPAs of 3.00–4.00 (β = −0.64, p < .001). Both math self-efficacy (β = 0.27, p < .001) and science self-efficacy (β = 0.26, p < .001) were significant predictors of STEM major attainment and persistence, with increases in these variables resulting in higher odds of the outcome. Female sex and Asian race identity remained significant, while SES was no longer significant.

Model 3 was significant, F(14, 178) = 15.90, p < .001, McFadden’s R Square = 0.1005. For Model 3, the Archer–Lemeshow goodness-of-fit test was not significant, and the adjusted Wald test was significant, indicating good model fit. In this model, school counselor percentage of time spent on college-readiness counseling predicted student STEM major attainment and persistence, with 21% or more time spent on college-readiness counseling being more likely to result in the outcome, compared to 20% or less time spent on college-readiness counseling (β = .26, p < .05). School counselor’s caseload was not significant. Female sex, Asian race identity, STEM GPA, math self-efficacy, and science self-efficacy all remained significant predictors in the final model. The model correctly classified 77.34% of the cases, with higher specificity (95.94%) than sensitivity (19.40%).

Discussion

A sequential logistic regression analysis provided the means for exploration of the research question: Do school counselor caseload and percentage of time spent on college-readiness counseling predict STEM major attainment and persistence? Sequential logistic regression allowed for sociocultural context to be considered in the prediction of STEM career–related performance. This is important because the structure of opportunity (e.g., SES, education access, social support), socialization of gender roles, and other societal and family norms influence abilities, self-efficacy, outcome expectations, and goals within SCCT (Lent & Brown, 1996). The first model included person inputs and background environmental influences (Lent et al., 1994), including FGCS status, race/ethnicity, sex, and SES. Students of Asian race/ethnicity had higher odds of persisting in a STEM major or attaining a degree, compared to the White student reference group, which echoes previous research (Chen, 2013; Mau, 2016). SES also predicted the outcome, with students of higher SES having higher odds of STEM persistence and attainment, which is aligned with previous research on students’ SES status and STEM outcomes (Chen, 2013). Finally, female students had lower odds of persisting in a STEM major or attaining a STEM degree than male students in the model; this gender disparity in STEM academic and career-related outcomes has also been noted in the literature (Mau, 2016).

The second model extended the investigation of predictors of STEM major attainment and persistence to include self-efficacy variables (i.e., math self-efficacy, science self-efficacy) and STEM high school GPA, in addition to still accounting for the person inputs and background environmental influences. Within this second model, Asian-identifying students and female students held the same patterns of significance as in the first model, which was that Asian-identifying students had higher odds of attaining or persisting, while female students had lower odds. When accounting for the self-efficacy variables, Hispanic-identifying students then showed significantly higher odds of persisting in a STEM major and attaining a STEM degree. Previous research does not report higher odds of Hispanic student STEM major persistence and attainment (Mau, 2016; NSF, 2021). However, this result in the model suggests that when Hispanic students have equitable math self-efficacy, science self-efficacy, and STEM GPAs, their opportunity for STEM success is increased, which has been reflected in an SCCT academic persistence model with Latinx engineering student participants (Lee et al., 2015). STEM self-efficacy is an important subject for school counselors to address with students (Falco, 2017), given its influential role in STEM outcomes (Mau & Li, 2018; Shaw & Barbuti, 2010).

The second model demonstrated that as math self-efficacy and science self-efficacy scores increased, the odds of a student persisting in a STEM major or attaining a STEM degree increased significantly. Further, students with higher STEM GPAs in high school were more likely to persist in STEM majors or attain a STEM degree. This is aligned with SCCT, which suggests previous learning experiences and prior accomplishments have a positive effect on career-related outcomes (Lent & Brown, 1996). Previous research (Chen, 2013) has also suggested that lack of preparation in advanced STEM courses in high school leads to more STEM major attrition.

The final model included all previous variables and added the two school counseling access variables: school counselor caseload and school counselor percentage of time spent on college-readiness counseling. Variables that remained significant in the model, in the same directionality of odds of the outcome, were: Asian race/ethnicity, Hispanic race/ethnicity, sex, math self-efficacy, science self-efficacy, and high school STEM GPA. The final model showed women were less likely to persist in STEM majors or attain a STEM degree even when accounting for the access to school counseling variables. This gender disparity is unfortunately reflective of the extant literature on STEM outcomes (Chen, 2013). It also perhaps speaks to the barriers school counselors face when working with historically underrepresented students surrounding STEM (Cabell et al., 2021), such as a lack of encouragement from educators for girls to pursue STEM endeavors (Grossman & Porche, 2014).

In the current study, school counselor caseload was not significant in the model. This finding is not aligned with previous research that found the addition of each school counselor to a school’s staff was associated with a 10% increase in 4-year college-going rates (Hurwitz & Howell, 2014), which suggests the influence of caseload on student postsecondary outcomes, as typically more school counselors on staff results in lower caseloads. However, it is important to note that school counselor caseload did have a significant relationship with the percentage of time spent on college-readiness counseling in the current study, with more students on a caseload resulting in less time spent on college-readiness counseling, according to the bivariate correlation analysis.

School counselor percentage of time spent on college-readiness counseling was significant in the final model, and the results indicated that students who have a school counselor who spends at least the national average of time on college-readiness counseling (i.e., 21%) have higher odds of persisting in STEM majors or attaining a STEM degree. Students who have a school counselor who spends 21% or more of their time on college-readiness counseling have 29% higher odds of STEM major persistence and attainment 3 years post–high school graduation. This finding is novel in the literature. School counseling and STEM counseling is a relatively new area of research in the school counseling literature (Falco, 2017; Schmidt et al., 2012). The current study’s finding on the impact of school counselors’ college-readiness counseling on STEM outcomes extends existing research that has noted the importance of school counselors’ role in STEM counseling (Falco, 2017; Falco & Summers, 2019; Shillingford et al., 2017).

Implications
     School counselors can use the results of this study to inform their STEM education–focused college-readiness counseling work. A promising result of the study was that school counselors’ percentage of time spent on college-readiness counseling was predictive of STEM major attainment and persistence. Although there were still inequities in which students were achieving this outcome, including female students. This is helpful information to lead school counselors to target intervention efforts with girls. For instance, girls may benefit from more STEM-focused occupational information and verbal persuasion (i.e., encouragement) from school counselors. These results indicate that school counselors should increase their knowledge and awareness of the barriers their female students are facing related to STEM and seek to correct those barriers. Barriers can include school climate, which school counselors can address through both the messages they themselves and all school staff are sending to their female students about STEM. In terms of consultation, it has been suggested school counselors should play an important role in working with STEM teachers to develop curricula that are unbiased and culturally sensitive to the needs of female and minority students, and the results of the study show the long-lasting effects of how a ninth-grade student perceives their self-efficacy in math and science, supporting this suggestion (Mau, 2016).

Additionally, high school STEM GPA was predictive of persisting and attaining a STEM degree. School counselors encourage high achievement from all students, and this result does not suggest that school counselors should focus their STEM career exploration on just those students who have higher STEM GPAs, assuming those with lower STEM GPAs will not want to enroll as STEM majors in college or cannot be successful once there. All students, regardless of STEM GPA, should receive STEM counseling opportunities. School counselors should also strive to create an environment that is inclusive for all students to be successful in STEM. Further, school counselors can connect their students to the resources to support their success in STEM coursework.

Math and science self-efficacy were important predictive factors of persistence and attainment in a STEM degree, and these areas of self-efficacy can be targeted through interventions with students; previous literature has provided suggestions on how school counselors can do so (Falco, 2017; Schmidt et al., 2012; Shillingford et al., 2017). Developing STEM self-efficacy is important, because when this was held constant, there were no students of different races/ethnicities who were at lower odds of persisting and attaining a STEM degree, nor did SES have an influence on outcomes. School counselors must remain vigilant of the structural inequalities underrepresented students face and remove these barriers (Wolniak et al., 2016).

The results of this study also emphasize the importance of counselor educators intentionally discussing STEM career development in the career counseling and other school counseling curriculum. Research has shown school counselors do not feel knowledgeable about careers in the STEM fields and desire more STEM content information to inform their work (Cabell et al., 2021; Hall et al., 2011). STEM counseling within the school counselor repertoire is a relatively new topic (Schmidt et al., 2012), and counselor educators must be aware of this counseling area and incorporate it into their curriculum. Additionally, the results of this study support the need for collaborations between university counseling programs and neighboring school districts to increase counseling access and improve underrepresented students’ STEM outcomes. Finally, both counselor educators and school counselors can use the results of this study, and the many others that have proven the effectiveness of school counseling, to advocate for lower counselor-to-student ratios and more funding for school counselors.

Limitations and Future Research
     There are limitations to utilizing secondary analysis of existing data. Specifically, researchers are not privy to selection of the variables and the researchers’ bias can influence which variables are selected to study an outcome; there are many more variables in this dataset which could be included for an exploration of the research question (Cheng & Phillips, 2014). However, the use of the NCES-led HSLS:09 dataset allowed for an extensive number of variables for a massive longitudinal study (NCES, 2020a). A potential area for future exploration in this model could also be school counselors’ self-efficacy in college counseling and STEM counseling and how that impacts students’ outcomes. Further, causal inferences should not be assumed in logistic regression models; probability in correctly predicting an outcome does not mean that these variables cause the outcomes (Tabachnick & Fidell, 2013).

Future research studies could utilize multilevel modelling methods to account for school-level variables, such as staff-to-student ratio, percentage of students on free-and-reduced lunch, and geographic area. This would further investigate systemic influences on access to school counseling and student outcomes and could have the potential to increase the percentage of variance accounted for by the models. Additionally, there has recently been follow-up data added to the HSLS:09 dataset, which includes postsecondary transcripts; this study could be replicated with this data.

Research on school counselors and STEM is growing and should be continued. For instance, researchers have explored school counselors’ experiences regarding STEM and STEM counseling (Cabell et al., 2021; Shillingford et al., 2017). Quantitative research surrounding this topic is needed as well to measure differences in STEM counseling allocation and student STEM outcomes as a result of school counselors’ preparation and efficacy in this area. Finally, an understanding of how counselor education programs are and are not preparing their students to engage in college-readiness counseling and STEM counseling is warranted.

Conclusion

This study provides encouraging results regarding the impact of school counselors’ college-readiness counseling on students’ STEM major attainment and persistence. Results detailed how science and math self-efficacy had strong predictive power on STEM outcomes, which informs school counseling practice. Through increased training in college-readiness counseling and STEM counseling in school counseling training programs, and continued attention to a holistic model of college readiness, school counselors can continue to play an integral role in all students’ college and STEM readiness through providing college-readiness counseling (Gilfillan, 2017; Schmidt et al., 2012).

 

Conflict of Interest and Funding Disclosure
Data collected and content shared in this article
were part of a dissertation study, which was
awarded the 2021 Dissertation Excellence Award
by the National Board for Certified Counselors.

 

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Dana L. Brookover, PhD, NCC, is a licensed school counselor and an assistant professor at the University of Scranton. Correspondence may be addressed to Dana L. Brookover, McGurrin Hall Room 435, McGurrin Hall, The University of Scranton, Scranton, PA 18510, brookoverdl@gmail.com.

 

Suicide, Suicide Assessment Self-Efficacy, and Workplace Anxiety: Implications for Training, Practice, and Research

Alexander T. Becnel, Lillian Range, Theodore P. Remley, Jr.

 

In a national sample of current school counselors with membership in the American School Counselor Association (N = 226), we examined the prevalence of suicide training among school counselors as well as differences in suicide assessment self-efficacy and workplace anxiety between school counselors who were exposed to student suicide and those who were not. The results indicate that 38% of school counselors were not prepared for suicide prevention during graduate training. Although school counselors’ exposure to suicide was not related to their workplace anxiety, those who were exposed to a student suicide attempt had higher suicide assessment self-efficacy scores than those who were not. This study demonstrates the impact of suicide exposure on school counselors and the need for additional suicide assessment training.

Keywords: school counselors, suicide, suicide assessment, self-efficacy, workplace anxiety

 

     Suicide continues to be a growing concern for young people in the United States. Suicide is the second leading cause of death among children between the ages of 11 and 18, claiming the lives of 2,127 middle school– and high school–aged children in 2019 alone (Centers for Disease Control and Prevention [CDC], 2021). In 2019, a nationwide survey found that 18.8% of high school students reported seriously considering attempting suicide, 15.7% reported making a plan to attempt suicide, and 8.9% reported attempting suicide (Ivey-Stephenson et al., 2019). As youth suicide rates continue to rise (National Institute of Mental Health [NIMH], 2019), it is becoming increasingly important to understand how school counselors are prepared to work with suicidal youth, as well as the impact of suicidality on them.

     Children and adolescents spend significant amounts of time at school, making school counselors the primary suicide and risk assessors for this population (American School Counselor Association [ASCA], 2020b). School counselors are more likely to assess youth for suicide risk than any other mental health professional (Schmidt, 2016). In 2002, a national study of ASCA members found that 30% of professional school counselors experienced a suicide-related crisis event while they were graduate student interns (Allen et al., 2002). In a more recent study, about two thirds of school counselors reported that they were conducting multiple suicide assessments each month (Gallo, 2018). Stickl Haugen et al. (2021) found that 79.8% of school counselors worked with a student who had previously attempted suicide and 36.7% experienced a student’s death by suicide. As school counselors become more frequently exposed to student suicide, it is important to understand their preparation for this role and the impact of these events on the school counselors themselves.

School Counselor Suicide and Crisis Training
     Although school counselors are often exposed to student suicide, many school counselors lack appropriate crisis intervention and suicide assessment training (Allen et al., 2002; Springer et al., 2020; Wachter Morris & Barrio Minton, 2012) and lack confidence in their ability to assess students for suicide risk (Gallo, 2018; Schmidt, 2016). About 20 years ago, one third of school counselors entered the field without any formal crisis intervention coursework and nearly 60% did not feel adequately prepared to handle a school crisis event (Allen et al., 2002). Ten years later, school counselors did not fare any better, with less than a quarter of school counselors reporting that they completed a course in crisis intervention and nearly two thirds reporting that a crisis intervention course was not even offered during their master’s program (Wachter Morris & Barrio Minton, 2012). Not surprisingly, therefore, school counselors feel unprepared. In a national survey, 44% of school counselors reported being unprepared for a student suicide attempt, and 57% reported being unprepared for a student’s death by suicide (Solomonson & Killam, 2013). In another national survey, Gallo (2018) found that only 50% of school counselors thought that their training adequately prepared them to assess suicidal students, and only 59% felt prepared to recognize a student who was at risk. These results are especially troubling considering that the Council for Accreditation of Counseling and Related Educational Programs (CACREP) requires school counselor education programs to provide both suicide prevention and suicide assessment training (CACREP, 2015).

Exposure to Suicide and Self-Efficacy
     Mental health professionals often question their professional judgment following an exposure to suicide (Sherba et al., 2019; Thomyangkoon & Leenars, 2008). Consequently, it is imperative to explore school counselor self-efficacy in the aftermath of a student suicide. Self-efficacy is the degree to which individuals believe that that they can achieve self-determined goals, and individuals are more likely to be successful in achieving those goals simply by belief in their success (Bandura, 1986). Counselor self-efficacy is defined as counselors’ judgment of their ability to provide counseling to their clients (Larson et al., 1992). As counselors spend more years in practice, their self-efficacy increases (Goreczny et al., 2015; Kozina et al., 2010; Lent et al., 2003). Further, counselor education faculty have significantly higher levels of suicide assessment self-efficacy than their students (Douglas & Wachter Morris, 2015). The relationship between counselor self-efficacy and work experience is well documented, so it is imperative to control for years of counseling experience as a potential covariate when studying other factors that can affect counselor self-efficacy.

     Although the literature regarding school counselors’ exposure to suicide is sparse, more studies have focused on the experiences of related professions, such as clinical counselors, social workers, psychiatrists, and psychologists. In a national survey, 23% of clinical counselors experienced a client’s death by suicide at some point in their career (McAdams & Foster, 2002). In the aftermath of their clients’ deaths by suicide, those counselors reported a loss of self-esteem and an increase of intrusive thoughts. They increased referrals for hospitalization for clients at risk, gave increased attention to signs for suicide, and increased their awareness of legal liabilities in their practices. In a study of community-based mental health professionals who experienced a client death by suicide, one third considered changing careers and about 15% considered early retirement in the aftermath of the suicide (Sherba et al., 2019). Psychologists who felt responsible for the death were more likely to experience a sense of professional incompetence (Finlayson & Graetz Simmonds, 2018). Among psychiatrists, those who experienced a patient’s suicidal death were more likely in the future to suggest hospitalization for patients who showed risk signs for suicide (Greenberg & Shefler, 2014). Additionally, 20% of the psychiatrists in Thomyangkoon and Leenars’s (2008) study considered changing professions after experiencing a patient death by suicide. Given the similarities in these professions, it is reasonable to suggest that school counselors may feel more anxious about their jobs following a suicide exposure.

     To date, there are only three published studies that explore suicide exposures among school counselors (Christianson & Everall, 2008; Gallo et al., 2021; Stickl Haugen et al., 2021). In a qualitative study, high school counselors felt a lack of personal support from their fellow staff members and noted the importance of self-care in the aftermath of a student death by suicide. Additionally, those who lost students to suicide thought that a lack of practice standards made it difficult to navigate these difficult situations (Christianson & Everall, 2008). In another qualitative study, elementary school counselors who worked with suicidal students recognized their important work in preventing suicide but also reported a lack of suicide prevention training opportunities tailored toward working with young children (Gallo et al., 2021). In a quantitative study, most school counselors thought that a student’s death by suicide left both personal and professional impacts on their lives. These school counselors most often reported low mood, a sense of guilt or responsibility, and preoccupation with the incident as personal impacts. They also identified heightened awareness of suicide risk, more professional caution around suicide, and seeking additional training as professional impacts. The researchers suggested that future studies should determine if the number of student deaths by suicide influences the impact of the suicide exposure (Stickl Haugen et al., 2021). However, this study did not examine anxiety, an important personal impact, nor did it examine self-efficacy in dealing with suicide attempts, a more likely occurrence than suicide deaths.

Research Questions
     The following research questions guided this study:

  • What is the prevalence of graduate and postgraduate training in suicide prevention, crisis intervention, and suicide postvention among current school counselors?
  • Are there differences in suicide assessment self-efficacy between school counselors exposed and not exposed to student deaths by suicide and suicide attempts, controlling for years of school counseling experience as a covariate?
  • Does the number of suicide exposures relate to school counselors’ level of suicide assessment self-efficacy when controlling for years of school counseling experience as a covariate?
  • Are there differences in workplace anxiety between school counselors exposed and not exposed to student deaths by suicide and suicide attempts, controlling for years of school counseling experience as a covariate?

Method

Procedure
     We obtained approval from our university’s Human Subjects Protection Review Committee prior to conducting this study. Using a random number generator, we randomly selected 5,000 members from the ASCA member directory to receive a link to the survey. When potential participants clicked the link, they viewed and agreed to an informed consent statement before they were permitted to view the survey. This statement also informed participants that they could stop participation or withdraw their participation at any time. Upon agreement to the informed consent statement, participants were directed to the survey. This online survey was administered via Qualtrics, which allowed them to respond anonymously.

Participants
     From the 5,000 potential participants, 422 began the survey. From these participants, 101 opened the survey and did not answer any questions, 5 did not agree to the informed consent statement, 29 reported that they were not current school counselors, and 60 did not complete the survey. Thus, 226 of the 5,000 ASCA members completed the survey (4.52%). An a priori power analysis (Cohen, 1992) with a power of .8, a medium effect size, and α = .05 determined that the required sample size for our most robust test was 175.

     Participants were 226 current school counselors (201 women, 88.9%; 25 men, 11.1%). The racial categories included 192 White (85%), nine Black or African American (4%), eight “other” races (3.5%), six Asian (2.7%), five biracial or multiracial (2.2%), three American Indian or Alaska Native (1.3%), and three not reporting race (1.3%). The ethnicity categories included 210 participants (92.9%) who were not of Hispanic or Latino or Spanish origin and 16 (7.1%) who were of Hispanic or Latino or Spanish origin. The mean age was 39 years (SD = 10.68), and the mean years of experience working as a school counselor was 7 (SD = 6.98). With regard to school setting, 52 school counselors worked in an elementary or primary school (23%), 58 worked in a middle or junior high school (25.7%), 81 worked in a high school (35.8%), 19 worked in a K–12 school (8.4%), and 16 worked in another type of school not listed (7.1%). Although ASCA does not provide demographic information about their members, this sample is similar in its demographic makeup to the sample in Gilbride et al.’s (2016) study, which sought to describe the demographic identity of ASCA’s membership.

Instrumentation
     The survey packet consisted of three instruments: the demographic questionnaire, the Counselor Suicide Assessment Efficacy Survey (CSAES; Douglas & Wachter Morris, 2015), and the Workplace Anxiety Scale (WAS; McCarthy et al., 2016).

Demographic Questionnaire
     Using a demographic questionnaire, we asked participants to identify the following information: sex, race, ethnicity, age, years of school counseling experience, and school type (e.g., high school, middle school). Additionally, we asked participants to identify the types of suicide exposures that they have encountered in their school counseling careers. If they reported exposure to either deaths by suicide or suicide attempts, the survey followed up with additional questions about the number of exposures, the amount of time since the first suicide exposure, and the amount of time since the most recent suicide exposure. We asked participants if their schools had crisis plans or crisis teams. We also asked participants if they had training in suicide prevention, crisis intervention, and suicide postvention during graduate school and the number of postgraduate training hours in each of these areas.

CSAES
     The CSAES evaluates counselors’ confidence in their ability to assess clients for suicide risk and intervene with a client at risk of suicide. It includes 25 items in four subscales: General Suicide Assessment, Assessment of Personal Characteristics, Assessment of Suicide History, and Suicide Intervention. Each item is rated on a 5-point Likert scale from 1 (not confident) to 5 (highly confident). High scores indicate high self-efficacy. Among school counselors in the original study, each subscale had good internal consistency (α = .88–.81) and acceptable goodness of fit. As suggested by Douglas and Wachter Morris (2015), we scored each subscale separately and averaged each score. This process created four comparable subscale scores.

WAS
     The WAS measures participants’ job-related anxiety. This scale asks participants to rate eight items such as “I worry that my work performance will be lower than that of others at work” on a 5-point scale from 1 (strongly disagree) to 5 (strongly agree). High scores on the WAS indicate higher levels of job-related anxiety. The WAS demonstrated good internal consistency (α = .94) and acceptable goodness of fit (McCarthy et al., 2016).

Data Analysis
     To address our first research question, we used descriptive statistics to examine the prevalence of training among the participants. We used analysis of covariance (ANCOVA) to detect differences in both suicide assessment self-efficacy (CSAES scores) and workplace anxiety (WAS scores) while controlling for years of school counseling experience between school counselors who were exposed to student suicide and those who were not. We considered exposure to deaths by suicide and exposure to suicide attempts as different types of exposure. Therefore, we performed a total of four ANCOVAs: (a) differences in CSAES scores between school counselors exposed to deaths by suicide and those not exposed, (b) differences in CSAES scores between school counselors exposed to suicide attempts and those not exposed, (c) differences in WAS scores between school counselors exposed to deaths by suicide and those not exposed, and (d) differences in WAS scores between school counselors exposed to suicide attempts and those not exposed. We also used analysis of variance (ANOVA) to determine the difference in years of school counseling experience between those exposed to suicide and those not exposed. To determine the relationship between the number of suicide exposures and counselor suicide assessment self-efficacy, we also completed two partial correlations between the number of exposures to student death by suicide and CSAES scores, and the number of exposures to student suicide attempts and CSAES scores.

Results

     A total of 64 school counselors reported that they experienced a student death by suicide during their school counseling experience (28.3%), with a mean of 2.11 deaths (SD = 2.21). On average, their first suicide death was 6.72 years ago (SD = 5.87), and the most recent suicide death was 3.84 years ago (SD = 3.88). A total of 124 participants experienced a student suicide attempt during their school counseling experience (54.9%), with a mean of 5.36 attempts (SD = 10.54). On average, the first suicide attempt was 5.91 years ago (SD = 6.07), and the most recent attempt was 1.82 years ago (SD = 2.10). Of all 226 school counselors, 195 worked in schools that have crisis plans (86.3%), and 170 worked in schools that have crisis teams (75.2%).

Suicide Training
     Regarding suicide prevention training during their graduate program, 140 (62%) received some training, but 86 (38%) received no training. Regarding crisis intervention training during their graduate program, 142 (63%) received some, but 84 (37%) received none. Regarding suicide postvention, only 87 (38.5%) received some, but 139 (61.5%) received none. The number of postgraduate training hours varied widely for each preparation type. For suicide prevention, training hours averaged 12.20 (SD = 28.61); for crisis intervention, training hours averaged 9.04 (SD = 15.51); and for suicide postvention, training hours averaged 6.45 (SD = 18.14). We removed one participant’s postgraduate training data that was more than 3 standard deviations higher than the mean. In order to better illustrate the distribution of postgraduate training hours, we grouped the number of training hours into four categories: 0 hours, 1–10 hours, 11–50 hours, and more than 50 hours of postgraduate training. Nearly a quarter of the participants (24.3%) received no postgraduate training in suicide prevention, about a third of the participants (30.5%) received no postgraduate training in crisis intervention, and half (50.4%) received no postgraduate training in suicide postvention.

     To further demonstrate the disparity of suicide training, cross-tabulation was performed between graduate training and the number of postgraduate training hours. We reported this data in Table 1. Most surprisingly, 25 school counselors (11.1%) received no graduate training in suicide prevention, nor any postgraduate hours of training in suicide prevention; another 45 (19.9%) received no graduate training and only 10 or fewer hours of postgraduate training in suicide prevention, making nearly 1 in 3 school counselors unprepared to provide suicide prevention services. Crisis intervention fared similarly with 26 school counselors (11.5%) reporting no graduate training and no postgraduate training hours and 41 school counselors (18.1%) reporting no graduate training and 10 or fewer postgraduate training hours. Again, nearly 1 in 3 school counselors were not adequately prepared to provide this important service. Crisis postvention fared the worst, with 80 school counselors (35.4%) reporting that they received no graduate training and no postgraduate training hours, and 46 school counselors (20.4%) reporting no graduate training and fewer than 10 hours of postgraduate training. More than half of the school counselors surveyed are unprepared to face the aftermath of a suicide.

 

Table 1 

Graduate Training and Postgraduate Training Hours

Number of postgraduate training hours Received graduate training Did not receive graduate training
Frequency Percentage Frequency Percentage
Suicide Prevention
   0 hours      30   13.3   25     11.1
   1–10 hours      73   32.3   45     19.9
   11–50 hours      29   12.8   15       6.6
   50 or more hours        8     3.6     1       0.4
Total    140   62.0   86     38.0
Crisis Intervention
   0 hours      43   19.0   26     11.5
   1–10 hours      69   30.5   41     18.1
   11–50 hours      26   11.5   16       7.0
   50 or more hours        4     1.8     1       0.4
Total    142   63.0   84     37.0
Suicide Postvention
   0 hours      34   15.0   80     35.4
   1–10 hours      37   16.4   46     20.4
   11–50 hours      12     5.3   11       4.8
   50 or more hours        4     1.8     2       0.9
Total      87   38.5 139     61.5

 

Suicide Exposure and Suicide Assessment Self-Efficacy
     An ANOVA indicated that school counselors exposed to a student death by suicide had significantly more years of school counseling experience (M = 11.9, SD = 7.87) than school counselors not exposed to a student death by suicide (M = 5.1, SD = 5.56): F(1, 224) = 21.512, p < .001. Controlling for years of school counseling experience as a covariate, an ANCOVA indicated that there was no significant difference between these two groups in General Suicide Assessment, F(1, 223) = .316, p = .574; Assessment of Personal Characteristics, F(1, 223) = .156, p = .694; Suicide Intervention, F(1, 223) = .028, p = .867; or Assessment of Suicide History, F(1, 223) = 1.095, p = .133.

     Similarly, results of an ANOVA indicated that school counselors exposed to student suicide attempts had significantly more years of school counseling experience (M = 8.8, SD = 7.31) than counselors not exposed (M = 4.9, SD = 5.94): F(1, 224) = 8.055, p = .005. Controlling for years of school counseling experience, an ANCOVA indicated significant differences between the two groups in General Suicide Assessment, F(1, 223) = 6.014, p = .015; Assessment of Personal Characteristics, F(1, 223) = 7.140, p = .008; and Suicide Intervention, F(1, 223) = 6.671, p = .010; but not Assessment of Suicide History, F(1, 223) = .763, p = .383. Overall, effect sizes were small.

Number of Exposures and Self-Efficacy
     A partial correlation between the number of suicide exposures and CSAES scores while controlling for years of school counseling experience was not statistically significant. There was no significant relationship between the number of death by suicide exposures and General Suicide Assessment, r(61) = .137, p = .285; Assessment of Suicide History, r(61) = .207, p = .104; Assessment of Personal Characteristics, r(61) = .170, p = .184; or Suicide Intervention, r(61) = .077, p = .551. Likewise, there was also no significant relationships between the number of suicide attempt exposures and General Suicide Assessment, r(121) = −.028, p = .762; Assessment of Suicide History, r(121) = .087, p = .336; Assessment of Personal Characteristics, r(121) = .131, p = .150; or Suicide Intervention, r(121) = .076, p = .401. We reported data regarding the frequency of suicide exposure in Table 2.

Suicide Exposure and Workplace Anxiety
     In WAS scores, an ANCOVA revealed that there were no significant differences between school counselors exposed and not exposed to a student death by suicide when controlling for years of school counseling experience: F(1, 223) = .412, p = .522. Likewise, an ANCOVA revealed that there was no significant difference in WAS scores between school counselors exposed and not exposed to student suicide attempts when controlling for years of school counseling experience: F(1, 223) = .238, p = .626. To further illustrate the relationship between years of school counseling experience and workplace anxiety, a correlation coefficient indicated that these measures were significantly related, r(224) = −.260, p < .001.

Discussion

     Among these school counselors, more than a quarter experienced a student’s death by suicide and over half experienced a student’s suicide attempt. These results are consistent with previous studies indicating that many school counselors will eventually be exposed to a student suicide during their careers (Allen et al., 2002; Gallo, 2018; Schmidt, 2016; Stickl Haugen et al., 2021). Given how common suicide experiences are, school counselors need to be trained to manage suicide-related crises.

Training
     A surprising result in our study was the overall lack of suicide and crisis training reported. As seen in Table 1, nearly 2 in 5 school counselors (38%) reported that they received no suicide prevention training during their graduate education. Additionally, a quarter of the school counselors in this study reported that they received no postgraduate training in suicide prevention, and half reported between 1 and 10 hours. Thus, a sizeable portion of these school counselors were not adequately trained to incorporate suicide prevention programs into their school counseling practice. This finding echoes Gallo (2018), who reported that only 60% of school counselors felt prepared to identify students at risk for suicide. These rates are poor considering that CACREP requires suicide assessment and suicide prevention training as a standard of all counselor education programs (CACREP, 2015). Further, ASCA states that school counselors are responsible for identifying students at risk for suicide and ensuring that suicide prevention programs are in place in schools (ASCA, 2020a). The lack of training reported in this study is particularly troubling given that all of the participants in this study were members of ASCA.

 

Table 2 

Frequency of Student Suicide Exposure

Variable Frequency Percentage
Number of student deaths by suicide (n = 64)
   1 37 57.8
   2 15 23.4
   3–5   8 12.5
   > 5   4   6.3
Years since first death by suicide (n = 64)
   Within 1 year 12 18.8
   1 and 5 years 25 39.0
   6 and 10 years 12 18.8
   More than 10 years 15 23.4
Years since most recent death by suicide (n = 64)
   Within 1 year 23 35.9
   Between 1 and 5 years 26 40.6
   Between 6 and 10 years 11 17.2
   More than 10 years   4   6.3
Number of student suicide attempts (n = 124)
   1 29 23.4
   2 29 23.4
   3–5 44 35.5
   > 5 22 17.7
Years since first student attempt (n = 124)
   Within 1 year 30 24.2
   Between 1 and 5 years 51 41.1
   Between 6 and 10 years 21 17.0
   More than 10 years 22 17.7
Years since most recent attempt (n = 124)
   Within 1 year 84 67.7
   Between 1 and 5 years 33 26.6
   Between 6 and 10 years   6   4.8
   More than 10 years   1   0.8

 

     Crisis intervention training among school counselors also was poor. Comparable to the finding on suicide prevention training, a third of these school counselors reported no graduate training in crisis intervention. Further, more than a third reported that they did not receive postgraduate training hours in crisis intervention, and nearly half received between 1 and 10 hours of postgraduate training. A significant portion of these school counselors were not adequately prepared to respond to crises in their schools. These findings are slightly worse than the findings from 20 years ago when one third of a sample of school counselors reported that they entered the field with no formal crisis intervention coursework (Allen et al., 2002). However, these findings are much better than Wachter Morris and Barrio Minton’s (2012) study in which only 20% of school counselors completed a course in crisis intervention during their master’s degree program. Although preparation has increased, crisis preparation for school counseling students must continue to improve given that school counselors regularly experience crises (Wachter, 2006) and school counseling students often experience crises while still in graduate school completing their practicum or internship (Wachter Morris & Barrio Minton, 2012). The number of school counselors who experienced a student suicide event in the current study also supports the notion that school counselors regularly experience crises.

     Most of these school counselors (61.5%) were not trained in their graduate programs for suicide postvention. Half of the surveyed school counselors reported that they received no postgraduate training hours in suicide postvention, with an additional 38% reported having received between 1 and 10 hours of postgraduate training. These results demonstrate that the vast majority of school counselors are not prepared to respond to a student’s suicidal death. This finding is distressing because school counselors play a vital role in the aftermath of a student suicide (Maples et al., 2005; Substance Abuse and Mental Health Services Administration [SAMHSA], 2016).

Suicide Assessment Self-Efficacy
     Among these counselors, exposure to suicide alone did not make a difference with their suicide assessment self-efficacy or workplace anxiety. Years of school counseling experience appears to have a much more important role in suicide assessment self-efficacy and reduced anxiety than experiencing a student’s death by suicide. This result supports previous studies that found that years of experience has a positive relationship with self-efficacy (Douglas & Wachter Morris, 2015; Kozina et al., 2010; Lent et al., 2003). It also parallels the previous finding that the impact of a client’s suicidal death on a mental health practitioner decreases as the practitioner gains years of experience (McAdams & Foster, 2002). This result is different from Stickl Haugen et al.’s (2021) finding that school counselors who were exposed to a student death had higher levels of suicide assessment self-efficacy than those not exposed. However, Stickl Haugen et al. did not control for years of school counseling experience.

     In contrast, exposure to suicide attempts did make a difference in suicide assessment self-efficacy. Even after controlling for years of experience, counselors with suicide attempt experience reported more efficacy in three of four subscales: General Suicide Assessment, Assessment of Personal Characteristics, and Suicide Intervention. One explanation for this outcome is that a student suicide attempt experience might motivate school counselors to learn about suicide and the risk factors associated. This explanation echoes Wagner et al.’s (2020) finding that counselors found additional training in the aftermath of a suicide very helpful. Many of the school counselors in the current study received no formal training, so it is possible that these experiences helped them fill in knowledge gaps, which in turn increased their self-efficacy. Training increases self-efficacy (Al-Darmaki, 2004; Mirick et al., 2016; Wachter Morris & Barrio Minton, 2012), so it is also possible that this experience worked as an in vivo training for these school counselors, increasing their self-efficacy.

Workplace Anxiety
     Although mental health clinicians often experience symptoms of anxiety in the wake of a student suicide (McAdams & Foster, 2002; Sherba et al., 2019), present results suggest that a student’s death or suicide attempt does not have an impact on school counselors’ workplace anxiety. One explanation for this finding is the relationship between self-efficacy and anxiety. Overall, these school counselors had high self-efficacy scores in each of the four subscales. Previous research indicated that as self-efficacy increases, anxiety decreases (Bodenhorn & Skaggs, 2005; Gorecnzy et al., 2015; Larson et al., 1992). The death by suicide experience might not have impacted the counselors’ anxiety in this study because of their overall high self-efficacy. Another explanation is that the school counselors in this study had on average several years of experience (M = 7.05). Workplace anxiety levels decrease as school counselors spend more time on the job.

Implications
     These results have several implications for school counselors and school counselor educators. First, school counselor educators and school counseling graduate programs should be aware of both the overall disparity of graduate-level suicide and crisis training as well as the benefits that training can provide to future school counselors. Regarding suicide prevention, crisis intervention, and suicide postvention, there are far too many untrained school counselors among the current body of school counselors. School counseling students are a vulnerable group when it comes to suicide assessment self-efficacy (Douglas & Wachter Morris, 2015), so it is imperative to support their professional development. School counseling graduate programs must increase their efforts to adequately train and prepare school counselors for suicide prevention, assessment, and intervention.

     Second, school counselors should prepare to face the probability of having to deal with student suicide attempts and student deaths by suicide. If school counselors do not receive this training during their graduate programs, then they must seek continuing education opportunities that address suicide prevention, crisis intervention, and suicide postvention. Suicide and crisis training increases counselor self-efficacy (Mirick et al., 2016; Wachter Morris & Barrio Minton, 2012), making appropriate preparation vital. Additionally, school counselors could consider clinical supervision as a supplemental layer of support. School counselors receive supervision at much lower rates than their clinical counterparts (Perera-Diltz & Mason, 2012) even though many school counselors desire more supervision (Cook et al., 2012). Given that school counseling–focused supervision can increase self-efficacy (Tang, 2019) and school counselors feel a lack of personal support in the aftermath of a suicide (Christianson & Everall, 2008), school counselors must seek clinical supervision.

     Finally, school counselor educators should consider training efforts that focus specifically on student suicide attempts. In the current study, school counselors exposed to a suicide attempt were more efficacious than school counselors not exposed to a student suicide attempt. Modeling these experiences through the use of specific role plays could help school counseling students feel more confident about their suicide assessment capabilities. Although CACREP does not require counselor education programs to provide suicide postvention training (CACREP, 2015), perhaps standards should adapt to include this important training area. Regardless, programs should also emphasize this training to best prepare school counselors.

Limitations and Suggestions for Future Research
     Some factors limited this study. Although we had a national sample, we surveyed only current members of ASCA. It is possible that school counselors who are not members of ASCA might have responded differently. The study also had a low response rate (4.64%). Those school counselors who responded may be uniquely interested in this area, so the results may not reflect all school counselors. This study also did not limit the types of school counselors who could participate. It is possible that school counselors who work with younger children, such as elementary and primary school counselors, have less familiarity with suicide assessment and intervention than those school counselors who work with older children. The inclusion of these counselors could have affected the results of this study. Finally, this study did not ask participants if they graduated from a CACREP-accredited program. Because suicide prevention and assessment training are required components of CACREP-accredited programs, it is possible that school counselors who graduated from these programs may have different levels of training and self-efficacy than those trained in unaccredited programs.

     For future studies, researchers should consider limiting their samples to specific levels of schooling such as elementary, middle, or high school. This change would help illustrate the nuanced differences among school counselors in different academic environments as well as increase focus on the school counselors who most often work with suicidal students. Future studies should also consider surveying a sample that includes all school counselors, not just ASCA members. Researchers should also differentiate between school counselors who graduated from CACREP-accredited programs and those who did not. Collecting this data would allow researchers to detect if there are any differences in suicide assessment training and self-efficacy between these two groups. Finally, future researchers should consider designing a study that seeks to identify the factors that most impact suicide assessment self-efficacy. Although this study showed that a suicide attempt experience could impact suicide assessment self-efficacy, other factors, such as self-confidence, could have a larger influence.

     Suicide continues to be understudied in school counseling. Even though this study demonstrates the high likelihood that a school counselor will experience a student suicide, school counselors continue to report a lack of preparation in suicide prevention, crisis intervention, and suicide postvention. Although school counselors who experienced a student suicide attempt appeared to gain self-efficacy from their experiences, additional training in counseling suicidal students might help school counselors feel prepared before they face such serious situations. If additional training can help school counselors save students from suicide, then efforts must be made to adequately prepare them.

 

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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Alexander T. Becnel, PhD, NCC, LPC, is a doctoral candidate at the University of Holy Cross. Lillian Range, PhD, is a professor at the University of Holy Cross. Theodore P. Remley, Jr., JD, PhD, NCC, is a professor at the University of Holy Cross. Correspondence may be addressed to Alexander T. Becnel, 4123 Woodland Drive, New Orleans, LA 70131, abecnel2@uhcno.edu.

Group Differences Between Counselor Education Doctoral Students’ Number of Fieldwork Experiences and Teaching Self-Efficacy

Eric G. Suddeath, Eric R. Baltrinic, Heather J. Fye, Ksenia Zhbanova, Suzanne M. Dugger,
Sumedha Therthani

 

This study examined differences in 149 counselor education doctoral students’ self-efficacy toward teaching related to their number of experiences with fieldwork in teaching (FiT). Results showed counselor education doctoral students began FiT experiences with high levels of self-efficacy, which decreased after one to two FiT experiences, increased slightly after three to four FiT experiences, and increased significantly after five or more FiT experiences. We discuss implications for how counselor education doctoral programs can implement and supervise FiT experiences as part of their teaching preparation practices. Finally, we identify limitations of the study and offer future research suggestions for investigating FiT experiences in counselor education.

Keywords: teaching preparation, self-efficacy, fieldwork in teaching, counselor education, doctoral students

 

Counselor education doctoral students (CEDS) need to engage in actual teaching experiences as part of their teaching preparation (Baltrinic et al., 2016; Baltrinic & Suddeath, 2020a; Barrio Minton, 2020; Swank & Houseknecht, 2019), yet inconsistencies remain in defining what constitutes actual teaching experience. Fortunately, several researchers (e.g., Association for Counselor Education and Supervision [ACES], 2016; Hunt & Weber Gilmore, 2011; Suddeath et al., 2020) have identified examples of teaching experiences, which we aggregated and defined as fieldwork in teaching (FiT). FiT includes the (a) presence of experiential training components such as co-teaching, formal teaching practicums and/or internships, and teaching assistantships (ACES, 2016); (b) variance in amount of responsibility granted to CEDS (Baltrinic et al., 2016; Barrio Minton & Price, 2015; Orr et al., 2008; Suddeath et al., 2020); and (c) use of regular supervision of teaching (Baltrinic & Suddeath, 2020a; Suddeath et al., 2020). Findings from several studies suggested that a lack of FiT experience can thwart CEDS’ teaching competency development (Swank & Houseknecht, 2019), contribute to CEDS’ feelings of insufficient preparation for future teaching roles (Davis et al., 2006), create unnecessary feelings of stress and burnout for first-year faculty (Magnuson et al., 2004), and lead to feelings of inadequacy among new counselor educators (Waalkes et al., 2018). Counselor education (CE) researchers reference FiT experiences (Suddeath et al., 2020) among a variety of teaching preparation practices, such as co-teaching (Baltrinic et al., 2016), supervision of teaching (Baltrinic & Suddeath, 2020a), collaborative teaching teams (CTT; Orr et al., 2008), teaching practicums (Baltrinic & Suddeath, 2020a; Hall & Hulse, 2010), teaching internships (Hunt & Weber Gilmore, 2011), teaching to peers within teaching instruction courses (Baltrinic & Suddeath, 2020b; Elliot et al., 2019), and instructor of record (IOR) experiences (Moore, 2019).

Participants across studies emphasized the importance of including FiT experiences within teaching preparation practices. Both CEDS and new faculty members reported that engaging in actual teaching (e.g., FiT) as part of their teaching preparation buffered against lower teaching self-efficacy (Baltrinic & Suddeath, 2020a; Elliot et al., 2019; Suddeath et al., 2020). These findings are important because high levels of teaching self-efficacy are associated with increased student engagement (Gibson & Dembo, 1984), positive learning outcomes (Goddard et al., 2000), greater job satisfaction, reduced stress and emotional exhaustion, longevity in the profession (Klassen & Chiu, 2010; Skaalvik & Skaalvik, 2014), and flexibility and persistence during perceived setbacks in the classroom (Elliot et al., 2019; Gibson & Dembo, 1984).

FiT Within Counselor Education
     Existing CE teaching literature supports the presence and use of FiT within a larger framework of teaching preparation. Despite existing findings, variability exists in how FiT is both conceptualized and implemented among doctoral programs and in how doctoral students specifically engage in FiT during their program training. Current literature supporting FiT suggests several themes, which are outlined below, to support our gap in understanding of (a) whether FiT experiences are required, (b) the number of FiT experiences in which CEDS participate, (c) the level and type of student responsibility, and (d) the supervision and mentoring practices that support student autonomy within FiT experiences (e.g., Baltrinic et al., 2016, 2018; Orr et al., 2008; Suddeath et al., 2020).

Teaching Internships and Fieldwork
     Teaching internships are curricular teaching experiences in which CEDS co-teach (most often) a master’s-level course with a program faculty member or with peers while receiving regular supervision (Hunt & Weber Gilmore, 2011). These experiences are offered concurrently with pedagogy or adult learning courses (Hunt & Weber Gilmore, 2011) or after taking a course (Waalkes et al., 2018). Teaching internships typically include group supervision (Baltrinic & Suddeath, 2020a), though the frequency and structure of supervision varies greatly (Suddeath et al., 2020). Participants in Baltrinic and Suddeath’s (2020a) study reported that teaching practicum and internship experiences are often included alongside multiple types of internships (e.g., clinical, supervision, and research), which led to less time to process their own teaching experiences. The level of responsibility within FiT experiences also varies. Specifically, CEDS may take on minor roles, including “observing faculty members’ teaching and . . . contributing anecdotes from their counseling experiences to class discussion” (Baltrinic et al., 2016, p. 38), providing the occasional lecture or facilitating a class discussion, or engaging in administrative duties such as grading and making copies of course materials (Hall & Hulse, 2010; Orr et al., 2008). Research also suggests that CEDS may share the responsibility for designing, delivering, and evaluating the course (Baltrinic et al., 2016). Finally, CEDS may take on sole/primary responsibility, including the design and delivery of all aspects of a course (Orr et al., 2008).

Co-Teaching and CTT
     It is important to distinguish formal curricular FiT experiences such as teaching practicums and internships from informal co-curricular co-teaching experiences. For example, Baltrinic et al. (2016) identified co-teaching as a process of pairing experienced faculty members with CEDS for the purpose of increasing their knowledge and skill in teaching through supervised teaching experiences. CEDS often receive more individual supervision and mentoring in these informal experiences based on individual agreements between the CEDS and willing faculty members (Baltrinic & Suddeath, 2020a). One example of a formal co-teaching experience (i.e., CTT) comes from Orr et al. (2008). In this model, CEDS initially observe a course or courses while occasionally presenting on course topics. The CEDS then take the lead for designing and delivering the course while under the direct supervision (both live in the classroom and post-instruction) of counseling faculty members.

Instructor of Record
     At times, CEDS have the opportunity to teach a course as the sole instructor, what Moore (2019) and Orr et al. (2008) defined as an instructor of record (IOR). In these cases, IORs are fully responsible for the delivery and evaluation components of the course, including determining students’ final grades. CEDS may take on IOR roles after completing a progression of teaching responsibilities over time under supervision (Moore, 2019; Orr et al., 2008). In some instances, CEDS who serve as IORs are hired as adjunct or part-time instructors (Hebbani & Hendrix, 2014). Ultimately, it seems like a respectable outcome of teaching preparation in general, and specifically FiT, to prepare CEDS to transition into IOR roles. CEDS who attain the responsibility of IOR for one class are partially prepared for managing a larger teaching workload as a faculty member (i.e., teaching three classes per semester; 3:3 load).

Impact of Teaching Fieldwork
     Overall, researchers identified FiT experiences as essential for strengthening CEDS’ feelings of preparedness to teach (Hall & Hulse, 2010), for fostering their teaching identities (Limberg et al., 2013; Waalkes et al., 2018), and for supporting their perceived confidence and competence to teach (Baltrinic et al., 2016; Orr et al., 2008). CE research suggests several factors that contribute to the relative success of the FiT experience. For example, Hall and Hulse (2010) found fieldwork most helpful when the experiences mimicked the actual roles and responsibilities of a counselor educator rather than guest lecturing or providing the occasional lecture. Participants in Hunt and Weber Gilmore’s (2011) study echoed this sentiment, emphasizing the importance of experiences related to the design, delivery, and evaluation of a course. Important experiences included developing or co-developing course curriculum and materials (e.g., exams, syllabi, grading rubrics), facilitating class discussions, lecturing, and evaluating student learning. Additionally, these experiences helped CEDS to translate adult learning theories and pedagogy into teaching practice, which is an essential process for strengthening CEDS’ teaching identity (Hunt & Weber Gilmore, 2011; Waalkes et al., 2018). CE literature also points to the importance of providing CEDS with multiple supervised, developmentally structured (Orr et al., 2008) FiT experiences to increase levels of autonomy and responsibility with teaching and related duties (Baltrinic et al., 2016; Baltrinic & Suddeath, 2020a; Orr et al., 2008). Hall and Hulse found that teaching a course from start to finish contributed most to CEDS’ perceived preparedness to teach. The CTT approach (Orr et al., 2008) is one example of how CE programs developmentally structure FiT experiences.

Research affirms the integration of supervision across CEDS’ FiT experiences (e.g., Baltrinic & Suddeath, 2020a; Elliot et al., 2019; Hunt & Weber Gilmore, 2011). CEDS receive the essential support, feedback, and oversight during supervision that helps them make sense of teaching experiences and identify gaps in teaching knowledge and skills (Waalkes et al., 2018). Research suggests that structured, weekly supervision is most helpful in strengthening CEDS’ perceived confidence (Suddeath et al., 2020) and competence in teaching (Orr et al., 2008). Baltrinic and Suddeath (2020a) and Elliot et al. (2019) also identified supervision of FiT as an essential experience for buffering against CEDS’ fear and anxiety associated with initial teaching experiences. Both studies found that supervision led to fewer feelings of discouragement and perceived failures related to teaching, as well as increased confidence in their capabilities, even when teaching unfamiliar material. Elliot et al. attributed this to supervisors normalizing CEDS’ teaching experiences as a part of the developmental process, which helped them to push through the initial discomfort and fear in teaching and reframe it as an opportunity for growth.

Self-Efficacy Toward Teaching
     Broadly defined, self-efficacy is the future-oriented “belief in one’s capabilities to organize and execute the courses of action required to produce given attainments” (Bandura, 1997, p. 3). Applied to teaching, it is confidence in one’s ability to select and utilize appropriate teaching behaviors effectively to accomplish a specific teaching task (Tschannen-Moran et al., 1998). Research in CE has outlined the importance of teaching self-efficacy on CEDS’ teaching development, including its relationship to a strengthened sense of identity as a counselor educator (Limberg et al., 2013); increased autonomy in the classroom (Baltrinic et al., 2016); greater flexibility in the application of learning theory; increased focus on the teaching experience and students’ learning needs instead of one’s own anxiety; and pushing through feelings of fear, self-doubt, and incompetence associated with initial teaching experiences (Elliot et al., 2019). Previous research affirms FiT as a significant predictor of teaching self-efficacy (Olguin, 2004; Suddeath et al., 2020; Tollerud, 1990). Recently, Suddeath et al. (2020) found that students participating in more FiT experiences also reported higher levels of teaching self-efficacy.

Purpose of the Present Study
     In general, research supports the benefits of FiT experiences (e.g., increased self-efficacy, strengthened teaching identity, and a better supported transition to the professoriate) and ways in which FiT experiences (e.g., multiple, developmentally structured, supervised) should be provided as part of CE programs’ teaching preparation practices. Past and current research supports a general trend regarding the relationship between CE teaching preparation, including FiT experiences, and teaching self-efficacy (Suddeath et al., 2020). However, we know very little about how the number of FiT experiences, specifically, differentially impacts CEDS’ teaching self-efficacy. To address this gap, we examined the relationship between the number of CEDS’ FiT experiences and their reported self-efficacy in teaching. Accordingly, we proceeded in the present study guided by the following research question: How does CEDS’ self-efficacy toward teaching differ depending on amount of FiT experience gained (i.e., no experience in teaching, one to two experiences, three to four experiences, five or more experiences)? This research question was prompted by the work of Olguin (2004) and Tollerud (1990), who investigated CEDS’ reported differences in self-efficacy toward teaching across similarly grouped teaching experiences. We wanted to better understand the impact of FiT experiences on CEDS’ teaching self-efficacy given the prevalence of teaching preparation practices used in CE doctoral programs.

Method

Participant Characteristics
     A total of 171 individuals responded to the survey. Participants who did not finish the survey or did not satisfy inclusionary criteria (i.e., 18 years or older and currently enrolled in a doctoral-level CACREP-accredited CE program) were excluded from the sample, leaving 149 usable surveys. Of these 149 participants, 117 (79%) were female and 32 (21%) were male. CEDS ranged in age from 23–59 years with a mean age of 34.73. Regarding race, 116 CEDS (73%) identified as White, 25 (17%) as Black, six (4%) as Asian, one (0.7%) as American Indian or Alaskan Native, and one (0.7%) as multiracial. Fifteen participants (10%) indicated a Hispanic/Latino ethnicity. Of the 149 participants, 108 provided their geographic region, with 59 (39%) reportedly living in the Southern United States, 32 (21%) in the Midwest, 10 (7%) in the West, and eight (5%) in the Northeast. Participants’ time enrolled in a CE program ranged from zero semesters (i.e., they were in their first semester) to 16 semesters (M = 6.20).

Sampling Procedures
     After obtaining IRB approval, we recruited participants using two convenience sampling strategies. First, we sent counselor education and supervision doctoral program liaisons working in CACREP-accredited universities a pre-notification email (Creswell & Guetterman, 2019), which contained an explanation and rationale for this proposed study; a statement about informed consent and approval; a link to the composite survey, which included the demographic questionnaire; a question regarding FiT experiences; the Self-Efficacy Toward Teaching Inventory (SETI; Tollerud, 1990); and a request to forward the recruitment email (which was copied below the pre-notification text) to all eligible doctoral students. Next, we solicited CEDS’ participation through the Counselor Education and Supervision Network Listserv (CESNET-L), which is a professional listserv of counselors, counselor educators, and master’s- and doctoral-level CE students. We sent two follow-up participation requests, one through CESNET-L and the other to doctoral program liaisons (Creswell & Guetterman, 2019) to improve response rates. We further incentivized participation through offering participants a chance to win one of five $20 gift cards through an optional drawing.

Data Collection
     We collected all research data through the survey software Qualtrics. CEDS who agreed to participate clicked the survey link at the bottom of the recruitment email, which took them to an informed consent information and agreement page. Participants meeting inclusionary criteria then completed the basic demographic questionnaire, a question regarding their FiT experiences, and the SETI.

Measures
     We used a composite survey that included a demographic questionnaire, a question regarding FiT experiences, and a modified version of the SETI. To strengthen the content validity of the composite survey, we selected a panel of three nationally recognized experts known for their research on CEDS teaching preparation to provide feedback on the survey items’ “relevance, representativeness, specificity, and clarity” as well as “suggested additions, deletions, and modifications” of items (Haynes et al., 1995, pp. 244, 247). We incorporated feedback from these experts and then piloted the survey using seven recent graduates (i.e., within 4 years) from CACREP-accredited CE doctoral programs. Feedback from the pilot group influenced final modifications of the survey.

Demographic Questionnaire
     The demographic questionnaire included questions regarding CEDS’ sex, age, race/ethnicity, geographic region, and time in program. Example items included: “Age in years?,” “What is your racial background?,” “Are you Hispanic or Latino?,” and “In which state do you live?”

Fieldwork Question
     We used CE literature (e.g., ACES, 2016; Baltrinic et al., 2016; Orr et al., 2008) as a guide for defining and constructing the item to inquire about CEDS’ FiT experiences, which served as the independent variable in this study. In the survey, FiT was defined as teaching experiences within the context of formal teaching internships, informal co-teaching opportunities, graduate teaching assistantships, or independent teaching of graduate or undergraduate courses. Using this definition, participants then indicated “the total number of course sections they had taught or cotaught.” Following Tollerud (1990) and Olguin (2004), we also grouped participants’ FiT experiences into four groups (i.e., no experience, one to two experiences, three to four experiences, five or more experiences) to extend their findings.

Self-Efficacy Toward Teaching
     To measure self-efficacy toward teaching, the dependent variable in this study, we used a modified version of the SETI. The original SETI is a 35-item self-report measure in which participants indicate their confidence to implement specific teaching skills and behaviors in five teaching domains within CE: course preparation, instructor behavior, materials, evaluation and examination, and clinical skills training. We modified the SETI according to the expert panel’s recommendations, which included creating 12 new items related to using technology in the classroom and teaching adult learners, as well as modifying the wording of several items to match CACREP 2016 teaching standards. This modified version of the SETI contained 47 items. Examples of new and modified items in each of the domains included: “Incorporate models of adult learning” (Course Preparation), “Attend to issues of social and cultural diversity” (Instructor Behavior), “Utilize technological resources to enhance learning” (Materials), “Construct multiple choice exams” (Evaluation and Examination), and “Provide supportive feedback for counseling skills” (Clinical Skills Training). The original SETI produced a Cronbach’s alpha of .94, suggesting strong internal consistency. Other researchers using the SETI reported similar findings regarding the internal consistency including Richardson and Miller (2011), who reported alphas of .96, and Prieto et al. (2007), who reported alphas of .94. The internal consistency for the modified SETI in this study produced a Cronbach’s alpha of .97, also suggesting strong internal consistency of items.

Design
     This study used a cross-sectional survey design to investigate group differences in CEDS’ self-efficacy toward teaching by how many FiT experiences students had acquired (Creswell & Guetterman, 2019). Cross-sectional research allows researchers to better understand current beliefs, attitudes, or practices at a single point in time for a target population. This approach allowed us to gather information related to current FiT trends and teaching self-efficacy beliefs across CE doctoral programs.

Data Preparation and Analytic Strategy
     After receiving the participant responses, we coded and entered them into SPSS (Version 27) for conducting all descriptive and inferential statistical analyses. Based upon previous research by Tollerud (1990) and Olguin (2004), we then grouped participants according to the number of experiences reported: no fieldwork experience, one to two experiences, three to four experiences, and five or more experiences. We then ran a one-way ANOVA to determine if CEDS’ self-efficacy significantly (p < .05) differed according to the number of teaching experiences accrued, followed by post hoc analyses to determine which groups differed significantly.

Results

We sought to determine whether CEDS with no experience in teaching, one to two experiences, three to four experiences, or five or more experiences differed in terms of their self-efficacy toward teaching scores. Overall, individuals in this study who reported no FiT experience indicated higher mean SETI scores (n = 10, M = 161.00, SD = 16.19) than those with one to two fieldwork experiences (n = 37, M = 145.59, SD = 21.41) and three to four fieldwork experiences (n = 32, M = 148.41, SD = 20.90). Once participants accumulated five or more fieldwork experiences (n = 70, M = 161.06, SD = 19.17), the mean SETI score rose above that of those with no, one to two, and three to four FiT experiences. The results also indicated an overall mean of 5.51 FiT experiences (SD = 4.63, range = 0–21).

As shown in Table 1, a one-way ANOVA revealed a statistically significant difference between the scores of the four FiT groups, F (3, 145) = 6.321, p < .001, and a medium large effect size (h2 = .12; Cohen, 1992). Levene’s test revealed no violation of homogeneity of variance (p = .763). A post hoc Tukey Honest Significant Difference test allowed for a more detailed understanding of which groups significantly differed. Findings revealed a statistically significant difference between the mean SETI scores for those with one to two fieldwork experiences and five or more experiences (mean difference = −15.46, p = .001) and for those with three to four and five or more experiences (mean difference = −12.65, p = .018). There was no significant difference between those with no FiT experience and those with five or more experiences, and in fact, these groups had nearly identical mean scores (i.e., 161.00 and 161.06, respectively). Although the drop is not significant, there is a mean difference of 15.40 from no FiT experience to one to two experiences. These results suggest that perceived confidence in teaching, as measured by the SETI, began high, dropped off after one to two experiences, slightly rose after three to four, and then increased significantly from 148.41 to 161.06 after five or more experiences, returning to pre-FiT levels.

Table 1

Means, Standard Deviations, and One-Way Analysis of Variance for Study Variables

Measure No FiT 1–2 FiT 3–4 FiT 5 or More FiT F (3, 145) h2
M SD         M    SD M    SD M   SD
SETI 161.00 16.19     145.59  21.41 148.41   20.90 161.06 19.17 6.321* .12

Note. SETI = Self-Efficacy Toward Teaching Inventory; FiT = fieldwork in teaching.
*p < .001.

 

Discussion

The purpose of this study was to investigate whether CEDS with no experience in teaching, one to two experiences, three to four experiences, or five or more experiences differed in terms of their self-efficacy toward teaching scores. Overall, one-way ANOVA results revealed a significant difference in SETI scores by FiT experiences. Post hoc analyses revealed an initial substantial drop from no experience to one to two experiences and a significant increase in self-efficacy toward teaching between one to two FiT experiences and five or more experiences as well as between three to four FiT experiences and five or more experiences.

The CE literature supports the general trend observed in this study, that as the number of FiT experiences increases, so does CEDS’ teaching self-efficacy (e.g., Baltrinic & Suddeath 2020a; Hunt & Weber Gilmore, 2011; Suddeath et al., 2020). Many authors have articulated the importance of multiple fieldwork experiences for preparing CEDS to confidently transition to the professoriate (e.g., Hall & Hulse, 2010; Orr et al., 2008). Participants in a study by Hunt and Weber Gilmore (2011) identified engagement in multiple supervised teaching opportunities that mimicked the actual teaching responsibilities required of a counselor educator as particularly helpful. Tollerud (1990) and Olguin (2004) found that the more teaching experiences individuals acquired during their doctoral programs, the higher their self-efficacy toward teaching. Encouragingly, nearly half of CEDS in this study (47%) indicated that participating in five or more teaching experiences increased their teaching self-efficacy. This increase in teaching self-efficacy may be due to expanded use of teaching preparation practices within CE doctoral programs (ACES, 2016).

Participants in the current study reported an initial drop in self-efficacy after their initial FiT experiences, which warrants explanation. Specifically, the initial drop in CEDS’ self-efficacy could be due to discrepancies between their estimation of teaching ability and their actual capability, further supporting the idea of including actual FiT earlier in teaching preparation practices, albeit titrated in complexity. Though one might assume that as participants acquired additional teaching experience their SETI scores would have increased, the initial pattern from no experience to one to two FiT experiences did not support this. However, self-efficacy is not necessarily a measure of actual capability, but rather one’s confidence to engage in certain behaviors to achieve a certain task (Bandura, 1997). It is plausible that participants may have initially overestimated their own abilities and level of control over the new complex task of teaching, which may explain the initial drop in self-efficacy among participants. For participants lacking FiT experience, social comparison may have led them to “gauge their expected and actual performance by comparison with that of others” (Stone, 1994, p. 453)—in this case, with other CEDS with more FiT experiences.

Social comparisons used to generate appraisals of teaching self-efficacy beliefs may be taken from “previous educational experiences, tradition, [or] the opinion of experienced practitioners” (Groccia & Buskist, 2011, p. 5). Thus, participants in this study who lacked prior teaching experience may have initially overestimated their capability as a result of previous educational experiences. When individuals initially overestimate their abilities to perform a new task, they may not put in the time or effort needed to succeed at a given task. Tollerud (1990) suggested that those without any actual prior teaching experience may not realize the complexity of the task, the effort required, or what skills are needed to teach effectively. In the current study, this realization may be reflected in participants’ initial drop in mean SETI scores from no teaching experiences to one to two teaching experiences.

The CE literature offers clues for how to buffer against this initial drop in self-efficacy. For example, CE teaching preparation research suggests the importance of engaging in multiple teaching experiences (Suddeath et al., 2020) with a gradual increase in responsibility (Baltrinic et al., 2016) and frequent (i.e., weekly) supervision from CE faculty supervisors, as well as feedback and support from peers (Baltrinic & Suddeath, 2020a, 2020b; Elliot et al., 2019). These authors’ findings reportedly support students’ ability to normalize their initial anxiety, fears, and self-doubts; conceptualize their struggle and discomfort as a part of the developmental process; push through perceived failings; and reflect on and grow from initial teaching experiences. Elliot et al. (2019) noted specifically that supervision with peer support increased participants’ (a) ability to access an optimistic mindset amidst self-doubt, (b) self-efficacy in teaching, (c) authenticity in subsequent teaching experiences, and (d) facility with integrating theory into teaching practice. Overall, the current findings add to the CE literature by suggesting CE programs increase the number of FiT experiences (to at least five, preferably) for CEDS.

Our findings also reflect similarities in CEDS’ self-efficacy patterns to those of Tollerud (1990) and Olguin (2004). Similar to Tollerud and Olguin, we grouped participants according to the number of FiT experiences: no fieldwork experience, one to two experiences, three to four experiences, and five or more experiences. This study identified the same pattern in teaching self-efficacy as observed by Tollerud and Olguin, with those who reported no FiT experience indicating higher mean SETI scores than those with one to two FiT experiences and three to four FiT experiences. Although scores slightly increased from one to two FiT experiences to three to four FiT experiences, it was not until CEDS accumulated five or more FiT experiences that the mean SETI score rose above that of those with no FiT experiences. The consistency of this pattern over the span of 30 years seems to confirm the importance of providing CEDS several FiT opportunities (i.e., at least five) to strengthen their  self-efficacy in teaching. Though responsibility within FiT experiences was aggregated in this study as it was in Tollerud and Olguin, research (e.g., Baltrinic et al., 2016; Orr et al., 2008) and common sense would suggest that CEDS need multiple supervised teaching opportunities with progressively greater responsibility and autonomy. However, future research is needed to examine how CEDS’ self-efficacy toward teaching changes over time as they move from having no actual teaching experience, to beginning their FiT, to accruing substantial experiences with FiT.

Implications

For many counselor educators, teaching and related responsibilities consume the greatest proportion of their time (Davis et al., 2006). As such, providing CEDS multiple supervised opportunities (Orr et al., 2008; Suddeath et al., 2020) to apply theory, knowledge, and skills in the classroom before they transition to the professoriate seems important for fostering teaching competency (Swank & Houseknecht, 2019) and, ideally, mitigating against feelings of stress and burnout that some first-year counselor educators experience as a result of poor teaching preparation (Magnuson et al., 2006). Given the initial drop in self-efficacy toward teaching as identified in this study and the relationship between higher levels of self-efficacy and increased student engagement (Gibson & Dembo, 1984) and learning outcomes (Goddard et al., 2000), greater job satisfaction, reduced stress and emotional exhaustion (Klassen & Chiu, 2010; Skaalvik & Skaalvik, 2014), and flexibility and persistence during perceived setbacks in the classroom (Elliot et al., 2019), several suggestions are offered.

Although it is an option in many CE doctoral programs, some CEDS may graduate without any significant FiT experiences (Barrio Minton & Price, 2015; Hunt & Weber Gilmore, 2011; Suddeath et al., 2020). Although not all CEDS want to go into the professoriate, for those interested in working in academia, it is our hope that programs will provide students with multiple—and preferably at least five—developmentally structured supervised teaching opportunities. Whether these are formal curricular FiT experiences such as teaching practicums and internships or informal co-curricular co-teaching or IOR experiences (and likely a combination of the two), CE literature suggests that these experiences should include frequent and ongoing supervision (Baltrinic & Suddeath, 2020a) and progress from lesser to greater responsibility and autonomy within the teaching role (Baltrinic et al., 2016; Hall & Hulse, 2010; Orr et al., 2008). These recommendations for the structuring of FiT are important given the incredible variation in this aspect of training (e.g., Orr et al., 2008; Suddeath et al., 2020) and the consistency in the observed pattern of self-efficacy toward teaching and the number of FiT experiences (Olguin, 2004; Tollerud, 1990).

To help buffer against the initial drop in self-efficacy toward teaching scores from zero to one to two teaching experiences in this study and previous research (Olguin, 2004; Tollerud, 1990), research emphasizes the importance of increased oversight and support of CEDS before and during their first teaching experiences (Baltrinic & Suddeath, 2020a; Elliot et al., 2019; Stone, 1994). CE faculty members who teach coursework in college teaching, are instructors for teaching internships, and/or are providing supervision of teaching for FiT experiences should normalize initial anxiety and self-doubt (Baltrinic & Suddeath, 2020a; Elliot et al., 2019) and encourage realistic expectations for students’ first teaching experiences (Stone, 1994). Stone (1994) suggested that fostering realistic expectations in those engaging in a new task may actually “increase effort, attention to strategy, and performance by increasing the perceived challenge of tasks” (p. 459). This was evident in Elliot et al.’s (2019) study in which CEDS reframed the initial struggles with teaching experiences as opportunities for growth and development. On the other hand, individuals who overestimate or strongly underestimate self-efficacy may not put in the time or effort needed to succeed at a given task. For example, those who overestimate their capabilities may not increase their effort, as they already believe they are going to perform well (Stone, 1994). Similarly, those who underestimate their ability may not increase effort or give sufficient attention to strategy, as they perceive that doing so would not improve their performance anyway. These findings support the need for CE programs to provide oversight and support and engender realistic expectations before or during students’ first FiT experiences.

Limitations and Future Research
     Limitations existed related to the sample and survey. Representativeness of the sample, and thus generalizability of findings, is limited by the voluntary nature of the study (i.e., self-selection), cross-sectional design (i.e., tracking efficacy beliefs over time), and solicitation of participants via CESNET-L (i.e., potential for CEDS to miss the invitation to participate) and doctoral program liaisons (i.e., unclear how many forwarded the invitation). Another limitation relates to the variability in participants’ FiT experiences, such as the assigned role and responsibility within FiT, frequency and quality of supervision, and whether and how experiences were developmentally structured. Additionally, self-report measures were used, which are prone to issues of self-knowledge (e.g., over- or underestimation of capability with self-efficacy, accurate recall of FiT experiences) and social desirability.

Future research could utilize qualitative methods to investigate what components of FiT experiences (e.g., quality, type of responsibility) prove most helpful in strengthening CEDS’ self-efficacy and how it changes with increased experience. Given the limitations of self-efficacy, researchers could also investigate other outcomes (e.g., test scores, student evaluations) instead of or alongside self-efficacy. Although this study identified the importance of acquiring at least five FiT experiences for strengthening SETI scores, little is known about how to developmentally structure FiT experiences so as to best strengthen self-efficacy toward teaching. Researchers could use quantitative approaches to investigate the relationship between various aspects of CEDS’ FiT experiences (e.g., level of responsibility and role, frequency and quality of supervision) and SETI scores. Researchers could also develop a comprehensive model for providing FiT that includes recommendations as supported by CE research (e.g., Baltrinic et al., 2016; Baltrinic & Suddeath, 2020a, 2020b; Elliot et al., 2019; Orr et al., 2008; Suddeath et al., 2020; Swank & Houseknecht, 2019). Finally, instead of investigating FiT experiences of CEDS and their impact on teaching self-efficacy, future research could investigate first-year counselor educators to determine if and how their experience differs.

Conclusion

Investigating teaching preparation practices within CE doctoral programs is essential for understanding and improving training for future counselor educators. Although research already supports the inclusion of multiple supervised teaching experiences within CE doctoral programs (Suddeath et al., 2020), the results of this study provide greater clarity to the differential impact of FiT experiences on CEDS’ teaching self-efficacy. Given the consistently observed pattern of teaching self-efficacy and FiT experiences from this and other studies over the last 30 years, doctoral training programs should thoughtfully consider how to support students through their first FiT experiences, and ideally, offer students multiple opportunities to teach.

 

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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Eric G. Suddeath, PhD, LPC-S (MS), is an associate professor at Denver Seminary. Eric R. Baltrinic, PhD, LPCC-S (OH), is an assistant professor at the University of Alabama. Heather J. Fye, PhD, NCC, LPC (OH), is an assistant professor at the University of Alabama. Ksenia Zhbanova, EdD, is an assistant professor at Mississippi State University-Meridian. Suzanne M. Dugger, EdD, NCC, ACS, LPC (MI), SC (MI, FL), is a professor and department chair at Florida Gulf Coast University. Sumedha Therthani, PhD, NCC, is an assistant professor at Mississippi State University. Correspondence may be addressed to Eric G. Suddeath, 6399 South Santa Fe Drive, Littleton, CO 80120, ericsuddeath@gmail.com.

Career Counseling in Middle Schools: A Study of School Counselor Self-Efficacy

Carrie Sanders, Laura E. Welfare, Steve Culver

Students in K–12 schools benefit from career counseling as a means to improve their readiness for academic and career success. This quantitative study explored the career counseling self-efficacy of 143 practicing middle school counselors using the Career Counseling Self-Efficacy Scale-Modified and a subscale of the School Counselor Self-Efficacy Scale. Although school counselors were confident overall, evidence of specific areas of concern and limited time for career counseling was found. Results related to the importance of prior teaching experience in relation to career counseling self-efficacy also were highlighted. Implications for school counselors and policymakers include examining the amount of time school counselors spend on providing career counseling in comparison to time spent on non-counseling–related duties.

Keywords: career counseling, middle schools, school counselors, self-efficacy, time

All students in K–12 do not have the same exposure to career opportunities. Providing avenues for students to learn about and identify ways to access a variety of careers is the responsibility of counselors in the school setting. School counselors contribute to students’ development in the domains of academic, career, and social and emotional development through comprehensive school counseling programs (American School Counselor Association [ASCA], 2014). ASCA published ASCA Mindsets and Behaviors for Student Success: K–12 College and Career Readiness Standards for Every Student (2014), which offers a framework of desired mindsets and behaviors for college and career readiness. This resource and others highlight the importance of a school counselor’s work in the career domain. However, school counselors’ knowledge and self-efficacy in the career counseling field may impact their ability to be effective in this aspect of their work (O’Brien, Heppner, Flores, & Bikos, 1997; Perrone, Perrone, Chan, & Thomas, 2000). This quantitative study explored the career counseling self-efficacy of practicing middle school counselors. As students move through elementary and secondary school, they continuously learn valuable knowledge and skills to explore postsecondary options and prepare to enter into the world of work. Middle school is an important time in this continuum for students as they consider their future academic and career plans and identify pathways to achieve their goals. The results of this study, as well as results related to the amount of time middle school counselors spend providing career counseling, yielded valuable implications for school counselors, K–12 stakeholders, and counselor educators.

The Importance of Career Counseling

Students begin to develop career awareness in elementary school, explore careers during middle school, and move into career preparation and planning in high school. Career counseling connects the experiences students have in school to their future, which enhances academic motivation and provides meaning to and purpose for the work they are doing in school (Curry, Belser, & Binns, 2013; Scheel & Gonzalez, 2007). As children and adolescents learn about themselves and the world of work, they are more likely to make informed career decisions, value school, succeed academically, and engage in school offerings (Kenny, Blustein, Haase, Jackson, & Perry, 2006; Orthner, Jones-Sanpei, Akos, & Rose, 2013; Perry, Liu, & Pabian, 2010).

Career counseling is needed in middle school in order to inspire young adolescents to make preliminary career decisions, to prepare them to take desired high school classes, and to equip them for future career pathways (Akos, 2004; Osborn & Reardon, 2006). Curriculum that integrates postsecondary college and career options in middle school has the potential to provide support and motivation for students (Curry et al., 2013). This type of curriculum connects directly to the comprehensive school counseling program. In schools with fully implemented comprehensive counseling programs that include career counseling, students self-reported higher grades, perceived they are better prepared for the future, recognized the relevance of school, and experienced a sense of belonging and safety, more so than in schools with less comprehensive school counseling programs (Lapan, Gysbers, & Petroski, 2001; Lapan, Gysbers, & Sun, 1997). In summary, establishing connections between a student’s academic preparation and possible career options benefits students in various ways, and school counselors are essential guides in the career exploration process.

Career Counseling in Schools

Despite this empirical evidence of its importance (Anctil, Smith, Schenck, & Dahir, 2012; Barker & Satcher, 2000; Osborn & Baggerly, 2004), school counselors can face barriers to implementing career counseling, including limited time because of competing demands, negative perceptions about career counseling, and low school counselor self-efficacy. For example, school counselors are often called upon to perform non-counseling tasks that take time away from providing a comprehensive school counseling program. School counselors desire to be engaged in promoting positive student outcomes and would prefer to spend less time on non-counseling–related activities (Orthner et al., 2013; Scarborough & Culbreth, 2008). There is some evidence that the desire to spend more time on counseling applies directly to career counseling, as found in a study of school counselors at all levels (Osborn & Baggerly, 2004). But, other studies have found that some school counselors are uncertain about the importance of career counseling (Perrone et al., 2000). These findings may indicate that although there is a desire to spend more time providing career counseling, there is uncertainty about its value.

Another potential barrier that is a focus of this study is individual school counselor self-efficacy. Self-efficacy, a core construct in this study, centers on the belief one has in his or her ability to perform a task (Bandura, 1986, 1997; Eccles & Wigfield, 2002). Self-efficacy of school counselors would be defined as beliefs about their abilities to provide effective counseling services (Larson & Daniels, 1998). High self-efficacy among school counselors would promote adaptive delivery of school counseling services to meet the needs of diverse student populations (Bodenhorn & Skaggs, 2005; Larson & Daniels, 1998). Social cognitive career theory (Lent & Brown, 2006; Lent, Brown, & Hackett, 2000) offers a framework for understanding self-efficacy in action—that is, how it impacts the interactions between individuals, their behaviors, and their environments. O’Brien and Heppner (1996) explored social cognitive career theory as it applies to interest, engagement, and performance of career counseling.

The interaction between people, their behavior, and their environment provides a highly dynamic relationship. Performance in educational activities is the result of ability, self-efficacy beliefs, outcome expectations, and established goals. School counselors have varied training experiences and personal self-efficacy beliefs that impact the delivery of a career counseling program. A school counselor’s self-efficacy in career counseling can increase through four primary sources: personal performance, vicarious learning, social persuasion, and physiological and affective states (Bandura, 1997). School counselor self-efficacy may be influenced by many things such as graduate training, service learning, internships, professional development, and years of experience (Barbee, Scherer, & Combs, 2003; Lent, Hill, & Hoffman, 2003; O’Brien et al., 1997). Teaching is a related experience that may impact career counseling self-efficacy. Some authors have highlighted prior teaching experience as helpful in the preparation of school counselors; others have not found such evidence (Baker, 1994; Peterson & Deuschle, 2006; Smith, Crutchfield, & Culbreth, 2001). Skills school counselors use to provide classroom guidance, which is one delivery method for career counseling services, are similar skills to those used by effective teachers (Akos, Cockman, & Strickland, 2007; Bringman & Lee, 2008; Peterson & Deuschle, 2006), so it is reasonable to expect that school counselors without teaching experience may be less comfortable managing a classroom of students than those with teaching experience (Geltner & Clark, 2005; Peterson & Deuschle, 2006).

There are two studies that have explored self-efficacy of school counselors with and without prior teaching experience. Scoles (2011) compared self-efficacy of 129 school counselors serving across all grade levels and did not find a statistically significant difference between those with and without teaching experience. In contrast, Bodenhorn and Skaggs (2005) found that respondents with teaching experience (n = 183) reported significantly stronger self-efficacy than those without teaching experience (n = 42). These conflicting findings about the importance of prior teaching experience suggest that further study is warranted.

Purpose for the Study

Given the importance of beginning career exploration early and the essential role school counselors play in that process, this study focused on career counseling in the middle school setting. Understanding practicing school counselors’ self-efficacy and their time spent providing career counseling will help administrators and policymakers better understand ways to increase career counseling in middle schools. As such, the following research questions were posed: (1) What are middle school counselors’ levels of self-efficacy in career counseling? (2) How does middle school counselor self-efficacy in career counseling vary with previous K–12 teaching experience? and (3) What is the relationship between middle school counselor self-efficacy in career counseling and the amount of time spent providing career counseling?

Method

A quantitative research design was used for this study. The researcher examined school counselor self-efficacy in the career counseling domain. A school counselor was invited to participate if he or she was a current middle school (sixth, seventh, or eighth grade) counselor in Virginia at the time of the study and his or her email information was provided on a district or school website. The electronic survey included three instruments: an information questionnaire that was used to collect data about personal experiences and training, the Career Counseling Self-Efficacy Scale-Modified (CCSES-Modified; O’Brien et al., 1997), and a subscale of the School Counselor Self-Efficacy Scale (SCSE-Subscale; Bodenhorn & Skaggs, 2005).

Descriptive statistics were compiled by computing means, standard deviations, and minimum and maximum scores for total career counseling self-efficacy, as identified by both the CCSES-Modified and the SCSE-Subscale independently. Means and standard deviations of the 25 items of the CCSES-Modified and the seven items of the SCSE-Subscale also were calculated.

Two analyses of variance (ANOVA) and a t-test were used to determine if there were statistically significant differences among means. Participants were given the opportunity to report their years of counseling experience both full- and part-time, and the researcher combined these to get a total number. This number was obtained by taking the total reported number of years as a full-time school counselor and adding that to .5 multiplied by the reported number of years as a part-time school counselor. Then, the researcher created discrete levels to represent groups of experience once the data had been collected in order to conduct the analysis. Identifying the range of experience of the sample and using a scale appropriate for the sample determined the discrete levels. These three levels represented those who had the least experience, those in the middle, and those with the most experience as a school counselor. The researcher conducted an ANOVA with these groups and the SCSE-Subscale mean and a separate ANOVA with the identified groups and the CCSES-Modified mean.

The researcher obtained an answer of “yes” or “no” to indicate previous teaching experience. A separate value was given to answers of “yes” and “no” and the values were used to run a t-test with the mean for the SCSE-Subscale and the CCSES-Modified mean.

Participants indicated the total number of hours of conference presentations, workshops, or trainings that focused primarily on career counseling within the last 3 years. First, the researcher identified the range of the number of hours of training participants reported receiving in career counseling within the last 3 years. Then, the researcher created discrete levels to represent groups of recent training once the data was collected in order to conduct the analysis.

The third research question required a correlation to analyze the relationship between school counselor self-efficacy in career counseling and the amount of time (measured in percent) spent providing career counseling.

Participants

The participants for this study were practicing middle school counselors, defined as counselors working in a school housing students in grades 6 through 8 at the time the survey was completed. The data cleaning procedures described below resulted in 143 participants out of 567 invitations, which is a 25% response rate. Of the 143 participants, 23 (16.1%) were male and 117 (81.8%) were female (three participants omitted this item). Regarding race, 110 participants (76.9%) identified as White/Caucasian, 20 (14.0%) as African American, four (2.8%) as Hispanic/Latino, and one (0.7%) as Multiracial, while five (3.5%) preferred not to answer and three participants omitted this item. Participants’ ages ranged from 25 to over 65 years with an average age of 45 years (SD = 11; respondents who reported being 65 and over were coded as 65).

Regarding training, the participants reported their highest level of education: 125 participants (87.4%) reported having a master’s degree as their highest level of education, 11 (7.7%) had an education specialist degree, six (4.2%) reported having a doctoral degree, and one participant omitted this item. Participants reported a mean of 13.3 years (SD = 7.4) of experience providing school counseling. Regarding full-time teaching experience in a K–12 school, 47 (32.9%) participants had experience, while 94 (65.7%) did not have this experience, and two people omitted this item.

Instruments

The 49-item online survey included 17 items to gather demographic and professional information, the 25-item CCSES-Modified (O’Brien et al., 1997), and seven items from the Career and Academic Development subscale of the SCSE (Bodenhorn & Skaggs, 2005).

Career Counseling Self-Efficacy Scale-Modified. The CCSES-Modified (O’Brien et al., 1997) was used to assess overall career counseling self-efficacy. Participants were asked to indicate their level of confidence in their ability to provide career counseling. For this study, the terms “client” and “career client” were replaced with the term “student” to be more congruent with school counselor terminology. Permission was granted from the first author of the scale to the researcher to make these changes (K. O’Brien, personal communication, January 7, 2013). The CCSES-Modified contains 25 items that are rated on a 5-point Likert-type scale (0 = Not Confident, 4 = Highly Confident). Within the CCSES-Modified, there are four subscales: Therapeutic Process and Alliance Skills, Vocational Assessment and Interpretation Skills, Multicultural Competency Skills, and Current Trends in the

World of Work, Ethics, and Career Research. The full scale has a reported internal consistency reliability coefficient of .96 (O’Brien et al., 1997).

 School Counselor Self-Efficacy Scale-Subscale. One subscale from the SCSE (Bodenhorn & Skaggs, 2005) was included in this study. The SCSE Career and Academic Development subscale was designed for school counselors to examine self-efficacy in the career domain. Using a 5-point Likert-type scale (1 = Not Confident, 5 = Highly Confident), participants indicated their level of confidence on each of the seven items. Bodenhorn and Skaggs (2005) reported a subscale internal consistency reliability coefficient of .85.

Indices of Reliability in the Present Study

The internal consistency reliability in this sample for the CCSES-Modified was α = 0.941 and the SCSE-Subscale was α = 0.871. The CCSES-Modified had four subscales: Therapeutic Process and Alliance Skills (10 items, α = 0.820), Vocational Assessment and Interpretation skills (6 items, α = 0.855), Multicultural Competency Skills (6 items, α = 0.913), and Current Trends in the World of Work, Ethics, and Career Research (3 items, α = 0.747). All of these exceed the common threshold for reliability for similar measures. The CCSES-Modified total score and the SCSE-Subscale score had a strong positive 2-tailed Pearson correlation (0.792), which was statistically significant at the 0.01 level. This strong positive relationship suggests these two measures captured related information from the participants.

Procedure

The original sampling frame consisted of 576 middle school counselors with publicly available email addresses, which were collected from public school websites in all counties in Virginia. After Institutional Review Board approval was secured, participants were sent an email invitation with the informed consent and link to the web survey. One week later, participants were sent a reminder email. Upon completion of the survey, participants were given the opportunity to vote for one of five organizations to receive a $100 donation as a token of appreciation for their time completing the survey. After the recruitment email was sent, there were nine people who indicated they were not eligible to participate. These included three individuals who sent a return email indicating that they were out of the office during the survey administration, three who were not currently middle school counselors, two who reported needing school division approval, and one person who had difficulty accessing the survey. This reduced the actual sampling frame to 567.

Data Cleaning

One hundred and sixty-one respondents answered the survey items. There were 18 respondents who omitted 15% or more of the items from the CCSES-Modified or the SCSE-Subscale and were therefore removed from the study. This changed the total number of remaining respondents to 143. Of the 143 remaining, there were eight respondents who each omitted one item that was used to measure career counseling self-efficacy on the CCSES-Modified or the SCSE-Subscale. Each omitted item was replaced with the individual’s scale mean (e.g., mean imputation; Montiel-Overall, 2006), and those respondents were included in the analyses. When the omitted item was part of an analysis for Research Question 2 or 3, the respondent was removed from the affected analysis. Omissions on the demographic questionnaire are noted above in the description of the participants.

Results

RQ1: What are school counselors’ levels of self-efficacy in career counseling?

Overall, middle school counselors who participated in this study were moderately confident, confident, or highly confident in their ability to provide career counseling services. According to the CCSES-Modified, counselors felt least confident in the subscales of Multicultural Competency Skills and Current Trends in the World of Work, Ethics, and Career Research, while they reported the most confidence in their Therapeutic Process and Alliance Skills. Specific areas of school counselor self-efficacy deficits were related to special issues present for lesbian, gay, and bisexual students in the workplace and in career decision-making, as well as special issues related to gender and ethnicity in the workplace and in career decision-making. Table 1 provides descriptive statistics and reliability for each subscale and the total scale.

Table 1 Career Counseling Self-Efficacy Scale-Modified Subscale Scores (N = 143)
 Subscales

Min

Max

M

SD

α

Item M

Item SD

Therapeutic Process andAlliance Skills(10 items)

21

40

35.24

4.05

0.82

3.52

0.40

Vocational Assessment andInterpretation Skills(6 items)

5

24

18.08

4.21

0.86

3.01

0.70

Multicultural Competency Skills(6 items)

0

24

16.52

4.79

0.91

2.75

0.80

Current Trends in the World of Work,Ethics, and Career Research(3 items)

3

12

8.09

2.44

0.75

2.69

0.81

Total ScaleTotal Instrument Score (25 items)

32

99

77.94

13.60

0.94

3.12

0.54

Note. 1 = Not Confident and 4 = Highly Confident.

The means and standard deviations for the SCSE-Subscale are listed in Table 2. On average, participants were confident or highly confident in their abilities to attend to student career and academic development.

Table 2
School Counselor Self-Efficacy Scale-Subscale Individual Item Responses  (N = 143)

% Response

1

   2

 3

  4

  5

M

SD

1. Implement a program which enables all students to make
informed career decisions.

       1

3

20

34

43

4.16

.89

2. Deliver age-appropriate programs through which students
acquire the skills needed to investigate the world of work.

2

18

34

46

4.24

.81

3. Foster understanding of the relationship between learning
and work.

0

9

40

51

4.42

.65

4. Teach students to apply problem-solving skills toward
their academic, personal, and career success.

1

8

36

55

4.45

.69

5. Teach students how to apply time and task management
skills.

2

6

35

57

4.46

.71

6. Offer appropriate explanations to students, parents, and
teachers of how learning styles affect school performance.

2

15

39

44

4.24

.79

7. Use technology designed to support student successes and
progress through the educational system.

6

22

44

29

3.96

.86

Total Subscale Score

29.93

4.08

Note. 1 = Not Confident, 3 = Moderately Confident, 5 = Highly Confident.

RQ2: How does school counselor self-efficacy in career counseling vary with previous K–12 teaching experience?

Two t-tests were conducted to identify if there was a difference between career counseling self-efficacy among participants with and without previous experience as a teacher. Separate means and standard deviations were calculated for the two groups—those who had teaching experience (n = 47) scored higher on the CCSES-Modified (M = 82.2, SD = 9.7) and the SCSE-Subscale (M = 30.9, SD = 3.4) than those without teaching experience (n = 94), CCSES-Modified (M = 75.8, SD = 14.7) and SCSE-Subscale (M = 29.4, SD = 4.3).

Independent t-tests were performed to determine if the differences between the groups were statistically significant. For the CCSES-Modified, the assumption of homogeneous variances was not satisfied (Levene’s test, F = 7.13, p < .05); therefore, the more conservative t-test was used to assess for a statistically significant difference (t = -3.06, p = .003). The mean score for the teaching experience group (M = 82.2, SD = 9.7) was statistically higher than the mean score for those without teaching experience (M = 75.8, SD = 14.7). For the SCSE-Subscale, the assumption of homogeneous variances was satisfied (Levene’s test, F = 3.71, p = .055, d = .51). The mean score of the group with teaching experience (M = 30.9, SD = 3.4, d = .39) was statistically different from the mean score of the group without teaching experience (M = 29.4, SD = 4.3), t = -2.03, p = .045. Cohen’s d is a valuable index of effect size for statistically significant mean differences (Cohen, 1988). The Cohen’s d of .51 for the CCSES-Modified and .39 for SCSE-Subscale both represent medium effect sizes.

RQ3: What is the relationship between middle school counselor self-efficacy in career counseling and the amount of time spent providing career counseling?

The third research question required a correlation to analyze the relationship between school counselor self-efficacy in career counseling and the percent of work time spent providing career counseling. Participants reported the percentage of time they spend providing responsive services to students in the three school counseling domains, as well as testing coordination and other non-counseling–related activities, which is represented in Table 3. The averages and standard deviations of the percentage of time spent in each subscale were: personal/social counseling (M = 36.25, SD = 15.39), academic counseling (M = 23.32, SD = 10.47), career counseling (M = 12.15, SD = 6.98), Virginia State Standards of Learning (SOL) testing coordination (M = 11.83, SD = 12.88), and other non-counseling–related activities (M = 16.44, SD = 12.55). One participant omitted this item; therefore, N = 142 in Table 3. There was no statistically significant relationship between the CCSES-Modified and time providing career counseling (r = .160, p = .057) and a statistically significant weak positive relationship (r = .286, p = .001) between the SCSE-Subscale and time providing career counseling.

Table 3 Self-Efficacy and Time Providing Career Counseling

  % Career Counseling

Career Counseling Self-Efficacy Scale-Modified Pearson Correlation

.160

Sig. (2-tailed)

.057

N

142

School Counselor Self-Efficacy Scale-Subscale Pearson Correlation

 .286*

Sig. (2-tailed)

.001

N

142

Note. *Correlation is significant at the 0.01 level (2-tailed)

Discussion

There were several key findings from this study of middle school counselors’ self-efficacy with career counseling. First, it is important to note that there was a wide range in the total self-efficacy scores for middle school counselors. As a group, these counselors were the most confident in their Therapeutic Process and Alliance Skills, and least confident in Multicultural Competency Skills and Current Trends in the World of Work, Ethics, and Career Research. Specifically, special issues related to gender, ethnicity, and sexual orientation in career decision-making and in the workplace were areas of concern. School counselors who had previous K–12 teaching experience were significantly more confident providing career counseling than those without, as assessed by both measures. Finally, a Pearson correlation indicated there was a weak positive correlation between the SCSE-Subscale and the percentage of time school counselors indicated they spend providing career counseling. There was not a statistically significant relationship between the CCSES-Modified and time spent providing career counseling.

In this study, results indicate that middle school counselors spend more time doing non-counseling–related activities than providing career counseling, which is alarming. Career development is one of the three primary domains of a comprehensive school counseling program, and it is important for school counselors to create career development opportunities for students. The majority of school counselors report the importance of career counseling; however, middle school counselors acknowledge they spend less time on career counseling than they prefer (Osborn & Baggerly, 2004). There is a need to reprioritize career counseling, which includes recognizing and acknowledging how career counseling intersects with academic and personal and social counseling in K–12 schools (Anctil et al., 2012).

Career counseling is valuable and evidence needs to be provided to indicate how non-counseling–related tasks take time away from school counselors’ ability to offer adequate career counseling for students. Test coordination is time-consuming and an example of a non-counseling duty that some school counselors perform. Considering the amount of time this role requires, school counselors would find more time to provide career counseling services for students without this obligation. School counselors should gather evidence and provide accountability reports about how career counseling efforts contribute to student engagement and success.

Implications for School Counselors, K–12 Stakeholders, and Counselor Educators

In general, the practicing school counselors in this study had ample self-efficacy with regard to providing career counseling. However, there were certain items on the CCSES-Modified and the SCSE-Subscale that reveal discrepancies in middle school counselors’ levels of confidence. Counselors felt least confident in the subscales of Multicultural Competency Skills and Current Trends in the World of Work, Ethics, and Career Research. Specifically, they reported lower self-efficacy addressing special issues related to gender, ethnicity, and sexual orientation in relation to the world of work. In light of these findings, counselor preparation programs need to further investigate what is being taught in career counseling courses, how the content is being delivered, possible gaps in curriculum, and opportunities for outreach to current school counselors through continuing education. Given the powerful movement for advocacy related to these important social issues, it is in some ways confirming that the practicing counselors in this study felt less confident in these areas. Perhaps the national attention on issues of privilege and oppression related to gender, ethnicity, and sexual orientation has shed light on individual or systemic challenges these school counselors face as they try to serve diverse young adolescents in a dynamic phase of their development.

There are opportunities to increase career counseling self-efficacy related to gender, ethnicity, and sexual orientation in relation to the world of work. Bandura (1997) highlighted personal performance, vicarious learning, and social persuasion as particularly effective strategies for increasing self-efficacy. Continuing education, supervision, and professional organization engagement may be the best opportunities for continued development in these areas (Tang et al., 2004). In-service training and continuing education could be offered to provide school counselors relevant information to support their professional development and promote an increase in career counseling self-efficacy. Gaining up-to-date knowledge about the experiences of students with varied gender identities, ethnicities, and sexual orientations will best prepare school counselors to serve the entire student body. Observing advocacy approaches modeled by other leaders may inspire school counselors to use their voices in their own systems. Relatedly, this finding makes it apparent that K–12 school systems need clear and powerful policies and leadership around gender-, ethnicity-, and sexual orientation-related issues. School counselors are well positioned to partner with principals and superintendents in this important change process.

The second research question provided additional information about a somewhat contentious issue in previous research. School counselors who had teaching experience had higher career counseling self-efficacy than those who did not have teaching experience. This finding contradicts the findings of a study conducted with school counselors in Ohio (Scoles, 2011) and supports the findings of the national study conducted by Bodenhorn and Skaggs (2005), as described above. Contradictory findings like these beg for more research. Perhaps the higher self-efficacy of those with previous teaching experience is related to the preparation in specific academic disciplines that teachers receive. It could be that because these school counselors were previously trained in a specific academic area, they are more confident in talking with students about careers in that particular career cluster (e.g., science teachers who become school counselors may be more prepared to discuss careers in science, technology, engineering, and mathematics with students). Conversely, this potentially narrow view of career opportunities may limit the career exploration of students if school counselors do not include a wide array of career options. An excellent area for further research would be to identify how previous teaching experience may specifically impact school counselor self-efficacy.

School counselors without teaching experience, although lower in self-efficacy than those school counselors with teaching experience, still had high career counseling self-efficacy. This suggests that school counselors without teaching experience have confidence in their ability to provide career counseling. If, as Peterson and Deuschle (2006) suspected, the advantage of those with prior teaching experience is because of the increased training and practice in classroom management and lesson preparation, one would expect that effect to diminish as years of school counseling experience are accumulated. A larger sample than the one in this study would be necessary to test that empirically. If, however, the impetus for the significant impact of teaching experience is more general, those newer school counselors without teaching experience may be adjusting to the setting and to new ways of managing their time, balancing multiple roles and responsibilities, incorporating community involvement, working with parents, fostering collaborative relationships, and becoming familiar with local resources. All of these tasks take time and effort and could impact a school counselor’s self-efficacy to provide adequate services to students. It may be helpful for school counselors without teaching experience to ask for support and suggestions from seasoned school counselors in the district to learn from their experiences. In addition, professional development programming could be established for school counselors to become more familiar with the specific roles and responsibilities related to the career information, education, and counseling needs within a particular community.

Finally, the third focus of the study was on how school counselors use their time and if self-efficacy is related to that allocation. Most alarming about these findings was that school counselors are spending less time providing career counseling than they are doing non-counseling–related duties. A large percentage of middle school counselors’ time was reported to be spent coordinating testing or doing other non-counseling–related tasks, which is not the most efficient use of school counselors’ strengths. School counselors are uniquely trained to provide supplemental support for students in the academic, personal and social, and career domains in order to promote student success; therefore, it would be advantageous if they were able to utilize their time in a way that is consistent with the needs of students. One option to address the time constraint, particularly in this day of tighter budgets, is to utilize someone with an administrative background for the non-counseling duties in order for the school counselor to have time to incorporate adequate career counseling into their school counseling program. This is particularly important for middle school counselors providing career counseling because middle school students are preparing academic and career plans that will serve as a guide through high school and postsecondary educational endeavors (Trusty, Niles, & Carney, 2005; Wimberly & Noeth, 2005).

The world of work is continually changing, which makes it important to be aware of the current trends in this area. As these changes happen, marginalized populations face unique issues in the area of career exploration and planning. Counselors need to be trained adequately to provide career counseling to clients. In addition to providing relevant information, promoting thoughtful reflection, and facilitating discussions for counselors-in-training, counselor educators could provide outreach and continuing education opportunities focused on career counseling.

Just as career counseling may be infused with academic and personal and social counseling for school counselors, counselor educators may consider infusing career counseling concepts throughout other courses and experiences during a training program. Counselor educators could model this authentic type of integration. Counselor educators could talk more about various career clusters and the value of career counseling throughout a training program rather than just in one specific course. Counselor educators may also facilitate discussions with counselors-in-training about their own career counseling experiences, allowing trainees time to reflect on their experience. In addition, trainees could talk about how they have worked with people in roles other than a counselor through the career exploration and planning process.

Counselors need to consider ways to utilize and increase the support of administration and teachers to identify what needs to change in order for them to reallocate their time so they are able to provide more career counseling. Providing evidence of the positive impact of their work may be an effective strategy. There are many approaches to this, such as utilizing current research studies to communicate support for the value of career counseling efforts. In addition, school counselors can gather data from current students, parents, and alumni regarding their perception of and desire for career counseling services through surveys or focus groups. Once specific programs are implemented, school counselors can evaluate the outcomes of the career counseling efforts through both formal and informal assessment procedures with students, teachers, and parents. Administrators should continue to express support for the career counseling efforts of school counselors and show support by advocating for more personnel in order for students to receive adequate career counseling and to meet the demand of the non-counseling tasks that counselors are assigned.

Limitations

The findings should be considered in light of the limitations of the study. Because of the nature of instruments that involve self-report, the results are based on the current perception of the participants and not objective assessments of the effectiveness of their work. Also, it may be more socially and professionally desirable to have confidence in personal abilities and, therefore, some participants may have answered the way they thought they should. This study was limited to those middle school counselors who had publically available e-mail addresses and were working in Virginia. Non-respondents and middle school counselors outside of Virginia are not represented in these findings; therefore, generalizing the findings should be considered with caution. Furthermore, the 406 non-respondents and the 18 respondents who did not complete the entire survey may be systematically different from the 143 respondents who were included.

Conclusion

This study has provided important new information about the self-efficacy of school counselors in the middle school setting as related to career counseling. Career counseling self-efficacy was high overall, with specific areas of deficit related to gender, ethnicity, and sexual orientation. Those school counselors who had previous teaching experience had even higher career counseling self-efficacy than those who did not. High self-efficacy in school counselors had little or no impact on the time spent providing career counseling services. Tailoring continuing education opportunities in career counseling and providing clear administrative leadership would further strengthen practicing school counselor self-efficacy. Utilizing support personnel for non-counseling–related duties may allow school counselors to use their career counseling skills and training to help middle school students explore and connect with careers, thereby improving academic and life outcomes.

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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Carrie Sanders is a visiting assistant professor at Virginia Tech. Laura E. Welfare, NCC, is an associate professor at Virginia Tech. Steve Culver is Director of Assessment and Analytics at North Carolina A&T State University. Correspondence may be addressed to Carrie Sanders, 1750 Kraft Drive, Suite 2005, Blacksburg, VA 24061, cbrill@vt.edu.

Self-Efficacy, Attachment Style and Service Delivery of Elementary School Counseling

Kimberly Ernst, Gerta Bardhoshi, Richard P. Lanthier

This study explored the relationships between demographic variables, self-efficacy and attachment style with a range of performed and preferred school counseling activities in a national sample of elementary school counselors (N = 515). Demographic variables, such as school counselor experience and American School Counselor Association (ASCA) National Model training and use, were positively related to performing intervention activities that align with the ASCA National Model. Results of hierarchical regression analyses supported that self-efficacy beliefs also predicted levels of both actual and preferred service delivery of intervention activities. Interestingly, self-efficacy beliefs also predicted higher levels of performing “other” non-counseling activities that are considered to be outside of the school counselor role. An insecure attachment style characterized by high anxiety predicted a lower preference for intervention activities and also predicted the discrepancy between actual and preferred “other” non-counseling activities, revealing a higher preference for performing them.

Keywords: school counselor, ASCA National Model, self-efficacy, attachment style, service delivery

Professional school counselors are important contributors to education and serve an essential role in the academic, personal, social and career development of all students (American School Counselor Association [ASCA], 2012). Over the past decade, school counselors have been increasingly called upon to embrace data-driven, evidence-based standards of practice (ASCA, 2012; Erford, 2016) that bolster the achievement of all students (Shillingford & Lambie, 2010). Comprehensive developmental school counseling programs that are consistent with the ASCA National Model are currently considered best practice (ASCA, 2012) and identified as an effective means of delivering services to all students (Burnham & Jackson, 2000; Carey & Dimmitt, 2012; Gysbers & Henderson, 2012).

Data from school counseling research indicate that comprehensive developmental school counseling programs make a positive difference in student outcomes (Carey & Dimmitt, 2012; Scarborough & Luke, 2008). These programs are shown to impact overall student development positively, including academic, career and emotional development, as well as academic achievement (Fitch & Marshall, 2004; Lapan, Gysbers, & Petroski, 2001; Sink & Stroh, 2003). Furthermore, a range of individual school counselor activities and interventions is associated with positive changes in a number of important student outcomes, including academic performance, school attendance, classroom behavior and self-esteem (Whiston, Tai, Rahardja, & Eder, 2011).

However, studies examining actual school counselor practice indicate that school counselors spend a significant amount of time on activities that are not reflective of ASCA best practices, including clerical, administrative and fair share duties that take them away from performing essential school counseling activities (Bardhoshi, Schweinle, & Duncan, 2014; Burnham & Jackson, 2000; Foster, Young, & Hermann, 2005; Scarborough & Luke, 2008). A factor impeding school counselors’ ability to perform activities that align with best practices includes being burdened with time-consuming tasks that are outside their scope of practice (Bardhoshi et al., 2014). This may stem from either the historically ambiguous school counselor role (Gysbers & Henderson, 2012) or from competing demands from numerous stakeholders who may not fully understand the components of an effective school counseling program (Bemak & Chung, 2008). Indeed, school counselors report not spending adequate time engaged in the professional activities that they prefer (Scarborough, 2005; Scarborough & Luke, 2008), even though these preferences are consistent with best practice recommendations (Scarborough & Culbreth, 2008). Therefore, for many school counselors, performing within their professional role and sticking to best practice recommendations regarding their service delivery can be challenging and stressful (McCarthy, Kerne, Calfa, Lambert, & Guzmán, 2010).

Given that school counseling program implementation and interventions that align with ASCA are associated with positive outcomes for students in a variety of domains, and that tension exists between the actual and preferred practice of school counselors, the question now becomes: What factors contribute to effective school counseling service delivery? Studies indicate a positive relationship between years of experience and school counselor practice (Scarborough & Culbreth, 2008; Sink & Yillik-Downer, 2001), as it may take several years of experience to implement the breadth and complexity of interventions in a programmatic manner. Research outside the field of school counseling also has expanded beyond demographic variables to indicate that a number of individual characteristics, such as attachment style (Dozier, Lomax Tyrrell, & Lee, 2001; Hazan & Shaver, 1987), emotional stability, locus of control, self-esteem (Judge & Bono, 2001) and self-efficacy (Judge & Bono, 2001; Larson & Daniels, 1998), are related to an individual’s work performance.

To understand the underlying mechanisms that affect school counselor work performance, studies have explored potential organizational (e.g., school climate, perceived administration support), structural (e.g., training, supervision), and personal variables (e.g., experience, self-efficacy) related to counselor practice (Scarborough & Luke, 2008). Two school counselor interpersonal variables are of special focus in this study: self-efficacy and attachment. Individuals with higher levels of self-efficacy set higher goals for themselves and show higher levels of commitment, motivation, resilience and perseverance in achieving set goals (Bodenhorn & Skaggs, 2005), making the examination of school counselor self-efficacy important in investigating effective service delivery. On the other hand, attachment theory highlights the process by which early childhood development influences an individual’s capacity to relate to others and regulate emotion. Many lines of theoretical and empirical research in education and psychology have examined how attachment characteristics influence adult functioning, supporting the introduction of school counselor attachment style as a factor relating to work performance (Desivilya, Sabag, & Ashton, 2006; Hazan & Shaver, 1987; Kennedy & Kennedy, 2004; Marotta, 2002). School counselor self-efficacy and attachment characteristics are personal attributes conceptualized to contribute to the ability of school counselors to perform intervention activities that align with ASCA recommendations and positively impact student development and achievement.

 

Self-Efficacy

Self-efficacy involves beliefs about one’s own capability to successfully perform given tasks to accomplish specific goals (Lent & Hackett, 1987). As individuals confront important problems and tasks, they choose actions based on their beliefs of personal efficacy (Bandura, 1996). Self-efficacy may be a critical factor in school counselor work performance. Two meta-analytic studies of empirical research examining self-efficacy have shown that for a variety of occupations, there is a positive relationship between self-efficacy and work performance (Larson & Daniels, 1998; Stajkovic & Luthans, 1998). Studies examining school counselor self-efficacy have been a more recent addition to the literature, with reported results indicating that self-efficacy is related to school counselor gender, teaching experience (Bodenhorn & Skaggs, 2005), and supportive staff and administrators (Sutton & Fall, 1995).

In a study that extended the findings of previous self-efficacy research (Sutton & Fall, 1995), Scarborough and Culbreth (2008) examined factors that predicted discrepancies between actual and preferred practice in school counselors. Both self-efficacy beliefs and the amount of perceived administrative support predicted the difference between school counselors’ actual and preferred practice, with higher levels of support and outcome expectancy predicting higher levels of preferred intervention activities performance. In the current study, we plan to extend Scarborough and Culbreth’s work by examining the links between comprehensive elementary school counselor practice and overall school counselor self-efficacy while introducing attachment characteristics as a possible variable related to school counselor performance.

 

Attachment

Attachment theory describes how early experiences with attachment figures (e.g., mother) create inner representations referred to as internal working models. Those internal working models then shape patterns of behavior in response to significant others and to stressful situations (Mikulincer, Shaver, & Pereg, 2003). Adult attachment categories reflect those created in infancy and childhood and include secure, preoccupied (or anxious), dismissing (or avoidant), and fearful (both anxious and avoidant) styles (Bartholomew & Horowitz, 1991). In adults, attachment style encompasses affective responses in a variety of relationships, including co-workers, and can be activated by a number of stressful situations, including a stressful work environment (Mikulincer & Shaver, 2003, 2007).

Working effectively in a job or career contributes in meaningful ways to life satisfaction, self-esteem and social status, whereas not working effectively (and experiencing overload or burnout) can be extremely stressful and can cause serious emotional and physical difficulties (Mikulincer & Shaver, 2007). Specifically for school counselors, Wilkerson and Bellini (2006) reported that emotion-focused coping is a significant predictor of burnout, lending support to the examination of interpersonal factors in school counselor practice. To work effectively and not succumb to burnout, school counselors may have to activate self-regulatory skills associated with attachment, such as exploring alternatives, refining skills, adjusting to variation in tasks and role demands, and exercising self-control (Mikulincer & Shaver, 2007). In the field of school counseling, challenges include facing multiple demands and conflicting responsibilities (Cinotti, 2014); therefore, interpersonal communication, negotiation and adaptation become essential. Although attachment theory has received very little attention in school counseling literature (Pfaller & Kiselica, 1996), existing research suggests that various aspects of work are likely to be affected by individual differences in attachment style (Mikulincer & Shaver, 2007).

The purpose of this study was to explore demographic and interpersonal factors related to elementary school counseling practice. This research employed an associational survey research design to examine the relationships between school counselor overall self-efficacy, attachment style, and a range of performed and preferred activities in a sample of ASCA members who are elementary school counselors. Building on previous studies, we controlled for the anticipated variance in school counselor activities that might be contributed by previously identified demographic variables, including years of experience, ASCA National Model training and ASCA National Model use (Scarborough & Culbreth, 2008).

The first research question inquired about the relationship between self-efficacy beliefs and school counselor performed and preferred intervention activities that align with ASCA, controlling for the potential effect of the identified demographic variables. We hypothesized that self-efficacy beliefs would predict both school counselor preference and actual performance of these core activities, after controlling for the potential effect of relevant demographic variables. The second research question inquired about the relationship between attachment style and both counseling and non-counseling activities, controlling for the effect of the identified demographic variables. We hypothesized that school counselors who endorse higher levels of anxiety may prefer to engage in fewer intervention activities and more non-counseling activities. This could be in an effort to please others and conform to the administrative, fair share and clerical demands of the job. No hypothesis was forwarded on attachment avoidance and discrepancies between actual and preferred activities, as related research has not examined a possible relationship.

 

Method

 

Participants

The sample for this study consisted of elementary-level school counselors whose e-mail addresses were listed on the ASCA national database. We made the decision to select only elementary school counselors because of the unique emphasis on student personal and social development at this level (Dahir, 2004), as well as the distinct developmental needs of the student population that could potentially tap into school counselor attachment (Scarborough, 2005). Recruitment e-mails were sent to 3,798 ASCA member elementary school counselors through SurveyMonkey, employing a 3-wave multiple contact procedure. The original sample was adjusted to 3,550 because of undeliverable e-mail addresses. In total, 663 individuals responded to the survey, yielding a return rate of 19%. A priori power analysis using G*Power software determined that a minimum sample of 107 participants likely was necessary when conducting a multiple regression analysis with three independent variables. This G*Power calculation was based on an alpha level of .05, minimum power established at .80 and a moderate treatment effect size, and was conducted in the planning stages to inform needed sample size and minimize the probability of Type II error (Faul, Erdfelder, Buchner, & Lang, 2009). Therefore, surveys with incomplete data were completely removed from the analysis, resulting in a final sample size of 515 and a usable response rate of 14.5%.

The sample consisted of 89.6% females and 9.8% males (3 participants did not indicate gender). In terms of race and ethnicity, 86.6% were Caucasian, 6% African American, 2.9% Hispanic, 1.6% Multiracial, 1.4 % Asian/Pacific Islander, and 0.4% Native American (1.2% did not indicate race or ethnicity). The predominately female and Caucasian sample is consistent with school counseling research and reflective of the population (Bodenhorn & Skaggs, 2005).

Years of experience ranged from < 1 to 38, with a mean of 10.24 years. School enrollment ranged from 70 to 3,400 students, with a mean of 583.49 students. The large maximum enrollment number was caused by the inclusion of elementary-level counselors who were employed in K–12 schools. Counselor caseload ranged from 6 to 1,500, with the mean being 454.68 students. The mean age of respondents was 44 years, with a standard deviation of 11.02 years, and an age range spanning from 25 to 68 years. Regarding ASCA National Model (2012) training, only 8.5% reported not having received any training, with the overwhelming majority of the participants having received training from professional development opportunities sought on their own (67.6%), as part of master’s-level coursework (53.2%), or through their school district (31.5%). Only 5.2% of respondents reported no use of the ASCA National Model, with 14% reporting limited use, 33.8% some use, 31.5% a lot of use, and 15% extensive use.

 

Instruments

Instrumentation consisted of four measures, including a demographic questionnaire, the School Counselor Activity Rating Scale (SCARS; Scarborough, 2005), the School Counselor Self-Efficacy Scale (SCSE; Bodenhorn & Skaggs, 2005) and the Experiences in Close Relationships Scale-Short Form (ECR-Short Form; Wei, Russell, Mallinckrodt, & Vogel, 2007).

Demographic questionnaire. A demographic questionnaire consisting of 14 questions collected relevant information regarding participant age, gender, ethnicity, region, school setting (i.e., private, public) and level (e.g., elementary, middle), student enrollment, counselor caseload characteristics, degree earned, licensure and certification, years of experience and training in and use of the ASCA National Model. Demographic data were selected for inclusion based on a literature review indicating important relationships between these variables and school counseling outcomes (Scarborough & Culbreth, 2008; Sink & Yillik-Downer, 2001).

     School Counselor Activity Rating Scale (SCARS). The SCARS is a 48-item scale reflecting best practice recommendations for school counselors based on the ASCA National Standards (Campbell & Dahir, 1997) and the ASCA National Model (ASCA, 2003). It was designed to measure the frequency with which school counselors perform specific work activities, and the preferred frequency of performing those activities (Scarborough, 2005; Scarborough & Culbreth, 2008). The instrument contains five sections—counseling, consultation, curriculum, coordination and “other” activities. Participants indicate their actual and preferred performance of common school counseling activities on a frequency scale (1 = rarely do this activity to 5 = routinely do this activity), including “other” non-counseling activities that fall outside the school counselor role (e.g., coordinate the standardized testing program). A SCARS total score is calculated by adding the totals from each subscale or calculating mean scores, with higher scores indicating higher levels of engagement.

The SCARS validation study supported a four-factor solution representing the counseling, coordination, consultation and curriculum categories. Analysis on the “other” school counseling activities subscale, consisting of 10 items reflecting non-counseling activities, resulted in three factors: clerical, fair share and administrative. Convergent and discriminant construct validity also were reported (Scarborough, 2005). Cronbach’s alpha reliability coefficients, as reported by Scarborough on the eight subscales of actual and preferred dimensions, were .93 and .90 for curriculum; .84 and .85 for coordination; .85 and .83 for counseling; .75 and .77 for consultation; .84 and .80 for clerical; .53 and .58 for fair share; and .43 and .52 for administrative. In the current study, the Cronbach’s alpha coefficients for actual and preferred practice were .90 and .83 for curriculum; .84 and .86 for coordination; .80 and .81 for counseling; and .76 and .73 for consultation.

The intervention total subscale in our study consisted of the composite of the counseling, consultation, curriculum and coordination subscales, with Cronbach’s alpha reliability coefficients of .91 on both the actual and the preferred use dimensions. Similar to Scarborough (2005), the “other” duties subscale, consisting of clerical, fair share and administrative duties, had moderate reliability, with Cronbach’s alpha of .63 on the actual, and .68 on the preferred. The activities total subscale consisted of a combination of all SCARS subscales, with Cronbach’s alpha being .89 on the actual and .90 on the preferred. Various studies have been conducted since the initial validation of the SCARS and support its use as a tool yielding valid and reliable school counselor process scores (Scarborough & Culbreth, 2008; Shillingford & Lambie, 2010).

School Counselor Self-Efficacy Scale (SCSE). The SCSE (Bodenhorn & Skaggs, 2005) is a 43-item

self-report instrument designed to measure school counselor self-efficacy. The SCSE uses a 5-point Likert-type scale to measure responses (ranging from 1 = not confident to 5 = highly confident) and consists of five subscales: personal and social development; leadership and assessment; career and academic development; collaboration; and cultural acceptance. A composite mean is calculated to demonstrate overall self-efficacy. SCSE responses were evaluated for reliability, omission, discrimination and group differences (Bodenhorn & Skaggs, 2005), with results supporting high reliability for the composite scale (α = .95). Analyses also indicated group differences demonstrating score validity for the scale—participants who had teaching experience, had been practicing for three or more years, and were trained in and used the ASCA National Standards reported higher levels of self-efficacy. The total scale SCSE alpha in the current study was .96.

     Experiences in Close Relationships Scale (ECR)-Short Form. The ECR-Short Form (Wei et al., 2007) is a 12-item self-report measure designed to assess a general pattern of adult attachment. The ECR-Short Form is based on the longer Experiences in Close Relationship Scale (Brennan, Clark, & Shaver, 1998). Factor analysis revealed two dimensions of adult attachment, anxiety and avoidance, which have received professional consensus (Bartholomew & Horowitz, 1991; Mikulincer & Shaver, 2003). High scores on either or both of these dimensions are indicative of an insecure adult attachment orientation. Low levels of attachment anxiety and avoidance indicate a secure orientation (Bartholomew & Horowitz, 1991; Brennan et al., 1998; Lopez & Brennan, 2000; Mallinckrodt, 2000).

Internal consistency was adequate with coefficient alphas from .77 to .86 for the anxiety subscale and from .78 to .88 for the avoidance subscale, and confirmatory factor analyses provided evidence of construct validity with a two-factor model (i.e., anxiety and avoidance), indicating a good fit for the data. Reported test-retest reliabilities averaged .83. For the current study, ECR-S alphas were .75 for the anxiety subscale and .81 for the avoidance subscale.

Data Analysis
Data were analyzed using the Statistical Package for Social Sciences (SPSS Version 18), with multiple hierarchical regressions used to answer both research questions. Hierarchical regression was selected to determine the relative importance of the predictor variables, over and above that which can be accounted for by other previously identified predictors regarding school counselor service delivery (i.e., years of experience, ASCA National Model training and ASCA National Model use). Predictor variables included self-efficacy beliefs (SCSE total score), attachment anxiety (ECR-Short Form Anxiety subscale) and attachment avoidance (ECR-Short Form Avoidance subscale). Outcome variables included actual (SCARS total Actual scale) and preferred (SCARS total Preferred scale) intervention activities, “other” non-counseling activities (SCARS Other Activities scale) and the discrepancy between actual and preferred intervention and “other” activities.

Prior to analysis of the research questions, correlations were conducted among the predictor and outcome variables. Identified predictors (i.e., years of experience, ASCA National Model training and ASCA National Model use) were also correlated with the SCARS criterion variables. For the hierarchical regression, identified predictors were entered first as a block, followed by the new predictors included in this study (Field, 2009). This predetermined order of entry is congruent with Cohen and Cohen’s (1993) recommendations for using hierarchical regression and entering the demographic variables in the initial step. Additionally, the order of entry reflected the principle of presumed causal priority (Cohen & Cohen, 1993; Petrocelli, 2003). For the second step, we decided to enter attachment anxiety prior to avoidance, as we anticipated it would be more important in predicting the outcome variables (Field, 2009). Reported effect size estimates reflect the following guidelines: r of .1 (small), .3 (medium) and .5 (large); and R2 of .01 (small), .09 (medium) and .25 (large; Cohen, 1988).

 

Results

We first examined the correlation among the identified school counselor demographic variables (control variables) and the actual and preferred SCARS variables. Years of experience showed a small but significant positive correlation with actual intervention activities (r = .20, p < .05). ASCA National Model use showed a moderate positive correlation with actual intervention activities (r = .44, p < .05), but smaller relationships with preferred intervention activities (r = .15, p < .05). Additional correlation analysis revealed relationships among school counseling experience and the main predictor variables that were of interest in this study. For example, years of experience showed a significant, although small, negative correlation to attachment anxiety (r = -.14, p < .05). Both attachment anxiety and avoid-
ance showed negative correlations to self-efficacy (r = -.20 and -.15, p < .05, respectively). Lastly, self-
efficacy showed a small positive correlation with years of experience (r = .25, p < .05) and ASCA National Model use (r =.27, p < .05).

Self-Efficacy Predicting Actual and Preferred Intervention and Other Activities
     Multiple hierarchical regression analyses were conducted to determine if self-efficacy was positively associated with actual and preferred intervention activities, after controlling for demographic variables (see Table 1). Self-efficacy was the predictor variable and actual and preferred intervention activities were the criterion variables in separate analyses. Because years of experience, ASCA National Model training and ASCA National Model use were correlated with the SCARS criterion variables, these control variables were entered as a block prior to entering self-efficacy beliefs. The model for actual activities was significant: F(1, 506) = 112.37, p < .05, supporting the hypothesis. The standardized beta between self-efficacy and actual intervention activities was .40 and the effect size based on the adjusted R2 statistic indicated that 37% of the variance in actual activities was accounted for by self-efficacy, after blocking for the control variables, a large effect size. Results for preferred school counselor activities showed a similar result, as the model for preferred activities also was significant: F(1, 506) = 78.59, p < .05. The standardized beta between self-efficacy and preferred intervention activities was .39, and the adjusted R2 indicated 15% of the variance in preferred activities was accounted for by self-efficacy, after blocking for the control variables, a medium effect size.


Table 1.

Results from hierarchical multiple regression using self-efficacy to predict SCARS actual and preferred intervention activities

Block 1

Block 2

Predictor Variable

B

SE B

β

B

SE B

β

Actual
Experience (years)

0.01

0.00

 0.20*

0.01

0.01

0.10*

A.N.M. Training

-0.02

0.03

-0.60

-0.02

0.03

-0.03

A.N.M. Use

0.22

0.02

0.44*

0.17

0.02

0.34*

Self-Efficacy

0.45

0.04

0.40*

R2

0.23

0.37

F for change in R2

50.46*

112.37**

Preferred
Experience (Years)

0.00

0.00

 0.04

-0.00

0.00

-0.05

A.N.M. Training

-0.00

0.03

-0.01

-0.01

0.03

-0.01

A.N.M. Use

0.06

0.02

0.15*

0.02

0.02

0.05

Self-Efficacy

0.37

0.04

0.39**

R2

0.02

0.15

F for change in R2

3.92*

78.59*


Note: Analysis N = 511 (actual & preferred); * p < .05. A.N.M. denotes ASCA National Model.

 

Similar hierarchical multiple regression analyses were conducted using school counselor self-efficacy as the predictor variable and “other” school counseling activities as the criterion variable, after controlling for demographic variables (see Table 2). The models for preferred and actual “other” activities were both significant; F(1, 506) = 20.89, p < .05; and F(1, 506) = 13.60, p < .05, respectively. The standardized beta for actual “other” activities was .21 and for preferred “other” activities was .17. Self-efficacy accounted for (R2 =) 43% of the variance in actual “other” activities performed and (R2 =) 33% of preferred “other” activities, indicating large effect sizes.
Table 2.

Results from hierarchical multiple regression using self-efficacy to predict SCARS actual and preferred “other” non-counseling activities

Block 1

Block 2

Predictor Variable

B

SE B

β

B

SE B

β

Actual
Experience (Years)

0.00

0.00

0.02

-0.00

0.00

-0.03

A.N.M. Training

0.04

0.04

0.05

0.04

0.04

-0.05

A.N.M. Use

-0.04

0.03

-0.06

-0.07

0.03

-0.11

Self-Efficacy

0.29

0.06

0.21*

R2

0.00

0.43

F for change in R2

0.63

20.89*

Preferred
Experience (Years)

0.01

0.00

 0.07

0.00

0.00

0.03

A.N.M. Training

-0.02

0.04

-0.03

-0.02

0.04

-0.03

A.N.M. Use

-0.00

0.03

-0.0

-0.00

0.03

-0.00

Self-Efficacy

0.22

0.06

0.17*

R2

0.02

0.33

F for change in R2

1.13

13.60**


Note: Analysis N = 511 (actual & preferred); * p < .05. A.N.M. denotes ASCA National Model.
Attachment Predicting Actual and Preferred Intervention and “Other” Activities
     Hierarchical multiple regressions were used to assess the ability of attachment style to predict school counselor interventions and “other” non-counseling activities, after controlling for demographic variables. In our study, attachment style was measured by the ECR-Short Form (Wei et al., 2007) on two dimensions—attachment anxiety and avoidance. As in the regression analyses for counselor self-efficacy, years of experience, ASCA National Model training and ASCA National Model use were entered as a block prior to entering attachment anxiety and avoidance. Attachment anxiety, but not attachment avoidance, revealed predictive utility for the SCARS preferred intervention subscale scores, showing a negative relationship: F(1, 505) = 2.60, p < .05. The standardized beta for preferred intervention activities was -.11 and attachment anxiety accounted for only 2% of the variance for preferred intervention activities, a small effect size.

To test whether attachment anxiety was associated with discrepancies between a range of actual and preferred school counseling activities, separate regression analyses were performed. We used attachment anxiety and attachment avoidance as the predictor variables and the discrepancy score variables that were created by subtracting the actual from the preferred scores for the actual and preferred intervention activities and “other” activities subscales. As before, years of experience, ASCA National Model training and ASCA National Model use were correlated with the SCARS criterion variables and were entered as a block prior to entering the attachment variables. For intervention activities, a relationship was not supported for either attachment anxiety or attachment avoidance. However for the “other” non-counseling activities, a relationship between attachment anxiety and the actual/preferred discrepancy revealed a statistically significant result over and above that accounted for by demographic variables: F(1, 505) = 3.16, p < .05 with a standardized beta of .12. Therefore, attachment anxiety predicted a discrepancy that revealed a higher preference for performing “other” non-counseling activities. However, the effect size showed that anxiety accounted for only 1% of the variance in the “other” activities discrepancy score (see Table 3).


Table 3

Results from hierarchical multiple regression using attachment to predict SCARS intervention scores and the actual/prefer discrepancy scores for intervention and “other” activities

Block 1

Block 2

Block 1

Block 2

Predictor Variable

B

SE B

β

B

SE B

β

B

SE B

β

B

SE B

β

Intervention Actual

Intervention Discrepancy

Experience (years)

0.01

0.00

 0.20*

0.02

0.00

 0.19*

-0.01

0.00

-0.18*

-0.01

 0.00

 -0.18*

A.N.M. Training

-0.02

0.03

 -0.03

-0.02

0.02

 -0.02

0.01

0.03

  0.02

0.02

0.03

 0.02

A.N.M. Use

0.22

0.02

 0.44*

0.22

0.02

 0.44*

-0.16

0.02

-0.34*

0.16

0.02

 0.34*

Anxiety

-0.03

0.02

 -0.06

-0.01

0.02

 -0.03

Avoidance

0.01

0.02

 0.02

0.00

0.02

 -0.01

R2

0.23

0.00

0.15

         0.00

F for change in R2

       50.46*

0.34

        29.69*

0.33

Intervention Preferred

“Other” Discrepancy

Experience (years)

0.00

0.00

 0.04

0.00

0.03

0.02

0.04

0.03

 0.06

0.03

0.03

 0.04

A.N.M. Training

0.00

0.03

 -0.01

0.00

0.03

0.00

-0.61

0.31

 -0.10*

-0.57

0.31

-0.09

A.N.M. Use

0.06

0.02

0.15*

0.06

0.02

 0.14*

0.57

0.24

 0.12*

0.57

0.23

 0.12*

Anxiety

-0.05

0.02

-0.11*

-0.58

0.23

 0.12*

Avoidance

0.01

0.02

0.02

0.29

0.25

 0.06

R2

0.02

 0.01

0.02

0.01

F for change in R2

         3.92*

         2.6

         3.21*

         3.16*


Note:
Analysis N = 511 (actual & preferred); * p < .05. A.N.M. denotes ASCA National Model.

 

Discussion

To date, few studies have examined how school counselor personal characteristics are linked to successful programs (Scarborough & Luke, 2008). Using a nationwide sample, we examined how self-efficacy is related to a range of school counselor activities in elementary schools and introduced attachment style as a potential variable related to school counselor practice. Years of experience working as a school counselor as well as the training in and use of the ASCA National Model in program implementation were identified from the literature as variables of importance and were included in our analyses.

As anticipated the number of years of experience was related to actual performance of intervention activities by school counselors. Also, school counselors in this sample who had received more training in the ASCA National Model were more likely to perform the intervention activities of counseling, consultation, curriculum and coordination. These activities are considered core activities for effective program implementation. Furthermore, counselors who endorsed more fully implementing the ASCA National Model within their program were significantly more likely to perform these core intervention activities and also indicated a preference for spending their time in these activities. This result is in line with previous findings supporting that counselors who incorporated the National Standards for School Counseling Programs (Campbell & Dahir, 1997) into their programs were more likely to have preferences that aligned with professional standards and actually practiced as they preferred (Scarborough & Culbreth, 2008). It is promising that over 75% of school counselors in the current study reported some use to extensive use of the ASCA National Model. The large number of counselors who reported ASCA National Model use could be indicative of a recent focus to define standards of practice and increase positive student outcomes through systematic and programmatic delivery. With regard to non-counseling activities, results did not support a relationship with ASCA National Model training and use.

     Looking beyond the demographic variables, the findings of the current study support previous research that found important links between school counselor self-efficacy beliefs and program implementation (Bodenhorn, Wolfe,  & Airen, 2010). In the current study, overall school counselor self-efficacy beliefs predicted the delivery of activities aligned with the ASCA National Model above and beyond the demographic variables analyzed. School counselors who believed they were capable of performing in accordance with activities aligned with the ASCA National Standards were more likely to actually perform and want to perform school counseling intervention activities consistent with the ASCA National Model.

It is interesting to note that school counselors with higher self-efficacy beliefs were more likely to perform non-counseling activities when compared to counselors with lower self-efficacy. These results suggest that counselors with higher levels of self-efficacy beliefs may not discriminate between intervention and “other” non-counseling activities, by performing both more frequently. Highly efficacious school counselors may simply do more, whether or not the activity aligns with ASCA recommendations. As demands for school counselors increase and current expectations for school counselors do not perfectly align with professional best practices (Cinotti, 2014), highly efficacious school counselors may tackle all duties earnestly in order to address their responsibilities.

In the current study, attachment anxiety negatively predicted school counselor preferred engagement in intervention activities (i.e., counseling, consultation, curriculum, coordination), indicating that anxiously attached school counselors actually preferred to perform fewer intervention activities. Additionally, school counselor attachment anxiety predicted a discrepancy between actual and preferred activities that are considered outside the scope of school counseling practice, including clerical, administrative and fair share responsibilities. When considering the relationship between attachment anxiety and this discrepancy, which revealed a higher preference for performing these “other” activities, there are a few possible explanations. Perhaps anxiously attached counselors reporting a greater discrepancy on the “other” subscale find it more difficult to align their identity with the counseling professional identity model promoted by ASCA. Although these non-counseling activities do not align with ASCA recommendations, they are nevertheless expected and valued by supervisors. Research has suggested that anxiously attached individuals may tend to take on additional work obligations as a way to please others and tend to be motivated by approval of colleagues and supervisors (Hazan & Shaver, 1987). Additionally, anxiously attached workers seek close relationships with their colleagues and supervisors and have more difficulty resisting unreasonable demands in the workplace (Leiter, Day, & Price, 2015). Given that school administrators directly influence the assignment of inappropriate duties performed by school counselors, and that strong advocacy and leaderships skills are essential to negotiate an identity and role that is more aligned with ASCA recommendations (Cinotti, 2014), anxiously attached school counselors may find it more difficult to test those relationships and may instead endorse the identity expected by their supervisors. Indeed, the literature points out that school administrators perceive school counselors as operating mainly from an educator—versus a counselor—professional identity (Cinotti, 2014).

There was a low variability in attachment scores of this particular sample (i.e., school counselors endorsed relatively high levels of self-efficacy and low levels of attachment insecurity), which could have contributed to the results of this research. Within the clinical training component of their education, school counselors are taught the importance of ongoing self-exploration and to develop awareness of their responses within the context of clinical practice. It is possible that education and training in the importance of self-awareness could interrupt effects on school counselor practice that are related to higher levels of attachment anxiety.

Counselors in this sample consistently indicated that they preferred to spend more time in intervention activities that are in keeping with best practices and are related to positive outcomes for students and preferred to spend less time in non-counseling related activities. When compared to other research using the SCARS, they also reported engaging in fewer non-counseling activities. As performing non-counseling activities is associated with burnout in school counselors (Bardhoshi et al., 2014), this is a positive finding that might be reflective of the current direction of the profession.

 

Study Limitations

The potential for self-selection and social desirability bias was a limitation of this study. Only elementary school counselors who were ASCA members were invited to participate. It is possible that those members who did volunteer to participate may differ in a variety of ways from those individuals who did not respond. Given the $115 membership fee to join the association, it is possible that counselors from wealthier school districts, with higher salaries or access to a counseling budget assisting with the membership fee, are more heavily represented. School counselors who chose to become members of ASCA may vary distinctly in work-related performance, self-efficacy beliefs and attachment style than those counselors who chose not to become members of the association. ASCA members likely have more professional development opportunities and more exposure to information regarding best practices, which could impact both their self-efficacy beliefs and practice.

Despite our use of multiple contact procedures to obtain an acceptable response rate, a limitation worth noting is the lower response rate. Lower response rates are often noted for online surveys (Dillman, Smyth, & Christian, 2014), including in the field of counseling (Granello & Wheaton, 2004). Although we received over 200 undeliverable e-mails, which reduced the original sample size, there is no way to accurately estimate how many individuals actually received the survey in their inbox (Granello & Wheaton, 2004). It is indeed possible that spam-filtering software resulted in many invitations not reaching their intended recipients. Therefore, our reported response rate represents a conservative estimate (Vespia, Fitzpatrick, Fouad, Kantamneni, & Chen, 2010). In addition, it was assumed that the attrition of 100 participants was likely the result of the time required to complete the survey. Our analysis supported that there were no statistically significant differences between the two groups (i.e., completers and non-completers) on demographic variables and that our final sample size was adequate for the selected statistical tests. However, readers should use caution when generalizing the results of this study to all elementary school counselors. A final consideration is that causal relationships cannot be derived from the results of this study, as the research design was relational in nature.

 

Implications for School Counseling Practice
     Previous studies have indicated that higher levels of school counselor self-efficacy are positively associated with higher levels of comprehensive program implementation (Bodenhorn et al., 2010). For many, the route to increased self-efficacy is through personal and vicarious accomplishments (Bodenhorn et al., 2010; Scarborough & Culbreth, 2008; Sutton & Fall, 1995). Therefore, opportunities to learn and practice the skill set specific to school counseling must be promoted in the education and training of students.

School counselor educators have a crucial role in ensuring that future school counselors have a strong foundation with which to begin their careers. Counselor education programs have often not provided adequate preparation for school counselors because there has been incongruence between their training and their actual roles in schools (McMahon, Mason, & Paisley, 2009). A novice school counselor who has had education and training that is consistent with his or her actual work role will have greater chances of acquiring increased self-efficacy from the start. In a cascade, self-efficacy will likely promote stronger program implementation and, in turn, positive student outcomes.

More specifically, requiring trainees to provide a range of services will support the transition from training to work. Trainees need opportunities to provide specific interventions (e.g., counseling individuals and groups, teaching classroom lessons) while also evaluating the impact of these interventions, teaching them how to use data in their programs and potentially boosting self-efficacy beliefs (Akos & Scarborough, 2004). Trainees should also be given opportunities to engage in coordination activities to gain experience in the organizational aspects of a comprehensive developmental school counseling program. Finally, counselor educators who supervise internship courses must maintain strong communication with site supervisors to ensure continuity and appropriate trainee experiences.

Although effect sizes related to attachment characteristics in this study were small, they imply that attachment theory could be a useful adjunct to understanding school counselor practice. Using attachment concepts as a guide for supervision or structured professional development opportunities could assist school counselors’ ongoing efforts to understand their own behavior and motivations in the work setting. Graduate coursework specific to attachment constructs has the potential to be a useful component of school counselor education, especially because the cultivation of healthy interpersonal relationships has a tremendous potential to facilitate positive change in schools.

 

Recommendations for Future Counseling Research
The moderately strong association in this study between school counselor self-efficacy and activities recommended by the ASCA National Model indicates that understanding the factors affecting school counselor self-efficacy warrants further attention. Research outside the field of school counseling has identified a positive relationship between attachment security and higher levels of competence and self-efficacy beliefs (Mikulincer & Shaver, 2007). Given that self-efficacy was significantly negatively correlated to both attachment anxiety and avoidance in this study, additional studies examining these relationships may clarify possible connections between school counselor self-efficacy beliefs and attachment characteristics. We did not examine whether SCSE subscales were differentially related to school counselor activities. Doing so could identify professional areas about which counselors feel most efficacious and those that need bolstering. Explaining the reasons some school counselors perform more successfully is an enduring goal of counseling research (Sutton & Fall, 1995).

Our results did indicate significant relationships between attachment anxiety and school counselor practice. Specifically, attachment anxiety predicted a lower preference for intervention activities, as well as a discrepancy between actual and preferred “other” non-counseling activities that revealed a higher preference for performing them. Although small, these results could lead to further understanding of the factors related to differences in school counselor practice. As this study has taken a broad view of how school counselor practice could be affected by attachment dimensions, qualitative studies examining the unique experiences of anxiously attached counselors in their work environment have the potential to reveal important perspectives. Identifying how attachment style may contribute to the endorsement and performance of specific intervention activities could lead to a greater understanding of school counseling practice.

 

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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Kimberly Ernst is a counselor in independent practice in Washington, DC. Gerta Bardhoshi, NCC, is an Assistant Professor at the University of Iowa. Richard P. Lanthier is an Associate Professor at George Washington University. Data for this article originated from the first author’s doctoral dissertation. Correspondence can be addressed to Gerta Bardhoshi, College of Education, N352 Lindquist Center, Iowa City, IA 52242-1529, gerta-bardhoshi@uiowa.edu.