Organizational Variables Contributing to School Counselor Burnout: An Opportunity for Leadership, Advocacy, Collaboration, and Systemic Change

Leigh Falls Holman, Judith Nelson, Richard Watts

 

 

This study utilizes a correlation matrix to examine relationships between variables identified in literature (role ambiguity, role conflict, assignment of non-counseling duties, coworker and supervisor support, and level of control over time and task) as measured by the Demand Control Support Questionnaire (DCSQ), and elements of school counselor burnout (SCBO) as measured by the Counselor Burnout Inventory (CBI) subscales (Exhaustion, Incompetence, Negative Work Environment, Devaluing Clients, and Deterioration in Personal Life). Findings indicate experiencing high external demands, such as assignment of non-counseling duties; experiencing the school as a negative place to work; and experiencing low levels of support from colleagues and supervisors result in high levels of exhaustion and contribute to burnout. These variables need further exploration using a hierarchical multiple regression to analyze the amount of variance they contribute to SCBO. The article includes a discussion of ethical concerns, future research, and practice implications for school counselor educators, supervisors, educational administrators, and school counselors.

 

Keywords: school counselor burnout, non-counseling duties, role conflict, organizational variables, leadership

 

 

School counselors are a valuable resource in supporting a school’s mission to help children and adolescents develop into healthy, well-functioning, contributing members of society. However, when school counselors experience high levels of chronic job stress and burnout, those experiences may result in negative effects on the students and schools they serve (Falls & Nichter, 2007; Holman & Grubbs, 2018). Therefore, identifying those variables most likely to contribute to school counselor burnout (SCBO) is crucial for counselor educators’ and supervisors’ development of prevention, monitoring, and early intervention protocols. With this end in mind, this study is the next in a series of research projects we are pursuing to systematically evaluate variables potentially related to SCBO in order to develop a model of SCBO in the future.

 

Background of School Counselor Burnout

Research suggests demographic variables potentially contribute to the development of SCBO, including high caseloads (Bardhoshi, Schweinle, & Duncan, 2014; Falls & Nichter, 2007; Gunduz, 2012), location of the school (Butler & Constantine, 2005), grade level served (DeMato & Curcio, 2004; Rayle, 2006), and gender and ethnicity of the counselor (Butler & Constantine, 2005; Falls & Nichter, 2007). However, our recent study utilizing a series of factorial ANOVAs systematically analyzed levels of job stress and burnout in relationship to these variables. The findings indicated, contrary to suggestions in the literature, that none of these variables is significantly related with both job stress and burnout (Holman, Watts, Robles-Pina, & Grubbs, 2018). These findings led us to seek additional potential SCBO contributing variables for exploration. Below we discuss additional variables we identified and how we operationalized them for the current study.

External Demands

There are several features of external demands highlighted by the literature, which we describe below. Ultimately, we included role ambiguity, assignment of non-counseling duties, and role conflict in the current study.

 

     Role ambiguity. The literature indicates that role ambiguity may contribute to SCBO (Culbreth, Scarborough, Banks-Johnson, & Solomon, 2005; Falls & Nichter, 2007; Holman & Grubbs, 2018). School counselors frequently experience situations where various stakeholders, including administrators, teachers, parents, and students, have conflicting ideas about the school counseling role. Differences in understanding the appropriate role of the school counselor is defined as role ambiguity.

 

In addition to these stakeholders, school counselors have their own understanding of their roles. School counselors’ conceptualization of their roles is based on their graduate school training (Culbreth et al., 2005; Gibson, Dollarhide, & Moss, 2010; Goodman-Scott, 2015; Watkinson, Goodman-Scott, Martin, & Biles, 2017). However, role ambiguity among school counselors might result from lack of clarity from graduate school programs about the unique manifestation of counseling in a school environment, particularly if school counseling classes are add-on classes to clinical mental health coursework (Falls & Nichter, 2007). Additionally, educational administrators often have little if any instruction in their graduate programs regarding how to best utilize a school counselor in helping reach the school’s overall mission (Amatea & Clark, 2005; Dodson, 2009; Lieberman, 2004; Shoffner & Williamson, 2000). As such, this could be an area of professional advocacy school counselors need to pursue in order to reduce role ambiguity.

 

Further, the duties assigned by administrators due to role ambiguity are often inconsistent with the American School Counselor Association’s National Model (ASCA; 2012). ASCA’s model indicates school counselors should design and deliver comprehensive school counseling programs that promote student achievement. According to ASCA (2012), “school counseling programs are comprehensive in scope, preventative in design and developmental in nature” (p. 1). Appropriate duties include individual student academic program planning; interpreting testing; responsive counseling services related to school participation and achievement; collaboration with teachers, administrators, and parents; identifying and developing programming for student and school needs; advocating for students; and analyzing disaggregated data (ASCA, 2012).

 

     Assignment of non-counseling duties. The assignment of non-counseling duties, those inconsistent with ASCA’s National Model (ASCA, 2012), is a significant subset of external demands that negatively impact school counselors (Falls & Nichter, 2007; Holman, Grubbs, Robles-Pina, Nelson, & Watts, 2019). In fact, several studies have indicated that the assignment of inappropriate non-counseling duties (e.g., master scheduling, substitute teaching, conducting state mandated testing, lunch duty, clerical duties) is a potential variable contributing to SCBO (Baggerly & Osborn, 2006; Bardhoshi et al., 2014; DeMato & Curcio, 2004; Falls & Nichter, 2007; Holman & Grubbs, 2018; Moyer, 2011).

 

However, one concern with these studies is the use of the School Counselor Activity Rating Scale’s Other Counseling Duties subscale (SCARS; Scarborough, 2005) to operationalize the assignment of non-counseling duties. The SCARS Other Counseling Duties subscale asks counselors to rate how often they participate on committees within the school; coordinate standardized testing programs; organize outreach to low income families; respond to health issues (e.g., check for lice, eye screening, 504 coordination); perform hall, bus, and cafeteria duty; schedule students for class; maintain educational records; handle discipline; and substitute teach.

According to the developer of the instrument, despite the overall strength of the other SCARS subscales, this subscale demonstrates low reliability (Scarborough 2005). It also does not measure the complex and varied external demands that school counselors experience from multiple stakeholders (Adelman & Taylor, 2002; Baker & Gerler, 2004; Culbreth et al., 2005; Falls & Nichter, 2007; Herlihy, Gray, & McCollum, 2002; Holman & Grubbs, 2018; House & Hayes, 2002). Therefore, in order to measure this construct for the current study, we sought to find another instrument that might measure these non-counseling duties commonly assigned to school counselors. After we discuss the other variables identified as potentially contributing to SCBO, we will discuss a different instrument for operationalizing non-counseling duties.

 

     Role conflict. Role conflict occurs when school counselors experience multiple external demands from a variety of stakeholders (i.e., administrators, parents, teachers, and students). They report feeling so overwhelmed with attempting to meet all of these externally imposed expectations that they have trouble actually following the ASCA model (Falls & Nichter, 2007; Holman & Grubbs, 2018). As a result, school counselors experience job stress from competing externally imposed demands, each exerting pressure on school counselors’ limited time and resources.

 

Control Over School Counselor Tasks and Time

Conflicting external demands can become even more challenging when school counselors believe they do not have the ability to choose which tasks to prioritize or how much time to spend on different tasks. This can occur because building administrators insist the school counselor rigidly adhere to only those tasks the administrator believes are important, many of which may be contrary to the ASCA National Model (Falls & Nichter, 2007). Alternatively, school counselors may experience pressure from a building administrator who prioritizes some activities and a director of guidance who prioritizes completely different activities. School counselors may believe they cannot address student needs or conduct needs-based programming because there simply is not enough time to do so. School counselor job stress research indicated that the level of control counselors experience over how they spend their time might affect their level of job stress (Lee, Cho, Kissinger, & Ogle, 2010). Therefore, this is another potential variable we need to explore in relationship to SCBO.

 

Coworker Support and Supervision for School Counselors

The SCBO literature identifies two additional related variables, coworker support (Bardhoshi et al., 2014; Gunduz, 2012; Holman & Grubbs, 2018; Lambie, 2007; Thomas, 2011) and supervisory support (Bardhoshi et al. 2014; Holman & Grubbs, 2018; Moyer, 2011; Thomas, 2011), as potentially affecting the development of SCBO. Coworker support refers to the quality of relationships school counselors have with their fellow counselors, teachers, and administrators. Supervisory support refers to either the school counselor’s administrative supervisor or a clinical supervisor, which varies from school to school and district to district. Some school counselors have only a building administrator with little other supervisory support, while others have fellow counselors, perhaps even senior school counselors, whom they rely on for clinical supervision. Some districts have directors of guidance who act as school counselor supervisors. Regardless of how support structures are manifest in schools, the support variable, including both perceived support from colleagues and supervisory support, needs to be explored in relationship to SCBO.

 

Methods

 

We first obtained Institutional Review Board approval. Our research question was: What is the relationship of external demands on time, perceived control over work duties, and colleague and supervisor support with school counselor burnout symptomology? This current study builds on our previous research examining potential demographic variables identified in the literature as potential predictor variables for SCBO. In this study, we explored the significance, strength, and direction of the correlations between role ambiguity, role conflict, and assignment of non-counseling duties, measured by the Demand Control Support Questionnaire (DCSQ) Demand subscale; perceived control school counselors have over how their time is spent on the job, measured by the DCSQ Control subscale; school counselors’ perceptions regarding the level of support they experience from supervisors and colleagues, measured by the DCSQ Supervisor and Colleague Support subscale; and levels of SCBO measured by the Counselor Burnout Inventory (CBI) subscales. We intend to utilize the findings of this and our previous research to develop a model of SCBO in the future.

 

Participants

A priori, we conducted a power analysis determining that we needed 174 participants for sufficient power (a < .05, ß = .8), with a medium effect size (GPower, 2008). We solicited participants by sending emails with a link to our consent and survey to all school counselors in the state of Texas from a list provided by the Texas Education Agency. Employing a criterion sampling strategy, we only included those who met the following criteria: (a) certified school counselor in Texas, and (b) working in a public elementary, middle, or high school (Gay, Mills, & Airasian, 2011). Our non-random sample of 449 school counselors is representative of the population of Texas certified school counselors with most being White (81%), followed by smaller groups of Black (10%) and Hispanic (9%) counselors. Most (93%) reported having master’s degrees with the remainder holding educational specialist or doctoral degrees.

 

The sample represents elementary school (43%), middle school (22%), and high school (35%) counselors. Most of the counselors worked in suburban locations (47%), with rural (28%) and urban (26%) almost evenly split to make up the remainder of the sample. They reported working in schools ranging in size from 100 to 3,400 students. Over half the counselors responding reported caseloads of over 400 (53%), with those reporting 251–400 students (35%) as the next largest group, and those with less than 250 (11%) being the least represented group. The mean age of the participants was 44 years, with an average of 13 years’ experience in educational settings. Almost half (43%) were school counselors for 5 years or less. A quarter (25%) reported being counselors between 6 and 10 years, and 32% reported having at least 11 years’ experience as a school counselor.

 

Instruments

The current study gathered demographic data in addition to utilizing two instruments. The first is the DCSQ (Karasek & Theorell, 1990) and the second is the CBI (Lee et al., 2007).

DCSQ. The DCSQ (Karasek & Theorell, 1990) is a 30-item scale measuring “psychological work demands, job control and workplace social support” (Williams, Sundelin, & Schmuck, 2001, p. 71). It is the most recent iteration of a scale measuring job demands and psychological workload, decision latitude or control over tasks, and coworker and supervisory support on the job. The goal of the instrument, according to the developers, is “gathering objective data about work environments relevant for prevention-oriented goals of improving social and psychological working conditions” (Karasek et al., 1998; p. 328). It is self-administered and takes approximately 15 minutes to complete (Karasek, 1979; Karasek et al., 1998; Karasek & Theorell, 1990). Participants rate each statement on a 4-point Likert scale: 1 = strongly disagree, 2 = disagree, 3 = agree, and 4 = strongly agree. The subscales used in our study measure external demands (9 questions), perceived control (9 questions), and supervisor and coworker support (11 questions).
Multiple studies conducting exploratory factor analyses on the questionnaire support the dimensional structure (Cheng, Luh, & Guo, 2003; Choobineh, Ghaem, & Ahmedinejad, 2011; de Araújo & Karasek, 2008; Edimansyah, Rusli, Naing, & Mazalisah, 2006; Eum et al., 2007; Gimeno, Benavides, Amick, Benach, & Martínez, 2004; Gomez-Ortiz & Moreno, 2009; Kawakami, Kobayashi, Araki, Haratani, & Furui, 1995; Li, Yang, Liu, Xu, & Choi, 2004; Mase et al., 2012; Nehzat, Huda, & Tajuddin, 2014). In a recent study, both exploratory and confirmatory factor analysis examined goodness of fit using the Root Mean Square Error of Approximation, finding the values indicate good (.08) to excellent (.05) fit (Santos, Carvalho, & de Araújo, 2016). Additionally, research analyzing the data using a Comparative Fit Index and Tucker-Lewis Index compared the hypothetic model with independent variables finding both indices vary from 0 to 1 and values were above .90, indicating adequate fit (Santos, et al., 2016). They also established composite reliability for each factor loading and respective measurement error at or above .70, indicating satisfactory internal consistency (Santos et al., 2016). Finally, research has demonstrated adequate performance in discriminant validity (Santos et al., 2016).

According to Karasek and colleagues (1998), the coefficients on each subscale indicate strong internal consistency: Demand (.71–.79), Control (.80–.84), and Supervisor and Coworker Support
(.72–.85). Additionally, the “internal consistency of the scales tend to be similar across populations and between men and women” (Karasek et al., 1998, p. 336). The Cronbach’s alphas coefficient for women is .73 and for men is .74, both within acceptable ranges (Karasek et al., 1998). Additionally, several studies support the reliability of the scale format we used in our study (Kawakami & Fujigaki, 1996; Kawakami et al., 1995).

CBI. The CBI (Lee et al., 2007) is a 20-item self-report instrument measuring counselor burnout. Respondents rate each item on a 5-point Likert scale ranging from 1 (never true) to 5 (always true). A distinguishing feature of the CBI is that it includes both personal and organizational factors in determining level of burnout, whereas the Maslach Burnout Inventory (MBI) uses a model of burnout exclusive of organizational factors (Maslach, 1982; Maslach, Jackson, & Leiter, 1996, 1997). This is significant given that the literature indicates organizational factors, such as external demand on school counselor’s time spent on non-counseling duties (e.g., car duty, scheduling, test administration), as contributing to school counselor burnout (Baggerly & Osborn, 2006; Butler & Constantine, 2005; Culbreth et al., 2005; DeMato & Curcio, 2004; Falls & Nichter, 2007; Lambie, 2007; Mullen & Gutierrez, 2016; Rayle, 2006; Thompson & Powers, 1983; Wilkerson & Bellini, 2006).

The CBI developers established initial psychometrics using an exploratory factor analysis to evaluate construct validity and confirmed their findings with a second exploratory factor analysis. They identified five factors accounting for 66.9% of the total variance in school counselor burnout. Factor 1 is Negative Work Environment (NWE). This subscale includes items such as, “I feel frustrated with the system in my workplace,” thus measuring stress attributed to the work environment other than personal and interpersonal problems. Factor 2 is Devaluing Clients, which includes items such as, “I am no longer concerned about the welfare of my clients,” thus measuring a counselor’s challenges with connecting empathically with student clients. Factor 3 is Deterioration in Personal Life. This subscale includes items such as, “I feel I do not have enough time to spend with my friends,” thus measuring counselor’s perceptions of job-related stress on their personal life. Factor 4 is Exhaustion, including items such as, “Due to my job as a counselor I feel tired most of the time,” thus measuring physical and emotional exhaustion attributed to the job. Finally, Factor 5 is Incompetence. This subscale includes items such as, “I feel I am an incompetent counselor,” thus measuring the counselor’s self-perception of effectiveness on the job. Internal consistency of subscales is acceptable, ranging between .73 and .85 (Lee et al., 2007).
Initially, the instrument developers analyzed the psychometric properties of the CBI with two samples. Although not designed specifically to measure burnout among school counselors, the first sample of 258 counselors included 32.6% professional school counselors, and the second sample of 132 contained 43.2% professional school counselors (Lee et al., 2007, p. 144). Further, researchers validated the instrument with several counseling subspecialties, including school counselors (Lee et al., 2010; O’Sullivan & Bates, 2014). One study of the CBI with 272 school counselors using confirmatory factor analysis found the factor structure valid for use specifically with school counselors (Gnilka, Karpinski, & Smith, 2015). Additionally, test-retest reliability using a 6-week interval demonstrates strong reliability with subscale Cronbach alphas ranging from .72 to .85 (Lee et al., 2007). Finally, both concurrent validity (Lee et al., 2007; Wallace, Lee, & Lee, 2010) and discriminant validity (Lee et al., 2007; O’Sullivan & Bates, 2014; Puig et al., 2012) are well established.

 

Data Collection

Consistent with our approved protocol, we sent a survey link through Survey Monkey to all school counselor emails provided by the Texas Education Agency. We believe that school counselors suffering burnout are less likely to self-select without an additional incentive to participate because of the negative effects of burnout; therefore, they are more likely to be professionally disengaged. As such, we offered an incentive $50 gift certificate drawing for those choosing to participate and who provided their contact information at the end of the survey. According to Dillman (2014), the offer of an incentive is likely to improve the response rate and inclusion of participants that would not otherwise self-select to take the survey. After reading and agreeing to the consent document, participants completed an online survey comprised of the demographic questionnaire, the DCSQ, and the CBI.

 

Data Analysis
We downloaded the data from Survey Monkey to Excel and transferred it to SPSS. Once transferred, we eliminated any participants with missing data, leading to our final sample described above. We then conducted descriptive statistics including measures of central tendency, variability and dispersion, distributional shape, and histograms to evaluate normality, in order to ensure that the data collected is appropriate for the analysis conducted. After establishing that the data met the assumptions of normality, linearity, and homoscedasticity, we calculated the reliability coefficients for each of the instruments, namely the DCSQ and CBI, to evaluate their reliability. Once satisfied that each instrument demonstrated adequate reliability coefficients (.70 or higher), we conducted a Pearson’s product moment correlation to explore the relationships between the subscales for each instrument (Field, 2005). We examined the correlation matrix to evaluate evidence of multicollinearity, looking for correlations between two scales of .80 or higher. There were no subscales in the correlation matrix indicating multicollinearity.

 

Results

 

The reliability of the DCSQ and CBI subscales is documented in Table 1, and the relationships between the subscales is documented in Table 2. The DCSQ Demand subscale indicated a significant relationship to each CBI subscale; however, only four of them are large enough to interpret. These included a significant positive relationship between the Demand subscale and the CBI Exhaustion subscale (r = .608, p < .01), the CBI Incompetence subscale (r = .297, p < .01), the CBI NWE subscale (r = .517, p < .01), and the CBI Deterioration in Personal Life subscale (r = .518, p < .01). Although low, the Demand subscale also demonstrated significant negative relationships to the DCSQ Coworker and Supervisor Support subscale (r = -.272, p < .01). Therefore, increases in external demands placed on school counselors will likely result in higher levels of exhaustion, feelings of incompetence, experience of their work environment as negative, and deterioration in their personal lives. However, with increasing levels of coworker and supervisory support, external demands may have less impact on school counselors.

 

 

Table 1

 

DCSQ Subscale Reliability

 

Subscale Cronbach’s Alpha Cronbach’s Alpha based on standardized items Number of Items
DCSQ Control .171 .145   9
DCSQ Demand .807 .813   9
DCSQ Coworker Support .828 .843   6
DCSQ Supervisor Support .891 .890   5
DCSQ Support .907 .909 11
CBI Exhaustion .895 .900   4
CBI Incompetence .730 .733   4
CBI Negative Work Environment .828 .827   4
CBI Devaluing Clients .743 .759   4
CBI Deterioration in Personal Life .837 .836   4

 

 

 

Table 2

 

Correlation Matrix (DCSQ and CBI Subscales)

 

Subscale 1 2 3 4 5 6 7 8
1. Control 1 -.246** .294** -.153** -.106* -.330** -.038 -.181**
2. Demand -.246** 1 -.272** .608** .297** .517** .142** .518**
3. Support .294** -.272** 1 -.224** -.166** -.646** -.221** -.252**
4. Exhaustion -.153** .608** -.224** 1 .430** .539** .161** .717**
5. Incompetence -.106* .297** -.166** .430** 1 .464** .409** .435**
6. new -.330** .517** -.646** .539** .464** 1 .314** .552**
7. Devaluing Clients -.038 .142** -.221** .161** .409** .314** 1 .277**
8. Deter in Pers Life -.181** .518** -.252** .717** .435** .552** .277** 1

 

Note. *p < .05 ** p < .01

 

 

 

The Control subscale demonstrated significant negative correlations with the Demand (r = -.246,
p < .01), Exhaustion (r = -.153, p = < .01), Incompetence (r = -.106, p < .05), and Deterioration in Personal Life (r = -1.81, p < .01) subscales, and demonstrated a significant positive relationship with Coworker and Supervisor Support (r = .294, p < .01). However, only the NWE subscale (r = -.330, p < .01) correlation is large enough to interpret, increased control being significantly negatively correlated with NWE. Although the other correlations are low, there may be interaction effects that warrant future exploration. Therefore, the data suggested that with increased control over how school counselors spend their time, they are impacted less by external demands. They also experienced lower levels of exhaustion, feelings of incompetence, and deterioration in their personal lives. Working in an NWE results in school counselors feeling they have significantly less control over their day-to-day work.

 

The DCSQ Coworker and Supervisor Support subscale was significantly negatively related to the Demand (r = -.272 p < .01), Exhaustion (r = -.224, p < .01), Incompetence (r = -.166, p < .01),  Devaluing Clients (r = -.221, p < .01), and Deterioration in Personal Life (r = -.252, p < .01) subscales. However, only the NWE subscale correlation was large enough to interpret (r = -.646, p < .01). The Coworker and Supervisor Support subscale is significantly positively related to Control (r = .294, p < .01). These data indicate that increased perceptions of support from coworkers and supervisors decrease school counselors’ negative experience of external demands on their day-to-day work. They also feel lower levels of exhaustion, incompetence, experiences of devaluing their students, and deterioration in their personal lives. Similar to the Control variable discussed above, experiences of coworker and supervisory support are perceived to be lower when school counselors experience their work environments as negative.

 

Discussion and Implications

 

Although this study was formulated to expand research regarding demographic variables related to school counselor burnout, they were not found to be significant (Holman et al., 2018). Therefore, the current study focused on exploring organizational variables that may contribute to SCBO. After evaluating the literature, we identified the variables of role ambiguity, role conflict, and assignment of non-counseling duties, which we operationalized using the DCSQ Demand subscale; coworker and supervisory support, which we operationalized using the DCSQ Support subscale; and the level of control school counselors perceive they have over their time and tasks, which we operationalized using the DCSQ Control subscale.

 

We utilized a correlation matrix to explore relationships between these variables and the subscales of the CBI, which is a valid and reliable measure of SCBO. Our findings indicated organizational variables including high external demands, such as assignment of non-counseling duties; experiencing the school as a negative place to work; and experiencing low levels of support from colleagues and supervisors resulted in high levels of exhaustion and contributed to burnout. These variables need further exploration in future research using a hierarchical multiple regression to analyze the amount of variance they contribute to SCBO. This can provide school counselor educators, supervisors, school administrators, and school counselors with valuable information on the best areas of focus for prevention and intervention activities.

 

External Demands

The Demand subscale consistently demonstrates the strongest correlations across the matrix. This subscale measures psychological work overload and job conflict that result from role ambiguity such as the assignment of non-counseling duties. Items included whether the job requires employees to “work fast” or “work hard,” perception of “no excessive work,” having “enough time” to complete tasks, experiencing “conflicting demands” or frequent “task interruption,” experiencing the job as “hectic,” or that they have to “wait on others” to complete their job (Karasek et al., 1998).

 

Research on school counselor role ambiguity supports work overload and job conflict as both antecedents and consequences of role ambiguity in cyclical fashion (Paisley & McMahon, 2001). Additionally, our previous research supports the likelihood of interactions between these constructs, indicating that the DCSQ Demand subscale measures the assignment of non-counseling duties due to role ambiguity, thus resulting in role conflict and work overload (Holman et al., 2019). Role ambiguity, role conflict, and work overload interact to contribute to SCBO (Falls & Nichter, 2007; Holman & Grubbs, 2018; Maslach, 1982; Selye, 1976).

 

Given these data, we recommend school counselor educators and supervisors consider integrating ways to manage psychological workload in their pedagogical development of emerging school counselors. In addition, we recommend school counseling professionals self-monitor levels of psychological workload in order to identify job stress early and intervene through being proactive in planning self-care activities and continually monitoring levels of job stress so that early intervention and remediation is possible. School counselor educators, supervisors, and school counselors also should consider methods for systematically educating stakeholders on the appropriate role of a school counselor and advocate for that role. One way to do so is to utilize data-driven methods such as needs assessments and both formative and summative program evaluation measures.

 

By engaging in data-driven practice, school counselors have the necessary tools to communicate their roles and their worth to important stakeholders. School counselors should be proactive in reporting results from formative and summative program evaluation to stakeholders. This is consistent with the ASCA National Model (ASCA, 2012); however, school counselors likely increase their burnout risk when they continue to wait for administrators to direct them in which activities they will perform. We recommend that school counselors take command of their role by approaching the job from a professional school counselor mindset that demonstrates their role through action, rather than waiting to respond to others’ perceptions of their role.

 

Coworker and Supervisory Support

     Perceiving higher levels of coworker and supervisory support has a significant inverse relationship with the level of external demands the school counselor experiences on the job. This likely makes sense when we consider that the demands most often prioritized by school counselors are those that come from supervisors. This is consistent with previous literature that found coworker and supervisory support mediates SCBO (Falls & Nichter, 2007). Although significant, the level is just under .3. Given that support is significantly related to a decrease in SCBO, it is important to include the variable in a future regression analysis; however, based on the small correlation, this variable is likely to account for less variance in SCBO than some may hypothesize. The largest relationship involving level of support is the fact that when school counselors perceive they have low levels of support, they experience their work settings in a negative light. It is difficult with this limited data to understand whether the low support results in feeling negative about the work environment or vice versa. This is an area for exploration in the future, as it could provide important information about potential prevention.

 

Potential Effects of SCBO

Our research suggests that having a negative experience of one’s school environment is very important because it negatively impacts school counselors’ levels of student engagement and competency on the job. Additionally, the data indicated that school counselors working in a negative school environment not only experience high levels of exhaustion but also demonstrate a significant deterioration in their personal lives. The seminal literature on burnout among professionals who are not school counselors has extensively documented the physical, psychological, and interpersonal effects of job stress and burnout (e.g., Maslach, 1982; Selye, 1976). Additionally, preliminary research on SCBO indicated that school counselors report similar negative physical and psychological experiences resulting from job stress (Falls & Nichter, 2007; Holman & Grubbs, 2018). These include developing high blood pressure, overeating, engaging in substance abuse, developing insomnia, and exacerbation of mental health issues related to mood disorders and anxiety (Falls & Nichter, 2007; Holman & Grubbs, 2018).

 

Our study supports this existing research that there is a positive relationship between deterioration in personal life and burnout. Given both anecdotal experiences and decades of research on stress and burnout, these results probably seem obvious. However, the impact of SCBO on school counselors’ personal and professional lives, and specifically on the schools and students they serve, needs further examination in research uniquely focused on these topics.

 

     Deterioration in personal life. If we value the professional school counselors who provide supportive services for our schools, students, teachers, and parents, we should be concerned with their well-being. Counselor educators, supervisors, and those stakeholders who advocate for support of school counselors must actively demonstrate the value we have for school counselors. As such, we recommend that school counselor educators and supervisors develop intentional educational advocacy activities to teach the myriad of stakeholders in our communities about the effective role of school counselors. We tend to do a good job through our professional organizations lobbying for funding for school counselors. However, we do not always adequately educate school administrators, specifically, on the appropriate roles for a school counselor and on how utilizing school counselors in these roles ultimately benefits the school’s mission of developing healthy, knowledgeable, and well-functioning members of society who contribute to a positive community climate.

 

     Professional incompetence. The Incompetence subscale utilized in our study was significantly related to experiencing low levels of control over time and tasks, and low levels of support. Responses also demonstrated significant relationships with feeling high levels of external demands on time, experiencing exhaustion, perceiving one’s school environment as negative, devaluation of students, and deterioration in their personal lives. Although professional school counselors in previous studies have indicated that they do not view themselves as incompetent, measured as low sense of personal accomplishment by the MBI (Butler & Constantine, 2005; Lambie, 2007; Wilkerson & Bellini, 2006), our findings demonstrated a positive relationship between feelings of incompetence and SCBO.

 

One potential reason might be that the CBI, as an alternative measure normed specifically on school counselors, may provide a more nuanced and accurate method for measuring this construct. However, future research should examine this, determining whether these findings warrant this conclusion. It is our belief that there is a complex interplay of factors not yet identified in the literature which may improve our understanding of this variable. Therefore, future research should examine the development of school counselor incompetence more closely to gain a better understanding of how it manifests among this population.

 

We believe another interpretation for conflicting results on reported levels of incompetence among school counselors is that they do not view themselves as incompetent or lacking professional ability. Rather, they view themselves as being externally prevented from using the counseling skills they have. This happens due to conflicting external demands involving assignment of non-counseling duties prioritized as more important than counseling-specific duties (Falls & Nichter, 2007; Holman et al., 2019).

Regardless, if using the CBI to monitor SCBO levels, high scores on the Incompetence subscale would suggest school counselors are experiencing professional impairment. As a result, they are at risk of unethical behavior that may cause harm to students and schools. These risks include developing compassion fatigue or vicarious trauma, developing mental health or substance abuse issues that may impact performance, or even engaging in boundary violations with students through inappropriate relationships. Thus, we recommend school counselor educators, supervisors, and school districts monitor this as a form of risk management through periodic surveys or regular supervisory sessions where directors of guidance and administrators can gather qualitative data about levels of job stress in school counselors’ experience. We argue that once high levels of incompetence develop, the counselor is likely experiencing burnout requiring significant intervention, which might include taking a sabbatical or supervisors counseling these impaired professionals out of the profession. We emphasize the importance of prevention and early intervention in order to avoid school counselors developing high levels of incompetence.

 

Limitations and Future Research

 

The current study has several potential limitations, including that self-report research may result in respondents answering based on social desirability, or they might exaggerate their experiences. However, most of our limitations stem primarily from the limited school counseling sample. For reliable generalization beyond the population of school counselors in Texas, future research needs to evaluate these variables with school counselors in other geographic areas. Doing so might reflect differences across the diverse population of school counselors. Similarly, Caucasian participants (81%) are overwhelmingly represented in our sample. Although this may be consistent with the population of Texas school counselors, the sample does not represent the total population of school counselors to which we wish to generalize. Therefore, future research should seek to develop more ethnically diverse samples when replicating this study.

 

In addition, almost half our sample (43%) were elementary school counselors; therefore, future researchers should examine differences between counselors in elementary, middle, and high school levels in relationship to these predictor variables, perhaps conducting separate studies with each level to determine how much variance demand, control, and supervision or support variables impact SCBO among each of these groups. This is particularly salient in light of concerns about role ambiguity and role conflict developing out of discrepancies between school counselor training and actual duties on the job. In fact, research indicates that training for school counselors on level-specific (elementary and secondary) issues and activities has decreased over time from 14% of programs in 2000 to 2% in 2010 (Pérusse, Goodnough, & Noël, 2001; Pérusse, Poynton, Parzych, & Goodnough, 2015). Further, Goodman-Scott (2015) found no significant differences in recently graduated school counselors regarding content of coursework preparing them for elementary versus secondary placements. In fact, research has indicated that counselor educators preparing school counselors for elementary school positions make pedagogical decisions (e.g., what material to teach in classes and what classes to offer) primarily due to external influences like licensure requirements and job openings, rather than developmental needs of emerging school counselors (Goodman-Scott, Watkinson, Martin, & Biles, 2016). Therefore, future research also might examine interaction effects between grade level training and actual duties in relationship to burnout.

 

Similarly, future researchers should examine differences between urban, suburban, and rural locations in relationship to the predictor variables measured in the current study, given that almost half the sample (47%) worked in suburban locations. Again, separate studies may provide better information about differences between location of the school and school counselors’ experiences regarding the impact of external demands, decision latitude (control), and levels of perceived support or supervision on development of SCBO, if any exist.

 

Over half of our sample (53%) had caseloads of 400 or more, which is larger than that recommended by the ASCA National Model (ASCA, 2012). Although this may be common across the country, we suggest future research test whether these high caseloads may interact with other variables to influence the developmental trajectory of job stress. Therefore, future research should examine school counselors’ caseloads as they interact with levels of external demands, decision latitude, supervision, and colleague support to gain a more nuanced understanding of how these variables interact to influence development of SCBO.

 

Finally, interaction effects between these variables and identification of potential mediating and moderating variables will provide nuance in our understanding of diverse developmental trajectories of SCBO. By further exploring these, we may identify improved methods of monitoring, prevention, and early intervention, which can all work to support and sustain quality school counselors.

 

Conclusion

 

This project was the next one in a series of systematic studies evaluating potential contributing variables suggested in the SCBO literature. Given the serious potential impact of burnout on sustaining school counselors and on potential competency issues discussed above, which could violate school counselors’ ethical duty to promote student welfare, it is crucial that we understand the development of burnout in this counselor population. Our exploration of demographic variables indicated none of these significantly relate to development of job stress and burnout for school counselors surveyed, contrary to suggestions in previous literature (Holman et al., 2018). However, the current study demonstrated several variables that do correlate with school counselor burnout.

 

Stakeholders who demonstrate a lack of understanding about the appropriate role and duties of school counselors should be aware of conflicting demands on counselors’ time that increase job stress. These include inappropriate duties such as substitute teaching, standardized test administration, master scheduling, and disciplining students. As a result, these counselors experience high levels of psychological stress and emotional exhaustion, consistent with the traditional model of burnout discussed in the literature. Stress and exhaustion have negative effects on counselors’ personal and professional lives. Their experiences of stress are further exacerbated when they experience low levels of support from coworkers and supervisors. The combination of low support with high demands and low control over decision making likely contributes to school counselors’ experiencing their school environment negatively. External demands, emotional exhaustion, deterioration in personal life, low support and supervision, and NWE are potential predictor variables that might contribute to development of school counselor burnout and need further evaluation in future research.

 

Due to the results of this and previous studies, we recommend school counselors take the following steps to reduce the negative effects of stress that can result in burnout. Counselors should intentionally pursue preventative self-care planning and continual monitoring of stress levels with early intervention and remediation when heightened stress is identified. Additionally, we recommend school counselors be conscientious about engaging in data-driven practice for self-advocacy with stakeholders in order to improve stakeholder awareness of appropriate school counseling activities. We recommend that counselor educators develop pedagogical supports and induction practices that might serve to inoculate emerging school counselors to the typical stressors experienced in this professional role. Finally, we recommend ongoing supports, including consultation, supervision, networking, and personal counseling, when necessary to help school counselors manage stress levels. Future research should develop a model of school counselor burnout and explore potential mediating variables and interaction effects between variables. Doing so can inform future prevention and intervention efforts.

Conflict of Interest and Funding Disclosure

The authors reported no conflict of interest

or funding contributions for the development

of this manuscript.

 

References

 

Adelman, H. S., & Taylor, L. (2002). School counselors and school reform: New directions. Professional School Counseling, 5, 235–248.

Amatea, E. S., & Clark, M. (2005). Changing schools, changing counselors: A qualitative study of school administrators’ conceptions of the school counselor role. Professional School Counseling, 9, 16–27.

American School Counselor Association. (2012). ASCA National Model: A framework for school counseling programs. Alexandria, VA: Author.

Baggerly, J., & Osborn, D. (2006). School counselors’ career satisfaction and commitment: Correlates and predictors. Professional School Counseling, 9, 197–205.

Baker, S. B., & Gerler, E. R. (Eds.). (2004). School counseling for the twenty-first century (4th ed.). Upper Saddle River, NJ: Pearson Education.

Bardhoshi, G., Schweinle, A., & Duncan, K. (2014). Understanding the impact of school factors on school counselor burnout: A mixed-methods study. The Professional Counselor, 4, 426–443.
doi:10.15241/gb.4.5.426

Butler, S. K., & Constantine, M. G. (2005). Collective self-esteem and burnout in professional school counselors. Professional School Counseling, 9, 55–62.

Cheng, Y., Luh, W. M., & Guo, Y. L. (2003). Reliability and validity of the Chinese version of the Job Content Questionnaire in Taiwanese workers. International Journal of Behavioral Medicine, 10, 15–30.

Choobineh, A., Ghaem, H., & Ahmedinejad, P. (2011). Validity and reliability of the Persian (Farsi) version of the Job Content Questionnaire: A study among hospital nurses. Eastern Mediterranean Health Journal, 17, 335–341.

Culbreth, J. R., Scarborough, J. L., Banks-Johnson, A., & Solomon, S. (2005). Role stress among practicing school counselors. Counselor Education and Supervision, 45, 58–71. doi:10.1002/j.1556-6978.2005.tb00130.x

de Araújo, T. M., & Karasek, R. A. (2008). Validity and reliability of the Job Content Questionnaire in formal and informal jobs in Brazil. Scandinavian Journal of Work, Environment & Health, 34, 52–59.
doi:10.5271/sjweh.3792

DeMato, D. S., & Curcio, C. C. (2004). Job satisfaction of elementary school counselors: A new look. Professional School Counseling, 7, 236–245.

Dillman, D. A. (2014). Mail and internet surveys: The tailored design method (4th ed.). Hoboken, NJ: Wiley and Sons.

Dodson, T. (2009). Advocacy and impact: A comparison of administrators’ perceptions of the high school counselor role. Professional School Counseling, 12, 480–487. doi:10.1177%2F2156759X0901200606

Edimansyah, B. A., Rusli, B. N., Naing, L., & Mazalisah, M. (2006). Reliability and construct validity of the Malay version of the Job Content Questionnaire (JCQ). The Southeast Asian Journal of Tropical Medicine and Public Health, 37, 412–416. doi:10.15171/ijoem.2015.632

Eum, K.-D., Li, J., Jhun, H.-J., Park, J.-T., Tak, S.-W., Karasek, R. A., & Cho, S.-I. (2007). Psychometric properties of the Korean version of the Job Content Questionnaire: Data from health care workers. International Archives of Occupational and Environmental Health, 80, 497–504. doi:10.1007/s00420-006-0156-x

Falls, L., & Nichter, M. (2007). The voices of high school counselors: Lived experience of job stress. Journal of School Counseling, 5, 1–32.

Field, A. (2005). Discovering statistics using SPSS (2nd ed.). London, UK: SAGE.

Gay, L. R., Mills, G. E., & Airasian, P. (2011). Educational research: Competencies for analysis and application (10th ed.). Upper Saddle River, NJ: Prentice-Hall.

Gibson, D. M., Dollarhide, C. T., & Moss, J. M. (2010). Professional identity development: A grounded theory of transformational tasks of new counselors. Counselor Education & Supervision, 50, 21–38. doi:10.1002/j.1556-6978.2010.tb00106.x

Gimeno, D., Benavides, F. G., Amick, B. C., Benach, J., & Martínez, J. M. (2004). Psychosocial factors and work related sickness absence among permanent and non-permanent employees. Journal of Epidemiology & Community Health, 58, 870–876. doi:10.1136/jech.2003.016634

Gnilka, P. B., Karpinski, A. C., & Smith, H. J. (2015). Factor structure of the Counselor Burnout Inventory in a sample of professional school counselors. Measurement and Evaluation in Counseling and Development, 48(3), 177–191. doi:10.1177/0748175615578758

Gomez-Ortiz, V., & Moreno, L. (2009). Psychosocial work factors (demand-control and effort-reward imbalance), mental health and blood pressure: A study with school teachers in Bogotá, Colombia. Universitas Psychologia, 9, 393–407.

Goodman-Scott, E. (2015). School counselors’ perceptions of their academic preparedness and job activities. Counselor Education and Supervision, 54, 57–67. doi:10.1002/j.1556-6978.2015.00070.x

Goodman-Scott, E., Watkinson, J. S., Martin, I., & Biles, K. (2016). School counseling faculty perceptions and experiences preparing elementary school counselors. The Professional Counselor, 6, 303–317. doi:10.15241/egs.6.4.303

GPower 3.0.10 [Computer software]. (2008). Retrieved from https://download.cnet.com/G-Power/3000-2054_4-
10647044.html

Gunduz, B. (2012). Self-efficacy and burnout in professional school counselors. Educational Sciences: Theory & Practice, 12, 1761–1767.

Herlihy, B., Gray, N., & McCollum, V. (2002). Legal and ethical issues in school counselor supervision. Professional School Counseling, 6, 55–60.

Holman, L. F., & Grubbs, L. (2018). Examining the theoretical framework for the unique manifestation of burnout among high school counselors? Journal of Counselor Preparation and Supervision, 11.

Holman, L. F., Grubbs, L., Robles-Pina, R., Nelson, J., & Watts, R. (2019). Reliable measurement of non-counseling duties and other organizational variables on school counselor job stress and burnout. Manuscript submitted for publication.

Holman, L. F., Watts, R., Robles-Pina, R., & Grubbs, L. (2018). Exploration of potential predictor variables leading to school counselor burnout. Journal of School Counseling, 16(9). Retrieved from https://files.eric.ed.gov/fulltext/EJ1184754.pdf

House, R. M., & Hayes, R. L. (2002). School counselors: Becoming key players in school reform. Professional School Counseling, 5, 249–256.

Karasek, R. A. (1979). Job demands, job decision latitude, and mental strain: Implications for job redesign. Administrative Science Quarterly, 24, 285–308.

Karasek, R. A., Brisson, C., Kawakami, N., Houtman, I., Bongers, P, & Amick, B. (1998). The Job Content Questionnaire (JCQ): An instrument for internationally comparative assessments of psychosocial job characteristics. Journal of Occupational Health Psychology, 3, 322–355.

Karasek, R. A., & Theorell, T. (1990). Healthy work, stress, productivity and the reconstruction of working life. New York, NY: Basic Books.

Kawakami, N., & Fujigaki, Y. (1996). Reliability and validity of the Japanese version of the Job Content Questionnaire: Replication and extension in computer company employees. Industrial Health, 34, 295–306.

Kawakami, N., Kobayashi, F., Araki, S., Haratani, T., & Furui, H. (1995). Assessment of job stress dimensions based on the job demands-control model of employees of telecommunication and electric power companies in Japan: Reliability and validity of the Japanese version of the Job Content Questionnaire. International Journal of Behavioral Medicine, 2, 358–375.

Lambie, G. W. (2007). The contribution of ego development level to burnout in school counselors: Implications for professional school counseling. Journal of Counseling & Development, 85, 82–85.

Lee, S. M., Baker, C. R., Cho, S. H., Heckathorn, D. E., Holland, M. W., Newgent, R. A., . . . Yu, K. (2007). Development and initial psychometrics of the Counselor Burnout Inventory. Measurement and Evaluation in Counseling and Development, 40, 142–154.

Lee, S. M., Cho, S. H., Kissinger, D., & Ogle, N. T. (2010). A typology of burnout in professional counselors. Journal of Counseling & Development, 88, 131–138.

Li, J., Yang, W., Liu, P., Xu, Z., & Choi, S. I. (2004). Psychometric evaluation of the Chinese (mainland) version of the Job Content Questionnaire: A study in university hospitals. Industrial Health, 42, 260–267.

Lieberman, A. (2004). Confusion regarding school counselor functions: School leadership impacts role clarity. Education, 124, 552–558.

Mase, J., Ota, A., Inoue, K., Iida, T., Tsutsumi, U., Yatsuya, H., & Ono, Y. (2012). Reliability and validity of the Japanese translated version of the Swedish Demand-Control-Support Questionnaire. Industrial Health, 50, 467–475.

Maslach, C. (1982). Burnout: The cost of caring. Englewood Cliffs, NJ: Prentice-Hall.

Maslach, C., Jackson, S. E., & Leiter, M. P. (1996). Maslach burnout inventory manual (3rd ed.). Mountain View, CA: CPP.

Maslach, C., Jackson, S. E., & Leiter, M. P. (1997). Maslach burnout inventory (3rd ed.). In C. P. Zalaquett & R. J. Wood (Eds.), Evaluating stress: A book of resources (pp. 191–218). Lanham, MD: The Scarecrow Press.

Moyer, M. (2011). Effects of non-guidance activities, supervision, and student-to-counselor ratios on school counselor burnout. Journal of School Counseling, 9(5). Retrieved from http://jsc.montana.edu/articles/v9n5.pdf

Mullen, P. R., & Gutierrez, D. (2016). Burnout, stress and direct student services among school counselors. The Professional Counselor, 6, 344–359. doi:10.15241/pm.6.4.344

Nehzat, F., Huda, B. Z., & Tajuddin, S. H. (2014). Reliability and validity of Job Content Questionnaire for university research laboratory staff in Malaysia. The Southeast Asian Journal of Tropical Medicine and Public Health, 45, 481–489.

O’Sullivan, D., & Bates, J. K. (2014). The relationship among personal and work experiences: Implications for rehabilitation counselor well-being and service provision. Rehabilitation Research, Policy, and Education, 28, 45–60.

Paisley, P. O., & McMahon, H. G. (2001). School counseling for the 21st century: Challenges and opportunities. Professional School Counseling, 5, 106–115.

Pérusse, R., Goodnough, G. E., & Noël, C. J. (2001). A national survey of school counselor preparation programs: Screening methods, faculty experiences, curricular content, and fieldwork requirements. Counselor Education and Supervision, 40, 252–262. doi:10.1002/j.1556-6978.2001.tb01258.x

Pérusse, R., Poynton, T. A., Parzych, J. L., & Goodnough, G. E. (2015). Changes over time in masters level school counselor education programs. Journal of Counselor Preparation and Supervision, 7, 185–203. doi:10.7729/73.1072

Puig, A., Baggs, A., Mixon, K., Park, Y. M., Kim, B. Y., & Lee, S. M. (2012). Relationship between job burnout and personal wellness in mental health professionals. Journal of Employment Counseling, 49, 98–109.

Rayle, A. D. (2006). Do school counselors matter? Mattering as a moderator between job stress and job satisfaction. Professional School Counseling, 9, 206–215. Retrieved from https://www.jstor.org/stable/4273
2672

Santos, K. O. B., Carvalho, F. M., & de Araújo, T. (2016). Factor structure and validity indicators of the Job Content Questionnaire: Discussing stress in work contexts. Psychology, 7, 1424–1437.
doi:10.4236/psych.2016.712142

Scarborough, J. L. (2005). The School Counselor Activity Rating Scale: An instrument for gathering process data. Professional School Counselor, 5, 274–283. Retrieved from https://www.jstor.org/stable/42732469

Selye, H. (1976). The stress of life. New York, NY: J. B. Lippincott Company.

Shoffner, M. F., & Williamson, R. D. (2000). Engaging preservice school counselors and principals in dialogue and collaboration. Counselor Education and Supervision, 40, 128–140.

Thomas, M. K. (2011). Stress and Burnout in urban school counselors: An investigation into moderating factors. Dissertation Abstracts International Section A: Humanities and Social Sciences, 72(2-A). doi:10.1002/j.1556-6678.2006.tb00428.x

Thompson, D., & Powers, S. (1983). Correlates of role conflict and role ambiguity among secondary school counselors. Psychological Reports, 52, 239–242.

Wallace, S. L., Lee, J., & Lee, S. M. (2010). Job stress, coping strategies, and burnout among abuse-specific counselors. Journal of Employment Counseling, 47, 111–122. doi:10.1002/j.2161-1920.2010.tb00096.x

Watkinson, J. S., Goodman-Scott, E. C., Martin, I., & Biles, K. (2017). Counselor educators’ experiences preparing preservice school counselors: A phenomenological study. Counselor Education and Supervision, 57(3), 178–193. doi:10.1002/ceas.12109

Wilkerson, K., & Bellini, J. (2006). Intrapersonal and organizational factors associated with burnout among school counselors. Journal of Counseling & Development, 84, 440–450.
doi:10.1002/j.1556-6678.2006.tb00428.x

Williams, R. M., Sundelin, G., & Schmuck, M. L. (2001). Reliability of the demand-control questionnaire for sewing machine operators. Work, 16, 71–75.

 

Leigh Falls Holman is an assistant professor at the University of Memphis. Judith Nelson is an associate professor at Sam Houston State University. Richard Watts is a Distinguished Professor of Counseling at Sam Houston State University. Correspondence can be addressed to Leigh Falls Holman, CEPR, 100 Ball Hall Walker Ave., Memphis, TN 38152, lfalls@memphis.edu.