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.

Burnout, Stress and Direct Student Services Among School Counselors

Patrick R. Mullen, Daniel Gutierrez

The burnout and stress experienced by school counselors is likely to have a negative influence on the services they provide to students, but there is little research exploring the relationship among these variables. Therefore, we report findings from our study that examined the relationship between practicing school counselors’ (N = 926) reported levels of burnout, perceived stress and their facilitation of direct student services. The findings indicated that school counselor participants’ burnout had a negative contribution to the direct student services they facilitated. In addition, school counselors’ perceived stress demonstrated a statistically significant correlation with burnout but did not contribute to their facilitation of direct student services. We believe these findings bring attention to school counselors’ need to assess and manage their stress and burnout that if left unchecked may lead to fewer services for students. We recommend that future research further explore the relationship between stress, burnout and programmatic service delivery to support and expand upon the findings in this investigation.

 

Keywords: burnout, stress, school counselors, student services, service delivery

 

The American School Counselor Association (ASCA; 2012) recommends that school counselors enhance the personal, social, academic and career development of all students through the organization and facilitation of comprehensive programmatic counseling services. Delivery of student services is part of a larger framework articulated by ASCA’s National Model (2012) that also includes management, accountability and foundation components of school counseling programs. However, ASCA notes that school counselors should “spend 80 percent or more of their time in direct and indirect services to students” (ASCA, 2012, p. xii). ASCA defines indirect student services as services that are in support of students and involve interactions (e.g., referrals, consultations, collaborations and leadership) with stakeholders other than the student (e.g., parents, teachers and community members). On the other hand, direct student services are interactions that occur face-to-face and involve the facilitation of curriculum (e.g., classroom guidance lessons), individual student planning and responsive services (e.g., individual, group and crisis counseling). In either case, ASCA charges school counselors with prioritizing the delivery of student services.

 

As a part of their work, school counselors often incur high levels of stress that may result from multiple job responsibilities, role ambiguity, high caseloads, limited resources for coping and limited clinical supervision (DeMato & Curcio, 2004; Lambie, 2007; McCarthy, Kerne, Calfa, Lambert, & Guzmán, 2010). In addition, burnout can result from the ongoing experience of stress (Cordes & Dougherty, 1993; Maslach, 2003; Schaufeli & Enzmann, 1998) and can result in diminished or lower quality rendered services (Lawson & Venart, 2005; Maslach, 2003). While research on burnout is common in the school counseling literature (Butler & Constantine, 2005; Lambie, 2007; Wachter, Clemens, & Lewis, 2008; Wilkerson & Bellini, 2006), studies have not focused on the relationship between burnout and school counselors’ service delivery. Yet, burnout has the potential to produce negative consequences for the work rendered by school counselors and could result in fewer services for students (Lambie, 2007; Lawson & Venart, 2005; Maslach, 2003). Therefore, the purpose of this research was to examine the contribution of school counselors’ levels of burnout and stress to their delivery of direct student services.

 

School Counselors and the Delivery of Student Services

 

Research on school counselors’ delivery of student services has produced positive findings. In a meta-analysis that included 117 experimental studies, Whiston, Tai, Rahardja, and Eder (2011) identified that, in general, school counseling services have a positive influence on students’ problem-solving and school behavior. Furthermore, in schools where school counselors completed higher levels of student services focused on improving academic success, personal and social development, and career and college readiness, students experienced a variety of positive outcomes, such as increased sense of belongingness, increased attendance, fewer hassles with other students, and less bullying (Dimmitt & Wilkerson, 2012). Moreover, researchers have shown that the higher occurrence of school counselor-facilitated services is beneficial for students’ educational experience and academic outcomes (Carey & Dimmitt, 2012; Lapan, Gysbers, & Petroski, 2001; Wilkerson, Pérusse, & Hughes, 2013). Overall, the services conducted by school counselors have a positive impact on student success. As such, research investigating the factors related to higher incidence of school counselors’ direct student services could provide significant educational benefits to schools.

 

Researchers have examined a variety of topics that relate to increased student services. Clemens, Milsom, and Cashwell (2009) found that if school counselors had a good relationship with their principal and were engaged in higher levels of advocacy, they were likely to have increased implementation of programmatic counseling services. Another study concluded that school counselors’ values were not associated with the occurrence of service delivery, but researchers did find counselors with higher levels of leadership practices also delivered more school counseling services (Shillingford & Lambie, 2010). Other factors related to increased levels of school counselors’ service delivery are increased job satisfaction (Baggerly & Osborn, 2006; Pyne, 2011) and higher self-efficacy (Ernst, 2012; Mullen & Lambie, 2016). These studies provided notable contributions to the literature; however, at this time no known studies have examined the relationship among school counselors’ burnout, perceived stress and direct student services.

 

Stress and Burnout Among School Counselors

 

Stress is a significant issue that relates to the impairment of work performance (Salas, Driskell, & Hughes, 1996) and is a likely problem for school counselors. The construct of stress has a rich history in scientific literature dating back to the 1930s (Cannon, 1935; Selye, 1936). Selye (1980) articulated one of the first broad definitions of stress by defining it as the “nonspecific results of any demand upon the body” (p. vii). Over time, various authors developed an assortment of definitions (Ivancevich & Matteson, 1980; Janis & Mann, 1977; McGrath, 1976), but Lazarus and Folkman’s (1984) definition of stress is common among scholars (Driskell & Salas, 1996; Lazarus, 2006). In their Transactional Model of Stress and Coping, Lazarus and Folkman (1984) defined stress as a “particular relationship between the person and the environment that is appraised by the person as taxing or exceeding his or her resources and endangering his or her wellbeing” (p. 19). Lazarus and Folkman conceptualized that stress results from an imbalance between one’s perception of demands or threats and their ability to cope with the perceived demands or threats. Consequently, one’s appraisal of demands and their assessment of their coping ability becomes a critical issue in relationship to whether or not the demand will trigger a stress response.

 

McCarthy et al. (2010) applied Lazarus and Folkman’s model of stress (1984) to school counselors using an instrument that measures the demands and resources experienced by school counselors called the Classroom Appraisal of Resources and Demands–School Counselor Version (McCarthy & Lambert, 2008). McCarthy et al. (2010) found that school counselors who reported challenging demands as a part of their job also had higher levels of stress. This finding is troubling considering that school counselors oftentimes encounter ambiguous job duties, inconsistent job roles and conflicts in their job expectations (Burnham & Jackson, 2000; Culbreth, Scarborough, Banks-Johnson, & Solomon, 2005; Lambie, 2007; Scarborough & Culbreth, 2008). An additional concern is that stress occurring over an extended period of time can lead to emotional and physical health problems (Sapolsky, 2004) along with increased likelihood of leaving the profession (DeMato & Curcio, 2004). Fortunately, prior research reveals that school counselors have reported low stress levels (McCarthy et al., 2010; Rayle, 2006). Still, research on school counselors’ stress and its effects on the services they provide is important.

 

An additional factor that we believe may have an impact on direct student services is burnout. Burnout was first recognized in the 1970s (Freudenberger, 1974; Maslach, 1976) and is considered to have significant consequences for counseling professionals (Butler & Constantine, 2005; Lambie, 2007; Lawson, 2007; Lee et al., 2007). The topic of burnout is common in the literature across many disciplines (Schaufeli, Leiter, & Maslach, 2009) and has been given particular attention in school counseling research (Butler & Constantine, 2005; Lambie, 2007; Wachter et al., 2008; Wilkerson & Bellini, 2006). Freudenberger (1974, 1986) suggested that burnout results from depleted energy and the feelings of being overwhelmed that emerge from the exposure to diverse issues related to helping others, which over time affects one’s attitude, perception and judgment. Pines and Maslach (1978) described burnout as an ailment “of physical and emotional exhaustion, involving the development of negative self-concept, negative job attitude, and loss of concern and feelings for clients” (p. 234). In 1981, the Maslach Burnout Inventory (MBI) was developed as a method to measure one’s experience of burnout in the helping and human service field (Maslach & Jackson, 1981).

 

More recently, Lee et al. (2007) expanded the measurement of burnout and presented the construct of counselor burnout, which they defined as “the failure to perform clinical tasks appropriately because of personal discouragement, apathy to symptom stress, and emotional/physical harm” (p. 143). Within their model, Lee and associates found that counselor burnout includes the constructs of exhaustion, negative work environment, devaluing clients, incompetence and deterioration in personal life. These constructs correlate with the factors measured by the MBI (Maslach & Jackson, 1981), but provide a definition consistent with the work of school counselors (Gnilka, Karpinski, & Smith, 2015).

 

Many researchers have explored factors related to school counselor burnout. Overall, scholars have found that school counselors report low levels of burnout (Butler & Constantine, 2005; Gnilka et al., 2015; Lambie, 2007; Wachter et al., 2008; Wilkerson & Bellini, 2006). Nonetheless, researchers also reported that higher collective self-esteem is associated with a higher sense of personal accomplishment and lower emotional exhaustion (Butler & Constantine, 2005), whereas higher levels of ego development are associated with higher personal accomplishment (Lambie, 2007). Moreover, Wilkerson and Bellini (2006) discovered that school counselors who handle stressors with emotion-focused coping are at a higher risk of experiencing burnout symptoms, and Wilkerson (2009) established that school counselors’ emotion-focused coping increases their likelihood of experiencing symptoms of burnout. Yet, there is no research on the connection between school counselors’ burnout and the direct student services they provide despite a high likelihood that burnout is the cause of fewer and deteriorated services for students (Maslach, 2003).

 

The purpose of this study was to build upon existing literature regarding school counselors’ stress, burnout and their facilitation of direct student services. The guiding research questions were: (a) Do practicing school counselors’ levels of burnout and perceived stress contribute to their levels of service delivery? and (b) Do practicing school counselors’ levels of stress correlate with their burnout? Consequently, the following research hypotheses were examined: (a) School counselors’ degree of burnout and perceived stress contributes to their facilitation of direct student services, and (b) School counselors’ degree of perceived stress correlates positively with their level of burnout.

 

Method

 

Procedures

To answer the research questions associated with this study, we employed a cross-sectional research design (Gall, Gall, & Borg, 2007). Furthermore, this study utilized online survey data collection procedures. Prior to any data collection, we received approval from the Institutional Review Board at the first author’s university. During the first step in the data collection process, we retrieved the name and e-mail address of every school counselor listed in the ASCA online directory of membership. Next, we generated a simple random sample of school counselors. Then, we sent the sample selected from the ASCA online directory a series of three e-mails that aligned with tailored design method (Dillman, Smyth, & Christian, 2009) recommendations for survey research. Each e-mail contained a brief description of the survey and a link to the online survey managed by Qualtrics (2013). If a participant wished to take the survey, he or she was directed to the Web site that posted the explanation of the study. If they agreed to participate, they would move forward and complete the survey. Participants were screened as to whether they were practicing school counselors or not (e.g., student, counselor educator or retired). Of the 6,500 participants sampled, 41 indicated they were not a practicing school counselor. In addition, 312 e-mails were not working at the time of the survey. Out of the 6,147 practicing school counselors surveyed, 1,304 (21.21% visit response rate) visited the survey Web site and 926 completed the survey in its entirety, which resulted in a 15.06% useable response rate. The response rate received for this study is high in comparison to studies using similar methods (e.g., 14%, Harris, 2013; 11.4%, Mullen, Lambie & Conley, 2014).

 

Participant Characteristics

     Participants (N = 926) were practicing school counselors in private, public and charter K–12 educational settings from across the United States. The mean age was 43.27 (SD = 10.03) and included 816 (88.1%) female and 110 (11.9%) male respondents. The participants’ ethnicity included 50 (5.4%) African Americans, 5 (.5%) Asian Americans, 29 (3.1%) Hispanic Americans, 11 (1.2%) Multiracial, 2 (.2%) Native Americans, 4 (.4%) Pacific Islanders, 811 (87.6%) European Americans, and 13 (1.5%) participants who identified their ethnicity as “Other.” On average, participants had 10.97 (SD = 6.92) years of experience and 401.45 (SD = 262.05) students on their caseload. The geographical location of the participants’ work setting favored suburban (n = 434, 46.9%) and rural communities (n = 321, 34.7%) with fewer school counselors working in urban settings (n = 171, 18.5%). Most participants reported that they worked in the high school grade levels (n = 317, 34.2%) closely followed by elementary (n = 270, 29.2%) and middle school or junior high school (n = 203, 21.9%) grade levels, with 136 (14.7%) respondents working in another grade level format (e.g., grades K–12, K–8, or 6–12).

 

Measures

This study used the (a) Counselor Burnout Inventory (CBI; Lee et al., 2007), (b) the School Counselor Activity Rating Scale (SCARS; Scarborough, 2005), and (c) the Perceived Stress Scale (PSS; Cohen, Kamarck, & Mermelstein, 1983). Participants also completed a researcher-created demographics form regarding their personal characteristics (e.g., age, gender and ethnicity) and work-related characteristics (e.g., location type, grade level, caseload, experience as a school counselor and percentage of time they directly work with students).

 

CBI. The CBI (Lee et al., 2007) is a 20-item self-report measure that examines counselor burnout across five domains. The domains that make up the CBI include: (a) exhaustion, (b) incompetence, (c) negative work environment, (d) devaluing client, and (e) deterioration in personal life. The CBI makes use of a 5-point Likert rating scale that ranges from 1 (never true) to 5 (always true) and examines emotional states and behaviors representative of burnout. Some sample items include “I feel exhausted due to my work as a counselor” (exhaustion), “I feel I am an incompetent counselor” (incompetence), “I feel negative energy from my supervisor” (negative work environment), “I have little empathy for my clients” (devaluing client), and “I feel I have poor boundaries between work and my personal life” (deterioration in personal life). Lee et al. (2007) demonstrated the construct validity of the CBI through an exploratory factor analysis that identified a five-factor solution in addition to a confirmatory factor analysis that supported the five-factor model with an adequate fit to the data.

 

Gnilka et al. (2015) found support for the five-factor structure of the CBI (Lee et al., 2007) with school counseling using confirmatory factor analysis, which supports the CBI as an appropriate measure for school counselor burnout. Lee et al. (2007) established convergent validity for the CBI based upon the correlations between the subscales on the Maslach Burnout Inventory-Human Services Survey (Maslach & Jackson, 198l) and the CBI. In prior research, the Cronbach’s alphas of the CBI subscales indicated good internal consistency (Streiner, 2003) with score ranges of .80 to .86 for exhaustion, .73 to .81 for incompetence, .83 to .85 for negative work environment, .61 to .83 for devaluing client, and .67 to .84 for deterioration in personal life (Lee et al., 2007; Lee, Cho, Kissinger, & Ogle, 2010; Puig et al., 2012). The internal consistency coefficients of the CBI in this investigation also were good (Streiner, 2003) with Cronbach’s alphas of .87 for exhaustion, .79 for incompetence, .84 for negative work environment, .79 for devaluing client, and .81 for deterioration in personal life.

 

SCARS. The SCARS (Scarborough, 2005) is a 48-item verbal frequency measure that examines the occurrence that school counselors actually perform and prefer to perform components of the ASCA National Model (2012). The SCARS measures school counselors’ ratings of activities based on the four levels of interventions articulated by ASCA (1999) and the ASCA National Model (2003). Unfortunately, a more recent version of the SCARS that articulates the new ASCA National Model (2012) does not exist. Nevertheless, this study utilized two SCARS scales (counseling and curriculum) that measure the incidence of direct student services. To the benefit of this investigation, the direct services measured on the SCARS have not changed in the new edition of the ASCA National Model (2003, 2012). Similar to Shillingford and Lambie (2010) and Mullen and Lambie (2016), this investigation utilized the actual scale, but not the prefer scale, on the SCARS (Scarborough, 2005) because this study sought to examine the frequency that school counselors delivered direct student services, not their preferences and not the difference between their preference and actuality. The subscales that measure direct student services used in this study included the counseling (e.g., group and individual counseling interventions; 10 items) and curriculum (e.g., classroom guidance interventions; 8 items) subscales, whereas the coordination, consultation and other activities scales were not used because they measure indirect activities.

 

The SCARS (Scarborough, 2005) assesses the frequency of school counselor service delivery with a 5-point Likert rating scale that ranges from 1 (I never do this) to 5 (I routinely do this). Scores on the SCARS can be total scores or mean scores. Some sample items from the counseling subscale are “Counsel with students regarding school behavior” and “Provide small group counseling for academic issues.” Some sample items from the curriculum subscale are “Conduct classroom lessons addressing career development and the world of work” and “Conduct classroom lessons on conflict resolution.” Scarborough (2005) examined the validity by investigating the variances in score on the actual scale based on participant grade level and found that participants’ grade level had a statistically significant effect across the scales with small to large effect sizes (e.g., ranging from .11 to .68[ω2]), which supported the convergent validity of the SCARS. Additionally, construct validity was supported using factor analysis. In prior research using the SCARS, the internal consistency of the counseling and curriculum scales was strong with Cronbach’s alphas of .93 for the curriculum actual scale and .85 for the counseling actual scale (Scarborough, 2005). The internal consistency coefficients of the SCARS actual subscales in this investigation were good (Streiner, 2003) with Cronbach’s alphas of .77 for the counseling scale and .93 for the curriculum scale.

 

PSS. The PSS (Cohen et al., 1983) is a 10-item self-report measure that examines the participants’ appraisal of stress by asking about feelings and thoughts during the past month. The PSS uses a 5-point Likert scale that ranges from 0 (never) to 4 (very often) and includes four positively stated items that are reverse coded. Some sample items include, “In the last month, how often have you felt that you were on top of things?” (reverse coded), and “In the last month, how often have you been upset because of something that happened unexpectedly?” The PSS has been shown to have acceptable internal consistency with Cronbach’s alphas ranging from .84 to .91 (Chao, 2011; Cohen et al., 1983; Daire, Dominguez, Carlson, & Case-Pease, 2014). The internal consistency coefficient of the PSS in this study also was acceptable (Streiner, 2003) with a Cronbach’s alpha of .88.

 

Results

 

Preliminary Analysis

Initial screening of the data included the search for outliers (e.g., data points three or more standard deviations from the mean) using converted z-scores (Osborne, 2012), which resulted in identifying 21 cases that had at least one variable with an extreme outlier. To accommodate for these outliers, the researchers utilized a Windorized mean based on adjacent data points (Barnett & Lewis, 1994; Osborne & Overbay, 2004). Next, the assumptions associated with structural equation modeling (SEM) were tested (e.g., normality and multicollinearity; Hair, Black, Babin, Anderson, & Tatham, 2006; Tabachnick & Fidell, 2007). Multicollinearity was not present with these data; however, the data violated the assumption of normality of a single composite variable (e.g., devaluing clients scale on the CBI). Researchers conducted descriptive analyses of the data using the statistical software SPSS. Table 1 presents the means, standard deviations and correlations for the study variables.

 

Model Testing

This correlational investigation utilized a two-step SEM method (Kline, 2011) to examine the research hypothesis employing AMOS (version 20) software. The first step included a confirmatory factor analysis (CFA) to inspect the measurement model of burnout and its fit with the data. Then, a structural model was developed based on the measurement model. The measurement model and structural model were appraised using model fit indices, standardized residual covariances, standardized factorial loadings and standardized regression estimates (Byrne, 2010; Kline, 2011). Modifications to the models were made as needed (Kline, 2011). Both the measurement and the structural models employed the use of maximum likelihood estimation technique despite the presence of non-normality based on recommendations from the literature (Curran, West, & Finch, 1996; Hu, Bentler, & Kano, 1992; Lei & Lomax 2005; Olsson, Foss, Troye, & Howell, 2000).

 

 

 

 

 

Table 1 Correlations among measures of direct student services, perceived stress, and burnout

M

SD

1

2

3

4

5

6

7

8

9

Counseling

3.02

.60

Curriculum

2.77

1.16

.44

Percent of Time

59

78

.36

.27

Perceived Stress

1.56

.63

-.15

-.11

-.14

Exhaustion

3.04

.86

-.15

-.11

-.11

.61

Incompetence

2.29

.68

-.31

-.14

-.18

.49

.44

NEW

2.56

.87

-.23

-.19

-.22

.46

.53

.39

DC

1.39

.50

-.20

-.17

-.14

.32

.28

.45

.64

DPL

2.39

.80

-.19

-.12

-.16

.58

.66

.41

.47

.30

Note. N = 926. All correlations (r) were statistically significant (p < .001). Counseling = frequency of direct counseling services, curriculum = frequency of direct curriculum services, percent of time = percent of time in direct services to students, NEW = negative work environment, DC = devaluing client, DPL = deterioration in personal life.

 

 

Multiple fit indices were examined to determine the goodness of fit for the measurement model and structural model (Hu & Bentler, 1999; Kline, 2011; Weston & Gore, 2006). The fit indices that were used include: (a) chi-square, (b) comparative fit index (CFI), (c) goodness of fit (GFI), (d) standardized root mean square residual (SRMSR), and (e) root mean square error of approximation (RMSEA). Furthermore, we consulted the normed fit index (NFI) and Tucker-Lewis index (TLI) because they are more robust to non-normal data as compared to other indices (Lei & Lomax, 2005). For a detailed description of these fit indices, readers can review the works of Hu and Bentler (1999), Kline (2011), and Weston and Gore (2006). We used these fit indices to establish a diverse view of model fit.

 

     Measurement model. First, we employed a CFA model to examine the latent variable representing burnout (Lee et al., 2007). The research team totaled each subscale on the CBIs to develop a composite score for each domain. The initial measurement model for burnout produced acceptable standardized factor loadings ranging from .41 (devaluing client) to .57 (incompetence), .62 (negative work environment), .77 (deterioration in personal life), and .82 (exhaustion). Furthermore, all fit indices for the measurement model indicated an adequate fitting model except chi-square, RMSEA, and TLI: χ2 (df = 5, N = 926) = 107.07, p < .001; GFI = .96; CFI = .92; RMSEA = .15; SRMR = .06; NFI = .92; TLI = .85. Therefore, we consulted the modification indices and standardized residual covariance matrix and tested a new CFA based upon these consultations.

 

The modifications indices indicated the need to correlate the error terms for incompetence and devaluing client. The resulting model produced a model in which all fit indices indicated an adequate fitting model: χ2 (df = 4, N = 926) = 12.03, p = .02; GFI = .99; CFI = .99; RMSEA = .05; SRMR = .02; NFI = .99; TLI = .99. Further inspection of the standardized factor loadings for the model indicated they were all acceptable except for the factor loading for devaluing client, which dropped to .36 (below .40; Stevens, 1992). While these modifications improved the overall fit of the CFA, the correlation of incompetence and devaluing client has no theoretical justification (Byrne, 2010). In addition, the correlation of the error terms for incompetence and devaluing client produced a standardized factor loading below the noted standard of .40 (Kline, 2011; Stevens, 1992). Subsequently, we removed the subscale of devaluating client given: (a) the low factor loading produced after modification of the initial model, and (b) the lack of normality in the composite score.

 

Next, we examined the new modified measurement model that included the removal of the subscale devaluing client. The resulting model (see Figure 1) produced a model in which all fit indices indicated a good fitting model: χ2 (df = 2, N = 926) = 8.25, p = .02; GFI = .99; CFI = .99; RMSEA = .06; SRMR = .02; NFI = .99; TLI = .98. The modified measurement model for burnout produced acceptable standardized factor loadings ranging from .53 (incompetence) to .63 (negative work environment), .77 (deterioration in personal life), and .85 (exhaustion). In review of the model fit indices and standardized factor loadings, we deemed the measurement model acceptable for use in the structural model.

 

     Structural model. We developed the structural model (see Figure 1) based on a review of the literature, and it was theorized in this model that school counselors’ perceived stress correlates to school counselors’ burnout and contributes to the frequency with which they provide direct student services. In addition, this model tested the hypothesized model that school counselors’ burnout contributes to their frequency of direct student services. The structural model includes the measurement model previously tested that consisted of the latent variable of burnout. School counselors’ perceived stress and burnout were defined as exogenous or independent variables. Perceived stress was a manifest variable consisting of participants’ composite scores on the PSS (Cohen et al., 1983).

 

Additionally, we defined the manifest variables of percentage of time at work providing direct services to students, direct curriculum activities, and direct counseling activities as the endogenous or dependent variables that measure participants’ facilitation of direct student services. The variable of percentage of time at work providing direct services to students was a single demographic item reported by participants, while direct curriculum activities and direct counseling activities were the participants’ composite scores derived from subscales on the SCARS (Scarborough, 2005). In addition, the error terms of the direct student services variables—percentage of time at work providing direct services to students, direct curriculum activities and direct counseling activities—were correlated given that they measure similar constructs.

 

An examination of the structural model indicated a strong goodness of fit for all fit indices except for chi-square: χ2 (df = 14, N = 926) = 108.37, p < .001; GFI = .97; CFI = .96; RMSEA = .07; SRMR = .04; NFI = .95; TLI = .91. The researchers deemed the structural model as suitable with these data despite the significant chi-square (Henson, 2006; Kline, 2011; Weston & Gore, 2006). A closer examination of the standardized regression weights identified that school counselors’ burnout scores contributed to 12% (β = -.35, p < .001) of the variance in their direct counseling activities and 5% (β = -.22, p < .001) of the variance in their direct curriculum activities. Furthermore, school counselors’ burnout scores contributed to 6% (β = -.24, p < .001) of the variance in percentage of time at work providing direct services to students. Perceived stress did not contribute to direct counseling activities (β = .11, p = .04), direct curriculum activities (β = .06, p = .31), and percentage of time at work providing direct services to students (β = .04, p = .51). In addition, perceived stress and burnout produced a statistically significant correlation (β = .75, p < .001; 56% of the variance explained).

 

The structural model (Figure 1) indicates that school counselors’ level of counselor burnout had a negative contribution to the frequency of their direct counseling activities, direct curriculum activities and percentage of time at work providing direct services to students. However, it should be noted that the effect sizes of these findings were small to medium (Sink & Stroh, 2006). An additional finding from this investigation was that the perceived stress correlated with burnout with a large effect size (Sink & Stroh, 2006); however, perceived stress did not have a statistically significant contribution to school counselors’ direct counseling activities, direct curriculum activities, and percentage of time at work providing direct services to students.

 

 

Figure 1. Final hypothesized structural model depicting the relationship between school counselors’ (N = 926) perceived stress, burnout, and direct student services.

 

Discussion

 

This study examined the relationship between school counselors’ reported burnout, perceived stress and frequency of direct student services. The findings indicated burnout was a statistically significant contributor to the frequency of direct counseling services (β = -.35; medium effect size) and direct curriculum services (β = -.22; small to medium effect size). Furthermore, the findings identified that burnout was a significant contributor to the participants’ report of the percentage of time they spend on their job working directly with students (β = -.24; small to medium effect size). Although the results should be interpreted with some level of caution, we found that burnout also had a statistically significant relationship to frequency of direct student services with increased levels of burnout relating to lower levels of direct student services. Nonetheless, these findings are not surprising considering the literature on burnout emphasizes the important role burnout plays on the effort one places on their job, with individuals presenting with higher burnout typically having lower investment interest in their job (Garman, Corrigan, & Morris, 2002; Landrum, Knight, & Flynn, 2012; Maslach, 2003). While the findings support the literature on the role of burnout, they also bring attention to the possibility that burnout does not have a strong relationship to school counselors’ facilitation of direct counseling services as noted by the small effect size.

 

An interesting finding was that school counselors’ degree of perceived stress did not contribute to the direct student services variables and yet did correlate with burnout. In fact, the relationship between perceived stress and counselor burnout had a large effect size, with 56% of the variance among these variables explained by their relationship. This finding accentuates the difference between the constructs of burnout and stress because burnout had a statistically significant relationship with the direct student services variables and stress did not, despite the strength of the relationship between burnout and stress. One interpretation of this finding is that school counselors’ ability to manage and cope with stress permits them to complete their job functions, whereas burnout may be more challenging to overcome. Furthermore, scholars state that prolonged exposure to stress worsens or cultivates burnout (Cordes & Dougherty, 1993; Schaufeli & Enzmann, 1998). This finding is logical given the theory behind burnout (Lee et al., 2007; Maslach, 2003); yet, this is one of only a few studies (McCarthy et al., 2010; Wilkerson & Bellini, 2006) in the school counseling literature to examine this relationship. However, these results need further exploration. As McCarthy et al. (2010) noted, the construct of stress is multidimensional (includes appraisal of resources and demands) and the PSS (Cohen et al., 1983) is a single-dimension scale. Therefore, a scale that examines stress in a multifaceted manner may produce different results.

 

An additional finding worth discussion involves the measurement model of the CBI (Lee et al., 2007). Specifically, this study found that the construct of devaluing client did not fit with the data. Furthermore, participants reported low scores regarding the devaluing client scale, as indicated by the descriptive statistics. The devaluing client subscale also was the only subscale on the CBI that was not normally distributed. These results were similar to Gnilka et al.’s (2015) findings that indicated school counselors are likely to maintain high levels of empathy and positive regard for their students. These findings may indicate that the devaluing clients subscale may not reflect symptoms of burnout for school counselors. This is a promising finding as it suggests that school counselors do not develop a negative perspective of students because of the negative consequences of their job.

 

The descriptive statistics from this investigation also provide some noteworthy information. First, participants reported moderate to low levels of burnout across the five factors of the CBI (Lee et al., 2007), with exhaustion having the highest mean score. These results are consistent with prior research (Butler & Constantine, 2005; Lambie, 2007; Wachter et al., 2008; Wilkerson & Bellini, 2006) on burnout and indicate that, overall, school counselors report low levels of burnout. An additional finding was that school counselors reported a low level of perceived stress, which is surprising given the challenge of role ambiguity, confusion and conflict (Burnham & Jackson, 2000; Culbreth et al., 2005; Lambie, 2007; Scarborough & Culbreth, 2008). However, school counselors have reported low levels of stress in other research (e.g., McCarthy et al., 2010; Rayle, 2006). The last noteworthy finding from the descriptive statistics was the measures of direct student services. This investigation was one of the first to focus specifically on the topic of direct student services versus other aspects of school counselors’ roles. This study found that school counselors reported that, on average, they spend over half their time working directly with students. In addition, they reported high frequencies for facilitating both curriculum and counseling activities. These findings are promising and consistent with other research examining these constructs (Mullen & Lambie, 2016; Scarborough & Culbreth, 2005; Shillingford & Lambie, 2010). Overall, the results from this study provide new and novel information for the school counseling discipline.

 

Limitations and Implications for Future Research

Readers should interpret these findings within the context of their limitations. Some limitations from this study include: (a) associational research using correlation statistics does not establish cause and effect relationships; (b) the response rate, although high as compared to other studies with similar methods, is low; and (c) the generalizability of these findings is limited by the sampling procedures (e.g., only sampled ASCA members; Gall et al., 2007). In addition, participants who respond to surveys may have different characteristics as compared to those school counselors who chose not to participate (Gall et al., 2007).

 

The findings from this study have implications for future research. A prominent direction for future research is the examination of the relationship between stress and programmatic service delivery, including direct student services. This study identified that perceived stress has no relationship with direct service delivery, but a multidimensional measure of stress (McCarthy & Lambert, 2008) may produce different results. Similarly, this study found that perceived stress relates to higher levels of burnout and supports the theory that chronic stress relates to increased burnout. Future research might further confirm these findings.

 

Another relevant future research implication is exploring factors that prevent or mediate the contribution of burnout to school counselor service delivery, considering this investigation found a significant relationship between these constructs. A variety of mechanisms may serve as buffers between burnout and programmatic service delivery, such as coping skills, career-sustaining behaviors, emotional intelligence, grit, or self-efficacy. Nonetheless, the identification of preventative skills or personal traits that inhibit the effects of burnout may lead to interventions to support school counselors’ work. Future research also can examine training interventions that target school counselors’ susceptibility to burnout or stress. A final research implication is the need to replicate and confirm our findings. Researchers might consider replicating this study with similar or different measures and data collection methods.

 

Implications for School Counseling Practitioners and Supervisors

The degree of perceived stress for participants in this study had a positive correlation with their degree of burnout. Furthermore, participants’ burnout negatively contributed to their level of direct student services. While this study included several limitations, these findings provide more evidence for the positive relationship between stress and burnout, in addition to the negative contribution burnout can have on the job functions of school counselors. In an effort to support direct student services, it would behoove school counselors to take steps to increase their awareness about their well-being, including symptoms of burnout, and seek support to address concerns as they arise. Additionally, school counselors’ failure to address burnout is an ethical concern (American Counseling Association, 2014). School counselors could utilize a self-assessment (i.e., Counselor Burnout Inventory [Lee et al., 2007] or Professional Quality of Life Scale [Stamm, 2010]) to examine their level of burnout and subsequently address their work functions and lifestyle to alleviate symptoms.

 

As Moyer (2011) pointed out, supervision plays a vital role in school counselor development and can be a way to alleviate burnout. Thus, supervisors can provide opportunities for school counselors to learn ways to assess their well-being with the aim of developing career-sustaining behaviors to prevent burnout. For example, supervisors can inform school counselors of available screening measures and provide resources to aid in the development of career-sustaining behaviors. Similarly, supervisors can create activities (Lambie, 2006) that assess school counselors’ well-being, which allows counselors to address negative feelings. Efforts made to prevent burnout may increase the chances of school counselors performing direct student services. Higher rates of direct student services, such as individual and group counseling, also may lead to better educational outcomes for students (Lapan, 2012).

 

In an effort to reduce school counselors’ burnout and potentially increase their delivery of direct student services, practitioners and supervisors can initiate wellness-related activities. Butler and Constantine (2005) noted that peer supervision or consultation along with social support from colleagues and administrators might be helpful for reducing the effects of burnout. Furthermore, Lawson and Myers (2011) reported on the highest rated career-sustaining behavior, which provides potential to support the wellness of school counseling practitioners. As Meyer and Ponton (2006) noted, counselors as a whole tend to put their own wellness to the side in order to provide services to their clients. Therefore, another consideration for school districts and school counseling organizations is to offer wellness-focused training that could raise attention to counselors’ level of stress and burnout and provide strategies to enhance their wellness. Additionally, school counselors should remember to advocate for the profession and for themselves (Young & Lambie, 2007). It is important that administrators understand the critical wellness needs of school counselors, and school counselors should be among the first to advocate for this cause. As these findings indicate, there is a relationship between burnout and the quality of services offered by school counselors. Therefore, it is important that counselors “learn to be their own advocates and help dysfunctional workplaces become well” (Young & Lambie, 2007, p. 99).

 

In summary, this study examined the association of practicing school counselors’ degree of burnout, perceived stress and frequency of direct student services. The findings indicated that higher levels of burnout contribute to a decreased frequency of direct student services. Furthermore, school counselors’ perceived stress does not contribute to their facilitation of direct student services, but was positively associated with burnout. Overall, these findings are encouraging because the descriptive statistics indicate that school counselors operate at a low level of burnout and perceived stress and provide a moderate to high frequency of direct student services.

 

 

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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Patrick R. Mullen, NCC, is an Assistant Professor at the College of William and Mary. Daniel Gutierrez, NCC, is an Assistant Professor at the University of North Carolina – Charlotte. Correspondence can be addressed to Patrick Mullen, School of Education, P.O. Box 8795, College of William & Mary, Williamsburg, VA  23188, prmullen@wm.edu.