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.


References

Akos, P., & Scarborough, J. L. (2004). An examination of the clinical preparation of school counselors. Counselor Education and Supervision, 44, 96–107. doi:10.1002/j.1556-6978.2004.tb01863.x

American School Counselor Association. (2003). The ASCA national model: A framework for school counseling programs. Alexandria, VA: Author.

American School Counselor Association. (2012). The ASCA national model: A framework for school counseling programs (3rd ed.). Alexandria, VA: Author.

Bandura, A. (1996). Ontological and epistemological terrains revisited. Journal of Behavior Therapy and Experimental Psychiatry, 27, 323–345. doi:10.1016/S0005-7916(96)000493

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

Bartholomew, K., & Horowitz, L. M. (1991). Attachment styles among young adults: A test of a four-category model. Journal of Personality and Social Psychology, 61, 226–244. doi:10.1037/0022-3514.61.2.226

Bemak, F., & Chung, R. C.-Y. (2008). New professional roles and advocacy strategies for school counselors: A multicultural/social justice perspective to move beyond the nice counselor syndrome. Journal of Counseling & Development, 86, 372–381.

Bodenhorn, N., & Skaggs, G. (2005). Development of the School Counselor Self-Efficacy Scale. Measurement and Evaluation in Counseling and Development, 38, 14–28.

Bodenhorn, N., Wolfe, E. W., & Airen, O. E. (2010). School counselor program choice and self-efficacy: Relationship to achievement gap and equity. Professional School Counseling, 13, 165–174.

Brennan, K. A., Clark, C. L., & Shaver, P. R. (1998). Self-report measurement of adult attachment: An integrative overview. In J. A. Simpson & W. S. Rholes (Eds.), Attachment theory and close relationships (pp. 46–76). New York, NY: Guilford Press.

Burnham, J. J., & Jackson, C. M. (2000). School counselor roles: Discrepancies between actual practice and existing models. Professional School Counseling, 4, 41–49.

Campbell, C. A., & Dahir, C. A, (1997). Sharing the vision: The national standards for school counseling programs. Alexandra, VA: American School Counselor Association Press.

Carey, J., & Dimmitt, C. (2012). School counseling and student outcomes: Summary of six statewide studies. Professional School Counseling, 16, 146–153.

Cinotti, D. (2014). Competing professional identity models in school counseling: A historical perspective and commentary. The Professional Counselor, 4, 417–425.

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum.

Cohen, J., & Cohen, P. (1993). Applied multiple regression/correlation analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum.

Dahir, C. A. (2004). Supporting a nation of learners: The role of school counseling in educational reform. Journal of Counseling & Development, 82, 344–353.

Desivilya, H. S., Sabag, Y., & Ashton, E. (2006). Prosocial tendencies in organizations: The role of attachment styles and organizational justice in shaping organizational citizenship behaviour. International Journal of Organizational Studies, 14, 22–42. doi:10.1108/10553180610739731

Dillman, D. A., Smyth, J. D., & Christian, L. M. (2014). Internet, mail, and mixed-mode surveys: The tailored design method (4th ed.). New York, NY: Wiley.

Dozier, M., Lomax, L., Tyrrell, C. L., & Lee, S.W. (2001). The challenge of treatment for clients with dismissing states of mind. Attachment and Human Development, 3, 62–76.

Erford, B. T. (2016). Professional school counseling: Integrating theory and practice into a data-driven, evidence-based approach. In B. T. Erford (Ed.), Professional School Counseling: A Handbook of Theories, Programs, and Practices (3rd ed., pp. 3–8). Austin, TX: ProEd.

Faul, F., Erdfelder, E., Buchner, A., & Lang, A.-G. (2009). Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41, 1149–1160. doi:10.3758/BRM.41.4.1149

Field, A. P. (2009). Discovering statistics using SPSS (3rd ed.). Los Angeles, CA: Sage.

Fitch, T. J., & Marshall, J. L. (2004). What counselors do in high-achieving schools: A study on the role of the school counselor. Professional School Counseling, 7, 172–179.

Foster, L. H., Young, J. S., & Hermann, M. (2005). The work activities of professional school counselors: Are the national standards being addressed? Professional School Counseling, 8, 313–321.

Granello, D. H., & Wheaton, J. E. (2004). Online data collection: Strategies for research. Journal of Counseling & Development82, 387–393.

Gysbers, N. C., & Henderson, P. (2012). Developing and managing your school guidance program (5th ed.). Alexandria, VA: American Counseling Association.

Hazan, C., & Shaver, P. (1987). Romantic love conceptualized as an attachment process. Journal of Personality and Social Psychology, 52, 511–524. doi:10.1037/0022-3514.52.3.511

Judge, T. A., & Bono, J. E. (2001). Relationship of core self-evaluations traits—self-esteem, generalized self-efficacy, locus of control, and emotional stability—with job satisfaction and job performance: A meta-analysis. Journal of Applied Psychology, 86, 80–92. doi:10.1037//0021-9010.86.1.80

Kennedy, J. H., & Kennedy, C. E. (2004). Attachment theory: Implications for school psychology. Psychology in the Schools, 41, 247–259. doi:10.1002/pits.10153

Lapan, R. T., Gysbers, N. C., & Petroski, G. F. (2001). Helping seventh graders be safe and successful: A statewide study of the impact of comprehensive guidance and counseling programs. Journal of Counseling & Development, 79, 320–330. doi:10.1002/j.1556-6676.2001.tb01977.x

Larson, L. M., & Daniels, J. A. (1998). Review of counseling self-efficacy literature. The Counseling Psychologist, 26, 179–218. doi:10.1177/0011000098262001

Leiter, M. P., Day, A., & Price, L. (2015). Attachment styles at work: Measurement, collegial relationships, and burnout. Burnout Research, 2, 25–35.

Lent, R. W., & Hackett, G. (1987). Career self-efficacy: Empirical status and future directions. Journal of Vocational Behavior, 30, 347–382. doi:10.1016/0001-8791(87)90010-8

Lopez, F. G., & Brennan, K. A. (2000). Dynamic processes underlying adult attachment organization: Toward an attachment theoretical perspective on the healthy and effective self. Journal of Counseling Psychology, 47, 283–300. doi:10.1037/0022-0167.47.3.283

Mallinckrodt, B. (2000). Attachment, social competencies, social support, and interpersonal process in psycho-therapy. Psychotherapy Research, 10, 239–266. doi:10.1093/ptr/10.3.23

Marotta, S. A. (2002). An ecological view of attachment theory: Implications for counseling. Journal of Counseling & Development, 80, 507–510.

McCarthy, C. J., Kerne, V. V. H., Calfa, N. A., Lambert, R. G., & Guzmán, M. (2010). An exploration of school

counselors’ demands and resources: Relationship to stress, biographic, and caseload characteristics.

Professional School Counselor, 13, 146–158.

McMahon, H. G., Mason, E. C. M., & Paisley, P. (2009). School counselor educators as educational leaders promoting systemic change. Professional School Counseling, 13, 116–124. doi:10.5330/PSC.n.2010-13.116

Mikulincer, M., & Shaver, P. R. (2003). The attachment behavioral system in adulthood: Activation, psycho-dynamics, and interpersonal processes. In M. P. Zanna (Ed.), Advances in experimental social psychology (Vol. 35, pp. 53–152). New York, NY: Academic Press.

Mikulincer, M., & Shaver, P. R. (2007). Attachment in adulthood: Structure, dynamics, and change. New York, NY: Guilford Press.

Mikulincer, M., Shaver, P. R., & Pereg, D. (2003). Attachment theory and affect regulation: The dynamics, development, and cognitive consequences of attachment-related strategies. Motivation and Emotion, 27, 77–102. doi:10.1023/A:1024515519160

Petrocelli, J. V. (2003). Hierarchical multiple regression in counseling research: Common problems and possible remedies. Measurement and Evaluation in Counseling and Development, 36, 9–22.

Pfaller, J. E., & Kiselica, M. S. (1996). Implications of attachment theory for the role of school counselors. The School Counselor, 43, 208–217.

Scarborough, J. L. (2005). The School Counselor Activity Rating Scale: An instrument for gathering process data. Professional School Counseling, 8, 274–283.

Scarborough, J. L., & Culbreth, J. R. (2008). Examining discrepancies between actual and preferred practice of school counselors. Journal of Counseling & Development, 86, 446–459. doi:10.1002/j.1556-6678.2008.tb00533.x

Scarborough, J. L., & Luke, M. (2008). School counselors walking the walk and talking the talk: A grounded theory of effective program implementation. Professional School Counseling, 11, 404–416.

Shillingford, M. A., & Lambie, G. W. (2010). Contribution of professional school counselors’ values and leader-

ship practices to their programmatic service delivery. Professional School Counseling, 13, 208–217. doi:10.5330/PSC.n.2010-13.208

Sink, C. A., & Stroh, H. R. (2003). Raising achievement test scores of early elementary school students through comprehensive school counseling programs. Professional School Counseling, 6, 350–364.

Sink, C. A., & Yillik-Downer, A. (2001). School counselors’ perceptions of comprehensive guidance and counsel-ing programs: A national survey. Professional School Counseling, 4, 278–288.

Stajkovic, A., & Luthans, F. (1998). Self-efficacy and work-related performance: A meta-analysis. Psychological Bulletin, 124, 240–261. doi:10.1037/0033-2909.124.2.240

Sutton, J. M., Jr., & Fall, M. (1995). The relationship of school climate factors to counselor self-efficacy. Journal of Counseling & Development, 73, 331–336.

Vespia, K. M., Fitzpatrick, M. E., Fouad, N. A., Kantamneni, N., & Chen, Y.-L. (2010). Multicultural career counseling: A national survey of competencies and practices. The Career Development Quarterly59, 54–71. doi:10.1002/j.2161-0045.2010.tb00130.x

Wei, M., Russell, D. W., Mallinckrodt, B., & Vogel, D. L. (2007). The Experiences in Close Relationship Scale (ECR)-Short Form: Reliability, validity, and factor structure. Journal of Personality Assessment, 88, 187–204. doi:10.1080/00223890701268041

Whiston, S. C., Tai, W. L. , Rahardja, D., & Eder, K. C. (2011). School counseling outcome: A meta-analytic

examination of interventions. Journal of Counseling & Development, 89, 37–55.
doi:10.1002/j.1556-6678.2011.tb00059.x

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


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.

Examining the Practicum Experience to Increase Counseling Students’ Self-Efficacy

James Ikonomopoulos, Javier Cavazos Vela, Wayne D. Smith, Julia Dell’Aquila

Master’s level counseling programs accredited by the Council for Accreditation of Counseling and Related Education Programs (CACREP, 2016) require students to complete practicum and internship courses that involve group and individual or triadic supervision. Although clinical supervision provides students with effective skill development (Bernard & Goodyear, 2004), counseling students may begin practicum with low self-efficacy regarding their counseling abilities and skills. Given the importance of clinical supervision and counselor self-efficacy, it is surprising that there are limited studies that have examined the impact of supervision and practicum experience from the perspectives of supervisees. Almost all studies within this domain are qualitative and involve personal interviews with supervisees or supervisors (e.g., Hein & Lawson, 2008). In order to fill a gap in the literature and document the impact of the practicum experience, this study examined the effectiveness of the practicum experience encompassing direct counseling services, group supervision and triadic supervision to increase counseling students’ self-efficacy. First, we provide a literature review regarding group supervision, triadic supervision and counselor self-efficacy. Next, we present findings from a study with 11 counseling practicum students. Finally, we provide a discussion regarding the importance of these findings as well as implications for counseling practice and research.

 

Supervision in Counselor Education Coursework

CACREP requires an average of one and a half hours of weekly group supervision in practicum courses that involves an instructor with up to six counseling graduate students (Degges-White, Colon, & Borzumato-Gainey, 2012). Borders et al. (2012) identified that group supervisors use leadership skills, facilitate and monitor peer feedback, and encourage supervisees to take ownership of group process in group supervision. Borders and colleagues (2012) identified several benefits in group supervision, including exposure to multiple counselor styles and ability to learn about various educational issues. There also were challenges such as limited helpful feedback, brevity of case presentations, timing of group meetings and lack of educational opportunities. In another study, Conn, Roberts, and Powell (2009) compared hybrid and face-to-face supervision among school counseling interns. There were similarities in perceptions of quality of supervision, suggesting that distance learning can provide effective group supervision. CACREP counseling programs also require students to receive one hour of weekly supervision from a faculty member or doctoral student supervisor. Triadic is one form of supervision that involves a process whereby one supervisor meets and provides feedback with two supervisees (Hein & Lawson, 2008). Hein and Lawson (2008) explored supervisors’ perspectives on triadic supervision and found increased demands on the role of the supervisor. For example, supervisors felt additional pressure to support both supervisees in supervision. Additionally, Lawson, Hein, and Stuart (2009) investigated supervisees’ perspectives of triadic supervision. Noteworthy findings included: some students perceived less time and attention to their needs; importance of compatibility between supervisees; and careful attention must be given when communicating feedback, particularly if negative feedback must be given.

Finally, Borders et al. (2012) explored supervisors’ and supervisees’ perceptions of individual, triadic and group supervision. Benefits included vicarious learning experiences, peer-learning opportunities, and better supervisor feedback, while challenges included peer mismatch and difficulty keeping both supervisees involved.

 

Counselor Self-Efficacy

One of the most important outcome variables in counseling is self-efficacy. Bandura (1986) defined self-efficacy as individuals’ confidence in their ability to perform courses of action or achieve a desired outcome. Self-efficacy in counselor education settings might influence students’ thoughts, behaviors and feelings toward working with clients (Bandura, 1997). In the current study, counseling self-efficacy is defined as “one’s beliefs or judgments about his or her capabilities to effectively counsel a client in the near future” (Larson & Daniels, 1998, p. 1). Counselor self-efficacy also can refer to students’ confidence regarding handling the therapist role, managing counseling sessions and delivering helping skills (Lent et al., 2009). In higher education settings, researchers identified relationships between practicum students’ counseling self-efficacy and various client outcomes in counseling (Halverson, Miars, & Livneh, 2006). Self-efficacy also is positively related to performance attainment (Bandura, 1986), perseverance in counseling tasks, less anxiety (Larson & Daniels, 1998), positive client outcomes (Bakar, Zakaria, & Mohamed, 2011), and counseling skills development (Lent et al., 2009). Halverson et al. (2006) evaluated the impact of a CACREP program on counseling students’ conceptual level and self-efficacy. Longitudinal findings showed that counseling students’ perceptions of self-efficacy increased over the course of the program, primarily as a result of clinical experiences.

In another investigation, Greason and Cashwell (2009) examined mindfulness, empathy and self-efficacy among masters-level counseling interns and doctoral counseling students. Mindfulness, empathy and attention to meaning accounted for 34% of the variance in counseling students’ self-efficacy. Finally, Barbee, Scherer, and Combs (2003) investigated the relationship among prepracticum service learning, counselor self-efficacy and anxiety. Substantial counseling coursework and counseling-related work experiences were important influences on counseling students’ self-efficacy.

 

Purpose of Study

This study evaluated practicum experiences by using a single-case research design (SCRD) to measure the impact on students’ self-efficacy. In a recent special issue of the Journal of Counseling & Development, Lenz (2015) described how researchers and practitioners can use SCRDs to make inferences about the impact of treatment or experiences. SCRDs are appropriate for counselors or counselor educators for the following reasons: minimal sample size, self as control, flexibility and responsiveness, ease of data analysis, and type of data yielded from analyses. In the current study, the rationale for using an SCRD to examine the effectiveness of the practicum experience and triadic supervision was to provide counselor educators with insight regarding potential strategies that increase students’ self-efficacy. With this goal in mind, we implemented an SCRD (Lenz, Perepiczka, & Balkin, 2013; Lenz, Speciale, & Aguilar, 2012) to identify and explore trends of students’ changes in self-efficacy while completing their practicum experience. We addressed the following research question: to what extent does the practicum experience encompassing direct counseling services, group supervision and triadic supervision influence counseling graduate students’ self-efficacy?

 

Methodology

Instructors of record for three practicum courses formulated a plan to investigate the impact of the practicum experience on counseling students’ self-efficacy. We focused on providing students with a positive practicum experience with support, constructive feedback, wellness checks and learning experiences. With this goal in mind, we implemented a single case research design (Hinkle, 1992; Lenz et al., 2013; Lenz et al., 2012) to identify and explore trends of students’ changes in self-efficacy while completing their practicum experience. We selected this design to evaluate data that provides inferences regarding treatment effectiveness (Lenz et al., 2013). All practicum courses followed the same course requirements, and instructors shared the same level of teaching experience.

 

Participant Characteristics

We conducted this study with a sample of Mexican American counseling graduate students (N = 11) enrolled in a CACREP-accredited counseling program in the southwestern United States. This Hispanic Serving Institution had an enrollment of approximately 7,000 undergraduate and graduate students (approximately 93% of students at this institution are Latina/o) at the time of data collection. As a result, we were not surprised that all of the participants in the current study identified as Mexican American. Fifteen participants were solicited; four declined to participate. Participants (four men and seven women) ranged in age from 24 to 57 (M = 31; STD = 9.34). All participants were enrolled in practicum; we assigned participants with pseudonyms to protect their identity. Participants had diverse backgrounds in elementary education, secondary education, case management and behavioral intervention services. Participants also had aspirations of obtaining doctoral degrees or working in private practice, school settings, and community mental health agencies.

 

Instrumentation

     Counselor Activity Self-Efficacy Scale. The Counselor Activity Self-Efficacy Scale (CASES) is a self-report measure of counseling self-efficacy (Lent, Hill, & Hoffman, 2003). This scale consists of 31 items with a 10-point Likert-type scale in which respondents rate their level of confidence from 0 (i.e., having no confidence at all) to 9 (i.e., having complete confidence). Participants respond to items on exploration skills, session management and client distress (Lent et al., 2003), with higher scores reflective of higher levels of self-efficacy. The total score across these domains represents counseling self-efficacy. Reliability estimates range from .96 to .97 (Greason & Cashwell, 2009; Lent et al., 2003). We used the total score as the outcome variable in our study.

 

Treatment

Over the course of a 14-week semester, participants received 12 hours of triadic supervision and approximately 25 hours of group supervision. We followed Lawson, Hein, and Getz’s (2009) model through pre-session planning, in-session strategies, administrative considerations and evaluations of supervisees. During triadic supervision meetings with two practicum students, the instructor of record conducted wellness checks assessing students’ well-being and level of stress, listened to concerns about clients, observed recorded sessions, provided support and feedback, and encouraged supervisees to provide feedback. The instructor of record also facilitated group supervision discussions on clients’ presenting problems, treatment planning, note-writing, and wellness and self-care strategies. All practicum instructors collaborated and communicated bi-weekly to monitor students’ progress as well as students’ work with clients. All students obtained a minimum of 40 direct hours while working at their university counseling and training clinic, where services are provided to individuals with emotional, developmental, and interpersonal issues. Treatment for depression, anxiety and family issues are the most common issues. The population receiving services at this counseling and training clinic are mostly Mexican American and Spanish-speaking clients who are randomly assigned to a practicum student after an initial phone screening.

 

Procedure

We evaluated treatment effect using an AB SCRD (in our case, we referred to this more precisely as BT for baseline and treatment), using scores on the CASES as an outcome measure. During an orientation before the semester, practicum students were informed that their instructors were interested in evaluating changes in self-efficacy. Students who agreed to participate in the current study completed baseline measure one at this time. Following this, we selected a pseudonym to identify each participant when completing counselor self-efficacy activity (CSEA) scales throughout the study. The baseline phase consisted of data collection for 3 weeks before the practicum experience. The treatment phase began after the third baseline measure, when the first triadic supervision session was integrated into the practicum experience. Individual cases under investigation were practicum students who agreed to document their changes in self-efficacy while completing the practicum experience. Given that participants serve as their own control group in a single case design, the number of participants in the current study was considered sufficient to explore the research question (Lenz et al., 2013).

 

Data Collection and Analysis

We implemented an AB, SCRD (Lundervold & Belwood, 2000; Sharpley, 2007) by gathering weekly scores of the CASES. We did not use an ABA design with a withdrawal phase given that almost all students enrolled in internship immediately after the semester. As a result, we did not want to collect data that would have tapped into students’ internship experiences. After three weeks of data collection, the baseline phase of data collection was completed. The treatment phase began after the third baseline measure where the first triadic supervision session occurred. After the 13th week of data collection, the treatment phase of data collection was completed due to nearing completion of the semester, for a total of three baseline and ten treatment phase collections. We did not collect additional treatment data points given that students were scheduled to begin internship at the conclusion of the semester. We only wanted to measure the impact of the practicum experience.

Percentage of data points exceeding the median (PEM) procedure was implemented to analyze the quantitative data from the AB single case design (Ma, 2006). A visual trend analysis was reported as data points from each phase were graphically represented to provide visual representations of change over time (Ikonomopoulos, Smith, & Schmidt, 2015; Sharpley, 2007). An interpretation of effect sizes was conducted to determine the effectiveness of triadic supervision integrated into the practicum experience when comparing each phase of data collection (Sharpley, 2007). Interpreting effect sizes for the PEM procedure yields a proportion of data overlap between a baseline and treatment condition expressed in a decimal format that ranges from zero and one. Higher scores represent greater treatment effects while lower scores represent less effective treatments. This procedure is conceptualized as the analysis of treatment phase data that is contingent on the overlap with the median data point within the baseline phase. Ma (2006) suggested that PEM is based on the assumption that if the intervention is effective, data will be predominately on the therapeutic side of the median. If an intervention is ineffective, data points in the treatment phase will vacillate above and below the baseline median (Lenz, 2013). To calculate the PEM statistic, data points in the treatment phase on the therapeutic side of the baseline are counted and then divided by the total number of points in the treatment phase. Scruggs and Mastropieri (1998) suggested the following criteria for evaluation: effect sizes of .90 and greater are indicative of very effective treatments; those ranging from .70 to .89 represent moderate effectiveness; those between .50 to .69 are debatably effective; and scores less than .50 are regarded as not effective

 

Results

 

Figure 1 and Table 1 depict estimates of treatment effect using PEM across all participants. Detailed descriptions of participants’ experiences are provided below.

 

Participant 1

     Jorge’s ratings on the CASES illustrate that the practicum experience involving triadic supervision and group supervision was very effective for improving counselor self-efficacy. Before the treatment phase began, three of Jorge’s baseline measurements were above the cut-score guideline on the CASES with a total scale score of 123, which considers an individual to have low counseling self-efficacy for the CASES. Evaluation of the PEM statistic for the CASES (1.00) indicated that 10 scores were on the therapeutic side above the baseline (total scale score of 217). Scores above the PEM line were within a 122-point range. Trend analysis depicted a consistent level of improvement following the first treatment measure. The majority of improvement in confidence was found on items measuring exploration skills.

 

Participant 2

     Gina’s ratings on the CASES illustrate that the practicum experience involving triadic supervision and group supervision was moderately effective for improving counselor self-efficacy. Before the treatment phase began, three of Gina’s baseline measurements were above the cut-score guideline on the CASES with a total scale score of 123. Evaluation of the PEM statistic for the CASES (0.77) indicated that seven scores were on the therapeutic side above the baseline (total scale score of 194). Scores above the PEM line were within a 99-point range. Trend analysis depicted a consistent level of improvement following the second treatment measure. The majority of improvement in confidence was found on items measuring exploration skills, session management and client distress.

 

Participant 3

     Cecilia’s ratings on the CASES illustrate that the practicum experience and triadic supervision were very effective for improving counselor self-efficacy. Before the treatment phase began, three of Cecilia’s baseline measurements were above the cut-score guideline on the CASES with a total scale score of 123. Evaluation of the PEM statistic for the CASES (1.00) indicated that 10 scores were on the therapeutic side above the baseline (total scale score of 177). Scores above the PEM line were within a 162-point range. Trend analysis depicted a consistent level of improvement following the first treatment measure. The majority of improvement in confidence was found on items measuring exploration skills and session management.

 

 

Figure 1.

 

Graphical Representation of Ratings for Counselor Activity Self-Efficacy by Participants

 

 

Table 1

Participants’ Sessions and Their CASES Total Scale Score for Counselor Activity Self-Efficacy

 

Participant 4

     Natalia’s ratings on the CASES illustrate that the practicum experience and triadic supervision were very effective for improving her counselor self-efficacy. Before the treatment phase began, two of Natalia’s baseline measurements were above the cut-score guideline on the CASES with a total scale score of 123. Evaluation of the PEM statistic for the CASES (1.00) indicated that nine scores were on the therapeutic side above the baseline (total scale score of 138). Scores above the PEM line were within a 155-point range. Trend analysis depicted a consistent level of improvement following the first treatment measure. The majority of improvement in confidence was found on items measuring exploration skills.

 

Participant 5

     Yolanda’s ratings on the CASES illustrate that the practicum experience and triadic supervision were very effective for improving counselor self-efficacy. Before the treatment phase began, three of Yolanda’s baseline measurements were above the cut-score guideline on the CASES with a total scale score of 123. Evaluation of the PEM statistic for the CASES (0.90) indicated that nine scores were on the therapeutic side above the baseline (total scale score of 295). Scores above the PEM line were within a 27-point range. Trend analysis depicted a minimal level of improvement following the first treatment measure. The majority of improvement in confidence was found on items measuring exploration skills.

 

Participant 6

     Leticia’s ratings on the CASES illustrate that the practicum experience and triadic supervision were very effective for improving her counselor self-efficacy. Before the treatment phase began, three of Leticia’s baseline measurements were above the cut-score guideline on the CASES with a total scale score of 123. Evaluation of the PEM statistic for the CASES (1.00) indicated that 10 scores were on the therapeutic side above the baseline (total scale score of 293). Scores above the PEM line were within a 43-point range. Trend analysis depicted a consistent level of improvement following the first treatment measure. The majority of improvement in confidence was found on items measuring client distress.

 

Participant 7

     Robert’s ratings on the CASES illustrate that the practicum experience and triadic supervision were very effective for improving counselor self-efficacy. Before the treatment phase began, three of Robert’s baseline measurements were above the cut-score guideline on the CASES with a total scale score of 123. Evaluation of the PEM statistic for the CASES (1.00) indicated that 10 scores were on the therapeutic side above the baseline (total scale score of 197). Scores above the PEM line were within a 96-point range. Trend analysis depicted a consistent level of improvement following the first treatment measure. The majority of improvement in confidence was found on items measuring client distress.

 

Participant 8

   George’s ratings on the CASES illustrate that the practicum experience and triadic supervision were very effective for improving his counselor self-efficacy. Before the treatment phase began, three of George’s baseline measurements were above the cut-score guideline on the CASES with a total scale score of 123. Evaluation of the PEM statistic for the counselor activity self-efficacy measure (1.00) indicated that ten scores were on the therapeutic side above the baseline (total scale score of 300). Scores above the PEM line were within a 24-point range. Trend analysis depicted a consistent level of improvement following the first treatment measure. The majority of improvement in confidence was found on items measuring exploration skills.

Participant 9

     Jeremy’s ratings on the CASES illustrate that the practicum experience and triadic supervision were very effective for improving his counselor self-efficacy. Before the treatment phase began, two of Jeremy’s baseline measurements were above the cut-score guideline on the CASES with a total scale score of 123. Evaluation of the PEM statistic for the CASES (0.90) indicated that nine scores were on the therapeutic side above the baseline (total scale score of 142). Scores above the PEM line were within a 201-point range. Trend analysis depicted a consistent level of improvement following the second treatment measure. The majority of improvement in confidence was found on items measuring session management and client distress.

 

Participant 10

     Brittney’s ratings on the CASES illustrate that the practicum experience and triadic supervision were moderately effective for improving her counselor self-efficacy. Before the treatment phase began, three of Brittney’s baseline measurements were below the cut-score guideline on the CASES with a total scale score of 123. Evaluation of the PEM statistic for the CASES (0.88) indicated that eight scores were on the therapeutic side above the baseline (total scale score of 94). Scores above the PEM line were within a 132-point range. Trend analysis depicted a consistent level of improvement following the fourth treatment measure. The majority of improvement in confidence was found on items measuring session management.

 

Participant 11

     Jessica’s ratings on the CASES illustrate that the practicum experience and triadic supervision were very effective for improving her counselor self-efficacy. Before the treatment phase began, three of Jessica’s baseline measurements were above the cut-score guideline on the CASES with a total scale score of 123. Evaluation of the PEM statistic for the CASES (1.00) indicated that 10 scores were on the therapeutic side above the baseline (total scale score of 186). Scores above the PEM line were within a 71-point range. Trend analysis depicted a consistent level of improvement following the first treatment measure. The majority of improvement in confidence was found on items measuring exploration skills.

 

Discussion

The results of this study found that in all 11 investigated cases, the practicum experience ranged from moderately effective (PEM = .77) to very effective (PEM = 1.00) for improving or maintaining counselor self-efficacy during practicum coursework. For most participants, counseling self-efficacy continued to improve throughout the practicum experience as evidenced by high scores on items such as “Helping your client understand his or her thoughts, feelings and actions,” “Work effectively with a client who shows signs of severely disturbed thinking,” and “Help your client set realistic counseling goals.” Participants shared that the most helpful experiences during practicum to improve their counselor self-efficacy came from direct experiences with clients. This finding is consistent with Bandura’s (1977) conceptualization of direct mastery experiences where participants gain confidence with successful experiences of a particular activity. Participants also shared how obtaining feedback from clients on their outcomes and seeing their clients’ progress was important for their development as counselors. Other helpful experiences included processing counseling sessions with a peer during triadic supervision, and case conceptualization and treatment planning during group supervision. Obtaining feedback during triadic supervision from peers and instructors after observing recorded counseling sessions also was beneficial.

Qualitative benefits of supervision included vicarious learning experiences, peer-learning opportunities and better supervisor feedback (Borders et al., 2012). Findings from this study extend qualitative findings regarding benefits of the practicum experience and triadic supervision. The results of this study yielded promising findings related to the integration of triadic supervision into counseling graduate students’ practicum experiences. First, the practicum experience appeared to be effective for increasing and maintaining participant scores on the CSEA scale. Inspection of participant scores within treatment targets revealed that the practicum experience was very effective for nine participants and within the moderately effective range for two participants.

Lastly, informal conversations with participants indicate that triadic supervision provided participants with an opportunity to receive peer feedback. Participants also commented that weekly wellness checks were important due to stress from the practicum experience. Trends were observed for the group as a majority of participants improved self-efficacy consistently after their fourth treatment measure. In summary, direct services with clients, triadic supervision with a peer and group supervision as part of the practicum experience may assist counseling graduate students to improve self-efficacy.

 

Implications for Counseling Practice

There are several implications for practice. First, triadic supervision has been helpful when there is compatibility between supervisor and supervisees (Hein & Lawson, 2008). Compatibility between supervisees is helpful, as participants shared how having similar knowledge and experience contributed to their development. While all participants in the current study selected their partner for supervision, Hein and Lawson (2008) commented that the responsibility to implement and maintain clear and achievable support to supervisees lies heavily on supervisors. As a result, additional trainings should be offered to supervisors regarding clear, concise and supportive feedback. Such trainings and discussions can focus on clarity of roles and expectations for both supervisor and supervisee before triadic supervision begins. More training in providing feedback to peers in group supervision also can be beneficial as students learn to provide feedback to promote awareness of different learning experiences. We suggest that additional trainings will help practicum instructors and students identify ways to provide clear, constructive and effective feedback.

Practicum instructors can administer weekly or bi-weekly wellness checks and discuss responses on individual items on the Mental Well-Being Scale to monitor progress (Tennant et al., 2007). Additionally, counselor education programs would benefit from bringing self-efficacy to the forefront in the practicum experience as well as prepracticum coursework. Findings from the current study could be presented to students in group counseling and practicum coursework to facilitate discussion regarding how the practicum experience can increase students’ self-efficacy. Part of this discussion should focus on assessing baseline self-efficacy in order to help students increase perceptions of self-efficacy. As such, counselor educators can administer and interpret the CSEA scale with practicum students. There are numerous scale items (e.g., silence, immediacy) that can be used to foster discussions on perceived confidence in dealing with counseling-related issues. Finally, CACREP-accredited programs require 1 hour of weekly supervision and allow triadic supervision to fulfill this requirement. We recommend that CACREP and non-CACREP-accredited programs consider incorporating triadic supervision into the practicum experience and suggest that triadic supervision as part of the practicum experience might help students’ increase self-efficacy.

 

Implications for Counseling Research

The practicum experience seemed helpful for improving counseling students’ self-efficacy. However, information regarding reasons for this effectiveness of the practicum experience and triadic supervision was not explored. Qualitative research regarding the impact of the practicum experience on counselors’ self-efficacy can provide incredible insight into specific aspects of group or triadic supervision that increase self-efficacy. Second, more outcome-based research with ethnic minority counseling students is necessary. There might be aspects of group or triadic supervision that are conducive when working with Mexican American students (Cavazos, Alvarado, Rodriguez, & Iruegas, 2009). Third, exploring different models of group or triadic supervision to increase counseling self-efficacy is important. As one example, researchers could explore the impact of the Wellness Model of Supervision (Lenz & Smith, 2010) on counseling graduate students’ self-efficacy. Finally, all participants in our study attended a CACREP counseling program with mandatory individual or triadic supervision. Comparing changes in self-efficacy between students in CACREP and non-CACREP programs where weekly individual or triadic supervision outside of class is not mandatory would be important.

 

Limitations

There are several limitations that must be taken into consideration. First, we did not use an ABA design with withdrawal measures that would have provided stronger internal validity to evaluate changes to counselor self-efficacy (Lenz et al., 2012). Most practicum students in our study began internship immediately after the conclusion of the semester. As a result, collecting withdrawal measures in an ABA design would have tapped into students’ internship experiences. Second, although three baseline measurements are considered sufficient in single-case research (Lenz et al., 2012), employing five baseline measures might have allowed self-efficacy scores to stabilize prior to their practicum experience (Ikonomopoulos et al., 2015).

 

Conclusion

Based on results from this study, the practicum experience shows promise as an effective strategy to increase counseling graduate students’ self-efficacy. Implementing triadic supervision as part of the practicum experience for counseling students is a strategy that counselor education programs might consider. Provided are guidelines for counselor educators to consider when integrating triadic supervision into the practicum experience. Researchers also can use different methodologies to address how different aspects of the practicum experience influence counseling students’ self-efficacy. In summary, we regard the practicum experience with triadic supervision as a promising approach for improving counseling graduate students’ self-efficacy.

 

Conflict of Interest and Funding Disclosure

The authors reported no conflict of interest

or funding contributions for the development

of this manuscript.

 

References

Bakar, A. R., Zakaria, N. S., & Mohamed, S. (2011). Malaysian counselors’ self-efficacy: Implication for career counseling. The International Journal of Business and Management, 6, 141–147. doi:10.5539/ijbm.v6n9p141

Bandura, A. (1977). Toward a unifying theory of behavioral change. Psychological Review, 84, 191–215.

Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice Hall.

Bandura, A. (1997). Self-efficacy: The exercise of control. New York, NY: Freeman.

Barbee, P. W., Scherer, D., & Combs, D. C. (2003). Prepracticum service-learning: Examining the relationship with counselor self-efficacy and anxiety. Counselor Education and Supervision, 43, 108–120.

Bernard, J. M., & Goodyear, R. K. (2004). Fundamentals of clinical supervision (3rd ed.). Needham Heights, MA: Allyn & Bacon.

Borders, L. D. (2014). Best practices in clinical supervision: Another step in delineating effective supervision practice. American Journal of Psychotherapy, 68, 151–162.

Borders, L. D., Welfare, L. E., Greason P. B., Paladino, D. A., Mobley, A. K., Villalba, J. A., & Wester, K. L. (2012). Individual and triadic and group: Supervisee and supervisor perceptions of each modality. Counselor Education and Supervision, 51, 281–295.

Cavazos, J., Alvarado, V., Rodriguez, I., & Iruegas, J. R. (2009). Examining Hispanic counseling students’             worries: A qualitative approach. Journal of School Counseling, 7, 1–22.

Conn, S. R., Roberts, R. L., & Powell, B. M. (2009). Attitudes and satisfaction with a hybrid model of counseling supervision. Educational Technology and Society, 12, 298–306.

Council for Accreditation of Counseling and Related Educational Programs. (2016). 2016 CACREP standards. Retrieved from http://www.cacrep.org/wp-content/uploads/2016/02/2016-Standards-with-Glossary-rev-2.2016.pdf

Degges-White, S., Colon, B. R., & Borzumato-Gainey, C. (2013). Counseling supervision within a feminist framework: Guidelines for intervention. Journal of Humanistic Counseling, 52, 92–105.
doi:10.1002/j.2161-1939.2013.00035.x

Greason, P. B., & Cashwell, C. S. (2009). Mindfulness and counseling self-efficacy: The mediating role of attention and empathy. Counselor Education and Supervision, 49, 2–19.

Halverson, S. E., Miars, R. D., & Livneh, H. (2006). An exploratory study of counselor education students’ moral reasoning, conceptual level, and counselor self-efficacy. Counseling and Clinical Psychology Journal, 3, 17–30.

Hein, S., & Lawson, G. (2008). Triadic supervision and its impact on the role of the supervisor: A qualitative examination of supervisors’ perspectives. Counselor Education and Supervision, 48, 16–31.

Hinkle, J. S. (1992). Computer-assisted career guidance and single-subject research: A scientist-practitioner approach to accountability. Journal of Counseling & Development, 70, 391–395.

Ikonomopoulos, J., Smith, R. L., & Schmidt, C. (2015). Integrating narrative therapy within rehabilitative programming for incarcerated adolescents. Journal of Counseling & Development, 93, 460–470. doi:10.1002/j.1556-6676.2014.00000.x

Larson, L. M., & Daniels, J. A. (1998). Review of the counseling self-efficacy literature. The Counseling Psychologist, 26, 179–218.

Lawson, G., Hein, S. F., & Getz, H. (2009). A model for using triadic supervision in counselor education preparation programs. Counselor Education and Supervision, 48, 257–270.

Lawson, G., Hein, S. F., & Stuart, C. L. (2009). A qualitative investigation of supervisees’ experiences of triadic supervision. Journal of Counseling & Development, 87, 449–457.

Lent, R. W., Cinamon, R. G., Bryan, N. A., Jezzi, M. M., Martin, H. M., & Lim, R. (2009). Perceived sources of changes in trainees’ self-efficacy beliefs. Psychotherapy: Theory, Research, Practice, Training, 46, 317–327. doi:10.1037/a0017029

Lent, R. W., Hill, E., & Hoffman, M. A. (2003). Development and validation of the counselor activity self-efficacy scales. Journal of Counseling Psychology, 50, 97–108.

Lenz, A. S. (2013). Calculating effect size in single-case research: A comparison of nonoverlap methods. Measurement and Evaluation in Counseling and Development, 46, 64–73.

Lenz, A. S. (2015). Special issue editor’s introduction: Using single-case research designs to demonstrate evidence for counseling practices. Journal of Counseling & Development, 93, 387–393.
doi:10.1002/jcad.12036

Lenz, A. S., Perepiczka, M., & Balkin, R. S. (2013). Evidence of the mitigating effects of a support group for attitude toward statistics. Counseling Outcome Research & Evaluation, 4, 26–40. doi:10.1177/2150137812474000

Lenz, A. S., & Smith, R. L. (2010). Integrating wellness concepts within a clinical supervision model. The Clinical Supervisor, 29, 228–245. doi:10.1080/07325223.2020.518511

Lenz, A. S., Speciale, M., & Aguilar, J. V. (2012). Relational-cultural therapy intervention with incarcerated adolescents: A single-case effectiveness design. Counseling Outcome Research & Evaluation, 3, 17–29. doi:10.1177/2150137811435233

Lundervold, D. A., & Belwood, M. F. (2000). The best kept secret in counseling: Single-case (N = 1) experimental designs. Journal of Counseling & Development, 78, 92–102.

Ma, H. H. (2006). An alternative method for quantitative synthesis of single-subject researches: Percentage of                     data points exceeding the median. Behavior Modification, 30, 598–617.

Scruggs, T. E., & Mastropieri, M. A. (1998). Summarizing single-subject research: Issues and applications. Behavior Modification, 22, 221–242.

Sharpley, C. F. (2007). So why aren’t counselors reporting n = 1 research designs? Journal of Counseling & Development, 85, 349–356.

Tennant, R., Hiller, L., Fishwick, R., Platt, S., Joseph, S., Weich, S., . . . Stewart-Brown, S. (2007). The Warwick-Edinburgh Mental Well-being Scale (WEMWBS): Development and UK validation. Health & Quality of Life

Outcomes, 5, 63. doi:10.1186/1477-7525-5-63

 

James Ikonomopoulos, NCC, is an Assistant Professor at the University of Texas Rio Grande Valley. Javier Cavazos Vela is an LPC-Intern at the University of Texas Rio Grande Valley. Wayne D. Smith is an Assistant Professor at the University of Houston–Victoria. Julia Dell’Aquila is a graduate student at the University of Texas Rio Grande Valley. Correspondence concerning this article can be addressed to James Ikonomopoulos, University of Texas Rio Grande Valley, Department of Counseling, Main 2.200F, One West Univ. Blvd., Brownsville, TX 78520, james.ikonomopoulos@utrgv.edu.

Dig to Live: An Investigation of the Psychological Well-Being of Women Miners in Davao Oriental, Southeastern Philippines

Rose Anelyn Visaya-Ceniza

This study aimed to determine the psychosocial health status of women artisanal miners in the Philippines. Their socio-demographic characteristics and psychosocial health status are described to formulate a self-efficacy enhancement program to respond to their needs. This study utilized a descriptive multiple case study design. Primary data were gathered via a simple questionnaire regarding the respondents’ socio-demographic profile and psychosocial health status. Other primary data sources included key informant interviews, respondents’ journal entries, observations and outputs during the structured learning exercises, focus group discussion transcripts, and a researcher’s log. Documentary reviews also were utilized to obtain additional facts. The respondents were selected through a fishbowl method. Results show that the participants’ coping process, attitude of perseverance and stress management have a moderate impact on their ability to manage life experiences. The study resulted in a proposal for a self-efficacy enhancement program to improve the psychosocial health of women artisanal miners.

Keywords: women miners, psychosocial health, coping process, stress management, self-efficacy

 

In March 2008, the theme “Babae, Yaman Ka Ng Bayan” [Woman, You Are a Treasure of the Nation], emphasizing the worth of women in nation building, was bannered to celebrate Women’s Month in the Philippines. In Barangay Puntalinao, Banaybanay, Davao Oriental, Philippines, active artisanal and small-scale magnesite mining activities are visible to the community and visitors. Banaybanay is the last municipality of Davao Oriental, bordering the municipality of the Pantukan, Compostela Valley Province. Women join men at tilling and extracting minerals from steep mountains. This site was visited in October 2007 for an environmental scanning and initial investigation. The idea of conducting a study was discussed with the artisanal miners and they showed interest in the benefits of the study.

The southern part of Mindanao is rich in mineral resources. Nickel reserves are worth $215 billion (USD), copper reserves are worth $6.49 billion and gold reserves are worth $2.01 billion. Mindanao accounts for 48% of the country’s gold and 83% of the nickel reserves. According to Ambassador Li Jinjun, investors believe that the mining industry is the “ace” of Mindanao. In agreement, former resident of the Republic and current congresswoman of the province of Pampanga, the Honorable Gloria Macapagal Arroyo has made the revival of the mining industry one of her key tools in sustaining the country’s economic growth (Bautista, 2005).

According to the United Nations Development Program (1999), women involved in mining are more likely to be family-centered than men and spend their earnings on food, clothing, education and agriculture. In the Philippines, women artisanal miners’ daily routine involves direct exposure to sunlight, climbing difficult mountains, tilling and extracting minerals, and carrying heavy sacks of rocks, in addition to household chores and family obligations after work. Moreover, some women are undergoing the physiological discomforts of menopause.

In a focus group discussion (FGD) on perseverance, the women artisanal miners reported that they can bear the heat of the sun, the hazards at work and the workload at home in order to preserve their families and provide what is needed. Their husbands’ incomes are not enough for their families’ basic needs, typical of the life conditions of the rural poor in the Philippines. According to the Barangay Captain [Puntalinao community leader], these women persist at low-paying quarrying activities to subsist. Women artisanal miners manifest the spirit to persevere in life through their backbreaking work hours. This labor includes quarrying the rocks with a hammer and wedge, hitting the rocks in succession to break them into small pieces, packing them in a sack (which generally weighs no less than 110 pounds), and carrying the sacks to the buyer’s loading area. Workers aim to fill 25 sacks per day on average, which are sold to a local buyer for 10 pesos each in order to sustain daily family needs.

According to Greenspan (1992), households ideally spend up to 10% of total income to raise one child, 18% for two children and 26% for four children. Since many families lack the resources to raise children, the per-child share drops dramatically with each child. A household with four children spends 25% less per child than a household with two children. This information suggests that the sufficiency of the family economy depends on the number of children in the household, and thus establishes the need to work harder to ensure family survival as the number of children in the family increases. It is not surprising to find an extended family system among Filipino families (Mercado, 1974) and to see children helping their parents at income-generating endeavors.

The miners’ common statement, “Maayo na lang ning pagpamato, bisan ginagmay kaysa wala jud sapi” [Even if mining gives us insufficient income, it is better than having nothing at all], reveals the working poor perspective that is important in considering ways to improve the miners’ psychosocial well-being. These women, ranging from young adults to elders, are vulnerable to stress; their self-efficacy is a powerful personal resource in the coping process (see Lazarus & Folkman, 1987).

While studies have explored the experiences of miners, these studies have failed to grasp fully the psychosocial health situation of women artisanal miners in Philippine rural communities. Since mining is a major contributor to the country’s economy, artisanal mining is expected to spread soon to other rural communities. Therefore, the experiences of community women require attention in order to better anticipate their emerging psychosocial health issues. The theoretical frameworks utilized in developing this study included Erikson’s (1963) psychosocial development theory, which posits that each person experiences psychosocial crises or internal conflicts linked to life’s key stages, which define growth and personality. Social-cognitive and self-efficacy theory (Bandura, 1992, 1997), defined as beliefs about one’s capabilities to produce levels of performance that influence one’s life, also was utilized to formulate this study.

 

Method

The author utilized a descriptive multiple case study design. Primary data were gathered using a researcher-constructed questionnaire that investigated each respondent’s socio-economic profile and psychosocial health status. Other primary data sources included key informant interviews, respondents’ journal entries, observations and outputs during the structured learning exercises (SLEs), FGD transcripts, and the researcher’s log. Documents provided by the barangay [community] secretary also were reviewed.

Participants

Twenty-six women ages 26–70 volunteered. Eight were between 35 and 43 years old and eight were within the ages of 53–61. Five of the respondents were between ages 44 and 52 and two respondents were 26–34 years old. The artisanal miners participating in the study were identified from the barangay list and via the assistance of the barangay secretary. Based on the socio-demographic data drawn from the selected women miners of Barangay Puntalinao, Banaybanay, Davao Oriental, the respondents generally belonged among the rural poor migrant settlers and had low levels of educational attainment. Most participants were mothers responsible for large families and obliged to participate in mining to sustain daily family needs. Most participants owned their homes; however, the houses were located on rental lots, causing some degree of insecurity in terms of permanence of residence.

Data Sources

A 21-item survey, translated from English to Cebuano, provided a socio-demographic profile and psychosocial health status of each respondent, covering perseverance, stress management and coping processes. It was clustered into three areas: personal data, family structure and housing arrangement. Items 1–6 aimed to determine level of perseverance. Items 7–16 covered the impact of stress management styles, and items 17–21 determined the impact of coping processes on managing life circumstances. Responses were tallied using the following scale: 1.00–1.99 indicating that the given life experience had a high impact on psychosocial health status over the past month, 2.00–2.99 indicating moderate impact on psychosocial health and 3.00–4.00 indicating low impact.

Other primary sources of data included key informant interviews, respondents’ journal entries, observations and outputs during SLEs, transcripts from the FGD, and the researcher’s observation logs from her 3-day community immersion. The key informants included the Barangay Captain, the Barangay Health Worker and a sari-sari [small grocery] store owner, all of whom were interviewed during the researcher’s community immersion. A formal approval to conduct a study in the area was requested from the Barangay Captain. The Barangay Health Worker was interviewed about health conditions among the women miners and the barangay’s health programs for women. An interview also was conducted with a sari-sari store owner who had firsthand knowledge of the women residents’ consumer behavior and lived in a house located at the mining compound. Daily logs recorded what was witnessed and experienced during the immersion. The Barangay Puntalinao Development Plan (2000) also was used to gather basic community information such as the history, demography and topography of the barangay.

SLEs were conducted after the baseline data on psychosocial health status were obtained. The SLEs focused on coping processes, perseverance and stress management. During each SLE, a lecture was conducted and an assignment given for follow-up discussion with the group before the activity concluded. Outputs from the SLEs formed part of the data for the multiple case studies. A FGD with 14 randomly selected miners was conducted after the last SLE, focusing on coping processes, stress management and perseverance. Outputs from the FGD were utilized to validate and expand on the data extracted from the survey questionnaires and SLEs. The psychosocial health status of the respondents was monitored three months after the conclusion of the last SLEs. It provided feedback on the sessions’ lasting effects on the psychosocial health management of the respondents, despite the assessment of medium-term effectiveness, not included in the objectives of the study.

 

Results

Socio-Demographic Profile and Psychosocial Health Status

The general conditions of poverty resulted in multiple burdens, including reproduction. The high numbers of respondents’ children may have indicated that respondents spent much of their childbearing years within marriage. Six of the artisanal miners had four offspring. One of the respondents had nine and another had 14 children. Eighteen miners had children aged at least 22 years old. Three respondents had children 1 year old or younger, which suggests that more time and effort were needed to exert in mining to provide the needs of these children in the early stages of human development. Aside from economic needs, data implied that the women miners lived with their husbands and managed time for child care, despite long days at the mines.

Coping processes. The results showed that Filipino women artisanal miners’ coping processes had a moderate impact on recent life experiences for which they employed these coping strategies. The respondents had the ability to handle different trials in life, but the ability to use common coping strategies had a fair influence on being able to manage life circumstances well. It was evident from the women’s disclosures that multiple workloads consumed their being. However, the coping processes they employed had a low impact on solving family problems.

“Lisod kaayo ang among kahimtang labi na og mag-abot ang mga problema sa pamilya” [Our situation is very difficult most especially when the entire family encounters problems at the same time]. Because the women miners were responsible and accountable for problems encountered by the entire family, they became concerned when the family experienced difficulty. This finding was similar to findings from the United Nations Development Program (1999), which reported that women were more likely than men to devote resources for family upkeep, food and children’s education. Furthermore, prioritizing the needs of the family demonstrates adherence to the traditional Filipino value of kagandahang loob [compassion] (Miranda, 1992).

Among the 14 respondents who participated in the SLEs, coping behavior was utilized regarding problematic circumstances with their husbands’ vices and behaviors such as drinking, infidelity, physical abuse and financial neglect. Marital cases brought to the barangay office are usually reconciled through forgiveness and for economic reasons. Problems related to their children included participants’ daily absence from home, no contact while away from their children, early marriage and inability to support their children. According to the key informant, mining is considered a survival strategy despite its health risks, low compensation and daily starting time, as early as 5:00 a.m. (see Table 1).

According to one informant, a Barangay Health Worker who happened to be a neighbor of the miners, the miners often channeled time and effort into their mining in order to regain a sense of self-worth and focus on caring for their families, despite health risks and low compensation. During the FGD, the women miners mentioned using prayer as a coping strategy. Some Filipino women miners join religious organizations in order to express their feelings with fellow members. Miners’ journal entries indicated that they believed their present situation was their destiny.

 

Table 1

Psychosocial Health of Women Artisanal Miners at Barangay Puntalinao, Davao Oriental in Terms of Coping Processes

Coping Processes Indicator

M

SD

Description

Coping strategies employed

2.71

 .65

MI

Conflicts with in-laws or household members

1.84

1.01

HI

Conflicts with immediate family members

2.23

1.03

MI

Conflicts with friends

1.42

 .58

HI

Being taken advantage of

2.58

1.27

MI

Lots of responsibilities

3.69

  .62

LI

Note. LI = low impact, MI = moderate impact, HI = high impact.

 

Perseverance. The women miners’ attitude of perseverance had a high impact on their effective socializing with their neighbors. During FGDs, participants shared that the community had not encountered cultural problems because of respect for one another; in addition, most participants belonged to the Cebuano tribe. Based on the observation log, the women artisanal miners cared for each other and showed respect to everyone by treating each other without bias. Jocano (1999) wrote that the Filipino value delicadeza [being proper], is manifested, for instance, when one does not abuse a friendship by doing something that would be hurtful or embarrassing to a friend. This value is apparent in the practice of sabot that allows women to express and meet their needs for help without sacrificing their pride and dignity. Enriquez (1978) discussed kapwa as a mode of Filipino social interaction which he defined as “recognition of shared identities as well as the compassionate generosity to others in need.”

Based on the statement of the sari-sari store owner who was a neighbor of the respondents, the women miners usually incurred credit for food to be paid the following day. This practice of sabot [agreement] maintains social relations based on asal [consideration] as discussed by Jocano (1999) and kagandahang loob [compassion] as depicted by Miranda (1992). The moral undertone of these terms is best expressed by the Filipino concept of pakikiramay, or going out of one’s way in order to share the sorrow of others in times of crisis (Miranda, 1992). The practice of sabot, therefore, addresses the survival needs of the women in a manner that does not compromise their self-esteem, kindness and generosity.

It is evident that the women artisanal miners are insecure in terms of their housing, because most of their homes are built on property owned by other people. The participants’ attitude of perseverance had a moderate impact on dealing with the knowledge that the lot their houses were on could be revoked at any time. At the time the study was conducted, most of the houses had to be relocated to accommodate a road-widening project by the provincial government. Houses were uprooted and moved at least 10 meters from the road, causing the miners uncertainty about where to locate, or how far a potential relocation might be from the workplace.

Individual case studies showed that the women artisanal miners performed multiple roles including mother, wife, grandmother and household manager, as well as miner. Since these women were willing to sacrifice for their family, it was important for them to nurture their attitude to persist. Though they had the determination to continue with their various roles, they also needed to recharge from time to time. Their ability to manage the toll of their physical and psychological loads led them to a greater sense of self-efficacy. Such a sense allowed them to select challenging settings, explore their environments or create new ones (see Table 2).

 

Table 2

Psychosocial Health of Women Artisanal Miners at Barangay Puntalinao, Davao Oriental in Terms of Perseverance

Perseverance Indicator

M

SD

Description

Perseverance

2.88

.46

MI

Having your contributions overlooked

2.62

.85

MI

Hard work to look after and maintain house

3.70

.55

LI

Gossip about yourself

2.42

1.14

MI

Findings your work too demanding

3.88

   .59

LI

Financial conflicts with family members

2.31

1.29

MI

Feeling alone

2.85

   .97

MI

Experiencing high levels of heat

3.85

   .61

LI

Ethnic or tribal conflict

1.62

  .70

HI

Dissatisfaction with your physical fitness

1.85

1.12

HI

Dissatisfaction with your physical appearance

1.81

  .81

HI

Disqualifying positives

2.00

1.06

MI

Disliking your daily activities

2.85

1.05

MI

Note. LI = low impact, MI = moderate impact, HI = high impact.

 

Stress management. The women miners’ stress management styles had a moderate impact on their management of the stressors they encountered. Thus, there was room for improvement in their repertoire of stress management techniques to help prevent exhaustion or burnout. The data, moreover, showed that the miners did not harbor insecurities regarding their physical appearance and fitness. In addition, because of the forgiving attitude of the participants, violent family conflicts were avoided and rarely compounded their difficulties. Instead of borrowing trouble, the women generally opted to forgive.

Data showed that the stress management styles of the women miners had high impact with regard to viewing the future and remaining optimistic and hopeful. As for techniques employed, one participant stated that watching teleseryes, or television series, was a common means of relaxation among the women in the community. Women often finished doing household chores in the evening and watched television. Based on the study log, the miners and their children and grandchildren typically gathered inside the house around 7:30 p.m. to watch television. Teleseryes provided a medium for sympathetic catharsis. For instance, when the women witnessed someone’s misfortune, they compared it with their own and felt better afterward. When they viewed someone being oppressed on television, they tended to feel better about their own situation. When the oppressed character fought back, the viewer identified with the character’s desire to oppose malevolent forces. More importantly, sympathetic catharsis brought stress to a manageable level (see Table 3).

 

Table 3

Psychosocial Health of Women Artisanal Miners at Barangay Puntalinao, Davao Oriental in Terms of Stress Management

Stress Management Indicator

M

SD

Description

Stress management techniques

2.54

 .45

MI

Unsatisfactory housing and conditions

2.35

.85

MI

Trying to secure loans

3.08

1.16

LI

Too many things to do at once

3.52

 .64

LI

Take on the burdens of the entire family

3.70

.79

LI

Note. LI = low impact, MI = moderate impact, HI = high impact.

 

The Barangay Health Worker who was interviewed for the study happened to own a karaoke machine and stated that the women miners sometimes came over and sang whenever they had extra money (each song costs one peso on the videoke machine).These were occasions for the miners to bond and socialize as they sang, danced and laughed. During the FGD on stress management, it was mentioned that playing bingo also was one of the miners’ common pastimes, providing another social activity and an opportunity to connect with others and meet a very basic human need for the women.

Based on the survey of psychosocial health status, stress management strategies had a low impact on addressing stressful daily activities. According to one participant, “Usahay kapuyon ko og makabati og sakit sa lawas tungod kay dili lalim ang akong trabaho” [I get tired sometimes and do not feel good physically because my work is not that easy].


Discussion

The participants in this study indicated a need to enhance their coping strategies to cope with adversities in their lives. While they have the fighting spirit, their coping strategies could be improved further. A sense of self-worth must be further developed for the participants to be aware of their respective capabilities to exercise control over stressful situations. If this need was met further and more positive self-efficacy achieved, the miners would be better able to enhance their psychosocial health status.

Most of the women artisanal miners married at an early age and were financially unable to finish school. They were driven to engage in mining for many years to sustain the basic needs of their families. Most of the respondents have husbands and children who mine as well. More often than not, children are forced to discontinue school and begin work to help support the family. Despite being poor, the women have not surrendered to the trials of life, holding on to aspirations and possessing the following self-related cognition: “I can do it.” This attitude allows them to overcome the lack of opportunities by mining as a way to earn income and sustain the needs of their families.

Mining is perceived as God-sent and affords the women an opportunity to be self-reliant and gain a measure of control over their daily experience. Most of the respondents have persevered for the sake of their children and grandchildren. In addition to their labor, physical and emotional abuse from their husbands increases their suffering; yet they tend to be forgiving. Coleman (1998) advocated the therapeutic value of forgiveness as follows: “Forgiveness is a must in any family problem where there has been deep hurt, betrayal, or disloyalty” (p. 78). If there can be no reconciliation, forgiveness is the process that enables the forgiver to move on with life unencumbered with the pain of betrayal. Madanes (1991) further asserted, “The only way we can survive from day to day without emotional breakdown is by forgiving and forgetting” (p. 416). This study did not explore why the women miners forgive the wrongs done to them. It was found, however, that the women tend to forgive their husbands, although some still nurse hurts and resentment.

For the women, mining plays a major role in survival. The activity is described as a means of livelihood, a family bonding activity and source of hope for life. Furthermore, it also is seen as a chance to establish good relationships with colleagues, or pakikipagkapwa, and to enjoy work despite discomfort and hard work.

Most participants aim to build a semi-concrete house with comfortable rooms in a lot that they would own. In addition, the security of their residence is questionable when affected by the road-widening project of the provincial government. Still, the respondents expressed optimism as symbolized by the blooming flowers and abundant trees in their drawings (their output during their SLE), depicting joy and love in their households (see Appendix for an example).

Women artisanal miners in the Philippines would benefit from learning strategies to effectively address problems they encounter. They need to develop a sense of personal efficacy for approaching threatening situations with assurance that they can exercise control over these threats. The miners are hopeful and optimistic; therefore, it would be worthwhile to engage them cognitively and affectively and to facilitate decision-making that would allow them to gain insight into how to better manage resources and improve psychosocial health.

 

Implications

Given the socio-demographic characteristics, as well as the presentation of different life experiences, aspirations and psychosocial health status of the women artisanal miners, this study discovered that the miners would benefit from an intervention that revitalizes them, despite day-to-day stressors. Although the women are able to cope with various life difficulties, there is a need to enhance their coping strategies for managing stress. The miners should be more aware of their capabilities to exercise control over their own functioning and over the events that affect their lives, and thereby develop a stronger sense of personal efficacy. If these needs are met and self-efficacy achieved, the women miners will be able to enhance their psychosocial health status.

Optimism is commonly manifested in the stories told by the women artisanal miners. According to Bandura (1992), people with high assurance of their own capabilities approach difficult tasks as challenges to be mastered rather than threats to be avoided. Such an efficacious outlook fosters interest and engrossment in activities. A person who believes in being able to cause events can conduct a more active and self-determined life course. This can-do cognition mirrors a sense of control over one’s environment, and reflects the belief of being able to master challenging demands by means of adaptive action. This attitude also can be regarded as an optimistic view of one’s capacity to deal with stress (Bandura, 1992; Maddux,  1995; Wallston, 1994). This study reveals the importance of helping women miners enhance self-efficacy to maintain psychosocial health.

After the exploration of the women miners’ psychosocial health status, the researcher discovered that the miners need an intervention in order to be revitalized despite the various obstacles they encounter from day to day. They need training on how to maintain a positive outlook on life and how to believe in their potential to endure as a mother, wife, grandmother and daughter, as well as person. Considering the lifestyle and psychosocial health status of the women miners in terms of perseverance, coping processes and stress management, the self-efficacy enhancement program focuses on effective ways of creating a strong sense of efficacy among the miners in order to sustain the perseverance needed to succeed.

 

Conclusion

The stories of the women artisanal miners suggest that their coping processes, attitude of perseverance and stress management strategies have a moderate impact on their ability to manage their respective life experiences. As the 14 individual case studies were examined further for their psychosocial health status, the author found that most of the women artisanal miners face economic crises as well as maternal and marital problems. Despite these challenges, they manifest a forgiving attitude, which reflects the notion that such sacrifice is necessary for the sake of the family’s survival.

The miners also are optimistic about the future, an attitude that was manifested during the sharing of their aspirations in life through drawings. All participants mentioned positive life visions and goals. Flowers and trees were commonly drawn, which symbolized the participants’ desires to have happy and harmonious families. Children wearing togas and parents pinning ribbons on a graduation day also depict the participants’ yearning for the education and advancement of the next generation. Semi-concrete houses with comfortable rooms are illustrated to show longing for comfort and security in living conditions. All these aspects of the drawings (see Appendix) demonstrate that the women artisanal miners have plans and hopes in life that give them the determination to persist. Optimistic processes are an essential key to gaining a sense of self-efficacy.

The women miners possess the optimistic attitude to carry on, but there is room for them to discover more about how to control their functioning and manage their psychosocial health status more effectively. Therefore, it is necessary to help them enhance their coping strategies and stress management techniques.

 

Conflict of Interest and Funding Disclosure

The authors reported no conflict of  interest or funding contributions for the development of this manuscript.

 

References

Bandura, A. (1992). Self-efficacy mechanism in psychobiologic functioning. In R. Schwarzer (Ed.), Self-Efficacy: Thought control of action (pp. 355–394). Washington, DC: Hemisphere.

Bandura, A. (1997). Self-efficacy and health behaviour. In A. Baum, S. Newman, J. Weinman, R. West, & C. McManus (Eds.), Cambridge handbook of psychology, health and medicine (pp. 160–162). Cambridge, England: Cambridge University Press.

Barangay Puntalinao Development Plan. (2000). Davao City, Philippines

Bautista, R. (2005, February 2). Revival of the mining industry. Philippine Daily Inquirer.

Coleman, P. W. (1998). The process of forgiveness in marriage and the family. In R. D. Enright & J. North (Eds.), Exploring forgiveness (pp. 75–94). Madison, WI: University of Wisconsin Press.

Enriquez, V. G. (1978). Kapwa: A core concept of Filipino social psychology. Philippine Social Sciences and Hummanities Review, 42,100–108

Erikson, E. H. (1963). Childhood and society (2nd ed.). New York, NY: Norton.

Greenspan, A. (1992). Poverty in the Philippines: The impact on family size. Asia-Pacific Population & Policy, 21, 1-4

Jocano, F. L. (1999). Filipino value system: A cultural definition. Quezon City, Philippines: Punlad Research House.

Madanes, C. (1991). Sex, love, and violence: Strategies for transformation. New York, NY: W. W. Norton.

Maddux, J. E. (Ed.). (1995). Self-efficacy, adaptation, and adjustment: Theory, research, and application. New York, NY: Plenum.

Mercado, L. N. (1974). Elements of Filipino philosophy. Tacloban City: Divine Word.

Miranda, D. M. (1992). Buting pinoy: Probe essays on value as Filipino. Manila, Philippines: Divine Word..

United Nations Development Program. (1999). Human development report. Retrieved from http://hdr.undp.org/sites/default/files/reports/260/hdr_1999_en_nostats.pdf

Wallston, K. A. (1994). Theoretically based strategies for health behavior change. In M. P. O’Donnell & J. S. Harris (Eds.), Health promotion in the workplace (2nd ed., pp. 185–203). Albany, NY: Delmar.

 

Appendix 

A Miner’s Drawing of Life Aspirations 

Rose Anelyn Visaya-Ceniza is the Head of the Guidance Counseling and Testing Center of the Davao Oriental State College of Science and Technology, Guang-Guang, Dahican, and a practicing psychologist at St. Camillus Hospital of Mati, Inc. Correspondence can be addressed to Rose Anelyn Visaya-Ceniza, DOSCST, Dahican, 8200 Mati City, Davao Oriental, Philippines, roseanelyn@yahoo.com.

The author previously published portions of this article: “An Exploration of the Psychosocial Health Status of Women Artisanal Miners in Mindanao, Philippines” in Procedia: Social and Behavioral Sciences, 91, 505–514.

Development of Counseling Students’ Self-Efficacy During Preparation and Training

Patrick R. Mullen, Olivia Uwamahoro, Ashley J. Blount, Glenn W. Lambie

Counselor preparation is multifaceted and involves developing trainees’ clinical knowledge, skills and competence. Furthermore, counselor self-efficacy is a relevant developmental consideration in the counseling field. Therefore, the purpose of this longitudinal investigation was to examine the effects of a counselor preparation program on students’ development of counseling self-efficacy. The Counselor Self-Efficacy Scale was administered to 179 master’s-level counselors-in-training at three points in their counselor training and coursework, including new student orientation, clinical practicum orientation and final internship group supervision meeting. Findings indicated that students’ experience in their preparation program resulted in higher levels of self-efficacy.

 

Keywords: counselor preparation, counselor training, self-efficacy, development, internship

 

 

The practice of counselor training is a complex, intentional process of reflective educational and experiential activities to promote the development of knowledge and skills (Bernard & Goodyear, 2013; Council for Accreditation of Counseling and Related Educational Programs [CACREP], 2009; McAuliffe & Eriksen, 2011). As such, the primary goal of counselor preparation programs is to educate and train students to become competent counselors by equipping them with necessary skills, knowledge and experiences (American Counseling Association, 2014; Bernard & Goodyear, 2013; CACREP, 2009). Furthermore, students training to be counselors increase their self-awareness and reflective practice throughout their educational experience (Granello & Young, 2012; Lambie & Sias, 2009; Rønnestad, & Skovholt, 2003). Increased understanding regarding counseling trainee development may aid educators’ ability to develop and deliver educational and supervision interventions.

 

Self-efficacy represents an individual’s beliefs or judgments about his or her ability to accomplish a given goal or task (Bandura, 1995). Furthermore, self-efficacy is a recognized measure of development in the counseling field (Larson & Daniels, 1998), has a positive influence on work-related performance (Bandura, 1982; Stajkovic & Luthans, 1998), and consequently works as an outcome and developmental consideration for counselor training. In addition, there are assortments of published research examining counseling trainees’ self-efficacy (e.g., Barbee, Scherer & Combs, 2003; Cashwell & Dooley, 2001; Kozina, Grabovari, Stefano, & Drapeau, 2010; Melchert, Hays, Wiljanen, & Kolocek, 1996; Tang et al., 2004); however, limited research examines counseling trainees’ development of self-efficacy in a longitudinal fashion based upon their experiences from start (e.g., educational courses) to finish (e.g., initial clinical experiences) in counselor preparation programs. Therefore, the purpose of this longitudinal investigation was to examine counselor trainees’ self-efficacy as they progressed through the educational and experiential components of a counselor preparation program.

 

Counseling Students’ Self-Efficacy

 

Bandura (1995) described perceived self-efficacy as “beliefs in one’s capabilities to organize and execute the courses of action required to manage prospective situations” (p. 2). Self-efficacy is considered an appropriate scientific lens for examining individuals’ beliefs regarding their ability to accomplish professional goals (Bandura, 1997) and is a common research topic in counseling literature (e.g., Larson & Daniels, 1998). Specifically, Bandura (1997) suggested that individuals’ ability to accomplish a task or goal not only necessitates skill and ability, but also the belief in oneself that provides the confidence and motivation to complete a task. Larson and Daniels (1998) stated that counseling self-efficacy is “one’s beliefs or judgments about her or his capabilities to effectively counsel a client in the near future” (p. 180). Self-efficacy is appropriate for the selection and training of counselors because of the construct’s stability and reliability (Beutler, Machado, & Neufeldt, 1994).

 

Self-efficacy is important in relation to counselor competence (Barnes, 2004; Larson & Daniels, 1998). Larson (1998) suggested that self-efficacy is a critical influence on one’s self-determining mechanisms and as a result is a critical variable in supervision. The importance of self-efficacy in the counseling field is documented by the development of measures of self-efficacy for various research constructs (e.g., Bodenhorn & Skaggs, 2005; Mullen, Lambie, & Conley, 2014; Sutton & Fall, 1995). Melchert and colleagues (1996) developed the Counselor Self-Efficacy Scale (CSES) to examine counselors’ and counselor trainees’ level of confidence in knowledge and skills regarding counseling competencies. Melchert and colleagues (1996) found that counseling students’ (N = 138) scores on the CSES varied based on their experience in their preparation program, with second-year students reporting more confidence than students in their first year of training. Additionally, Melchert and colleagues (1996) found that counselors (N = 138) with more years of clinical experience also reported greater levels of self-efficacy.

 

Counselors’ training, initial clinical experiences and supervision relates to their self-efficacy beliefs. Hill et al., (2008) found that skills training impacted undergraduate students’ confidence regarding the use of helping skills. However, Hill and colleagues (2008) noted that as students faced more difficult skills, their confidence decreased, but eventually increased upon gaining experience using the skill. Barbee and associates (2003) found that trainees’ (N = 113) participation in service learning had a positive relationship with counselor self-efficacy. However, these researchers also found that total credits of coursework (i.e., time in the preparation program) and prior counseling-related work were stronger predictors of self-efficacy as compared to service learning.

 

Supporting the findings from Barbee and colleagues (2003), Tang and colleagues (2004) found that students with more coursework, internship experience and related work experience reported higher levels of competence regarding counseling skills. Regarding self-efficacy during clinical experiences, Kozina and colleagues (2010) found that the counseling self-efficacy of first year master’s-level counseling students increased during initial work with clients during clinical experience. Additionally, Cashwell and Dooley (2001) found that practicing counselors receiving supervision, compared to those not receiving supervision, reported higher levels of self-efficacy, indicating that supervision supports increased beliefs of counseling efficacy. However, no published studies were identified examining counseling students’ longitudinal change in self-efficacy as a result of their participation in a counselor preparation program from the start of the program through their clinical experiences.

 

Purpose of the Study

 

The development of trainees is a vital topic for counselor education. Counselor educators and supervisors need a comprehensive understanding of student development with the aim of assessing student learning outcomes and facilitating pedagogical and supervisory interventions that support development. Enhancing counseling students’ self-efficacy regarding clinical skills is an important developmental goal within preparation programs, with higher self-efficacy suggesting increased likelihood of efficient and effective counseling services (Bandura, 1982; Bandura, 1997; Larson & Daniels, 1998; Stajkovic & Luthans, 1998). Research on counselor self-efficacy is common; however, no studies have investigated change in master’s-level counseling students’ self-efficacy over the course of their preparation program (i.e., longitudinal investigation). Therefore, we investigated the following research questions: (1) What is the relationship between counseling students’ demographic factors and self-efficacy at three key times during their preparation program? (2) Does counseling students’ self-efficacy change at three points during their graduate preparation program?

 

Method

 

Participants and Procedures

Participants included 179 master’s-level graduate students from a single CACREP entry-level counselor education program at a university in the Southeastern United States. Specifically, participants included several cohorts of entry-level counselor trainees who started the counselor training program during the spring 2008 through fall 2011 semesters and completed the program by the Summer 2013 semester. Institutional Review Board approval from the university was obtained prior to data collection and analysis. To protect the rights and confidentiality of the participants, all identifying information was removed and the data were aggregated.

 

The study was introduced to the participants during the counselor preparation program’s new student orientation (NSO; a mandatory information session prior to the start of trainees’ coursework). At this point, students were invited to be part of the study by completing a paper-and-pencil packet of instrumentation. Participants were invited to complete the second data collection point during a mandatory clinical practicum orientation (CPO) occurring prior to their initial clinical and supervision experience (approximately midpoint during the students’ program of study). The final data collection point was at the participants’ final internship group supervision meeting (FIGSM; end of students’ program of study).  A total accessible sample consisted of 224 students who fit the selection criteria for participate in this study. The selection criteria included the following: (a) started the program in the beginning of the spring 2008 semester and (b) graduated by the end of the fall 2011 semester. However, due to incomplete instrument packets, missing items (listwise deletion) or student attrition, 179 participants completed the instruments across all three data collection points, yielding a 79.91% response rate.

 

The participants included 151 females (84.4%) and 28 males (15.6%). Regarding age, 162 participants (90.5%) fell between the ages of 20 and 29, 13 participants (7.3%) were between the ages of 30 and 39, two participants (1.1%) fell between the ages of 40 and 49, and two participants (1.1%) were over 50 years of age. Participants’ ethnicities were as follows: 133 (74.3%) Caucasian, 36 (20.1%) African American, seven (3.9%) Hispanic American, one (0.6%) Asian American and 2 (1.1%) other ethnicity. Participants program tracks included mental health counseling (MHC; n = 78, 43.6%); marriage, couples and family counseling (MCFC; n = 46, 25.7%); and school counseling (SC; n = 55, 30.7%).

 

Counselor Preparation Program Experience

Students participating in this study were entry-level counseling trainees attending an academic unit with three CACREP-accredited master’s-level programs. The students were enrolled in one of the following three programs of study: (a) MHC; (b) MCFC; or (c) SC. Students’ early coursework in the counselor preparation program included core curriculum courses that focused on content knowledge and initial skill development required for advanced clinical courses. The course prerequisites for initial clinical practicum experience for all students included: (a) Introduction to the Counseling Profession, (b) Theories of Counseling and Personality, (c) Techniques of Counseling, (d) Group Procedures and Theories in Counseling, and (e) Ethical and Legal Issues. Additionally, students in the MHC and MCFC tracks were required to complete a Diagnosis and Treatment in Counseling course. Students in the MHC and MCFC tracks were required to complete 63 credit hours, while students in the SC track were required to complete 60 credits hours (if they did not have a teaching certificate) or 51 credit hours (if they had a valid teaching certificate). Courses were delivered by a diverse set of counselor educators who determined course content and style based on their individual pedagogical approaches.

 

Students participated in their clinical practicum course after their course prerequisites were met. SC students completed their internship after a single semester of clinical practicum (100 total clinical hours in practicum). Students in MHC and MCFC tracks completed their internship experience after two consecutive experiences in clinical practicum (200 total clinical hours in practicum). During their internship experience, SC students completed 600 clinical hours over one or two semesters and MHC and MCFC students completed 900 clinical hours over two semesters. Overall, students progressed through their course and clinical experiences over 2.5–3.5years, depending on their course load and time commitment preferences. Importantly, it was not required for all coursework to be completed prior to initial clinical experiences. Students completed non-prerequisite coursework at the time most accommodating to their schedule, but were required to complete all coursework by the time of graduation, with the FIGSM being one of the last class-based tasks in the program.

 

Measures

We utilized the CSES (Melchert et al., 1996) in this investigation to gather data on counseling trainees’ level of self-efficacy. In addition, a demographic questionnaire was used to collect data regarding participants’ biological gender, age, ethnicity and program track (i.e., MHC, MCFC or SC). The following section introduces and reviews the CSES.

 

Counselor Self-Efficacy Scale. The CSES is a 20-item self-report instrument that assesses counseling trainees’ competency regarding key counseling tasks for group and individual counseling (Melchert et al., 1996). The CSES was developed based upon a review of the literature with the goal of identifying key types of counseling competencies for counselors. The CSES uses 5-point Likert scale responses that indicate an individual’s level of confidence in his or her counseling ability, including “Never,” “Rarely,” “Sometimes,” “Frequently” or “Almost Always” answer options. Half of the items are worded in a negative fashion to avoid acquiescent response bias, requiring reverse coding. The total score of the CSES ranges from 20–100 and is calculated by adding the responses to all 20 items with consideration given to the reverse coded items. Some sample items from the CSES include the following: (a) I am not able to accurately identify client affect, (b) I can effectively facilitate appropriate goal development with clients, and (c) I can function effectively as a group leader/facilitator.

 

Melchert and colleagues (1996) reported a Cronbach’s alpha of .91 and a test-retest reliability (r = .85; p-value not reported) in their initial psychometric testing of the CSES with counseling psychologist students and licensed professional psychologists. In addition, Melchert and colleagues (1996) tested for convergent validity and reported an acceptable correlation (r = .83; p-value not reported) between the CSES and the Self-Efficacy Inventory (Friedlander & Snyder, 1983). Constantine (2001) found that the CSES had an acceptable internal consistency, with a Cronbach’s alpha of .77 with counseling supervisees. Additionally, Pasquariello (2013) found that Cronbach’s alpha ranged from .85–.93 with doctoral psychology students. For the current study, the internal consistency reliability for the CSES was acceptable, with a Cronbach’s alpha of .96 (Sink & Stroh, 2006; Streiner, 2003).

 

Data Analysis

A longitudinal study design was employed for this investigation. After completion of the data collection process, participants’ responses were analyzed using descriptive data analysis, one-way analysis of variance (ANOVA), repeated measures ANOVA, paired-samples t-test and mixed between/within-subjects ANOVA. Prior to analysis, the data were screened for outliers using the outlier labeling method (Hoaglin & Iglewicz, 1987; Hoaglin, Iglewicz, & Tukey, 1986), which resulted in identifying 11 cases with outliers. Therefore, Windsorized means were calculated based on adjacent data points to replace the outliers (Barnett & Lewis, 1994; Osborne & Overbay, 2004). The resulting data were checked for statistical assumptions and no violations were found. A sample size of 179 graduate counseling students was deemed appropriate for identifying a medium effect size (power = .80) at the .01 level for the employed data analysis procedures (Cohen, 1992).

 

Results

 

Counseling Trainees’ Self-Efficacy

Several one-way between-groups ANOVAs were conducted to examine the impact of each trainee’s age, gender, ethnicity and program track (i.e., SC, MHC or MCFC) on his or her level of self-efficacy at each of the three data collection points. There was no statistically significant relationship between self-efficacy and trainees’ age at the NSO data collection point (F[3, 178] = 1.35, p = .26), at the CPO data collection point (F[3, 178] = .39, p = .76) or at the FIGSM data collection point (F[3, 178] = .71, p = .55). Similarly, there was no statistically significant relationship between self-efficacy and trainees’ gender at the NSO data collection point (F[1, 178] = .48, p = .49), at the CPO data collection point (F[1, 178] = .02, p = .88) or at the FIGSM data collection point (F[1, 178] = .001, p = .97). There was no statistically significant relationship between self-efficacy and trainees’ ethnicity at the NSO data collection point (F[4, 178] = 1.03, p = .39), at the CPO data collection point (F[4, 178] = .82, p = .51) or at the FIGSM data collection point (F[4, 178] = .03, p = .97). Finally, there was no statistically significant relationship between self-efficacy and trainees’ program track at the NSO data collection point (F[2, 178] = .03, p = .97), at the CPO data collection point (F[2, 178] = .40, p = .67) or at the FIGSM data collection point (F[2, 178] = .04, p = .96).

 

Counseling Trainees’ Self-Efficacy Over the Course of the Program

A one-way within-subjects repeated measures ANOVA was conducted to examine participants’ (N = 179) CSES scores at the three data points (i.e., NSO, CPO, FIGSM). Table 1 presents the descriptive statistics. Mauchley’s Test indicated that the assumption of sphericity was violated, χ2(2) = .53, p < .001; therefore, the within-subjects effects were analyzed using the Greenhouse-Geisser correction (Greenhouse & Geisser, 1959). There was a statistically significant effect of time, F(1.3, 242.79)= 404.52, p < .001, Partial η2 = .69 on participants’ CSES scores. Sixty-nine percent of the variance in CSES scores can be accounted for by the time participants spent in the program (large effect size; Sink & Stroh, 2006; Streiner, 2003). Therefore, trainees scored higher on the CSES at each interval during their counselor preparation program.

 

Table 1

 

Descriptive Statistics for Self-Efficacy Across Data Collection Points

Data Collection Point

M

   SD

    Mdn

  Mode

Range

New student orientation

57.09

14.42

59

58

23–84 (61)

Clinical practicum orientation

77.43

8.53

78

79

53–99 (46)

Final internship group supervision meeting

83.04

6.80

84

76

66–95 (33)

Note. N = 179.

 

 

Several paired-samples t-tests were employed to evaluate the impact of time in the program on trainees’ self-efficacy. There was a statistically significant increase in trainees’ CSES scores from NSO to CPO, t (178) = 18.41, p < .001; η2 = .65. The mean increase in CSES scores between NSO and CPO was 20.33, with a 95% confidence interval ranging from 18.15–22.51. There was a statistically significant increase in trainees’ CSES scores from NSO to FIGSM, t (178) = 23.19, p < .001; η2 = .75. The mean increase in CSES scores between NSO and FIGSM was 25.94, with a 95% confidence interval ranging from 23.74–28.15. There was a statistically significant increase in trainees’ CSES scores from CPO to FIGSM, t (178) = 10.37, p < .001; η2 = .38. The mean increase in CSES scores between CPO and FIGSM was 5.61, with a 95% confidence interval ranging from 4.54–6.68. Overall, these results provide additional support indicating that trainees’ CSES scores had a statistically significant increase from the start of the program (NSO) to the end of the program (FIGSM). In addition, the span from the start of the program (NSO) to their initial clinical experience (CPO; i.e., completion of the core curriculum required for clinical work) had the largest increase in scores amongst consecutive time ranges (i.e., NSO to CPO and CPO to FIGSM).

 

A mixed between/within-subjects (split plot) ANOVA was conducted to assess the interaction effect of trainees’ degree track (i.e., SC; MHC; and MCFC) on their CSES scores across the three data points (i.e., NSO, CPO, FIGSM). Mauchley’s Test indicated that the assumption of sphericity was violated, χ2(2) = .53, p < .001; therefore, the effects were analyzed using the Greenhouse-Geisser correction (Greenhouse & Geisser, 1959). There was no significant interaction between trainees’ degree track and the data collection points, F(2.72, 239.58)= .12, p = .94; indicating that trainees’ track did not have an effect on their CSES scores across the data collection points, despite the differences in their program requirements.

 

Discussion

 

We examined the relationship between entry-level counseling trainees’ demographic characteristics and their reported self-efficacy at three key points during their graduate preparation program. The findings from this investigation indicated no relationship between participants’ age, gender, ethnicity or program track and their reported self-efficacy at any point in the program. These results are similar to Tang and colleagues’ (2004) findings, which identified no relationship between counseling trainees’ self-efficacy and their age. However, Tang and colleagues (2004) did find that total coursework and internship hours completed had a statistically significant impact on trainees’ counseling self-efficacy.

 

The current investigation is unique in that it longitudinally studied master’s-level counseling trainees’ self-efficacy at developmental points from the beginning to the end of their preparation program, while other studies have examined the construct of counseling self-efficacy through a cross-sectional framework or focused on clinical experiences (e.g., Barbee at al., 2003; Cashwell & Dooley, 2001; Kozina et al., 2010; Melchert et al., 1996; Tang et al., 2004). The results of this investigation identified differences in trainees’ self-efficacy at the three collection points (large effect size), indicating that trainees had an increase in self-efficacy as a result of their participation in the program. Additionally, the results identified mean differences in trainees’ self-efficacy as a result of time in the program from NSO to CPO and CPO to FIGSM. These findings are logical given the theoretical framework of self-efficacy (Bandura, 1986); however, these findings are important and relevant as they provide innovative empirical evidence for Bandura’s (1986) theory of self-efficacy.

 

Trainees’ self-efficacy increased the most between NSO and CPO, indicating that completing initial prerequisite content coursework had a larger impact on trainees’ development of efficacy compared to their time spent on initial clinical experience. This finding is important, considering that prior research has shown that initial clinical work increases self-efficacy (Kozina et al., 2010), whereas the findings in this investigation indicate that the majority of efficacy is developed prior to initial clinical experiences. The present results are consistent with those of Tang and colleagues (2004), who found that trainees with more completed coursework and more completed internship hours reported higher levels of self-efficacy. The findings of the current study builds upon Tang and colleagues’ (2004) findings, identifying the specific time within a counseling preparation program (i.e., initial coursework versus clinical experience) when the most growth in efficacy belief occurs.

 

The findings from the present investigation support models of education and supervision that utilize a social cognitive framework (e.g., Larson, 1998). Counselor self-efficacy represents a practitioner’s judgment about his or her ability to effectively counsel a client (Larson et al., 1992). Therefore, knowledge regarding counseling trainees’ development of self-efficacy during their preparation program prior to their clinical experiences affords supervisor practitioners and researchers insight into student development. Much of the existing literature focuses on trainees’ initial clinical experiences, neglecting the large impact that early coursework has on the development of self-efficacy.

 

Implications for Counselor Education and Supervision

We offer several implications for clinical supervisors based on the results from this investigation. First, our findings demonstrate that master’s-level counseling trainees’ self-efficacy increases as a result of their experiences in their preparation program, providing further evidence for Bandura’s (1986) theory of self-efficacy. Counselor educators are expected to monitor trainees’ progress and development throughout their training (Bernard & Goodyear, 2013), and self-efficacy is an established measure of development (Larson & Daniels, 1998); therefore, it serves as an appropriate outcome consideration for counselor preparation programs. Counselor educators can make use of available self-efficacy measures that focus on competency (e.g., CSES; Melchert et al., 1996) and evaluate trainees at milestones in their program as a measure of student learning outcomes. It is logical that trainees entering counselor preparation programs need high levels of instruction, modeling and guidance due to their inexperience in the discipline. Opportunities for modeling counseling skills across topic areas, along with occasions for practicing skills, provide chances for trainees to build mastery experiences early in their program. As noted by Kozina and colleagues (2010), giving feedback on the discrepancy between trainees’ skill competency and perceived efficacy may promote reflection and development at key times throughout their training program (Daniels & Larson, 2001; Hoffman, Hill, Holmes, & Freitas, 2005).

 

In addition, our findings identified the importance of trainees’ counselor preparation coursework. Specifically, increased student course requirements to meet accreditation standards (e.g., Bobby, 2013; CACREP, 2009; Hagedorn, Culbreth, & Cashwell, 2012) are likely to improve trainees’ self-efficacy (Tang et al., 2004). Prior research indicates that increased coursework as a result of higher accreditation standards has an effect on counselor knowledge (Adams, 2006). Our findings build on existing literature by indicating that coursework has an impact on trainees’ self-efficacy prior to their initial clinical experiences. Counselor educators should be strategic and identify prerequisite courses to enhance students’ self-efficacy on vital topics (e.g., counseling skills, group counseling, diagnosis and treatment courses) prior to students’ initial work with clients.

 

An additional implication relates to trainees’ level of self-efficacy as they enter initial clinical experiences. Participants in this study entered practicum with high levels of self-efficacy regarding clinical competence; and furthermore, participants had low to moderate increases in self-efficacy between practicum and the end of their internship. As such, our findings challenge the notion that growth in self-efficacy occurs during the clinical work phase of preparation (e.g., Kozina et al., 2010), because the majority of growth in self-efficacy for this study’s participants occurred prior to initial clinical experiences. On the other hand, participants’ reports of self-efficacy due to coursework may have been inflated, given that they had yet to complete their clinical work. Therefore, counselor educators should examine supervisees during their initial clinical work to assess their perceived efficacy and actual competence.

 

Limitations

As with all research, the present study has limitations. First, this study took place at a single counseling preparation program whose individual systemic factors may have influenced the participants’ experiences. Therefore, future studies should replicate the current investigation to confirm these findings. Second, this study utilized a single instrument that we identified based upon the research objectives for the study; however, more recently developed or validated instruments or a collection of instruments measuring the same construct may produce results that have different findings or implications. Additional limitations include the following: (a) potential unknown/unseen extraneous variables, (b) practice effects of participants retaking the same instruments three times, (c) participant attrition (i.e., 79.91% response rate), (d) cross-generational differences and (e) test fatigue (Gall, Gall, & Borg, 2007). Nevertheless, longitudinal research is considered a complex and comprehensive method of examining individual participants’ change over time (Gall et al., 2007), offering a contribution to the counselor education and supervision literature.

 

Recommendations for Future Research

Future research might expand this study to examine changes in postgraduate practitioners’ self-efficacy over an extended period of time (longitudinal study). Additionally, future researchers may examine: (a) the impact of self-efficacy on clinical outcomes, (b) the impact of clinical supervision on trainees’ self-efficacy and (c) the impact of initial clinical experiences (e.g., practicum) on trainees’ self-efficacy. Furthermore, researchers may examine other factors associated with counselor development (e.g., emotional intelligence, application of knowledge and theory, cognitive complexity). Researchers may examine the impact of specific pedagogical interventions on counseling trainees’ self-efficacy. Lastly, the findings from this study should be replicated in other institutes that train counseling professionals.

 

Counselor educators and supervisors promote counseling trainees’ professional competencies, enhancing their ability to provide effective counseling services to diverse clients. Research on counseling trainees’ development is imperative for understanding and attending to their counseling students’ educational and supervisory needs. The findings from this study indicate that counseling trainees experience an increase in their self-efficacy during their preparation programs.

 

Conflict of Interest and Funding Disclosure

The authors reported no conflict of

interest or funding contributions for

the development of this manuscript.

 

References

 

Adams, S. A. (2006). Does CACREP accreditation make a difference? A look at NCE results and answers. Journal of Professional Counseling: Practice, Theory, & Research, 34, 60–76.

American Counseling Association. (2014). 2014 ACA Code of Ethics. Alexandria, VA: Author.

Bandura, A. (1982). Self-efficacy mechanism in human agency. American Psychologist, 37, 122147. doi:10.1037/0003-066X.37.2.122

Bandura, A. (1986). The explanatory and predictive scope of self-efficacy theory. Journal of Social and Clinical Psychology, 4, 359–373.

Bandura, A. (Ed.). (1995). Self-efficacy in changing societies. Cambridge, England: Cambridge University Press.

Bandura, A. (1997). Self-efficacy: The exercise of control. New York, NY: Freeman.

Barbee, P. W., Scherer, D., & Combs, D. C. (2003). Prepracticum service-learning: Examining the relationship with counselor self-efficacy and anxiety. Counselor Education and Supervision, 43, 108–119. doi:10.1002/j.1556-6978.2003.tb01835.x

Barnes, K. L. (2004). Applying self-efficacy theory to counselor training and supervision: A comparison of two approaches. Counselor Education and Supervision, 44, 56–69. doi:10.1002/j.1556-6978.2004.tb01860.x

Barnett, V., & Lewis, T. (1994). Outliers in statistical data (3rd ed.). Chichester, England: Wiley & Sons.

Bernard, J. M., & Goodyear, R. K. (2013). Fundamentals of clinical supervision (5th ed.). Upper Saddle River, NJ: Pearson.

Beutler, L. E., Machado, P. P. P., & Neufeldt, S. A. (1994). Therapist variables. In A. E. Bergin & S. L. Garfield (Eds.), Handbook of psychotherapy and behavior change (4th ed., pp. 229–269). New York, NY: Wiley.

Bobby, C. L. (2013). The evolution of specialties in the CACREP standards: CACREP’s role in unifying the profession. Journal of Counseling & Development, 91, 35–43. doi:10.1002/j.1556-6676.2013.00068.x

Bodenhorn, N., & Skaggs, G. (2005). Development of the school counselor self-efficacy scale. Measurement and Evaluation in Counseling and Development, 38, 14–28.

Cashwell, T. H., & Dooley, K. (2001). The impact of supervision on counselor self-efficacy. The Clinical Supervisor, 20, 39–47. doi:10.1300/J001v20n01_03

Cohen, J. (1992). A power primer. Psychological Bulletin, 112, 155–159. doi:10.1037/0033-2909.112.1.155

Constantine, M. G. (2001). The relationship between general counseling self-efficacy and self-perceived multicultural counseling competence in supervisees. The Clinical Supervisor, 20, 81–90. doi:10.1300/J001v20n02_07

Council for Accreditation of Counseling and Related Educational Programs. (2009). 2009 standards. Retrieved from http://www.cacrep.org/2009standards.html

Daniels, J. A., & Larson, L. M. (2001). The impact of performance feedback on counseling self-efficacy and counselor anxiety. Counselor Education and Supervision, 41, 120–130. doi:10.1002/j.1556-6978.2001.tb01276.x

Friedlander, M. L., & Snyder, J. (1983). Trainees’ expectations for the supervisory process: Testing a developmental model. Counselor Education and Supervision, 22, 342–348. doi:10.1002/j.1556-6978.1983.tb01771.x

Gall, M. D., Gall, J. P., & Borg, W. R. (2007). Educational research: An introduction (8th ed.). Boston, MA: Pearson/Allyn & Bacon.

Granello, D. H., & Young, M. E. (2012). Counseling today: Foundations of professional identity. Upper Saddle River, NJ: Pearson.

Greenhouse, S. W., & Geisser, S. (1959). On methods in the analysis of profile data. Psychometrika, 24, 95–112.

Hagedorn, W. B., Culbreth, J. R., & Cashwell, C. S. (2012). Addiction counseling accreditation: CACREP’s role in solidifying the counseling profession. The Professional Counselor, 2, 124–133. doi:10.15241/wbh.2.2.124

Hill, C. E., Roffman, M., Stahl, J., Friedman, S., Hummel, A., & Wallace, C. (2008). Helping skills training for undergraduates: Outcomes and prediction of outcomes. Journal of Counseling Psychology, 55, 359–370. doi:10.1037/0022-0167.55.3.359

Hoaglin, D. C., & Iglewicz, B. (1987). Fine-tuning some resistant rules for outlier labeling. Journal of the American Statistical Association, 82, 1147–1149. doi:10.1080/01621459.1987.10478551

Hoaglin, D. C., Iglewicz, B., & Tukey, J. W. (1986). Performance of some resistant rules for outlier labeling. Journal of the American Statistical Association, 81, 991–999. doi:10.1080/01621459.1986.10478363

Hoffman, M. A., Hill, C. E., Holmes, S. E., & Freitas, G. F. (2005). Supervisor perspective on the process and outcome of giving easy, difficult, or no feedback to supervisees. Journal of Counseling Psychology, 52, 3–13. doi:10.1037/0022-0167.52.1.3

Kozina, K., Grabovari, N., De Stefano, J., & Drapeau, M. (2010). Measuring changes in counselor self-efficacy: Further validation and implications for training and supervision. The Clinical Supervisor, 29, 117–127. doi:10.1080/07325223.2010.517483

Lambie, G. W., & Sias, S. M. (2009). An integrative psychological developmental model of supervision for professional school counselors-in-training. Journal of Counseling & Development, 87, 349–356. doi:10.1002/j.1556-6678.2009.tb00116.x

Larson, L. M. (1998). The social cognitive model of counselor training. The Counseling Psychologist, 26, 219–273.

Larson, L. M., & Daniels, J. A. (1998). Review of the counseling self-efficacy literature. The Counseling Psychologist, 26, 179–218. doi:10.1177/0011000098262001

Larson, L. M., Suzuki, L. A., Gillespie, K. N., Potenza, M. T., Bechtel, M. A., & Toulouse, A. L. (1992). Development and validation of the counseling self-estimate inventory. Journal of Counseling Psychology, 39, 105. doi:10.1037/0022-0167.39.1.105

McAuliffe, G., & Eriksen, K. (Eds.). (2011). Handbook of counselor preparation: Constructivist, developmental, and experiential approaches. Thousand Oaks, CA: Sage.

Melchert, T. P., Hays, V. L., Wiljanen, L. M., & Kolocek, A. K. (1996). Testing models of counselor development with a measure of counseling self-efficacy. Journal of Counseling & Development, 74, 640–644. doi:10.1002/j.1556-6676.1996.tb02304.x

Mullen, P. R., Lambie, G. W., & Conley, A. H. (2014). Development of the ethical and legal issues in counseling self-efficacy scale. Measurement and Evaluation in Counseling and Development, 47, 62–78. doi:10.1177/0748175613513807

Osborne, J. W., & Overbay, A. (2004). The power of outliers (and why researchers should always check for them). Practical Assessment, Research & Evaluation, 9(6). Retrieved from http://pareonline.net/getvn.asp?v=9&n=6

Pasquariello, C. D. (2013). Enhancing self-efficacy in the utilization of physical activity counseling: An online constructivist approach with psychologists-in-training. (Unpublished doctoral dissertation). Virginia Commonwealth University, Richmond, VA.

Rønnestad, M. H., & Skovholt, T. M. (2003). The journey of the counselor and therapist: Research findings and perspectives on professional development. Journal of Career Development, 30, 5–44. doi:10.1177/089484530303000102

Sink, C. A., & Stroh, H. R. (2006). Practical significance: The use of effect sizes in school counseling research. Professional School Counseling, 9, 401–411.

Stajkovic, A. D., & Luthans, F. (1998). Self-efficacy and work-related performance: A meta-analysis. Psychological Bulletin, 124, 240261. doi:10.1037/0033-2909.124.2.240

Streiner, D. L. (2003). Starting at the beginning: An introduction to coefficient alpha and internal consistency. Journal of Personality Assessment, 80, 99–103. doi:10.1207/S15327752JPA8001_18

Sutton, J. M., Jr., & Fall, M. (1995). The relationship of school climate factors to counselor self-efficacy. Journal of Counseling & Development, 73, 331–336. doi:10.1002/j.1556-6676.1995.tb01759.x

Tang, M., Addison, K. D., LaSure-Bryant, D., Norman, R., O’Connell, W., & Stewart-Sicking, J. A. (2004). Factors that influence self-efficacy of counseling students: An exploratory study. Counselor Education and Supervision, 44, 70–80. doi:10.1002/j.1556-6978.2004.tb01861.x

 

 

Patrick R. Mullen, NCC, is an Assistant Professor at East Carolina University. Olivia Uwamahoro, NCC, is a doctoral candidate at the University of Central Florida. Ashley J. Blount, NCC, is a doctoral candidate at the University of Central Florida. Glenn W. Lambie, NCC, is a Professor at the University of Central Florida. Correspondence can be addressed to Patrick R. Mullen, 225A Ragsdale Bldg., Mail Stop 121, Greenville, NC 27858, mullenp14@ecu.edu.

 

Counseling Self-Efficacy, Quality of Services and Knowledge of Evidence-Based Practices in School Mental Health

Bryn E. Schiele, Mark D. Weist, Eric A. Youngstrom, Sharon H. Stephan, Nancy A. Lever

Counseling self-efficacy (CSE), defined as one’s beliefs about his or her ability to effectively counsel a client, is an important precursor of effective clinical practice. While research has explored the association of CSE with variables such as counselor training, aptitude and level of experience, little attention has been paid to CSE among school mental health (SMH) practitioners. This study examined the influence of quality training (involving quality assessment and improvement, modular evidence-based practices, and family engagement/empowerment) versus peer support and supervision on CSE in SMH practitioners, and the relationship between CSE and practice-related variables. ANCOVA indicated similar mean CSE changes for counselors receiving the quality training versus peer support. Regression analyses indicated that regardless of condition, postintervention CSE scores significantly predicted quality of practice, knowledge of evidence-based practices (EBP) and use of EBP specific to treating depression. Results emphasize the importance of CSE in effective practice and the need to consider mechanisms to enhance CSE among SMH clinicians.

 

Keywords: self-efficacy, school mental health, evidence-based practices, counselor training, depression

 

 

There are major gaps between the mental health needs of children and adolescents and the availability of effective services to meet such needs (Burns et al., 1995; Kataoka, Zhang, & Wells, 2002). This recognition is fueling efforts to improve mental health services for youth in schools (Mellin, 2009; Stephan, Weist, Kataoka, Adelsheim, & Mills, 2007). At least 20% of all youth have significant mental health needs, with roughly 5% experiencing substantial functional impairment (Leaf, Schultz, Kiser, & Pruitt, 2003). Further, less than one third of children with such mental health needs receive any services at all.

 

The President’s New Freedom Commission on Mental Health (2003) documented the position of schools as a point of contact and universal natural setting for youth and families, recognizing schools as a key factor in the transformation of child and adolescent mental health services (Stephan et al., 2007). In the past 2 decades, there has been a significant push for full-service schools that expand beyond a sole focus on education, and employ community mental health practitioners to respond to the emotional and behavioral needs of students (Conwill, 2003; Dryfoos, 1993; Kronick, 2000). The education sector is the most common provider of mental health services for children and adolescents (Farmer, Burns, Phillips, Angold, & Costello, 2003), with 70%–80% of youth who receive any mental health services obtaining them at school (Burns et al., 1995; Rones & Hoagwood, 2000). Therefore, attention must be paid to the quantity, quality and effectiveness of school mental health (SMH) services.

 

School Mental Health

 

In recent years, SMH programs, supported by both school staff (e.g., school psychologists, social workers, counselors) and school-based community mental health clinicians, have emerged as a promising approach to the provision of mental health services for students and families (Weist, Evans, & Lever, 2003). The growth of these programs has facilitated investigation of what constitutes high-quality SMH service provision (Nabors, Reynolds, & Weist, 2000; Weist et al., 2005). This work has been supported and furthered by the Center for School Mental Health, a federally funded technical assistance and training program to advance SMH programs within the United States. In collaboration with other SMH centers (e.g., UCLA Center for Mental Health in Schools) and interdisciplinary networks focused on school health, consensus was reached to develop a guiding framework defining best practices in SMH (Weist et al., 2005). These principles call for appropriate service provision for children and families, implementation of interventions to meet school and student needs, and coordination of mental health programs in the school with related community resources, among other things. For further explication of the framework and its development, see Weist et al. (2005).

 

Simultaneously, research developments through the Center for School Mental Health facilitated implementation of modular evidence-based practices (EBP; see Chorpita, Becker & Daleiden, 2007; Chorpita & Daleiden, 2009). A modular approach for intervention involves training clinicians in core, effective strategies for disorders frequently encountered in children (e.g., attention-deficit/hyperactivity disorder [ADHD], anxiety, depression, disruptive behavior disorders [DBD]). This approach enables individualized, flexible implementation of evidence-based strategies without the constraints of a manualized approach (Curry & Reinecke, 2003). The third guiding component to enhance quality in SMH practices is development of strategies to effectively engage and empower families (see Hoagwood, 2005).

 

Despite the development of such a framework, SMH clinicians often struggle to implement high-quality, evidence-based services (Evans et al., 2003; Evans & Weist, 2004). These clinicians are constrained by a lack of sufficient time, training in EBP, appropriate supervision, and internal and external resources (Shernoff, Kratchowill & Stoiber, 2003). For instance, a survey by Walrath et al. (2004) of Baltimore SMH clinicians suggested that the ratio of clinicians to students was 1:250, and in order to meet the mental health needs of students, clinicians would have to increase clinical hours by 79 per week to remediate student difficulties. Additionally, the school environment is often characterized as chaotic, hectic and crisis-driven (Langley, Nadeem, Kataoka, Stein, & Jaycox, 2010), with SMH clinicians citing difficulties implementing EBP given the schedules of students. As a result of the challenges limiting use of EBP in daily SMH practice, researchers are now evaluating the influences on successful delivery of EBP in schools, including the personal qualities of SMH professionals (e.g., attitudes, beliefs, skills, training; Berger, 2013), as well as environmental factors (e.g., school administrative support, access to community resources, sufficient space for practice; Powers, Edwards, Blackman & Wegmann, 2013) that may predict high-quality services (see Weist et al., 2014).

 

Previous work examining factors related to the provision of evidence-based SMH services by SMH clinicians suggested that the highest-rated facilitators of effective SMH practice were personal characteristics (e.g., desire to deliver mental health services), attitudes and openness toward use of EBP, and adequate training (Beidas et al., 2012; Langley et al., 2010). Alternatively, SMH clinicians reported a number of administrative, school site and personal barriers as significant obstacles to appropriate service delivery; such barriers include lack of sufficient training, overwhelming caseload, job burnout and personal mental health difficulties (Langley et al., 2010; Suldo, Friedrich, & Michalowski, 2010).

 

While researchers have evaluated the influence of SMH provider personal characteristics in relation to the delivery of high-quality SMH services, little attention has been paid to the importance of counseling self-efficacy (CSE). CSE is widely accepted as an important precursor to competent clinical practice (Kozina, Grabovari, De Stefano, & Drapeau, 2010). Further, building CSE is considered an important strategy in active learning when providing training in evidence-based therapies (Beidas & Kendall, 2010), and CSE in EBP is believed to be essential to implementation (Aarons, 2005). However, researchers have yet to systematically include measures of CSE in studies of EBP utilization by SMH providers.

 

Self-Efficacy

 

     Social-cognitive theory and its central construct, self-efficacy, have received much attention in the psychological literature, with more than 10,000 studies including these as central variables in the past 25 years (Judge, Jackson, Shaw, Scott, & Rich, 2007). Self-efficacy is defined as an individual’s beliefs about his or her ability to achieve desired levels of performance (Bandura, 1994), and it plays a key role in the initiation and maintenance of human behavior (Iannelli, 2000). Given the influence of self-efficacy expectancies on performance, researchers have evaluated how self-efficacy impacts a variety of action-related domains, including career selection (e.g., Branch & Lichtenberg, 1987; Zeldin, Britner, & Pajares, 2008), health-behavior change (e.g., Ramo, Prochaska, & Myers, 2010; Sharpe et al., 2008) and work-related performance (e.g., Judge et al., 2007; Stajkovic & Luthans, 1998). Specific to the mental health field, previous investigations have focused on how self-efficacy is related to counseling performance.

 

Counseling Self-Efficacy

The construct of CSE is defined as an individual’s beliefs about his or her ability to effectively counsel a client in the near future (Larson & Daniels, 1998). Studies of the structure and influence of CSE among a variety of mental health professionals, including counseling trainees, master’s-level counselors, psychologists, school counselors and students from related professions (e.g., clergy, medicine) have yielded mixed findings. Social desirability, counselor personality, aptitude, achievement (Larson et al., 1992) and counselor age (Watson, 2012) have shown small to moderate associations with CSE. CSE also is related to external factors, including the perceived and objective work environment, supervisor characteristics, and level or quality of supervision (Larson & Daniels, 1998).

 

However, the relationship of CSE with level of training is unclear. For the most part, CSE is stronger for individuals with at least some counseling experience than for those with none (Melchert, Hays, Wiljanen, & Kolocek, 1996; Tang et al., 2004). While the amount of training and education obtained have been reported as statistically significant predictors of degree of CSE (Larson & Daniels, 1998; Melchert et al., 1996), more recent work has not supported the existence of such predictive relationships (Tang et al., 2004). It also has been suggested that once a counselor has obtained advanced graduate training beyond the master’s level, the influence of experience on CSE becomes rather minimal (Larson, Cardwell, & Majors, 1996; Melchert et al., 1996; Sutton & Fall, 1995).

 

Some work has been done to evaluate interventions aimed at enhancing CSE by utilizing the four primary sources of self-efficacy, as defined by Bandura (1977; i.e., mastery, modeling, social persuasion, affective arousal). In two studies involving undergraduate recreation students, Munson, Zoerink & Stadulis (1986) found that modeling with role-play and visual imagery served to enhance CSE greater than a wait-list control group. Larson et al. (1999) attempted to extend these findings utilizing a sample of practicum counseling trainees, and found that self-evaluation of success in the session moderated the level of CSE postintervention (Larson et al., 1999), with perception of success significantly impacting the potency of the role-play scenarios. The same effect was not found for individuals in the videotape condition.

 

In addition to impacting clinician performance, CSE has been reported to indirectly impact positive client outcome (Urbani et al., 2002); for example, CSE has been associated with more positive outcomes for clients, more positive self-evaluations and fewer anxieties regarding counseling performance (Larson & Daniels, 1998). Thus, increasing CSE, which decreases clinicians’ anxiety, is important for client outcomes, as anxiety is reported to decrease level of clinical judgment and performance (Urbani et al., 2002). While there is some evidence that CSE is influential for client outcomes, minimal work has been done to evaluate this relationship.

 

CSE has been evaluated in a variety of samples; however, little work has been done to evaluate CSE of SMH practitioners and the factors that play into its development. Additionally, although some investigation has been conducted on factors that impact SMH practitioners’ abilities and performance, CSE is an element that seldom has been studied.

 

The current study aimed to examine the influence of a quality assessment and improvement (QAI) intervention on CSE in SMH practitioners, as well as the importance of CSE in regard to practice-related domains. The primary question of interest was, Does an intervention focused on QAI (target) result in higher levels of CSE than a comparison condition involving a focus on professional wellness (W) and supervision (control)? We investigated the influence of differential quality training and supervision on one’s level of CSE by comparing postintervention CSE scores between each condition after evaluating preintervention equivalency of CSE levels. Thus, we hypothesized that long-term exposure to the QAI intervention, family engagement/empowerment and modular EBP would result in significantly higher reports of CSE from those exposed to the QAI intervention than those exposed to the comparison intervention. Based on previous research, it is possible that specific counselor characteristics (e.g., age, experience) would predict CSE, such that individuals who are older and have more experience counseling children and adolescents would have higher CSE (Melchert et al., 1996; Tang et al., 2004; Watson, 2012). Thus, when evaluating training effects, these variables were included as covariates in the analysis of the relation between CSE and training.

 

Secondarily, this study aimed to evaluate the relation of professional experiences to CSE following exposure to the intervention. For this aim, the research question was, Does postintervention level of CSE predict quality of self-reported SMH practice, as well as knowledge and use of EBP? We hypothesized that level of CSE would predict quality of SMH practice, as well as attitude toward, knowledge and use of EBP regardless of intervention condition.

 

Method

 

This article stems from a larger previous evaluation of a framework to enhance the quality of SMH (Weist et al., 2009), funded by the National Institute of Mental Health (#1R01MH71015; 2003-2007; M. Weist, PI). As a part of a 12-year research program on quality and EBP in SMH, researchers conducted a two-year, multisite (from community agencies in Delaware, Maryland, Texas) randomized controlled trial of a framework for high-quality and effective practice in SMH (EBP, family engagement/empowerment and systematic QAI) as compared to an enhanced treatment as usual condition (focused on personal and school staff wellness). Only the methods pertaining to the aims of the current study have been included here (see Stephan et al., 2012; Weist et al., 2009 for more comprehensive descriptions).

 

Participants

A sample of 72 SMH clinicians (i.e., clinicians employed by community mental health centers to provide clinical services within the school system) from the three SMH sites participated for the duration of the study (2004–2006), and provided complete data for all study measures via self-report. All clinicians were employed by community-based agencies with an established history of providing SMH prevention and intervention services to elementary, middle and high school students in both general and special education programs.

 

A total of 91 clinicians participated over the course of the study, with a sample size of 64 in Year 1 and 66 in Year 2, with 27 clinicians involved only in Year 2. Out of the Year 1 sample (35 QAI and 29 W), 24 participants did not continue into Year 2 (13 QAI and 11 W). Dropout showed no association with nonparticipation and did not differ between conditions (37% QAI versus 38% comparison dropout rate). Investigations in this particular study focused on individuals who had completed at least one year of the study and had submitted pre- and postintervention measures. The 72 participants were predominantly female (61 women, 11 men) and were 36 years old on average (SD = 11.03). In terms of race and ethnicity, participants identified as Caucasian (55%), African American (26%), Hispanic (18%) and Other (1%). Participants reported the following educational levels: graduate degree (83%), some graduate coursework (13%), bachelor’s degree (3%), and some college (1%).  In terms of experience, clinicians had roughly 6 years of prior experience and had worked for their current agency for 3 years on average. The obtained sample is reflective of SMH practitioners throughout the United States (Lewis, Truscott, & Volker, 2008).

 

Measures

 

     Counseling self-efficacy. Participants’ CSE was measured using the Counselor Self-Efficacy Scale (Sutton & Fall, 1995). The measure was designed to be used with school counselors, and was created using a sample of public school counselors in Maine. Sutton and Fall modified a teacher efficacy scale (Gibson & Dembo, 1984), resulting in a 33-item measure that reflected CSE and outcome expectancies. Results of a principal-component factor analysis demonstrated initial construct validity, indicating a three-factor structure, with the internal consistency of these three factors reported as adequate (.67–.75). However, the structure of the measure has received criticism, with some researchers arguing that the third factor does not measure outcome expectancies as defined by social-cognitive theory (Larson & Daniels, 1998). Thus, we made a decision to use the entire 33-item scale as a measure of overall CSE. Respondents were asked to rate each item using a 6-point Likert scale (1 = strongly disagree, 6 = strongly agree). We made slight language modifications to make the scale more applicable to the work of this sample (Weist et al., 2009); for instance, guidance program became counseling program. CSE was measured in both conditions at the beginning and end of Years 1 and 2 of the intervention program.

 

     Quality of school mental health services. The School Mental Health Quality Assessment Questionnaire (SMHQAQ) is a 40-item research-based measure developed by the investigators of the larger study to assess 10 principles for best practice in SMH (Weist et al., 2005; Weist et al., 2006), including the following: “Programs are implemented to address needs and strengthen assets for students, families, schools, and communities” and “Students, families, teachers and other important groups are actively involved in the program’s development, oversight, evaluation, and continuous improvement.”

 

At the end of Year 2, clinicians rated the degree to which each principle was present in their own practice on a 6-point Likert scale, ranging from not at all in place to fully in place. Given that results from a principle components analysis indicated that all 10 principles weighed heavily on a single strong component, analyses focused primarily on total scores of the SMHQAQ. Aside from factor analytic results, validity estimates are unavailable. Internal consistency as measured by coefficient alpha was very strong (.95).

 

     Knowledge and use of evidence-based practices. The Practice Elements Checklist (PEC) is based on the Hawaii Department of Health’s comprehensive summary of top modular EBP elements (Chorpita & Daleiden, 2007). Principal investigators of the larger study created the PEC in consultation with Bruce Chorpita of the University of California, Los Angeles, an expert in mental health technologies for children and adolescents. The PEC asks clinicians to provide ratings of the eight skills found most commonly across effective treatments for four disorder areas (ADHD, DBD, depression and anxiety). Respondents used a 6-point Likert scale to rate both current knowledge of the practice element (1= none and 6 = significant), as well as frequency of use of the element in their own practice, and frequency with which the clinician treats children whose primary presenting issue falls within one of the four disorder areas (1 = never, 6 = frequently).

 

In addition to total knowledge and total frequency subscales (scores ranging from 4–24), research staff calculated four knowledge and four frequency subscale scores (one for each disorder area) by averaging responses across practice elements for each disorder area (scores ranging from 1–6). Clinicians also obtained total PEC score by adding all subscale scores, resulting in a total score ranging from 16–92. Although this approach resulted in each item being counted twice, it also determined how total knowledge and skill usage are related to CSE, as well as skills in specific disorder areas. While internal consistencies were found to be excellent for each of the subscales, ranging from .84–.92, validity of the measure has yet to be evaluated. Clinicians completed the PEC at end of Year 2.

 

Study Design

SMH clinicians were recruited from their community agencies approximately 1 month prior to the initial staff training. After providing informed consent, clinicians completed a set of questionnaires, which included demographic information, level of current training and CSE, and were randomly assigned to the QAI intervention or the W intervention. Four training events were provided for participants in both conditions (at the beginning and end of both Years 1 and 2). During the four training events, individuals in the QAI condition received training in the three elements reviewed previously. For individuals involved in the W (i.e., comparison) condition, training events focused on general staff wellness, including stress management, coping strategies, relaxation techniques, exercise, nutrition and burnout prevention.

 

At each site, senior clinicians (i.e., licensed mental health professionals with a minimum of a master’s degree and 3 years experience in SMH) were chosen to serve as project supervisors for the condition to which they were assigned. These clinicians were not considered participants, and maintained their positions for the duration of the study. Over the course of the project, each research supervisor dedicated one day per week to the study, and was assigned a group of roughly 10 clinicians to supervise. Within the QAI condition, supervisors held weekly group meetings with small groups of five clinicians to review QAI processes and activities in their schools, as well as strategies for using the evidence base; in contrast, there was no study-related school support for staff in the W condition.

 

Results

 

Preliminary Analyses and Scaling

     Analyses were conducted using SPSS, version 20; tests of statistical significance were conducted with a Bonferroni correction (Cohen, Cohen, West, & Aiken, 2003), resulting in the use of an alpha of .0045, two-tailed. To facilitate comparisons between variables, staff utilized a scaling method known as Percentage of Maximum Possible (POMP) scores, developed by Cohen, Cohen, Aiken, & West (1999). Using this method, raw scores are transformed so that they range from zero to 100%. This type of scoring makes no assumptions about the shape of the distributions, in contrast to z scores, for which a normal distribution is assumed. POMP scores are an easily understood and interpreted metric and cumulatively lead to a basis for agreement on the size of material effects in the domain of interest (i.e., interventions to enhance quality of services and use of EBP; Cohen et al., 1999).

 

Primary Aim

     Initial analyses confirmed retreatment equivalence for the two conditions, t (72) = –.383, p = .703. For individuals in the QAI condition, preintervention CSE scores averaged at 71.9% of maximum possible (SD = .09), while those in the comparison condition averaged at 71.3% of maximum possible (SD = .08). These scores were comparable to level of CSE observed in counseling psychologists with similar amounts of prior experience (Melchert et al., 1996).

 

Correlation analyses suggested that pretreatment CSE was significantly associated with age (r = .312, p = .008), race (r = –.245, p = .029), years of counseling experience (r = .313, p = .007) and years with the agency (r = .232, p = .048). Thus, these variables were included as covariates in an analysis of covariance (ANCOVA) evaluating changes in CSE between the QAI and comparison conditions. Results suggested a nonsignificant difference in change in CSE from pre- to postintervention between conditions, F (72) = .013, p = .910. For individuals in the QAI condition, postintervention CSE scores averaged at 73.1% of maximum possible (SD = .07), and for individuals in the comparison condition, CSE scores averaged at 72.8% of maximum possible (SD = .08). Additionally, when looking across conditions, results indicated a nonsignificant difference in change in level of CSE from pre- to postintervention, F (72) = .001, p = .971. Across conditions, clinicians reported roughly similar levels of CSE at pre- and postintervention time points (72% vs. 73% of maximum possible); see Table 1.

 

 

Table 1

 

Analysis of Covariance (ANCOVA) Summary of Change in CSE

 

Source

df

  F

  p

Partial η2

CSE

1

.001

.971

.000

CSE*Condition

1

.013

.910

.000

CSE*Age

1

.281

.598

.004

CSE*Race

1

1.190

.279

.018

CSE*Years of Experience

1

.032

.859

.000

CSE*Years with Agency

1

.003

.955

.000

Error

66

 

Note. N = 72.

 

 

Secondary Aim

     To investigate the influence of level of CSE on quality and practice elements in counseling, a series of individual regressions were conducted with level of postintervention CSE as the predictor variable, and indicators of attitudes toward EBP, knowledge and use of EBP, and use of quality mental health services as the outcome variables in separate analyses.

 

Table 2 shows that level of postintervention CSE significantly predicted the following postintervention variables: SMHQAQ quality of services (R2 = .328, F [60] = 29.34, p < .001); knowledge of EBP for ADHD (R2 = .205, F [46] = 11.54, p = .001), depression (R2 = .288, F [46]= 18.17, p < .001), DBD (R2 = .236, F [46]= 13.92, p = .001) and anxiety (R2 = .201, F [46]= 10.81, p = .002); usage of EBP specific to treating depression (R2 = .301, F [46]= 19.34, p < .001); and total knowledge of EBP (R2 = .297, F [44] = 18.20, p < .001). Results further indicated that postintervention CSE was not a significant predictor of usage of EBP for ADHD (R2 = .010, F [45] = .457, p = .502), DBD (R2 = .024, F [45] = 1.100, p = .300) and anxiety (R2 = .075, F [43] = 3.487, p = .069); and total usage of EBP (R2 = .090, F [43] = 4.244, p = .045).

 

 

Table 2

 

Results of Linear Regressions Between Level of Postintervention CSE and Outcome Variables

 

Variables

Beta

       R2

  Adjusted R2

      F   

        p

SMH Quality

0.573

0.328

0.317

29.337

0.000

EBP ADHD – Knowledge

0.452

0.205

0.187

11.583

0.001

EBP ADHD – Usage

0.100

0.010

–0.012

0.457

0.502

EBP Depression – Knowledge

0.536

0.288

0.272

18.168

0.000

EBP Depression – Usage

0.548

0.301

0.285

19.337

0.000

EBP DBD – Knowledge

0.486

0.236

0.219

13.922

0.001

EBP DBD – Usage

0.154

0.024

0.002

1.100

0.300

EBP Anxiety – Knowledge

0.448

0.201

0.182

10.811

0.002

EBP Anxiety – Usage

0.274

0.075

0.053

3.487

0.069

EBP Total Knowledge

0.545

0.297

0.281

18.197

0.000

EBP Total Usage

0.300

0.900

0.069

4.244

0.045

 

Note. To control for experiment-wise error, a Bonferroni correction was used and significance was evaluated at the 0.0045 level.

 

 

Discussion

 

While there has been some previous examination of the association between training and CSE, results have been mixed (see Larson & Daniels, 1998), and no such evaluations have been conducted within the context of SMH services. The current study stemmed from a larger evaluation of a framework to enhance the quality of SMH, targeting quality service provision, EBP, and enhancement of family engagement and empowerment (see Weist et al., 2009).

 

The present study had two primary aims. The first goal was to evaluate differences in level of CSE from pre- to postintervention between two groups of SMH clinicians. We expected that those who received information, training and supervision on QAI and best practice in SMH would report higher levels of CSE postintervention than those in the W condition. The secondary aim was to evaluate whether clinician reports of postintervention CSE would serve as predictors of quality of SMH practice, as well as knowledge and use of EBP. Given the influence that clinician CSE has been found to have on practice-related variables in previous studies (see Larson & Daniels, 1998), we hypothesized that higher level of CSE would significantly predict higher quality of SMH practice, and knowledge and usage of EBP.

 

Controlling for age, race, years of experience and years with the agency, findings did not confirm the primary hypothesis. No statistically significant differences in clinician reports of CSE from pre- to postintervention were observed between the QAI and W conditions. Regarding the secondary aim, however, clinician postintervention level of CSE was found to serve as a significant predictor of quality of practice; total knowledge of EBP specific to treating ADHD, DBD, anxiety and depression; and usage of EBP specific to treating depression. Findings are consistent with previous literature suggesting that CSE levels influence performance in a number of practice-related domains (Larson & Daniels, 1998).

 

Results did not support a significant predictive relation between CSE level and usage of EBP specific to treating ADHD, DBD and anxiety. The failure to find an association may be due to evaluating level of usage of EBP across conditions due to limited power to run the analyses by condition. Results from the original study suggested that individuals in the QAI condition were more likely to use established EBP in treatment (see Weist et al., 2009). Thus, as provider characteristics including CSE (Aarons, 2005) are known to be associated with adoption of EBP, it may be that examining these associations across conditions resulted in null findings.

 

While current results did support the importance of high CSE regarding practice-related domains, there was no significant difference in level of CSE between those who received information, training and supervision in QAI; use of EBP; and family engagement and empowerment compared to those in the W condition. Findings from the current study contrast with other research that has documented improvements in CSE following targeted interventions. Previous targeted interventions to increase CSE have resulted in positive outcomes when using micro-skills training and mental practice (Munson, Stadulis, & Munson, 1986; Munson, Zoerink, & Stadulis, 1986), role-play and visual imagery (Larson et al., 1999), a prepracticum training course (Johnson, Baker, Kopala, Kiselica, & Thompson, 1989) and practicum experiences (Larson et al., 1993).

 

As a curvilinear relation is reported to exist between CSE and level of training (Larson et al., 1996; Sutton & Fall, 1995), it may be that the amount of previous training and experience of this sample of clinicians, being postlicensure, was such that the unique experiences gained through the QAI and W conditions in the current study had a minimal impact on overall CSE. Many prior studies utilized students untrained in counseling and interpersonal skills (Munson, Zoerink & Stadulis, 1986) and beginning practicum students and trainees (Easton, Martin, & Wilson, 2008; Johnson et al., 1989; Larson et al., 1992, 1993, 1999). Regarding the usefulness of a prepracticum course and practicum experiences for level of CSE, significant increases were only observed in the beginning practicum students with no significant changes seen in advanced students. Additionally, no previous studies have evaluated the success of CSE interventions with clinicians postlicensure.

 

It also is plausible that failure to detect an effect was due to the high preintervention levels of CSE observed across clinicians. At baseline, clinicians in the QAI condition reported CSE levels of roughly 71.9% of maximum potential, whereas those in the W condition reported CSE levels of 71.3% of maximum potential. Previous research has found high levels of CSE among practitioners with comparable amounts of previous experience, with those having 5–10 years of experience reporting mean CSE levels of 4.35 out of five points possible (Melchert et al., 1996). Thus, the average level of CSE may be accounted for by the amount of previous education and training reported by clinicians, and the observed increase of 1.5% at postintervention may be a reflection of the sample composition.

 

Limitations

Due to a small sample size, the power to detect changes in CSE was modest. Because of efforts to increase power by increasing the sample size, the time between reports of pre- and postintervention levels of CSE varied within the sample. Some participants completed only a year or a year and a half instead of the full 2 years.

 

A further limitation was reliance on self-reported information from the participating clinicians regarding their level of CSE, quality of practice, and knowledge and usage of EBP. Thus, a presentation bias may have been present in that clinicians may have reported stronger confidence in their own abilities than they felt in reality, or may have inflated responses on their knowledge and usage of EBP.

 

An additional limitation concerns the fact that CSE was not included as an explicit factor in training. Increasing CSE was not an explicit goal, and training and supervision were not tailored so that increases in CSE were more likely. The relation between supervisory feedback and CSE also may depend on the developmental level and pretraining CSE level of the clinicians (Larson et al., 1999; Munson, Zoerink & Stadulis, 1986), with untrained individuals reporting large increases. Thus, increased performance feedback may or may not have enhanced CSE within this sample.

 

Future Directions

Based on these findings, future work is suggested to evaluate ways in which CSE can be increased among clinicians. As the training procedures utilized in this study failed to change CSE, it is important to determine what facets of CSE, if any, are conducive to change. Although the current study evaluated broad CSE, Bandura (1977) theorized that overall self-efficacy is determined by the efficacy and outcome expectancies an individual has regarding a particular behavior. Efficacy expectancies are individuals’ beliefs regarding their capabilities to successfully perform the requisite behavior. Efficacy expectancies serve mediational functions between individuals and their behavior, such that if efficacy expectancies are high, individuals will engage in the behavior because they believe that they will be able to successfully complete it. Outcome expectancies, on the other hand, involve individuals’ beliefs that a certain behavior will lead to a specific outcome, and mediate the relation between behaviors and outcomes. Therefore, when outcome expectancies are low, individuals will not execute that behavior because they do not believe it will lead to a specified outcome.

 

As with the current study, the majority of the existing studies investigating change in CSE have evaluated broad CSE without breaking the construct down into the two types of expectancies (i.e., efficacy expectancies and outcome expectancies). Larson and Daniels (1998) found that fewer than 15% of studies on CSE examined outcome expectancies, and of the studies that did, only 60% operationalized outcome expectancies appropriately. While clinicians may believe that they can effectively perform a counseling strategy, they may not implement said strategy if they do not believe that it will produce client change. Ways in which these concepts can be evaluated may include asking, for example, for level of confidence in one’s ability to effectively deliver relaxation training, as well as for level of confidence that relaxation training produces client change. Based on the dearth of work in this area, future efforts should involve breaking down CSE and correctly operationalizing efficacy expectancies and outcome expectancies to examine what sorts of influences these expectancies have on overall CSE.

 

Additionally, future efforts to investigate the enhancement of CSE may evaluate the pliability of this construct depending on level of training. Is CSE more stable among experienced clinicians compared to counseling trainees? Should CSE enhancement be emphasized among new clinicians? Or are different methods needed to increase one’s CSE depending on previous experience? This goal may be accomplished by obtaining sizeable, representative samples with beginning, moderate and advanced levels of training, and examining the long-term stability of CSE.

 

Future work should incorporate strategies of mastery, modeling, social persuasion and affective arousal to enhance the CSE of SMH clinicians. Although role-play was utilized in the current study, future interventions could include visual imagery or mental practice of performing counseling skills, discussions of CSE, and more explicit positive supervisory feedback. Furthermore, mastery experiences (i.e., engaging in a counseling session that the counselor interprets as successful) in actual or role-play counseling settings have been found to increase CSE (Barnes, 2004); however, this result is contingent on the trainee’s perception of session success (Daniels & Larson, 2001). Future efforts to enhance CSE could strategically test how to structure practice counseling sessions and format feedback in ways that result in mastery experiences for clinicians. Future investigations also may incorporate modeling strategies into counselor training, possibly within a group setting. Structuring modeling practices in a group rather than an individual format may facilitate a fluid group session, moving from viewing a skill set to practicing with other group members and receiving feedback. This scenario could provide counselors with both vicarious and mastery experiences.

 

The use of verbal persuasion—the third source of efficacy—to enhance CSE also has been evaluated in counseling trainees. Verbal persuasion involves communication of progress in counseling skills, as well as overall strengths and weaknesses (Barnes, 2004). While strength-identifying feedback has been found to increase CSE, identifying skills that need improvement has resulted in a decrease in CSE. Lastly, emotional arousal, otherwise conceptualized as anxiety, is theorized to contribute to level of CSE. As opposed to the aforementioned enhancement mechanisms, increases in counselor anxiety negatively predict counselor CSE (Hiebert, Uhlemann, Marshall, & Lee, 1998). Thus, it is not recommended that identification of skills that need improvement be utilized as a tactic to develop CSE. Finally, in addition to clinician self-ratings, future research should investigate CSE’s impact on performance as measured by supervisors, as well as clients. With growing momentum for SMH across the nation, it is imperative that all factors influencing client outcomes and satisfaction with services be evaluated, including CSE.

 

 

 

Conflict of Interest and Funding Disclosure

The authors reported no conflict of

interest or funding contributions for

the development of this manuscript.

 

 

 

References

 

Aarons, G. A. (2005). Measuring provider attitudes toward evidence-based practice: Consideration of organizational context and individual differences. Child and Adolescent Psychiatric Clinics of North America, 14, 255–271. doi:10.1016/j.chc.2004.04.008

Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84, 191–215. doi:10.1037/0033-295X.84.2.191

Bandura, A. (1994). Self-efficacy. In V. S. Ramachandran (Ed.), Encyclopedia of human behavior (Vol. 4, pp. 71–81). New York, NY: Academic Press.

Barnes, K. L. (2004). Applying self-efficacy theory to counselor training and supervision: A comparison of two approaches. Counselor Education and Supervision, 44, 56–69. doi:10.1002/j.1556-6978.2004.tb01860.x

Beidas, R. S., & Kendall, P. C. (2010). Training therapists in evidence-based practice: A critical review of studies from a systems-contextual perspective. Clinical Psychology: Science and Practice, 17, 1–30. doi:10.1111/j.1468-2850.2009.01187.x

Beidas, R. S., Mychailyszyn, M. P., Edmunds, J. M., Khanna, M. S., Downey, M. M., & Kendall, P. C. (2012). Training school mental health providers to deliver cognitive-behavioral therapy. School Mental Health, 4, 197–206. doi:10.1007/s12310-012-9047-0

Berger, T. K. (2013). School counselors’ perceptions practices and preparedness related to issues in mental health (Doctoral dissertation). Retrieved from http://hdl.handle.net/1802/26892

Branch, L. E., & Lichtenberg, J. W. (1987, August). Self-efficacy and career choice. Paper presented at the convention of the American Psychological Association, New York, NY.

Burns, B. J., Costello, E. J., Angold, A., Tweed, D., Stangl, D., Farmer, E. M., & Erkanli, A. (1995). Children’s mental health service use across service sectors. Health Affairs, 14, 147–159. doi:10.1377/hlthaff.14.3.147

Chorpita, B. F., Becker, K. D., & Daleiden, E. L. (2007). Understanding the common elements of evidence-based practice: Misconceptions and clinical examples. Journal of the American Academy of Child and Adolescent Psychiatry, 46, 647–652. doi:10.1097/chi.0b013e318033ff71

Chorpita, B. F., & Daleiden, E. L. (2009). CAMHD biennial report: Effective psychosocial interventions for youth with behavioral and emotional needs. Honolulu, HI: Child and Adolescent Mental Health Division, Hawaii Department of Health.

Cohen, P., Cohen, J., Aiken, L. S., & West, S. G. (1999). The problem of units and the circumstances for POMP. Multivariate Behavioral Research, 34, 315–346. doi:10.1207/S15327906MBR3403_2

Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). Mahwah, NJ: Erlbaum.

Conwill, W. L. (2003). Consultation and collaboration: An action research model for the full-service school. Consulting Psychology Journal: Practice and Research, 55, 239–248. doi:10.1037/1061-4087.55.4.239

Curry, J. F., & Reinecke, M. A. (2003). Modular therapy for adolescents with major depression. In M. A. Reinecke, F. M. Dattilio, & A. Freeman (Eds.), Cognitive therapy with children and adolescents (2nd ed., pp. 95–127). New York, NY: Guilford.

Daniels, J. A., & Larson, L. M. (2001). The impact of performance feedback on counseling self-efficacy and counselor anxiety. Counselor Education and Supervision, 41, 120–130. doi:10.1002/j.1556-6978.2001.tb01276.x

Dryfoos, J. G. (1993). Schools as places for health, mental health, and social services. Teachers College Record, 94, 540–567.

Easton, C., Martin, W. E., Jr., & Wilson, S. (2008). Emotional intelligence and implications for counseling self-efficacy: Phase II. Counselor Education and Supervision, 47, 218–232. doi:10.1002/j.1556-6978.2008.tb00053.x

Evans, S. W., Glass-Siegel, M., Frank, A., Van Treuren, R., Lever, N. A., & Weist, M. D. (2003). Overcoming the challenges of funding school mental health programs. In M. D. Weist, S. W. Evans, & N. A. Lever (Eds.), Handbook of school mental health: Advancing practice and research (pp. 73–86). New York, NY: Kluwer Academic/Plenum.

Evans, S. W., & Weist, M. D. (2004). Implementing empirically supported treatments in the schools: What are we asking? Clinical Child and Family Psychology Review, 7, 263–267. doi:10.1007/s10567-004-6090-0

Farmer, E. M., Burns, B. J., Phillips, S. D., Angold, A., & Costello, E. J. (2003). Pathways into and through mental health services for children and adolescents. Psychiatric Services, 54, 60–66. doi:10.1176/appi.ps.54.1.60

Gibson, S., & Dembo, M. H. (1984). Teacher efficacy: A construct validation. Journal of Educational Psychology, 76, 569–582. doi:10.1037/0022-0663.76.4.569

Hiebert, B., Uhlemann, M. R., Marshall, A., & Lee, D. Y. (1998). The relationship between self-talk, anxiety, and counselling skill. Canadian Journal of Counselling and Psychotherapy, 32, 163–171.

Hoagwood, K. E. (2005). Family-based services in children’s mental health: A research review and synthesis. Journal of Child Psychology and Psychiatry, 46, 690–713. doi:10.1111/j.1469-7610.2005.01451.x

Iannelli, R. J. (2000). A structural equation modeling examination of the relationship between counseling self-efficacy, counseling outcome expectations, and counselor performance. (Doctoral dissertation). Retrieved from ProQuest Dissertations and Theses database (9988728).

Johnson, E., Baker, S. B., Kopala, M., Kiselica, M. S., & Thompson, E. C., III (1989). Counseling self-efficacy and counseling competence in prepracticum training. Counselor Education and Supervision, 28, 205–218. doi:10.1002/j.1556-6978.1989.tb01109.x

Judge, T. A., Jackson, C. L., Shaw, J. C., Scott, B. A., & Rich, B. L. (2007). Self-efficacy and work-related performance: The integral role of individual differences. Journal of Applied Psychology, 92, 107–127. doi:10.1037/0021-9010.92.1.107

Kataoka, S. H., Zhang, L., & Wells, K. B. (2002). Unmet need for mental health care among U.S. children: Variation by ethnicity and insurance status. American Journal of Psychiatry, 159, 1548–1555. doi:10.1176/appi.ajp.159.9.1548

Kozina, K., Grabovari, N., De Stefano, J., & Drapeau, M. (2010). Measuring changes in counselor self-efficacy: Further validation and implications for training and supervision. The Clinical Supervisor, 29, 117–127. doi:10.1080/07325223.2010.517483

Kronick, R. F. (Ed.). (2000). Human services and the full service school: The need for collaboration. Springfield, IL: Thomas.

Langley, A. K., Nadeem, E., Kataoka, S. H., Stein, B. D., & Jaycox, L. H. (2010). Evidence-based mental health programs in schools: Barriers and facilitators of successful implementation. School Mental Health, 2, 105–113. doi:10.1007/s12310-010-9038-1

Larson, L. M., Cardwell, T. R., & Majors, M. S. (1996, August). Counselor burnout investigated in the context of social cognitive theory. Paper presented at the meeting of the American Psychological Association, Toronto, Canada.

Larson, L. M., Clark, M. P., Wesley, L. H., Koraleski, S. F., Daniels, J. A., & Smith, P. L. (1999). Video versus role plays to increase counseling self-efficacy in prepractica trainees. Counselor Education and Supervision, 38, 237–248. doi:10.1002/j.1556-6978.1999.tb00574.x

Larson, L. M., & Daniels, J. A. (1998). Review of the counseling self-efficacy literature. The Counseling Psychologist, 26, 179–218. doi:10.1177/0011000098262001

Larson, L. M., Daniels, J. A., Koraleski, S. F., Peterson, M. M., Henderson, L. A., Kwan, K. L., & Wennstedt, L. W. (1993, June). Describing changes in counseling self-efficacy during practicum. Poster presented at the meeting of the American Association of Applied and Preventive Psychology, Chicago, IL.

Larson, L. M., Suzuki, L. A., Gillespie, K. N., Potenza, M. T., Bechtel, M. A., & Toulouse, A. L. (1992). Development and validation of the counseling self-estimate inventory. Journal of Counseling Psychology, 39, 105–120. doi:10.1037/0022-0167.39.1.105

Leaf, P. J., Schultz, D., Kiser, L. J., & Pruitt, D. B. (2003). School mental health in systems of care. In M. D. Weist, S. W. Evans, & N. A. Lever (Eds.), Handbook of school mental health programs: Advancing practice and research (pp. 239–256). New York, NY: Kluwer Academic/Plenum.

Lewis, M. F., Truscott, S. D., & Volker, M. A. (2008). Demographics and professional practices of school psychologists: A comparison of NASP members and non-NASP school psychologists by telephone survey. Psychology in the Schools, 45, 467–482. doi:10.1002/pits.20317

Melchert, T. P., Hays, V. L., Wiljanen, L. M., & Kolocek, A. K. (1996). Testing models of counselor development with a measure of counseling self-efficacy. Journal of Counseling & Development, 74, 640–644. doi:10.1002/j.1556-6676.1996.tb02304.x

Mellin, E. A. (2009). Responding to the crisis in children’s mental health: Potential roles for the counseling profession. Journal of Counseling & Development, 87, 501–506. doi:10.1002/j.1556-6678.2009.tb00136.x

Munson, W. W., Stadulis, R. E., & Munson, D. G. (1986). Enhancing competence and self-efficacy of potential therapeutic recreators in decision-making counseling. Therapeutic Recreation Journal, 20(4), 85–93.

Munson, W. W., Zoerink, D. A., & Stadulis, R. E. (1986). Training potential therapeutic recreators for self-efficacy and competence in interpersonal skills. Therapeutic Recreation Journal, 20, 53–62.

Nabors, L. A., Reynolds, M. W., & Weist, M. D. (2000). Qualitative evaluation of a high school mental health program. Journal of Youth and Adolescence, 29, 1–13.

Powers, J. D., Edwards, J. D., Blackman, K. F., & Wegmann, K.M. (2013). Key elements of a successful multi-system collaboration for school-based mental health: In-depth interviews with district and agency administrators. The Urban Review, 45, 651–670. doi:10.1007/s11256-013-0239-4

President’s New Freedom Commission on Mental Health. (2003). Achieving the Promise: Transforming Mental Health Care in America. Final Report for the President’s New Freedom Commission on Mental Health (SMA Publication No. 03-3832). Rockville, MD: President’s New Freedom Commission on Mental Health.

Ramo, D. E., Prochaska, J. J., & Myers, M. G. (2010). Intentions to quit smoking among youth in substance abuse treatment. Drug and Alcohol Dependence, 106, 48–51. doi:10.1016/j.drugalcdep.2009.07.004.

Rones, M., & Hoagwood, K. (2000). School-based mental health services: A research review. Clinical Child and Family Psychology Review, 3, 223–241. doi:10.1023/A:1026425104386

Sharpe, P. A., Granner, M. L., Hutto, B. E., Wilcox, S., Peck, L., & Addy, C. L. (2008). Correlates of physical activity among African American and white women. American Journal of Health Behavior, 32, 701–713. doi:10.5555/ajhb.2008.32.6.701.

Shernoff, E. S., Kratochwill, T. R., & Stoiber, K. C. (2003). Training in evidence-based interventions (EBIs): What are school psychology programs teaching? Journal of School Psychology, 41, 467–483. doi:10.1016/j.jsp.2003.07.002

Stajkovic, A. D., & Luthans, F. (1998). Self-efficacy and work-related performance: A meta-analysis. Psychological Bulletin, 124, 240–261. doi:10.1037/0033-2909.124.2.240

Stephan, S. H., Weist, M., Kataoka, S., Adelsheim, S., & Mills, C. (2007). Transformation of children’s mental health services: The role of school mental health. Psychiatric Services, 58, 1330–1338. doi:10.1176/appi.ps.58.10.1330

Stephan, S., Westin, A., Lever, N., Medoff, D., Youngstrom, E., & Weist, M. (2012). Do school-based clinicians’ knowledge and use of common elements correlate with better treatment quality? School Mental Health, 4, 170–180. doi:10.1007/s12310-012-9079-8

Suldo, S. M., Friedrich, A., & Michalowski, J. (2010). Personal and systems-level factors that limit and facilitate school psychologists’ involvement in school-based mental health services. Psychology in the Schools, 47, 354–373. doi:10.1002/pits.20475

Sutton, J. M., Jr., & Fall, M. (1995). The relationship of school climate factors to counselor self-efficacy. Journal of Counseling & Development, 73, 331–336. doi:10.1002/j.1tb01759.x

Tang, M., Addison, K. D., LaSure-Bryant, D., Norman, R., O’Connell, W., & Stewart-Sicking, J. A. (2004). Factors that influence self-efficacy of counseling students: An exploratory study. Counselor Education and Supervision, 44, 70–80. doi:10.1002/j.1556-6978.2004.tb01861.x

Urbani, S., Smith, M. R., Maddux, C. D., Smaby, M. H., Torres-Rivera, E., & Crews, J. (2002). Skills-based training and counseling self-efficacy. Counselor Education and Supervision, 42, 92–106. doi:10.1002/j.1556-6978.2002.tb01802.x

Walrath, C. M., Bruns, E. J., Anderson, K. L., Glass-Siegal, M., & Weist, M. D. (2004). Understanding expanded school mental health services in Baltimore city. Behavior Modification, 28, 472–490. doi:10.1177/0145445503259501

Watson, J. C. (2012). Online learning and the development of counseling self-efficacy beliefs. The Professional Counselor, 2, 143–151.

Weist, M. D., Ambrose, M. G., & Lewis, C. P. (2006). Expanded school mental health: A collaborative community-school example. Children & Schools, 28, 45–50. doi:10.1093/cs/28.1.45

Weist, M. D., Evans, S. W., & Lever, N. A. (2003). Handbook of school mental health: Advancing practice and research. New York, NY: Kluwer Academic/Plenum.

Weist, M. D., Lever, N. A., Stephan, S. H., Anthony, L. G., Moore, E. A., & Harrison, B. R. (2006, February). School mental health quality assessment and improvement: Preliminary findings from an experimental study. Paper presented at the meeting of A System of Care for Children’s Mental Health: Expanding the Research Base, Tampa, FL.

Weist, M. D., Sander, M. A., Walrath, C., Link, B., Nabors, L., Adelsheim, S., . . . & Carrillo, K. (2005). Developing principles for best practice in expanded school mental health. Journal of Youth and Adolescence, 34, 7–13. doi:10.1007/s10964-005-1331-1

Weist, M., Lever, N., Stephan, S., Youngstrom, E., Moore, E., Harrison, B., . . . & Stiegler, K. (2009). Formative evaluation of a framework for high quality, evidence-based services in school mental health. School Mental Health, 1, 196–211. doi:10.1007/s12310-09-9018-5

Weist, M. D., Youngstrom, E. A., Stephan, S., Lever, N., Fowler, J., Taylor, L., . . . Hoagwood, K. (2014). Challenges and ideas from a research program on high-quality, evidence-based practice in school mental health. Journal of Clinical Child & Adolescent Psychology, 43, 244–255. doi:10.1080/15374416.2013.833097

Zeldin, A. L., Britner, S. L., & Pajares, F. (2008). A comparative study of the self-efficacy beliefs of successful men and women in mathematics, science, and technology careers. Journal of Research in Science Teaching, 45, 1036–1058. doi:10.1002/tea.20195

 

Bryn E. Schiele is a doctoral student at the University of South Carolina. Mark D. Weist is a professor at the University of South Carolina. Eric A. Youngstrom is a professor at the University of North Carolina at Chapel Hill. Sharon H. Stephan and Nancy A. Lever are associate professors at the University of Maryland. Correspondence can be addressed to Bryn E. Schiele, the Department of Psychology, Barnwell College, Columbia, SC 29208, schiele@email.sc.edu.