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

Kimberly Ernst, Gerta Bardhoshi, Richard P. Lanthier

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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.