Development and Factor Analysis of the Protective Factors Index: A Report Card Section Related to the Work of School Counselors

Gwen Bass, Ji Hee Lee, Craig Wells, John C. Carey, Sangmin Lee

The scale development and exploratory and confirmatory factor analyses of the Protective Factor Index (PFI) is described. The PFI is a 13-item component of elementary students’ report cards that replaces typical items associated with student behavior. The PFI is based on the Construct-Based Approach (CBA) to school counseling, which proposes that primary and secondary prevention activities of school counseling programs should focus on socio-emotional, development-related psychological constructs that are associated with students’ academic achievement and well-being, that have been demonstrated to be malleable, and that are within the range of expertise of school counselors. Teachers use the PFI to rate students’ skills in four construct-based domains that are predictive of school success. School counselors use teachers’ ratings to monitor student development and plan data-driven interventions.


Keywords: protective factors, factor analysis, school counselors, construct-based approach, student development


Contemporary models for school counseling practice (ASCA, 2012) emphasize the importance of school counselors using quantitative data related to students’ academic achievement to support professional decisions (Poynton & Carey, 2006), to demonstrate accountability (Sink, 2009), to evaluate activities and programs (Dimmitt, Carey, & Hatch, 2007), to advocate for school improvement (House & Martin, 1998) and to advocate for increased program support (Martin & Carey, 2014). While schools are data-rich environments and great emphasis is now placed on the use of data by educators, the readily available quantitative data elements (e.g., achievement test scores) are much better aligned with the work of classroom teachers than with the work of school counselors (Dimmitt et al., 2007). While teachers are responsible for students’ acquisition of knowledge, counselors are responsible for the improvement of students’ socio-emotional development in ways that promote achievement. Counselors need data related to students’ socio-emotional states (e.g., self-efficacy) and abilities (e.g., self-direction) that predispose them toward achievement so that they are better able to help students profit from classroom instruction and make sound educational and career decisions (Squier, Nailor, & Carey, 2014). Measures directly associated with constructs related to socio-emotional development are not routinely collected or used in schools. The development of sound and useful measures of salient socio-emotional factors that are aligned with the work of school counselors and that are strongly related to students’ academic success and well-being would greatly contribute to the ability of counselors to identify students who need help, use data-based decision making in planning interventions, evaluate the effectiveness of interventions, demonstrate accountability for results, and advocate for students and for program improvements (Squier et al., 2014).


Toward this end, we developed the Protective Factors Index (PFI) and describe herein the development and initial exploratory and confirmatory factors analyses of the PFI. The PFI is a 13-item component of elementary students’ report cards that replaces typical items associated with student deportment. The PFI is based on the Construct-Based Approach (CBA) to school counseling (Squier et al., 2014), which is based on the premise that primary and secondary prevention activities of school counseling programs should be focused on socio-emotional development-related psychological constructs that have been identified by research to be associated strongly with students’ academic achievement and well-being, that have been demonstrated to be malleable, and that are within the range of expertise of school counselors. The CBA clusters these constructs into four areas reflecting motivation, self-direction, self-knowledge and relationship competence.


The present study was conducted as collaboration between the Ronald H. Fredrickson Center for School Counseling Outcome Research and Evaluation and an urban district in the Northeastern United States. As described below, the development of the PFI was guided by the CBA-identified clusters of psychological states and processes (Squier et al., 2014). With input from elementary counselors and teachers, a 13-item report card and a scoring rubric were developed, such that teachers could rate each student on school counseling-related dimensions that have been demonstrated to underlie achievement and well-being. This brief measure was created with considerable input from the school personnel who would be implementing it, with the goal of targeting developmentally appropriate skills in a way that is efficient for teachers and useful for counselors. By incorporating the PFI into the student report card, we ensured that important and useful student-level achievement-related data could be easily collected multiple times per year for use by counselors. The purpose of this study was to explore relationships between the variables that are measured by the scale and to assess the factor structure of the instrument as the first step in establishing its validity. The PFI has the potential to become an efficient and accurate way for school counselors to collect data from teachers about student performance.




Initial Scale Development

The PFI was developed as a tool to gather data on students’ socio-emotional development from classroom teachers. The PFI includes 13 items on which teachers rate students’ abilities related to four construct-based standards: motivation, self-direction, self-knowledge and relationships (Squier et al., 2014). These four construct clusters are believed to be foundational for school success (Squier et al., 2014). Specific items within a cluster reflect constructs that have been identified by research to be strongly associated with achievement and success.


The PFI assessment was developed through a collaborative effort between the research team and a group of district-level elementary school administrators and teachers. The process of creating the instrument involved an extensive review of existing standards-based report cards, socio-emotional indicators related to different student developmental level, and rating scales measuring identified socio-emotional constructs. In addition, representatives from the district and members of the research team participated in a two-day summer workshop in August of 2013. These sessions included school counselors and teachers from each grade level, as well as a teacher of English language learners, a special education representative, and principals. All participants, except the principals, were paid for their time. Once the draft PFI instrument was completed, a panel of elementary teachers reviewed the items for developmental appropriateness and utility. The scale was then adopted across the district and piloted at all four (K–5) elementary schools during the 2013–2014 school year as a component of students’ report cards.


The PFI component of the report card consists of 13 questions, which are organized into four segments, based on the construct-based standards: motivation (4 items), self-direction (2 items), self-knowledge (3 items) and relationships (4 items). The items address developmentally appropriate skills in each of these domains (e.g., demonstrates perseverance in completing tasks, seeks assistance when needed, works collaboratively in groups of various sizes). The format for teachers to evaluate their students includes dichotomous response options: “on target” and “struggling.” All classroom teachers receive the assessment and the scoring rubric that corresponds to their grade level. The rubric outlines the observable behaviors and criteria that teachers should use to determine whether or not a student demonstrates expected, age-appropriate skills in each domain. Because the PFI instrument is tailored to address developmentally meaningful competencies, three rubrics were developed to guide teacher ratings at kindergarten and first grade, second and third grade, and fourth and fifth grade.


At the same time that the PFI scale was developed, the district began using a computer-based system to enter report card data. Classroom teachers complete the social-emotional section of the standards-based report card electronically at the close of each marking period, when they also evaluate students’ academic performance. The data collected can be accessed and analyzed electronically by school administrators and counselors. Additionally, data from two marking periods during the 2013–2014 school year were exported to the research team for analysis (with appropriate steps taken to protect students’ confidentiality). These data were used in the exploratory and confirmatory factor analyses described in this paper.



The PFI was adopted across all of the school district’s four elementary schools, housing grades kindergarten through fifth. All elementary-level classroom teachers completed the PFI for each of the students in their classes. The assessment was filled out three times during the 2013–2014 school year, namely in December, March and June. The data collected in the fall and winter terms were divided into two sections for analysis. Data from the December collection (N = 1,158) was used for the exploratory factor analysis (EFA) and data from the March collection was randomly divided into two subsamples (subsample A = 599 students and subsample B = 591 students) in order to perform the confirmatory factor analysis (CFA).


The sample for this study was highly diverse: 52% were African American, 17% were Asian, 11% were Hispanic, 16% were Caucasian, and the remaining students identified as multi-racial, Pacific Islander, Native Hawaiian, or Native American. In the EFA, 53.2% (n = 633) of the sample were male and 46.8% (n = 557) of the sample were female. Forty-seven kindergarten students (3.9%), 242 first-grade students (20.3%), 216 second-grade students (18.2%), 222 third-grade students (18.7%), 220 fourth-grade students (18.5%), and 243 fifth-grade students (20.4%) contributed data to the EFA.


The first CFA included data from 599 students, 328 males (54.8%) and 271 females (45.2%). The data included 23 kindergarten students (3.8%), 136 first-grade students (22.7%), 100 second-grade students (16.7%), 107 third-grade students (17.9%), 102 fourth-grade students (17.0%), and 131 fifth-grade students (21.9%). The data analyzed for the second CFA included assessments of 591 students, 305 males (51.6%) and 286 females (48.4%). The data consisted of PFI assessments from 24 kindergarten students (4.1%), 106 first-grade students (17.9%), 116 second-grade students (19.6%), 115 third-grade students (19.5%), 118 fourth-grade students (20.0%), and 112 fifth-grade students (19.0%).



Classroom teachers completed PFI assessments for all students in their class at the close of each marking period using the rubrics described above. Extracting the data from the district’s electronic student data management system was orchestrated by the district’s information technology specialist in collaboration with members of the research team. This process included establishing mechanisms to ensure confidentiality, and identifying information was extracted from student records.


Data Analyses

The PFI report card data was analyzed in three phases. The first phase involved conducting an EFA at the conclusion of the first marking period. The second phase was to randomly select half of the data compiled during the second marking period and perform a confirmatory factor analysis. Finally, the remaining half of the data from the second marking period was analyzed through another CFA.


Phase 1. Exploratory factor analysis. An initial EFA of the 13 items on the survey instrument was conducted using the weighted least squares mean adjusted (WLSM) estimation with the oblique rotation of Geomin. The WLSM estimator appropriately uses tetrachoric correlation matrices if items are categorical (Muthén, du Toit, & Spisic, 1997). The EFA was conducted using Mplus version 5 (Muthén & Muthén, 1998–2007).


Model fit was assessed using several goodness-of-fit indices: comparative fit index (CFI), Tucker-Lewis Index (TLI), root mean square error of approximation (RMSEA), and standardized root mean square residual (SRMR). We assessed model fit based on the following recommended cutoff values from Hu and Bentler (1999): CFI and TLI values greater than 0.95, RMSEA value less than 0.06, and SRMR value less than 0.08.


     Phase 2. First confirmatory factor analysis. An initial CFA was conducted on the 13 items from the instrument survey to assess a three-factor measurement model that was based on theory and on the results yielded through the exploratory analysis. Figure 1 provides the conceptual path diagram for the measurement model. Six items (3, 4, 6, 7, 11 and 13) loaded on factor one (C1), which is named “academic temperament.” Three items (8, 9 and 12) loaded on factor two (C2), which is referred to as “self-knowledge.” Four items (1, 2, 5 and 10) loaded on factor three (C3), which is titled “motivation.” All three latent variables were expected to be correlated in the measurement model.


This CFA was used to assess the measurement model with respect to fit as well as convergent and discriminant validity. Large standardized factor loadings, which indicate strong inter-correlations among items associated with the same latent variable, support convergent validity. Discriminant validity is evidenced by correlations among the latent variables that are less than the standardized factor loadings; that is, the latent variables are distinct, albeit correlated (see Brown, 2006; Kline, 2011; Schumacker & Lomax, 2010).


The computer program Mplus 5 (Muthén & Muthén, 1998-2007) was used to conduct the CFA with weighted least square mean and variance adjusted (WLSMV) estimation. This is a robust estimator for categorical data in a CFA (Brown, 2006). For the CFA, Mplus software provides fit indices of a given dimensional structure that can be interpreted in the same way as they are interpreted when conducting an EFA.


     Phase 3. Second confirmatory factor analysis. A second CFA was conducted for cross-validation. This second CFA was conducted on the 13 items from the instrument survey to assess a three-factor measurement model that was based on the results yielded through the first confirmatory factor analysis. The same computer program and estimation tactics were used to conduct the second CFA.



Phase 1. Exploratory Factor Analysis

Complete descriptive statistics for the responses to each of the 13 items are presented in Table 1. The response categories for all questions are dichotomous and also identified in Table 1 as “On Target” or “Struggling,” while incomplete data are labeled “Missing.” A total of 1,158 surveys were analyzed through the EFA. The decision to retain factors was initially guided by visually inspecting the scree plot and eigenvalues. The EFA resulted in two factors with eigenvalues greater than one (one-factor = 8.055, two-factor = 1.666, and three-factor = 0.869). In addition, the scree test also supported the idea that two factors were retained because two factors were left of the point where the scree plot approached asymptote. However, considering goodness-of-fit indices, the models specifying a three-factor structure and four-factor structure fit the data well. Methodologists have suggested that “underfactoring” is more problematic than “overfactoring” (Wood, Tataryn, & Gorsuch, 1996). Thus, there was a need to arrive at a factor solution that balanced plausibility and parsimony (Fabrigar, Wegener, MacCallum, & Strahan, 1999).

Methodologists (e.g., Costello & Osborne, 2005; Fabrigar et al., 1999) have indicated that when the number of factors to retain is unclear, conducting a series of analyses is appropriate. Therefore, two-, three-, and four-factor models were evaluated and compared to determine which model might best explain the data in the most parsimonious and interpretable fashion. In this case, the two-factor model was eliminated because it did not lend itself to meaningful interpretability. The four-factor model was excluded because one of the factors was related to only one item, which is not recommended (Fabrigar et al., 1999). Researchers evaluated models based on model fit indices, item loadings above 0.40 (Kahn, 2006), and interpretability (Fabrigar et al., 1999).


The three-factor measurement model fit the data well (RMSEA = 0.052, SRMR = 0.036, CFA = 0.994, TLI = 0.988, χ2 = 173.802, df = 42, p < 0.001). As shown in Table 2, the standardized factor loadings were large, ranging from 0.58 to 0.97. The first factor included six items. Items reflected students’ abilities at emotional self-control and students’ abilities to maintain good social relationships in school (e.g., demonstrates resilience after setbacks and works collaboratively in groups of various sizes). This first factor was named “academic temperament.”
The second factor included three items. All of the items reflected the understanding that students have about their own abilities, values, preferences and skills (e.g., identifies academic strengths and abilities and identifies things the student is interested in learning). This second factor was named “self-knowledge.” The third factor included four items. All of the items reflected personal characteristics that help students succeed academically by focusing and maintaining energies on goal-directed activities (e.g., demonstrates an eagerness to learn and engages in class activities). This third factor was named “motivation.” The three-factor measurement model proved to have parsimony and interpretability.


The two-factor model did not fit the data as well as the three-factor model (RMSEA = 0.072, SRMR = 0.058, CFA = 0.985, TLI = 0.978, χ2 = 371.126, df = 53, p < 0.001). As shown in Table 2, the standardized factor loadings were large, ranging from 0.59 to 0.94. The first factor included seven items. This first factor reflected self-knowledge and motivation. It was more appropriate to differentiate self-knowledge and motivation considering interpretability. The two-factor model provided relatively poor goodness-of-fit indices and interpretability.


The four-factor model fit the data slightly better than the three-factor model (RMSEA = 0.035, SRMR = 0.023, CFA = 0.998, TLI = 0.995, χ2 = 76.955, df = 32, p < 0.001). As shown in Table 2, the standardized factor loadings were large, ranging from 0.54 to 1.01. The first factor included one item, however, and retained factors should include at least three items that load 0.05 or greater (Fabrigar et al., 1999), so the first factor was removed. The second factor was comprised of six items that all relate to the construct of academic temperament. The third factor includes four items that reflect motivation. The fourth factor is composed of three items that relate to self-knowledge. The four-factor model was strong in terms of goodness-of-fit indices, though it was not possible to retain the first factor methodologically, due to the fact that it only involved one item. Therefore, given a series of analyses, the three-factor model was selected as the most appropriate.


Phase 2. First Confirmatory Factor Analysis

Complete descriptive statistics for the items are presented in Table 3. The responses for all items were dichotomous. A total of 569 (95.0%) of 599 surveys were completed and were used in the first CFA.





The three-factor measurement model provided good fit to the data (RMSEA = 0.059, CFI = 0.974, TLI = 0.984, χ2 = 104.849, df = 35, p < 0.001). Table 4 reports the standardized factor loadings, which

can be interpreted as correlation coefficients, for the three-factor model. The standardized factor loadings were statistically significant (p < 0.001) and sizeable, ranging from 0.72 to 0.94. The large standardized factor loadings support convergent validity in that each indicator was primarily related to the respective underlying latent variable. Table 5 reports the correlation coefficients among the three latent variables. The correlation coefficients were less than the standardized factor loadings, thus supporting discriminant validity.




Phase 3. Second Confirmatory Factor Analysis

Complete descriptive statistics for the items are presented in Table 3. The type of responses for all items was dichotomous. A total of 564 (95.4%) of 591 surveys had all the items complete and were used in the first CFA.


The second CFA was conducted on the three-factor measurement model to cross-validate the results from the first CFA. The three-factor model provided acceptable fit to the data in this second CFA (RMSEA = 0.055, CFI = 0.976, TLI = 0.983, χ2 = 100.032, df = 37, p < 0.001). Table 4 reports the standardized factor loadings, which can be interpreted as correlation coefficients, for the three-factor model. The standardized factor loadings were significantly large, ranging from 0.70 to 0.93. These large standardized factor loadings support convergent validity in that each indicator was largely related to the respective underlying latent variable. Table 5 reports the correlation coefficients among the three latent variables. The correlation coefficients were less than the standardized factor loadings so that discriminant validity was supported. Given these results, it appears that the three-factor model is the most reasonable solution.




The ASCA National Model (2012) for school counseling programs underscores the value of using student achievement data to guide intervention planning and evaluation. This requires schools to find ways to collect valid and reliable information that provides a clear illustration of students’ skills in areas that are known to influence academic achievement. The purpose of developing the PFI was to identify and evaluate socio-emotional factors that relate to students’ academic success and emotional health, and to use the findings to inform the efforts of school counselors. The factor analyses in this study were used to explore how teachers’ ratings of students’ behavior on the 13-item PFI scale clustered around specific constructs that research has shown are connected to achievement and underlie many school counseling interventions. Because the scoring rubrics are organized into three grade levels (kindergarten and first grade, second and third grade, and fourth and fifth grade), the behaviors associated with each skill are focused at an appropriate developmental level. This level of detail allows teachers to respond to questions about socio-emotional factors in ways that are consistent with behaviors that students are expected to exhibit at different ages and grade levels.


Considering parsimony and interpretability, the EFA and two CFAs both resulted in the selection of a three-factor model as the best fit for the data. Through the EFA, we compared two-, three- and four-factor models. The three-factor model showed appropriate goodness-of-fit indices, item loadings and interpretability. Additionally, the two CFAs demonstrated cross-validation of the three-factor model. In this model, the fundamental constructs associated with students’ academic behavior identified are “academic temperament,” “self-knowledge,” and “motivation.” “Self-knowledge” and “motivation” correspond to two of the four construct clusters identified by Squier et al. (2014) as critical socio-emotional dimensions related to achievement. The “academic temperament” items reflected either self-regulation skills or the ability to engage in productive relationships in school. Squier et al. (2014) differentiated between self-direction (including emotional self-regulation constructs) and relationship skills clusters.


Although not perfectly aligned, this factor structure of the PFI is consistent with the CBA model for clustering student competencies and corresponds to previous research on the links between construct-based skills and academic achievement. Teacher ratings on the PFI seemed to reflect their perceptions that self-regulation abilities and good relationship skills are closely related constructs. These results indicate that the PFI may be a useful instrument for identifying elementary students’ strengths and needs in terms of exhibiting developmentally appropriate skills that are known to influence academic achievement and personal well-being.


Utility of Results

The factor analysis conducted in this study suggests that the PFI results in meaningful data that can allow for data-based decision making and evaluation. This tool has possible implications for school counselors in their efforts to provide targeted support, addressing the academic and socio-emotional needs of elementary school students. The PFI can be completed in conjunction with the academic report card and it is minimally time-intensive for teachers. In addition to school-based applications, the socio-emotional information yielded is provided to parents along with their child’s academic report card. This has the potential to support school–home connections that could prove useful in engaging families in interventions, which is known to be beneficial. Finally, the instrument can help school counselors identify struggling students, create small, developmentally appropriate groups based on specific needs, work with teachers to address student challenges that are prevalent in their classrooms, evaluate the success of interventions, advocate for program support, and share their work with district-level administrators. The PFI could come to be used like an early warning indicator to identify students who are showing socio-emotional development issues that predispose toward disengagement and underachievement.


The PFI also may prove useful as a school counseling evaluation measure. Changes on PFI items (and perhaps on subscales related to the three underlying dimensions identified in the present study) could be used as data in the evaluation of school counseling interventions and programs. Such evaluations would be tremendously facilitated by the availability of data that is both within the domain of school counselors’ work and that is known to be strongly related to achievement.


The findings offer great promise in terms of practical implications for school personnel and parents. This analysis quite clearly illustrates “academic temperament,” “self-knowledge” and “motivation” as factors that are demonstrated to be foundational to school success. The results indicate that the teachers’ ratings of students’ behavior align with findings of existing research and, thus, that the instrument is evaluating appropriate skills and constructs.


Implications for School Counselors

The PFI was developed as a data collection tool that could be easily integrated into schools for the purpose of assessing students’ development of skills that correspond to achievement-related constructs. Obtaining information about competencies that underlie achievement is critical for school counselors, who typically lead interventions that target such skills in an effort to improve academic outcomes. Many developmental school counseling curricula address skills that fall within the domains of “academic temperament,” “self-knowledge,” and “motivation” (see: for a complete list of socio-emotional learning programs). Teachers can complete the PFI electronically, at the same intervals as report cards and in a similarly user-friendly format. Therefore, the PFI facilitates communication between teachers and school counselors regularly throughout the school year. Counselors can use the data to identify appropriate interventions and to monitor students’ responsiveness to school counseling curricula over time and across settings. Although not included in this analysis, school counselors could also measure correlations between PFI competencies and achievement to demonstrate how academic outcomes are impacted by school counseling interventions and curricula.


Limitations and Further Study

Despite the promising findings on these factor analyses, further research is needed to confirm these results and to address the limitations of the present study. Clearly, additional studies are needed to confirm the reliability of PFI teacher ratings and future research should explore inter-rater reliability. Further research also is needed to determine if reliable and valid PFI subscales can be created based on the three dimensions found in the present study. Test-retest reliability, construct validity and subscale inter-correlations should be conducted to determine if PFI subscales with adequate psychometric characteristics can be created. Subsequent studies should consider whether students identified by the PFI as being in need of intervention also are found by other measures to be in need of support. Another important direction for future research is to examine the relationships between teachers’ ratings of students’ socio-emotional skills on the PFI and the students’ academic performance. Establishing a strong link between the PFI and actual academic achievement is an essential step to documenting the potential utility of the index as a screening tool. As this measure was developed to enhance data collection for data-based decision making, future research should explore school counselors’ experiences with implementation as well as qualitative reporting on the utility of PFI results for informing programming.


Although the present study suggests that the PFI in its current iteration is quite useful, practically speaking, researchers may consider altering the tool in subsequent iterations. One possible revision involves changing the format from dichotomous ratings to a Likert scale, which could allow for teachers to evaluate student behavior with greater specificity and which would benefit subscale construction. Another change that could be considered is evaluating the rubrics to improve the examples of student behavior that correspond to each rating on the scale and to ensure that each relates accurately to expectations at each developmental level. Furthermore, most of the items on the current PFI examine externalizing behaviors, which poses the possibility that students who achieve at an academically average level, but who experience more internalizing behaviors (such as anxiety), might not be identified for intervention. Subsequent iterations of the PFI could include additional areas of assessment, such as rating school behavior that is indicative of internalized challenges. Finally, it will be important to evaluate school counselors’ use of the PFI to determine if it actually provides necessary information for program planning and evaluation in an efficient, cost-effective fashion as is intended.

Conflict of Interest and Funding Disclosure

The authors reported no conflict of interest

or funding contributions for the development

of this manuscript.





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Gwen Bass is a doctoral researcher at the Ronald H. Fredrickson Center for School Counseling Outcome Research at the University of Massachusetts. Ji Hee Lee is a doctoral student at Korea University in South Korea and Center Fellow of the Ronald H. Frederickson Center for School Counseling Outcome Research at the University of Massachusetts. Craig Wells is an Associate Professor at the University of Massachusetts. John C. Carey is a Professor of School Counseling and the Director of the Ronald H. Frederickson Center for School Counseling Outcome Research at the University of Massachusetts. Sangmin Lee is an Associate Professor at Korea University. Correspondence can be addressed to Gwen Bass, School of Cognitive Science, Adele Simmons Hall, Hampshire College, 893 West Street, Amherst, MA 01002,


Shelter From the Storm: Addressing Vicarious Traumatization Through Wellness-Based Clinical Supervision

Seth C. W. Hayden, Derick J. Williams, Angela I. Canto, Tyler Finklea

Counselors continually encounter clients who have experienced emotional and psychological trauma. Repeated vicarious exposure to clients’ trauma can affect counselors’ personal and professional wellness. Vicarious traumatization can impair counselors’ current and future clinical work and lead to significant distress. Clinical supervisors can play an important role in assessing and supporting counselors’ wellness related to vicarious traumatization. The purpose of this article is to introduce a framework and related strategies for counseling supervisors based on wellness theory to address vicarious traumatization in counselors. A case study is provided to illustrate an integrated wellness approach to supervision.

Keywords: vicarious traumatization, counselor wellness, clinical supervision, emotional trauma, psychological trauma



Mental health counselors who provide services to traumatized clients (e.g., military personnel, clients who have been victimized, witnesses to traumatic events) help to process traumatic experiences. Consequently, providing therapy to traumatized clients often involves the counselor listening to repeated graphic descriptions of traumatic recollections while remaining empathically engaged during discussions (Moulden & Firestone, 2007). For example, counselors working with military personnel and veterans may be provided information that involves the gruesome details of service members’ recollections, including death (e.g., via combat, witnessed aftermath of execution) and violence to children. In addition, these clients are often struggling to manage their own anxiety dealing with the overall threat to personal survival in combat situations. There also may be instances in which counselors are exposed to clinical concerns such as addictions that may not involve diagnosable traumatic stress but have the potential to be significantly impactful on the therapist. The effect of this vicarious exposure to clients’ experiences can place counselors at risk to be traumatized themselves. This exposure can negatively impact their psychological well-being and contribute to the development of vicarious trauma.


Although there is some discussion within the professional literature regarding vicarious exposure to clients’ traumatizing recollections, limited information is available regarding how to address this issue in supervision. Supervisors may benefit from operating within a theoretical framework to support counselor supervisees’ exposure to vicarious trauma. Given the potential for significant detrimental effects on counselors, it seems imperative to focus attention on vicarious exposure to trauma within the context of clinical supervision.


Trauma and Vicarious Exposure


     Traumatic events have been described as negative, sudden and uncontrollable (Creamer, McFarlane, & Burgess, 2005; Olff, Langeland, Draijer, & Gersons, 2007; Sarri, 2005), often involving serious injury, threats of death or actual death, or challenges to the physical integrity of oneself or another (American Psychiatric Association, 2013). Traumatic experiences often result in a crisis during which an individual is unable to effectively use typical problem-solving methods and can experience frustration and distress with the disruption of daily activities and life goals (Brammer, 1985; Caplan, 1961; James & Gilliland, 2013). Traumatization also can occur when individuals have neither the internal nor external resources to adequately cope with the results of these crisis events (van der Kolk, 1989). It has been stated that traumatic events are not the cause of harm to individuals’ psychological or physical self; it is their reaction to the trauma that leads to harm (Williams, 2006).


In general practice, counselors are often exposed to and affected by trauma-related issues shared by clients (Michalopoulos & Aparicio, 2012). Approximately 70% of 221 mental health workers reported being exposed to moderate or profound amounts of trauma material in a study examining vicarious or secondary exposure to trauma (Kadambi & Truscott, 2004). In an earlier study, 37% of mental health workers reported emotional, physical and mental problems related to secondary trauma associated with their clinical work (Cornille & Myers, 1999). Additional research has confirmed the potential deleterious effects on counselors of continual exposure to clients’ traumatic issues (e.g., Arvay, 2001; Buchanan, Anderson, Uhlemann, & Horwitz, 2006; Figley, 2002; Pearlman & Mac Ian, 1995).


While providing general psychotherapy can affect a counselor both personally and professionally, trauma therapy often has a unique effect on therapists distinctive from general counseling (Pearlman & Mac Ian, 1995). Counselors who work primarily with clients with trauma issues are at a higher risk for developing vicarious trauma than those with a general caseload (Brady, Guy, Poelstra, & Brokaw, 1997; Chrestman, 1995; Cunningham, 1999; Kassan-Adams, 1995; Pearlman & Mac Ian, 1995 Schauben & Frazier, 1995).


Vicarious Traumatization

Figley (1983) suggested “secondary victimization” and “secondary traumatic stress” as terms to characterize the effect of exposing traumatic material to other people. Furthermore, secondary traumatic stress has been defined by Figley (1993) as the natural consequent behaviors and emotions resulting from awareness of a traumatizing event experienced by a significant other and the associated stress resulting from helping or wanting to help. Though similar in its connection to the impact on counselors exposed to the traumatic experiences of clients, vicarious traumatization (VT) possesses unique characteristics in relation to the degree of impact.


VT was later coined as a term to describe the situations in which a counselor experiences intrusive imagery that appear as disruptions to a therapist’s imagery system of memory and yield painful experiences of images and emotions associated with clients’ traumatic memories (Pearlman & Saakvitne, 1995). As described in Moulden and Firestone (2007), the three primary characteristics of VT are: (a) pervasive impact that affects several aspects of therapists’ lives; (b) cumulative effect in that each exposure to the trauma reported by victims increases the risk and impact of the trauma response in the helper; and (c) potentially permanent detrimental emotional and psychological effects such as a change in perspective and imagery. The primary symptoms of VT include disturbances in affect tolerance, cognitive frame of reference, interpersonal relationships, psychological needs and identity (Moulden & Firestone, 2007), with effects that can be profound and long-lasting (McCann & Pearlman, 1990). In contrast, counselors experiencing VT have been found to experience decreased personal and professional sense of well-being, depending on their personal trauma history and length of time working with traumatized clients (Pearlman & Mac Ian 1995). In addition, there is a disrupted sense of safety and altered perceptions of self that are significantly correlated with experiencing negative psychological effects (Culver, McKinney, & Paradise, 2011). There have been indications of positive effects of VT as exposure to vicarious trauma may even result in psychological growth of the counselor (Brockhouse, Msetfi, Cohen, & Joseph, 2011).  Regardless of the nature of the impact, there appears to be unique aspects of providing services to clients experiencing issues of trauma.


Several internal and external factors contribute to the manifestation of VT. Counselors’ personal trauma history, the meaning of traumatic life events to counselors, psychological style, interpersonal style, professional development, and current stressors and supports may all influence the development of VT (McCann & Pearlman, 1990).  Elements faced in the work environment, such as the nature of the clientele and the material they present in therapy, stressful client behaviors, and social and cultural context, also may contribute to VT (McCann & Pearlman, 1990. Though one experience with a client’s traumatic issue can negatively affect the counselor, the manifestation of VT often occurs after repeated exposure to clients’ traumatic narratives (Moulden & Firestone, 2007; Pearlman & Mac Ian, 1995). Due to the potential for counselors to experience VT, organizational support systems to manage the impact of trauma work are needed (Cohen & Collens, 2013). Clinical supervision, when held at regular intervals, provides an opportunity for the identification and remediation of VT to promote the wellness of counselors.


Supervision for Vicarious Traumatization


Lack of training and supervision have been cited as points of concern for counselors at risk for developing VT. For example, Pearlman and Mac Ian (1995) found that trauma therapists who did this work for a shorter period of time and did not receive supervision reported higher levels of disrupted beliefs associated with their clinical work. More recently, Dunkley and Whelan (2006) found that only about a third (27.9%) of the counselors providing trauma therapy via the telephone received supervision.


The literature supports the purported need for supervision among trauma counselors.  In a structured interview of mental health agency directors (n = 5) working in New Orleans post-Hurricane Katrina, all five directors believed that coping strategies and support were necessary for mental health practitioners to continue working with trauma victims (Culver et al., 2011). Similarly, in a recent study with six peer-nominated master therapists, all six stressed the importance of counselors receiving supervision to lower the risk of VT when working with trauma victims (Harrison & Westwood, 2009). Further supporting these findings, Michalopoulos and Aparicio (2012) found that a decrease in VT symptoms can be predicted by high levels of social support. Neumann and Gamble (1995) recommended that supervision be provided by experienced trauma therapists. Given the indications of a need for support of counselors working with trauma victims by clinicians and supervisors, ensuring appropriate supervision of trauma-focused counseling is a necessary component in addressing the impact of the work.


During the process of supervision, it is important for supervisors to be mindful of the potential for VT manifesting in their supervisees. The signs of distress that may become evident in supervision include changes in counselors’ behavior with and reaction to clients, intrusions of client stories in counselors’ lives, signs of burnout, feelings of being overwhelmed, signs of withdrawal in either the counseling or the supervisory relationship, and indications of general stress and decreased self-care (Etherington, 2000). If VT appears present, it is imperative that supervisors address this issue.


A positive relationship between supervisor and supervisee may reduce disruptions in cognitive beliefs (Dunkley & Whelan, 2006). For counselors experiencing symptoms of VT, the supportive supervision environment can promote the counselor’s ability to acknowledge, express and work through these painful experiences (McCann & Pearlman, 1990). When the affective response to the clinical work is not acknowledged and addressed, there is a risk that counselors may be unable to maintain a warm, empathetic and responsive stance in their clinical interactions, thereby increasing risk of harm to clients (McCann & Pearlman, 1990).


Counselor Competence

In relation to the impact of VT on counselors, the American Counseling Association’s Code of Ethics (2014) emphasizes the importance for counselors to address potential impairment (Section C.2.g., F.5.b.) and client welfare (Section F.1.a.). Supervisors play a critical role in this process by providing a context in which impairment of the counselor and by extension the welfare of clients can be addressed. Supervisors are thus ethically obligated to address VT among supervisees as the presence of this condition may limit the capabilities of counselors (F.6.b.). If it becomes apparent that their needs will not be fully met within the context of supervision, a referral for additional mental health counseling for the supervisee may be necessary (F.6.c.).


It is important to note that not every counselor who works with traumatic material develops VT (Moulden & Firestone, 2007). Nonetheless, supervisors of counselors at risk for VT should address the inherent challenges in working with trauma. Failure to provide appropriate supervision, in which counselors are able to address their work with clients, can be considered unethical given the potential harm to the clinician (Sommer & Cox, 2005). Utilizing a theoretically sound, holistic approach in supervision can provide a framework to address the myriad of issues associated with counselor VT.


In addition to accessing mental health assistance if needed, supervision is an important resource for counselors who work with issues of trauma. The manner in which supervision is structured appears critical in the appropriate assessing and remediating of VT. Using a holistic and integrated approach can offer a comprehensive strategy to ensure the well-being of counselors at risk for VT.


Effective Components of Supervision in Relation to VT

     Counselors have noted that engaging in supervision itself is a positive coping strategy to address the impact of working with victims of trauma (Hunter & Schofield, 2006). Researchers have typified effective supervision of trauma counselors into several core elements. Four components of effective supervision of trauma counselors suggested by Pearlman and Saakvitne (1995) are (1) a strong theoretical grounding in trauma therapy; (2) attention to both conscious and unconscious aspects of treatment; (3) a mutually respectful interpersonal climate for supervision; and (4) educational content that directly addresses VT. Similarly, Sommer and Cox (2005) offered four themes of effective supervision and training of counselors at risk for VT: (1) freely discussing personal feelings and reactions to trauma counseling; (2) the need for focused attention on VT, both in supervision and at the agency level; (3) utilizing a gentle, collaborative approach to supervision rather than an expert-based model; and (4) addressing the potential for dual relationships between supervisor and supervisee. In addition, counselors defined good supervision as having two main components: practical case management through advice, direction and reassurance, and a space in which counselors can voice any traumatic incidences or personal reactions arising from their encounter (Hunter & Schofield, 2006). A wellness approach has been offered as a unique framework to address VT within the context of supervision that can be utilized to support counselors working with victims of trauma (Lenz & Smith, 2010). The wellness approach is highlighted henceforth while keeping in mind the majority of the tenets proposed by Pearlman and Saakvitne (1995) and Sommer and Cox (2005).


A Wellness Framework for Supervision

Lenz and Smith (2010) noted that when wellness is an essential part of the supervision process, the effects of trauma can be prevented or mitigated. Models of wellness address physical, mental, social, emotional, and spiritual as well as other aspects of individuals’ lives (e.g., Ardell, 1988; Hettler, 1984; Myers & Sweeney, 2004; Myers, Sweeney, & Witmer, 2000). Wellness has been defined as a way of life focused toward optimal health and well-being. Within this perspective, the body, mind and spirit are integrated, resulting in a life lived more fully within the human and natural community. Fully realized, it is considered a state of optimal health and well-being that each individual is capable of achieving.  This is a condition that exists on a continuum as opposed to an end state (Myers et al., 2000; Roscoe, 2009).


Lenz and Smith (2010) introduced the Wellness Model of Supervision (WELMS). Supervisors engaging in this approach are able to address issues that arise in supervision in a fluid and adaptable manner. The authors emphasized a process for educating supervisees about wellness, assessing supervisees’ level of wellness, evaluating wellness throughout the supervisory relationship, and developing strategies to address supervisees’ personal wellness. In a study by Lenz, Sangganjanavanich, Balkin, Oliver, & Smith (2012), when comparing WELMS to alternate approaches to supervision, individuals assigned to the WELMS group developed more comprehensive persona definitions of wellness in addition to increasing their total wellness over the span of 10 weeks.


Alternately, the Indivisible Self Model of Wellness (IS-Wel; Myers & Sweeney, 2004) is an evidence-based model of wellness (Hattie, Myers, & Sweeney, 2004; Myers & Sweeney, 2004) that can be applied to help supervisees address the conscious and unconscious effects of VT as it relates to: (1) Coping Self (e.g., stress and burnout); (2) Essential Self (e.g., identity and self-care); (3) Creative Self (e.g., professional/work well-being and emotions); (4) Physical Self (e.g., physical health and eating habits); and (5) Social Self (e.g., interpersonal relationships and expressions of love). The IS-Wel model (Myers & Sweeney, 2004) may have particular utility in addressing VT, given the holistic and interconnected nature of the model. Additionally, this model incorporates the opportunity for formal assessment of the five factors described above using the Five Factor Wellness Inventory (5F-Wel; Myers & Sweeney, 2005)


In regard to the relationship between supervisor and counselor, Sommer and Cox (2005) recommended that trauma-sensitive supervision should utilize a collaborative strengths-based approach and should include time for talking about the effects of the work and concomitant personal feelings. A collaborative relationship that focuses on the strengths of supervisees also is a cornerstone to the wellness approach (Myers & Sweeney, 2008). An IS-Wel approach to supervision is structured to provide opportunities for supervisees to reflect on their emotional and cognitive resources to deal with the effects of VT. The purpose of this paper is to integrate the aforementioned wellness and supervision models into an overall wellness approach to the process of supervision for VT.


Process of Supervision Using an Integrated Wellness Model


Wellness Approach With VT

In the initial work of utilizing a wellness approach, supervisors assist supervisees with evaluating their own wellness. An informal assessment of the counselor is performed noting not only the content of the supervisee’s discussion, but also his/her disposition, affect, and associated thinking as the supervisee articulates case material. Supervisors also attend specifically to, and assess for, features of VT (e.g., change in perspective, cognitive frame of reference). In cases where there is concern for the potential for VT, the supervisor would intentionally inquire about the recurrence and intrusiveness of case material in the supervisee’s personal life as well as other symptoms of VT.


Formal assessment of wellness can be accomplished via the IS-Wel model (Myers & Sweeney, 2004) using the previously mentioned 5F-Wel inventory (Myers & Sweeney, 2005). As a standardized measure, this instrument provides not only normative references, but also an opportunity for discussion of one’s definition of wellness. The respondents indicate their agreement on a scale ranging from strongly disagree to strongly agree to an array of questions such as “I am satisfied with how I cope with stress,” “I eat a healthy amount of vitamins, minerals, and fiber each day,” and “I often see humor even when doing a serious task” (Myers & Sweeney, 2005). There are additional demographic questions used to provide a description of the various characteristics of the supervisee. The supervisor uses the wellness assessment data to determine the impact of the exposure to traumatic material on the counselor’s physical and psychological well-being.


Supervisors use the results of the wellness assessment as an opportunity to discuss wellness with the counselor. Specifically, supervisors discuss the results, educate the supervisee about wellness and collaborate with the supervisee to develop a plan for strategies to address VT using a strengths-based approach (Sommer & Cox, 2005). At this juncture, it is suggested that supervisors take the facilitator role rather than that of an expert (Lenz & Smith, 2010).


Working within the supervisory relationship, supervisors may suggest coping strategies for supervisees to mitigate the stress associated in working with victims of trauma. Personal coping mechanisms include counselors maintaining a balance of work, play and rest (Pearlman & Mac Ian, 1995; Trippany, White Kress, & Wilcoxon, 2004), and cultivating skills to decrease one’s negative reaction to stress such as a mindfulness practice (Rybak, 2013). Supervisors and supervisees can co-create intervention strategies to attend to potential reactions related to the supervisees’ clinical work.  Self-care on the part of counselors is an important component of lessening the potential effects of VT (Sommer & Cox, 2005) and can be considered an aggregated result of the various elements of the IS-Wel (Myers & Sweeney, 2004). Supervisors also can support counselors at risk for VT by continually evaluating the wellness of their supervisees throughout the supervision process.


A key element of an integrated wellness approach is to be adaptable to the needs of a diverse population of supervisees. Learning the multicultural identity of supervisees early in the supervisory alliance can assist in creating a supportive supervisory climate, identifying key beliefs and potential resources that may come to bear in maintaining counselor wellness. Considering the diverse needs of supervisees at all junctures, but especially when a heightened likelihood of impairment exists, can be a critical element of effectively preventing and remediating VT.


Connectivity and Caseload Management

In the application of the integrated wellness approach within counseling supervision, supervisors can be strategic in helping supervisees mitigate the VT response. In order to empower supervisees to be active agents in assessing and enhancing their wellness, supervisors can provide specific information regarding the integrated model of wellness. This can be beneficial to both parties offering a common reference point to be used throughout supervisees’ clinical work. Embedding elements of the integrated model into different modalities of supervision (i.e., individual, triadic, and group) can also reinforce critical elements of this approach. Equipped with this information, supervisees can be the primary manager of their own wellness with the supervisor serving in a facilitative and supportive role.


To ensure meaningful engagements on the part of supervisees allowing for examination of the five elements of the IS-Wel (i.e., Coping Self, Essential Self, Creative Self, Physical Self, Social Self), supervisors can encourage their supervisees to increase collegial interaction and avoid professional isolation. Formal or informal support groups may be an adjunctive venue in which these components are assessed and remediated when appropriate. Evidence suggests that support groups for professionals who deal with trauma issues in their clinical work are a useful tool (McCann & Pearlman, 1990). Discussion regarding these resources can occur both at the beginning of the supervisory relationship and at appropriate times when a supervisee appears at risk for VT.


Apart from support groups, supervisors can take an active role to support the Coping Self by monitoring the amount of traumatized clients assigned to a counselor. As noted earlier, the amount of exposure to client trauma is related to VT in counselors (Pearlman & Mac Ian, 1995). Managing counselors’ caseloads through monitoring and limiting the number of trauma clients can minimize the potential vicarious effects of working with traumatized clients (Trippany et al., 2004). According to Pearlman and Mac Ian (1995), this can minimize the cumulative effect of counselors’ work with clients with traumatic experiences. For example, the caseload of traumatized clients could be equally distributed among qualified providers so as to avoid overwhelming or overloading a counselor at risk for VT, even if trauma therapy is the expertise of only one or a few in the agency. Training for those not specializing in this topic can broaden the number of counselors equipped to address this issue. Additional professional development opportunities, such as workshops focused on trauma therapy, may also help other agency personnel become more comfortable in providing services to traumatized clients.


In the following section, a composite case is provided to illustrate the integrated wellness approach to supervision with counselors treating traumatized clients. In this example, the clinical supervisor is working with a counselor who has several clients struggling with issues of trauma related to military experiences. This case incorporates the previously discussed strategies but is not the only potential response clinical supervisors may utilize to address the counselor’s issues. It is suggested that the reader consider the adaptability of the case to their own supervisory interactions.


Case Study of Richard


Richard was a licensed professional counselor working in a community mental health agency near a U.S. Marine Corps military installation. This installation had several military personnel who returned from deployment in which they were involved in active combat. Although a civilian agency, the counselors on staff provided services to many military personnel and veterans. Thus, this agency was often identified as a resource to military service members and their families.


Richard did not have a personal history of military service, but had extended family members who were military veterans. He had a passion for assisting soldiers who were struggling with issues of trauma related to their combat service. As a result, Richard attended several trainings on combat-related psychological trauma and was also familiar with military culture based on his experiences growing up in a family connected to the military.


Sarah, Richard’s clinical supervisor, was tasked with assigning the military referrals to various counselors. An unintended trend developed in which clients who endorsed trauma symptoms were assigned to Richard due to his interest in this area. Richard’s caseload began with two or three new referrals a month related to the return of a military division from deployment. As time passed, the frequency of referrals increased significantly to eight to nine new referrals per month. Thus, an informal protocol was established in which Richard was designated as the primary counselor for those reporting trauma issues, mostly combat-related PTSD, sleep disturbance and interpersonal difficulties. Richard initially indicated his appreciation for the opportunity to work with this population as he was honored to serve them in this capacity.


Initially excited to assist these clients, Richard started exhibiting changes in his personal and professional perspectives. In his conversations with his colleagues, Richard expressed he had been ruminating about some of the gruesome details that his clients described in trauma counseling sessions. He also expressed feeling generally overwhelmed in relation to his work in the agency. Richard stated that a majority of his clients seemed to have significant traumatic experiences and that he felt emotionally drained at the end of his time with them due to the intensive nature of his clinical work. In a group supervision meeting, Richard shared that he found himself thinking more about his clients’ issues while away from work, often contributing to difficulty being psychologically present with his family and friends.


Structure of Supervision

As his supervisor, Sarah followed an integrated wellness approach to address the counseling and professional issues discussed with supervisees. Her approach to supervision involved working collaboratively with supervisees and educating them about wellness throughout the supervision process. Using informal and formal assessments, Sarah assisted supervisees in evaluating their personal wellness. She then worked with her supervisees to co-construct a holistic wellness plan. She used the IS-Wel model of wellness (Myers & Sweeney, 2004, 2005) to address specific aspects of wellness including Coping Self (e.g., stress and burnout), Essential Self (e.g., identity and self-care), Creative Self (e.g., professional/work well-being and emotions), Physical Self (e.g., physical health and eating habits), and Social Self (e.g., interpersonal relationships and expressions of love). Sarah often administered the 5F-Wel (Myers & Sweeney, 2005). She would discuss elements of the wellness approach both in individual and group supervision meetings, ensuring congruence and consistency of her approach across the different methods of supervision. The information gathered from this assessment would be used to determine areas of focus in Sarah’s work with her supervisees.



In Sarah’s subjective assessment of Richard, she noticed changes in his disposition from his previous affable state to a more pessimistic outlook on his personal and professional life. In a subsequent supervision meeting, Richard discussed the trauma experiences of his clients in depth and became tearful when discussing a client who had witnessed the death of his unit members due to an improvised explosive device. Sarah further assessed how Richard’s counseling experiences were affecting his perceptions of his clients in relation to the context of their clinical work. Additionally, she inquired about how clients’ trauma recollections were affecting Richard’s professional life, personal relationships and level of self-care.


Through this informal assessment, Sarah discovered that Richard lacked hope in his clients’ ability to overcome their symptoms related to trauma experiences. He reported withdrawing from family and friends in addition to constantly thinking about his clients’ trauma experiences. It appeared that Richard was being negatively impacted both personally and professionally by his engagement with his clients’ trauma-related concerns.


Concerned for Richard’s well-being, Sarah aimed to provide a supportive environment to help him work through his painful experiences. Sarah determined she would use the context of supervision to assess his well-being and acknowledged the potential for a referral for counseling for Richard if deemed necessary. In her interactions with Richard, Sarah continually affirmed her interest in Richard’s personal and professional development and inquired into his activity apart from work. She emphasized the collaborative aspect of supervision and created a supportive environment via the use of empathy, non-judgmental interaction and willingness to allow him to direct their discussion.


Sarah formally evaluated Richard’s wellness using the 5F-Wel inventory (Myers & Sweeney, 2005). She believed that the comprehensive nature of this evaluation tool would provide Richard with an understanding of various aspects of his well-being, while also providing him with an understanding of the interconnectedness of his overall functioning. Richard was initially unsure of the shift of focus within supervision from his clients to him, but was willing to engage given his self-disclosed struggles. Sarah provided a detailed rationale for the shift, indicating her sense that Richard appeared to be significantly impacted by his work with his clients. Sarah made sure to ground the discussion in the importance of Richard’s clients receiving quality assistance, differentiating her role as his supervisor despite the personal nature of their focus on Richard. She requested that Richard be willing to share if he felt the conversation seemed too much like a counseling interaction.


Evaluation and Results

Richard was provided with the results of the 5F-Wel assessment (Myers & Sweeney, 2014), including a visual profile of his overall wellness. Given the results of the 5F-Wel, Richard noted that his Physical Wellness (i.e., exercise and nutrition) score was low, yet he was satisfied with the physical aspects of his life. He also noted that his Social Self (i.e., friendship and love), Coping Self (i.e., leisure, stress management, self-worth, and realistic beliefs), and aspects of his Creative Self (i.e., thinking, emotions, positive humor, work, and control) were low. He expressed satisfaction with the high score on the Essential Self domain (i.e., spirituality and gender identity).



In their next session, Sarah and Richard discussed his wellness. Using the profile of his 5F-Wel results, she explained to Richard that all aspects of his wellness are interconnected, and a change in one domain can impact other aspects of his well-being. Despite the empirical support for the assessment, Sara explained that the results of his evaluation should be interpreted with caution as various aspects can influence the results such as his mood during the administration process, interpretation of specific items on the inventory and his understanding of the words in each item.


To help Richard connect the assessment results with the self-assessment of his wellness, Sarah asked Richard to informally rate his current wellness on a scale of 1 to 10. This number was then compared to the results on the formal inventory. Richard rated his wellness as a 4. This was repeated within each area of the wellness perspective.


Sarah spent the remainder of this supervision session educating Richard on aspects of his wellness using the accompanying definitions presented in the wellness profile (see Myers & Sweeney, 2011). The two of them discussed Richard’s positive and negative reactions to the results. They then processed the possible reasons why scores on certain aspects of wellness were low or high. Sarah explained that positive, high levels of wellness can be used to address lower levels of wellness.


Stress Reduction Plan

Richard chose to develop a plan, with Sarah’s help, for addressing the stress related to VT. Sarah helped Richard explore various strategies that would support his efforts for improving his wellness in the Coping Self (i.e., stress management) area. Richard and Sarah outlined activities that addressed Richard’s Physical Self, an area in which Richard scored slightly lower than his self-perception in this area. Given the interconnectedness of the domains, Sarah suggested increased physical activity to positively affect his stress management and improve problematic sleeping patterns as a result of VT. Specifically, Richard decided to add resistance training to his normal four-day-per-week cardiovascular exercise.


Almost immediately, Richard sensed an improvement in Physical Self and in his sleep patterns. Richard also noticed the indirect effects of these activities on some other aspects of his wellness. For example, he was able to meet more people while at the gym (an improvement in Social Self), and became more grounded spiritually (the time he spent in cardiovascular exercise allowed him time to reflect on the spiritual aspects of his life). However, Richard’s overall stress level had not improved.


Despite this change in activity, Sarah noticed that Richard’s stress management skills had seemingly regressed in that he reported an increase in his level of anxiety as he would prepare for his sessions. The two believed that now that Richard spent more time addressing and mobilizing the physical aspects of his life, he had less time to complete work-related tasks, increasing his stress level. Though Richard enjoyed the noted improvements, his concern for his time management and decreased coping suggested to him that these activities were not addressing the negative effects of VT and his overall wellness.


Thus, Sarah helped Richard choose alternate activities to address the stress management and self-worth issues related to VT. Richard chose to review the positive aspects of his Creative Self (e.g., work) in determining this plan. They decided that Richard might benefit by examining his work schedule to optimize time devoted to developing other aspects of his life to assist in coping with the traumatic material he was exposed to via his clients. It was hoped that strategically adjusting his work schedule also would provide him an opportunity to reach work-related goals.


Sarah became conscious of the number of traumatized clients she assigned to Richard. She also focused the next couple of group supervision meetings on the concept of VT to assist Richard as well as other counselors on staff to process their reaction to their clinical work. Sarah used the time in group supervision to educate the staff of symptoms indicative of the potential harmful consequences of working with traumatized clients. She also added a formal case presentation component to the group supervision meetings to allow further processing and debriefing for the counselors. She specifically encouraged Richard to attend available professional development activities. Richard’s ongoing supervision continually involved discussion of his well-being, focusing on his work with clients as well as his sleep patterns and stress levels.


Over a period of a few weeks, Richard’s stress management and self-worth improved. Though initially hesitant to engage in the shift in focus, he expressed appreciation for Sarah’s ability to educate him regarding the interconnectedness of his wellness, her ability to continually evaluate all aspects of his wellness, her sense of helping him create plans to live a full life, and her support in addressing the symptoms related to VT for the improvements he had experienced. In her approach, she balanced offering a supportive environment while still serving the role of supervisor, as is consistent with previous literature on addressing VT in counseling supervision (Berger & Quiros, 2014). In the future, Sarah endeavored to more equitably distribute clients with trauma concerns to other staff members and provide training to those new to this type of work.


Case Study Summary

This case was provided to illustrate the potential manifestation and remediation of VT within a supervisory relationship utilizing an integrated wellness approach. Readers may find details of this example not applicable to their specific experience, as there exists significant variance in the characteristics of clients, counselors and supervisors. This discussion does, however, provide a framework in which an integrated wellness approach can be implemented within clinical supervision to prevent and remediate VT.


Future Considerations


Given the potential impact of clinical work on counselors, supervisors would benefit from considering comprehensive and integrated approaches to supervision. There is a need to establish best practices in intervening when counselors demonstrate signs of VT. While prevention of this concern is ideal, VT may still occur, requiring interventions to alleviate this condition. Further examination both in research and practice regarding ways in which a supervisor can effectively intervene by utilizing specific approaches with a counselor with VT is still needed.


Additional empirical examination of theoretical approaches in supervision, such as wellness models to address VT, would be a useful contribution in assisting supervisors to effectively support their supervisees. While the wellness approach appears applicable to identifying and remediating VT, more research studies investigating the effectiveness of this approach would further the body of knowledge pertaining to strategies for addressing VT. Although wellness is one approach, other approaches may complement this framework, including existential-based conversations on meaning attributed to clinical interactions, as well as discussions regarding the impact of this type of work on the counselor. Given the severity of impact on counselors at risk, future research on identifying empirically validated approaches for addressing VT within the clinical supervision context is warranted.




Repeated exposure to clients with trauma-based issues can lead to cognitive, behavioral and emotional disturbance in the counselor, potentially leading to VT. The lack of training and quality supervision for counselors providing trauma therapy is a systemic issue contributing to the development of VT. Clinical supervisors are in a unique position to identify and remediate this issue. Quality supervision can be an effective deterrent and intervention for this potentially harmful condition. Supervisors can emphasize the positive aspects of counselors’ work and encourage engagement in self-care. Ensuring that supervisees who address traumatic concerns are supported in their work can significantly benefit both counselors and their clients.

Conflict of Interest and Funding Disclosure

The authors reported no conflict of interest

or funding contributions for the development

of this manuscript.






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Seth C. W. Hayden, NCC, is an Assistant Professor of Counseling at Wake Forest University. Derick J. Williams, NCC, is an Assistant Professor and Program Area Director of the Counselor Education Program School Counseling Specialty Area at the University of Virginia. Angela I. Canto is an Assistant Professor in the Psychological and Counseling Services program area at Florida State University. Tyler Finklea is a doctoral candidate in the Combined Counseling and School Psychology program at Florida State University and a graduate intern in the American University Counseling Center. Correspondence can be addressed to Seth C. W. Hayden, Wake Forest University, 1834 Wake Forest, Winston-Salem, NC 27106,