The Impact of Student Success Skills on Students’ Metacognitive Functioning in a Naturalistic School Setting

Brett Zyromski, Melissa Mariani, Boyoung Kim, Sangmin Lee, John Carey

This study evaluated the impact of the Student Success Skills (SSS) classroom curriculum delivered in a naturalistic setting on the metacognitive functioning of 2,725 middle and high school students in Kentucky. SSS was implemented as one intervention to fulfill an Elementary and Secondary School Counseling Grant. Results in students’ self-reports indicated that those who received the intervention demonstrated increased ability to regulate their levels of emotional arousal. No additional significant differences were found. These findings differ from the results of previous outcome studies involving SSS. Implications for implementing SSS in naturalistic school settings and directions for future research are discussed.

Keywords: Student Success Skills, naturalistic, metacognitive functioning, classroom curriculum, emotional arousal

The purpose of this study was to evaluate the impact of the Student Success Skills (SSS) school counseling curriculum (Brigman, Campbell, & Webb, 2004; Brigman & Webb, 2012) delivered in a naturalistic setting on students’ metacognitive functioning. In this case, the authors use the term naturalistic setting to describe a typical school environment, one which lacks the additional supports (e.g., hiring national trainers) that would be present in a more controlled research study. SSS is an evidence-based, school counselor-delivered, social-emotional learning intervention that is designed to support students by teaching them three integral skill sets: (a) cognitive and metacognitive skills (e.g., goal setting, progress monitoring and memory skills); (b) social skills (e.g., interpersonal skills, social problem solving, listening and teamwork skills); and (c) self-regulation skills (e.g., managing attention, motivation and anger). Research has identified this curriculum as important in promoting students’ academic achievement and success in school (Collaborative for Academic, Social, and Emotional Learning, 2015; Webb & Brigman, 2006).
SSS was designed based on reviews of educational psychology research literature that identified critical skills such as information processing, emotional self-management, and positive social skills needed for student success (Bransford, Brown, & Cocking, 1999; Durlak, Weissberg, Dymnicki, Taylor, & Schellinger, 2011; Greenberg et al., 2003; Hattie, Biggs, & Purdie, 1996; Marzano, Pickering, & Pollock, 2001; Masten & Coatsworth, 1998; Wang, Haertel, & Walberg, 1994; Zins, Weissberg, Wang, & Walberg, 2004). The curriculum (Brigman & Webb, 2012) can be delivered in two formats: (1) the SSS classroom program and (2) the SSS small group program (Brigman et al., 2004), both of which are intended for use with students in grades 4 through 12. SSS is a highly structured, manualized program that consists of weekly 45-minute lessons. The classroom format includes five lessons, while the small group program includes eight lessons. Both sets of weekly lessons are intended to be delivered in chronological order over the corresponding number of consecutive weeks. A 45-minute booster session is delivered once a month for 3 months in the spring.

Developers of SSS designed the curriculum to follow a scripted, manualized format; implementers are encouraged to follow the sequencing, format and language provided in order to ensure fidelity of treatment. If practitioners go “off-script” or change the recommended delivery of the lessons, it may result in less favorable outcomes that might not meet the same levels as have been found in past research. That being said, the SSS program comes with detailed manuals that include recommended verbiage, descriptive diagrams and supplemental handouts (Brigman & Webb, 2012). During each lesson, students learn and practice strategies in five distinct areas: (a) goal setting, progress monitoring and success sharing; (b) creating a caring, supportive and encouraging classroom environment;
(c) cognitive and memory skills; (d) calming skills; and (e) building healthy optimism. Specific strategies are taught and practiced each week and are reviewed and reinforced during subsequent lessons. Between lessons, students are encouraged to apply the new strategies that were taught and to work on the academic and personal goals that they set for themselves during the SSS session. Teachers also are expected to cue students to use the strategies during regular classroom lesson time.

 

Research has established the effectiveness of SSS in several quasi-experimental and experimental studies. SSS implementation has resulted in enhanced academic achievement as measured by standardized achievement tests (Brigman & Campbell, 2003; Brigman, Webb, & Campbell, 2007; C. Campbell & Brigman, 2005; Webb, Brigman, & Campbell, 2005) and district math and reading achievement measures (Lemberger, Selig, Bowers, & Rogers, 2015). Two studies have suggested that the effects of SSS on academic achievement are at least partially mediated by changes in students’ metacognitive functioning (Lemberger & Clemens, 2012; Lemberger et al., 2015). Lemberger and Clemens (2012) found that participation in SSS small groups was associated with improvements in students’ executive functions (as measured by the Behavior Rating Inventory of Executive Function [BRIEF]; Gioia, Isquith, Guy, & Kenworthy, 2000) and increased metacognitive activity (as measured by the Junior Metacognitive Awareness Inventory [Jr. MAI]; Sperling, Howard, Miller, & Murphy, 2002). Lemberger et al. (2015) found that participation in the classroom version of SSS was associated with improvement in executive functions (as measured by the BRIEF-SR; Guy, Isquith, & Gioia, 2004).

 

While researchers have established the efficacy of SSS in well-controlled research environments, little is known about its effectiveness when delivered in naturalistic settings. The purpose of the present study was to measure the effectiveness of the SSS curriculum when delivered in a naturalistic setting within regularly functioning schools. In this study, SSS was implemented in five schools in a district in Kentucky as part of a school counseling improvement project funded by an Elementary and Secondary School Counseling Demonstration Grant awarded by the U.S. Department of Education. The five middle and high schools collaborated together through a regional educational cooperative to apply for the grant. Demographic information for each school can be found in the Setting section below. The grant funded all necessary SSS curriculum materials and provided support for school counselors in evaluating the impact of the program. However, funding was not available to hire national trainers. National trainers are not a requirement when purchasing a manualized school intervention and many schools do not possess the funds needed to hire national trainers. Thus, this funded project provided an opportunity to evaluate the effectiveness of SSS in a naturalistic school setting.

 

The primary evaluation question was: When implemented in a naturalistic setting, does SSS impact students’ metacognitive functioning, as determined by (1) knowledge and regulation of cognition as measured by the Junior Metacognitive Awareness Inventory (Jr. MAI; Sperling et al., 2002) and (2) use of skills related to self-direction of learning, support of classmates’ learning, and self-regulation of arousal as measured by the Student Engagement in School Success Skills survey (SESSS; Carey, Brigman, Webb, Villares, & Harrington, 2013)? The secondary question was: Does the magnitude of any changes in metacognitive functioning depend on the degree to which SSS was implemented with fidelity?

Method

 

Setting

Five participating schools were chosen due to their participation in the Elementary and Secondary School Counseling grant. Specific population and demographic data related to all five schools can be found in Table 1.

 

Table 1

 

Brief Description of the Five Schools in the Study

 

School Enrollment& Grades Served Location Ethnicity Rates Gender Rates Socio-Economic Indicators
School 1 1,484 StudentsGrades 9–12 Suburban/Rural African American-0.8%American Indian-0%Asian American-1.2%

European American-95.8%

Hispanic American-0.9%

Two or More Races-1.2%

 

Female-50.2%Male-49.8% Qualifying for Free
Lunch-28%Qualifying for Reduced Lunch-7.6%
School 2 1,154 StudentsGrades 6–8 Suburban/Rural African American-1.1%American Indian-0.1%Asian American-0.7%

European American-94.1%

Hispanic American-2%

Two or More Races-2%

 

Female-49%Male-51% Qualifying for Free Lunch-33.5%Qualifying for Reduced Lunch-7.8%
School 3 325 StudentsGrades 7–12 Urban African American-2.8%American Indian-0%Asian American-0.6%

European American-95.1%

Hispanic American-1.2%

Two or More Races-0.3%

 

Female-54.5%Male-45.5% Qualifying for Free Lunch-68.6%Qualifying for Reduced Lunch-8.6%
School 4 570 StudentsGrades 6–8 Rural African American-1.4%American Indian-0%Asian American-0.2%

European American-97.5%

Hispanic American-0.5%

Two or More Races-0.4%

 

Female-48.4%Male-51.6% Qualifying for Free Lunch-50.5%Qualifying for Reduced Lunch-7.9%
School 5 471 StudentsGrades 6–8 Urban African American-11.5%American Indian-0.4%Asian American-0.4%

European American-69%

Hispanic American-10%

Two or More Races-7.9%

 

Female-45.2%Male-54.8% Qualifying for Free Lunch-62.2%Qualifying for Reduced Lunch-6.4%

Note: The demographic categories are listed as reported by the state reporting system.

 

Participants

A total of 2,725 students participated in the study with roughly equal numbers of male (50.1%) and female (49.9%) students. A relatively large percentage of participants (41.2%) qualified for free or reduced lunch. Less than 1% of participants were classified as Limited English Proficient and 11.2% qualified for special education services. In terms of racial and ethnic diversity, the participants were less diverse than desired. Eighty-five percent of participating students identified as White (non-Hispanic), 4% as Multiracial, 6% as African American, and 4% as Hispanic. All other groups combined accounted for the remaining 1% of participants. Proportionally more sixth-, seventh-, and eighth-grade students participated in the study. The percentages of participants by grade were: 20.5% sixth grade; 20.9% seventh grade; 20% eighth grade; 10.7% ninth grade; 9.9% tenth grade; 9.2% eleventh grade; and 8.7% twelfth grade.

 

Completed Jr. MAI surveys (pretest and posttest) were obtained from 1,565 students (57% of the total). Completed SESSS surveys were obtained from 1,612 students (59% of the total). School counselors were required by the grant to serve as point persons for the delivery and collection of pre- and post-instruments. School counselors also were trained on instrument collection using a structured, scripted protocol. Instruments were administrated in paper format. Although trained in data collection procedures, not all participating school counselors successfully captured both pre- and post-assessments. Issues around successfully collecting paper instruments contributed to the loss of data. For example, 4% of the Jr. MAI surveys were incomplete and 4% of the SESSS surveys were incomplete. Rather than estimating missing data in these instances, it was determined that only data from fully complete instruments would be used in the analyses.

 

Preparation of the School Counselors

An SSS manual was provided to each of the schools the year prior to implementation of the program. School counselors reviewed the SSS materials and met with the grant project manager to discuss the content and instructional processes associated with the SSS classroom guidance interventions. Again, school counselors within the five schools did not receive formal training from the national SSS trainers on how to implement the curriculum. Formal training was a cost not included in the grant. The lack of formal training reflected the more naturalistic approach to the study. More often than not, school counselors that purchase a manualized program do not have the funding to hire national trainers to guide implementation. School counselors review the manual and follow the manualized program during implementation. This approach was reflected in this study. School counselors at each school used the SSS curriculum manuals and did their best to adhere to the recommended lesson sequence and scripts (Brigman & Webb, 2012). Next, the school counselors at each school conducted a pilot SSS small group in the spring semester, prior to the onset of the whole-school SSS implementation. The intent of the pilot implementation was to ensure that the school counselors were thoroughly familiar with the materials and implementation procedures. After conducting the pilot studies, the school counselors provided 3 hours of SSS training to partner teachers prior to implementation of the whole-school SSS intervention. The teachers in all schools also received a copy of the SSS classroom manual (Brigman & Webb, 2012) to review prior to implementing the curriculum with their students. Delivery of the SSS classroom format began the subsequent fall semester (2013) and concluded the following spring (2014).

 

 

Procedures for Delivering SSS and Fidelity Issues

In every school, the school counselors experienced some problems implementing the SSS curriculum with fidelity. Implementing the program with complete fidelity would have reflected the exact scope and sequence scripted within the SSS manual, mainly delivering the program over a 45-minute time period once a week for 5 consecutive weeks. Schools varied from this scope and sequence, resulting in a lack of fidelity of the recommended implementation format for SSS. However, schools adjusted delivery of SSS in a way that reflected their educational priorities, again reflecting a more naturalistic approach than a traditional controlled research study. The primary resistance school counselors encountered related to teachers’ and administrators’ reluctance to lose instructional time as a consequence of in-class implementation of SSS. Each school identified a contextually appropriate approach to addressing this initial resistance to devoting class time to SSS. In two of the schools, teachers (rather than counselors) delivered the SSS curriculum within their own classrooms. In the other three schools, the SSS curriculum was delivered through learning communities (i.e., advisories), which are existing scheduled blocks of time during which teachers facilitate small groups (8–15 students) outside their normal classrooms. For example, a ninth-grade biology teacher might be responsible for leading a group of students across several grades with whom the teacher does not interact outside of this learning community. The manner in which SSS was delivered in each school is detailed below.

 

School One. The SSS curriculum was not delivered with complete fidelity. Instead, the school leadership determined it was more feasible for teachers to deliver the curriculum through learning communities, once a week for 30 minutes for 10 weeks.

 

School Two. The SSS curriculum was delivered with reasonable fidelity once a week for 60 minutes over a 5-week period by teachers. However, instead of being delivered in a traditional classroom format, the school leadership determined it more feasible to deliver the curriculum through learning communities.

 

School Three. SSS was delivered with reasonable fidelity. Five teachers (trained and supervised by the school counselor) delivered the SSS curriculum in the prescribed format detailed in the SSS classroom manual. The five teachers delivered SSS to all students in the school through various courses, including a study skills course (seventh and eighth grades), a social studies course (ninth grade), a biology course (tenth grade), a college readiness course (eleventh grade) and an English course (twelfth grade).

 

School Four. The SSS curriculum was delivered with reasonable fidelity to all grade levels (sixth through eighth) during social studies courses. The social studies teachers were trained and supervised by the school counselor to deliver the program.

 

     School Five. The SSS curriculum was not delivered with complete fidelity. The school leadership determined it more feasible to deliver the curriculum through learning communities two to three times a week for 25 minutes for each session over a 5-week period.

 

Procedures for Collecting SESSS and Jr. MAI Data

Pretest data were collected at the beginning of the 2013 school year and posttest data were collected in late April and early May of the 2013–2014 school year, before the end-of-grade standardized testing ensued. Prior to beginning the project, school counselors completed a Collaborative Institutional Training Initiative to alert them to issues relating to voluntary participation and confidentiality. School counselors were then trained to follow an instrument administration manual (developed for the project) so that they could administer the SESSS and the Jr. MAI in a standardized fashion. They administered the SESSS and the Jr. MAI using standardized, scripted procedures. In order to protect the confidentiality of the students, school counselors changed the student identification numbers for each student by adding a randomly determined number for each school. No other person besides the school counselor knew the number by which the student identification numbers were changed. All data were kept in a locked file cabinet in the primary investigator’s office. Data were entered into a database, which was saved on an encrypted, password-protected hard drive. As an additional safeguard, the data from each school were saved on an external hard drive and transported by hand to the primary investigator’s office.

 

Instruments

 

Junior Metacognitive Awareness Inventory (Jr. MAI)

The present study used the 18-item version of the Junior Metacognitive Awareness Inventory (Jr. MAI; Sperling et al., 2002), a self-report scale that has two subscales that measure students’ knowledge of cognition and regulation of cognition. The Jr. MAI is used to screen learners for potential metacognitive and cognitive strategy interventions. Sperling et al. (2002) developed two versions of the Jr. MAI based on the Metacognitive Awareness Inventory (Schraw & Dennison, 1994). The 12-item version was developed for students in grades 3 through 5, while the 18-item version was developed for older students.

 

Available evidence suggests that the Jr. MAI and its subscales are reliable. Sperling et al. (2002) reported an internal consistency-based reliability estimate of .82 for the overall scale. Sperling, Richmond, Ramsay, and Klapp (2012) reported an internal consistency reliability of .76 for the knowledge of cognition subscale and .80 for the regulation of cognition subscale. Sperling et al. (2002) found that the Jr. MAI total score (for both versions of the instruments) correlated with other direct measures of student metacognition, but not with teachers’ ratings of students’ metacognitive abilities. Relatedly, Sperling et al. (2012) found the student scores on the 18-item version of the Jr. MAI correlated significantly with their scores on the Swanson Metacognitive Questionnaire (SMQ; Swanson, 1990), their science grade point average and their overall grade point average.  Recently, the 12-item version of the Jr. MAI was used to measure the impact of SSS on students’ metacognitive functioning. Lemberger and Clemens (2012) found that SSS delivered in small group format to fourth- and fifth-grade students resulted in measurable increases in Jr. MAI scores.

 

Student Engagement in School Success Skills (SESSS) Survey

The study also employed the Student Engagement in School Success Skills (SESSS) survey. The SESSS (Carey et al., 2013) is a 27-item scale that was developed to measure the extent to which students use strategies that have been shown to be related to enhanced academic achievement (Hattie et al., 1996; Masten & Coatsworth, 1998; Wang et al., 1994). The SESSS has three subscales that measure students’ self-direction of learning, support of classmates’ learning and self-regulation of arousal.

 

Carey et al. (2013) found in an exploratory factor analysis of the SESSS scores of 402 fourth through sixth graders that a four-factor solution provided the best model of scale dimensionality considering both the solution’s clean factor structure and the interpretability of these factors. However, in a confirmatory factor analysis study (Brigman et al., 2014) using SESSS scores from a diverse sample of almost 4,000 fifth-grade students, researchers found that while a four-factor model fit the data well, the scales associated with two subscales correlated so highly (r = .90) as to be indistinguishable. Consequently, the items associated with the two factors were combined and the subsequent three-factor model also proved to better fit the data.

 

Brigman et al. (2014) suggested that the SESSS is best thought of as having three underlying factors corresponding to self-direction of learning, support of classmates’ learning, and self-regulation of arousal. Based on factor loadings, Brigman et al. (2014) created three SESSS subscales. The self-direction of learning subscale (19 items) reflects the students’ intentional use of cognitive and metacognitive strategies to promote their own learning. The support of classmates’ learning subscale (six items) reflects the students’ intentional use of strategies to help classmates learn effectively. Finally, the self-regulation of arousal subscale (three items) reflects students’ intentional use of strategies to control disabling anxiety and cope with stress.

 

Available data indicate that the SESSS is a reliable assessment tool. Carey et al. (2014) reported an overall alpha coefficient of 0.91. Furthermore, Villares et al. (2014) reported that the coefficient alphas for the three SESSS subscales (self-direction of learning, support of classmates’ learning and self-regulation of arousal) were .89, .79 and .68, respectively.

 

Data Analysis

In order to answer the current study’s research questions, the authors conducted separate multivariate analysis of variance (MANOVA) with a repeated measure (pretest-posttest time) for the Jr. MAI and the SESSS. In the Jr. MAI, the two subscales (knowledge of cognition and regulation of cognition) were the dependent variables. For the SESSS MANOVA, the three subscales (self-direction of learning, support of classmates’ learning, self-regulation of arousal) were the dependent variables.

 

After performing the MANOVAs, follow-up repeated measures of analysis of variance (ANOVA) were conducted, where appropriate, to determine the significance of the pretest-posttest changes for individual subscales. Effect sizes (Cohen, 1988) also were calculated to determine the magnitude of pretest-posttest change in subscale associated with the intervention. For significant subscale changes, effect sizes were compared across schools to ascertain whether the level of fidelity of SSS implementation was related to the intervention’s size of effect.

 

Results

 

MANOVA analyses with a repeated measure (pretest-posttest) were performed to determine the differences between Jr. MAI and SESSS subtests across the pretest-posttest time periods in order to answer the primary evaluation question. The primary question was: When implemented in a naturalistic setting, does SSS impact students’ metacognitive functioning, as determined by (1) knowledge and regulation of cognition as measured by the Jr. MAI (Sperling et al., 2002) and (2) use of skills related to self-direction of learning, support of classmates’ learning and self-regulation of arousal as measured by the SESSS (Carey et al., 2013)? The results of these MANOVAs are shown in Table 2. For the Jr. MAI, the repeated measures MANOVA revealed a significant difference (F (1, 1562) = 3267.47, p < .00l) between the two subscales (knowledge of cognition and regulation of cognition). However, no significant difference existed between the pretest and posttest time points. The interaction effect of main effects, subscale and time was not significant.

 

Table 2

 

Repeated Measure MANOVA:  Effects of SSS on Students’ Metacognitive Activity

 

Dependent Measures                          Jr. MAI                        SESSS
Main effects
Subtest

        3267.47***

                       356.24***
Time

.3900

                       19.84***
Interaction effect
Subtest * Time

  1.4400

28.25***

Note. ***p<.001

 

     In contrast, SESSS repeated measures MANOVA revealed both a significant main effect of Subscale (F (2, 1610) = 356.24, p < .00l) and a significant interaction effect of Subscale x Time (F (2, 1610) = 28.25, p < .00l). Figure 1 shows that the self-regulation of arousal subscale (subscale 3) corresponded to a significantly greater mean change across time, compared to the self-direction of learning (subscale 1) and the support of classmates’ learning (subscale 2) subscales.

 

Figure 1. Pre-Post SSS Treatment Changes in Metacognitive Functioning and Success Skill Use: Means for Jr. MAI and SESSS subtests at Pretest (Time 1) and Posttest (Time 2).

 

Jr. MAI                                                                     SESSS

 

 

For Jr. MAI Subtest 1 = Knowledge of Cognition and Subtest 2 = Regulation of Cognition

For SESSS Subtest 1 = Self-Direction of Learning, Subtest 2 = Support of Classmates’ Learning,
and Subtest 3 = Self-Regulation of Arousal

 

Based on these MANOVA results, authors conducted follow-up repeated measures ANOVAs in order to test the significance of pretest-posttest changes for all three SESSS subscales. Only the SESSS self-regulation of arousal subscale indicated a significant change (F (1, 1610) = 46.147, p < .001) over time, reflecting a self-reported increase in students’ abilities to regulate their levels of potentially debilitating arousal after SSS participation. As shown in Table 3, the effect size of the self-regulation of arousal subscale (Cohen’s d = -.18) pretest-posttest change would be classified as small (Cohen, 1988).

 

 

Table 3

 

Effect Sizes of ANOVAs with Repeated Measures (T1 and T2) for Jr. MAI and SESSS

 

Pre

Post

Cohen’s d

Component

M

SD

M

SD

Knowledge of Cognition

3.18

.83

3.16

.85

+.02

Regulation of Cognition

3.96

.60

3.96

.65

+.00

The Self-Direction of Learning

2.32

.65

2.33

.66

-.02

The Support of Classmates’ Learning

2.59

.74

2.63

.74

-.05

The Self-Regulation of Arousal

2.16

.88

2.32

.87

-.18

 

     The secondary research question was: Does the magnitude of any changes in metacognitive functioning depend on the degree to which SSS was implemented with fidelity? Implementation fidelity was not strongly related to SSS effect size. Cohen’s d effect sizes (Cohen, 1988) were computed for each school to assess the impact of SSS on self-regulation of arousal. Schools 2, 3 and 4 (who had reasonable fidelity of implementation) had effect sizes of .20, .17 and .26 respectively. Schools 1 and 5 (who had the greatest deviation from implementation fidelity) reported effect sizes of .30 and .13, respectively. Therefore, the schools in this study showed considerable variability in effect sizes (.13 to .30). School differences across other factors (e.g., experience levels of SSS leaders, grade levels of students) may have contributed to this variability.

 

In summary, although significant findings were not found for pre- and posttests related to the Jr. MAI, significant findings were found for the SESSS subscale self-regulation of arousal (p < .001), indicating that students increased their ability to regulate levels of potentially debilitating arousal after participating in the SSS intervention. Examination of Cohen’s d effect sizes suggested that implementation fidelity, or the amount that schools varied from the scope and sequence laid out in the SSS manuals, did not correlate to level of effect size. This result suggests that the SSS intervention resulted in positive outcomes even when practitioners modified the scope and sequence to fit the needs of their setting.

 

Discussion

 

Evaluation Question 1. Does SSS delivered in a naturalistic setting impact students’ metacognitive functioning? The results of the present study suggest that when implemented in a naturalistic setting, SSS can be expected to result in statistically significant increases in students’ abilities to regulate potentially debilitating emotional arousal. These enhanced abilities might reasonably be expected to result in benefits related to improved academic performance (Durlak et al., 2011) and better school behavior (perhaps helping students increase their self-control related to daily interpersonal conflict and stressful events; Galla & Wood, 2015). The overall effect of SSS on emotional self-regulation, while statistically significant, was comparatively small. The present study failed to find evidence that SSS influenced other aspects of students’ metacognitive functioning, including their knowledge of cognition, regulation of cognition, use of strategies related to the self-direction of learning, or use of strategies to support fellow classmates’ learning.

 

     Evaluation Question 2. Does the magnitude of any changes in metacognitive functioning depend on the degree to which SSS was implemented with fidelity? While the schools in this study showed considerable variability in effect sizes, implementation fidelity was not strongly related to SSS effect size. For example, School 1 scored lowest on implementation fidelity, but demonstrated the greatest effect size (.30). The degree of departure from fidelity was not large enough to detract from SSS’s effect on students’ self-regulation of arousal.

 

Relationship to Previous SSS Findings

The present study failed to replicate the results of previous studies that found significant effects of SSS on students’ metacognition (Lemberger & Clemens, 2012; Lemberger et al., 2015). While the present study as well as Lemberger and Clemens’ study (2012) both used the Jr. MAI to measure changes in students’ metacognition, the two studies differed in terms of SSS delivery format (classroom vs. small group). The failure to replicate Jr. MAI-measured changes after SSS participation may be related to differences in the format (classroom vs. group) for SSS delivery, or to differences in the delivery context (naturalistic vs. controlled).

 

While this study and the Lemberger et al. (2015) study both delivered the SSS classroom format, these studies differed in the instruments they used to measure students’ metacognitive functioning (the SESSS and Jr. MAI vs. the BRIEF). Differences in results may be related to differences in instrumentation or to differences in the delivery context (naturalistic vs. controlled).

 

Limitations

     A limitation of this study is the use of a one-group pre-post design rather than a quasi-experimental design with a control group. Study researchers were constrained by the practical realities of the school environment, such that it was not feasible to implement SSS in such a way as to result in a comparison group. In addition, researchers were unable to locate similar schools that were willing to have students participate in a comparison group. Since it is not always feasible to employ a control group design, a one-group pre-post design may be used to attempt to replicate the findings of stronger research studies and can point to findings that need to be investigated later using stronger evaluation designs (D. T. Campbell & Stanley, 1963; Shadish, Cook & Campbell, 2001).  The present evaluation, in fact, furthers the understanding of the effects of SSS and highlights directions for future research.

 

The failure to collect data in some schools resulted in losses of both the Jr. MAI and the SESSS data. Corresponding complete pretest and posttest surveys were obtained from only 57% and 59% of participating students, respectively. While the lack of strong control over data collection can be thought of as an inherent problem in natural setting evaluations, care should be taken in future studies to strengthen data collection processes, as it is difficult to speculate on the impact of the loss of data in this study. Loss of data in smaller studies could be extremely harmful to the validity of the study. In the present study, there was no reason to believe that the loss of data was related to students’ reactivity to the intervention; however, it is possible that this loss impacted the results, and additional studies are needed to address this issue.

 

Implications for Future Research

It is important to understand the extent and nature of SSS’s impact on students’ metacognitive functioning, whether SSS’s well-established impact on academic performance (Brigman & Campbell, 2003; Brigman, Webb, & Campbell, 2007; C. Campbell & Brigman, 2005; Lemberger et al., 2015; Webb et al., 2005) is mediated by changes in students’ metacognitive functioning or other variables, and whether the impact on academic performance is related to general improvements in all students or an improvement in the functions of specific groups of students. Larger-scale intervention studies are needed to understand relationships between SSS proximal changes in students’ abilities and functioning (e.g., metacognitive functioning, emotional self-regulation, engagement, self-efficacy and motivation) and distal changes in students’ academic performance. It is important to understand which proximal changes in students are mediating their distal improvements in academic performance. It could be that SSS’s effects on academic performance are mediated by one or several of these variables. It also could be that SSS’s effects on academic performance are mediated by relatively broad variables (e.g., self-efficacy) that would be expected to be evident in virtually all students or that are relatively specific (e.g., reductions in debilitating test anxiety) and would be expected to be evident in only some students.

 

Understanding the mediator(s) of SSS’s effects on academic performance would be useful in identifying the most appropriate target groups for this intervention. As such, future studies are needed to explore whether SSS is most appropriate as a Tier 1 intervention for all students or as a Tier 2 intervention for some groups of “at-risk” students. Given that the results of the present study suggested that SSS helped students who struggled with self-regulation of arousal, it is especially important to examine the effectiveness of SSS as a Tier 2 intervention, specifically for students who demonstrate difficulties with emotional self-regulation. Finally, further research is needed to determine the practical significance of SSS on academic performance when it is implemented in less controlled, more naturalistic settings, and to determine how deviations from implementation fidelity and other contextual factors (e.g., expertise of the SSS leaders) correspond to expected social-emotional and academic achievement-related outcomes.

 

Implications for Practice

The results of the present study indicated that SSS, even when implemented in a naturalistic school setting (as opposed to a highly controlled setting), can have a positive impact on students’ abilities to regulate their emotional arousal. The magnitude of the overall impact of SSS on students’ ability to regulate arousal appears to be relatively small. However, readers should note that this effect size was computed based on students in the general population, not students experiencing difficulties with emotional self-regulation. It is likely that SSS would have had a larger estimated effect size if the target group of participants was those who had emotional self-regulation difficulties. However, the SSS curriculum positively impacted student outcomes even when the program was not implemented as designed. Though practitioners are encouraged to follow the manual and schedule as recommended, the results are encouraging in that impacts can still be found even if practitioners modify the design.

 

Conflict of Interest and Funding Disclosure

The authors reported no conflict of interest

for the development of this manuscript.
This project was supported by an Elementary and
Secondary School Counseling Demonstration
Grant project from the Department of Education
no. S215E13422.

 

 

 

References

 

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Brett Zyromski is an Assistant Professor at The Ohio State University. Melissa Mariani is an Assistant Professor at Florida Atlantic University. Boyoung Kim is a Research Professor at Korea University. Sangmin Lee is an Associate Professor at Korea University. John Carey is a Professor at the University of Massachusetts Amherst. This project was supported by an Elementary and Secondary School Counseling Demonstration Grant project from the Department of Education, no. S215E13422. Correspondence can be addressed to Brett Zyromski, Department of Educational Studies, Counselor Education, PAES Building, 305 W. 17th Ave., Columbus, OH, zyromski.1@osu.edu. 

Human Sex Trafficking in America: What Counselors Need to Know

Stacey Diane A. Litam

The social justice issue of human sex trafficking is a global form of oppression that places men, women and children at risk for sexual exploitation. Although a body of research exists on the topics of human trafficking, literature specific to the mental health implications for counselors working with this population is limited. Counselors should increase their awareness of the vulnerabilities that place persons at risk of becoming trafficked. Additionally, obtaining a deeper understanding of the indicators and processes through which persons become trafficked is necessary in order to provide appropriate services. Counselors should learn how force, fraud and coercion influence the wellness of trafficked persons. The following article provides an overview of the relevant information pertinent to sex trafficking and addresses the counseling implications for working with sex trafficked survivors.

 

Keywords: human sex trafficking, sexual exploitation, social justice, trafficked survivors, oppression

 

The sexual exploitation of men, women and children through sex trafficking continues to occur in the United States and across the globe at an increasingly alarming rate. Despite misconceptions that sex trafficking requires transportation across state or country borders, the majority of victims are domestically trafficked within their own country by persons of the same nationality (Shelley, 2010; U.S. Department of State, 2009). Rates of forced labor are unknown and notoriously difficult to obtain due to methodological deficiencies (Fedina, 2015) and issues related to reporting and victim identification (Chesnay, 2013; Hyland, 2001; Laczko & Gramegna, 2003). However, the International Labour Organization (n.d.) estimates 27 million people become trafficked annually—4.5 million of whom are victims of forced sexual exploitation. Children and adolescents are exceptionally vulnerable to forced entry into the sex trade. The National Center for Missing and Exploited Children (2014) reported that 1 in 5 runaways are at risk for forced sexual exploitation. This represents an increase from an estimated 1 in 6 in 2014 (Polaris, 2016). Additionally, a study conducted by Estes and Weiner (2002) estimated that 326,000 youth are at risk for child trafficking. Counselors must become educated in recognizing the signs of trafficked persons, vulnerabilities to becoming trafficked, and the processes by which persons are forced into sexual exploitation in order to obtain a deeper understanding of the client’s worldview and provide appropriate support.

 

Existing literature addressing the mental health needs of sex trafficked survivors remains extremely limited (Hossain, Zimmerman, Abas, Light, & Watts, 2010; Tsutsumi, Izutsu, Poudyal, Kato, & Marui, 2008). Instead, the current body of research has focused on the sexual consequences of trafficking-related health issues such as sexually transmitted infections and rates of HIV among trafficked women in Asia (Beyrer, 2001; Beyrer & Stachowiak, 2003; Silverman et al., 2006; Silverman et al., 2007). The following article provides a brief overview of the definition, terms and processes associated with human trafficking. Next, the vulnerabilities and signs that a person has been or is currently being trafficked are presented. Finally, we address the clinical implications of working with trafficked survivors and identify trauma-sensitive interventions. Although female pronouns are used in this article, this detail is not intended to minimize the fact that many cisgender men, as well as lesbian, gay, bisexual and transgender persons, become victims of forced sexual exploitation (Martinez & Kelle, 2013; Oram, Stöckl, Busza, Howard, & Zimmerman, 2012).

Definition, Terms and Processes of Sex Trafficking

 

Despite the growing awareness of modern day slavery, the act of human trafficking is not a new phenomenon. In Imperial Rome, it has been estimated that between 30–40% of the Roman population was comprised of slaves trafficked from nearby countries such as Thrase, Gaul, Britain and Germany (Collingridge, 2006). In fact, during the height of the Roman Empire, wars were fought solely to procure more slaves (Cahill, 1995; Goldsworthy, 2006). Human trafficking was not limited to European countries. Beginning in 1619, both White and African slaves were taken from their countries and imported to Virginia to help construct the colonies (D. Davis, 2006; Jordan & Walsh, 2007). Human trafficking and modern day slavery are acts of social injustice that have historically exploited men, women and children.

 

According to the Trafficking Victims Protection Act (U.S. Department of State, 2000), the act of human trafficking refers to the recruitment, harboring, transportation, provision or obtaining of a person for commercial sex through force, fraud or coercion, or in which the person induced to perform a sex act is under 18 years of age. Despite common misconceptions, for an act to be considered sex trafficking, forced movement across the state is not required (U.S. Department of State, 2000). Sex trafficking includes a wide variety of traditionally accepted forms of labor, including commercial sex, exotic dancing and pornography (Logan, Walker, & Hunt, 2009). The following sections address the three components of control associated with human trafficking, namely force, fraud and coercion. Specific strategies used by traffickers to obtain and maintain control also are described.

 

Force

As defined by the United States Department of Health and Human Services (2012), force pertains to the physical restraint or serious physical harm that traffickers use to obtain and maintain control. According to Chesnay (2013), methods of force are typically used to break down the victim’s spirit. Examples of force as a means of control include rape, physical violence, intimidation, physical confinement and restricted freedom (Williamson & Prior, 2009; Zimmerman et al., 2008). Traffickers may introduce an addiction to an illicit substance or use existing drug or alcohol addictions to force persons into exploitative circumstances (Raphael & Ashley, 2008; Raymond et al., 2002; Whitaker & Hinterlong, 2008; Williamson & Prior, 2009; Zimmerman, 2003). According to findings by Whitaker and Hinterlong (2008), victims’ resistance often leads to additional or more forceful control mechanisms used by traffickers. For example, traffickers may initially use physical or sexual violence and increase the severity (e.g., burning or torturing victims) when disobeyed. Additionally, Whitaker and Hinterlong discovered the presence of gendered patterns of control or the concept that different strategies are used when eliciting compliance from men and women (e.g., use of threats to community members and drug addiction in men, and threats to family relationships and references about the world being dangerous in women). It is important to note that not all trafficked persons experience physical suffering (Aradau, 2004; Belser, 2005).

 

Fraud

     Fraud, or the use of false promises to lure persons into the human trafficking industry, is another method used by traffickers to control and exploit their victims (United States Department of Health and Human Services, 2012). Although fraud is typical in labor trafficking scenarios (e.g., women are offered appealing job opportunities overseas as a nanny or model and then forced into prostitution upon arrival), this tactic also is employed within sex trafficking scenarios (Belser, 2005; Whitaker & Hinterlong, 2008). Traffickers may recruit children from low-income families by promising parents that their children will be safer, better cared for and taught a useful skill or trade (Albanese, 2007; U.S. Department of State, 2009). Once recruited, victims enter into debt bondage and are promised freedom upon repayment to traffickers for their services (Williamson et al., 2010). Unfortunately, the result of debt bondage is a never-ending cycle from which victims cannot escape (Chesnay, 2013). Upon incurring a debt, persons in forced labor scenarios become trapped as traffickers enforce high interest rates, withhold payment, and charge for miscellaneous expenses such as the cost for food, transportation, condoms, and other supplies (International Labour Organization, 2005). Albanese (2007) described one case in which traffickers used fraud after recruiting two girls from Vancouver, British Columbia, and transporting them to Hawaii. In this scenario, the traffickers withheld the girl’s passports and threatened to circulate photographs of them engaging in sex acts in order to obtain their compliance. For many victims of forced labor, fraud is a strategy used by traffickers to exploit dreams or hope for a better life (U.S. Department of State, 2009).

 

Coercion

     Coercion, or using threats of physical harm or physical restraint against a person, is another context of control associated with human trafficking (United States Department of Health and Human Services, 2012). Coercion can take the form of direct physical violence or be psychological in nature (Logan et al., 2009; U.S. Department of State, 2009). In many cases, traffickers coerce victims by threatening to harm their families if they do not comply with their demands (Whitaker & Hinterlong, 2008; Williamson & Prior, 2009). Coercive tactics can directly exploit cultural beliefs, such as the case described by Whitaker and Hinterlong (2008) in which a victim believed she had to obey a trafficker because he kept a lock of her hair. Homeless youth who lack resources (e.g., food, protection, drugs) become coerced by adults that provide shelter and later demand “payment” in the form of sex (Hagan & McCarthy, 1997, p. 48). Although some victims are controlled by traffickers, others are coerced into sexual exploitation by boyfriends, girlfriends and friends (Hagan & McCarthy, 1997; Widom & Kuhns, 1996). Traffickers may coerce their victim’s compliance through the use of a grooming process (Herman, 1992) in which a connection is forged between victims and their traffickers in order to produce intense loyalty (Priebe & Suhr, 2005). When threats, force or coercion is used for the purpose of exploitation, victim consent is not relevant (Logan, 2007).

 

     The grooming process. The seasoning, or grooming, process refers to the progression of power used by traffickers to control their victims and, in some cases, forge a trauma bond (Smith, Vardaman, & Snow, 2009). Similar to “Stockholm syndrome,” in which hostages relate to and defend their captors (Smith et al., 2009), trauma bonding is a form of coercive control in which traffickers instill a sense of fear as well as gratitude for being allowed to live (United States Department of Health and Human Services, 2012). As outlined by O’Connor and Healy (2006), the grooming process stages are ensnaring, creating dependence, taking control, and total dominance. During the ensnaring phase, traffickers begin to identify themselves as a trustworthy and valuable person in the victim’s life (O’Connor & Healy, 2006). Traffickers may provide favors, purchase expensive gifts, show affection and enter into a romantic relationship with the victim (Albanese, 2007). For many adolescents, this façade may represent the only affirming, reliable and secure relationship in their lives, and victims quickly find themselves emotionally invested. Next, traffickers create dependence. During this process, victims gradually become separated from their families and friends (O’Connor & Healy, 2006). Traffickers may convince victims that other persons in their lives are unreliable or untrustworthy. At the completion of this stage, victims begin to rely solely on their traffickers for support and become isolated from their previous lives (O’Connor & Healy, 2006). The taking control stage is characterized by a shift in the traffickers’ behavior from caring and supportive to controlling and possessive (O’Connor & Healy, 2006). The trafficker may begin to use threats, violence and drugs as methods of control and dictate whom the victim sees and where she goes (Whitaker & Hinterlong, 2008). At the end of this stage, traffickers may test the victims’ commitment to the relationship and demand that they begin selling commercial sex to prove their love (O’Connor & Healy, 2006). Once victims have become completely dependent on their traffickers and are convinced that the easiest way to earn money and maintain their relationships is through selling sex, total dominance has been achieved (O’Connor & Healy, 2006). Although the grooming process outlined by O’Connor and Healy is a helpful model that represents how many persons become trafficked, these series of stages may not occur in every case. Persons may enter the commercial sex trade through a variety of avenues, and their experiences of becoming trafficked may be consistent with, or distinct from, O’Connor and Healy’s model.

 

Contexts of Control

Just as variability exists within the stages of grooming, different factors influence whether the grooming process itself results in victim compliance. Traffickers use a variety of recruitment techniques and forms of exploitation to obtain and maintain control (Shelley, 2010). Contexts of control acknowledge the complex associations that influence the relationship between victim and trafficker (Whitaker & Hinterlong, 2008). These factors include the individual resiliencies of trafficked persons, the grooming process, and the methods of force, fraud and coercion used by traffickers (Whitaker & Hinterlong, 2008). According to Whitaker and Hinterlong (2008), the four contexts of control include control-seeking, control mechanisms, controllability and resistance. The context of control-seeking refers to the trafficker’s desire to limit the victims’ choices in order to increase the likelihood that their desires are met (Whitaker & Hinterlong, 2008). Traffickers with higher rates of control-seeking seek more power over victims’ behaviors, appearance and travel (Whitaker & Hinterlong, 2008). They may determine what victims wear, control how they interact with buyers, confine persons to specific locations, identify and enforce a mandatory amount of earnings per day, or withhold passports, money and identifying documents (Whitaker & Hinterlong, 2008; Zimmerman, 2003). Traffickers use control mechanisms (e.g., threats of violence, debt bondage, psychological intimidation and acute violence) to obtain and maintain control of victims, and they may vary depending on the victims’ level of controllability, or capacity to resist due to their social or financial context, cultural or personal beliefs, physical limitations, or other deficiencies (Shelley, 2010; Whitaker & Hinterlong, 2008). Thus, a trafficker may attempt to recruit a young woman by showering her with expensive gifts and affection, but if she demonstrates a low level of controllability (e.g., she has a strong support system, is financially stable, has high self-efficacy), the control mechanisms are less effective (Whitaker & Hinterlong, 2008). Controllability can be further delineated into six subdomains: social, financial, physical, cultural, psychological and institutional (Whitaker & Hinterlong, 2008). Persons with a strong combination across these six subdomains have lower controllability levels and are less likely to become trafficked through the grooming process (Whitaker & Hinterlong, 2008). Because trafficked people are unable to predict or manage events that influence their health and safety, the methods of control in human trafficking are parallel to the characteristics of abuse described in the literature on torture (Saporta & Van der Kolk, 1992).

 

Vulnerabilities and Risk Factors

 

     The market for commercial sex represents a diverse avenue that incorporates a wide spectrum of activities and transactions across many settings (Anderson & O’Connell Davidson, 2003). Although survivors of human trafficking are not limited to race, ethnicity, age, gender or socioeconomic status, vulnerabilities such as location, poverty, sexual minority status and childhood trauma history, among other factors, influence higher rates for potential sexual exploitation (Albanese, 2007;  Bales, 2007; Hyland, 2001; Kidd & Liborio, 2011; Martinez & Kelle, 2013). The following section outlines a variety of risk factors that have been linked to entrance into the sex trafficking trade.

Location as Risk Factor

Within the global human trafficking industry, there are origin and destination countries that influence the direction of movement and likelihood that persons become victims of forced sexual exploitation (Bales, 2007). Often, third world countries are origin countries characterized by locations with a large supply of available victims (Bales, 2007). The country may be in a state of conflict and social unrest or have high rates of poverty, government corruption and a lack of viable employment opportunities (Bales, 2007). Because trafficking is strongly linked to rates of poverty and minimal employment opportunities (Loff & Sanghera, 2004), many people willingly go with traffickers believing they will receive better opportunities abroad and can send money home to their families (Chung, 2009). Once recruited from origin countries, survivors are transported to destination countries, characterized by locations with high demand for commercial sex (Bales, 2007). Some locations, such as the United States, are bidirectional countries, in which victims are both recruited and put to work (Farr, 2005).

 

Although many persons become trafficked across international borders, the majority of victims in the United States are trafficked domestically (U.S. Department of State, 2009), with an increase of minors recruited from the Midwest (Williamson & Prior, 2009). In a study of 13 youth involved with forced sexual exploitation, respondents explained that recruitment occurred on the streets, while walking to friends’ houses, with peers, at corner stores, at malls, at their own homes, and waiting to meet with a probation officer outside the juvenile justice center (Williamson & Prior, 2009). In most cases, youth were approached by someone they knew, a mutual acquaintance, or people they recognized from their community (Williamson & Prior, 2009). Thus, counselors need to become familiar with recruitment cities, destination cities and bidirectional cities (Williamson & Prior, 2009). Recruitment and destination cities respectively refer to locations where persons are obtained and transported to meet the growing demand for commercial sex (K. Davis, 2006). Although victims may become recruited and forced into sexual exploitation in any city across the United States, smaller cities in the Midwest have been linked to increased rates of recruitment (K. Davis, 2006). Recruitment cities share similar characteristics, such as access to numerous highways that facilitate victim transportation to destination cities where demand for commercial sex is greatest (K. Davis, 2006). Once obtained, victims are transported to high-demand locations such as Chicago, Detroit and Las Vegas (Wilson & Dalton, 2007. Additional factors that seem to link location to sex trafficking exist. Previous studies have found increased rates of commercial sexual exploitation in areas with higher ratios of females to males (Rao & Presenti, 2012), in places with legalized prostitution (Cho, Dreher, & Neumayer, 2013), and within areas characterized by large populations of transient males such as military personnel, truckers, tourists, and conventioneers (Estes & Weiner, 2002; Farley & Kelly, 2000).

 

Interpersonal and Intrapersonal Risk Factors

     In addition to location, other vulnerabilities to becoming trafficked exist, including individual, family, peer-related and environmental factors (Williamson & Prior, 2009). Persons from any socioeconomic background, race or ethnicity may become trafficked (McClain & Garrity, 2010). A study exploring the shared characteristics of adolescent females in the commercial sex industry identified low IQ scores and multiple mental health disorders as common factors (Twill, Green, & Traylor, 2010). History of risky or deviant behavior exposes adolescents to increased risk for becoming trafficked. For example, adolescents selling, buying and using drugs all increase the likelihood of crossing paths with a trafficker (McClain & Garrity, 2010; Walsh & Donaldson, 2010). Additional risk factors such as poverty, unemployment, isolation, low self-efficacy, drug addiction and history of physical and sexual abuse have been linked with entrance into the sex trafficking industry (Bales, 2007; Kidd & Liborio, 2011). Although not all trafficked persons have histories of childhood abuse (Chudakov, Ilan, Belmaker, & Cwikel, 2002), persons forced into sexual exploitation have commonly experienced violence prior to becoming trafficked, which increases their vulnerability to entering the sex trafficking trade and influences the greater likelihood of developing future mental health concerns (Hossain et al., 2010).

 

Homelessness and Sexual Minority Status as Risk Factors

Runaway, homeless or throwaway children are recruited into trafficking rings and exposed to extreme forms of abuse (Estes & Weiner, 2002). Many are killed as a result of violence or from diseases incurred from their sexual victimization (Estes & Weiner, 2002; Mitchell, Finkelhor, & Wolak, 2010). Adolescents are typically approached by traffickers within 48 hours of living on the street (Jordan, Patel, & Rapp, 2013). Traffickers are predatory in nature and adept at identifying vulnerable persons in need of safety, security and protection (Albanese, 2007; Jordan et al., 2013). LGBT persons are especially at risk of forced sexual exploitation due to increased rates of high-risk behaviors and homelessness (Martinez & Keele, 2013). According to the National Coalition for the Homeless (2009), sexual minority youth are twice as likely to experience sexual abuse before the age of 12 and are 7.4 times more likely to become victims of sexual violence. Counselors working with LGBT adolescents must assess their clients’ histories and explore whether they have engaged in survival sex or substance abuse or have been homeless. Survival sex is characterized by the exchange of sexual acts for shelter, food, money, protection, favors or other resources (Estes & Weiner, 2002; Williams & Frederick, 2009). It is important to note that persons from stable families may become trafficked. Young women may go willingly with friends to parties and become enamored with charming men involved in the sex trafficking trade or become flattered by the attentions of predatory older men (Chesnay, 2013). According to a study conducted by Raphael and Myers-Powell (2010) that interviewed 25 ex-pimps in Chicago, the prime candidate for recruitment was a blonde runaway.

 

Social Media and Internet Use as Risk Factor

Free access and anonymity with the Internet has created greater opportunity for offenders to purchase sex online where a wider variety of options exist (Chung, 2009; McCarthy, 2010; Raphael & Myers-Powell, 2010). Social media Web sites such as Myspace, Twitter and Facebook have been identified as a frequent tool used by traffickers to recruit adolescents into the sex trafficking trade (Demir, 2010; Jordan et al., 2013; Raphael & Myers-Powell, 2010; Williamson & Prior, 2009). Offenders cited the use of social media Web sites to contact, groom and connect with their victims, whereas online advertisement Web sites such as Craigslist were used to sell their victims (Raphael & Myers-Powell, 2010).

 

Adolescents with low levels of self-efficacy may be at increased risk for victimization due to higher rates of social media use. According to the Pew Research Center (2013), 74% of adults online use social networking sites, with young adults ages 18 to 29 representing the vast majority of social media users. Research exploring the relationship between social media use and the well-being of young adults has yielded significant findings that promote a deeper understanding of how traffickers select and recruit victims online. A study conducted by Meier and Gray (2014) linked photo activity on Facebook with greater than ideal internalization and self-objectification. Michikyan, Subrahmanyam, and Dennis (2014) additionally discovered that young adults experiencing emotional instability were more strategic in their online self-presentation, presumably to seek reassurance. Social networking site use also has been found to increase levels of self-efficacy, satisfy a need for belonging and improve self-esteem in college-aged students (Gangadharbatla, 2008). Upon examination of these pre-existing vulnerabilities, counselors can acquire a deeper understanding of how the grooming process may result in trauma bonds and entrance into the sex trafficking trade. For at-risk adolescents that lack a strong support system, experience low levels of self-efficacy and seek affirmation through their social media presence, online connections with traffickers may satisfy their deep desires for validation. Because traffickers are predatory in nature and gravitate toward vulnerable persons with low self-efficacy and high rates of controllability, counselors working with adolescents and young adults should provide education on topics related to Internet safety and the consequences of promoting a sexually suggestive online presence.

 

Possible Signs of Trafficking

 

Counselors working with at-risk populations (e.g., clients with addictions, and a history of homelessness and trauma) must recognize the possible signs that clients are being trafficked. Because many victims remain invisible to law enforcement (Hyland, 2001) and counselors, the identification and treatment of victims represents one of the greatest challenges in working with this population (McClain & Garrity, 2010). According to Polaris (2015), a variety of indicators exist that may suggest forced exploitation.

 

Signs of Trafficking in Mental Health Settings

Counselors and other helping professionals should assess clients for signs of trafficking, including instances in which clients are under 18 and providing commercial sex acts, have a controlling older boyfriend, work excessively long or unusual hours, or have few personal possessions (Polaris, 2015). Within behavioral health settings, clients may present as fearful, anxious, depressed, submissive or tense with avoidant eye contact (Polaris, 2015). Trafficked persons rarely seek counseling independently and have likely endured intense, ongoing victimization and may present with depression, dissociative reactions, suicidal ideation, post-traumatic stress disorder, feelings of guilt,  shame and self-mutilation (Chesnay, 2013). Clients also may have histories of solicitation charges, substance use issues, or a need for safe and stable housing, lack a strong support system, and have visible bruises or branding (Chesnay, 2013; Hyland, 2001; Jordan et al., 2013). Branding refers to a method of identification used by traffickers to indicate ownership and may be tattoos or carvings (Jordan et al., 2013; Shared Hope International, 2016). It is the author’s experience that some clients that become addicted to opiates by their oppressors are forced to inject in locations on their bodies that will not detract from their overall marketability as a reusable commodity. In many cases, these locations include the inner thighs or between the fingers or toes. As one anonymous survivor (a client of the author) explained, “Nobody is going to buy someone with track marks.” A trend exists in which offenders trafficking drugs are beginning to traffic people (Shelley, 2010). Whereas drugs can be sold once, people can be sold repeatedly and thus represent a more profitable and less risky business venture (Neville & Martinez, 2004; Shelley, 2010).

 

Signs of Trafficking in Medical Settings

Trafficked persons may present in health care settings, although these instances occur at a low rate. Persons are only allowed to seek medical attention when traffickers believe their condition prevents monetary gain, at which point they can become disposable (Chesnay, 2013; Neville & Martinez, 2004). Medical issues associated with trafficked survivors within health care settings may include sexually transmitted infections, pregnancy, history of unsafe abortions, chronic pain, malnutrition, substance use issues, and sleep deprivation (Chesnay, 2013; Estes & Weiner, 2002). Counselors and medical professionals may additionally note that trafficked survivors struggle during a mental status exam (Chesnay, 2013). Due to a combination of working long hours, exhaustion, and frequent transportation to and from locations, trafficked persons may respond incorrectly to questions regarding time, place and person (Chesnay, 2013).

 

Signs of Trafficking in School Settings

School counselors need to be mindful of signs that students are being trafficked. Adolescents may be trafficked out of their own homes and transported to and from school by their oppressor (U.S. Department of Education, 2013). Possible signs that students are being trafficked within educational settings include references to frequent travel to other cities, signs of bruising, presence of depression, anxiety, or fear, coached or rehearsed responses to questions, and inappropriate dress based on weather conditions (U.S. Department of Education, 2013). Additionally, school counselors need to be mindful of children who have significantly older boyfriends or girlfriends, describe concern for the safety of family members if they disclose, or care for children that are not family members (U.S. Department of Education, 2013). When a child is being sex trafficked, they may be absent from school or miss periods of time while being sold to other communities (Williamson & Prior, 2009).

 

Challenges of Working With Trafficked Clients

 

Counselors may experience feelings of frustration and helplessness upon discovery that clients are rarely willing to leave their traffickers despite their dire situations. It is important to remember that many adolescents who become sex trafficked experience neurological effects from childhood physical, emotional and sexual trauma that inhibits their abilities to make pragmatic choices or escape their traffickers (Reid & Jones, 2011). The presence of chronic fear can inflict barriers to cognitive processing and decision making, which explains why some survivors do not escape when the opportunity arises (Loewenstein, Weber, Hsee, & Welch, 2001; Logan, Walker, Jordan, & Leukefelt, 2006). Due to the familiarity of unhealthy relationships and the lack of self-efficacy required to pursue change, childhood victims of sexual trauma are more likely to accept situations characterized by abuse (Reid & Jones, 2011). Counselors are encouraged to seek supervision, connect with colleagues and practice regular self-care routines in order to avoid experiencing burnout, secondary trauma, and compassion fatigue when working with this population.

 

Counselors working with trafficked clients are often faced with a series of challenges since an intervention modality specific to sex trafficked survivors has not yet been developed (Jordan et al., 2013). Although a small body of research exists on the health consequences associated with human trafficking, limited research has explored the mental health consequences of trafficking (Hossain et al., 2010; Tsutsumi et al., 2008). Current treatments are borrowed from evidence-based interventions originally developed for post-traumatic stress disorder and survivors of domestic violence, slavery and captivity (Jordan et al., 2013).

 

Assess Client’s Current State

Whether providing individual or group counseling to sex trafficked clients, several treatment considerations should be examined. First, counselors should assess whether the client is currently being trafficked or whether a sex trafficking history exists. Naturally, the counselor’s role will differ significantly depending on the client’s present situation. In the author’s experience, clients that are currently trafficked rarely seek mental health services independently. Instead, clients may present to counseling as the result of court mandates associated with drug or solicitation charges. Clients that are currently trafficked often resist help from mental health providers and avoid reporting due to well-founded fears of physical violence or threats of retribution if they disclose their situation (Flores, 2010). Therefore, building strong rapport with sex trafficked clients is critical (Chesnay, 2013). Because of the fraud and deception used by traffickers during the grooming process, many trafficked persons demonstrate marked difficulty with trusting others (Belser, 2005). It is essential that counselors build trust with the client by demonstrating unconditional positive regard, empathy and authenticity. Counselors may support clients by developing individualized safety plans and sharing valuable resources (e.g., The National Human Trafficking Hotline: 1-888-373-7888). Once a strong therapeutic relationship has been established, counselors may begin pursuing a variety of counseling goals, including psychoeducation, supporting clients through the stages of personal change, engaging in group counseling, medication management, addressing substance use issues, and promoting reintegration through education and job training.

 

Counselors working with sex trafficked survivors must assess whether the client has access to necessary resources, including housing, food, water, shelter and medicine. Ensuring that survivors are equipped with safe and stable homes minimizes the likelihood that they are simply returning to the same endangering conditions (Feingold, 2005). Counselors should work with sex trafficked clients to explore the circumstances that increased their risk for sexual exploitation. Once the situations are identified, counselors must work collaboratively with clients to create a sustainable maintenance promotion plan. Chesnay (2013) explained that once basic physiological needs and safe housing are obtained, mental health professionals can begin reframing the client’s worldview from “victim” to “survivor” to “thriving survivor.”

 

Asking Helpful Questions

In addition to taking the client’s trafficking situation into consideration, it is important to remain mindful of the language used when working with this population. Clients will rarely, if ever, identify with the term trafficked and also are likely to struggle with identifying their partner and protector as a pimp or trafficker (Chesnay, 2013). Trafficked clients may explain that they are working to help their boyfriends (Priebe & Suhr, 2005). Counselors and other mental health professionals are encouraged to accept the client’s identified terms and work within their individual framework (Chesnay, 2013).

 

Providing psychoeducation on the process, rates and prevalence of sex trafficking may be beneficial for clients to promote insight. Educational modalities that shift pertinent information from general to specific may be helpful in gradually exposing clients to difficult concepts. Counselors should work collaboratively with clients to identify salient issues and validate their experiences to promote recognition and exploration on the effects of trafficking. Counselors may use statements such as, “Many young adolescents living on the streets feel scared and find someone to protect and care for them. I wonder whether this is true for you?” Or, “Some people care so much about their partners that they feel obligated to prove their love and begin doing things they are not really comfortable with. I am curious whether this has been your experience as well?” Offering opportunities for clients to disclose information in a safe, nonjudgmental and accepting environment can increase client insight, promote counselor awareness of client history and facilitate therapeutic growth. Additionally, counselors should determine whether clients have access to safe and stable housing. If basic physiological needs are not met, clients may struggle to focus on higher order needs such as developing a safety plan or emotion regulation.

 

Assess Client’s Stage of Change

For clients that are currently trafficked, the stages of change outlined by Norcross, Krebs, and Prochaska (2011) may be a helpful tool for examining clients’ willingness to engage in counseling. Clients in the precontemplation stage may respond positively to counseling strategies aimed at increasing education and awareness. When clients present in the stage of contemplation, counselors may be most supportive by exploring client ambivalence. Counselors may facilitate costs and benefits analyses with the client regarding their current predicaments. Regardless of the client’s stage of change it is important that counselors do not force the client to leave their oppressor. This may put the client, their families and other loved ones at risk (Flores, 2010). Instead, counselors must listen, affirm and provide the client with resources such as the trafficking hotline and empower them to call when ready. It is important that counselors assess the severity and duration of trafficking-related abuse and recognize how these experiences influence recovery time (Hossain et al., 2010). In a sample of 204 trafficked girls and women, the presence of sexual violence during a trafficking experience had an independent effect on mental health symptoms (Hossain et al., 2010). Hossain and colleagues (2010) concluded that persons trafficked for longer periods of time have an increased likelihood of abusive episodes and prolonged feelings of entrapment, alienation, loss of control, humiliation and helplessness—all of which are associated with developing mental health disorders in the future. Counselors can better accommodate the needs of persons that have been trafficked for longer periods of time by providing longer duration post-trafficking care.

 

Assess Entrance Into Trafficking

Other treatment considerations pertain to the process through which clients became trafficked. Clients recruited and controlled through a grooming process may struggle to identify their captors as oppressors due to the presence of a trauma bond (United States Department of Health and Human Services, n.d.). Cases also exist in which clients have been trafficked by family members or sold to traffickers by their parents (Shelley, 2010). In some instances, adolescents and children are forced into sexual exploitation by their parents or siblings in order to support drug addictions or to avoid financial burdens (Estes & Weiner, 2002). One survivor, a client of the author, reported that a family member diagnosed with schizoaffective disorder trafficked her for a period of 2 months. The client described how the family member would hold a firearm to his neck and threaten to commit suicide if she did not provide him with heroin. The client explained how she felt forced to complete commercial sex acts with drug dealers, as this strategy was the quickest and easiest way to obtain illicit substances within her impoverished community. Counselors should work to identify their biases regarding how persons are trafficked, and by whom, in order to identify survivors and provide appropriate services.

 

Counseling Sex Trafficked Clients

 

     Counselors working with sex trafficked survivors should be prepared to employ a variety of trauma-sensitive interventions to support the individual needs of each client. Trauma-sensitive interventions identify safety as the foundation for working with persons to eliminate self-harm, develop trustworthy relationships, overcome challenges, promote wellness and remove themselves from dangerous situations (Najavits, 2002). Helping traumatized clients to regain a sense of control is critical (Goodman & Calderon, 2012). For example, counselors may use mindfulness-based activities such as body scans and body awareness exercises to help clients differentiate between current and past experiences (Rothschild, 2000). Counselors can use other mindfulness techniques, such as focusing on the present and emphasizing the mind-body connection, to help clients identify and reduce the somatic symptoms of arousal when no threats are present (Goodman & Calderon, 2012). Finally, counselors can help clients practice imagining, and returning attention to, comforting images to increase their sense of safety and decrease arousal (Goodman & Calderon, 2012). Ideally, counselors will empower their clients to redefine their lives not by their pasts, but by their futures (Chesnay, 2013).


Creative Interventions

     Creative-based interventions are especially powerful with sex trafficked clients because they provide opportunities for clients to make choices. For clients who have long been told what to do and have lived according to their trafficker’s demands, the presentation of choices and sense of control may represent an exciting and difficult challenge. Creative arts interventions have received a great deal of empirical support for clients presenting with trauma. Research that investigated resiliency has identified the importance of creativity, humor, flexibility, and movement as effective interventions to improve traumatized clients’ self-esteem, hope and prosocial behaviors (Johnson, Lahad, & Gray, 2009; Lahad, 2000; Raynor, 2002). Additionally, therapeutic art has been shown to be efficacious for work with clients presenting with emotional disturbances, grief and loss, low self-efficacy, depression, post-traumatic stress disorder, anxiety, and feelings of guilt and shame (Johnson et al., 2009; Slayton, D’Archer, & Kaplan, 2010). Creative interventions can be used to help clients reframe ideas, shift perspectives, externalize emotions and gain deeper understanding of events (Bradley, Whiting, Hendricks, Parr, & Jones, 2008). According to Lev-Weisel (1998), clients that struggle to find words to describe their traumatic experiences may prefer creative interventions as a means of expression. Counselors can integrate the use of creative and expressive interventions using mandalas or other art mediums to support clients in promoting openness while providing a sense of structure. Future areas of research are needed to determine the efficacy of creative interventions specific to clients with a history of sex trafficking.

 

Cognitive Behavioral Therapies

     Clients with a history of sex trafficking can benefit from cognitive behavioral therapies due to their internalization of derogatory labels (Hickle & Roe-Sepowitz, 2014). Counselors working with trafficked clients can identify and challenge these labels in order to decrease the presence of shame and other meta-emotions (e.g., anger at oneself for feeling shame). Additional evidence-based counseling interventions that may be useful for sex trafficked client populations include Eye Movement Desensitization and Reprocessing with adults (Maxfield, 2003; Shapiro, 1989) and trauma-focused cognitive behavioral therapy with children (Cohen, Berliner, & Mannarino, 2010; Cohen, Mannarino, Berliner, & Deblinger, 2000). The use of dialectical trauma-focused cognitive behavioral therapy is effective with both children (Racco & Vis, 2015) and adults with histories of trauma and post-traumatic stress disorder (Wagner, Rizvi, & Harned, 2007). Although trauma-focused cognitive behavioral therapy and dialectical trauma-focused cognitive behavioral therapy have not been tested specifically for sex trafficked populations, research indicates that these modalities are successful in helping children overcome histories of trauma and abuse (Classen, Koopman, Nevill-Manning, & Spiegel, 2001; Cohen & Mannarino, 1997). Future research studies should investigate the efficacy of cognitive behavioral therapies with sex trafficking survivors in order to standardize appropriate treatment methods for this unique population.

 

Group Counseling

     Providing survivors of forced sexual exploitation with an opportunity to participate in group counseling can empower persons to share similar experiences while creating a sense of community and support (Hickle & Roe-Sepowitz, 2014). Peer support is a crucial component for treatment since bearing witness to the similar lived experiences of other survivors provides a unique dimension of support and sense of universality (Chesnay, 2013). Counselors working with trafficked persons may focus on accomplishing a variety of treatment goals, including feeling identification, establishing safety, addressing substance use, countering internalized stigma and labels, providing psychoeducation and establishing healthy boundaries. Shame can be reduced by prompting discussions about taboo and stigmatizing topics within group settings (Hickle & Roe-Sepowitz, 2014). Many trafficked survivors have upheld the belief that they are the only ones who have been trafficked by parents, have engaged in survival sex, or who have been forced into sexual exploitation by boyfriends or girlfriends. According to Estes and Weiner (2002), boys that performed oral sex on adult males as a result of forced sexual exploitation experienced a profound sense of shame. Addressing these foci of shame can help clients recognize the universality of their experiences, build rapport with peers and facilitate trust in the group setting. Counselors should listen openly to the client’s stories of shame and receive them with empathy in order to dispel their negativistic beliefs. Psychoeducation within group settings can be used to explain how traffickers use coercion and other techniques to recruit young women (Hickle & Roe-Sepowitz, 2014).

 

Expressive techniques that allow group members to process trauma experiences without dissociating from the event are beneficial in promoting therapeutic growth (Hickle & Roe-Sepowitz, 2014). Clients can use markers, colored pencils and other artistic mediums to draw, color or write on an outlined body where they feel specific emotions such as pain, shame, anger, fear and guilt (Hickle & Roe-Sepowitz, 2014). Words and pictures from magazines also can be used to represent emotions or past and present states of mind and facilitate the healing process. The author has facilitated mask exercises within group settings to support trafficked clients in identifying and processing their ideal and actual selves. Once completed, the pictures and masks can be processed with other group members and similar or different experiences, emotions and challenges can be discussed.

 

Conclusion

 

Although social and cultural norms, poverty, gendered inequality and childhood history represent important vulnerability factors, the social injustice known as sex trafficking could not occur without the demand for sexual exploitation (Matheson & Finkel, 2013). A deeper understanding is needed to comprehend how persons become trafficked (Whitaker & Hinterlong, 2008). Additionally, a dearth of research remains that identifies specific evidence-based and trauma-sensitive modalities developed specifically for sex trafficked survivors (Chesnay, 2013; Jordan et al., 2013). The experiences, challenges and reflections of the author have been presented with the intention of providing education, support and guidance to other counselors serving this unique population. Regardless of which counseling tools are used, establishing and building a strong therapeutic alliance is a valuable tool that counselors can employ to support sex trafficked persons (Chesnay, 2013). Although challenging at times, establishing rapport requires a nonjudgmental attitude and a willingness to bear witness to clients’ experiences, without pointing out what survivors could have done differently (Chesnay, 2013).

 

It is important to remember that trafficked persons are often survivors of long-term childhood trauma characterized by instability within the home, childhood sexual trauma and community violence (Bales, 2007; Hossain et al., 2010; Kidd & Liborio, 2011; Williamson & Prior, 2009). Many adolescents were targeted, recruited and trafficked due to pre-existing vulnerabilities and high controllability factors (Whitaker & Hinterlong, 2008). Counselors are tasked with a unique position to provide corrective relational experiences characterized by the nonjudgmental acceptance, support and affirmation desperately needed by this population. Fewer resources and services exist for trafficked survivors than for victims of any other crime (Clawson, Dutch, & Cummings, 2006). Counselors should connect sex trafficked survivors to necessary social service supports, including case management services, safe and stable housing, and services aimed at supporting the successful reintegration of clients into the community through education and job training (Williamson & Prior, 2009). Future areas of research should explore the profiles of traffickers and standardize how mental health and medical providers can better identify, serve, protect, and support trafficked survivors (Bales, 2005). Finally, counselors are called to continue promoting awareness on the prevalence and signs of sex trafficked survivors. Increasing awareness and decreasing demand for sexually exploited persons are the fundamental steps necessary to end the human rights violation of sex trafficking (Chung, 2009; Kotrla, 2010).

 

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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Stacey Diane A. Litam is a doctoral candidate at Kent State University and a mental health counselor at Moore Counseling and Mediation Services Inc. Correspondence can be addressed to Stacey Litam, Moore Counseling and Mediation Services, 4600 Carnegie Avenue, Cleveland, Ohio 44103, slitam@kent.edu.

The Common Factors Discrimination Model: An Integrated Approach to Counselor Supervision

A. Elizabeth Crunk, Sejal M. Barden

Numerous models of clinical supervision have been developed; however, there is little empirical support indicating that any one model is superior. Therefore, common factors approaches to supervision integrate essential components that are shared among counseling and supervision models. The purpose of this paper is to present an innovative model of clinical supervision, the Common Factors Discrimination Model (CFDM), which integrates the common factors of counseling and supervision approaches with the specific factors of Bernard’s discrimination model for a structured approach to common factors supervision. Strategies and recommendations for implementing the CFDM in clinical supervision are discussed.

Keywords: supervision, common factors, specific factors, discrimination model, counselor education

Clinical supervision is a cornerstone of counselor training (Barnett, Erickson Cornish, Goodyear, & Lichtenberg, 2007) and serves the cardinal functions of providing support and instruction to supervisees while ensuring the welfare of clients and the counseling profession (Bernard & Goodyear, 2014). Numerous models of clinical supervision have been developed, varying in emphasis from models based on theories of psychotherapy, to those that focus on the developmental needs of the supervisee, to models that emphasize the process of supervision and the various roles of the supervisor (Bernard & Goodyear, 2014). However, despite the abundance of available supervision models, there is little evidence to support that any one approach is superior to another (Morgan & Sprenkle, 2007; Storm, Todd, Sprenkle, & Morgan, 2001). Thus, a growing body of clinical supervision literature underscores a need for strategies that integrate the most effective elements of supervision models into a parsimonious approach rather than emphasizing differences between models (Lampropoulos, 2002; Milne, Aylott, Fitzpatrick, & Ellis, 2008; Morgan & Sprenkle, 2007; Watkins, Budge, & Callahan, 2015). Common factors models of supervision bridge the various approaches to supervision by identifying the essential components that are shared across models, such as the supervisory relationship, the provision of feedback, and supervisee acquisition of new knowledge and skills (Milne et al., 2008; Morgan & Sprenkle, 2007). Other common factors approaches to supervision draw on psychotherapy outcome research, aiming to extrapolate common factors of counseling and psychotherapy—such as the therapeutic relationship and the instillation of hope—to clinical supervision approaches (Lampropoulos, 2002; Watkins et al., 2015)

Although reviews of the supervision literature allude to commonalities among supervision approaches (Bernard & Goodyear, 2014), there is a dearth of published literature offering practical strategies for bridging common factors of counseling and supervision. Perhaps even more limited is literature that addresses the necessary convergence of both common and specific factors, or the integration of common factors of supervision with particular interventions that are applied in various supervision approaches (e.g., role-playing or Socratic questioning; Watkins et al., 2015). In a recent article, Watkins and colleagues (2015) proposed a supervision model that extrapolates Wampold and Budge’s (2012) psychotherapy relationship model to specific factors of supervision, encouraging supervisors to apply such relationship common factors to some form of supervision. However, there remains a need for a structured approach to supervision that integrates the common factors of counseling and supervision with the specific factors of commonly used, empirically supported models of clinical supervision.

Because the common factors are, by definition, elements that are shared among theories of counseling and supervision, it can be argued that common factors approaches can be applied to almost any supervision model. However, we argue for the integration of common factors with the discrimination model for several reasons. First, the relationship has been found to be the essential common factor shared among counseling (Lambert & Barley, 2001; Norcross & Lambert, 2014) and supervision approaches, and is often cited as the most critical element of effective supervision and other change-inducing relationships, such as counseling, teaching and coaching (Lampropoulos, 2002; Ramos-Sánchez et al., 2002). The supervisory roles of teacher, counselor and consultant are built into the discrimination model, providing supervisors with natural avenues for fostering a strong supervisory relationship. However, the proposed Common Factors Discrimination Model (CFDM) expands on the discrimination model by providing specific recommendations for how supervisors might use such roles as opportunities for developing and maintaining the supervisory relationship. Second, we consider Bernard’s (1979, 1997) discrimination model to lend itself well to common factors approaches to supervision, as both are concerned with process aspects of supervision, such as tailoring supervision interventions to the needs of the supervisee. Finally, because the discrimination model is widely used by practicing supervisors (Timm, 2015), common factors approaches are likely to fit naturally with customary supervision practices of more experienced supervisors who espouse the discrimination model, yet the CFDM is concise enough for novice supervisors to grasp and apply. Thus, the purpose of this manuscript is to build on Watkins and colleagues’ (2015) model by presenting the CFDM, an innovative approach to supervision that converges common factors identified in both counseling and supervision and integrates them with the specific factors of Bernard’s (1979, 1997) discrimination model. Specifically, we will (a) review the relevant literature on common factors approaches to counseling and supervision and the discrimination model; (b) provide a rationale for a model of supervision that integrates the specific factors of the discrimination model with a common factors approach; and (c) offer strategies and recommendations for applying the CFDM in clinical supervision.

The Common Factors Approach

The notion of therapeutic common factors resulted from psychotherapy outcome research suggesting that psychotherapies yield equivalent outcomes when compared against each other and, thus, what makes psychotherapy effective is not the differences between therapies, but rather the commonalities among them (Lambert, 1986). Wampold’s (2001) landmark research revealed that the theoretical approach utilized by the therapist (e.g., psychodynamic therapy) explained less than 1% of therapy outcome. In light of these findings, researchers and clinicians have been urged to minimize the importance placed on specific clinical techniques and interventions; instead, an emphasis on the commonalities among therapies that are associated with positive outcomes (Norcross & Lambert, 2011), such as the therapeutic alliance, empathy, positive regard, and collaboration within the therapeutic relationship (Norcross & Lambert, 2014; Norcross & Wampold, 2011), is more useful for describing therapeutic changes.

Among the most influential common factors approaches is Lambert’s model of therapeutic factors (see Lambert & Barley, 2001, for a review). Although lacking in stringent meta-analytic or statistical methods, Lambert and Barley (2001) presented four primary factors that are shared among therapeutic approaches (with the percentage that each factor contributes to therapy outcome indicated): (a) extratherapeutic factors (i.e., factors associated with the client, as well as his or her environment; 40%); (b) common factors (i.e., relationship factors such as empathy, warmth, positive regard, supporting the client in taking risks; 30%); (c) placebo, hope, and expectancy factors (i.e., the client’s hope and expectancy for improvement, as well as trust in the treatment; 15%); and (d) skills/techniques factors (i.e., components specific to various therapies, such as empty chair or relaxation techniques; 15%). Although a variety of common factors have been identified in the psychotherapy outcome research, numerous meta-analyses have identified the therapeutic relationship as the sine qua non (Norcross & Lambert, 2011, p. 12) of common factors that account for positive outcomes irrespective of the specific treatment utilized (Norcross & Wampold, 2011). They stated: “although we deplore the mindless dichotomy between relationship and method in psychotherapy, we also need to publicly proclaim what decades of research have discovered and what tens of thousands of relational therapists have witnessed: The relationship can heal” (Norcross & Lambert, 2014, p. 400).

Although the common factors are necessary for producing positive counseling outcomes, this does not mean that specific factors are irrelevant (Norcross & Lambert, 2011). On the contrary, prior research indicates that engaging in specific treatment interventions is associated with the working alliance and with positive counseling outcomes (Tryon & Winograd, 2011; Wampold & Budge, 2012). Watkins and colleagues (2015) noted that treatment interventions are necessary in maintaining client hope and expectations for positive counseling outcomes, stating, “The specific ingredients create benefits through the common factor of expectations, and respecting that interdependent common/specific factor dynamic is vital to treatment outcome” (p. 221).

Common Factors Approaches to Supervision

Although the concept of common factors in counseling and psychotherapy is not a new one and has been the focus of considerable empirical research (Frank, 1982; Lambert & Barley, 2001; Lambert & Ogles, 2004; Rosenzweig, 1936), applying the common factors approach to clinical supervision is relatively novel (Morgan & Sprenkle, 2007). Counseling and clinical supervision are distinct interventions; however, Milne (2006) makes a case for extrapolating findings from psychotherapy research to supervision, as both share common structures and properties of education, skill development, problem-solving and the working alliance. Furthermore, Bernard and Goodyear (2014) noted, “because therapy and supervision are so closely linked, developments in psychotherapy theory inevitably will affect supervision models” (p. 59).

Despite frequent reference to the similarities among supervision models, literature that specifically addresses common factors of supervision approaches is scarce (Bernard & Goodyear, 2014). In our review of the supervision literature, we identified five articles that endorsed common factors approaches to supervision and counselor training (Castonguay, 2000; Lampropoulos, 2002; Milne et al., 2008; Morgan & Sprenkle, 2007; Watkins et al., 2015). Following Castonguay’s (2000) seminal work on training in psychotherapy integration, Lampropoulos (2002) was among the first to address the parallels that exist between common factors of both counseling and supervision, advocating for a theoretically eclectic approach to supervision and for the prescriptive matching of common factors to supervisee needs. For example, Lampropoulos (2002) suggested that supervisors might integrate psychodynamic theory as a means of increasing supervisees’ awareness of countertransference and attachment patterns, or cognitive theory in order to restructure supervisees’ unhelpful thoughts about counseling and supervision.

In contrast to Lampropoulos’s (2002) model, which extrapolates common factors of counseling to supervision, Morgan and Sprenkle (2007) and Milne and colleagues (2008) endorsed approaches that bridge similarities between supervision models. Morgan and Sprenkle (2007) identified a number of common factors among models of supervision, grouping these factors into the following three dimensions falling on their respective continua: (a) emphasis, ranging from specific clinical competence to general professional competence; (b) specificity, ranging from the idiosyncratic needs of supervisees and clients to the general needs of the profession as a whole; and (c) supervisory relationship, ranging from collaborative to directive. The authors (Morgan & Sprenkle, 2007) then proposed a model of supervision that applies these three dimensions of supervision to the supervisor roles of coach, teacher, mentor and administrator. In contrast, Milne and colleagues (2008) conducted a best evidence synthesis of the supervision literature to summarize the current state of empirical research on supervision practices and applied their findings to a basic model of supervision. Although both models (Milne et al., 2008; Morgan & Sprenkle, 2007) contributed viable descriptive models of common factors approaches to supervision, they were limited in providing specific strategies for supervisors to employ in a given situation. Furthermore, neither model specifically addressed the intersection of common factors of counseling and common factors of supervision. Thus, noting that common factors of counseling and specific factors of supervision approaches are interdependently related, Watkins and colleagues (2015) proposed a common/specific factors model, designating the supervisory relationship as the crowning common factor and encouraging supervisors to apply this relationship-centered model to the specific factors of “some form of supervision” (Watkins et al., 2015, p. 226). Following Watkins and colleagues’ recommendations, we therefore present an integrated approach to supervision by applying the common factors of counseling and supervision to the specific factors of the discrimination model.

 The Discrimination Model

The discrimination model (Bernard, 1979, 1997) provides a conceptualization of clinical supervision as both an educational and a relationship process (Bernard & Goodyear, 2014; Borders & Brown, 2005). In essence, the discrimination model involves the dual functions of assessing the supervisee’s skills and choosing a supervisor role for addressing the supervisee’s needs and goals. The supervisee is assessed on three skill areas, or foci: (a) intervention (observable behaviors that the supervisee demonstrates in session, such as demonstration of skills and interventions); (b) conceptualization (cognitive processes, such as the supervisee’s ability to recognize the client’s themes and patterns, as well as the supervisee’s level of understanding of what is taking place in session); and (c) personalization (supervisee self-awareness and ability to adapt his or her own personal style of counseling while maintaining aware-ness of personal issues and countertransference). Furthermore, over 30 years ago, Lanning (1986) proposed the addition of assessing the supervisee’s professional behaviors, such as how the supervisee approaches legal and ethical issues.

When the supervisor has assessed the supervisee’s skill level in each of the three foci, the supervisor utilizing the discrimination model assumes the appropriate role for addressing the supervisee’s needs and goals: (a) teacher (assumed when the supervisor perceives that the supervisee requires instruction or direct feedback); (b) counselor (appropriate for when the supervisor aims to increase supervisee reflectivity, or to process the supervisee’s internal reality and experiences related to his or her professional development or work as a counselor); or (c) consultant (a more collaborative role that is assumed when the supervisor deems it appropriate for the supervisee to think and act more independently, or when the supervisor aims to encourage the supervisee to trust his or her own insights). It is important to note that the supervisor does not take on the singular form of any of the three roles, but rather makes use of the knowledge and skills that are characteristic of each role (Borders & Brown, 2005). The discrimination model is situation-specific; therefore, supervisor roles and foci of assessment might change within a supervision session and across sessions. Consequently, supervisors are advised to remain attuned to the supervisee’s needs in order to attend to his or her most pressing focus area and to assume the most suitable role for addressing these needs rather than displaying strict adherence to a preferred focus or role (Bernard & Goodyear, 2014).

The discrimination model is considered to be an accessible, empirically validated model for supervisors and can be adapted in complexity depending on the supervisor’s level of readiness (Bernard & Goodyear, 2014; Borders & Brown, 2005). Using multidimentional scaling in an empirical study of the discrimination model, Ellis and Dell (1986) provided validation for both the teacher and counselor roles, although the consultant role did not emerge as a distinct role. Their findings are consistent with other studies that provided support for the teacher and counselor roles, but not for the consultant role (Glidden & Tracey, 1992; Goodyear, Abadie, & Efros, 1984; Stenack & Dye, 1982). Thus, the consultant role might be more difficult to distinguish from the teaching and counseling roles, perhaps, as Bernard and Goodyear (2014) noted, because the consultant role requires supervisors to put aside their position of expert or therapist and act more collaboratively with their supervisees. Ellis and Dell provided an alternate (and conflicting) explanation, suggesting that consultation might be an underlying component of both the teaching and counseling roles. These findings indicate a need for future research and possible modification of the discrimination model; however, the discrimination model is generally supported by empirical research.

Rationale for an Integrated Model

Watkins and colleagues (2015) stated: “Akin to the ‘great psychotherapy debate’ about effectiveness (Wampold, 2001), a ‘great psychotherapy supervision debate’ about effectiveness is eminently likely” (p. 17). Several cross-cutting models of clinical supervision have been proposed (Milne et al., 2008; Morgan & Sprenkle, 2007), as well as models that extrapolate common factors of counseling to supervision practices (Lampropoulos, 2002; Watkins et al., 2015); however, there has yet to be a model that systematically converges both. Given the abundance of empirical support for common factors in counseling, we have conceptualized a new model, the CFDM, to integrate a supervision approach that is grounded in effective counseling and supervision practices. Furthermore, Watkins and colleagues encouraged supervisors to apply common factors of counseling to the specific factors of some form of supervision; however, to our knowledge, no such model integrating common factors with the specific factors of an empirically supported model of supervision has been published. Thus, the CFDM combines essential factors of supervision models, converges them with common factors of counseling approaches, and applies them to the specific factors of Bernard’s (1979, 1997) discrimination model for a structured approach that bridges effective elements of both counseling and supervision.

Bernard and Goodyear (2014) pointed to the supervisory relationship as one of the most essential factors in supervision; however, a major criticism of the discrimination model is that the model itself does not thoroughly address the supervisory relationship (Beinart, 2004). Similarly, Freeman and McHenry (1996) found that supervisors ranked the development of clinical skills as their top goal for supervising counselors-in-training and identified that supervision involves taking on the roles of teacher, challenger and supporter, but relationship building did not surface as an emphasis of counselor supervision (Bell, Hagedorn, & Robinson, 2016). Thus, the CFDM builds on the discrimination model by incorporating tenets of the supervisory relationship that are consistent with common factors of counseling and supervision, such as the working alliance (Bordin, 1983), the real relationship (Watkins, 2015), and the instillation of hope (Lambert & Barley, 2001; Lampropoulos, 2002). Historically, the supervision literature suggests that novice supervisors, in particular, might manage feelings of self-doubt and uncertainty by employing a highly structured supervision style, focusing on providing supervisees with feedback on counseling techniques or client diagnosis and placing less emphasis on attending to the supervisory relationship (Hess, 1986; Hess & Hess, 1983). Furthermore, whereas building rapport is a top priority in many therapeutic relationships, counselor supervisors might prioritize other factors instead, such as scheduling, paperwork, and evaluation, before establishing a relationship with the supervisee (Bell et al., 2016). Because the discrimination model is a widely used approach to supervision (Timm, 2015), experienced counselors who wish to incorporate common factors of supervision and counseling into their customary supervision practice will likely find the CFDM to be an intuitive supervision approach. The following section provides a description of the four primary tenets of the CFDM, as well as strategies and recommendations for applying the CFDM in supervision.

The Common Factors Discrimination Model

The CFDM is an innovative model of supervision that aims to integrate the common factors of counseling and supervision with the specific factors of Bernard’s (1979, 1997) discrimination model for a structured, relationship-centered approach to clinical supervision. The CFDM builds on existing supervision models that extrapolate common factors of counseling to supervision practices (Lampropoulos, 2002; Watkins et al., 2015). The CFDM also draws on the discrimination model (Bernard, 1979, 1997) as a method of assessing supervisee needs and tailoring feedback and support accordingly. Although the melding of common factors with the discrimination model has yet to be empirically tested as an integrated approach to supervision, both approaches have received substantial empirical support as standalone models. Empirical research supports common factors approaches to counseling and other change-inducing relationships; however, the CFDM’s underpinnings in the more prescriptive discrimination model provide a structured approach to common factors supervision. In addition, there is evidence to suggest the effectiveness of common factors approaches across cultures (Dewell & Owen, 2015).

We have proposed a model that combines effective common factors of counseling and supervision with the specific factors of Bernard’s (1979, 1997) widely used, empirically supported and accessible discrimination model for a structured approach to common factors supervision. The primary tenets of the CFDM were derived by reviewing the literature on common factors models of supervision and purposively selecting the most common elements, including: (a) development and maintenance of a strong supervisory relationship, (b) supervisee acquisition of new knowledge and skills, (c) supervisee self-awareness and self-reflection, and (d) assessment of supervisees’ needs and the provision of feedback based on the tenets of Bernard’s (1979, 1997) discrimination model. The following section provides a brief fictional case illustration followed by specific strategies for applying the CFDM to supervision. Specific examples for matching common factors with tenets of the discrimination model are provided in Table 1, based on an illustrative case example, followed by a discussion of the primary tenets of the case to the CFDM.

 

Case Illustration

André, a master’s student in mental health counseling, is completing his first semester of clinical practicum at his university’s community counseling center. Although André demonstrates competency across many clinical and professional domains, as a novice counselor trainee he struggles with reflecting feeling with clients in session. His supervisor has noticed that André tends to sidestep emotional topics in session and, instead of reflecting feeling, responds to emotional content by asking the client unrelated questions or by changing the subject. In the few instances in which he has attempted to reflect feeling, André has been inaccurate in his reflections, undershooting the intensity of the client’s feelings or misreading the client’s emotions altogether. This has sometimes led to tension and frustration between André and his clients. Using the CFDM, his supervisor might utilize the following strategies in supervision with André. In the following section, the case of André is discussed, integrating the primary tenets of the CFDM.

 

Application of the CFDM

The Supervisory Relationship

Bernard and Goodyear (2014) suggested that the supervisory relationship is a critical factor in effective supervision, regardless of the model of supervision that is followed. Thus, the central tenet of the CFDM is the development of a collaborative supervisory relationship that is characterized by the Rogerian conditions of empathy, genuineness, and unconditional positive regard (Lampropoulos, 2002). Utilizing the CFDM with André, the supervisor approaches her supervisory roles of teacher, counselor and consultant with warmth and acceptance as she addresses André’s difficulty reflecting feeling with his client, rather than using a confrontational or critical approach. Furthermore, she explores with André his personal experiences with emotion, taking into consideration his background and cultural factors that could play a role in his relationship with emotion.

The real relationship. The real relationship (Lampropoulos, 2002; Watkins, 2015) refers to a supervisory relationship that is unaltered by transference or countertransference and is characterized by empathy, warmth, genuineness, unconditional positive regard and trust. The expression of humor and optimism also is recommended in developing a common factors-influenced supervisory relationship. Extrapolating from Gelso’s (2014) tripartite model of the psychotherapy relationship, Watkins (2015) defined the real relationship as “the personal relationship between supervisor and supervisee marked by the extent to which each is genuine with the other and perceives/experiences the other in ways that befit the other” (p. 146). Factors of the real relationship are critical in supervision, as they allow supervisees to develop trust in the supervisory relationship and provide safety for supervisees to disclose vulnerabilities, mistakes and personal concerns (Storm et al., 2001).

Because the evaluative and hierarchical nature of supervision might make the supervisory relationship vulnerable to supervisory ruptures (Burke, Goodyear, & Guzzardo, 1998; Nelson & Friedlander, 2001; Safran, Muran, Stevens, & Rothman, 2007), the CFDM utilizes a collaborative evaluation process (Rønnestad & Skovholt, 1993), in which supervisees have the opportunity to practice evaluating their skills independently throughout their training either by journaling or by completing an evaluation form about their session and submitting their self-evaluation to their supervisor. Supervisee self-evaluations are then processed in supervision. The CFDM supervisor in the case illustration might use this strategy with André to allow him to raise self-awareness and to receive regular feedback on his skills. Furthermore, assuming the teacher role of the discrimination model, his supervisor might direct André to conduct a self-assessment of his reflections of feeling following each session, which he could bring into supervision to discuss and receive her feedback.

Because the supervisory relationship is the central tenet of the CFDM, it is advisable to evaluate and monitor the relationship throughout supervision. Furthermore, Lampropoulos (2002) recommended that supervisors identify and attempt to repair ruptures as soon as possible, as ruptures can be deleterious to supervision process and outcome. One such measure for evaluation of the supervisory relationship is the Supervisory Relationship Questionnaire (SRQ; Palomo, Beinart, & Cooper, 2010), a 67-item assessment of the supervisee’s perceptions of the supervisory relationship. Other plausible measures include the Working Alliance Inventory (Bahrick, 1990) and the Revised Relationship Inventory (Schacht, Howe, & Berman, 1988). Allowing André to assess the supervisory relationship and give his supervisor feedback can provide insight into André’s perception of their relationship and can allow the supervisor to consider making changes in her approach, if necessary. This also conveys to André that his feedback is valuable and that their supervisory relationship is collaborative.

The working alliance. The working alliance in supervision refers to the collaborative development of goals and tasks for supervision (Bordin, 1983; Constantino, Castonguay, & Schut, 2002; Lampropoulos, 2002). The working alliance is established in the CFDM by collaboratively developing a supervision contract between the supervisor and the supervisee (Lampropoulos, 2002) at the very beginning of the supervisory relationship. Goals for supervision that are addressed in the contract include evaluating supervisees’ strengths and areas for growth and identifying specific skills to be learned, as well as issues related to supervisee theoretical orientation. The tasks used to reach these goals can include process notes, live supervision, and interpersonal process recall (IPR; Kagan & Kagan, 1997) as a collaborative approach to processing André’s strengths and areas for growth, and for facilitating André’s self-reflection and self-awareness. The purpose of these tasks is to provide structure and opportunities for instruction, feedback, and evaluation, while allowing the supervisee to engage in self-evaluation, application of new skills, corrective action, and exploration of alternative approaches. The CFDM draws from the discrimination model when developing the contract as a means of evaluating supervisee’s three levels of foci (i.e., intervention, conceptualization and personalization). For example, when developing the supervision contract with André, the supervisor would consider André’s current level of competency with regard to techniques and clinical skills, case conceptualization skills, and self-awareness and personal style.

Instillation of hope and the creation of expectations. Frank and Frank (1991) noted the impact of positive expectations and hope in effecting change in counseling. Placebo, hope and expectancy factors emerged as a single common factor among most counseling approaches, with Lambert and Barley (2001) noting that instillation of hope accounts for 15% of client outcome. Watkins (1996) addressed the issue of demoralization in supervision, stating that beginning counselors can experience poor self-efficacy and might feel overwhelmed as they navigate their professional identity development. Watkins (1996) stated that supervisors are able to utilize the supervisory relationship as a means of encouraging supervisees and providing structure within the relationship to foster hope. Recently, Watkins and colleagues (2015) endorsed the creation of expectations and the provision of some method of supervision as a pathway by which supervisee change occurs. CFDM supervisors can incorporate hope and expectancy into supervision by using the consultant role of the discrimination model to explain to supervisees the process of supervision, and by collaborating with supervisees to provide supervision that builds on those expectations. Practical tools that André’s supervisor might implement to promote hope and positive expectations include developing a supervision contract with André or providing him with a professional disclosure statement in order to explain the process of supervision and to set supervisory rituals in motion (Watkins et al., 2015). Lampropoulos (2002) also suggested setting short- and long-term goals with supervisees as a means of instilling hope.

Supervisee Self-Awareness and Self-Reflection

An additional tenet of the CFDM is supervisee self-reflection concerning issues that influence professional development (Lampropoulos, 2002). CFDM supervision emphasizes the importance of encouraging supervisees to explore their strengths and areas for growth, and personal issues that might affect their work in counseling, as well as their therapeutic styles (Lampropoulos, 2002; Milne et al., 2008). The CFDM attempts to facilitate supervisee self-reflection by implementing strategies such as collaborative evaluation and the supervision contract (discussed above). Furthermore, the CFDM utilizes IPR (Kagan & Kagan, 1997), in which the supervisor and supervisee watch videotape of a supervisee’s counseling session together, pausing the tape at moments that either the supervisor or supervisee deems critical for further inquiry and processing. Taking on the role of counselor, the supervisor utilized IPR to explore what André was experiencing during that moment of the counseling session that might have prevented him from demonstrating reflection. Consistent with the common factors model, the supervisor confronted André with warmth, empathy and acceptance.

Acquisition of Knowledge and Skills

According to the discrimination model (Bernard, 1979, 1997), one of the primary roles of the supervisor is that of teacher. Thus, in addition to providing support and feedback, supervisors are in a position to impart knowledge and to facilitate supervisees’ acquisition of skills—a factor of supervision that surfaces in the majority of supervision models (Milne et al., 2008; Morgan & Sprenkle, 2007). Lampropoulos (2002) stated that supervisees might learn through direct instruction, through shaping (i.e., gradual learning of a desired behavior) and through their own personal experience. In addition, supervisees have opportunities to learn by imitating the behaviors of their supervisors and other counselors (Lampropoulos, 2002). Given that skills and techniques factors account for 15% of counseling outcome (Lambert & Barley, 2001), supervisors are in a position to model skills and techniques of counseling in supervision as a means of fostering supervisee learning and skill acquisition. Integrating common factors with the discrimination model, André’s supervisor might take on the role of teacher to watch a video clip with André of a recent counseling session in which André struggled to reflect feeling, directing him to role-play with his supervisor other ways that he could respond to his client when emotional content is disclosed. André’s supervisor also could provide him with a list of “feeling words” or other relevant resources in order to help him to increase his awareness of emotion and to broaden his feelings vocabulary.

Assessment of Supervisee Needs and the Provision of Feedback

A final tenet of the CFDM is assessment of supervisee needs and the provision of feedback utilizing the roles and foci presented in the discrimination model. Using the CFDM, the supervisor would implement tailoring (also referred to in the counseling literature as prescriptive matching)—or adapting supervision to fit the characteristics, worldviews and preferences of the supervisee—as would be done with clients in common factors approaches to counseling (Norcross & Halgin, 1997). In their review of the literature on clinical supervision, Goodyear and Bernard (1998) identified attending to supervisees’ individual differences as an essential component of effective supervision. Furthermore, tailoring is inherent in the discrimination model, which recommends matching the supervisor’s role to supervisee needs (Bernard, 1979, 1997). As a beginning clinician, André might express a greater need for structured, directive supervision compared to more experienced supervisees (Stoltenberg, McNeill, & Crethar, 1994). Because André self-disclosed his perception of emotion and how this relates to his identity as a male, his supervisor should include this in her conceptualization of André and how he approaches work with clients. Furthermore, this is a value that she might continue exploring with André in future supervision sessions if it could have an impact on his clinical work with clients. Multiple supervision models have recommended matching supervision to the supervisee’s therapeutic approach and cognitive and learning styles (e.g., level of cognitive complexity; Loganbill, Hardy, & Delworth, 1982; Stoltenberg, 1981), and Norcross and Halgin (1997) suggested beginning the supervisory relationship with a needs assessment to determine the supervisee’s unique needs, goals and preferences for supervision. Although tailoring can pose unique challenges for supervisors providing triadic or group supervision, individual differences such as supervisees’ level of experience, learning goals, gender and ethnicity can be taken into account in these formats.

Table 1

CFDM: Examples of DM Focus and Role Intersections and Common Factors Strategies (CFS)

Supervisor Roles (DM)
Supervision Focus Area (DM) and CFS

Teacher

Counselor

Consultant

Intervention André reports that he is uncertain of how to perform a lethality assessment. André struggles to reflect feeling and meaning with clients. André is interested in using children’s books in session with elementary-aged children.
Common Factors Strategy: Supervisor teaches André the necessary steps of assessing for lethality, then the dyad engage in a role play in which the supervisee tests his new knowledge by performing a lethality assessment with the supervisee acting as the client.(Acquisition of New Knowledge and Skills) Supervisor asks André to reflect on the fact that he demonstrates empathy toward his clients while in supervision but struggles to show empathy by reflecting feeling and meaning in session.(Self-Exploration, Awareness, and Insight) Supervisor provides André with resources for using bibliotherapy in child counseling and offers to help the supervisee brainstorm methods for utilizing this intervention in counseling.(Acquisition of Knowledge and Skills)
Conceptualization André struggles to provide client with accurate diagnosis. André perceives himself as being an ineffective counselor because he has difficulty choosing interventions in session. André requests more information on client stages of change.
Common Factors Strategy: Supervisor and André practice diagnosing fictional clients using case studies from a DSM-5casebook. Supervisor then assigns André homework to practice completing a few case studies independently. Supervisor and André review and discuss André’s answers collaboratively during following supervision session.(Acquisition of Knowledge and Skills) Supervisor reflects supervisee’s feelings of inadequacy, offers encouragement, and normalizes the developmental challenges of supervisees. (Supervisory Relationship – Instillation of Hope and Raising of Expectations) Supervisor assists supervisee with locating information on client stages of change and discusses with supervisee the idea of conceptualizing client’s progress in counseling within the context of the client’s stage of change. (Acquisition of Knowledge of Skills)
Personalization André exhibits behaviors that resemble racial microaggressions. André’s performance anxiety causes him to appear distracted in session. André shares that a client reminds him of his deceased mother.
Common Factors Strategy: Supervisor reviews videotape of session with André and identifies an instance in which he exhibits a microaggression toward client. Supervisor gives André feedback on microaggressions and encourages André to engage in self-reflection on personal biases. (Provision of Feedback) Supervisor reflects André’s feelings of anxiety and asks André to reflect on how his anxiety may be affecting his work with clients. (Supervisory Relationship – The Real Relationship) Supervisor offers to help André process countertransference and communicates to André that he has handled the situation ethically and professionally by sharing with his supervisor his feelings of countertransference toward his client. (Supervisory Relationship and Provision of Feedback)

Practical Challenges and Limitations

Utilization of the CFDM might pose challenges that warrant discussion. For example, the CFDM might intensify the parallel process due to its similarities to the structures and processes of counseling. Moreover, CFDM’s parallels to counseling might blur the lines between supervision and counseling, making it important for supervisors to clearly delineate the role and functions of supervision. Thus, the CFDM endorses utilizing the Rogerian condition of genuineness to facilitate an open, collaborative discussion between the supervisor and supervisee when potentially problematic issues of parallel processing arise in supervision. Furthermore, the CFDM might be vulnerable to challenges in dual relationships, as the various discrimination model roles that the supervisor might assume could blur the lines between the supervisory relationship versus other relationships that the supervisor might have with the supervisee, such as that of instructor. Therefore, supervisors utilizing the CFDM are encouraged to have an open discussion with supervisees from the beginning of supervision concerning the purposes, limitations and boundaries of the supervisory relationship. Such conversations can be facilitated with the use of a professional disclosure statement that outlines the supervisor’s roles (Blackwell, Strohmer, Belcas, & Burton, 2002; Cobia & Boes, 2000).

Because the central tenet of the CFDM is the identified supervisory relationship, a potential challenge that is perhaps inherent in the CFDM is addressing weaknesses and ruptures in the supervisory relationship. The CFDM might also be challenging for supervisors or supervisees who inherently struggle to establish strong supervisory and therapeutic relationships. Supervisees who demonstrate limited ability to establish a strong therapeutic relationship might benefit from direct instruction on behavioral skills that facilitate the therapeutic relationship, such as reflections of feeling and meaning. Lampropoulos (2002) recommended that gatekeeping measures be implemented for students who consistently demonstrate deficiency in establishing a strong therapeutic relationship with clients. Finally, outcome research is indicated to examine the validity of applying common factors principles of psychotherapy to clinical supervision, as well as the empirical merit of an integrated common factors and discrimination model of supervision.

Conclusion

The supervision literature abounds with approaches for supervising counselors; however, there is little evidence that any one approach outperforms another. Common factors approaches to counseling and supervision draw on the components that are shared among models for a parsimonious approach that places emphasis on the factors that are essential in producing positive counseling and supervision outcomes. However, although such factors are necessary, they are not sufficient for yielding positive change. Therefore, Watkins and colleagues (2015) noted the necessity of applying the specific factors of some form of supervision to a common factors approach. We have responded to this call by presenting the CDFM, which integrates the specific factors of Bernard’s (1979, 1997) discrimination model with the most common elements of counseling and supervision approaches: (a) the supervisory relationship, (b) supervisee acquisition of new knowledge and skills, (c) supervisee self-awareness and self-reflection, and (d) assessment of supervisees’ needs and the delivery of feedback according to the tenets of the discrimination model.

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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A. Elizabeth Crunk is a doctoral candidate at the University of Central Florida. Sejal M. Barden is an Assistant Professor at the University of Central Florida. Correspondence can be addressed to Elizabeth Crunk, University of Central Florida, College of Education and Human Performance, Department of Child, Family, and Community Sciences, 4000 Central Florida Blvd., P.O. Box 161250, Orlando, FL 32816-1250, elizabethcrunk@gmail.com.

Moving Beyond Debate: Support for CACREP’s Standard Requiring 60 Credit Hours for School Counseling Programs

Clare Merlin, Timothy Pagano, Amanda George, Cassandra Zanone, Benjamin Newman

The Council for Accreditation of Counseling and Related Educational Programs (CACREP) recently released its 2016 standards. Included in these standards is a requirement for school counseling master’s programs to have a minimum of 60 credit hours by the year 2020. This credit hour requirement is an increase from the previous 48-hour requirement and has caused considerable debate in the counselor education field. In this article, the authors assert that the credit hour increase will lead to positive or neutral effects for school counseling programs and benefit the field of school counseling as a whole. This claim is supported by historical examples, anticipated benefits to school counseling, and findings from a pilot study with school counseling programs that previously transitioned to 60 credit hours (N = 22).

 

Keywords: CACREP, accreditation, school counseling, counselor education, credit hours

 

The unification of the counseling profession is an aspiration long held within the field (American Counseling Association, 2009; Bobby, 2013; Simmons, 2003). However, historic differences in Council for Accreditation of Counseling and Related Educational Programs (CACREP) standards for completion of a counseling degree complicate a singular identity for the profession. Without a unified expectation of degree requirements, professionals who identify as “counselors” struggle to find a consentient definition for the counseling role. In order to reach unification in the field, it is necessary for counseling organizations and professionals to agree on the minimum credit requirements needed to obtain a counseling degree (Bobby, 2013; Williams, Milsom, Nassar-McMillan, & Pope, 2012).

 

Minimum credit requirements for a school counseling degree gained recent attention as CACREP released updated standards in 2016, including a new standard (1.J.) requiring 60 semester credit hours for all counseling specializations, including school counseling, rather than the previous 48-credit hour requirement (CACREP, 2015). CACREP designed this standard to create unity among program specialties so that all specialties—addictions counseling, career counseling, clinical mental health counseling, clinical rehabilitation counseling, college counseling and student affairs, marriage, couple, and family counseling, and school counseling—require the same number of credit hours (CACREP, 2015; Williams et al., 2012).

 

The publication of standard 1.J. has implications for numerous counselor education programs. In 2014, the authors researched the 229 CACREP-accredited school counseling programs in existence  at the time and found that 170 programs, or 74%, required less than 60 credit hours for program completion. Similarly, in a study examining school counselor education programs (N = 126), Perusse, Poynton, Parzych, and Goodnough (2015) found that programs ranged in credit hour requirements from 30 to 67 semester credit hours, with an average of 49.6 credit hours. Sixty-one percent of program coordinators surveyed indicated that they required between 48 and 59 credit hours, whereas only 18% required 60 to 67 credit hours, and 14% required 36 to 45 credit hours. Although only 57% of the sample surveyed was CACREP-accredited, the percentage of participants requiring less than 60 credit hours in their programs in 2015 (75%) indicates that for these programs to become CACREP-accredited or reaccredited, many program coordinators will need to increase credit hours to 60 to meet standard 1.J.

 

Despite CACREP’s intentions for unification via standard 1.J., the standard’s implications for school counseling programs across the country have led to debate among counselor educators. In this article, the authors acknowledge concerns over the standard’s implications but suggest that an increase in required credit hours for CACREP-accredited school counseling programs will ultimately benefit school counseling programs and the school counseling field as a whole. The authors support this claim with a review of the history of CACREP and credit hour increases, prior research on the topic, results of a pilot study with programs that previously transitioned to 60 credit hours, and anticipated benefits for the school counseling field.

 

History

 

CACREP began in 1981 as a partnership between the Association for Counselor Education and

Supervision (ACES) and the American Personnel and Guidance Association, now known as the American Counseling Association (ACA; Bobby, 2013; Urofsky, Bobby, & Ritchie, 2013). This formation resulted when leaders from ACES, the American School Counselor Association (ASCA), the American College Personnel Association, and American Personnel and Guidance Association created comprehensive accreditation standards for counseling programs (Urofsky et al., 2013). Prior to the formation of CACREP in 1981, the only accreditation for counseling programs was provided by ACES on a voluntary basis (CACREP, 2017).

 

CACREP was formed to address three purposes: (a) to create guidelines reflecting expectations of the counseling profession, (b) to promote professionalism in counseling, and (c) to increase credibility in the profession (Adams, 2006; Bobby, 1992). More than 30 years later, the central mission of CACREP remains promoting the profession of counseling and related fields via “the development of preparation standards; the encouragement of excellence in program development; and the accreditation of professional preparation programs” (CACREP, 2017, para. 54). Through this process, CACREP provides accreditation to individual programs at the master’s and doctoral levels (CACREP, 2014).

 

Each area of CACREP accreditation maintains different programmatic standards in addition to a core set of general standards required of all counseling programs. CACREP designed the school counseling standards to prepare graduates to work with K–12 students to effectively address their personal/social, academic and career concerns (CACREP, 2015). CACREP standards appear increasingly valuable as leaders in the counseling profession seek a unified professional identity, particularly in light of the widely varying state licensing standards for counselors (Mascari & Webber, 2013). The CACREP standards serve as universal guidelines of best practices in educating future counselors. Moreover, researched benefits of attending a CACREP-accredited counseling program instead of a non-accredited program may include “increased internship and job opportunities, improved student quality, helpfulness in private practice, increased faculty professional involvement and publishing, and acceptance into a counselor education doctoral program” (Mascari & Webber, 2013, p. 20).

 

CACREP standards appear particularly relevant in the school counseling profession. In a study of 187 school counselors, on average, participants rated the CACREP school counseling standards as “highly” or “very highly” important to school counseling (Holcomb-McCoy, Bryan, & Rahill, 2002). This finding indicates support for the value of CACREP school counseling standards to the field of school counseling (Branthoover, Desmond, & Bruno, 2010), which is important, given that school counseling programs are the most represented master’s counseling specialty among CACREP-
accredited programs. School counseling programs comprise 36% of all CACREP-accredited programs, nearly 10% more than clinical mental health counseling programs (CACREP, 2016a).

 

Standards Changes

Despite research on the perceived value and benefits of CACREP standards, multiple facets of CACREP have proven controversial within the counseling profession. These controversies serve as proverbial lightning rods, creating conversation among leaders in the field (Schmidt, 1999). Historically, debate emerged in counselor education due to standards revisions. As in most professions, CACREP regularly modifies its standards to account for changes in the field of counseling (Adams, 2006). To modify the standards, a CACREP standards Revisions Committee formulates revised standards, releases the standards to the public for a comment period, and revises standards according to public feedback. They then release a second draft of revised standards, allow for public comment, and revise the standards accordingly before releasing a final set of revised standards (Williams et al., 2012). Periodic revisions of CACREP standards help counseling leaders address the current and future training needs of professional counselors (Bobby & Urofsky, 2008). These modifications are integral to the development of the counseling profession and parallel other helping professions that regularly revise training standards (Adams, 2006).

 

     2009 Standards changes. One standards change controversy stems from the counseling profession developing a professional identity independent from counseling psychology and other counseling-
related fields. CACREP 2009 standard I.W.2. indicated that core faculty members preferably are trained in Counselor Education and Supervision doctoral programs (CACREP, 2009).

 

Research conducted shortly after the standard was published in 2009 demonstrated mixed opinions on the standards change—55% of the 180 counselor educators surveyed agreed or strongly agreed with the standard and 45% disagreed or strongly disagreed with it (Cannon & Cooper, 2010). Although counseling leaders may be attempting to move the field toward unification with standards like I.W.2., standards changes will not transpire without debate in the field.

 

Around the same time, a second debate emerged when proposed 2009 CACREP standards required community counseling programs to become clinical mental health counseling programs with 60 credit hours, rather than the previous 48-hour community counseling requirement, in order to become accredited (CACREP, 2009). This standard eventually became part of the 2009 CACREP standards, but not before raising fractured dialogue among counselor educators (Henriksen, Van Wiesner, & Kinsworthy, 2008). Henriksen et al. (2008) found opinions among 51 counselor educators in the state of Texas were nearly evenly divided about the issue—49% preferred to keep a 48-credit hour minimum, and 51% preferred a switch to a 60-hour minimum.

 

Similarly, Cannon and Cooper (2010) surveyed 295 CACREP counselor educators and found that attitudes toward the 2009 standards changes were mixed. They found attitudes toward the credit hour increase differed between community counseling counselor educators and clinical mental health counselor educators. Twenty-seven percent of community counselor educators agreed or strongly agreed with the 48-credit hour requirement, whereas only 4% of clinical mental health counselor educators agreed with the same requirement. Across all participants, 31% indicated satisfaction with the 2009 standard revisions, 38% disagreed or strongly disagreed that they were satisfied with the revisions, and 31% reported indecision. Similar disagreement over standards changes emerged six years later around the 2016 CACREP standards.

 

2016 Standards changes. On May 12, 2015, CACREP released the 2016 Standards, effective July 1, 2016. These standards are the product of a review process in which a Standards Revision Committee comprised of counselor educators from across the country examined if and how the CACREP Standards needed to be changed to meet the shifting needs of the counseling profession. They also focused on “simplifying, clarifying, and consolidating the existing standards” in their revisions (CACREP, 2012, para. 1). CACREP released the first draft of the 2016 Standards in September 2012 and allowed for public comment. They revised the Standards according to feedback, released the revised draft for further public comment, and revised the standards once more (Williams et al., 2012). The Standards Revision Committee then submitted a final Standards draft to the CACREP Board of Directors for adoption. It was adopted and released in May 2015 (CACREP, 2016b).

 

The 2016 CACREP standards suggest more equitable education among the different counseling specializations with regard to the required number of credits a student must accrue in order to graduate (CACREP, 2015).  For example, although the 2009 CACREP standards required that the addictions counseling, clinical mental health counseling, and marriage, couple, and family counseling programs had a minimum of 60 semester credit hours, the school counseling, career counseling, and student affairs and college counseling programs required only a minimum of 48 semester credit hours (CACREP, 2009). The proposed 2016 Standards, however, require that all degree programs have a minimum of 60 credit hours by 2020 (CACREP, 2015). In time, these changes aim to unify all counseling specializations (Williams et al., 2012). Such an increase in credits aligns with CACREP’s mission of developing standards that better the profession and affirm a unified identity (Bobby, 2013).

 

When CACREP published proposed standard 1.J., requiring school counseling programs to have a minimum of 60 credit hours by 2020 (CACREP, 2015), debate arose. At the 2013 ACES School Counseling Interest Network meeting, counselor educators expressed concern about the proposed standard (Transforming School Counseling and College Access Interest Network [TSCCAIN], 2013). Some attendees asserted that mandating an increase to 60 credit hours would disenfranchise low-income students. Attendees argued that an increase in program costs and subsequently, tuition costs, could make counseling less practically desirable to otherwise qualified prospective students. Additionally, some counselor educators stated that increasing the number of credits for school counseling programs would place an undue burden on the training programs themselves by forcing these programs to hire more faculty members to teach additional courses. However, some counselor educators expressed support for the proposed credit hour increase, suggesting the standard could lead to higher quality applicants to school counseling programs and ultimately produce better qualified professionals in the field (TSCCAIN, 2013).

 

Although concerns about the outcomes of transitioning to 60 credit hours are understandable, when compared to the gains that can be made by increasing credit hours, standard 1.J. appears warranted. Three pieces of evidence support this claim: existing research on credit hour increases, data from a pilot study, and anticipated benefits to the school counseling field.

 

Existing Research

 

To date, no research has explored the implications of changing school counseling credit hour requirements from 48 to 60; however, it is beneficial to explore other fields of study to understand trends, long-term effects and the manner in which other researchers have studied this topic. Previous studies either focused on non-counseling fields (T. K. Fagan, personal communication, November 1, 2014) or are in school counseling-related fields, but the research is significantly outdated (Barkley & Percy, 1984; Hollis, 1998).

 

More than 30 years ago, Barkley and Percy (1984) explored enrollment in counselor education programs. As the most recent individuals to publish on this topic, their research still warrants attention. Barkley and Percy’s study examined the declining rate of applications to counselor education programs (N = 90) in the United States at that time. They used correlation research to examine whether or not relationships existed between the number of applications to programs, program accreditation status, and whether programs had increased credit hours between 1975 and 1983. Barkley and Percy found that although accredited programs in their sample (n = 8) had more applicants than non-accredited programs (n = 77), those that increased credit hours (n = 39) encountered fewer applicants than those that did not (n = 37). They hypothesized that applicants to lower credit hour programs were more interested in attending lower credit requirement schools than higher credit requirement schools (Barkley & Percy, 1984; Hollis, 1998). They found that these relationships were weak, however, and concluded: “There is no evidence from this study to support a hypothesis that seeking accreditation and/or moderate increases in credit hour requirements results in declining enrollments” (Barkley & Percy, 1984, pp. 23–24).

 

In the related field of school psychology, the National Association of School Psychologists (NASP) is a professional association recognized by the National Council for the Accreditation of Teacher Education as a specialized professional association. NASP began reviewing and approving school psychology programs in 1988. In 2011, approximately 70% of school psychology programs in the United States were NASP-approved (Prus & Strein, 2011). When the NASP credit hour requirement for school psychology programs changed from a master’s degree to a 60-credit hour Educational Specialist (Ed.S.) requirement, programs that adjusted to meet this new requirement received a comparable amount of applications (T. K. Fagan, personal communication, November 1, 2014). This outcome in school psychology suggests that school counseling programs increasing to 60 credit hours also may receive similar numbers of applicants after increasing to 60 credits as they did before increasing credit hours.

 

Although little research addresses differences between counseling programs before and after credit hour changes, research on CACREP-accredited programs and non-accredited programs may indicate potential differences, given that, on average, accredited programs require more credit hours than non-accredited programs (Hollis, 1998; Mascari & Webber, 2013). In 1998, Hollis compared admissions data from 104 mental health counseling programs and found that on average, CACREP-accredited programs required students to have higher grade point averages for admission (3.02) than non-accredited programs (2.91). Minimum GRE scores for admissions were nearly the same, but graduation rates differed. Despite similar average enrollments across programs, CACREP-accredited programs graduate more students on average than non-accredited programs (Hollis, 1998). This research may indicate potential differences in graduation rates and admission standards between programs with higher and lower credit hour requirements.

 

These three examples suggest that credit hour increases do not lead to poorer outcomes for programs and may in fact enhance the overall educative experience. Though findings did not include conclusive evidence of benefits from increasing credit hours, the studies showed that after programs increased credit hours, they encountered similar admissions outcomes (Barkley & Percy, 1984; T. K. Fagan, personal communication, November 1, 2014) or improved graduation rates (Hollis, 1998) compared to those measures before increasing credit hours. Consequently, there is no research base to conclude that increasing counseling program credit hours is harmful to counseling programs in admissions or graduation rates.

 

Pilot Study

 

Although existing research is consistent, it is outdated. To understand the potential outcomes school counseling programs encounter when they increase credit hours, the authors conducted a pilot study to explore the admissions and job placement data of CACREP-accredited school counseling master’s programs that previously transitioned to 60 credit hours. In 2014, 59 (26%) of the 229 school counseling CACREP-accredited programs required 60 credits or more for program graduates. This number constitutes more than one quarter of all CACREP-accredited school counseling programs, despite CACREP requiring only 48 credit hours at the time. Furthermore, it supports Hollis’ (1998) assertion that counseling programs often increase their required credit hours before higher standards are established. These increases may symbolize support for and valuing of increased credit hours for the benefit of program graduates. The authors collected admissions and job placement data from CACREP program liaisons (henceforth, “participants”) whose school counseling programs previously transitioned to 60 credit hours. They also explored the participants’ perceptions regarding whether transitioning to 60 credit hours impacted program admissions and graduate job placement rates. Though the study was a pilot with limited sample size (N = 22), the exploratory data may prove insightful for school counseling faculty members looking to transition programs to 60 credit hours.  These data also may be helpful for researchers to understand the potential impact of credit hour transitions on programs.

 

Participants provided data via a 26-item electronic questionnaire. Twenty-four questions addressed quantity of applications, quality of applications (measured by enrolled students’ undergraduate grade point average [GPA], GRE scores, racial demographics, gender demographics, international demographics, and out-of-state demographics [Cassuto, 2016]), and graduate job placement rates. Two open-ended questions explored participants’ perspectives on the topic. The questions read: “From your perspective, what, if any, impact did the transition to a 60-credit graduation requirement for master’s school counseling programs at your institution have on the quantity, quality and diversity of applicants?” and, “What (if any) feedback on the survey would you like to provide to the researchers?”

 

Positive and Neutral Outcomes

CACREP standard 1.J. established equal credit hour requirements in order to create unity among counseling specialties, thus leading to positive effects for the profession (Williams et al., 2012). In their pilot study, the authors found that all participants contributing program data (n = 7) experienced positive or neutral effects in some items measuring admissions quality, admissions quantity or graduate job placement rates after transitioning to 60 credit hours. Although data indicated mixed experiences for two items, enrolled students’ undergraduate GPAs and GRE scores, in the majority of items participants encountered only positive and neutral effects. These items were: racial diversity of enrolled students, number of enrolled international students, number of enrolled out-of-state students, and job placement rates of program graduates.

 

Participants who provided comments to open-ended questions (n = 22) contributed further insights on these positive outcomes after transitioning to 60 credit hours. Nine participants explicitly stated that transitioning to a 60-credit hour minimum had a positive impact on their school counseling master’s programs. For example, one participant stated that the 60-credit hour program format “brought better applicants,” and another participant said, “I believe our student applicant pool increased in size as well as improved in quality of applicant.” A third participant indicated the following as a result of changing to 60 credit hours:

 

The quality of our program increased as did our enrollment. We anticipated an initial drop in enrollment that never materialized. Students told us that they preferred the comprehensive training they would get with a 60-hour program and selected us over other 48-hour programs. Our program grew as a result of moving to 60 hours.

 

This feedback suggests that for this participant’s program, transitioning to 60 credit hours clearly led to positive results.

 

Six participants responded to open-ended questions indicating neutral outcomes from transitioning to 60 credit hours. They stated that they did not believe their programs’ transition to a 60-credit hour minimum had an impact on admissions or job placement rates. For example, one participant noted, “The transition from 48 to 60 hours seemed to have no effect whatsoever on the quantity and quality and/or diversity of applicants.” Another participant described the change as having “little to no negative impact” on their program, and another described it as having “minimal impact.” The latter participant wrote, “I see no significant change in applicant qualifications.”

 

It is notable that three of the items that did not change for any participants—quantity of enrolled international students, quantity of enrolled out-of-state students, and enrolled students’ racial diversity—are items measuring program diversity. This finding suggests that for the participants in this pilot study, the credit hour transition did not impact applicant diversity to their school counseling programs. This may counter the notion that requiring 60 credit hours for program completion will disenfranchise certain students due to increased tuition (TSCCAIN, 2013). In addition, previous research indicates variables such as financial aid packages, faculty contact with prospective students, diverse student populations, and faculty diversity influence the recruitment of diverse students (Guiffrida & Douthit, 2010; Shin, Smith, Goodrich, & LaRosa, 2011; Talleyrand, Chung, & Bemak, 2006). These variables may be more impactful on recruiting diverse students than program credit hours.

 

Negative Outcomes

Despite the professed intent of CACREP standard 1.J. (Williams et al., 2012), some counselor educators speculated that such credit hour increases would have negative effects on school counseling programs (TSCCAIN, 2013). Of all participants in the pilot study whose programs transitioned to a 60-credit hour requirement, none expressed perceptions that increasing their credit hours led to negative outcomes. This finding suggests opposition to arguments that increasing to 60 credit hours will result in harmful effects in programs. The fact that 22 study participants commented on their transitions to 60 credit hours and none expressed the belief that transitioning caused negative outcomes appears noteworthy.

 

Descriptive statistics of program data showed that only one item, enrolled students’ gender diversity, decreased or stayed the same when participants’ programs transitioned to 60 credit hours. Although this finding may indicate worsening gender disparity in counseling, recent statistics demonstrate a consistent discrepancy in the number of male and female individuals in the counseling profession (Evans, 2013). According to data from ACA, males consistently comprised only 26–29% of the ACA membership between 2002 and 2012 (Evans, 2013). Given the consistency of these percentages over time, it is reasonable that the participants in this study saw gender diversity decrease or stay the same despite transitioning to 60 credit hours because the construct is one that is stable over time and may not have been impacted by credit hour increases. Similarly, CACREP’s 2015 Annual Report authors noted that only 18% of students enrolled in CACREP programs are male (CACREP, 2016a), adding additional legitimacy to a concern for gender disproportionality in counseling overall and disaffirming concern for decreased gender diversity due to credit hour increases.

 

Program Factors Impacting Outcomes

In the debate over increasing school counseling program credit hours, dialogue centered on the impact that a credit hour increase might have on programs. However, pilot study findings indicated that when programs previously transitioned to 60 credit hours, program-specific characteristics likely had a greater impact on transition outcomes than the transition itself.  For example, multiple participants indicated that current events during the time of their credit hour transition appeared to impact their program admissions and student job placement rate more than the actual credit hour transition. As one participant explained:

 

I don’t think the 60 credits had any impact. The year we moved to 60 was right when the economy went bust, so all of our programs experienced a drop in applicants. We tend to be pretty consistent in the quality of our applicants overall as well as in the relative diversity of our applicants.

 

Other participants noted that their original number of credit hours prior to transitioning to 60 credits likely impacted their program outcomes after transitioning. Several participants worked in school counseling programs that transitioned from 55 or 57 credit hours to 60 credits. They stated that increasing their program requirements by just a few credit hours did not appear to impact their program admissions or graduate job placement rate.

 

     Another participant indicated school counselors in their state are paid a higher salary if they graduate from 60-credit hour programs. Therefore, offering a school counseling program with a 60-credit hour track helped market the program, the participant reported. If school counseling faculty members work in states in which school counselors receive higher salaries for earning 60 credit hours, then a credit hour increase may lead to more positive changes in admissions than negative ones.

 

Lastly, hosting other counseling specialties (e.g., clinical mental health, addictions) at a university may impact a school counseling program and its transition to 60 credit hours. One participant noted that their school counseling program increased to a 60-credit hour minimum because the other counseling programs at their institution already required 60 credit hours. This participant said, “We decided to move all programs to 60 hours rather than have the difference in concentrations (in part due to perceptions of why one concentration would require more than the other).” If faculty members are increasing credit hours for school counseling programs at institutions in which other counseling programs already required 60 credit hours, the credit increase may be more widely accepted by potential applicants and lead to neutral or positive outcomes in admissions.

 

According to pilot study participants, each of these program factors impacted the effects their programs encountered after changing to 60 or more credit hours. Counselor educators leading school counseling programs that have not yet transitioned to 60 credit hours may take note of the factors and examine their own programs’ characteristics that may impact transition outcomes. Counselor educators would benefit from reflecting on the context and characteristics of their programs before concluding that increasing to 60 credit hours will be problematic.

 

Benefits to School Counselors

 

As the field of school counseling has evolved, so has the preparation of school counselors-in-training. Such preparation has evolved from an emphasis on vocational guidance (Cinotti, 2014), to training on comprehensive programming (ASCA, 2012; DeKruyf, Auger, & Trice-Black, 2013), to training on leadership and advocacy to create systemic change in schools (Ockerman, Patrikakou, & Feiker Hollenbeck, 2015). Researchers, counselor educators and school counselors are frequently calling for even better training. Recent calls include better preparation in instructional techniques to effectively conduct classroom guidance lessons (Ohrt, Blalock, & Limberg, 2016), collaborative coursework with educational leadership students (Beck, 2016; DeSimone & Roberts, 2016), preparation specific to working in urban areas (Hannon, 2016), suicide assessment practice (Douglas & Wachter-Morris, 2015), training in navigating professional identity issues (Gilbride, Goodrich, & Luke, 2016; Scarborough & Luke, 2008) and improved training in Response to Intervention to advance school counseling services (Ockerman et al., 2015).

 

In creating CACREP standard 1.J., CACREP has created an opportunity for counselor educators to add coursework that meets these calls and better prepares school counselors-in-training for the needs they will encounter in schools. Counselor educators may want to consider adding courses on the preparation topics called for, such as consultation in school counseling (Ockerman et al., 2015), leadership in school counseling (Beck, 2016; DeSimone & Roberts, 2016), and conducting classroom guidance lessons (Ohrt et al., 2016). In better training future school counselors in these areas, counselor educators can enhance the expertise of school counselors graduating from their programs, and ultimately better support K–12 students.

 

Lastly, CACREP’s standard 1.J. holds the potential to benefit the school counseling field as a whole. School counselors serve as both counselors and educators in schools and often receive mixed messages about this dual role (Cinotti, 2014). CACREP’s previous school counseling credit hour requirements may have contributed to school counselor role confusion, suggesting that school counselors were not as well-trained as clinical mental health counselors or counselors in other specialties requiring 60 credit hours. In establishing the same credit hour requirements for all counseling programs, CACREP has asserted that school counselors are equally as well-prepared as their colleagues in clinical mental health, marriage and family counseling, addictions counseling, and other specialties. Such an affirmation lends support to the professional standing of school counselors in the counseling field.

 

Future Research

 

     With the recent release of the 2016 CACREP standards and the inclusion of standard 1.J. requiring 60 credit hours for school counseling programs, faculty members who work at programs with less than 60 credit hours may want to look to the 59 programs that have already transitioned to 60 credit hours as models for transition. Although counselor educators have understandable concerns about the impact that a credit hour increase may have on school counseling programs, previous research and the authors’ pilot study findings provide limited support for these concerns. Instead, research indicates that on average, school counseling programs may encounter improved outcomes in programs admissions and graduate job placement rates or similar outcomes to those experienced before increasing credit hours. Future research on programs that transition to 60 credits will prove valuable in confirming these outcomes.

 

To conduct this research, researchers will need longitudinal program data, including ongoing admissions and job placement data, from universities. In collecting data for their pilot study, the authors learned that many school counseling programs do not maintain continuous data on admissions and job placement. Of the 34 participants who initially responded to the pilot study questionnaire, 27 participants could not provide complete quantitative data on program admissions or job placement rates. Many of these participants noted that they were unable to do so because such data were unavailable. Some participants reported that transitioning to 60 credit hours so long ago inhibited them from finding and submitting data; seven participants indicated that they transitioned to 60 credit hours more than 15 years ago.

 

Reasons for unavailable data varied, but most had to do with the absence of data-keeping over time. One participant wrote, “I apologize that I don’t have concrete data for you. It’s a long time ago that we changed to 60 hours (8 years). I was not program director then.” Another participant explained, “We transitioned almost 30 years ago . . . and it would be impossible to get the information to you.” A different participant highlighted that aggregate data-keeping presented a challenge. They wrote, “I am sorry I cannot answer the first part of this survey. Because we have a counselor-first identity, all program admission processes are in aggregate—we do not have separate data for community counseling students, clinical mental health counseling students, and school counseling students.”

 

These data-keeping challenges pose an obstacle for future research on the impact of credit hour changes on counseling programs. They also support Shin and colleagues’ (2011) findings that counselor education programs often do not maintain admissions data. In their survey research study of 114 CACREP liaisons, Shin et al. found that although some participants reported maintaining admissions and student race and ethnicity data for up to 20 years, other programs reported keeping this data for as little as one year. Moreover, 57% of participants reported not retaining information on prospective students that declined admission to their programs. Although these data may or may not be related to the impact that credit hour changes have on counseling programs, these data-keeping percentages suggest that counseling programs could benefit from collecting and maintaining data in more thorough and consistent ways.

 

When conducting research on credit hour increases, researchers may also want to examine data points other than admissions and job placement. When counselor educators devote added credit hours to new coursework, they can consider how this coursework will benefit counselors-in-training, then measure those benefits. For example, if counselor educators devote extra credit hours to coursework in advanced techniques, they should collect and maintain data on the counseling techniques of counselors-in-training before and after transitioning to 60 credit hours. If counselor educators create extra coursework in consultation in schools, advocacy or leadership, these skills can be assessed in students before and after creating the courses. Evaluations from employers of alumni can also be examined to explore if counselor ratings improve after increasing credit hours.

 

If researchers are to better understand the impact that credit hour changes have on counseling programs, it is imperative that counselor educators regularly collect and store data on program outcomes. If counselor educators can begin doing so before credit hour changes take effect, they may be able to track trends in program outcomes associated with the credit hour changes over time. Researchers would be wise to begin longitudinal studies with programs in order to collect data on an ongoing basis and determine if the credit hour change has any effect. This research could prove useful in informing future CACREP standards, including potential credit hour changes. As Barkley and Percy (1984) recommended more than three decades ago, “Counselor education programs [ought to] begin keeping data on applications, acceptances, and enrollments. . . . These factors are too important to the life of most counselor education programs not to have accurate data readily available” (p. 25).

 

Conclusion

 

     In the three and half decades since CACREP was established, credit hour increases for accredited programs have been met with divided reactions from counselor educators (Cannon & Cooper, 2010; Henriksen et al., 2008; TSCCAIN, 2013). The publication of CACREP’s 2016 Standards is no exception. Counselor educators are wise to consider the program implications of any new standard, including standard 1.J. However, to date, no research provides cause to believe that this standard will significantly contribute to negative school counseling program outcomes. To the contrary, previous research indicates program outcomes will improve or stay the same after increasing credit hours, and findings from the authors’ pilot study reflect similarly. Future research can provide further valuable insights on the impact of credit hour increases on counseling programs.

 

Conflict of Interest and Funding Disclosure
This research study was conducted by the authors and was supported in part by a CACREP Student Research Grant. The article is the sole work of the authors and does not necessarily reflect the beliefs or ideas of CACREP, the CACREP Board of Directors, or CACREP staff.

 

 

 

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Williams, D. J., Milsom, A., Nassar-McMillan, S., & Pope, V. T. (2012). 2016 CACREP standards revision committee at turn one. Counseling Today, 55(5), 56.

 

Clare Merlin, NCC, is an Assistant Professor at the University of North Carolina at Charlotte. Timothy Pagano, NCC, is a doctoral candidate at the University of North Dakota. Amanda George, NCC, is a Professional School Counselor for Loudon County Public Schools in Sterling, VA. Cassandra Zanone, NCC, is a J.D. candidate at the University of California at Los Angeles. Benjamin Newman, NCC, is a doctoral student at the College of William and Mary. Correspondence can be addressed to Clare Merlin, 9201 University City Boulevard, Charlotte, NC, 28223, cmerlin1@uncc.edu.

 

Addictions Content Published in Counseling Journals: A 10-Year Content Analysis to Inform Research and Practice

Edward Wahesh, S. Elizabeth Likis-Werle, Regina R. Moro

This content analysis includes 210 articles that focused on addictions topics published between January 2005 and December 2014 in the journals of the National Board for Certified Counselors (NBCC), Chi Sigma Iota (CSI), the American Counseling Association (ACA), and ACA member divisions. Results include the types of addictions content and behaviors studied as well as the populations and data analytic techniques used in the addictions research articles. Whereas most articles discussed addictions counseling techniques, addictions issues among non-clinical populations, and professional practice issues, fewer articles addressed clients in treatment, utilized clinical populations, or analyzed intervention outcomes. Implications for addictive behaviors and addictions counseling scholarship in professional counseling are discussed.

Keywords: addictive behaviors, addictions counseling, content analysis, NBCC, ACA

Professional counselors have an ethical obligation to be actively involved in continuing education in order to remain current on relevant professional issues and scientific information related to their client population and setting (American Counseling Association [ACA], 2014). Continuing education also is required by licensing and certification bodies for credential renewal. One way continuing education is achieved is through reading and contributing to peer-reviewed journal articles. Publications can expose professional counselors, counselor educators and counselors-in-training to new and innovative practices grounded in empirical research.

Professional journals represent “the repository of the accumulated knowledge of a field” (American Psychological Association, 2010, p. 9). A number of journals are produced by the major counseling certification and professional organizations, including The Professional Counselor, published by the National Board for Certified Counselors (NBCC); the Journal of Counselor Leadership and Advocacy, published by Chi Sigma Iota International (CSI); and the Journal of Counseling & Development (JCD), which is the flagship journal of ACA. In addition to JCD, there are 20 journals published by ACA member divisions. ACA member division-sponsored journals publish articles that inform counseling practices and contribute to the body of research on topics that are salient to the particular settings, populations, interest areas, and issues associated with the division. An area that is relevant to most professional counselors, regardless of specialty area or setting, is addiction.

According to the Substance Abuse and Mental Health Services Administration (SAMHSA), in 2014 there were an estimated 21.5 million Americans (8% of the population aged 12 or older) living with a substance use disorder (SUD; SAMHSA, 2015). It is likely that many individuals with SUDs also have other co-occurring mental health conditions. In fact, 2014 estimates suggest 7.9 million adults (i.e., 18 years and older) in the United States had both a past-year SUD and a mental illness diagnosis. Among adolescents, approximately 1.3 million reported a past-year SUD; 28.4% of these (over 300,000) had experienced a major depressive episode in the past year (SAMHSA, 2015).

While not all professional counselors will specialize in addictions counseling, given this prevalence it is likely counselors will need to provide services to individuals with an SUD (Chandler, Balkin, & Perepiczka, 2011; Harwood, Kowalski, & Ameen, 2004; Salyers, Ritchie, Cochrane, & Roseman, 2006). In addition, professional counselors are more than likely to come into contact with clients of any age who are impacted by someone else’s addiction (e.g., friend, family member). This may explain why the Council for Accreditation of Counseling and Related Educational Programs (CACREP; 2016) requires that all counselors-in-training, regardless of counseling specialty, learn about the theories and etiology of addictions. Salyers et al. (2006) found little consensus among CACREP-accredited programs in how addictions issues were addressed; in fact, when asked where substance abuse was covered in the curriculum, more than 25 different courses were listed by CACREP program representatives. Counselors-in-training learn about addictions in a variety of ways, such as by taking a course in addictions, encountering clients with addictive behaviors in practicum or internship, or learning about addictions in other courses. Since addictions-related training seems to occur throughout the counseling curriculum, all counselor educators, regardless of their particular area of specialty, should maintain an awareness of current trends in addictions science and theory.

Given that knowledge of addictive behaviors is an important aspect of professional counselor identity (CACREP, 2009; 2016), it is necessary that professional counselors have access to scientific information and practice-oriented resources on addiction that are consistent with the philosophical orientation of the profession. Whereas related professions, such as psychology, public health and social work, produce peer-reviewed publications on addictions and addictions treatment that can be utilized by professional counselors, these resources may not reflect the qualities that make professional counseling unique. Examining the state of the counseling literature on addictive behaviors and additions counseling can inform efforts to improve access to scientific information and evidence-based practices that represent the core philosophy of the counseling profession. Further, an assessment of available addictions research can help to shed light on the state of the counseling profession, as production of original research has been regarded as a standard for measuring the identity development of a profession (Mate & Kelly, 1997).

Research on trends in addictions publications in professional counseling is scarce. Moro, Wahesh, Likis-Werle, and Smith (2016) utilized content analysis to investigate the frequency and type of addictions content within a sample of Association for Counselor Education and Supervision  conference programs and four ACA-sponsored journals (JCD, Counselor Education and Supervision, Counseling Outcome Research and Evaluation [CORE], and Measurement and Evaluation in Counseling and Development) that appeal to counselor educators. These authors found that about 2% of conference sessions and articles between 2007 and 2011 addressed addictions counseling. Most of the articles identified in this analysis focused on treatment strategies, particularly among diverse populations. Although the study by Moro et al. is informative, it is limited in that it comprised a 5-year time period and included only a small subset of professional counseling journals. Examining all professional counseling journals during a lengthier time frame would provide professional counselors and researchers with a more comprehensive snapshot of what aspects of addictions theory, prevention, intervention and treatment have been discussed within the counseling literature. This information can be used to inform efforts to promote the production of research and publications that address specific areas of addiction that are currently lacking.

The purpose of the present study was to provide an overview of available literature on addictions topics in professional counseling journals published between January 2005 and December 2014. Moreover, the types of addictions content, addictive behaviors and addictions-related research were examined. The research questions that guided this study were: (1) To what extent do counseling journals address addictions topics? (2) What addictive behaviors and types of content were addressed? (3) How much addictions research was published in counseling journals? and (4) What types of populations and data analytic techniques were represented in this research?

Methods

Content analysis was utilized to address the research questions. This methodology was selected because content analysis is a systematic approach to summarize and make valid and replicable inferences from written communication (Krippendorff, 2013). A review of the literature shows that content analysis has served as a valuable methodology to identify publication trends over time and highlight attention on specific topics within the counseling profession. Content analysis has been used in the counseling literature to examine topics such as multicultural counseling (Arredondo, Rosen, Rice, Perez, & Tovar-Gamero, 2005), pedagogy in counselor education (Barrio Minton, Wachter Morris, & Yaites, 2014), and research in counseling (Ray et al., 2011). Studies by Barrio Minton et al. (2014), Arrendondo et al. (2005), and Ray et al. (2011) were of journal articles during a similar time frame as the present study (i.e., 10 years). Content analysis procedures used in this study include identifying articles, generating and refining the content analysis protocol, conducting a pretest, data collection, assessment of reliability and validity, and reporting the results.

The research team consisted of three professors and two master’s-level graduate students. The professors each possess a doctoral degree in counselor education and specialize in addictions counseling. Two professors identify as White females and one professor is a White male. The graduate assistants, both White females, hold bachelor’s degrees in psychology, completed a course in counseling research methods, and participated in a workshop on content analysis facilitated by the first author before joining the research team. The graduate assistants were responsible for searching for applicable articles using predetermined keywords and identifying the total number of articles for each journal during the time period; the three assistant professors (first, second, and third authors) participated in the search for articles as well as in the development of the content analysis protocol and coding process.

The Professional Counselor, published by NBCC, the Journal of Counselor Leadership and Advocacy, published by CSI, and 21 ACA and ACA member division peer-reviewed journals (Table 1) were identified as having published articles on addictions between the years 2005 and 2014. Because the purpose of the study was to present a survey of all available articles on addictions content in professional counseling journals between 2005 and 2014, all journals were included in the analysis even if they were not in press during the entire 10-year period under analysis.

A set of keywords was generated to identify relevant articles to be used in the study. These keywords included: (a) general terms taken from the literature on addiction and addictions treatment (e.g., addiction, prevention, relapse, recovery, abstinence, co-morbidity, behavioral and process addictions, and mutual support groups); (b) terminology drawn from the Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.; DSM-IV-TR; American Psychiatric Association, 2000) and the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5; American Psychiatric Association, 2013), such as substance use disorders, dependence, intoxication, withdrawal, substance abuse and opioid maintenance; and (c) a list of drug classifications (and common pseudonyms) from the DSM-IV-TR and DSM-5, including alcohol (drinking), amphetamine, cannabis (marijuana), cocaine, hallucinogen, opioid, stimulant, gambling, inhalant, sedative, caffeine and nicotine (tobacco, smoking).

Two graduate assistants independently conducted electronic searches using PsycINFO, EBSCO and ERIC of the keywords, titles and abstracts of all articles (editorial statements, book reviews, errata and advertisements excluded) during the specified time period to identify relevant articles and provide the total number of articles published for each journal. Journals not indexed within these electronic databases were searched by reading the electronic version of each issue’s table of contents and article abstracts and keywords. Following this process, the first author met with the graduate assistants in order to reconcile any differences between their lists of applicable texts and total number of journal articles found. A preliminary list of 226 articles was identified and reviewed by each author to determine suitability for the study. Fifteen articles were removed from the analysis because they did not discuss addictions or addictions treatment; for example, two articles included the keyword “substance abuse” in the abstract, but not in the article itself. To maintain independence, one article was removed because it had been published twice.

The authors developed a content analysis protocol that included definitions and categories for each coding variable. To address research questions 1–3, the following variables were developed: (a) addiction-related content topic, (b) addictive behavior and (c) type of research article. In order to assess research question 4, (d) data analytic technique and (e) research population also were included as variables. Categories of each variable were initially developed by the authors based on their knowledge of the addictions literature as well as past content analysis research of counseling journals. The authors then pretested the protocol by coding 40 randomly selected articles within the sample (approximately 20%) to purify the coding scheme and conduct a preliminary assessment of coder agreement. Following this process, the authors met to refine existent category definitions, agree on the inclusion of additional variable categories and determine which variables would be single versus multiple classification. High inter-rater agreement (85% or higher) across all five study variables was observed among the three coders during the pilot phase. A pattern was not observed in the disagreements among the coders, suggesting that the framework possessed acceptable construct validity (Insch, Moore, & Murphy, 1997).

Once the protocol was refined, all articles were coded independently by two members of the research team (first, second, and third authors). Krippendorff’s alpha (Krippendorff, 2013), with a minimum acceptable value set at α = .80, was utilized to assess agreement among the coders. This coefficient was selected to capture inter-rater reliability because it estimates error in observed agreement attributable to chance and accounts for small sample sizes. Using a reliability measure designed for small samples was an important consideration because research question 4 relates only to a smaller subset of the sample used in the study. Further, the use of two coders for each article was to ensure that the total number of observations for each variable in this study exceeded the minimum number recommended by Krippendorff (2013) for an alpha value greater than .80 at the .01 level of significance (i.e., according to Krippendorff [2013] two coders would have to code at least 103 units). The “odd-man-out” procedure recommended by Insch et al. (1997), in which a third coder determined the final category when differences emerged, was used to reconcile disagreements between coders.

Coding Variables

Five variables were identified by coders in the study. All articles (N = 210) were coded utilizing three of the variables: addiction-related content topic, addictive behavior and type of research. Two variables were used to code research articles identified within the sample. Percentage of agreement (observed agreement [OA]) and Krippendorff’s alpha (α) were calculated for each variable.

Addiction-related content topic. The purpose of this variable was to identify the area of addictions counseling and research that the article addressed. Categories were initially drawn from content analyses by Ray et al. (2011) and Moro et al. (2016) and modified for the present study. Because the purpose of this variable was to identify the main content focus of the articles, a single classification system was used, which meant that coders were required to assign each article to one category. The use of a single classification system is recommended when coding variables that represent latent meaning and require greater interpretation by the coder (Insch et al., 1997). The variable included the following categories: approaches to counseling, professional practice, population variables, client variables, counselor variables, measurement, and effectiveness of counseling and preventative interventions (OA = 87.6%; α = .85). Approaches to counseling included articles that presented specific addictions-related counseling techniques, models or treatment programs. The professional practice issues category contained articles that described addiction-related counselor training, credentialing, ethics, diagnosis or trends in the field. Population variables included articles that described characteristics of a non-clinical population; the client variables category contained articles that addressed addictions or addictions counseling within a clinical population. Articles on the characteristics or perceptions of professional counselors were assigned to the counselor variables category. The measurement category included any article with a focus on instrument development, formal assessment or psychometrics. Effectiveness of counseling and preventative interventions represented articles that focused on evaluating an intervention or prevention program or technique.

Addictive behavior. This variable represented the types of addictive behavior addressed in the articles. Coders were instructed to record all addictive behaviors and substances described in each article (i.e., multiple classification) using a list of categories that included relevant keywords developed by the researchers for the text search. If a specific type of behavior or substance was not discussed, coders labeled the article as general substance use. Categories representing specific behaviors and substances included: general substance use, alcohol, nicotine, opioids, cannabis, stimulants, ecstasy and behavioral addictions (OA = 95%; α = .90).

Type of research. Each article was coded as non-research, qualitative, quantitative or mixed methods (OA = 98.5%; α = .98). Classifications were based on past content analysis research of counseling journals (Moro et al., 2016; Ray et al., 2011), and coders were required to assign each article to one category. Articles that were assigned to the three research categories (i.e., qualitative, quantitative and mixed methods) were used to address research question 4.

Data analysis. All research articles were coded in order to determine the types of data analytics used by the authors. The coding variable included 15 categories (i.e., descriptive statistics, regression analysis, theme analysis and coding, chi-square test, multivariate analysis of variance/multivariate analysis of covariance, correlation, analysis of variance/analysis of covariance, structural equation modeling, t-test, confirmatory factor analysis, exploratory factor analysis, other nonparametric test, discriminant analysis, canonical analysis, and cluster analysis), and coders were instructed to assign each article to multiple categories when appropriate (e.g., case where a single research article included multiple types of analysis; multiple classification). The scheme for grouping different types of data analysis was based on a framework by Erford et al. (2011) in their content analysis of articles published in JCD. Percentage of agreement among coders in the present study was 82.4% and α = .79. Because inter-rater reliability is slightly below the recommended minimum of .80 (Krippendorff, 2013), readers are encouraged to interpret these results with caution.

Research population. The various populations examined in the research articles were recorded using this variable (OA = 91%; α = .88). Because an article could potentially include multiple populations (e.g., African American, male, college students), coders were instructed to code each article with as many categories as necessary (i.e., multiple classification). When coding, research team members used a preliminary list of possible categories derived from several previous content analysis studies of counseling journals (Byrd, Crockett, & Erford, 2012; Smith, Ng, Brinson, & Mityagin, 2008). This resulted in 11 discrete categories: undergraduates, children and adolescents, adults (non-college, 18 years and older), families, men only, women only, clients in addictions treatment, addictions professionals, counseling students, multicultural populations and LGBT populations. To improve the conciseness of the findings, several smaller categories were combined to create the multicultural populations category. A twelfth category was designated for articles that did not include a research sample.

Results

Research Question 1: To What Extent Do Counseling Journals Address Addictions Topics?

Table 1 provides a listing of counseling journals as well as the number of addictions-related articles in relationship to total publication. The percentage of the total number of addictions-related articles in comparison to total number of published articles was 4.5%. As expected, the Journal of Addiction & Offender Counseling (JAOC) published the highest percentage of addictions articles (76.1%). The journal with the next highest percentage of addictions articles was the Journal of Military and Government Counseling (13.8%), followed by the Journal of LGBT Issues in Counseling (9.6%), the Journal of College Counseling (8.6%), and CORE (8.3%). Six journals published less than 1% of their articles on addictions: The Career Development Quarterly (0.0%), Journal of Counselor Leadership and Advocacy (0.0%), Journal for Social Action in Counseling and Psychology (0.0%), Counselor Education and Supervision  (0.5%), Journal of Multicultural Counseling and Development (0.5%), and Professional School Counseling (0.9%).

The authors also examined the first research question by calculating the percentage of addictions-related articles during each year of publication. The number and percentage of addictions articles published for each year is as follows: 2005 (n = 18; 4.0%), 2006 (n = 20; 4.5%), 2007 (n = 20; 4.7%), 2008 (n = 14; 3.0%), 2009 (n = 17; 3.9%), 2010 (n = 21; 4.5%), 2011 (n = 30; 6.3%), 2012 (n = 30; 6.4%), 2013 (n = 20; 4.0%), and 2014 (n = 20; 4.7%). The percentage of addictions articles remained relatively stable during this period; however, a slight increase in the percentage of articles published on addictions was observed in 2011 and 2012.

Research Question 2: What Types of Addictive Behaviors and Content Topics Were Addressed?

All seven categories included in the addiction-related content topic variable were represented in the data. The highest number of addictions articles focused on population variables (n = 57; 27%), or addictions issues within non-clinical groups. The content topics approaches to counseling (n = 43; 20%) and professional practice issues (n = 39; 19%) were the second and third most represented categories. Fewer addiction-related articles were published on the following content topics: client variables (n = 20; 10%), measurement (n = 18; 9%), effectiveness of counseling and preventative interventions (n = 17; 8%), and counselor variables (n = 16; 7%).

Additional analysis revealed that among the 18 articles in the measurement category, 14 different assessment instruments were represented. Whereas most instruments (n = 10) were discussed in only one article each, the Substance Abuse Subtle Screening Inventory-3 (SASSI-3; Miller & Lazowski, 1999) was included in eight of the articles in this category. Three instruments were included in two articles: the Core Alcohol and Drug Survey (Core Institute, 1994), CAGE questionnaire (Ewing, 1984) and the Michigan Alcohol Screening Test (Selzer, 1971). Further, additional analysis of the effectiveness of counseling and preventative interventions category found that only four articles addressed prevention; three of these articles discussed a similar intervention to prevent college student drinking and one presented findings of an evaluation of a school-based substance abuse prevention program.

Table 1

Addiction Articles in Professional Counseling Journals, 2005–2014

Journal

No. of Addiction Articles Found

No. of Total
Possible Articles

% Addiction to No. of Total
Articles

The Professional Counselor

5

113

4.4

Journal of Counselor Leadership & Advocacy

0

13

0.0

Journal of Counseling & Development

9

561

1.6

Adultspan Journal

5

101

5.0

The Career Development Quarterly

0

282

0.0

Counseling and Values

6

191

3.1

Counselor Education and Supervision

1

199

0.5

Journal of Addiction & Offender Counseling

70

92

76.1

Journal of College Counseling

14

163

8.6

Journal of Employment Counseling

5

182

2.8

Journal of Humanistic Counseling

3

175

1.7

Journal of Multicultural Counseling and Development

1

194

0.5

Counseling Outcome Research and Evaluation

4

48

8.3

The Family Journal

17

554

3.1

Journal of Creativity in Mental Health

15

251

6.0

Journal of LGBT Issues in Counseling

13

136

9.6

Journal of Mental Health Counseling

11

244

4.5

Journal for Social Action in Counseling and Psychology

0

87

0.0

The Journal for Specialists in Group Work

5

209

2.4

Measurement and Evaluation in Counseling and Development

8

176

4.6

Professional School Counseling

4

432

0.9

Rehabilitation Counseling

10

208

4.8

Journal of Military and Government Counseling

4

29

13.8

Total

210

4,640

4.5

Note. The first issue of The Professional Counselor was published in 2011; Counseling Outcome Research and Evaluation was first published in June 2010; Journal of LGBT Issues in Counseling was first published in October 2008; Journal for Social Action in Counseling was first published in April 2007; Journal of Creativity in Mental Health was first published in September 2007; the first issue of Journal of Military and Government Counseling was published in January 2013; the first issue of the Journal of Counselor Leadership and Advocacy was published in 2014.

 

The addictive behavior coding variable also was used to assess this research question. General substance use was by far the most represented addictive behavior in the articles (n = 142; 68%), followed by alcohol consumption (n = 46; 22%) and behavioral addictions (n = 11; 5%). Specific substances were addressed in fewer articles: nicotine (n = 8; 4%), opioids (n = 4; 2%), stimulants (n = 4; 2%), cannabis (n = 3; 1%) and ecstasy (n = 1; 0.5%). The total values exceed the actual number of research articles included in the analysis because some articles addressed more than one addictive behavior. In the behavioral addictions category, sex addiction was addressed in three articles, three articles included a general discussion of behavioral addictions, and addictions to gambling, gaming, Internet, self-injury and food were each mentioned once.

Research Question 3: How Much Addictions Research Was Published in Counseling Journals?

This research question was addressed using the type of research coding variable. Approximately 60% of addictions-related articles (n = 127) were original research. Among these articles, 82% were quantitative (n = 104) and 13% were qualitative (n = 17). Mixed methods was the smallest category (n = 6), representing 5% of all addictions research. Articles coded as “non-research” (n = 83) included innovative methods papers, professional practice papers, interviews, and literature reviews on topics such as counseling theory and special populations.

Research Question 4: What Types of Populations and Data Analytic Techniques Are Represented in the Addictions Research?

Research population and data analysis were the coding variables used to assess this research question. Table 2 lists the various types of participants used in the addictions-related research articles. The most common population examined was adults (n = 49; 40%), or individuals (18 years and older) not enrolled in college, followed by undergraduates (n = 36; 29%) and addictions professionals (n = 26; 21%). The total values exceed the actual number of research articles included into the analysis because some articles included more than one population. The multicultural populations category represented a number of ethnic groups including African Americans, Native Americans and Hispanic Americans, as well as a sample of participants in Korea. Three articles were not included in this analysis because they did not involve research with human subjects (e.g., content analysis of substance use screenings).

Table 2 Types of Participants Used in Addictions Research Articles
Population Count

%

Adults

49

40

Undergraduates

36

29

Addictions Professionals

26

21

Clients in Addictions Treatment

18

15

LGBT Populations

13

10

Children and Adolescents

9

7

Multicultural Populations

9

7

Men Only

8

6

Families

5

4

Women Only

4

3

Counseling Students

2

2

Note. Three articles were removed because they did not include human subjects (n = 124). Some articles include more than one population. Therefore, the total values may exceed the actual number of research articles accepted into the analysis.

All 15 data analytic techniques were represented within the addiction-related research articles (Table 3). Descriptive statistics (n = 34; 27%), regression analysis (n = 31; 24%) and theme analysis/coding (n = 22; 17%) were the most used techniques. Data strategies less likely to be utilized include discriminant analysis (n = 4; 3%), canonical analysis (n = 3; 2%) and cluster analysis (n = 1; 1%). The total values exceed the actual number of research articles included in the analysis because some articles utilized more than one data analysis strategy.

Table 3 Type of Data Analysis Used in Addictions Research Articles
Data Analytic Procedure

Count

%

Descriptive Statistics

34

27

Regression Analysis

31

24

Theme Analysis/Coding

22

17

Chi-Square Test

16

13

MANOVA/MANCOVA

14

11

ANOVA/ANCOVA

13

10

Correlation

12

9

Structural Equation Modeling

10

8

t-test

9

7

Confirmatory Factor Analysis

7

5

Exploratory Factor Analysis

5

4

Other Nonparametric

5

4

Discriminant Analysis

4

3

Canonical Analysis

3

2

Cluster Analysis

1

1

Note. Some articles used more than one procedure. Therefore, the total values may exceed the actual number of research articles accepted into the analysis (n = 127). MANOVA = multivariate analysis of variance; MANCOVA = multivariate analysis of covariance; ANOVA = analysis of variance; ANCOVA = analysis of covariance.

Discussion

Articles published in 23 professional counseling journals between January 2005 and December 2014 were examined to assess the scope with which addictions were represented in the professional counseling literature. Overall, 210 (4.5%) of the 4,640 articles published addressed addictions content. Not surprisingly, JAOC, a publication sponsored by the International Association of Addictions and Offender Counselors, contained the most articles on addictions. It also is noteworthy that several journals with higher percentages of addictions articles were launched within the period of time the analysis was conducted (e.g., Journal of Military and Government Counseling and Journal of LGBT Issues in Counseling). The introduction of these journals may suggest that increased attention is being given to addictions issues or, at the very least, to populations that are more vulnerable to experiencing the consequences of addictive behaviors.

The higher percentage of articles in 2011 and 2012 may have been associated with changes to addictions-related professional training and diagnostic considerations that occurred around these years. In 2009, CACREP introduced an addictions counseling specialty area and added language in their standards requiring all students to learn about the etiology, prevention and treatment of addictions; therefore, it is possible that during the years following these changes, there was an increased interest in the teaching of addictions content to counselors-in-training. Alternatively, the revised formulation for the diagnosis of SUD in the DSM-5, published in 2013, also may have contributed to the increase in addictions articles. Leading up to the publication of the DSM-5 there may have been greater discussion as to how addictive disorders are conceptualized and assessed.

The most common type of article published addressed addiction-related issues within non-clinical populations; fewer articles focused on topics specific to individuals receiving addictions counseling. Even fewer articles included research on outcomes of prevention and counseling interventions. The presence of only four articles in the sample (1.9%) that assessed the efficacy of prevention efforts is concerning given that prevention has been found to be a key facet of professional counselor identity (Mellin, Hunt, & Nichols, 2011) and is considered by CACREP (2016) as “foundational knowledge” (p. 8) for all counseling professionals. This discrepancy may suggest that despite being regarded as an important component of professional training and identity, little is actually done pertaining to prevention practice and research by professional counselors.

Although relatively few articles in the sample included addictions outcomes research, it is promising that CORE was established by the Association for Assessment and Research in Counseling  in 2010 as a venue for outcomes research and program evaluation findings (Hays, 2010). Since the inception of CORE, its publication of addiction research has resulted in it being one of the top five journals in our study publishing on addiction topics.

Among the assessment instruments in articles that focused on addictions-related measurement issues, the SASSI-3 (Miller & Lazowski, 1999) was the most commonly discussed. The amount of attention given to the use of the SASSI-3 appears to be warranted considering the popularity of this instrument among professional counselors and clinical mental health counselors in particular. In a national survey of counselor assessment practices by Peterson, Lomas, Neukrug, and Bonner (2014), the SASSI-3 was the highest ranked test of addictive behaviors among all professional counselors. Among clinical mental health counselors, it was the third highest ranked inventory overall, behind the Beck inventories for depression and anxiety. Further, Neukrug, Peterson, Bonner, and Lomas (2013) found that more than three-quarters of counselor educators who teach assessment use the SASSI-3 in their courses. Despite the widespread use of the SASSI-3, it does have its limitations; the SASSI-3 can be cost prohibitive for some clients and requires that those who use it receive specialized training. As a result, examining the psychometric properties of other instruments, specifically measures that are free or more cost effective and do not require specialized training to interpret, seems prudent.

The limited number of articles addressing specific types of addictive behaviors is problematic. Although common physiological and psychosocial processes exist across all addictive behaviors, there also are unique factors associated with the etiology, prevention and treatment of the various drug classifications and behavioral addictions (Brooks & McHenry, 2015). Indeed, prevention and intervention efficacy often correlate with information tailored to each need. In light of the current opioid and prescription drug epidemic—a 137% increase in drug overdose deaths and 200% increase in opioid deaths from 2000 to 2014 (Rudd, Aleshire, Zibbell, & Gladden, 2016)—examining the prevention and treatment of this specific classification of substances would be a prudent area of research.

Analysis of addictions-related research revealed that nearly two-thirds of all articles in the sample represented original empirical research. This is higher than what Ray et al. (2011) found in their content analysis of 15 counseling journals in print between 1998 and 2007; these authors found that approximately one in three articles published included original research. These findings suggest that despite addictions not being a topic commonly discussed across counseling journals, there may be greater attention to conducting research on addictive behaviors by counseling researchers. Or, this may reflect an overall trend among counseling journals to publish research since the final year (2007) of the content analysis conducted by Ray et al. (2011). The level of sophistication of data analysis in the articles in this sample is comparable to findings from past content analyses of long term publication trends in specific counseling journals; for instance, descriptive statistical techniques were among the most commonly used methods of analysis in JCD (Erford et al., 2011) and Journal of College Counseling (Byrd et al., 2012).

One of the most commonly used groups in addictions research was college students, which may indicate an over-reliance on the use of convenience sampling across institutions of higher education. A concerning trend observed in the data was that addictions professionals were utilized more as research participants than were clients in addictions treatment. Greater attention to understanding individuals who are enrolled in treatment can help researchers and professional counselors identify successful ways to tailor and personalize counseling interventions to fit the needs of specific client populations. In addition, although several articles used diverse populations, fewer studies examined addictions issues among discrete groups of men and women only. Moreover, twice as many articles were found that focused on men compared to women only. Additional research examining gender differences is necessary considering that men and women face unique issues related to the development and treatment of addictive behaviors (National Institute of Drug Abuse, 2015).

Limitations

The findings of this study should be viewed within the context of several limitations. An advantage of content analysis is that it can be used to help organize and summarize large quantities of information; however, by assigning each individual article to a category, it is possible that some distinctive characteristics of the articles in the sample may have been lost or trivialized (Riffe, Lacy, & Fico, 2014). In addition, the process of creating categories for the articles is researcher-driven and, even though efforts were made to develop the coding framework using the available literature, it is possible that different researchers would not have created the same levels of the study variables.

Other limitations relate to data collection and the coding process. Since the purpose of the present study was to analyze articles that focused on addictions, the sample was developed through a review of journal titles, abstracts and keywords only—an approach utilized in previous content analyses of specific topics within the counseling literature (Barrio Minton et al., 2014; Evans, 2013). In the unlikely event that an article focusing on addictions did not include one of the search terms in these three areas, it would not have been included in this study. Also, this study did not include articles in counseling journals that are affiliated with regional or statewide counseling organizations, such as The Journal of Counselor Preparation and Supervision, published by the North Atlantic Region Association for Counselor Education and Supervision, or the Virginia Counselors Journal, which is the journal of the Virginia Counseling Association. The authors chose to restrict their data collection to include only journals produced by NBCC, CSI, ACA and ACA member divisions because they believed that a content analysis of articles sampled from these national publications would provide a general overview of the addictions-related content discussed throughout the counseling literature.

Although inter-rater agreement among coders for most variables was satisfactory, reliability for coding the data analysis variable was lower than the minimal acceptable threshold suggested by Krippendorff (2013). Possible reasons for low concordance include the number of categories for this variable and the inconsistencies in how data analytic techniques were described within the various articles in the sample. Finally, as this study presented an overview of the types of addictions-related articles published in counseling journals, the quality of the publications was not evaluated during the coding process. This may be a possible next step for counseling researchers that could yield more rigor and, subsequently, evidence-based practices for addictions prevention and counseling.

Implications for Professional Counselors

According to the ACA Code of Ethics (2014), “Counselors have a responsibility to the public to engage in counseling practices that are based on rigorous research methodologies” (Section C, p. 8). When addressing issues related to addictive behaviors, professional counselors have a modest yet relatively diverse literature available to help guide their practice. Despite the fact that a large number of articles in the sample described approaches to addictions counseling, many of these papers were conceptual in nature and did not include original empirical research to assess counseling outcomes. To better assist professional counselors in using research-informed approaches, it is necessary for greater attention to be given by counselor educators and researchers to producing addictions-related intervention research and program evaluations.

The limited number of articles that evaluated treatment approaches also may represent a more endemic issue in counseling and counselor education. Many professional counselors report not feeling adequately prepared to operationalize and measure client outcomes, despite recognizing the need for these skills in their work (Peterson, Hall, & Buser, 2016). Although these skills have been identified as key research competencies in counselor education (Wester & Borders, 2014), it is unclear how these competencies are addressed in entry-level and doctoral research curricula. Researchers may wish to examine the ways in which professional counselors and counselor educators learn how to evaluate treatment outcomes. This may help inform the development of new pedagogical strategies that lead to an increased production of outcomes research on approaches to counseling and prevention in counseling journals.

In addition to a call for research on counseling outcomes, it also seems apparent that there is a need for more sophisticated research questions and hypotheses in research conducted on addictive behaviors. Addiction is a multifaceted phenomenon that involves the interplay of multiple biological, psychological and social determinants (American Society of Addiction Medicine, 2011); therefore, the use of descriptive statistics or univariate procedures may not capture the complexities of how addictive behaviors are initiated, maintained and extinguished. The use of more sophisticated data analytic techniques by researchers may help address this issue. Structural equation modeling can be utilized to simultaneously test the fit of an explanatory model of addictive behavior comprised of multiple independent and dependent variables. For example, Wahesh, Lewis, Wyrick, and Ackerman (2015) utilized structural equation modeling to evaluate the fit of a mediational model of collegiate drinking that included multiple determinants of alcohol use. Alternatively, qualitative methods can be used by researchers to provide an in-depth understanding of how various interpersonal, social and cultural variables shape individual behavior (Likis-Werle & Borders, 2017).

One way that counseling journals can increase the publication of articles that address specific issues related to addiction is by offering a special issue or section on these topics. Journal editors can develop a call for papers that focus on addictions-related issues salient to their publication’s readership. Depending on the particular journal’s audience, this can include examining prevention, a specific classification of addictive behaviors, or intervention outcomes, areas that were not well represented in the current sample of articles. For example, in 2011 CORE dedicated a special section (Volume 2, Issue 1) to substance abuse outcome research and measures. The use of special issues or sections across counseling journals can ensure that professional counselors have access to information that is germane to their work. JAOC may seem like a natural venue for topics related to addictions in counseling; however, that perception is problematic because JAOC is geared toward addictions and offender counselors, making it possible that the particular populations studied, findings and implications in articles published in this journal are not as relevant to professional counselors in other settings.

Although journal articles represent an important source of professional development, it is possible that professional counselors utilize other venues for continuing education. Future researchers can examine continuing education practices of counselors to determine the particular sources of education and whether or not the information provided through these venues is consistent with the typical scope of practice and professional identify of the counseling profession. Relatedly, it also seems necessary to determine where else counseling researchers and counselor educators publish their research on addictions counseling. While counselor educators in CACREP-accredited programs are expected to demonstrate scholarly activity in counseling (CACREP, 2016), it is possible that some addictions counselor educators publish in journals outside of counseling that specialize in addictions or have higher impact factors. Journal impact factors are a method of determining a journal’s significance in comparison to other journals in the field. Some counselor educators may seek to publish in journals with a more favorable impact factor for evaluation purposes related to faculty tenure and promotion (Fernando & Barrio Minton, 2011). Assessing author publication trends by reviewing the curriculum vitae of addictions counselor educators can help identify the journals in which they most frequently publish. Examining these trends can identify the types of addictions-related research and other scholarly work that are being produced by counselor educators and counseling researchers but are not appearing in counseling journals.

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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Edward Wahesh, NCC, is an Assistant Professor at Villanova University. S. Elizabeth Likis-Werle is an Assistant Professor at East Tennessee State University. Regina R. Moro, NCC, is an Assistant Professor at Boise State University. Correspondence can be addressed to Edward Wahesh, Villanova University, Education and Counseling (SAC 302), 800 E. Lancaster Avenue, Villanova, PA 19085, edward.wahesh@villanova.edu.