Volume 6 - Issue 2 - The Professional Counselor

Experiences of Male Counselor Educators: A Study of Relationship Boundaries

Jul 20, 2016 | Article, Volume 6 - Issue 2

Dee C. Ray, David D. Huffman, David D. Christian, Brittany J. Wilson

The vast majority of graduate students in the social sciences, especially in mental health fields, are females (Crothers et al., 2010; Healey & Hays, 2012). In a recent report on counseling programs, an average of 76% of students admitted and graduated yearly from entry-level counseling programs were women (Schweiger, Henderson, McCaskill, Clawson, & Collins, 2012). Although counseling is one field that attracts mostly female graduate level students, a historical review indicates that males made up approximately 80% of counselor education faculties in the 1980s (Anderson & Rawlins, 1985). In recent years, as the number of females who seek doctoral degrees in counseling has increased, so has the number of female counselor educators, correlating to fewer males entering the field of counselor education. Currently, the average number of males admitted and graduated yearly from doctoral-level counseling programs has been reported at a meager 25% (Schweiger et al., 2012). As counselor educators strive to build best practices for working with diverse populations, it seems relevant to explore the experiences of male counselor educators as well as suggest practices that improve conditions for male counselor education faculty.

In the preparation of counselors, counselor educators are encouraged to build relationships with students that lead to greater self-awareness, personal development and interpersonal learning, which inform their work as counselors. Literature cites the importance of the relationships between counseling faculty and students as “paramount” (Dollarhide & Granello, 2012, p. 290), suggesting that it “stands out above all other factors” (McAuliffe, 2011, p. 32) in the education of adults. It seems reasonable to assume that if counselor educators espouse the importance of the relationship between client and counselor, they extend this value to their students, building relationships that facilitate learning. Thus, a belief that the relationship between teacher and student leads to mutual support and growth comprises the hallmark of humanistic education (Dollarhide & Granello, 2012).

Although the American Counseling Association (ACA) Code of Ethics (2014) asserted that counselor educators are restricted from sexual or romantic relationships with students, universities and counselor education programs typically do not clearly articulate boundaries when approaching the multiple roles adopted by faculty members (Owen & Zwahr-Castro, 2007). In the absence of guidelines and open discussion regarding faculty–student relationships, legal concerns can permeate the university environment. Sexual harassment suits have increased, and many universities have responded by going beyond sexual harassment policies and adding additional policies that restrict sexual or romantic consensual relationships between faculty and students (Bartlett, 2002; Kiley, 2011). Male faculty members seem especially affected by the legal environment and Nicks (1996) reported males had significantly higher concerns than females regarding unjust accusations of harassing a student. In the current environment of legality and ambiguous ethical guidelines, Kress and Dixon (2007) cautioned that counselor educators might choose to distance themselves from students to avoid the appearance of impropriety or placing themselves in complex ethical situations. However, there is a dearth of literature regarding issues of relationship dynamics based on sexuality and gender in academia over the last 20 years.

Further complicating the issue of faculty–student relationships is that female professors and students are more likely to perceive complex relationship issues as unethical when compared to their male counterparts. In a comparison between female and male counselor educators and counselor education students, Bowman, Hatley, and Bowman (1995) found that females were significantly more likely to rate activities outside the traditional student–teacher relationship as unethical. This finding has been supported in multiple studies regarding undergraduate students (Ei & Bowen, 2002; Oldenburg, 2005; Owen & Zwahr-Castro, 2007). Female undergraduate students were more likely to rate a relationship scenario as unethical when the professor was identified as a male as compared to scenarios with female professors (Oldenburg, 2005) and more likely to be negative than males about questionable scenarios such as sexual relationships, doing favors for a professor, and doing things alone with an instructor (Ei & Bowen, 2002). Owen and Zwahr-Castro (2007) found that female undergraduate students judged approximately one-third of faculty–student interaction scenarios as significantly more inappropriate than male students, identifying nonacademic-related interaction that occurred off campus as most inappropriate. Although not specifically explored, the tendency of females to find behaviors unethical when compared to the perceptions of males has been attributed in the literature to sensitivity of women to power differentials and potential for exploitation based on cultural experience (Ei & Bowen, 2002; Owen & Zwahr-Castro, 2007). In the context of current ratios in counselor education of a majority number of female faculty to a minority number of male graduate students, it is difficult to ascertain the perception of power dynamics based on gender.

The changing context of counselor education may present unique challenges for male faculty to navigate with little guidance. A review of the literature highlights a complex environment where male counselor educators engage in faculty–student relationships within a context of power differences and potential legal complications. The current study was conceived in a doctoral level clinical course in which male and female doctoral students processed their teaching experiences with master’s students. During the discussion, male doctoral students serving as instructors shared experiences regarding relationships with their students that appeared uniquely different from experiences shared by female colleagues. Concerns emerged regarding practices of male counselor educators when entering a female-prevalent field as a person in a position of power. As a result, we proposed that the following factors might influence the interactions of male counselor educators on a daily basis in their roles with students: majority of female graduate students, decreasing number of male faculty, increases in legal action, ambiguity of ethical guidelines, possible attraction between professors and students, and a contextual field that values human relationships. The purpose of this study was to discover attitudes and practices of male counselor educators regarding faculty-student relationships. Our research questions included: (a) what are the practices and attitudes of male counselor educators related to relationships with students and colleagues? and (b) what specific practices do male counselor educators employ to maintain boundaries with students?

Methodology

Participants and Data Collection

Using Schweiger et al.’s (2012) compilation of counseling program information, a member of the research team identified names typically attributed to males among listed faculty names, resulting in the identification of 330 males within the United States. The research team then matched the names with e-mails on university Web sites. An initial recruitment e-mail was sent to the identified sample asking for participation. Following the initial recruitment e-mail, 41 of the identified original sample responded as ineligible (22 contact e-mails were immediately returned as unavailable; 6 identified as female; and 13 identified as no longer working as a counselor educator or having never worked as a counselor educator). This resulted in a potential sample of 289. Two more e-mails were sent as reminders regarding participation. The final sample consisted of 163 male counselor educators who completed the survey, resulting in a response rate of 56%.

A summary of demographic characteristics of the 163 male counselor educators who completed the survey is presented in Table 1. In this sample, male counselor educators were mostly White, non-Hispanic (n=125). African American (n=14) and Hispanic (n=11) males also were represented, but only in small numbers, and Asian males (n=4) were few. Most of the sample identified as married/partnered (87%) and heterosexual (89%), with gay or bisexual males represented by approximately 10% of participants. The sample was more diverse in areas of age, rank, child status, and years as counselor educators.

Survey Development

We developed our survey in two phases. The research team brainstormed issues that emerged during discussion, such as the possible attitudes of male counselor educators, including feeling isolated or unsupported due to fewer numbers of male colleagues, or practices that might emerge in working with students of the opposite gender with the intent of ensuring a sense of safety. Based on discussion and an extensive literature review, the research team created a list of quantitative items surveying demographics, attitudes and practices of male counselor educators. We distributed the survey to a pilot group of six male counselor educators who represented diversity in age, experience, ethnicity and sexual orientation. The pilot participants reviewed each question and commented on its usefulness, acceptability and clarity. Based on pilot feedback, the research team modified the survey to include 22 demographic questions, 32 attitude and practice questions, and four open-ended questions. The survey was formatted for the Survey Research Suite (Qualtrics) and final quantitative data was transferred into SPSS for analysis.

Demographic questions included items regarding personal, family and program characteristics of the faculty members, and questions regarding the faculty members’ professional designations and teaching assignments. Attitude items (Cronbach’s α = .66) consisted of questions related to the impact of being male on both collegial and student relationships. Practice items (Cronbach’s α = .64) consisted of questions related to the participant’s actual practices in relating to students (e.g., private meetings, lunch/dinner, after class). For the full scale, Cronbach’s α was calculated at .70. Four open-ended questions addressed ethical challenges, thoughts related to being male, ways the counselor educator might act differently, and strategies used to avoid complications with students.

Table 1

Demographic Characteristics of Male Counselor Educator Participants

Variable	N	%	M	SD	Mdn	Range
Age	155		51.61	11.08	53	27–76
Ethnicity
African American	14	8.6
Asian	4	2.5
White, Non-Hispanic	125	76.7
White, Hispanic	11	6.7
Self-Identified as Other	8	4.9
Relationship Status
Single	14	8.6
Married/Partnered	142	87.1
Divorced/Separated	5	3.1
Widowed	1	.6
Sexual Identity
Gay	13	8.0
Heterosexual	145	89.0
Bisexual	3	1.8
Status Regarding Children
No Children	30	18.4
Adult Children	74	45.4
Minor Children in Home	55	33.7
Minor Children Part Home	1	.6
Minor Children Not in Home	2	1.2
Years As Counselor Educator	161		15.07	10.85	12	1–45
Faculty Rank
Assistant	38	23.3
Associate	50	30.7
Full	58	35.6
Lecturer/Interim	4	2.5
Other	13	8.0
Total Number of Male Faculty	156		4.04	1.81	4	1–10
Total Number of Female Faculty	155		4.27	2.27	4	0–13
Estimated % of Male Students	163		18.21	11.24	16	0–78
Estimated % of Female Students	162		77.66	18.55	80	0–99

The first three open-ended questions were used for qualitative analysis and the final question was used to create a list of strategies employed by male counselor educators to aid in their student relationships.

Analysis and Results

The research team used a parallel mixed-methods design (Teddlie & Tashakkori, 2009) to explore the experiences of male counselor educators. We utilized qualitative thematic analysis for data generated from three open-ended questions and optional comments following each quantitative survey question and quantitative statistical analysis for multiple-choice survey questions. By conducting independent quantitative and qualitative analyses in a parallel simultaneous nature, we allowed the separate analyses to inform one another and provide a more integrated understanding of the data (Teddlie & Tashakkori, 2009). Due to overlap in analysis and results consequential from a mixed-methods approach, we chose to present analyses and results categorized by method (qualitative and quantitative) in the following section.

Qualitative Analyses

Responses to the three open-ended questions and optional comments were analyzed from a perspective of transcendental phenomenology to explore the lived experiences of participants (Creswell, 2007; Moustakas, 1994). Within this qualitative tradition, we worked to bracket or set aside our own preconceptions about the phenomenon as much as possible to remain focused on the views of participants (Moerer-Urdahl & Creswell, 2004; Moustakas, 1994). The research team, consisting of two male doctoral students and one female tenured faculty member, discussed our student–teacher relationship experiences regarding gender and power differences. Through reflection and discussion, we developed greater awareness of how our experiences have influenced our views of being and working with male counselor educators. Team discussion allowed us to understand and bracket our positions in the development of data collection and analysis methods.

Because the experiences of male counselor educators have received little attention in literature and research, a phenomenological approach allowed for understanding to emerge from participants’ written reports as data was broken down into smaller units of meaning and reconstructed into broader themes that were clearly defined (Creswell, 2007; Giorgi, 1985). Following data collection, we independently coded responses to three open-ended questions, a smaller portion of the data, to identify initial concepts. Next, we met to review and compare our concepts. Silverman and Marvasti (2008) identified the appropriate use of smaller portions of data to establish preliminary categories. We discussed each unit of meaning in the text that was relevant to the focus of study (Giorgi, 1985), compared each concept to previous statements and discovered an initial list of broader themes suggesting common experiences among participants (Creswell, 2007). The research team clarified category definitions by comparing data units within each category for similarities and differences. Responses to optional comments sections in the survey were reviewed for inclusion in the text. Comments that offered information beyond the scope of the survey question referenced were included in the text for qualitative analysis. Then individual team members independently examined the entire text and coded each unit of meaning under the appropriately perceived category. Finally, we met as a group to develop consensus on final categories and to assign textural excerpts to appropriate themes. As suggested by Potrata (2010), research team members focused on exploring potential differences in coding rather than focusing on consistency when coming to consensus in order to illuminate complexities of the male counselor educator experience. Frequencies were tabulated to represent the magnitude of each category within the sample, and verbatim illustrative quotes were selected to clarify the meaning of each category. Saldaña (2013) suggested that magnitude coding adds supplemental texture to provide richer results in qualitative analysis.

Qualitative Results

In order to address our first research question regarding practices and attitudes of male counselor educators, participants were asked to respond to three open-ended questions to address their experiences and practices as male counselor educators. Seventy-one responses were recorded for the first question, “What ethical challenges, if any, are related to being male in counselor education?” One hundred responses were recorded for the second question, “What are your thoughts related to being male in counselor education?” Ninety-six responses were recorded for the third question, “What are the ways you act differently in student relationships because you are male?” We also coded additional comments of significance that followed each survey item. In all, qualitative analysis included the coding of 359 answers of varying lengths. During qualitative analysis, the research team discovered that participants’ answers appeared to be addressing similar themes across all questions. Hence, all answers were collapsed into one analysis.

The research team identified 10 distinct themes expressed by participants regarding the experiences of being a male counselor educator. We identified “modify behavior” as the most predominant theme, magnified by frequency (32%). This theme included intentional changes in action or interpersonal expression related to being male in professional relationships. Another major theme, “no difference” (frequency 23%) included beliefs and experiences that no unique relationship challenges exist in counselor education related to being male. Expressions of feeling “isolated or lonely” (frequency 11%) described participant experiences of feeling a lack of support as well as awareness of being a minority in the profession. Responses regarding “sexual attraction” (frequency 11%) involved experiences of sexual attraction in professional relationships. A theme of “perception of impropriety” (frequency 10%) included attention to the perception of others regarding appropriate behavior. Expressions of “prejudice or discrimination” (frequency 9.5%) involved experiences of negative beliefs or actions of others related to one’s gender. Additionally, qualitative data revealed themes related to participants’ “awareness” of professional relationships, “awareness of power difference” in relationships, the importance of a “caring or safe environment,” and “ethnicity or orientation” as part of one’s identity as a male counselor educator. A comprehensive presentation of all themes is included in Table 2.

Our second research question regarding specific practices of male counselor educators was addressed through our fourth open-ended survey question, which indicated participants cited over 40 different strategies they used to structure their relationships with students. In general faculty–student interactions, respondents indicated that they did not meet alone with students; only met with students on campus; interacted in groups when others were present; avoided jokes, conversations or language that could be perceived as too friendly; referred to family/significant others in class and conversation; avoided sharing too much personal information; made no physical contact; and avoided being overtly interested in students’ relationship issues. When meeting with students, respondents reported that they kept their doors open, structured meetings with an agenda, met in classrooms, ensured others were around, and avoided engaging in counseling with students. Participants also indicated that they consulted with colleagues regarding student relationships, had colleagues present for potentially problematic student interactions, addressed student relationship issues as soon as they arose, notified department chairs of any concerns and documented interactions. On a personal level, participants reported that they focused on having a balanced personal life, increased self-awareness of interactions, reminded self of boundaries, and engaged in honest and transparent interactions.

Quantitative Analyses

We used results from qualitative analysis to inform decision making regarding variables of interest for quantitative analysis. Due to the extensive data resultant from the 32-question survey of practices and attitudes and need for manuscript brevity, we narrowed survey data results to the survey items that matched qualitative theme results. We chose to explore one survey item per qualitative theme that appeared to closely match the qualitative analysis. Following final coding discussion, the research team identified five attitude and practice questions from the survey that appeared to be related to content evolving from the qualitative analysis. The qualitative theme of modifying behavior appeared most closely linked to the survey item, “I interact differently with female students than male students.” The theme represented by some respondents, that there were no differences related to being male, most closely aligned with the item, “I have unique ethical challenges related to being male in counselor education.” The item linked to the qualitative theme of avoiding the appearance of impropriety, “I structure my individual interaction with students to avoid the appearance of impropriety,” was further explored. The qualitative themes of isolation and discrimination were matched to two items: “I feel isolated in my faculty because I am male,” and “I feel discriminated against by faculty members because I am male.” Although most respondents did not agree with these final two statements, we chose to explore them further due to the distinct voices of some respondents related to ethnicity and sexual orientation within the data.

Table 2

Themes Related to Male Counselor Educators’ Experiences

Theme	Definition	Freq.	Responses	Sample Statements
Modify Behavior	Intentional changes in action or interpersonal expression related to being male	32%	115	“. . . crucial to make sure distinct boundaries are established”“. . . have to focus on being appropriately relational”“must balance being supportive with providing clear boundaries”
NoDifference	No unique challenges in counselor education related to being male	23%	82	“No specific challenges related to my gender”“Ethics are ethics, male or female”“How I act has little to do with being male”
Awareness	Indicating awareness or self-awareness regarding professional relationships	13%	47	“. . . we need to be very aware of situations and interactions with female students”“Know one’s self”“I am now more aware of how I interact”
IsolatedorLonely	Experiencing lack of support and awareness of being a minority in profession	11%	39	“I feel a bit like an endangered species”“There are simply some things I can only talk with other men about”“I recognize males are a minority in the field”
Sexual Attraction	Experiences of sexual attraction in professional relationships	11%	38	“Dealing with feelings of attraction with students and colleagues”“I am attracted to female students but do not act on it”“I have to refocus my thoughts if I feel an attraction to a student or colleague”
Perception of Impropriety	Attention to the perception of others regarding appropriate behavior	10%	37	“. . . don’t want to give the impression of being unethical”“Avoiding any appearance of misconduct”“. . . vigilant in protecting myself from false accusations”
Awareness of Power Difference	Awareness of the impact of privilege and power in relationships	10%	35	“Being aware of my male privilege and not abusing it”“I can be male without being dominating”“I do see the same gender politics and gender roles in my profession as I see in society…”
PrejudiceorDiscrimination	Experiences of negative or devaluing beliefs or actions of others related to being male	9.5%	34	“tendency to view males as the victimizer”“. . . uniquely male issues that could arise in counseling situations are downplayed”“I sometimes experience sexism against men in the comments of my female colleagues”
Caringor Safe Environment	Intention to provide support and safety to students	6%	21	“We want to provide a caring environment”“I want students to feel comfortable around me.”“. . . do not want any female to feel anxious”
Ethnicityor Orientation as Part of Identity	Influences of ethnicity and sexual identity upon male professional experiences	4%	15	“Being a male and an ethnic minority is challenging and often lonely”“. . . being Black and male is more of a challenge than being male alone”“I feel isolated not because I am male but because I am a gay male”

Note: Frequency = Number of participants who shared theme-related statements

Quantitative Results

Descriptive results for the five survey items are presented in Table 3. In order to explore relationships between survey items of interest, we employed Pearson product-moment correlation coefficient analyses on the five variables. There were statistically significant positive correlations between perception of unique ethical challenges and the four other variables: feeling isolated
(r = .290, n = 149, p < .001); interacting differently with female students (r = .317, n = 147, p < .001); structuring interactions to avoid appearance of impropriety (r = .190, n = 148, p = .021); and feeling discriminated against (r = .217, n = 150, p = .008). The more a male counselor educator felt there were unique ethical challenges related to being male, the more likely he was to feel isolated and discriminated against, structure interactions with students to avoid the appearance of impropriety, and interact differently with females than males. Additionally, there was a statistically significant positive correlation between feeling isolated and feeling discriminated against (r = .371, n = 149, p < .001). The more isolated a male counselor educator felt, the more likely he was to feel discriminated.

Table 3

Survey Items Related to Relationships for Male Counselor Educators

				Percent of Responses
Survey Item	N		Σ	SD 1	D 2	N 3	A 4	SA 5
I feel isolated in my faculty because I am male.	149	1.89	.94	36.8	36.8	11.7	5.5	1.2
I interact differently with female students than male students.	147	2.90	1.02	6.7	29.4	21.5	30.7	1.8
I structure my individual interactions with students to avoid the appearance of impropriety.	148	3.76	.92	1.8	9.2	13.5	50.9	15.3
I have unique ethical challenges related to being male in counselor education.	150	2.79	1.03	9.2	30.7	23.9	26.4	1.8
I feel discriminated against by faculty members because I am male.	150	2.05	1.06	31.9	39.9	6.1	12.3	1.8

Note: SD=Strongly Disagree, D=Disagree, N=Neutral, A=Agree, SA=Strongly Agree

We further explored ethnicity and sexual orientation in relationship to the dependent variables of isolation and discrimination based on qualitative findings that indicated these characteristics impact the views of male counselor educators. We conducted four separate one-way between-groups analyses of variance to explore the impact of ethnicity and gender on isolation and discrimination. There was a statistically significant difference in ethnicity for isolation, F(4, 144) = 5.78, p < .001, η²= .14. Means for ethnicity included Asian x̅ = 2.0; African American x̅ = 1.71; White/Non-Hispanic x̅ = 1.84; White/Hispanic x̅ = 1.64; Self-Identified as Other x̅ = 3.43. There was a statistically significant difference in ethnicity for discrimination, F(4, 144) = 5.25, p = .001, η²= .13. Means for ethnicity included Asian x̅ = 2.0; African American x̅ = 2.23; White/Non-Hispanic x̅ = 1.94; White/Hispanic x̅ = 1.91; Self-Identified as Other x̅ = 3.71. There was a statistically significant difference in sexual orientation for isolation, F(2, 145) = 3.81, p = .024, η²= .05. Means for sexual orientation included Gay x̅ = 2.58; Heterosexual x̅ = 1.83; Bisexual x̅ = 1.67. There was no statistically significant difference in sexual orientation for discrimination, F(2, 145) = .70, p = .50, η²= .01.

Discussion

The sample in this study reasonably represents the current population of male counselor educators in CACREP-accredited programs. Although the sample reported equivalent numbers between male and female faculty, they also reported a disproportionate number of female students (78%) to male students (18%), as indicated in previous literature (Schweiger et al., 2012). The sizeable response rate to this survey, as well as its representativeness, lends credibility to findings.

Themes and Characteristics Related to Being a Male in Counselor Education

Qualitative analyses indicated that participants expressed diversity of attitudes and practices regarding the impact of being male upon professional relationships. The most predominant theme, “modify behavior,” indicated that being male influenced choices made by male counselor educators in their interactions with students. Conversely, the second dominant theme, “no difference,” indicated that some counselor educators do not feel that there is any difference in interactions with students or colleagues related to being male. A lack of consensus existed among male counselor educators regarding the influence of being male upon their professional relationships.

When male counselor educators acknowledged there were differences related to being a male in the field, qualitative analysis revealed additional themes related to isolation, discrimination, fear of appearing inappropriate, interacting differently with females than males and need for awareness. We wanted to explore characteristics related to these feelings, which prompted the correlational analyses.

Quantitative and qualitative analyses indicated that the appearance of impropriety was of considerable concern for male counselor educators. A majority of participants agreed or strongly agreed that they structured their interactions to avoid appearance of impropriety. Results revealed a statistically significant positive relationship between expressing a perception of unique ethical challenges for males and structuring interactions to avoid appearance of impropriety. Participants who perceived unique challenges as males also tended to take steps to avoid appearing inappropriate in their professional relationships. This finding supports qualitative themes of male counselor educators’ concerns regarding the appearance of impropriety and fear of the cultural myth of the lecherous professor (Bellas & Gossett, 2001).

Sexual attraction emerged as a relevant issue through qualitative analyses. A vast majority of respondents reported that they had experienced being attracted to a student, with frequency of feelings ranging from rare to a regular occurrence. Also, a majority of the sample reported experiencing a student being attracted to them. These results suggest that sexual attraction was experienced as a common phenomenon in male teacher–student relationships. However, participants often described their feelings of attraction as natural reactions that posed no threat if not acted upon.

When addressing the influence of student gender upon their behavior with students, male counselor educators reported diverse perspectives. Participants were asked if they interacted differently with female students than male students. Responses were about evenly distributed from “disagree” to “agree.” The variance in responses may reflect the larger disagreement among participants regarding the influence of gender upon professional relationships. The qualitative themes of “modify behavior” and “no difference” may provide context for understanding diverse results regarding this question. Correlational analysis revealed that the more a participant perceived unique challenges as a male counselor educator, the more he reported interacting differently with female students compared to male students.

Some participants also reported experiencing isolation related to being a male counselor educator. Qualitative data revealed unique experiences of isolation related to ethnicity and sexual orientation. Although there were a small number of participants who identified as gay, bisexual, African American, Latino, Asian, or other ethnicity, we chose to conduct quantitative analysis to further explore their voices, which were clearly articulated as unique in qualitative analyses. Further quantitative analysis indicated that participants who self-identified as “other” for ethnicity were more likely to feel isolated in comparison with other ethnicities. Likewise, gay male counselor educators also were more likely to feel isolated in the profession. However, gay males did not report higher levels of feeling discriminated against as compared to heterosexual males. Previous research indicates gay males may experience isolation related to not being out to co-workers, often motivated by fear of discrimination (Wright, Colgan, Creegany, & McKearney, 2006). Another possible interpretation could be that gay male counselor educators feel isolated due to interacting with fewer colleagues who are similar to them, but who they experience as accepting or non-discriminatory.

Linked to isolation, we also asked male counselor educators if they had faculty colleagues with whom they could discuss challenges. This point seemed especially salient due to qualitative results indicating male counselor educators rely on consultation as one intervention for dealing with student relationship issues. A majority of respondents agreed or strongly agreed to having a colleague on their faculty with whom they could discuss male-related issues. Qualitative and quantitative analyses identified ethnicity as an important contributor to the experiences of male counselor educators. Qualitative data included a small but consistent voice of African American male counselor educators who expressed increased isolation due to a combination of ethnicity and gender. Quantitative analysis also indicated that participants who identified as African American reported more frequent experiences of discrimination in their professional environment. These findings coincide with research indicating that African American males experience prejudice and discrimination in higher education due to stereotype images of African American males as underachieving, disengaged and threatening (Harper, 2009). Brooks and Steen (2010) discussed concerns related to the lack of African American male counselor educators and the obstacles they face in the academic setting. Participants who self-identified as “other” on ethnicity also showed increased experiences of discrimination as well as isolation. Correlational analysis confirmed the co-occurrence of these two themes, revealing a positive relationship between feeling isolated and feeling discriminated against. Asian males were more likely to feel isolated and structure their interactions to avoid appearances of impropriety, which reflects previous accounts of Asian professors in the literature (Culotta, 1993) in which they experienced isolation from their colleagues and increased student mentoring demands because of their minority status.

In returning to the issue of concern related to practices of male counselor educators in building humanistic and growth-inspiring relationships with students, the results of the current study provide some insight. Many male counselor educators appear to be aware and concerned that being male may influence how they are perceived by students and how they approach their relationships with students. However, results indicate that participants sought methods and strategies that allowed them to pursue relationships while also being sensitive to students’ perceptions of safety. Figure 1 provides specific strategies highlighted by participants that allow male counselor educators to engage in student–teacher relationships that recognize the power differential between student and teacher, inherent challenges with sexual attraction, and yet still allow the student and teacher to benefit from an accepting, inspiring relationship that mirrors the therapeutic relationship.

Limitations

The survey method used for this study was selected for exploratory purposes and did not involve the use of a rigorous assessment designed to interpret results through reliability and validity procedures; hence, results must be interpreted with caution. Additionally, the survey sample may not represent the views of the entire population of male counselor educators.

Figure 1.

Strategies Used by Male Counselor Educators to Build Student Relationships.

Note: General Interactions = strategies used in everyday interactions; Student Meetings = strategies used when having to meet with students individually; Interventions = strategies used when complications arise.

Due to the extensiveness of collected data, we were unable to report all findings related to the uniqueness of the sample. Respondents reported rich qualitative narratives and variations in their attitudes and practices. The variations are not fully represented in this report. The use of a one-time open-ended questionnaire precluded use of qualitative interviews that would reveal further depth of themes. Additionally, minority groups, such as specific ethnicities and those who identified as gay and bisexual, appeared to have a distinct voice in this survey. However, due to low representation, data analysis was limited in representing their experiences. We attempted to rectify this limitation by voicing those narratives in the qualitative analysis.

Implications

The purpose of this research was to reveal attitudes and practices of male counselor educators, allowing the reader an understanding of how the experience of being male influences the daily choices of male counselor educators. Implications of this research study include better understanding of the experiences of counselor educators that lead to enhanced job satisfaction for males, best practices to improve faculty–student relationships and possible areas for further investigation. Additionally, in Figure 1, we provide a list of behaviors used by male counselor educators to ensure appropriate student–teacher boundaries. This list offers male counselor educators possible strategies to address perceptions of impropriety or misconduct.

If male counselor educators experience greater job satisfaction, then more males may choose the counseling field, as they observe possible role models with whom they identify. Substantial variables identified by this study that might influence job satisfaction are feelings of isolation, discrimination, fear of appearing inappropriate and hypervigilance to behavioral interactions with students. Qualitative data revealed a desire by male counselor educators to offer a safe, caring environment, qualified by some respondents as an authentic relationship. Findings indicate that if male counselor educators feel limited by personal loneliness or concern for appearances, this will most likely interfere with their student and faculty relationships. Consultation with and support of colleagues appeared to be a process regularly utilized by many of the male counselor educators in this study. Counselor education departments would benefit from engaging in practices that promote collegiality and support among faculty members as well as formalizing mentoring processes.

Male counselor educators revealed that they take measures to modify their behaviors with students, especially female students. Our results indicate that fear of impropriety, awareness of cultural power differentials, desire to create safe relationships with students and realistic awareness of potential sexual attraction prompt male counselor educators to engage in behaviors that will provide safety for students and for themselves. These strategies reveal concrete behavioral actions taken to ensure the maintenance of boundaries with students. Kolbert, Morgan, and Brendel (2002) concluded that faculty must consider student perceptions of a relationship as the primary criterion in making decisions regarding their interactions with students. This conclusion requires considerable awareness from male counselor educators related to how they present themselves and how students perceive them. One common strategy used by male counselor educators and commonly supported in the literature (Ei & Bowen, 2002) is engaging in group activities, as opposed to one-on-one activities, in order to establish authentic relationships in a safe environment.

The most cited strategy among this sample was not being alone or out of sight from others when engaging in personal interactions with students. In a field where confidentiality is the base of intervention, this particular strategy seems incongruous, especially for professionals who value relationship in teacher–student interactions. Additionally, students may question a faculty member’s authenticity if intimacy is avoided in the relationship. However, contextual, legal and cultural considerations appear to encourage these types of restraints. Counselor education departments may benefit from discussion of these issues of behavior, relationship, philosophy and safety in an open forum among faculty and with students.

The relational experiences of male counselor educators have gone virtually unexamined in literature and research, leaving many opportunities for further inquiry. Some participants indicated that ethnicity influenced their experiences and relationships, yet sample size prevented meaningful exploration. Further research may investigate the unique experiences of African American, Latino and Asian male counselor educators. Likewise, sexual orientation emerged as a major influence for some participants. An exploration of experiences of gay male counselor educators is needed to enhance understanding of their relational experiences and the influence of gender.

Participants expressed concerns about perceptions of impropriety with students, feelings of isolation within the profession, and experiences of prejudice and discrimination in their work environments. These elements require further exploration to better understand the nature of these experiences and investigate causal factors to heighten sensitivity and identify appropriate measures for creating a safe environment for faculty and students. Participants also indicated that they alter behavior in student relationships to avoid the appearance of impropriety and maintain professional boundaries. Further research could explore the implications of those decisions for the quality of relationships with students. A study of student perspectives would greatly enhance understanding of these relational dynamics. Additionally, a study of ways in which female counselor educators approach their relationships with students, in regard to feeling restricted or limited in intimacy, is warranted.

This study provides an enhanced understanding of male counselor educators’ perceptions and experiences of their relationships with students and colleagues. Male counselor educators shared a unique voice of experience. Further research may expand understanding of male counselor educator experiences, provide insights to improve the quality of faculty–student relationships and assist in developing male role models for the future of our profession.

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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Dee C. Ray, NCC, is a Professor at the University of North Texas. David D. Huffman is an Adjunct Professor at the University of North Texas. David. D. Christian is an Assistant Professor at the University of Arkansas. Brittany J. Wilson, NCC, is Assistant Director, Child and Family Resource Clinic, University of North Texas. Correspondence can be addressed to Dee C. Ray, University of North Texas, 1155 Union Circle, Box 310829, Denton, TX 76203, dee.ray@unt.edu.

Assessing the Accuracy of the Substance Abuse Subtle Screening Inventory-3 Using DSM-5 Criteria

Jul 20, 2016 | Article, Volume 6 - Issue 2

John M. Laux, Robin M. DuFresne, Allison K. Arnekrans, Sylvia Lindinger-Sternart, Christopher P. Roseman, Amy Wertenberger, Stephanie Calmes, Darren W. Love, Andrew M. Burck, Jim Schultz

The Substance Abuse Subtle Screening Inventory-3 (SASSI-3; Miller & Lazowski, 1999) is a substance use screen that uses logically derived, or obvious questions, as well as subtle, or empirically derived questions. The SASSI-3 can be completed, scored and interpreted in 15 minutes. Side one consists of 67 true–false items selected for their ability to statistically differentiate between a criterion group of persons with substance dependence and a control group of non-substance dependent persons. The 67 empirically derived items are used in an effort to defeat dissimulation and are similar in nature and purpose to items found on the MacAndrew Alcoholism Scale-Revised (MAC-R; MacAndrew, 1965). As such, these empirically derived items are useful with individuals who are either intentionally or unintentionally denying a substance use disorder (Laux, Piazza, Salyers, & Roseman, 2012). These comprise the Symptoms scale (SYM), which assesses the symptoms and consequences of drug and alcohol use; the Obvious Attributes scale (OAT), a measure of the obvious symptoms of substance dependence; the Subtle Attributes scale (SAT), an indirect measure of substance use that employs items with non-substance-related content; the Defensiveness scale (DEF), which measures denial or minimization; the Supplemental Addiction Measure scale (SAM), which discriminates general defensiveness from defensiveness related to substance use; the Family Versus Control Subjects scale (FAM), which identifies those who are likely to focus on the thoughts and feelings of others to their own neglect; the Correctional scale (COR), used to detect response patterns similar to those produced by persons with a history of criminal behaviors; and the Random Answering Pattern scale (RAP), designed to identify haphazard answering. Side one also includes questions about respondents’ marital status, employment status, education, ethnicity and income.

Side Two consists of 12 items specific to alcohol use and 14 items regarding use of other substances. Response options to these 26 items are never, once or twice, several times, and repeatedly. These 26 items comprise the Face Valid Alcohol (FVA) and Face Valid Other Drugs (FVOD) scales and are similar to items found on the Michigan Alcoholism Screening Test (MAST; Selzer, 1971) and the CAGE (Ewing, 1984). The SASSI-3 is interpreted using nine decision rules. The first five decision rules are based solely on the unique contributions of individual scales. The remaining four decision rules involve a combination of two or more scales. A decision rule is coded “yes” if the associated SASSI-3 scale or scales’ raw score is equal to or greater than the decision rule’s cut score. Otherwise, the decision rule is coded as “no.” The respondent is determined to have a “high probability of having a substance dependence disorder” if any of the decision rules are met (Miller & Lazowski, 1999, p. 10).

Not only does the SASSI-3 do a better job of identifying alcohol use disorders than the MAST, CAGE and MAC-R (Laux, Perera-Diltz, Smirnoff, & Salyers, 2005; Laux, Salyers, & Kotova, 2005), it provides the added benefit of screening for drug use other than alcohol. The most recent inquiry into substance use screens indicated that the SASSI-3 is the substance use screen most frequently used by Master Addictions Counselors certified by the National Board for Certified Counselors (Juhnke, Vacc, Curtis, Coll, & Paredes, 2003).

The SASSI-3 Manual (Miller & Lazowski, 1999) reported a sensitivity (true positive) rate of 94.6% and specificity (true negative) rate of 93.2%. Subsequent field research produced results consistent with the psychometric claims made in the SASSI-3 Manual (Burck, Laux, Harper, & Ritchie, 2010; Burck, Laux, Ritchie, & Baker, 2008; Calmes et al., 2013; Hill, Stone, & Laux, 2013; Laux, Perera-Diltz, Smirnoff, & Salyers, 2005; Laux, Salyers, & Bandfield, 2007; Laux, Salyers, & Kotova, 2005; Wright, Piazza, & Laux, 2008). Further, Laux et al. (2012) demonstrated that the SASSI-3’s empirical items and associated decision rules increased the instrument’s screening accuracy. In addition, persons’ willingness and ability to self-report having a substance use disorder as described in the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR; American Psychiatric Association [APA], 2000) did not negatively affect the instrument’s sensitivity. Laux et al. (2012) found that the SASSI-3 produced high sensitivity rates across varying levels of motivation to change among persons who lost parental rights due to substance use.

APA published the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) in 2013. This most current version of the DSM brought forward major and important changes to the way the substance use disorder (SUD) chapter is conceptualized (Dailey, Gill, Karl, & Barrio Minton, 2014). Notably, the former dichotomous substance abuse and substance dependence categories have been removed and replaced with a continuum under the heading of “Substance Use Disorders” (APA, 2013, p. 483). The criterion formerly associated with the substance abuse and substance dependence disorders have been merged onto one continuum, to which craving has been added. Clients are determined to have a mild SUD if two or three criteria are met, a moderate SUD when four to five symptoms are met, and a severe SUD when six or more symptoms are endorsed.

Because previous versions of the DSM criteria were frequently used as the gold standard against which SUD screens were compared (Ashman, Schwartz, Cantor, Hibbard, & Gordon, 2004; Lazowski, Miller, Boye, & Miller, 1998), it is of interest to investigate the degree to which the SASSI-3 accurately predicts the new DSM-5 substance use diagnostic criteria. Our literature review produced two examples of empirical comparison between the SASSI-3, or its predecessors, and DSM criteria. The first (Lazowski et al., 1998) reported on the standardization efforts that produced the instrument’s third version. This research team used the data from persons whose case files had a DSM-III-R (APA, 1987) or a DSM-IV (APA, 1994) substance use diagnosis and an administration of the SASSI-3. How the participants were diagnosed was not specified. The results of this investigation found that the SASSI-3’s overall accuracy rating was 97%, the sensitivity rating was 97% and the specificity rating was 95%. A second study (Ashman et al., 2004) sought to determine the SASSI-3’s ability to screen for substance abuse among persons with traumatic brain injury. Ashman et al. (2004) used the Structured Clinical Interview for DSM-IV (First, Spitzer, Gibbon, & Williams, 1996) as the criterion variable against which the SASSI’s results were compared. These authors concluded that while the SASSI’s overall decision and FVA scale yielded “modest accuracy, sensitivity, and specificity rates” (p. 198), the FVOD scale had high sensitivity (95%) but only moderate accuracy (83%) and specificity (82%) among persons with traumatic brain injury.

The purpose of this study was to extend this line of research and examine the SASSI-3’s ability to accurately assess the presence of an SUD using DSM-5 criteria. Specifically, the authors calculated kappa statistics to estimate the degree of agreement between the SASSI-3’s overall decision rules, its individual decision rules and counselors’ DSM-5 SUD diagnoses. This analysis is important because these decision rules directly affect the SASSI-3’s final SUD classification (i.e., high probability of substance dependence disorder/low probability). Further, we examined the SASSI-3’s specificity and sensitivity using receiver operating characteristics (ROC) curves. We hypothesized that we would find good agreement between the overall SASSI-3 score and the DSM-5 SUD diagnosis. We further expected to find good agreement between the SASSI-3 face valid scales and the DSM-5 SUD diagnosis. We expected to find a moderate to low agreement between the SASSI-3 subtle scales and the DSM-5 SUD diagnosis. Additionally, we hypothesized that the ROC analysis would provide optimal cut-off scores for each of the SASSI-3 subscales that would improve those scales’ sensitivity and specificity. Study participants were selected from an inpatient SUD treatment center, an urban university, and a community mental health center that provides court-ordered outpatient treatment for clients with substance use issues. These populations were selected in order to match the populations on which the SASSI-3 was standardized (Miller & Lazowski, 1999).

Method

Participants

This study included participants (N = 241) recruited between October 2013 and May 2014. There were 114 females (47.3%) and 127 males (52.7%). The participants’ average age was 33.63 (SD = 6.83, range = 19–47). One hundred thirty-one (54.4%) were European American, 52 (21.6%) were African American, 7 (2.9%) were Hispanic, 12 (5.0%) were biracial, and 4 (1.7%) were Asian American. Thirty-five (14.5%) provided no ethnic background information. The average number of years of education completed was 12.48 (SD = 1.79, range = 7–18). Thirty-two (13.3%) were married, 156 (64.7%) were never married, 27 (11.2%) were divorced, 16 (6.6%) were separated, 4 (1.7%) were widowed, and 6 (2.5%) did not indicate a marital status. Thirty-three (13.7%) participants listed their employment as full-time, 22 (9.1%) as part-time, 91 (37.8%) as not employed, 65 (27.0%) as student, 9 (3.7%) as home maker, 13 (5.4%) were disabled, 2 (.8%) listed retired, and 6 (2.5%) listed no employment status. The sample features fewer employed, and more unemployed and student participants than the SASSI-3 normative sample (Miller & Lazowski, 1999).

Participants were recruited from three sites in Ohio. A total of 117 (48.5% of the total sample) participants were recruited from an adults-only comprehensive community mental health substance abuse treatment center. Another 61 subjects (25.3% of the total) were recruited from a private, non-profit organization specializing in court-ordered outpatient mental health treatment. Finally, 63 students (26.1% of the sample) enrolled at a large, public, urban university in Ohio were recruited to provide a sample of individuals who were less likely to be substance users. A one-way ANOVA [F(2, 233) = 24.28, p = .000, η²= .172] showed that the college students’ mean age (M = 23.86, SD = 9.04) was significantly lower than the inpatient substance abuse clients’ (M = 35.80, SD = 11.36) and the outpatient clients’ (M = 32.80, SD = 10.88).

Procedure and Materials

The procedures involved here were approved by the sponsoring institution’s Institutional Review Board and the data collection sites, and were consistent with the American Counseling Association’s Code of Ethics (2014). Three licensed counselors who had completed two graduate courses in testing and assessment conducted standardized interviewing and administered SASSI-3s. All three counselors completed training in SUD interviewing and SASSI-3 administration and scoring prior to the study’s beginning. All persons receiving treatment at sites 1 and 2 were asked to participate. A total of 117 of the 118 (99.2%) persons at site 1 and 61 of the 64 (95.3%) persons at site 2 agreed to participate. Sixty-three of 79 students (79.8%) enrolled in one of three separate undergraduate counseling courses agreed to participate.

Each participant met individually with a researcher who used the structured SUD questionnaire to conduct an interview and administered the SASSI-3. The SASSI-3s were scored and interpreted by a fourth researcher who had no knowledge of the interviewing researchers’ diagnostic impressions. For quality control purposes, the senior author reviewed the SASSI-3 scoring and questionnaire results.

Instruments

Structured Substance Use Disorder Questionnaire. At present, no structured guide or screen exists that was developed and normed using the current DSM-5 SUD criteria. To ensure that the counselors were uniform in their substance use interviews and that their interviews were consistent with the DSM-5 criteria, we designed a 22-item questionnaire to determine whether participants would meet criteria for a DSM-5 SUD. This questionnaire was based on the 11 criteria for an SUD from the DSM-5 (APA, 2013). These items were yes/no questions corresponding to the criteria for an SUD and were divided into two sections. The first 11 items applied to alcohol use and the second 11 items applied to the use of other drugs. Consistent with the DSM-5’s SUD section, participants who responded “yes” to two or more items in either section met criteria for a DSM-5 substance use disorder.

Endorsement of two items in the first section indicated the participant met criteria for an SUD involving alcohol use; endorsement of two items in the second section indicated the participant met criteria for an SUD involving other drugs. Severity of the SUD was based on decision rules provided in the DSM-5: 2–3 symptoms indicated a mild SUD, 4–5 symptoms indicated a moderate SUD, and 6 or more symptoms indicated a severe SUD (APA, 2013). Counselors clarified the meaning of items as needed. No distinction was made between different types of drug use (marijuana, cocaine, etc.) because the SASSI-3 does not do so. The internal consistency estimates for the alcohol and other drug use sections were high ( = .94 and  = .97, respectively).

Data Analysis

The authors used two methods of statistical analysis. Cohen’s kappa was used to measure the agreement between the two dichotomous DSM-5 SUD diagnosis variables (i.e., met criteria or not) and the overall score on the SASSI-3 (high probability of substance dependence disorder/low probability). Cohen’s kappa also was used to compare the DSM-5 diagnosis of either an SUD involving alcohol or one involving other drug use to the score on the SASSI-3 subscale 1 (FVA) or subscale 2 (FVOD), respectively. It was then used to measure agreement between the DSM-5 SUD diagnosis and the scores on subscales 3–9 on the SASSI-3. The value of the kappa is between 0 and 1 and is divided into 5 levels of agreement: .01 to .20 signifies slight agreement; .21 to .40 fair; .41 to .60 moderate; .61 to .80 substantial; and .81 to .99 near perfect agreement (Landis & Koch, 1977).

Unlike the kappa, ROC curve analysis is used with continuous variables. ROC analysis allows one to measure a trade-off between specificity (true positives) and sensitivity (true negatives; Youngstrom, 2014). ROC allows the investigator to determine how specificity and sensitivity change when the cut-off value of the continuous variable is changed. ROC value is expressed as an area under the ROC curve (AUROC). ROC curves are graphically represented as the relationship between an instrument’s specificity (horizontal axis) and sensitivity (vertical axis). ROC curves are interpreted by finding the point on the graph where a scale’s sensitivity and specificity are balanced. To the naked eye, this optimal point is where the curve begins to flatten out at the top. ROC analyses are performed on individual scales, but not multiple scales. As such, ROC analyses can only be performed on those SASSI-3 decision rules that involve individual scales (decision rules 1–5). Decision rules 6–9 involve input from two or more SASSI-3 scales and are therefore not subject to ROC analysis. The ROC scores are categorized as follows: ≥ .90, excellent; ≥ .80, good; ≥ .70, fair; and < .70, poor (Youngstrom, 2014).

Results

A review of the participants’ random answering profile (RAP) scores indicated that all profiles were valid. Of the 241 participants, the SASSI-3 classified 153 (63.5%) as having a high probability of having a substance dependence disorder. Raw SASSI-3 scale scores were converted to t scores using the SASSI-3 Manual’s Appendix C (Miller & Lazowski, 1999).

Table 1

SASSI-3 Scale Descriptive Data and Internal Consistency Estimates

SASSI-3 Scale	Mean t score	Standard Deviation	Range	Alpha

FVA	55.67	15.86	41-110	0.93

FVOD	70.58	25	5-116	0.97

SYM	63.58	14.68	36-92	0.81

OAT	60.23	12.25	35-85	0.74

SAT	58.35	14.78	24-99	0.52

DEF	45.33	10.81	24-73	0.53

SAM	62.76	12.09	30-94	0.63

FAM	44.1	12.18	4-76	0.24

COR	61.21	13.74	36-88	0.63

Note. FVA = Face Valid Alcohol scale; FVOD = Face Valid Other Drugs scale; SYM = Symptoms scale; OAT = Obvious Attributes scale; SAT = Subtle Attributes scale; DEF = Defensiveness scale; SAM = Supplemental Addiction Measure scale; FAM = Family versus Control Subjects scale; COR = Correctional scale.

Table 1 represents each SASSI-3 scale’s mean, standard deviation, range of scores and Cronbach’s alpha. These internal consistency reliability estimates were comparable with previously reported alphas (Burck, Laux, Harper, & Ritchie, 2010; Burck et al., 2008). The counselor’s interviews indicated that 188 (78.0%) of the participants met SUD criteria as specified in the DSM-5. Of these 188, 25 (13.3%) had a mild SUD, 13 (6.9%) were moderate, and 127 (67.6%) had a severe SUD. Of the 188 participants diagnosed with an SUD, 85 participants (45.2%) had an alcohol use disorder. Of these 85, 33 (38.8%) had a mild alcohol SUD, 13 (15.3%) were moderate, and 39 (45.9%) were severe. One hundred thirty-three participants (55.2%) were positive for an SUD other than alcohol. Of these 133, 10 (7.5%) had a mild disorder, 8 (6.0%) were moderate, and 115 (86.5%) were severe.

Cohen’s kappa (κ) statistic was calculated to determine the agreement between the DSM-5 diagnosis (i.e., met criteria or not) and the SASSI-3 overall score and each of the SASSI-3’s decision rules. Table 2 presents the results of these analyses as well as the number of SASSI-3 true positive, true negative, false positive and false negative classifications. The overall SASSI-3’s agreement with the counselors’ diagnostic decisions was fair (κ = .423, p = .060). The SASSI-3 results concurred with counselors’ diagnostic interviews on 182 cases and disagreed on 59 cases. The SASSI-3’s sensitivity (true positives) and specificity (true negatives) rates were .75 and .77, respectively.

Table 2

Agreement Between Counselors’ Diagnoses and SASSI-3 Individual and Total Decision Rules

Rule	True Positive	True Negative	False Positive	False Negative	Kappa

1¹	31 (12.9%)	151 (62.7%)	5 (2.1%)	54 (22.4%)	0.383***

2²	105 (43.6%)	105 (43.6%)	3 (1.2%)	28 (11.6%)	0.745*****

3	91 (37.8%)	47 (19.5%)	6 (2.5%)	97 (40.2%)	0.229***

4	32 (13.3%)	53 (22.0%)	0 (0%)	156 (64.7%)	0.083**

5	38 (15.8%)	53 (22.0%)	0 (0%)	150 (62.2%)	0.100**

6	62 (25.7%)	50 (20.7%)	3 (1.2%)	126 (52.3%)	0.149**

7	107 (44.4%)	48 (19.9%)	5 (2.1%)	81 (34.0%)	0.313***

8	4 (1.7%)	52 (21.6%)	1 (0.4%)	184 (76.3%)	0.001*

9	59 (24.5%)	46 (19.1%)	7 (2.9%)	129 (53.5%)	0.100**

SASSI-3	141 (58.5%)	41 (17.0%)	12 (5.0%)	47 (19.5%)	0.423****

Note. 1 = Rule 1 kappa tested against positive for alcohol use disorder only. 2 = Rule 2 kappa tested against all substance use disorders but alcohol use. All other kappa values are calculated for each Decision Rule’s agreement a clinical diagnosis of any substance use disorder. * = less than chance agreement, ** = slight agreement, *** = fair agreement, **** = moderate agreement and ***** = substantial agreement (Landis & Koch, 1977).

A closer examination of the kappa data indicates that the SASSI-3 and its subscales’ areas of weakness were the false negative rates. That is, the SASSI-3 failed to identify persons as likely substance dependent that the counselors judged as substance dependent (i.e., met criteria or not). Based on the kappa data, the SASSI-3 overall score incorrectly categorized 47 (19.5%) of the sample as not in need of further SUD assessment. This suggests that the decision rules’ cut scores may be too high for this sample. To test this hypothesis, the researchers investigated the SASSI-3’s FVA, FVOD, SYM, OAT and SAT scales’ specificity and sensitivity using ROC analyses (Youngstrom, 2014).

The ROC analysis of the FVA scale produced an AUROC value of .861, p = .000, standard error = .026, with a 95% confidence interval range of .811 to .912. This indicates that there is a good agreement between the FVA scale and the counselors’ alcohol use disorder diagnoses (Youngstrom, 2014). A review of the coordinates of the curve (Figure 1) demonstrates that an adjusted FVA t score cut-off of 53.5 would provide the optimal balance between sensitivity (.79) and specificity (.80). A t score of 53.5 translates into an FVA raw score of approximately 6 for both sexes. Rule 1 was recalculated using a raw score of 6 for both sexes and a kappa statistic was calculated to determine the agreement rate between this new FVA cut score and the counselors’ alcohol use disorder diagnoses. The new kappa statistic was .551, p = .000. The new Rule 1 sensitivity and specificity rates were, respectively, .81 and .77. Rule 1’s false positive rate was .19 and the false negative rate was .23. Lowering the Rule 1 cut score to 6 improved the kappa statistic by .168.

Figure 1.

ROC Curve for FVA t Score Plotted Against Counselor Alcohol Use Disorder Diagnosis

Note. Diagonal segments are produced by ties.

The ROC analysis of the FVOD scale produced an AUROC value of .965, p = .000, standard error = .013, with a 95% confidence interval range of .940 to .990. This indicates that there is an excellent agreement between the FVOD scale and the counselors’ SUD other than alcohol dependence diagnoses (Youngstrom, 2014). A review of the coordinates of the curve (Figure 2) argued against making any adjustments to the current FVOD score cut-offs for Rule 2.

Figure 2.

ROC Curve for FVOD t Score Plotted Against Counselor SUD Diagnosis

Note. Diagonal segments are produced by ties.

The ROC analysis of the SYM scale produced an AUROC value of .803, p = .000, standard error = .035, with a 95% confidence interval range of .735 to .871. This indicates that there is a good agreement between the SYM scale and the counselors’ SUD diagnoses (Youngstrom, 2014). A review of the coordinates of the curve (Figure 3) demonstrates that an adjusted SYM t score cut-off of 56.5 would provide the optimal balance between sensitivity (.761) and specificity (.774). A t score of 56.5 translates into an SYM raw score of approximately 5 for males and 4 for females. Rule 3 was recalculated using these new raw scores and a kappa statistic was calculated to determine the agreement rate between this new SYM cut score and the counselors’ overall SUD diagnoses. The kappa statistic was .437, p = .000. The new Rule 3 sensitivity and specificity rates were, respectively, .76 and .77. Rule 3’s false positive rate was .23 and the false negative rate was .24. Lowering the Rule 3 cut score to 6 improved the kappa statistic by .208.

Figure 3.

ROC Curve for SYM, OAT and SAT t Scores Plotted Against Counselor SUD Diagnosis

Note. Diagonal segments are produced by ties.

The ROC analysis of the OAT scale produced an AUROC value of .717, p = .000, standard error = .038, with a 95% confidence interval range of .643 to .791 (Figure 3). This indicates that there is fair agreement between the OAT scale and the counselors’ SUD diagnoses (Youngstrom, 2014). It was not possible to adjust the OAT t score to produce an optimal cut-off score such that a balance between sensitivity and specificity could be obtained. For example, to attain a sensitivity rating of .82, the
t score cut-off would have to be lowered to 48.5, which would produce a specificity rating of .634.

The ROC analysis of the SAT scale produced an AUROC value of .654, p = .001, standard error = .037, with a 95% confidence interval range of .582 to .727 (Figure 3). This indicates that there is poor agreement between the SAT scale and the counselors’ SUD diagnoses (Youngstrom, 2014). As with the OAT scale, no cut-off score could be determined that would provide an optimal balance between sensitivity and specificity.

The SASSI-3’s overall decision was recalculated using the lowered Rule 1 and Rule 3 cut scores. This process resulted in a total of 188 persons being classified as likely dependent on the SASSI-3, or a change in the total number of classifications by 28. A follow-up analysis comparing the SASSI-3 final decision using the adjusted scores for Rules 1 and 3 and the original cut scores for Rules 2 and 4–9 with the counselors’ decisions produced a kappa of .457 (p = .000). This kappa is slightly higher than the kappa produced using unadjusted Rule 1 and 3 cut-offs (κ = .423). The adjusted process identified 161 of the 181 (sensitivity = .89) participants whom the counselors classified as having an SUD. However, this increased sensitivity came at the cost of decreased specificity. The adjusted process identified only 33 (specificity = .55) of those participants whom the counselors determined did not have an SUD. The false positive rate and the false negative rate for this adjusted process were, respectively .45 and .11. In sum, this process increased the number of true positives by 20, decreased the number of true negatives by 8, increased the number of false positives by 8, and decreased the number of false negatives by 20. As one might expect, lowering the cut scores on these two rules increased the instrument’s ability to detect the presence of problems, but did so at the cost of possibly overdiagnosing 8 (3%) additional participants while reducing the false negative classifications by 20 (8.3%).

Discussion

The DSM-5 section on SUDs includes significant changes. Chief among these changes is the movement away from an abuse/dependence dichotomy to an SUD continuum that includes all of the criteria previously unique to abuse and dependence disorders as well as the addition of a craving criterion. The present study examined the SASSI-3’s utility in predicting counselors’ diagnostic classifications using the new DSM-5 SUD criteria. The results provided a mixed picture. The SASSI-3’s agreement with the counselors’ diagnoses was moderate. This finding prompted us to conduct a similar series of kappa analyses for each of the SASSI-3’s decision rules and ROC analyses for the first five SASSI-3 decision rules. The last four decision rules could not be analyzed with the ROC as they are each composed of more than one scale of the SASSI-3. The decision rules’ agreement with the counselors’ diagnoses varied considerably. The kappa values presented in Table 1 are below what would be expected based on previously published agreement statistics using previous versions of the DSM (Miller & Lazowski, 1999). The SASSI-3 and its decision rules’ false negative values suggested that the instrument’s modest agreement with the counselors may have been a consequence of unnecessarily high raw score cut-off points. Consistent with Clements’ (2002) findings related to adjusting cut scores, the ROC score analyses presented mixed results. The ROC analyses provided evidence that lowered FVA and SYM cut scores improved these scales’ respective sensitivity and specificity estimates. The FVOD scale’s current cut score produced high sensitivity and specificity and did not need to be improved. The OAT and SAT cut scores could not be adjusted without unwanted compromises to either scale’s associated decision rules’ sensitivity and specificity. The SASSI-3’s overall decision was recalculated using the lowered Rule 1 and Rule 3 cut scores. This process resulted in an improvement in sensitivity with a slight decrease in specificity. The net result was an improvement in the SASSI-3’s overall agreement with licensed counselors’ SUD determinations. Our FVOD scale’s sensitivity and specificity findings are consistent with those of First et al. (1997) and Lazowski et al. (1998), and suggest that the FVOD scale is useful in predicting DSM-IV-TR and DSM-5 non-alcohol SUDs. Our FVA scale findings are consistent with those of First et al. (1997) but differ from those of Lazowski et al. (1998). There are no other SASSI-3 ROC analyses available for comparison.

These results elicit deliberation about whether SUD counselors would be better served by an SUD screening instrument that over- or under-predicts SUD diagnoses. In the case of a scoring method that produces higher sensitivity but lower specificity, resource allocation might be a concern. A counselor’s diagnostic time might be unnecessarily spent ruling out clients, and clients might be unnecessarily inconvenienced by participating in a full SUD assessment. Alternatively, counselors using a scoring method with lower sensitivity but higher specificity would have fewer clients unnecessarily inconvenienced and spend less time assessing persons who do not need SUD treatment. The unfortunate trade-off is that persons with an SUD who might benefit from assessment and treatment would otherwise be sent home without an appropriate recommendation.

The health, social, psychological and legal implications of misdiagnosing clients with SUDs have been documented (Brown, Suppes, Adinoff, & Thomas, 2001; Horrigan, Piazza, & Weinstein, 1996; McMillan et al., 2008). Therefore, SUD counselors would benefit from a screening instrument with high sensitivity and specificity (Tiet, Finney, & Moos, 2008). When that goal cannot be achieved, SUD counselors and agencies may want to consider which of these two is more important.

Counselors and their agencies might consider their patient population and setting. Among populations likely to have an SUD, specificity might be less important than sensitivity. Conversely, a counselor working at a community mental health agency or college counseling center may benefit from a highly sensitive instrument to identify clients with dual diagnosis treatment needs. In sum, this study represents the first investigation of the SASSI-3’s agreement with the new DSM-5 SUD criteria. Past research (e.g., Laux et al., 2012) has demonstrated that the SASSI-3’s subtle scales improve the instrument’s diagnostic accuracy over that which is obtained using face valid approaches only. As such, we are cautious about drawing strong conclusions about the SASSI-3’s agreement with the DSM-5 criteria until a larger sample of research is available.

Limitations and Suggestions for Future Research

ROC curve analysis allows for the examination of one scale at a time. Consequently, we were unable to use these methods to examine the SASSI-3 decision rules that use more than one scale (Rules 6, 7, 8 and 9). These decision rules include data from the instrument’s subtle and obvious questions and are important contributors to the overall instrument’s sensitivity and specificity. Thus, the inability to examine these decision rules excludes results that may impact the SASSI-3 sensitivity and specificity.

This study collected data from three different locations: a university campus, an inpatient SUD treatment center and an outpatient mental health counseling center. The participants from the college sample were significantly younger, by 9 and 11 years respectively, than those from the other collection sites. Because SUDs are progressive in nature, we recommend that subsequent researchers conduct sample-specific SASSI-3 analyses to determine whether or not population-specific, rather than universal, cut-offs would be useful. Additionally, because there were very few persons in this sample whose use of drugs other than alcohol was categorized as mild, it is not clear whether the FVOD’s lower kappa value was due to the instrument itself or the sample’s homogeneity.

Finally, the DSM-5’s SUD diagnosis is on a continuum and includes severity specifiers (mild, moderate or severe). It may be more diagnostically useful to expand the SASSI-3 to address these specifiers, rather than rely solely on the current dichotomous likely/not likely dependent conclusion. Future researchers are encouraged to determine what decision rule cut scores would be associated with each of the three levels of SUD severity.

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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John M. Laux is a Professor at The University of Toledo. Robin M. DuFresne is a practicing clinical counselor at the Zepf Center in Toledo, Ohio. Allison K. Arnekrans is an Assistant Professor at Central Michigan University. Sylvia Lindinger-Sternart is an Assistant Professor at the University of Great Falls. Christopher P. Roseman is an Associate Professor at The University of Toledo. Amy Wertenberger is a doctoral candidate at The University of Toledo. Stephanie Calmes is a professional counselor at Harbor Behavioral Health in Toledo, Ohio. Darren W. Love is the Treatment Program Manager at Court Diagnostic and Treatment Center in Toledo, Ohio. Andrew M. Burck is an Assistant Professor at Marshall University. Jim Schultz is a mental health counselor at Harbor Behavioral Health in Toledo, Ohio. Correspondence may be addressed to John M. Laux, MS 119, 2801 W. Bancroft St., Toledo, Ohio, 43606, John.Laux@utoledo.edu.

Counselor Educators and Students With Problems of Professional Competence: A Survey and Discussion

Jul 20, 2016 | Article, Volume 6 - Issue 2

Kathleen Brown-Rice, Susan Furr

It has been found that 10% of counselors-in-training are ill-suited for the profession (Gaubatz & Vera, 2002). In that, they have problems of professional competence (PPC) that impede their ability to function as professional counselors (Elman & Forrest, 2007). These PPC include skill competencies, ethical behaviors and appropriate personal functioning (Kaslow et al., 2007). To evaluate students in terms of professional competence and prevent those with inadequate skills and dispositions from entering the profession, gatekeeping is utilized. Counselor educators are required to be transparent in their gatekeeping procedures with students. Students are to be informed of “the levels of competency expected, appraisal methods, and timing of evaluations for both didactic and clinical competencies” and be provided “ongoing feedback” (American Counseling Association [ACA], 2014, p. 15). There has been significant research to provide counselor educators with information to establish gatekeeping and remediation procedures (Gaubatz & Vera, 2002; Homrich, DeLorenzi, Bloom, & Godbee, 2014; Hutchens, Block, & Young, 2013; Kerl, Garcia, McCullough, & Maxwell, 2002; McAdams, Foster, & Ward, 2007; Pease-Carter & Barrio Minton, 2012; Vacha-Haase, Davenport, & Kerewsky, 2004; Zoimek-Daigle & Christensen, 2010). However, little research has been done to examine the impact on counselor educators when interacting with students who have PPC and the roadblocks that impede educators’ ability to gatekeep.

Gatekeeping Procedures

Gatekeeping is a mechanism for counselor educators to determine the fitness of students to enter the counseling profession (Vacha-Haase et al., 2004). Gatekeeping begins as part of the admission process of a counseling program (Kerl & Eichler, 2007). During the admission process, counselor educators do not allow entry to prospective students who show traits, qualities or behaviors that would result in them not being able to meet professional competencies or who lack the prescribed academic requirements (Lumadue & Duffey, 1999; Swank & Smith-Adcock, 2013). However, gatekeeping is not just part of the admission process. Ziomek-Daigle and Christensen (2010) found that gatekeeping is a progressive activity that includes four phases, including preadmission screening, postadmission screening, remediation plan and remediation outcome.

Informing Students of Program Expectations

The American Counseling Association Code of Ethics (2014) provides that counseling students be aware of what type and degree of skill and knowledge will be required of them to be successful in the program, specific training goals and objectives, what students’ evaluations are based on, and the policies and procedures for students’ evaluations. One of the most important methods of ensuring understanding of expectations is informing students of the program’s expectations at the beginning of the program. Once clearly defined behaviors are established, sharing these expectations with students can result in fewer problematic situations (Kerl et al., 2002; McAdams et al., 2007). Furthermore, not providing students with clear expectations for conduct may be viewed as unfair to those wanting to become counselors (Homrich et al., 2014).

It is recommended that professional standards be made clear to students and applied consistently (Hutchens et al., 2013). Using multiple methods of distributing information is desired by students who have stated they want information shared both orally and in written form, and want the information presented throughout the program (Pease-Carter & Barrio Minton, 2012). Pease-Carter and Barrio Minton (2012) found that students desired information not only about academic expectations but also wanted to know about self-disclosure, reflection, personal growth and student rights.

Assessing Students’ PPC Behaviors

Individual programs have developed standards for evaluating students on professional competencies and use these evaluations to provide formative feedback (Kerl et al., 2002). Historically, the most commonly cited problematic behaviors have been inadequate clinical skills, defensiveness in supervision and deficient interpersonal skills (Vacha-Haase et al., 2004). Efforts to identify criteria for evaluating students in terms of professional behaviors, interpersonal behaviors and intrapersonal behaviors have recently been undertaken (Homrich et al., 2014), and these criteria provide a platform for developing clear expectations for counseling trainees.

Roadblocks to Gatekeeping

There are a variety of reasons that counselor educators do not engage in the gatekeeping process. Gateslipping rates have been reported as higher in programs where faculty members reported that their colleagues were concerned about being sued or receiving less than favorable teaching evaluations (Gaubatz & Vera, 2002; Jacobs et al., 2011). In some settings, colleagues and administration provide support for engaging in gatekeeping; however, lack of clear evidence and bias toward leniency lead to gateslippage (Brear & Dorrian, 2010). Absence of well-defined program policies may make it difficult to initiate gatekeeping conversations with a student as well (Jacobs et al., 2011).

Gatekeeping demands a great amount of time and energy, and situations involving PPC often seem unending (Gizara & Forrest, 2004). Not only do PPC have to be identified and communicated to the student, remediation plans need to be developed. Such plans may include helping the counselor-in-training obtain remedial assistance, providing intensified supervision, documenting the activities of the plan and ensuring the student understands due process options (Ziomek-Daigle & Christensen, 2010). When remediation plans are not successful, decisions about dismissal must be made, and the actions taken must be transparent (Kaslow et al., 2007).

There may be occasions where the gatekeeping responsibility is diffused among different entities. In a review of ethical issues around professional competence problems (Johnson et al., 2008), Johnson labeled this issue as the “hot potato game” (p. 589), where the last entity engaged with the problematic student is stuck with the issue. If a student is allowed to gateslip through the graduate program, then the training facility and licensing board now become involved. Rather than address the issue when it is first recognized, the student may be allowed to move to the next stage of training with the hope that the problem disappears or that that it is addressed at the next level. Addressing issues early in the training may help avoid more serious issues, like the empathy veil, later when students go to clinical sites.

The Empathy Veil

This term was coined by Brown-Rice and Furr (2014) and refers to the counselor educator’s need to empathize with the counselor-in-training, which can result in reluctance to engage in gatekeeping activities. Role tension may be one factor in developing an empathy veil. This term evolved from work by Sue and Sue (2012) where a person’s worldview is seen as having an invisible veil that is created by cultural conditioning and is believed to operate outside of consciousness. Forrest et al. (2013) found that empathy may contribute to avoiding confronting student issues for fear of damaging the relationship. Because of the role that faculty play in fostering growth and development, which often involves compassion and support, it may become difficult to provide accurate summative evaluations of trainees’ behaviors (Johnson et al., 2008). Given that many faculty members also are professional counselors, they may view their role as assisting the student in behavior change and thus work with the student to address interpersonal issues that interfere with developing counseling skills (Kerl et al., 2002). This empathy can be both a support and a challenge when difficult conversations about problematic professional, interpersonal and intrapersonal behaviors need to take place (Jacobs et al., 2011). Although empathy can create a safe environment in which to discuss difficulties, an educator’s empathy also can lead to overprotective behaviors that may actually interfere with the student’s development (Gizara & Forrest, 2004).

Role of Diversity

Another important area of consideration is how cultural differences intersect with PPC. When there is a cross-cultural student PPC situation, a complex power differential arises that not only is associated with the faculty–student relationship, but also related to cultural differences (Goodrich & Shin, 2013). Kaslow et al. (2007) proposed that consideration should be given to the impact of beliefs, values and attitudes when assessing competence problems. Fear of appearing biased may complicate identifying trainees with PPC and how decisions are made regarding students (Shen-Miller, Forrest, & Elman, 2009). The counselor educator’s own cultural background may influence how counselors-in-training are evaluated, and it is recommended that cultural dynamics be assessed when addressing PPC (Rust, Raskin, & Hill, 2013). Shen-Miller, Forrest, and Burt (2012) identified two approaches that often are used by faculty in assessing students—culture-attentive (i.e., approaches that include attention to aspects of diversity) or colorblind (i.e., inattention or minimization of differences associated with diversity). These views represent two ends of a “continuum of conceptualizing intersections between diversity and professional standards” (Shen-Miller et al., 2012, p. 1207). In trying to find a place on this continuum to address PPC, do counselor educators underidentify PPC because of fear of being biased? Or, are counselor educators more prone to overidentify PPC because of not examining contextual factors that influence competence? In this study, an attempt is made to examine counselor educators’ views of what interferes with their ability to address issues of counselor education student PPC.

Other Barriers

Previous research has found that educators believe that they have not been provided with sufficient training related to gatekeeping and remediation procedures, and they do not feel supported by their agency and colleagues (Gizara & Forrest, 2004; Vacha-Haase et al., 2004). Additionally, counselor educators may be reluctant to dismiss a student for dread of potential litigation and personal recrimination (Crawford & Gilroy, 2012; Hutchens et al., 2013) and receiving poor teaching evaluations (Gaubatz & Vera, 2002). Recent court cases have increased awareness about the legal consequences of gatekeeping. The Ward and Keeton cases have highlighted the need for counseling programs to establish clear statements about student expectations (Herlihy, Hermann, & Greden, 2014). Other cases have taught faculty members the importance of providing regular process evaluations and thorough documentation (McAdams & Foster, 2007). Reflection on the results of facing a court challenge includes the significance of having a measure of performance that helps faculty retain objectivity and the importance of adhering to established procedures (McAdams et al., 2007).

The purpose of this study was to answer the following research questions: (a) What types of master’s students’ PPC do Council for Accreditation of Counseling and Related Educational Programs (CACREP) counselor educators perceive have the greatest impact on them as educators? (b) What do CACREP counselor educators perceive are roadblocks that interfere with their ability to engage in the gatekeeping of master’s students with PPC? and (c) What is CACREP counselor educators’ knowledge of their programs’ protocol for addressing a student with PPC? In this study, student refers to a master’s student enrolled in the participant’s counseling program, colleague is another counselor educator teaching in the participant’s counseling program, and impact means to have a strong effect. PPC refers to attitudes and behaviors that could interfere with the professional competence of a counselor-in-training, including: (a) a lack of ability or opposition to acquire and integrate professional standards into one’s professional counseling behavior; (b) a lack of ability to attain professional skills and reach an acceptable level of competency; (c) a lack of ability to manage one’s stress, psychological dysfunction or emotional responses that may impact professional performance; or (d) engagement in unethical behavior (Falender, Collins, & Shafranske, 2009).

Methods

Participants and Procedures

Prior to initiating the study, institutional review board approval was obtained. Recruitment of participants was conducted by an e-mail to all faculty employed at CACREP-accredited programs in the United States. The researchers of this study obtained a list of accredited programs from the official CACREP Web site and then visited each program’s Web site to obtain the e-mail addresses of the program’s counselor educators. Seven programs did not list faculty e-mails on their university Web sites. The exact number of educators teaching in CACREP-accredited programs is not known, as the programs’ Web sites might have imprecise or out-of-date information. Based upon the e-mail addresses gathered from the university Web sites, a list of 1,584 faculty members was created. Thereafter, one e-mail solicitation was sent to all identified faculty that directed participants to an online survey entitled, Problems of Professional Competency Survey – Counselor Educator Version (PPCS-CE), which was located on Psychdata.com. Of the 1,584 e-mails that were sent, 71 were undeliverable due to lacking a valid address or security issues, 15 were returned with automatic responses that the faculty member was absent (e.g., on sabbatical, no longer at university, ill, professor emeritus), and five responses indicated that the receiver of the e-mail was not a counselor educator. This left a total sample size of 1,493 CACREP counselor educators. For a population of 1,500, a sample size of 306 is adequate to generalize with a confidence interval of 95% (Gay, Mills, & Airasian, 2009). A total of 382 participants completed the survey; however, respondents with missing or invalid data (n = 12, less than 4%) were eliminated via listwise deletion, leaving a total number of 370 participants included in this study. This resulted in an adequate sample size of 370 participants and a final response rate of 25%. Frequencies and percentages of the demographic variables in this study are reported in Table 1.

Table 1 Numbers and Percentages of Demographic Variables
Variable	Number	Percentage
Gender:
Female	213	58
Male	157	42
Background:
Caucasian	310	84
African American	24	6
Hispanic/Latino	12	3
Multi-Racial	15	4
Asian/Pacific Islander	8	2
Native American	1	1
Age:
20 years to 29 years	7	2
30 years to 39 years	77	21
40 years to 49 years	97	26
50 years to 59 years	76	21
60 years or older	113	31
Sexual Orientation:
Heterosexual	331	90
Bisexual	9	2
Gay or Lesbian	30	8

Description of Program:
Predominantly on Campus	318	86
Predominantly Online	7	2
Hybrid of Online/on Campus	45	12

Location of Program:
South	146	40
Northeast	93	25
Midwest	74	20
West	57	15
Highest Degree:
PhD – CACREP Program	201	54
PhD – Non-CACREP Program	38	10
EdS in Counseling	10	3
PhD – Counseling Psychology	31	8
PhD – Clinical Psychology	4	1
Other (doctoral in another discipline ormaster’s in counseling or related field)	86	23
Academic Rank:
Assistant Professor	145	39
Associate Professor	102	28
Professor	92	25
Clinical Instructor	8	2
Adjunct Instructor	6	.2
Other	17	5

Years Teaching in a CACREP-Accredited Program:
Less than 2 years	59	16
2 to 5 years	84	23
6 to 10 years	90	24
11 to 15 years	66	18
16 to 20 years	28	8
Over 20 years	43	12
Licenses and Certifications Held:
Licensed Professional Counselor	201	55
Licensed Alcohol and Drug Counselor	21	6
Provisionally Licensed Professional Counselor	14	4
Licensed Marriage & Family Counselor	33	9
Licensed Psychologist	37	10
Licensed Social Worker	7	2
Certified School Counselor	95	26
National Certified Counselor	199	54

Instrument

The survey for this present study was designed based upon the Problems of Professional Competency Survey – Master Student Version (PPCS-MS) developed by Brown-Rice and Furr (2013), related to determining master’s students’ enrolled in CACREP-accredited programs knowledge of classmates with PPC. The PPCS-MS was constructed based upon the literature regarding PPC in psychology, counseling and social work. To establish content validity and reliability, the PPCS-MS underwent an expert review process and two pilot studies to provide clarity and conciseness of the survey questions. Additionally, a principal components analysis created components representative of what the review of the literature provided on these issues (Brown-Rice & Furr, 2013). The questions and format of the PPCS-MS were used and adjusted to create a self-report survey entitled the Problems of Professional Competency Survey – Counselor Educator Version (PPCS-CE). This instrument was divided into three parts: Part I – Demographic Information, Part II – Counselor Educators and Students with PPC, and Part III – Counselor Educators’ Knowledge of Colleagues’ PPC (removed from this analysis). Part II included three sections. Section I, Counselor Educators’ Knowledge of Students’ Problems of Professional Competency, included one question to determine whether participants have observed students with PPC and two questions to determine participants’ knowledge of the type of students’ PPC and the impact of the problematic behavior. Each PPC was rank ordered from 1 being the most common and 9 being the least common observed behavior, and the impact of having a student with PPC was ranked ordered with 1 having the most impact and 9 having the least impact. Chi square analyses of each of the rank ordered items led to a rejection of the null hypotheses of the categories of the item occurring with equal probabilities.

Section II of Part II of the survey investigated counselor educators’ reactions to students’ PPC and consisted of seven questions. The answers to all these questions were based on a 5-point Likert scale (1 = strongly disagree to 5 = strongly agree). Section III, Counselor Educators’ Knowledge of Counseling Program’s Protocol for Addressing Problems of Professional Competency, included questions relating to responsibility for being aware of students PPC and programs’ protocols for addressing PPC. The first nine questions were evaluated on a 5-point Likert scale. The tenth item was unstructured to provide a place for participants to provide additional information.

Results

Types and Impact of Students’ Problematic Behavior

Of the 370 participants, the majority (91%, n = 338) reported that they had observed students with PPC in their programs. Additionally, 2% (n = 8) of the respondents indicated they did not know if there were students with PPC in their programs, leaving 7% (n = 24) who had not observed any students with PPC. To answer the first research question regarding the types and impact of master’s students’ PPC observed by CACREP counselor educators, the responses for the 338 participants who reported observing a student with PPC were examined according to the rank order question regarding the types of PPC that participants most observed with counselors-in-training in their programs. The most frequently identified problematic behaviors included inadequate clinical skills (M = 2.90, SD = 1.88), inadequate interpersonal skills (M = 3.15, SD = 1.69), inadequate academic skills (M = 3.38, SD = 2.29), inability to regulate emotions (M = 4.16, SD = 1.88), and unprofessional behavior (M = 4.29, SD = 2.13). Those behaviors ranked as less impactful were unprofessional behavior (M = 4.29, SD = 2.13), unethical behavior (M = 5.63, SD = 2.03), psychological concern (M = 6.20, SD = 1.84), personality disorder (M = 7.60, SD = 1.61), and substance use disorder (M = 7.69, SD = 1.68).

The responses for the rank order question regarding the type of impact of having counselors-in-training in their program with PPC focused on the behaviors having the most impact on the faculty member. Included in this list were disrupted the classroom learning environment (M = 2.99, SD = 1.86), negatively affected other students (M = 3.26, SD = 1.52), increased participant’s workload (M = 3.29, SD = 2.05), and increased participant’s stress (M = 3.39, SD = 1.64). Additional items that were ranked as less impactful included negatively affected client care (M = 5.06, SD = 2.44), negatively affected relationship with students (M = 5.47, SD = .87), negatively affected relationship with colleagues (M = 6.59, SD = 1.42), negatively affected reputation of the program (M = 6.81, SD = 1.90), and a grievance or litigation occurred (M = 8.25, SD = 1.94).

Roadblocks to Gatekeeping

All participants (n = 370) completed Section II, Part II of the PPCS-CE, and these participants’ responses for strongly agree and agree were combined to report the subsequent findings. Each of the participants reported degree of agreement or disagreement regarding beliefs around the roadblocks that interfere with their ability to engage in the gatekeeping of master’s students with PPC. Fifty-three percent (n = 197) reporting struggling emotionally to balance being empathetic with a student demonstrating PPC and their gatekeeping duties. When looking at addressing PPC with a student who is culturally different from the participant, 38% (n = 141) stated they were reluctant to do so due to the fear they would appear culturally insensitive, and 36% (n = 137) were reluctant to do so due to the fear of allegations of discrimination. Regarding being supported by others, 13% (n = 47) provided they did not feel supported by their chair to address a student who demonstrated PPC, and 13% (n = 47) stated they did not feel supported by their colleagues to address a student who demonstrated PPC. Further, 92% (n = 339) were concerned about the counseling profession when a student with PPC was allowed to pass through the program. Additionally, 30% (n = 110) provided they were reluctant to address a student demonstrating PPC for fear of recrimination (e.g., negative teaching evaluations, legal action).

Protocol for Addressing Students with PPC

When the participants’ responses for strongly agree and agree were combined, 99% (n = 368) believed it was their responsibility to be aware of students with PPC, 91% (n = 335) believed that it was their chair’s responsibility, and 96% (n = 354) believed it was both their chair and respondents’ responsibility to be aware of students with PPC. Additionally, 94% (n = 347) were aware of their programs’ procedures regarding how to address problematic behavior, 71% (n = 263) reported their chair had discussed their programs’ procedures regarding addressing PPC with them, and 38% (n = 140) stated they had received training from their program regarding how to intervene with a student who they believe is demonstrating PPC. Further, 87% (n = 321) were aware of the appropriate intervention to take with students with PPC, 51% (n = 189) would like more information regarding how to identify students with PPC, and 61% (n = 226) of the participants would like more information on how to respond to a student with PPC.

Discussion and Implications

The PPC identified in this study as being observed most frequently are consistent with those problematic behaviors identified in other studies. Vacha-Haase et al. (2004) also identified that inadequate clinical skills and deficient interpersonal skills were most commonly cited as problematic behaviors. In a study examining a proposed set of standards for clinical training, Homrich et al. (2014) identified three categories of behaviors needed by graduate students in clinical training, which included professional behaviors, interpersonal behaviors and intrapersonal behaviors. The types of PPC counselor educators observed in this study parallel the findings of Homrich et al. (2014) in that inadequate clinical skills and unprofessional behavior are similar to their theme of professional behaviors, and the category of inadequate interpersonal skills is comparable to their theme of interpersonal behaviors. Inability to regulate emotions is analogous to their theme of intrapersonal behaviors. Because they were examining clinical training standards, there was no mention of academic skills, yet this type of PPC was cited as a concern by many of the respondents in this study.

Examination of these data leads to questions about how counseling programs admit students. Both academic skills and interpersonal skills are areas that can be addressed through the admissions process. Smaby, Maddox, Richmond, Lepkowski, and Packman (2005) found that undergraduate GPA and GRE Verbal scores could be predictive of scores on the Counselor Preparation Comprehensive Examination (CPCE), which focus on knowledge, but were not highly predictive of personal development. Given the level of concern over academic skills, using these cognitive measures is important, but expanding the way of assessing academic ability also needs to be sensitive to issues around diversity and bias in standardized measures.

In a survey on admission screening measures, training directors indicated that the personal interview was the most effective screening measure (Leverett-Main, 2004). Using creative group strategies during the admission process has been advocated to help assess academic potential as well as dispositions (Swank & Smith-Adcock, 2013). Smith, Robinson, and Young (2007) found that an assessment of wellness might uncover issues around psychological distress that could affect performance in a counseling graduate education program.

Previous research has indicated that faculty members have concerns about addressing PPC because of their desire to be supportive of students (Johnson et al., 2008; Kerl et al., 2002), which would support the concept of the empathy veil (Brown-Rice & Furr, 2014). In this study, 53% of respondents reported struggling emotionally to balance empathy with their gatekeeping duties to intercede with a counselor-in-training with PPC. When the open-ended responses were reviewed, participants’ responses supported this empathetic struggle. For example, one respondent stated, “I have heard many times how a grade should be considered through compassion for student circumstances rather than demonstrated competency.” Another participant provided, “Our empathy wants to give them another chance, but our ethics don’t necessarily allow for it. It’s a struggle for me. It is not a part of the job that I anticipated. Although I remember learning the concept in my doctoral program, I wasn’t prepared to address it.” Therefore, it would appear that these counselor educators are struggling with empathy veils.

When looking at other roadblocks (e.g., lack of peer and institutional support, diversity in gatekeeping, threat of litigation or recrimination from a counselor-in-training), there were some interesting findings. Previous research has found a lack of support for counselor educators from administration and colleagues in dealing with problematic students (Gizara & Forrest, 2004; Vacha-Haase et al., 2004). This concern has been found to be especially true for field supervisors (Bogo, Regehr, Power, & Regehr, 2007; Homonoff, 2008). However, the results of the current study found that only 13% stated they did not feel supported by their chair or colleagues to address a student who demonstrated PPC. The open-ended responses supported these findings. For example, participants stated, “We have a culture and climate of supporting our gatekeeping role in the counseling profession”; “My colleagues and I work as a team in addressing student concerns”; and “I feel supported by my chair and department when dealing with such issues. We deal with these issues as a department. No one is alone in addressing such issues.” Therefore, for this study, lack of institutional and peer support do not seem to be roadblocks. This could be due to the fact that all the participants in this study worked at programs that were accredited by CACREP. CACREP (2016) requires a procedure for addressing student professional and personal development. Counselor educators at programs that are not CACREP-accredited may report different findings. A limitation of this study is that only faculty from CACREP-accredited programs were contacted. Future research focusing on non-CACREP programs and site supervisors regarding this issue may be beneficial. Those working in the field may not have a deep understanding of the role of gatekeeping and may need to develop clear guidelines for their role as supervisors for both counselors-in-training and for counselors seeking licensure.

When the counselor-in-training was from a different cultural background than the counselor educator, 38% of the respondents expressed concern about appearing culturally insensitive, and 36% were concerned about allegations of discrimination. Because this survey was a self-report measure, there is risk that some participants provided answers they considered to be socially desirable (which is a limitation of the study). The field of counseling is committed to multicultural competence in skills, knowledge and awareness, which could make it difficult for counselor educators to acknowledge problematic behaviors in students who are different from themselves. Research has indicated that White counselors tend to favor the colorblind approach in disposition cases (Neville, Lilly, Duran, Lee, & Browne, 2000). Yet fear of responding in a way that appears insensitive may have contributed to responding in socially desirable ways on this instrument. More exploration is needed in this area. While recent literature has addressed how to be culturally responsive when intervening with counseling students’ problematic behavior (Goodrich & Shin, 2013), there is a lack of research regarding culturally responsive performance standards. Until the counseling profession establishes clear performance expectations that are culturally sensitive, the tension between colorblind and culture-attentive expectations will continue to complicate responding to PPC. For example, class performance often has an evaluation component concerning class participation. If a student is from a culture where students do not contribute unless called upon by the professor, then this student may perform poorly because of not understanding expectations. The professor needs to be sensitive to this type of difference and work with the student to develop ways of being successful.

Few participants reported involvement in a legal action related to gatekeeping and remediation with a student demonstrating PPC; however, 30% stated they were reluctant to address a student for fear of retaliation from the student. Given that counselor educators who have been involved in such cases have disclosed the emotional toll these processes take on a program and its faculty members (Dugger & Francis, 2014; McAdams et al., 2007), it seems understandable that there is concern. Therefore, support from ACA, resources in the form of consultation with other campuses and endorsement of gatekeeping processes from one’s own campus are essential in navigating this demanding process. Although legal actions are not common, developing appropriate gatekeeping procedures will help prevent negative outcomes (Dugger & Francis, 2014).

In addition, Brown-Rice and Furr (2014) provided that counselor educators and supervisors should “maintain appropriate ethical boundaries and avoid dual relationships with counselors-in-training, inform and educate themselves regarding the proper gatekeeping protocols and limit their own hypocrisy regarding acting in a competent and ethical manner” (p. 5). There has been substantial research and discussion regarding ethical boundaries, dual relationships and establishing proper gatekeeping procedures (Brown, 2013; Kolbert, Morgan, & Brendel, 2002; Morrissette & Gadbois, 2006; Ziomek-Daigle & Christensen, 2010). However, there seems to be a lack of attention to the competence of counselor educators and how counselors-in-training perceive educators’ professional and personal competence. Do students see faculty members engaging in the same attitudes, skills, behaviors and self-awareness that they are required to adhere to? Are counselor educators modeling the behaviors they want to see in their students or do they hold students to different standards?

Almost all the participants (94%) provided they were aware of their programs’ procedures regarding how to address problematic behavior, and 87% were aware of the appropriate intervention to take with students with PPC. However, only 38% stated they had received training from their program regarding how to intervene with a problematic student. In the open-ended responses, participants stated that their programs had established procedures and all faculty members were aware of them; however, they also reported that PPC were minimized or not addressed. For example, one participant provided, “while there is often a policy in place . . . I find that colleagues fail to follow that policy in practice.” Another respondent stated, “It is also up to the adviser to address the issue with the student and create a plan of improvement. Not all faculty do this and this leads to students receiving different treatment.” Additionally, a participant shared that colleagues were resistant to “address inappropriate student attitudes, dispositions, personality characteristics, and behaviors unless they reach such a critical threshold that they pose a significant threat to clients or, in some cases, faculty egos.” It also appears that how a student is addressed may be related to faculty dynamics. For example, “Political alliances among faculty play a major role in determining which students are targeted for intervention.”

Participants overwhelmingly reported they were aware of their programs’ procedures and the appropriate interventions to take when they encounter counselors-in-training with PPC. However, they also reported that they struggle with their gatekeeping duties due to empathy, diversity issues and fear of recrimination; half of the participants (51%) stated they would like more information regarding how to identify students with PPC, and 61% would like more information on how to respond to these students. Apparently, counseling programs are doing a good job developing procedures and communicating these procedures to faculty members, as recommended by Gaubatz and Vera (2002). But there remains a disconnect between knowledge about procedures and the ability to implement a response to PPC that may be related to the roadblocks identified in this study.

Counselor educators and supervisors know what they are supposed to do if a PPC has been clearly delineated; however, they struggle with identifying problematic behavior that reaches a threshold of needing to be formally addressed and taking action related to problematic student behaviors. The gap between the recognition that a student is not meeting expectations and the point where formal action is initiated may be filled with the counselor educators’ own beliefs about how they can fix the problem as well as their own anxieties related to the barriers discovered in this study. The recognition of and intervention with students with PPC can be further complicated by counselor educators having to negotiate faculty politics. It would seem that more attention is needed on assisting counselor educators in negotiating these barriers to ensure students do not gateslip.

Conclusion

The results of this current study provide insight that educators are aware of counseling students with problematic behaviors, and these behaviors are impacting the learning environment, other students in the program and personal stress. It also appears that the largest roadblock present and impacting counselor educators’ ability to engage in gatekeeping procedures relates to their empathy veils. The authors of this article perceive that there is a struggle for counselor educators between balancing compassion for students’ life circumstances and developmental level with holding them to an acceptable level of professional competence. Counselor educators know it is their responsibility to engage in ethical gatekeeping procedures; however, they do not want to be excessively critical of students. Having an understanding of the empathy veil will assist educators in finding the balance between challenging and supporting students. Counselor educators must not accept students with PPC into their programs or allow them to move on without confronting and remediating their problematic behaviors. Educators need to do their due diligence and be willing to lift their empathy veils and engage in their gatekeeping responsibilities.

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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The Process and Implications of Diagnosing Oppositional Defiant Disorder in African American Males

Jul 20, 2016 | Article, Volume 6 - Issue 2

Marc A. Grimmett, Adria S. Dunbar, Teshanee Williams, Cory Clark, Brittany Prioleau, Jen S. Miller

Research studies indicate that the number of African Americans diagnosed with oppositional defiant disorder (ODD) is disproportionately higher than other demographic groups (Feisthamel & Schwartz, 2009; Schwartz & Feisthamel, 2009). One contributing factor for this disproportionality is that White American clients presenting with the same disruptive behavioral symptoms as African American clients tend to be diagnosed with adjustment disorder. Feisthamel and Schwartz (2009) concluded, “counselors perceive attention deficit, oppositional, and conduct-related problems as significantly more common among clients of color” (p. 51), and racial diagnostic bias may influence the assessment process. Racial biases in clinical decision making are explained in a conceptual pathway developed by Feisthamel and Schwartz (2007).

In the pathway, counselors who hold stereotypical beliefs about clients selectively attend to client information. The counselor’s judgment is influenced by personal bias, resulting in misdiagnosing the client. African American masculinity stereotypes of criminal mindedness, violent behavior, aggression and hostility (Spencer, 2013) held by counselors with low multicultural social justice counseling competence (Ratts, Singh, Nassar-McMillan, Butler, & McCullough, 2015; Sue, Arredondo, & McDavis, 1992) potentially foster misdiagnosis and overdiagnosis of African American males with ODD.

Studies on how African American males are diagnosed with ODD and specific implications for African American males are relatively nonexistent. McNeil, Capage, and Bennett (2002) indicated the majority of information on children diagnosed with ODD has been obtained from primarily White children and families. They recommended that counselors working with African American families consider the African American family’s unique stressors, worldviews and burdens; possible inclusion of the extended family; possible therapist biases that conflict with client’s worldview; and positive factors that lead to competency, self-reliance and health in African American culture (Lindsey & Cuellar, 2000). Thus, an appropriate ODD diagnosis in African American males requires assessment and treatment plan considerations that include other related factors.

Diagnosing Oppositional Defiant Disorder in African American Males

According to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5; American Psychiatric Association [APA], 2013), ODD is characterized by a pattern of behavior that includes angry and irritable mood, argumentative and defiant behavior, and/or vindictiveness. Symptoms must cause significant problems at home, school or work; must occur with at least one individual who is not a sibling; and must persist for 6 months or more (APA, 2013). The diagnostic assessment also determines that (a) these behaviors are displayed more often than is typical for peers, and (b) symptoms are not associated with other mental health disorders such as anxiety, depression, antisocial behavior and substance abuse disorders.

High rates of ODD diagnosis among African American males may occur because of low cultural competency in diagnosis and counselor bias (Guindon & Sobhany, 2001; Hays, Prosek, & McLeod, 2010; Snowden, 2003). Spencer and Oatts (1999) and Clark (2007), for example, found that health professionals misinterpreted symptoms of disruptive behavior disorders like ODD at greater rates for African American children. Misdiagnosis was common among children assessed as having symptoms of (a) obsessive compulsive disorder and response to rigid classroom rules, (b) bipolar disorder or attention-deficit/hyperactivity disorder and engagement in destructive behavior, and (c) anxiety disorder (e.g., social anxiety) and dislike for school, and defiance toward teachers. These symptoms also may result from unfair treatment and discrimination (Smith & Harper, 2015). Misdiagnosis of ODD can reasonably be expected to have potentially adverse implications for healthy psychological, emotional and social development in family and education systems.

Family Systems

Primary caregivers of children diagnosed with ODD report mild to moderate levels of depression and anxiety and severe levels of stress (Oruche et al., 2015). Caregivers report having overwhelming difficulty managing the aggressive and defiant nature of their children’s behaviors and constantly watching over their children to prevent them from hurting themselves or others (Oruche et al., 2015). The well-being of family members who are not primary caregivers (i.e., in some cases fathers, siblings, grandparents) is rarely considered in disruptive behavior research, although these family members experience many of the same stressors outlined by primary caregivers (Kilmer, Cook, Taylor, Kane, & Clark, 2008). Siblings of diagnosed adolescents have demonstrated high rates of anxiety, poor school performance and adjustment problems (Kilmer et al., 2008; Oruche et al., 2015). Children with disruptive behavior disorders whose family members participated in their treatment showed improved grade point averages and attendance and reduced drop-out rates relative to students whose family members considered themselves uninvolved (Reinke, Herman, Petras, & Ialongo, 2008). While family interventions appear helpful, an accurate diagnosis remains the first step in creating an effective treatment plan and not causing further harm to clients (e.g., school suspension, expulsion, incarceration; Smith & Harper, 2015).

Educational Systems

Students with aggressive disruptive behaviors also have higher rates of mental health risk factors, including school maladjustment, antisocial activity, substance use and early sexual activity (Schofield, Bierman, Heinrichs, & Nix, 2008). Children diagnosed with ODD experience a range of academic problems, including in-school suspensions (Reinke et al., 2008), high school drop-out (Vitaro, Brendgen, Larose, & Trembaly, 2005), and lower academic grades and achievement scores (Bub, McCartney, & Willett, 2007). ODD was not cited as a contributing factor; however, a recent report by Smith and Harper (2015) revealed that in Southern states African American males comprised 47% of student suspensions and 44% of expulsions from K–12 public schools in the United States, which was highest among all racial and ethnic groups. School administrators also were more likely to rate African American children higher on symptoms related to behavioral disorders than White American children (Epstein et al., 2005).

Finally, 50–70% of juveniles detained in the United States have a diagnosable behavioral health disorder (e.g., ODD; Schubert & Mulvey, 2014). While African American youth make up only 16% of the total youth population in the United States, they account for 37% of the detained population (National Council on Crime and Delinquency, 2007). Given the potential negative trajectory of an ODD diagnosis for some African American males, the diagnostic process warrants further consideration.

Method

Design

The purpose of this qualitative research study was to (a) help understand and explain the contextual factors, diagnostic processes and counseling outcomes associated with the diagnosis of ODD in African American males, and (b) identify, describe, and make meaning of patterns and trends in mental health care systems that may be associated with the apparent overdiagnosis of African American boys with ODD. A consensual qualitative research (CQR) design was employed in this study to identify, describe and make meaning of the diagnostic processes and outcomes related to ODD. The following components of CQR identified by Hill et al. (2005) were used in this study: (a) open-ended questions in semistructured interviews “to allow for the collection of consistent data across individuals, as well as more in-depth examination of individual experiences,” (b) research team collaboration (i.e., two judges and one auditor) throughout the data analysis process for multiple perspectives, (c) “consensus to arrive at the meaning of the data,” (d) an auditor to check the work of the two judges; and (e) “domains, core ideas, and cross-analyses in the data analysis” (p. 196).

Research Team

The research team included a counselor educator and licensed psychologist (African American male, age 42), counselor educator and licensed professional counselor (White American female, age 36), three clinical mental health graduate students (African American female, age 23; White American female, age 28; White American male, age 29) and one public administration graduate student (African American female, 34). All research team members had clinical experience (i.e., as mental health counselors, research and counseling interns, or parents of clients receiving counseling) with African American males who have been diagnosed with ODD. Training to conduct the study involved reading and discussing [Hill, Knox, Thompson, Williams, Hess, & Ladany, 2005; Hill, Thompson, & Williams, 1997]; attending in-person research team meetings to discuss, design, plan and implement the research study; and electronic communication throughout the process. Feelings and reactions (i.e., biases) related to the study were openly discussed among the research team throughout the process to minimize influences on data analysis. Research team biases included: (a) awareness of apparent disproportionality of ODD diagnosis in African American males compared to other populations, based on clinical experience, (b) potential low multicultural competence of counselors making diagnoses, and (c) difficulties for African American males with an ODD diagnosis.

Participants

Six mental health professionals met the following criteria for participation in this study: (a) the ability to verbally describe and explain the diagnostic criteria for ODD (during the interview for data collection), (b) a minimum of 2 years’ clinical experience working with clients who have ODD as demonstrated by professional resume or curriculum vitae and explanation at the interview, and (c) a professional mental health license.

The sample consisted of diverse practitioners in identity, years of experience, professional position and places of employment. Racial/ethnic and gender identities of participants were: African American female, African American male, multiracial Arab American female, White American female (n = 2), and White American male. Participant ages ranged from: (a) 30–35 years (n = 2), (b) 35–40 years (n = 2) and (c) over 40 years (n = 2). Reported mental health licenses included: licensed professional counselor associate (n = 1), licensed professional counselor (n = 2), licensed professional counselor supervisor (n = 1), licensed clinical social worker (n = 1) and licensed psychological associate (n = 1). Years holding licensure ranged from less than one to greater than 15. The majority of participants described their professional position as a clinical supervisor and mental health counselor (n = 3), with others identifying as mental health counselors (n = 2) and multisystemic therapy program supervisor (n = 1). All participants reported working within a private organization, with two participants employed by a for-profit community mental health agency, three participants by a non-profit community mental health agency and one participant in private practice.

Procedure

The Institutional Review Board for the Use of Human Subjects in Research evaluated and approved the study. Participant recruitment involved purposeful sampling of mental health providers from local Critical Access Behavioral Health Agencies likely to meet participant criteria. Research team members contacted 10 potential participants by e-mail and follow-up phone calls to explain the study and ask for their participation. Once eligibility had been determined based on selection criteria, six mental health professionals were selected to create an intentionally diverse sample. Participants scheduled an in-person appointment to complete the informed consent process with a team member, signed the form indicating understanding and agreement to participate in the study, and engaged in an in-depth interview lasting 1 to 1.5 hours, at the office of the participants or the first author. Codes and pseudonyms protected confidential participant information and data was audio-recorded and transcribed for each interview.

Measures

Semi-structured interviews. Interview questions for the study were based on a literature review, an evaluation of the DSM-5 (APA, 2013) criteria for ODD, and pilot field interviews with mental health professionals, clients, and clinical directors experienced in providing or receiving services related to ODD. Participants were asked 12 initial questions about the process of making an ODD diagnosis for African American male clients that focused on: life circumstances that contributed to an ODD diagnosis; structural and cultural factors related to diagnosis (e.g., What are the social systems involved in the diagnosis?); post-diagnosis outcomes and implications (e.g., What happens after a client receives the diagnosis?); and treatment plan considerations (e.g., What are the benefits and/or problems of the treatment plan?).

Data Analysis

Data were analyzed using CQR beginning with a start domain list created from the initial interview questions and transcript of the first interview, where all research team members coded first interview data into domains, “topics used to group or cluster data” (Hill et al., 2005, p. 200). Next, core ideas, “summaries of the data that capture the essence of what was said in fewer words with greater clarity,” from each domain were recorded using direct quotes from participants (Hill et al., 2005, p. 200). Cross-analysis was then completed to characterize the frequency of the data: “general applies to all or all but one case; typical applies to more than half up to cutoff for general; and variant applies to two cases up to the cutoff for typical” (Hill et al., 2005, p. 203). Finally, one team member acted as the auditor and provided feedback throughout the analysis process, and most importantly, ensured “that all important material has been faithfully represented in the core ideas, that the wording of the core ideas succinctly captures the essence of the raw data, and that the cross-analysis elegantly and faithfully represents the data” (Hill et al., p. 201).

The consensus process commenced in the collaborative team design and implementation of the study and proceeded with the independent analysis of the data by the coders and auditor. Domains, core ideas and cross-analyses were then presented, discussed, debated and confirmed during in-person research team meetings, by e-mail and video conferencing. A multilayered consensus process over time contributed to the stability of the data for trustworthiness, along with: (a) consistency and documentation of data collection procedures, (b) research team description and positionality statement, (c) providing quotes that capture core ideas, and (d) using a research team of coders and an auditor to analyze data. No cases were withheld from the initial cross-analysis for the stability check of the data, as Hill et al. (2005) found it is not necessary. Rather, Hill et al. (2005) suggested presenting “evidence of trustworthiness in conducting data analysis,” as described (p. 202).

Findings

Four domains were identified related to diagnosing ODD. Categories further define each domain, supported by core ideas using direct quotes from the participants. Table 1 shows the frequency of categories within each of the domains. Hill et al. (1997) outlined the following categories: general if it applies to all (6), typical if it applies to half or more (3–5), and variant if it applies to less than half of the participants (2 up to typical; all categories applied to at least half of the participants; therefore, none were variant).

Insurance Influence

Most insurance companies require counselors to diagnose clients with a mental disorder in order to obtain payment for mental health services (Kautz, Mauch, & Smith, 2008). Many insurance companies require that a diagnosis be made during the first few counseling sessions, sometimes within the very first counseling session. All participants described the role and influence of insurance companies and managed care in the diagnostic process. One participant expressed, “the diagnosis is necessary to get paid, so you have to find something. You are not looking objectively. You are just giving them a diagnosis.” The participant continued:

We see this proportion of diagnoses [with African American males] because the insurance in managed care world drives agencies like this one and drives providers to say that an [African American] child is diagnosed a particular way . . . There is this incentive to diagnose and to diagnose in a short period of time.

Table 1Summary of Domains From the Cross-Analysis of the Participants (N = 6)
Domain and Category	Frequency

Insurance influence
Diagnosis required for payment of services	General
Reimbursement likelihood drives the type of diagnosis given	General
Insufficient assessment time allotted for proper diagnosis	General
Oppositional defiant disorder diagnostic criteria
Criteria are too general	General
Criteria provide a convenient catch-all for providers	General
Oppositional defiant disorder is stigmatized
African American males	Typical
Long-term negative implications	Typical
Assessment, diagnosis and treatment
Family, community and other contextual considerations	General
Mental health counselor bias	Typical
Cultural and contextual integration	Typical

Findings suggested that the assessment time allotted by insurance companies to diagnose a mental disorder undermines the diagnostic process and invalidates the diagnosis. One participant emphasized, “the client is not going to open up to you within that time frame; this is the first time the child is ever seeing you. Those types of things progress over time.” Further structural and systemic assessment problems also were identified by another participant:

You’re allowed to do one assessment per year for the client . . . The assessor would take the previous assessment, use a majority of that information, and then just ask what has changed between then and now . . . there [are] a lot of questions that the previous assessment didn’t answer or didn’t really look into. So that piece gets missed.

Oppositional Defiant Disorder Diagnostic Criteria

The DSM-5 criteria for ODD are too general, providing a convenient catch-all for providers. Symptoms of ODD align with typical child and adolescent behavior as well as other childhood disorders (e.g., ADHD), adjustment disorder, depression and anxiety, depending on developmental context (APA, 2013). Every participant expressed the relative malleability of the ODD criteria. “It’s an easy diagnosis for most people to fit into that category, if they’re having trouble with the legal system and there’s nothing else going on,” noted one participant. Another added that ODD “serves as a holding cell for behaviors that are not understood.” Finally, one mental health counselor stated:
There are no differentials for ODD. It’s all under this blurry category of disruptive behaviors. On one hand it looks easy to diagnose, but on the other hand it’s very complicated when you are not ethically doing the right thing.

Oppositional Defiant Disorder Is Stigmatized

An ODD diagnosis carries negative social weight and judgment within and beyond the mental health fields. African American males are particularly vulnerable to diagnostic stigmatization due to multiple marginalizations that can occur when intersecting with other forms of oppression, such as racism (Arrendondo, 1999; Ratts et al., 2015). Most participants referenced long-term negative implications for these clients, including, “I think it leaves a permanent scar, with elementary kids all the way up.” One participant expressed further that:

I have had kids that have been diagnosed with [ODD] and they drop out. I have had young African American boys in my office and they say ‘You know this has been going on with me since I was a kid?’ And you know that they are telling the truth. They ask themselves, ‘Why am I still in school?’ So they drop out.

Another mental health counselor added:

I see it when we go to court even [with] an African American judge. African American boys would typically get a harsher sentence. It’s a systemic issue. We just start viewing through a lens and we automatically have an assumption to what the problem is. We have a negative interpretation of one kid’s actions versus another.

Assessment, Diagnosis and Treatment

Assessment, diagnosis and treatment do not account for family, community and other contextual problems affecting the client’s mood and behavior. One mental health counselor explained, “if the parent has been incarcerated, they are going to act out. If they are dealing with a domestic violence situation in their home, this is a way of relieving stress for them.” Another participant added:

We leave the whole family out of this process . . . That may be where the problems exist. It is person centered to a fault. To the neglect of it being family centered versus person centered or being both, because you would dare not want to intervene with a child and not involve family. Despite [that] the parents will come and say, 95% of the time, ‘I am okay—you need to fix my son or daughter.’ When treatment plans get tailored based on that premise, then everybody is in trouble.

Trauma also was identified as a contextual issue that warrants consideration in the diagnostic process.

Past trauma, living in very difficult situations, near or below poverty are not taken into account. What might be very adaptive behaviors for a kid, or might be situational dependent, are then just translated into the diagnosis.

Participants acknowledged mental health counselor bias plays a role in diagnosis as well. A mental health counselor may have a tendency to diagnose certain clients with ODD because it is a familiar and commonly used diagnosis. One mental health counselor stated, “a lot of times, particularly with new clinicians, [ODD] is a buzz word . . . like ADD was a buzz word years ago.” A different participant shared the diagnostic rationale, “it helps them, too, because it’s a relatively non-offensive diagnosis. It’s not as personal a diagnosis, so they don’t feel as bad being diagnosed oppositional defiant disorder as they would something else.”

The relative cultural competency of practitioners also was referenced by participants as potentially compromising the diagnostic process, with one indicating that:

When I think about oversight and training, it’s limited in terms of how much exposure they’ve had to diversity training or multiculturalism. What might present as disrespect or non-compliance might be very culturally appropriate . . . The assumption is made that these things are all dysfunctional for the individual as opposed to other contextual factors that are going on.

Discussion

The purpose of this study was to understand the diagnostic processes and implications associated with ODD. Findings suggest that a diagnosis of ODD can result from more factors than client symptoms fitting the diagnostic criteria. While none of the research or interview questions asked specifically about the role of insurance or managed care, every participant indicated that third party billing influenced the diagnostic process.

Specifically, the mental health counselors interviewed were keenly aware of the necessity of making a diagnosis for insurance reimbursement. It appeared that ODD is considered a reliable diagnosis for billing purposes; however, diagnostic necessity may also create an ethical dilemma for mental health counselors who want to provide quality care and need to earn a living. The possibility of racial diagnostic bias remains, even with insurance requirements, when African Americans are more likely to receive a diagnosis of ODD, while White Americans presenting with similar symptoms receive a diagnosis of adjustment disorder (Feisthamel & Schwartz, 2009; Schwartz & Feisthamel, 2009).

Professional ethical standards and best practices warrant full consideration of a diagnosis, including the purpose served and implications, as related to the health and well-being of clients (American Counseling Association [ACA], 2014). Even when a diagnosis is not warranted or conflicts with theoretical, philosophical or therapeutic approaches, mental health providers serving clients who do not pay cash for services are forced to accommodate diagnostic requirements. The use of a diagnosis as a therapeutic tool, designed to act in concert with others, has also come to serve as the gateway to mental health care services.

In the case of African American male clients, an ODD diagnosis can be particularly stigmatizing with immediate and long-term implications for marginalization and tracking (Cossu et al., 2015). Educational, judicial and incarceration data clearly demonstrate that African American males are disproportionately suspended and expelled from school compared to their peers (U.S. Department of Education Office for Civil Rights, 2014); receive harsher sentences in judicial systems for the same offenses as other defendants (Ghandnoosh, 2014; Rehavi & Starr, 2012); and are more likely to be stopped, searched, assaulted and killed by police officers than other community members (Gabrielson, Jones, & Sagara, 2014; Weatherspoon, 2004). Since ODD is categorized as a disruptive behavior disorder, it may be considered, intentionally or unintentionally, a justification, rationale or explanation for these disparate outcomes. When the diagnosis of a mental disorder is used for purposes other than helping the client, it opens the door to unintended and problematic consequences.

The assessment process is critical to making an accurate diagnosis and should not be limited to the most readily available, convenient or confirmatory information. With ODD, alternative, viable explanations for client symptoms have to be considered that may include family history and dynamics, personal trauma and social–cultural context. Guindon and Sobhany (2001) noted, “often there are discrepancies between the counselor’s perception of their clients’ mental health problems and those of the clients themselves” (p. 277). Again, there may be a tendency to diagnose African American males with perceived behavioral problems with ODD without full consideration of historical and contextual variables that may better explain mood and behavior and warrant a different diagnosis altogether (Hays et al., 2010).

Mental health counselors also have certain biases, within and beyond personal awareness, that create diagnostic tendencies, which may undermine the diagnostic process and invalidate the results of the assessment. Assessment practices and structures appear to accommodate intrinsic and individual information, more so than extrinsic and systemic variables (Hays et al., 2010). For these reasons, the gathering of client information for diagnostic purposes must be as comprehensive and inclusive as possible, notwithstanding measures to limit mental health counselor bias, such as supervision and consultation.

The ACA Code of Ethics outlines the need for even the most experienced counselors to seek supervision and consultation when necessary (ACA, 2014). One potential blind spot for many counselors experiencing bias toward African American male clients is not realizing the need for supervision and consultation when it arises. Understanding that ODD diagnoses within the African American male community have been shown to be inflated is a first step toward decreasing counselor bias. Second, recognizing the subjective nature of making an ODD diagnosis, especially since many of the behaviors and emotions listed as diagnostic criteria also “occur commonly in normally developing children and adolescents” (APA, 2013, p. 15) is another critical aspect of ensuring accurate diagnoses are made.

Counselors are trained from a multimodal approach to diagnosis based on Western medicine; therefore, diagnosing clients is a culturally-based practice (Sue & Sue, 2015). Furthermore, most research in the area of mental and behavioral health has, in large part, not included people of color (U.S. Department of Health and Human Services, 2001). Cultural discrepancies also are evident in the demographic characteristics represented within the counseling profession. Approximately 71% of counselors in the United States are women, and only 18.4% of counselors identify as Black or African American (U.S. Department of Labor, 2015); therefore, most African American male clients will likely have different cultural backgrounds from their counselors. These factors create a need for consultation and supervision to ensure that the personal and professional worldviews of counselors are not inhibiting accurate diagnosis and treatment planning for African American male clients.

In addition to supervision, another measure to limit counselor bias would be to practice reflective cultural auditing, a 13-step process for walking counselors through how culture may impact their work with clients from initial meeting through termination and follow-up. This process allows counselors to reflect on what may seem like client resistance, but may instead be a “disruption in the working alliance” (Collins, Arthur, & Wong-Wylie, 2010, p. 345) based on cultural differences. In addition to utilizing reflective audits of individual cases, it also can be helpful for counselors to review case files regularly, taking into account race and ethnic background, along with symptoms and reported diagnosis. Finding diagnostic patterns within one’s own practice can help counselors reflect on their clinical work and identify areas of bias that may exist.

Implications for Professional Counselors

Thinking through the diagnostic process and beyond the diagnosis requires the mental health counselor to consider and balance the needs of the client, provision of ethical and effective mental health services, expectations and requirements of employers, and earning a living. The following recommendations are offered to help mental health professionals balance these diagnostic considerations in light of current findings, particularly in the assessment and diagnosis of ODD.

In order to make an accurate diagnosis, billing considerations should not be a determining factor in the assessment process. We acknowledge that payment for services is a necessary component for earning a living as a mental health counselor; at the same time, there is an inherent conflict of interest between ethical diagnostic practices and billing when they are not considered as separate processes. Counselors can reference the ACA Code of Ethics (2014) regarding cultural sensitivity (Section E.5.b) as well as historical and social prejudices in the diagnosis of pathology (Section E.5.c). Additionally, counselors may reference the guidelines for informed consent in the counseling relationship (Section A.2.b), ensuring that clients are aware of how information in their client records will be used and how it may impact clients in the future. When appropriate, counselors may choose a less stigmatizing diagnosis initially (e.g., adjustment disorder), while continuing to learn more about a client’s context and cultural background before making a final diagnosis.

Consider extrinsic and external factors that may contribute to emotional and behavioral symptoms presented. It is important to keep in mind that a pattern of ODD behavior includes anger and irritability, argumentative and defiant behavior, and/or vindictiveness, which causes significant problems at work, school or home, and lasts at least 6 months. In order to qualify as ODD symptoms, these behaviors must occur with at least one person who is not a sibling, and must occur on their own (i.e., not as part of another mental health problem, such as depression, anxiety, antisocial behavior and substance abuse disorders). If family history and dynamics, personal trauma and community/contextual factors contribute to any of the above systems, a diagnosis of ODD may not be the most accurate, thereby leading to ineffective, if not harmful treatment plans and outcomes. A diagnosis of adjustment disorder may be more beneficial to ensure that the client receives adequate treatment, which would hopefully increase the client’s chances of having a positive counseling outcome.

African American males are diagnosed with ODD at a disproportionately higher rate than other social demographic groups (Feisthamel & Schwartz, 2009). Ethical and best practice standards require mental health professionals to understand personal biases that might inform their work as well as to develop strategies to reduce or eliminate negative impact (ACA, 2014; Ratts et al., 2015; Sue et al., 1992). In addition, mental health counselors need to use continuing education to remain aware of current trends in the field relevant to the populations they serve (ACA, 2014; Ratts et al., 2015). Health professionals should adhere to diagnostic criteria and integrate multicultural counseling competencies in order to avoid making decisions based on pre-defined misconceptions.

Implications for Counselor Educators and Supervisors

Included in the Council for Accreditation of Counseling and Related Educational Programs (CACREP) accreditation standards is the responsibility of counselor education programs to train students on “the effects of power and privilege for counselors and clients” (CACREP, 2016, p. 9). It is imperative that counselor educators provide specific training on racial bias among counselors, which often is automatic and hidden from conscious awareness (Abreu, 2001).

Creating a safe, comfortable, respectful classroom environment in which students are able to honestly self-reflect and ask questions is necessary to integrate and infuse multicultural and social justice counseling competence training within counselor education programs (Ratts et al., 2015). Counselors-in-training need the opportunity to think critically and experience cognitive dissonance in the classroom regarding ways African American males are portrayed and the erroneous assumptions often made by authority figures and institutions of power. In turn, counselors need to be aware of how these portrayals and assumptions potentially impact the mental health services African American males receive.

In addition to didactic teaching, experiential exercises also are critical for meaningful learning to take place (Sue & Sue, 2015). Assignments that illustrate personal and systemic prejudice can help students reflect on their own potential biases as well as build awareness of systemic influences that may impact clients of color in ways counselors-in-training previously had not considered. Reading assignments that illustrate common biases among counselors can normalize the phenomenon in ways that facilitate student openness to learning and self-reflection. In addition, using diverse theories when discussing diagnosis and treatment planning can ensure multiple perspectives are acknowledged, including the perspective that diagnoses can be both helpful and harmful to clients. Counselor educators have a responsibility to ensure students graduate with an awareness of the need to constantly monitor their own biases and prejudices toward African American males, as well as knowing when to seek supervision and consultation.

Finally, counselor educators can implement a multicultural competence approach to teaching clinical assessment and diagnosis. Guindon and Sobhany (2001) offered a conceptual framework that can be utilized in the classroom in order to achieve this goal: (a) obtain a specific and complete understanding of the client’s chief complaint, (b) be aware of discrepancies in counselor and client perceptions of clinical reality, (c) elicit clients’ clinical realities and explain counselor clinical models, (d) engage in active negotiation with the client as a therapeutic ally, (e) recognize the importance of renegotiation (of perception of presenting problem), and (f) use assessment instruments advisedly and with caution. The authors intended for this framework to be used by “counselors from any cultural background [to] assist those who are not like themselves” (Guindon & Sobhany, 2001, p. 279).

Limitations of the Study

The CQR model allowed the research team to independently and collaboratively analyze the data through a deliberate, thorough and comprehensive process over time to understand the meanings. Multiple perspectives and the relational dynamic within our team helped to check our own biases and to clearly grasp the view of our participants. The findings of this study represent an in-depth analysis of the perspectives of six licensed mental health professionals with experience diagnosing and working with clients who are diagnosed with ODD that may apply to some degree to working with similar populations and contexts. Life and professional experiences of the researchers and participants, however, naturally interact and influence our understandings of the meanings of the data. As such, different combinations of research team members, participants, or contexts could reveal similar, additional or different findings in a similar study. Finally, two graduate student members of the initial research team graduated before data analysis commenced; therefore, we had fewer coders than originally planned. Additional coders would have provided other perspectives on the data and may have further enhanced the meaning-making process.

Conclusion and Future Research

A mental health diagnosis such as ODD has destructive potential when not used properly. Professional counselors, then, have social power in their capacity to diagnose a client with a mental disorder (APA, 2013; Prilleltensky, 2008). Such power requires that counselors cultivate awareness of personal and professional biases that may influence the diagnostic process. Factors driving the diagnostic process extend beyond the mental health needs of the client and can play a critical role in assessment. Contextual explanations, including historic and systemic contexts, must be considered before a diagnosis is given. Attending to the role of counselor bias to prevent overdiagnosis is an ethical responsibility for which counselor educators and practicing counselors must hold themselves accountable.

Additional research is needed to consider whether the diagnosis–billing model is the most optimal and ethical for mental health care, particularly for preventive mental health and for African American male clients and other marginalized populations. Further study also is warranted to capture the long-term implications of an ODD diagnosis, including identifying ways in which a client‘s family can advocate for school and community resources (e.g., outpatient counseling, mentoring programs, support groups). Finally, possible relationships between an ODD diagnosis, school discipline practices and crime adjudication with marginalized groups (e.g., African American males) should be explored, given the drop-out-of-school-to-prison pipeline that is now widely recognized as a reality for many African American males (Barbarin, 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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Marc A. Grimmett is an Associate Professor at North Carolina State University. Adria S. Dunbar is an Assistant Professor at North Carolina State University. Teshanee Williams and Cory Clark are doctoral students at North Carolina State University. Brittany Prioleau and Jen S. Miller are licensed professional counselors. Correspondence can be addressed to Marc. A. Grimmett, Campus Box 7801, Raleigh, NC 27695-7801, marc_grimmett@ncsu.edu.

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

Jul 14, 2016 | Article, Volume 6 - Issue 2

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

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

Supervision in Counselor Education Coursework

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

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

Counselor Self-Efficacy

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

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

Purpose of Study

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

Methodology

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

Participant Characteristics

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

Instrumentation

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

Treatment

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

Procedure

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

Data Collection and Analysis

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

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

Results

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

Participant 1

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

Participant 2

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

Participant 3

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

Figure 1.

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

Table 1

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

Participant 4

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

Participant 5

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

Participant 6

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

Participant 7

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

Participant 8

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

Participant 9

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

Participant 10

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

Participant 11

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

Discussion

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

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

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

Implications for Counseling Practice

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

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

Implications for Counseling Research

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

Limitations

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

Conclusion

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

Conflict of Interest and Funding Disclosure

The authors reported no conflict of interest

or funding contributions for the development

of this manuscript.

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

An Exploration of Career Counselors’ Perspectives on Advocacy

May 20, 2016 | Article, Volume 6 - Issue 2

Melissa J. Fickling

Advocacy with and on behalf of clients is a major way in which counselors fulfill their core professional value of promoting social justice. Career counselors have a unique vantage point regarding social justice due to the economic and social nature of work and can offer useful insights. Q methodology is a mixed methodology that was used to capture the perspectives of 19 career counselors regarding the relative importance of advocacy interventions. A two-factor solution was reached that accounted for 60% of the variance in perspectives on advocacy behaviors. One factor, labeled focus on clients, emphasized the importance of empowering individual clients and teaching self-advocacy. Another factor, labeled focus on multiple roles, highlighted the variety of skills and interventions career counselors use in their work. Interview data revealed that participants desired additional conversations and counselor training concerning advocacy.

Keywords: social justice, advocacy, career counselors, Q methodology, counselor training

The terms advocacy and social justice often are used without clear distinction. Advocacy is the active component of a social justice paradigm. It is a direct intervention or action and is the primary expression of social justice work (Fickling & Gonzalez, 2016; Ratts, Lewis, & Toporek, 2010; Toporek, Lewis, & Crethar, 2009). Despite the fact that counselors have more tools than ever to help them develop advocacy and social justice competence, such as the ACA Advocacy Competencies (Lewis, Arnold, House, & Toporek, 2002) and the Multicultural and Social Justice Counseling Competencies (Ratts, Singh, Nassar-McMillan, Butler, & McCullough, 2015), little is known about practitioners’ perspectives on the use of advocacy interventions.

One life domain in which social inequity can be vividly observed is that of work. The economic recession that began in 2007 has had a lasting impact on the labor market in the United States. Long-term unemployment is still worse than before the recession (Bureau of Labor Statistics, U.S. Department of Labor, 2016a). Further, in the United States, racial bias appears to impact workers and job seekers, as evidenced in part by the fact that the unemployment rate for Black workers is consistently about double that of White workers (e.g., 4.1% White unemployment and 8.2% Black unemployment as of May 2016; Bureau of Labor Statistics, U.S. Department of Labor, 2016b). Recent meta-analyses indicate that unemployment has a direct and causal negative impact on mental health, leading to greater rates of depression and suicide (Milner, Page, & LaMontagne, 2013; Paul & Moser, 2009). Clearly, the worker role is one that carries significant meaning and consequences for people who work or want to work (Blustein, 2006).

The rate at which the work world continues to change has led some to argue that worker adaptability is a key 21st century skill (Niles, Amundson, & Neault, 2010; Savickas, 1997), but encouraging clients to adapt to unjust conditions without also acknowledging the role of unequal social structures is inconsistent with a social justice paradigm (Stead & Perry, 2012). Career counselors, particularly those who work with the long-term unemployed and underemployed, witness the economic and psychological impact of unfair social arrangements on individuals, families and communities. In turn, they have a unique vantage point when it comes to social justice and a significant platform from which to advocate (Chope, 2010; Herr & Niles, 1998; Pope, Briddick, & Wilson, 2013; Pope & Pangelinan, 2010; Prilleltensky & Stead, 2012).

It appears that although career counselors value social justice and are aware of the effects of injustice on clients’ lives, they are acting primarily at the individual rather than the systemic level (Cook, Heppner, & O’Brien, 2005; McMahon, Arthur, & Collins, 2008b; Prilleltensky & Stead, 2012; Sampson, Dozier, & Colvin, 2011). Some research has emerged that focuses on practitioners’ use of advocacy in counseling practice (Arthur, Collins, Marshall, & McMahon, 2013; Arthur, Collins, McMahon, & Marshall, 2009; McMahon et al., 2008b; Singh, Urbano, Haston, & McMahan, 2010). Overall, this research indicates that advocacy is challenging and multifaceted and is viewed as a central component of good counseling work; however, more research is needed if we are to fully understand how valuing social justice translates to use of advocacy interventions in career counseling practice. This study aims to fill this theory–practice gap by illuminating the perceptions of advocacy behaviors from career counselors as they reflect upon their own counseling work.

Methodology

Through the use of Q methodology, insight into the decisions, motivations and thought processes of participants can be obtained by capturing their subjective points of view. When considering whether to undertake a Q study, Watts and Stenner (2012) encouraged researchers to consider whether revealing what a population thinks about an issue really matters and can make a real difference. Given the ongoing inequality in the labor market, increased attention and energy around matters of social justice in the counseling profession, the lack of knowledge regarding practitioners’ points of view on advocacy, and career counselors’ proximity to social and economic concerns of clients, the answer for the present study is most certainly yes.

Q methodology is fundamentally different from other quantitative research methodologies in the social sciences. It uses both quantitative and qualitative data to construct narratives of distinct perspectives. The term Q was coined to distinguish this methodology from R; Q measures correlations between persons, whereas R measures trait correlations (Brown, 1980). Rather than subjecting a sample of research participants to a collection of measures as in R methodology, Q methodology subjects a sample of items (i.e., the Q sample) to measurement by a collection of individuals through a ranking procedure known as the Q sort (see Figure 1; Watts & Stenner, 2012). Individuals are the variables in Q methodology, and factor analysis is used to reduce the number of points of view into a smaller number of shared perspectives. Then interviews are conducted to allow participants to provide additional data regarding their rankings of the Q sample items. In this study, career counselors were asked to sort a set of advocacy behaviors according to how important they were to their everyday practice of career counseling. Importance to practice was used as the measure of psychological significance since career counselors’ perspectives on advocacy interventions were of interest, rather than self-reported frequency or competence, for example.

Q Sample

The Q sample can be considered the instrumentation in Q methodology. The Q sample is a subset of statements drawn from the concourse of communication, which is defined as the entire population of statements about any given topic (McKeown & Thomas, 2013). The goal when creating the Q sample is to provide a comprehensive but manageable representation of the concourse from which it is taken. For this study, the concourse was that of counselor advocacy behaviors.

The Q sampling approach used for this study was indirect, naturalistic and structured-inductive. Researchers should draw their Q sample from a population of 100 to 300 statements (Webler, Danielson, & Tuler, 2009). For this study, I compiled a list of 180 counselor social justice and advocacy behaviors from a variety of sources including the ACA Advocacy Competencies (Lewis et al., 2002), the Social Justice Advocacy Scale (SJAS; Dean, 2009), the National Career Development Association (NCDA) Minimum Competencies (2009), the Council for Accreditation of Counseling and Related Educational Programs (CACREP) Standards (2009), and key articles in counseling scholarly and trade publications.

Consistent with a structured-inductive sampling strategy, these 180 statements were analyzed to identify categories representing different kinds of advocacy behaviors. By removing duplicates and those items that were more aligned with awareness, knowledge or skill rather than behavior, I was able to narrow the list from 180 to 43 statements. These statements were sorted into five domains that were aligned with the four scales of the SJAS (Dean, 2009) and a fifth added domain. The final domains were: Client Empowerment, Collaborative Action, Community Advocacy, Social/Political Advocacy, and Advocacy with Other Professionals. Aligning the Q sample with existing domains was appropriate since advocacy had been previously operationalized in the counseling literature.

Expert reviewers were used to check for researcher bias in the construction of the Q sample, including the addition of the fifth advocacy domain. Three expert reviewers who were faculty members and published on the topic of social justice in career counseling were asked to review the potential Q sample for breadth, coverage, omissions, clarity of phrasing and the appropriateness of the five domains of advocacy. Two agreed to participate and offered their feedback via a Qualtrics survey, leading to a refined Q sample of 25 counselor advocacy behaviors (see Table 1). Five statements were retained in each of the five domains. Finally, the Q sample and Q sorting procedure were piloted with two career counselors, leading to changes in instructions but not in the Q sample itself. Pilot data were not used in the final analysis.

Participants

In Q methodology, participant sampling should be theoretical and include the intentional selection of participants who are likely to have an opinion about the topic of interest (McKeown & Thomas, 2013; Watts & Stenner, 2012). It also is important to invite participants who represent a range of viewpoints and who are demographically diverse. For the current study, the following criteria were required for participant inclusion: (a) holds a master’s degree or higher in counseling and (b) has worked as a career counselor for at least one year full-time in the past two years. For this study, career counselor was defined as having career- or work-related issues as the primary focus of counseling in at least half of the counselor’s case load. Regarding the number of participants in a Q study, emphasis is placed on having enough participants to establish the existence of particular viewpoints, not simply having a large sample since generalizability is not a goal of Q methodology (Brown, 1980). In Q methodology, it also is important to have fewer participants than Q sample items (Watts & Stenner, 2012; Webler et al., 2009).

Participants were recruited by theoretical sampling of my professional network of practitioners, and one participant was recruited through snowball sampling. Nineteen career counselors participated in the present study from six states in the Southeast, West and Midwest regions of the United States. The participant sample was 68% female (n = 13) and 32% male (n = 6); the sample was 84% White and included two Black participants and one multi-racial participant. One participant was an immigrant to the United States and was a non-native English speaker. The participant sample was 95% heterosexual with one participant identifying as gay. Sixty-three percent of participants worked in four-year institutions of higher education and one worked in a community college. Thirty-two percent (n = 6) provided career counseling in non-profit agencies. The average age was 43 (SD = 12) and the average number of years of post-master’s counseling experience was eight (SD = 7); ages ranged from 28 to 66, and years of post-master’s experience ranged from one and a half to 31 years.

Q Sorting Procedure

The Q sort is a method of data collection in which participants rank the Q sample statements according to a condition of instruction along a forced quasi-normal distribution (see Figure 1). There is no time limit to the sorting task and participants are able to move the statements around the distribution until they are satisfied with their final configuration. The function of the forced distribution is to encourage active decision making and comparison of the Q sample items to one another (Brown, 1980).

Figure 1

Sample Q Sort Distribution

The condition of instruction for this study was, “Sort the following counselor advocacy behaviors according to how important or unimportant they are to your career counseling work.” The two poles of the distribution were most important and most unimportant. Poles range from most to most so that the ends of the distribution represent the areas that hold the greatest degree of psychological significance to the participant, and the middle of the distribution represents items that hold relatively little meaning or are more neutral in importance (Watts & Stenner, 2012).

The Q sorts for this study were conducted both in person and via phone or video chat (i.e., Google Hangouts, Skype). Once informed consent was obtained, I facilitated the Q sorting procedure by reading the condition of instruction, observing the sorting process, and conducting the post-sort interview. Once each participant felt satisfied with his or her sort, the distribution of statements was recorded onto a response sheet for later data entry.

Post-Sort Interview

Immediately following the Q sort, I conducted a semistructured interview with each participant in order to gain a greater understanding of the meaning of the items and their placement, as well as his or her broader understanding of the topic at hand (Watts & Stenner, 2012). The information gathered during the interview is used when interpreting the final emergent factors. Items in the middle of the distribution are not neglected and are specifically asked about during the post-sort interview so that the researcher can gain an understanding of the entire Q sort for each participant. Although the interview data are crucial to a complete and rigorous factor interpretation and should be conducted with every participant in every Q study, the data analysis process is guided by the quantitative criteria for factor analysis and factor extraction. The qualitative interview data, as well as the demographic data, are meant to help the researcher better understand the results of the quantitative analysis.

Data Analysis

Data were entered into the PQMethod program (Schmolck, 2014) and Pearson product moment correlations were calculated for each set of Q sorts. Inspection of the correlation matrix revealed that all sorts (i.e., all participants) were positively correlated with one another, some of them significantly so. This indicated a high degree of consensus among the participants regarding the role of advocacy in career counseling, which was further explored through factor analysis.

I used centroid factor analysis and Watts and Stenner’s (2012) recommendation of beginning by extracting one factor for every six Q sorts. Centroid factor analysis is the method of choice among Q methodologists because it allows for a fuller exploration of the data than a principal components analysis (McKeown & Thomas, 2013; Watts & Stenner, 2012). Next, I calculated the significance level at p < .01, which was .516 for this 25-item Q sample.

The unrotated factor matrix revealed two factors with Eigenvalues near or above the commonly accepted cutoff of 1 according to the Kaiser-Guttman rule (Kaiser, 1970). Brown (1978) argued that although Eigenvalues often indicate factor strength or importance, they should not solely guide factor extraction in Q methodology since “the significance of Q factors is not defined objectively (i.e., statistically), but theoretically in terms of the social-psychological situation to which the emergent factors are functionally related” (p. 118). Since there currently is little empirical evidence of differing perspectives on advocacy among career counselors, two factors were retained for rotation.

In order to gain another perspective on the data, I used the Varimax procedure. I flagged those sorts that loaded significantly (i.e., at or above 0.516) onto only one factor after rotation. Four participants (2, 8, 9 and 17) loaded significantly onto both rotated factors and were therefore dropped from the study and excluded from further analysis (Brown, 1980; Watts & Stenner, 2012). Two rotated factors were retained, which accounted for 60% of the variance in perspectives on advocacy behaviors. Fifteen of the original 19 participants were retained in this factor solution.

Q methodology uses only orthogonal rotation techniques, meaning that all factors are zero-correlated. Even so, it is possible for factors to be significantly correlated but still justify retaining separate factors (Watts & Stenner, 2012). The two factors in this study are correlated at 0.71. This correlation indicates that the perspectives expressed by the two factor arrays share a point of view but are still distinguishable and worthy of exploration as long as the general degree of consensus is kept in mind (Watts & Stenner, 2012).

Constructing Factor Arrays

After the two rotated factors were identified, factor arrays were constructed in PQMethod. A factor array is a composite Q sort and the best possible estimate of the factor’s viewpoint using the 25 Q sample items. First, a factor weight was calculated for each of the 15 Q sorts that loaded onto a factor. Next, normalized factor scores (z scores) were calculated for each statement on each factor, which were finally converted into factor arrays (see Table 1). In Q methodology, unlike traditional factor analysis, attention is focused more on factor scores than factor loadings. Since factor scores are based on weighted averages, Q sorts with higher factor loadings contribute proportionally more to the final factor score for each item in a factor than those with relatively low factor loadings. Finally, factors were named by examining the distinguishing statements and interview data of participants that loaded onto the respective factors. Factor one was labeled focus on clients and factor two was labeled focus on multiple roles.

Factor Characteristics

Factor one was labeled focus on clients and accounted for 32% of the variance in perspectives on advocacy behaviors. It included nine participants. The demographic breakdown on this factor was: six females, three males; eight White individuals and one person who identified as multi-racial. The average age on this factor was about 51 (SD = 10.33), ranging from 37 to 66. Persons on this factor had on average 11 years of post-master’s counseling experience (SD = 8.6), ranging from one and a half to 31 years. Fifty-six percent of participants on this factor worked in 4-year colleges or universities, 33% in non-profit agencies, and one person worked at a community college.

Factor two was labeled focus on multiple roles and accounted for 28% of the variance in career counselors’ perspectives on advocacy behaviors. It included six participants. Five participants on this factor identified as female and one identified as male. Five persons were White; one was Black. The average age of participants on this factor was almost 35 (SD = 6.79), ranging from 29 to 48, and they had an average of just over seven years of post-master’s experience (SD = 3.76), ranging from three and a half to 14 years. Four worked in higher education, and two worked in non-profit settings.

Factor Interpretation

In the factor interpretation phase of data analysis, the researcher constructs a narrative for each factor by incorporating post-sort interview data with the factor arrays to communicate the rich point of view of each factor (Watts & Stenner, 2012). Each participant’s interview was considered only in conjunction with the other participants on the factor on which they loaded. I read post-sort interview transcripts, looking for shared perspectives and meaning, in order to understand each factor array and enrich each factor beyond the statements of the Q sample. Thus, the results are reported below in narrative form, incorporating direct quotes and paraphrased summaries from interview data, but structured around the corresponding factor arrays.

Table 1

Q Sample Statements, Factor Scores and Q Sort Values

No	Statement	Factor 1		Factor 2
		Factor Score	QSV	Factor Score	QSV
1	Question intervention practices that appear inappropriate.	0.09	1	0.54	1
2	Seek feedback regarding others’ perceptions of my advocacy efforts.	-0.85	-2	-0.75	-1
3	Serve as a mediator between clients and institutions.	-0.47	-1	-1.05	-2
4	Express views on proposed bills that will impact clients.	-0.97	-2	-1.96	-4
5	Maintain open dialogue to ensure that advocacy efforts are consistent with group goals.	-0.19	0	-0.05	0
6	Encourage clients to research the laws and policies that apply to them.	-0.31	0	0.15	0
7	Collect data to show the need for change in institutions.	-0.67	-2	-0.75	-2
8	Educate other professionals about the unique needs of my clients.	0.87	1	0.86	2
9	Help clients develop needed skills.	1.67	3	0.42	1
10	Assist clients in carrying out action plans.	-1.31	3	1.06	2
11	Help clients overcome internalized negative stereotypes.	1.02	2	0.89	2
12	Conduct assessments that are inclusive of community members’ perspectives.	-1.31	-3	0.5	1
13	With allies, prepare convincing rationales for social change.	-0.35	-1	-1.36	-3
14	Identify strengths and resources of clients.	2.17	4	1.62	3
15	Get out of the office to educate people about how and where to get help.	0.58	1	-0.47	-1
16	Teach colleagues to recognize sources of bias within institutions and agencies.	-0.37	-1	-0.37	-1
17	Deal with resistance to change at the community/system level.	-0.43	-1	-0.21	0
18	Collaborate with other professionals who are involved in disseminating public information.	-0.33	0	-0.4	-1
19	Help clients identify the external barriers that affect their development.	1.08	2	1.46	3
20	Use multiple sources of intervention, such as individual counseling, social advocacy and case management.	-0.32	0	1.73	4
21	Train other counselors to develop multicultural knowledge and skills.	0.15	1	0.19	0
22	Work to ensure that clients have access to the resources necessary to meet their needs.	1.03	2	0.85	1
23	Work to change legislation and policy that negatively affects clients.	-1.78	-4	-1.39	-3
24	Ask other counselors to think about what social change is.	-0.25	0	-0.22	0
25	Communicate with my legislators regarding social issues that impact my clients.	-1.45	-3	-1.28	-2

Note. Q sort values are -4 to 4 to correspond with the Q distribution (Figure 1) where 4 is most important
and -4 is most unimportant; QSV = Q Sort Value.

Results

Factor 1: Focus on Clients

For participants on the focus on clients factor, the most important advocacy behavior was to “identify client strengths and resources” (see Table 1). When speaking about this item, participants often discussed teaching clients self-advocacy skills, stating that this is a key way in which career counselors promote social justice. Identifying client strengths and resources was referred to as “the starting point,” “the bottom line” and even the very “definition of career counseling.” One participant said that counseling is about “empowering our clients or jobseekers, whatever we call them, to do advocacy on their own behalf and to tell their story.” In general, persons on this factor were most concerned with empowering individual clients; for example, “I would say, even when we’re doing group counseling and family counseling, ultimately it’s about helping the person in the one-to-one.” Similarly, one participant said, “Instead of fighting for the group in legislation or out in the community, I’m working with each individual to help them better advocate for themselves.” Interview data indicated that social justice was a strongly held value for persons on this factor, but they typically emphasized the need for balancing their views on social injustice with their clients’ objectives; they wanted to take care not to prioritize their own agendas over those of their clients.

Several participants on this factor perceived items related to legislation or policy change as among the least client-centered behaviors and therefore as the more unimportant advocacy behaviors in their career counseling work. Persons on this factor stated that advocacy at the systems level was neither a strength of theirs nor a preference. A few reported that there are other people in their offices or campuses whose job is to focus on policy or legislative change. There also was a level of skepticism about counselors’ power to influence social change. In regard to influencing legislative change in support of clients, one participant said, “I don’t think in my lifetime that is going to happen. Maybe someday it will. I’m just thinking about market change right now instead of legislative change.”

Interview data revealed that career counselors on this factor thought about advocacy in terms of leadership, both positively and negatively. One person felt that a lack of leadership was a barrier to career counselors doing more advocacy work. Another person indicated that leaders were the ones who publicly called for social change and that this was neither his personality nor approach to making change, preferring instead to act at the micro level. Finally, persons on this factor expressed that conversations about social change or social justice were seen as potentially divisive in their work settings. One White participant said the following:

There is a reluctance to do social justice work because—and it’s mostly White people—people really don’t understand what it means, or feel like they don’t have a right to do that, or feel like they might be overstepping. Talking about race or anything else, people are really nervous and they don’t want to offend or say something that might be wrong, so as a result they just don’t engage on that level or on that topic.

Factor 2: Focus on Multiple Roles

One distinguishing feature of the focus on multiple roles factor was the relatively high importance placed on using multiple sources of intervention (see Table 1). Participants described this as being all-encompassing of what a career counselor does and reflective of the multiple roles a career counselor may hold. One participant said, “You never know what the client is going to come in with,” arguing that career counselors have to be open to multiple sources of intervention by necessity. Another participant indicated that she wished she could rely more on multiple sources of intervention but that the specialized nature of her office constricted her ability to do so.

Participants on this factor cited a lack of awareness or skills as a barrier to their implementing more advocacy behaviors. They were quick to identify social justice as a natural concern of career counselors and one that career counselors are well qualified to address due to their ability to remain aware of personal, mental health and career-related concerns simultaneously. One participant said:

I don’t know if the profession of career counseling is really seen as being as great as it is in that most of us have counseling backgrounds and can really tackle the issues of career on a number of different levels.

In talking about the nature of career counseling, another participant said, “Social justice impacts work in so many ways. It would make sense for those external barriers to come into our conversations.”

Regarding collaborating with other professionals to prepare convincing rationales for social change, one participant stated that there are already enough rationales for social change; therefore, this advocacy behavior was seen as less important to her. Persons on this factor placed relatively higher importance on valuing feedback on advocacy efforts than did participants on factor one. One participant said she would like to seek feedback more often but had not thought of doing so in a while: “I did this more when I was in graduate school because you are thinking about your thinking all the time. As a practitioner, as long as social justice and advocacy are on my radar, that’s good.”

Discussion

Neither setting nor gender appeared to differentiate the factors, but age and years of post-master’s experience may have been distinguishing variables. Younger individuals and those with fewer years of post-master’s experience tended to load onto factor two. Factor one had an average age of 51 compared to 35 for factor two, and the average age for all study participants was 43. It is interesting to note that the four participants who loaded onto both factors and were therefore dropped from analysis had an average of just over two years of post-master’s counseling experience versus 11 for factor one and seven for factor two. It is possible that their more recent training regarding advocacy may account for some differences in perspective from those of more experienced counselors.

Participants on factor one (focus on clients) who emphasized the importance of individual clients tended to perceive it as more difficult to have conversations about social justice with their peers or supervisors. In contrast, participants on factor two (focus on multiple roles) were more likely to cite a lack of knowledge or skills regarding their reasons for not engaging in more advocacy behaviors beyond the client level. Factor arrays indicated that factor one participants viewed engaging at the community level as more important, whereas participants on factor two viewed conversations with colleagues and clients about social justice as more important to their work.

The broader view of persons on factor two regarding the career counselor’s role and their openness to acknowledging their own lack of awareness or skills may reflect a different kind of socialization around advocacy compared to persons on factor one. Career counselors who graduated from counseling programs prior to the emphasis on multicultural competence in the early 1990s or before the inclusion of social justice in the literature and CACREP standards in the first decade of the 21st century may have had limited exposure to thinking about contextual or social factors that impact client wellness. Persons on both factors, however, expressed interest in social justice and felt that the vast majority of advocacy behaviors were important.

In post-sort interviews, participants from both factors described a gradual shift in emphasis from a focus on the individual on the right hand (most important) side of the Q sort distribution to an emphasis on legislation on the left hand (most unimportant) side. For example, the statement identify strengths and resources of clients was one of the most important behaviors for nearly every participant. Likewise, the statement work to change legislation and policy that negatively affects clients was ranked among the most unimportant advocacy behaviors for both factors. Interestingly, the statement encourage clients to research the laws and policies that apply to them was a consensus statement with a Q sort value of 0, or the very middle of the distribution. Since this advocacy behavior is both client focused and presumably would provide clients with important self-advocacy skills, it is interesting that it was ranked lower than other items related to client self-advocacy. Some participants indicated that they considered this item a “passive” counselor behavior in that they might encourage clients to research laws but could not or would not follow up with clients on this task. One participant said she would like to encourage clients to research laws that apply to them but shared that she would first need to learn more about the laws that impact her clients in order to feel effective in using this intervention.

Participants were asked directly about potential barriers to advocacy and potential strengths of career counselors in promoting social justice. Responses are discussed below. The questions about strengths and barriers in the post-sort interview did not reference Q sample items, so participant responses are reported together below.

Barriers to Promoting Social Justice

In the post-sort interviews, lack of time was mentioned by nearly every participant as a barrier to implementing more advocacy in career counseling, and it often came in the form of little institutional support for engaging in advocacy. For example, participants indicated that while their supervisors would not stop them from doing advocacy work, they would not provide material support (e.g., time off, reduced case load) to do so. This finding is consistent with other literature that suggests that career counselors report a lack of institutional support for engaging in advocacy (Arthur et al., 2009).

Another major barrier to advocacy was a lack of skill or confidence in one’s ability as an advocate. Advocacy at the social/political level requires a unique set of skills (M. A. Lee, Smith, & Henry, 2013), which practitioners in the present study may or may not have learned during their counseling training. Pieterse, Evans, Risner-Butner, Collins, and Mason (2009) reviewed 54 syllabi from required multicultural courses in American Psychological Association (APA)- and CACREP-accredited programs and found that awareness and knowledge tended to be emphasized more than skill building or application of social justice advocacy. This seems to have been reflected in the responses from many participants in the present study.

Participants on both factors indicated that they held some negative associations to advocacy work, calling it “flag waving” or “yelling and screaming” about inequality or social issues. They expressed some concern about how they might be perceived by their peers if they were to engage in advocacy; however, involvement in this study seemed to provide participants with a new understanding of advocacy as something that happens at the individual as well as at the social level. Participants appeared to finish the data collection sessions with a more positive understanding of what advocacy is and could be.

Strengths of Career Counselors in Promoting Social Justice

In addition to discussing barriers to advocacy, participants were asked directly about strengths of career counselors in promoting social justice and were able to identify many. First and foremost, participants saw the ability to develop one-on-one relationships with clients as a strength. One participant nicely captured the essence of all responses in this area by stating, “The key thing is our work one-on-one with an individual to say that even though you’re in a bad place, you have strengths, you have resources, and you have value.” Participants indicated that social change happens through a process of empowering clients, instilling hope and seeing diversity as a strength of a client’s career identity. The ability to develop strong counseling relationships was attributed partially to participants’ counseling training and identity, as well as to their exposure to a broad range of client concerns due to the inseparable nature of work from all other aspects of clients’ lives (Herr & Niles, 1998; Tang, 2003).

Career counselors in this study served diverse populations and highly valued doing so. These participants described multicultural counseling skills and experience as central to competent career counseling and to advocacy. They felt that they possessed and valued multicultural competence, which bodes well for their potential to engage in competent and ethical advocacy work with additional training, experience and supervision (Crook, Stenger, & Gesselman, 2015; Vespia, Fitzpatrick, Fouad, Kantamneni, & Chen, 2010).

Finally, participants felt that career counseling is seen as more accessible than mental health counseling to some clients, giving career counselors unique insight into clients’ social and personal worlds. Participants reported having a broad perspective on their clients’ lives and therefore unique opportunities to advocate for social justice. Relatedly, participants noted that the more concrete and tangible nature of career counseling and its outcomes (e.g., employment) may lead policymakers to be interested in hearing career counselors’ perspectives on social issues related to work. One participant noted that “there’s a huge conversation to be had around work and social justice” and that career counselors’ key strength “is empowering clients and the broader community to understand the role of work.”

Implications for Career Counselors, Counselor Educators, and Supervisors

Nearly all participants described the sorting process as thought provoking and indicated that social justice and advocacy were topics they appreciated the opportunity to think more about. There was a strong desire among some practitioners in this study to talk more openly with colleagues about social justice and its connection to career counseling, but a lingering hesitation as well. Therefore, one implication of the present study is that practitioners should begin to engage in discussions about this topic with colleagues and leaders in the profession. If there is a shared value for advocacy beyond the individual level, but time and skills are perceived as barriers, perhaps a larger conversation about the role of career counselors is timely. Career counselors may benefit from finding like-minded colleagues with whom to talk about social justice and advocacy. Support from peers may help practitioners strategize ways to question or challenge coworkers who may be practicing career counseling in ways that hinder social justice.

To move toward greater self-awareness and ethical advocacy, practitioners and career counseling leaders must ask themselves critical and self-reflexive questions about their roles and contributions in promoting social justice (McIlveen & Patton, 2006; Prilleltensky & Stead, 2012). Some authors have indicated there is an inherent tension in considering a social justice perspective and that starting such conversations can even lead to more questions than answers (Prilleltensky & Stead, 2012; Stead & Perry, 2012). Counselors should turn their communication skills and tolerance for ambiguity inward and toward one another in order to invite open and honest conversations about their role in promoting social justice for clients and communities. The participants in this study seem eager to do so, though leadership may be required to get the process started in a constructive and meaningful way.

Counselor educators and supervisors can provide counselors-in-training increased experience with systemic-level advocacy by integrating the ACA Advocacy Competencies and the Multicultural and Social Justice Counseling Competencies into all core coursework. Even though broaching issues of social justice has been reported as challenging and potentially risky, counselor educators should integrate such frameworks and competencies in active and experiential ways (Kiselica & Robinson, 2001; M. A. Lee et al., 2013; Lopez-Baez & Paylo, 2009; Manis, 2012). Singh and colleagues (2010) found that even self-identified social justice advocates struggled at times with initiating difficult conversations with colleagues; they argued that programs should do more to help counselors-in-training develop skills “to anticipate and address the inevitable interpersonal challenges inherent in advocacy work” (p. 141). Skills in leadership, teamwork and providing constructive feedback might be beneficial to prepare future counselors for addressing injustice. Furthermore, Crook and colleagues (2015) found that advocacy training via coursework or workshops is associated with higher levels of perceived advocacy competence among school counselors, lending more support in favor of multi-level training opportunities.

Limitations

The current study is one initial step in a much-needed body of research regarding advocacy practice in career counseling. It did not measure actual counselor engagement in advocacy, which is important to fully understand the current state of advocacy practice; rather, it measured perceived relative importance of advocacy behaviors. Researcher subjectivity may be considered a limitation of this study, as researcher decisions influenced the construction of the Q sample, the factor analysis and the interpretation of the emergent factors. By integrating feedback from two expert reviewers during construction of the Q sample, I minimized the potential for bias at the design stage. Factor interpretation is open to the researcher’s unique lens and also may be considered a limitation, but if it is done well, interpretation in Q methodology should be constrained by the factor array and interview data. Although generalizability is not a goal of Q methodology, the sample size in this study is small and therefore limits the scope of the findings.

Suggestions for Future Research and Conclusion

Advocacy is central to career counseling’s relevance in the 21st century (Arthur et al., 2009; Blustein, McWhirter, & Perry, 2005; McMahon, Arthur, & Collins, 2008a), yet due to the complexity and personal nature of this work, more research is required if we are to engage in advocacy competently, ethically and effectively. There appears to be interest among career counselors in gaining additional skills and knowledge regarding advocacy, so future research could include analyzing the effects of a training curriculum on perceptions of and engagement with advocacy. Outcome research could also be beneficial to understand whether career counselors who engage in high levels of advocacy report different client outcomes than those who do not. Finally, research with directors of career counseling departments could be helpful to understand what, if any, changes to career counselors’ roles are possible if career counselors are interested in doing more advocacy work. Understanding the perspectives of these leaders could help further the conversation regarding the ideals of social justice and the reality of expectations and demands faced by career counseling offices and agencies.

This research study is among the first to capture U.S. career counselors’ perspectives on a range of advocacy behaviors rather than attitudes about social justice in general. It adds empirical support to the notion that additional conversations and training around advocacy are wanted and needed among practicing career counselors. Stead (2013) wrote that knowledge becomes accepted through discourse; it is hoped that the knowledge this study produces will add to the social justice discourse in career counseling and move the profession toward a more integrated understanding of how career counselors view the advocate role and how they can work toward making social justice a reality.

Conflict of Interest and Funding Disclosure

The author conducted this research with the assistance of grants awarded by the National Career Development Association, the North Carolina Career Development Association, and the Southern Association for Counselor Education and Supervision.

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Melissa J. Fickling, NCC, is an Assistant Professor at the University of Memphis. Correspondence can be addressed to Melissa J. Fickling, University of Memphis, Ball Hall 100, Memphis, TN 38152, mfckling@memphis.edu.

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