Practicing Counselors, Vicarious Trauma, and Subthreshold PTSD: Implications for Counselor Educators

Bethany A. Lanier, Jamie S. Carney

The purpose of this study was to gain an understanding of the relationship between vicarious trauma (VT) symptoms and subthreshold post-traumatic stress disorder (PTSD) symptoms among practicing counselors. The researchers determined the frequency of VT symptoms and subthreshold PTSD symptoms experienced among practicing counselors and common contributing factors that participants felt contributed to the development of VT symptoms. Implications are presented for counselor educators to determine how they best can prepare students.

 

Keywords: vicarious trauma, subthreshold post-traumatic stress disorder, PTSD, practicing counselors, counselor educators

 

 

Most counselors will likely work with clients addressing trauma (Sommer, 2008; Trippany, White Kress, & Wilcoxon, 2004). Thus, it is important for professional counselors to have an understanding of the dynamics of trauma and interventions to use with clients. Additionally, counselors should be educated on the impact that working with clients can potentially have on them, both personally and professionally. For instance, counselors who work with clients addressing trauma might themselves experience emotional and psychological symptoms, or vicarious trauma (VT). VT has been defined as a disruption in schemas and worldview because of chronic empathic engagement with clients. It is often accompanied by symptoms similar to those of post-traumatic stress disorder (PTSD), which occur as a result of secondary exposure to traumatic material that can result in a cognitive shift in the way the therapist experiences self, others, and the world (Jordan, 2010; Michalopoulos & Aparicio, 2012). Although estimates differ, it has been reported that as many as 50% of counselors are at risk of developing VT (National Child Traumatic Stress Network, 2011).

 

Counseling requires an immense amount of empathetic acceptance on the part of the counselor, which increases the counselor’s vulnerability to taking on their clients’ traumatic experiences (Finklestein, Stein, Greene, Bronstein, & Solomon, 2015). Empathic acceptance and increased vulnerability on the part of the counselor may increase the counselor’s likelihood of developing VT symptoms (Sommer, 2008). VT can have a detrimental effect on all aspects of the counseling process, including both the counselor’s professional and personal life. Practicing counselors experiencing VT have been found to leave the profession early and may also experience emotional and physical disorders, suicidal ideation, strained relationships, increased or continuous burnout, anger, and possible substance abuse (Bergman, Kline, Feeny, & Zoellner, 2015; Keim, Olguin, Marley, & Thieman, 2008). VT is highly detrimental to the counseling process and the care provided to clients. A counselor experiencing VT is more likely to make clinical errors, and VT can negatively impact the counseling relationship (Trippany et al., 2004). The negative implications associated with VT make it imperative that counselors and those who work with them (e.g., supervisors and counselor educators) understand all the factors that lead to the development of VT. This can include recognizing factors that decrease vulnerability, assessing VT, and intervening (Sommer, 2008). One of the initial components to this process is understanding how VT and related symptoms of subthreshold PTSD develop and the variables or experiences that can contribute to higher levels of vulnerability to VT symptoms. Subthreshold PTSD has been defined as the presence of clinically significant PTSD symptoms that fall short of the full Diagnostic and Statistical Manual of Mental Disorders PTSD diagnostic criteria (Bergman et al., 2015).

 

VT and Subthreshold PTSD

 

     As noted, VT can have a detrimental impact on all aspects of the counseling process. A counselor experiencing VT can report many of the symptoms associated with both VT and subthreshold PTSD. VT and subthreshold PTSD have been identified as closely related phenomena. Many counselors who experience VT also meet the criteria for subthreshold PTSD and share similar symptoms (Keim et al., 2008). Counselors who experience VT are in essence experiencing post-traumatic stress symptoms in response to hearing and processing the trauma experienced by their clients (Bercier & Maynard, 2015). Common similar symptoms of VT and subthreshold PTSD include experiencing recurring intrusive thoughts about clients or work, numbing of feelings, hypervigilance or increased anxiety, and a decrease in empathy (Howlett & Collins, 2014; Michalopoulos & Aparicio, 2012; Nelson, 2016).

 

Although there are limitations in the research on the variables that correspond to the development of VT and subthreshold PTSD among counselors, as well as the factors that address these vulnerabilities, the research has highlighted some areas of concern. Understanding these areas is a critical component of addressing the development, assessment, and intervention for VT and subthreshold PTSD, especially for supervisors and counselor educators who train and work with these counselors. One of these variables is years of experience. Although all practicing counselors are at risk for VT and subthreshold PTSD, novice counselors are at an especially elevated risk (Michalopoulos & Aparicio, 2012; Parker & Henfield, 2012). Novice counselors tend to have limited experience with trauma and often have limited training relevant to working with trauma (Newell & MacNeil, 2010; Parker & Henfield, 2012). Further, novice counselors might have trouble establishing boundaries during the early stages of professional identify development, which can contribute to an increase in vulnerability for developing VT and subthreshold PTSD (Howlett & Collins, 2014). Moreover, beginning counselors’ training and personal experiences may not have adequately prepared them for working with individuals dealing with trauma, so in turn they might not have received training on how to address trauma with their clients or identify the development of VT in themselves (Jordan, 2010; Mailloux, 2014; Trippany et al., 2004). It has been recommended that such training should include the key features of trauma, warning signs and symptoms, and strategies to prevent the development of VT and subthreshold PTSD (Newell & MacNeil, 2010).

 

     An essential element of training counselors on strategies to prevent or address the development of VT and subthreshold PTSD includes increasing awareness of the workplace dynamics that may increase vulnerability. Counselors spend a sizeable amount of their time ensuring that others take care of themselves while potentially neglecting their own personal self-care (Whitfield & Kanter, 2014). Neglecting self-care has been found to correspond to an increased rate for developing the negative effects of VT and subthreshold PTSD symptoms (Mailloux, 2014). In an effort to decrease VT and subthreshold PTSD practicing counselors must ensure they are incorporating various types of self-care on a regular basis. Counselors can incorporate self-care activities, such as adequate sleep, social interaction, exercise, a healthy diet, reading, and journaling, into their routine, but all too often practicing counselors let these activities slip (Jordan, 2010; Nelson, 2016).

 

Related to self-care is helping counselors to understand the importance of seeking support from peers and supervisors. Collaboration and consultation with peers and supervisors at the workplace are vital to minimize the adverse effects of VT and subthreshold PTSD (Jordan, 2010). To address possible VT and subthreshold PTSD, practicing counselors require support from colleagues in relation to case conceptualization and identification of impairment (Newell & MacNeil, 2010; Parker & Henfield, 2012; Whitfield & Kanter, 2014). Additionally, counselors should seek supervision specific to trauma to ensure they are not developing VT symptoms and subthreshold PTSD symptoms (Whitfield & Kanter, 2014). One of the concerns, however, is that for many counselors working at counseling sites with high caseloads related to trauma, there are often low levels of clinical supervision (O’Neill, 2010). These sites also can link to another variable that corresponds to higher levels of VT: the caseload of the counselor. For example, counselors with large caseloads are at increased risk of developing VT or subthreshold PTSD because the counselor may not be able to spend adequate amounts of time on each case and might overextend their time addressing case needs (Whitfield & Kanter, 2014). In addition, counselors with caseloads that deal primarily with trauma are at an increased risk of developing VT and subthreshold PTSD, especially if they have limited clinical experience (Bercier & Maynard, 2015; Newell & MacNeil, 2010; Trippany et al., 2004). Recognizing and understanding the contributors to VT and subthreshold PTSD are essential for counselor educators and supervisors to be aware of as they prepare new counselors to enter the field.

 

Counselor Educator and Supervisor Implications

 

When looking at the risk factors associated with VT and subthreshold PTSD, it is clear that a critical component to decrease risk is the training and support provided to counselors. Thus, it is imperative that counselor educators and supervisors be aware of the symptoms and factors that impact the development of VT and subthreshold PTSD. Keim et al. (2008) found that 12% of counselors-in-training (CITs) qualified for a PTSD diagnosis, highlighting the fact that counselor educators and supervisors need to be aware of and educate counselors to recognize the symptoms of VT and subthreshold PTSD. The Council for Accreditation of Counseling and Related Educational Programs (CACREP; 2015) reinforces the importance of this training by specifically requiring that programs educate CITs on trauma-related counseling skills and also engage students in methods to assess and address VT and subthreshold PTSD symptoms in themselves as practicing counselors. To meet this goal, counselor educators and supervisors must more fully understand the causes of VT and subthreshold PTSD (Keim et al., 2008).

 

This study was developed to assess the frequency of VT and subthreshold symptoms among practicing counselors. This included variables that correspond to the development of these symptoms. The data can contribute to our understanding of VT and subthreshold PTSD symptoms among counselors and provide a framework for working with counselors during supervision and in preparing CITs.

 

Method

 

Sample

Two hundred and twenty current practicing counselors completed the nationwide survey. Of the 220 participants, 219 participants reported gender; 23 (10.3%) respondents identified as male and 196 (87.9%) respondents identified as female. Of the participants, 217 (98.6%) reported they were over 19 years of age (range 23–65, M = 39). Two hundred and fifteen respondents indicated holding a master’s degree (97.8%). Thus, exclusion criteria removed five respondents from the data set for not meeting degree requirements—participants must have completed a master’s degree in counseling (i.e., school counseling, clinical mental health counseling, rehabilitation counseling, family and marriage counseling). Current work setting was reported by 207 of the respondents; 137 (62.3%) identified as school counselors, 24 (10.9%) reported working in a community mental health center, 17 (7.7%) reported working in a higher education center, 16 (7.35%) reported working in a private practice, and 13 (5.9%) reported “other,” which included settings such as employee assistance programs and crisis centers.

 

Six respondents (2.7%) reported less than one year of cumulative counseling experience, 50 (22.7%) reported 1–3 years of cumulative counseling experience, 31 (14.1%) reported 4–5 years of cumulative counseling experience, 47 (21.4%) reported 6–10 years of cumulative counseling experience, and 72 (32.7%) reported 10 years or more of cumulative counseling experience. Of the 220 respondents, 12 (5.5%) did not report how many years they have been in their current position, 8 (3.6%) reported being in their current position less than one year, 103 (10.9%) reported 1–3 years, 31 (14.1%) reported 4–5 years, 30 (13.6%) reported 6–10 years, and 36 (16.4%) reported being in their current position 10 or more years.

 

Instruments

Participants were asked to complete a brief demographic questionnaire and two surveys, the PTSD Checklist for the DSM-5 (PCL-5), developed by Blevins, Weathers, Davis, Witte, and Domino (2015), and the Secondary Trauma Stress Scale (STSS), developed by Bride, Robinson, Yegidis, and Figley (2004). The demographic questionnaire sought to understand the impact that years of experience, number of contributing factors, and preventive measures have on VT and subthreshold PTSD symptoms. Participants in this study also completed a series of measures assessing the rate of VT among practicing counselors, the number of participants who meet the criteria for subthreshold PTSD, and the impact of the types and number of professional supports on practicing counselors.

 

     Demographic measure. A basic demographic survey was developed and utilized to collect data on each respondent’s age, gender, current position, years of counseling experience, primary type of clientele served, and any licenses and credentials. Text entry was utilized to understand the type and number of professional supports respondents identified: supervision, peer support, years of experience, training specific to trauma, caseload size, and self-care implementation. The demographic survey collected basic information related to the participants’ counseling experience and background to gain an understanding of who chose to participate in the study. Further, the information gained was used to assist in developing implications for counselor educators and supervisors in preparing CITs to recognize VT symptoms and identify the types of professional supports needed.

 

     PTSD Checklist for the DSM-5 (PCL-5). The PCL-5 is a revision of the PTSD Checklist (PCL) that specifically assesses self-report measures of PTSD symptoms as outlined in the DSM-5 (Blevins et al., 2015). The PCL is one of the most widely used measures of PTSD symptoms, and the revised PCL-5 is the only instrument that specifically measures criteria defined in the DSM-5 (Blevins et al., 2015). The PCL-5 is a 20-item survey that corresponds to the 20 PTSD symptoms in the DSM-5 (Bovin et al., 2016). Respondents are asked to rank, from 0–4, how much they have been bothered by the presented symptom within the last month (Bovin et al., 2016). Sample topics include: having difficulty sleeping; feeling jumpy or easily startled; and avoiding memories, thoughts, or feelings related to the stressful event. In a validation study of the PCL-5, Blevins et al. (2015) found high internal consistency (.94), and the measure fell within the recommended range of inter-item correlation of .15 to .50. Test-retest reliability was r = .82 with a 95% confidence interval [.71, .89], and paired t-tests were significant (p < .01) for the PCL-5 between two test validations (Blevins et al., 2015). Cronbach’s alpha for this study indicated high internal consistency (.96) and test-retest reliability of r = .84.

 

     Secondary Trauma Stress Scale (STSS). The STSS, developed by Bride et al. (2004), was used to understand the number of VT symptoms among practicing counselors as well as to determine the relationship between VT symptoms and subthreshold PTSD symptoms among practicing counselors. The STSS is a 17-item self-report measure designed to assess helping professionals who may have experienced secondary traumatic stress and the frequency of intrusion, avoidance, and arousal symptoms (Bride et al., 2004; Ting, Jacobson, Sanders, Bride, & Harrington, 2005).

 

The STSS asks that respondents endorse how frequently an item was true for them in the past 7 days (Bride et al., 2004). Responses range from 1 to 5 in Likert form (1 = never and 5 = very often). Psychometric data for the STSS indicates very good internal consistency reliability with coefficient alpha levels of .93 for the total STSS scale, .80 for the Intrusion subscale, .87 for the Avoidance subscale, and .83 for the Arousal subscale (Bride et al., 2004). Ting et al. (2005) determined in their validation study of the STSS that internal consistency reliability for the 17 total STSS items was very high (.94) and was moderately high for the Intrusion subscale (.79), the Avoidance subscale (.85), and the Arousal subscale (.87), and all three factors were highly correlated with each other (intrusion–avoidance, r = .96; intrusion–arousal, r = .96; avoidance–arousal, r = 1.0), as indicated by a confirmatory factor analysis. Cronbach’s alpha for this study confirmed Ting et al.’s findings, as internal consistency reliability for the 17 total STSS items was very high (.94) and was moderately high for the Intrusion subscale (.80), the Avoidance subscale (.86), and the Arousal subscale (.89). Statements on the Intrusion subscale inquire about respondents’ intrusion symptomology on a Likert scale with statements such as “My heart started pounding when I thought about my work with clients” and “I had disturbing dreams about my work with clients.” The Avoidance subscale asks respondents to respond on a Likert scale to statements such as “I felt emotionally numb” and “I had little interest in being around others.” The final subscale, Arousal, asks respondents to respond on a Likert scale to statements such as “I had trouble sleeping” and “I expected something bad to happen.”

 

Procedures

Upon Institutional Review Board approval, participants were recruited via email through listserv solicitation that included the Alabama Counseling Association, the American School Counselor Association, the American Counseling Association, and CESNET. Participants were provided a link to an informed consent document and the research surveys in Qualtrics. Participation was restricted to practicing mental health or school counselors who had a master’s degree in counseling and had been a practicing counselor for at least 6 months at the time of the survey.

 

Design and Statistical Analyses

The purpose of this quantitative study was to investigate the frequency of VT symptoms and subthreshold PTSD symptoms experienced by practicing counselors. This included the relationship of VT symptoms and subthreshold PTSD symptoms with years of experience, work setting and type of clientele, and the number and type of professional supports utilized by practicing counselors. Descriptive analysis was used to determine what symptoms of VT and subthreshold PTSD practicing counselors experience. A linear regression was used to determine the relationship between VT symptoms and subthreshold PTSD symptoms. Linear regressions were utilized to determine the relationship years of experience, work setting and type of clientele, and professional supports have with VT symptoms and subthreshold PTSD symptoms among practicing counselors.

 

Results

 

Symptoms of VT and Subthreshold PTSD Experienced by Practicing Counselors

Descriptive statistics based on participants’ responses indicated symptoms of VT and subthreshold PTSD are being experienced by practicing counselors. On the STSS, all symptoms were experienced to some degree by 49.5% of the participants. Symptoms were rated significant if they scored higher than “never” on the STSS, meaning they had experienced the symptom to some degree within the past 7 days.

 

The most common symptom of VT experienced by participants was thinking about work with clients when not intending to do so (85.5%), as measured by the STSS. Additional symptoms of VT experienced commonly by participants included feeling emotionally numb (80.5%), becoming easily annoyed (79.1%), having difficulty concentrating (75.5%), and feeling discouraged about their future (75.5%). Experiencing disturbing dreams about their clients (49.5%) and feeling jumpy (56.4%) were the least common symptoms experienced by participants, but 49.5% of the participants experienced these symptoms. Table 1 outlines the VT symptoms of participants as measured by the STSS in descending order.

 

 

Table 1

 

STSS Symptom Distribution

Items in Descending Order n (%)
I thought about my work with clients when I didn’t intend to. 188 (85.5%)
I felt emotionally numb. 177 (80.5%)
I was easily annoyed. 174 (79.1%)
I felt discouraged about the future. 166 (75.5%)
I had trouble concentrating. 166 (75.5%)
I had trouble sleeping. 165 (75.0%)
I wanted to avoid working with some clients. 162 (73.6%)
I was less active than usual. 156 (70.9%)
Reminders of my work with clients upset me. 155 (70.5%)
My heart started pounding when I thought about my work with clients. 155 (70.5%)
I had little interest in being around others. 149 (67.6%)
It seemed as if I was reliving the trauma(s) experienced by my client(s). 133 (60.5%)
I expected something bad to happen. 132 (60.0%)
I avoided people, places, or things that reminded me of my work with clients. 126 (57.3%)
I noticed gaps in my memory about client sessions. 126 (57.3%)
I felt jumpy. 124 (56.4%)
I had disturbing dreams about my work with clients. 109 (49.5%)

 

 

 

 

Participant responses to the PCL-5, utilized to measure subthreshold PTSD symptoms, suggested practicing counselors are experiencing subthreshold PTSD symptoms. Symptoms were rated as significant if they scored higher than “not at all,” indicating they had experienced the symptom to some degree within the past month. The most common symptom reported to have been experienced by all participants (100%) was repeated, disturbing, or unwarranted memories of the stressful experience. Other symptoms that were reported to have been experienced commonly by practicing counselors included having trouble falling or staying asleep (71.4%), having difficulty concentrating (70.9%), feeling distant or cut off from other people (68.2%), and feeling very upset when something reminded them of the stressful experience (66.8%). Taking too many risks or doing things that could cause personal harm (36.8%); feeling or acting as if the stressful experience were actually happening again (42.7%); and experiencing repeated, disturbing dreams of the stressful experience (49.1%) were experienced least commonly by participants. Table 2 outlines the VT symptoms of participants as measured by the PCL-5 in descending order.

 

 

Table 2

 

PCL-5 Symptom Distribution

Items in Descending Order n (%)
Repeated, disturbing, and unwanted memories of the stressful experience? 220 (100%)
Trouble falling or staying asleep? 157 (71.4%)
Having difficulty concentrating? 156 (70.9%)
Feeling distant or cut off from other people? 150 (68.2%)
Feeling very upset when something reminded you of the stressful experience? 147 (66.8%)
Irritable behavior, angry outbursts, or acting aggressively? 139 (63.2%)
Avoiding memories, thoughts, or feelings related to the stressful experience? 139 (63.2%)
Having strong negative feelings such as fear, horror, anger, guilt, or shame? 134 (60.9%)
Having strong physical reactions when something reminded you of the stressful experience
(for example, heart pounding, trouble breathing, sweating)?
130 (59.1%)
Avoiding external reminders of the stressful experience (for example, people, places, conversations, activities, objects, or situations)? 127 (57.7%)
Being “superalert” or watchful or on guard? 125 (56.8%)
Having strong negative beliefs about yourself, other people, or the world (for example, having thoughts such as: I am bad, there is something seriously wrong with me, no one can be trusted, the world is completely dangerous)? 125 (56.8%)
Loss of interest in activities that you used to enjoy? 123 (55.9%)
Blaming yourself or someone else for the stressful experience or what happened after it? 121 (55.0%)
Trouble experiencing positive feelings (for example, being unable to feel happiness or have loving feelings for people close to you)? 119 (54.1%)
Feeling jumpy or easily startled? 116 (52.7%)
Trouble remembering important parts of the stressful experience? 113 (51.4%)
Repeated, disturbing dreams of the stressful experience? 108 (49.1%)
Suddenly feeling or acting as if the stressful experience were actually happening again
(as if you were actually back there reliving it)?
  94 (42.7%)
Taking too many risks or doing things that could cause you harm?   81 (36.8%)

 

 

 

 

Relationship Between VT Symptoms and Subthreshold PTSD Symptoms

     Linear regression models determined the relationship between VT symptoms and subthreshold PTSD symptoms among practicing counselors. In a backward regression, the PCL-5, measuring subthreshold PTSD symptoms, was entered as the dependent variable, and the subscales of the STSS, measuring VT symptoms, were entered as the independent variables. Results indicated that the more VT symptoms were experienced by practicing counselors, the more subthreshold PTSD symptoms were experienced. There was a significant relationship between results from the PCL-5 and all three STSS subscales. The relationship between subthreshold PTSD symptoms and the Intrusion subscale was significant (r = .676, p < .001). There also was a significant relationship between subthreshold PTSD symptoms and avoidance symptoms (r = .759, p < .001), and between subthreshold PTSD symptoms and arousal symptoms (r = .790, p < .001). Avoidance VT symptoms and arousal VT symptoms were the most predictive variables associated with developing subthreshold PTSD symptoms as evidenced in the restricted model regression summary. In the backward regression model, the Intrusion subscale of the STSS was eliminated as the least significant variable, which indicates the more arousal and avoidance symptoms were experienced as VT, the more subthreshold PTSD symptoms were experienced by the practicing counselors. In the full regression model (R2 Full = .656, F = 103.4, p < .001), results suggested a significant relationship, indicating that the more VT symptoms were experienced by practicing counselors, the more subthreshold PTSD symptoms were experienced. Through the restricted regression model (R2 Restricted = .655, F = 155.75, p < .001) and the F change test, results indicated that the restricted model is not worse than the full model because the observed F (.00000892; p = .647) does not exceed the critical F (df = 1,163), which is 3.94.

 

Relationship Among Demographics and Type of Professional Supports Among Practicing Counselors on VT

A backward linear regression model was utilized to determine the relationship between VT symptoms and years of experience, work setting and type of clientele, and type of professional supports among practicing counselors. There were two significant relationships within this regression in the restricted model of the regression. There was a significant negative correlation between VT symptoms and having a manageable caseload, indicating the more manageable caseload the counselor has, the fewer VT symptoms they have. In addition, there was a significant negative correlation between VT symptoms and having adequate supervision, indicating the more supervision received, the fewer VT symptoms experienced. Overall, the two variables (caseload and supervision) correlate with the dependent variable, VT symptoms (r = .273, R2 = .074). This overall correlation is unlikely due to chance (F = 8.159, p < .001). The F change test indicated the observed F (2.008; p = .158) does not exceed the critical F (df = 1, 202), which is 3.89. The semi-partial correlation between caseload and VT symptoms was -.173, while the semi-partial correlation between supervision and VT symptoms was -.150. The semi-partial correlation indicates the uniqueness of the relationship. The squared semi-partial correlation for supervision was (-.173)2 = .029, and the squared semi-partial correlation for caseload was (-.150)2 = .02., *p < .05.

 

Relationship Between Demographics and Type of Professional Supports Among Practicing Counselors on Subthreshold PTSD Symptoms

A backward linear regression model was utilized to determine the relationship between subthreshold PTSD symptoms and years of experience, work setting and type of clientele, and the number and type of professional supports among practicing counselors. With subthreshold PTSD symptoms as the dependent variable and years of experience, work setting and type of clientele, and type of professional supports as the independent variables, a backward linear regression was run to understand the relationship between the variables in the restricted model of the regression. Results indicated a significant relationship between subthreshold PTSD symptoms and those counselors who work primarily with adolescents or with sexual assault/domestic violence survivors. Overall, the two variables (adolescents and sexual assault/domestic violence) correlate with our dependent variable, subthreshold PTSD symptoms (r = .242, R2 = .059). This overall correlation is unlikely due to chance (F = 5.080, p = .007). The F change test indicated the observed F (2.255; p = .135) does not exceed the critical F (df = 1,162), which is 3.94. The semi-partial correlation between adolescents and subthreshold PTSD symptoms was .159, while the semi-partial correlation between sexual assault/domestic violence and subthreshold PTSD symptoms was .187. The semi-partial correlation indicates the uniqueness of the relationship. The squared semi-partial correlation for adolescents was (.159)2 = .025, and the squared semi-partial correlation for sexual assault/domestic violence was (.187)2 = .03. This data indicates that work setting and the type of clientele served by the counselor can influence risk for developing subthreshold PTSD symptoms.

 

Limitations

     One limitation for this study was the high percentage of participating school counselors (62.3%). This could have possibly skewed results as the type of clientele that the practicing counselors primarily worked with exhibited the most influence on symptoms of VT and subthreshold PTSD (i.e., adolescents). Additionally, this large percentage of school counselors could make the implications suggested in this study not as applicable for counselors in higher education settings.

 

An additional limitation of this study was the lack of demographics available to identify if counselors were in a rural setting or urban setting. Although the implications suggested are applicable to all counselors, demographic location could serve as an additional barrier to implementing the professional supports suggested.

 

Discussion

 

The purpose of this study was to develop an understanding of the frequency and characteristics of VT symptoms and subthreshold PTSD symptoms among practicing counselors, which was answered by the first research question. The most common VT symptom experienced by participants (85.5%) was thinking about their work with clients when they did not intend to outside of work. This finding is significant for counselor educators and supervisors as it indicates that VT symptoms are being experienced by the majority of the counselors in this study. All VT symptoms, as measured by the STSS, were experienced by 49.5% of the participants, indicating all 17 VT symptoms measured had been experienced to some degree by the counselors that participated in this study. This study adds to the current literature reported by Bride (2007) that 50% of child welfare counselors experience traumatic stress symptoms within the severe range. In addition, Cornille and Meyers (1999) reported 37% of their sample of child protection service workers reported clinical levels of emotional distress associated with secondary trauma, and Conrad and Kellar-Guenther (2006) reported 50% of child protection workers suffered “high” to “very high” levels of compassion fatigue.

 

In addition to measuring VT symptoms, the first research question was developed to acquire an understanding of the frequency of subthreshold PTSD symptoms experienced by counselors. Subthreshold PTSD symptoms were measured by the PCL-5 and results suggest practicing counselors are experiencing subthreshold PTSD symptoms. Of the 20 items in the PCL-5, all but three were experienced by at least 50% of the participants. All 220 (100%) of participants reported experiencing repeated, disturbing, and unwanted memories of the stressful experience. This finding is similar to that found by the STSS in that over 85% of participants had unwanted thoughts about experiences with clients outside of work. Furthermore, over 70% of participants reported having trouble sleeping and having difficulty concentrating in both the STSS and PCL-5 as symptoms of VT and subthreshold PTSD. Understanding the symptoms of VT and subthreshold PTSD experienced by participants was important, as previous studies have indicated that those who experience VT symptoms also experience subthreshold PTSD symptoms (Jordan, 2010). Additionally, the literature has reported VT symptoms and subthreshold PTSD symptoms as being one and the same (Finklestein et al., 2015).

 

The second research question was developed to gain an understanding of the relationship between VT symptoms and subthreshold PTSD symptoms. A linear backward regression with the PCL-5 measuring subthreshold PTSD symptoms was entered as the dependent variable, and the subscales of the STSS, measuring VT symptoms, were entered as the independent variables. Results from this regression model indicated that the more VT symptoms were experienced by practicing counselors, the more subthreshold PTSD symptoms were experienced. In the backward regression model, the Intrusion subscale of the STSS was eliminated as the least significant variable, which indicated that the more arousal and avoidance symptoms were experienced as VT, the more subthreshold PTSD symptoms were experienced by the practicing counselors, with the Intrusion scale not being significant. This finding is consistent with the extant literature that has reported VT symptoms being analogous to PTSD symptoms (Keim et al., 2008). Furthermore, this finding also is consistent with prior literature that reported counselors who experience VT symptoms also experience PTSD symptoms (Bercier & Maynard, 2015), as found in Bride’s (2007) study in which 34% of child welfare workers met the PTSD diagnostic criteria because of VT.

 

In an effort to answer the second research question, which was interested in the relationship between VT symptoms and subthreshold PTSD symptoms and years of experience, work setting and type of clientele, and the number and type of professional supports, two backward linear regression models were established. The first linear regression model was interested in the relationship between VT symptoms and years of experience, work setting and type of clientele, and the number and type of professional supports among practicing counselors. In this backward linear regression model, the STSS served as the dependent variable with years of experience, work setting and type of clientele, and the number and type of professional supports serving as the independent variables. Results indicate a significant relationship between VT symptoms and having a manageable caseload as well as between VT and utilizing supervision. A negative correlation between VT symptoms and having a manageable caseload indicates that the more manageable a counselor’s caseload, the less likely they were to experience VT symptoms. This finding is consistent with prior studies that indicate a manageable caseload as being a protective factor for counselors that can decrease their chance of developing both VT symptoms and subthreshold PTSD symptoms (Trippany et al., 2004). Additionally, there was a negative correlation between supervision as a professional support and the development of VT symptoms among counselors. Adequate supervision has been identified as a protective factor against the development of VT (Harrison & Westwood, 2009). Both of these findings are important implications for counselor educators and supervisors as they can be initiated in the classroom while CITs are preparing for a career in the counseling profession.

 

The second linear regression model focused on the relationship between subthreshold PTSD symptoms and years of experience, work setting and type of clientele, and the number and type of professional supports among practicing counselors. In this backward linear regression model, the PCL-5 served as the dependent variable with years of experience, work setting and type of clientele, and the number and type of professional supports serving as the independent variables. Results indicated a significant relationship between subthreshold PTSD symptoms and counselors who primarily work with adolescents and sexual assault/domestic violence survivors. These findings are consistent with prior literature that has indicated sexual assault counselors report more VT symptoms and subthreshold PTSD symptoms. For instance, Bride (2007) reported 65% of domestic violence and sexual assault social workers reported at least one symptom of VT, while Lobel (1997) reported over 20 years ago that 70% of sexual assault counselors experienced VT. Additionally, Schauben and Frazier (1995) reported that counselors who work with a higher percentage of sexual assault survivors report more disrupted beliefs about themselves and others, more subthreshold PTSD symptoms, and more VT than counselors who see fewer sexual assault survivors.

 

Implications for Counselor Educators and Supervisors

 

     The results of this study provide counselor educators and supervisors with information to prepare CITs to have an increased awareness of VT and subthreshold PTSD symptoms. This study established evidence that practicing counselors are experiencing numerous VT symptoms and subthreshold PTSD symptoms. In fact, this study found that all VT symptoms measured were experienced by 49.5% of the participants, and 17 of the 20 PTSD symptoms measured were experienced by all participants. Further, in an open-ended question in the brief demographic survey, participants provided the researcher with ideas they felt would increase awareness of VT and subthreshold PTSD and decrease VT and subthreshold PTSD symptoms. Over 40% of responses indicated a desire for more education on VT symptoms and subthreshold PTSD symptoms. With 49.5% of participants reporting VT symptoms and subthreshold PTSD symptoms, it is evident that additional education is needed related to these symptoms among practicing counselors. Keim et al. (2008) suggested educational trainings and workshops be provided to CITs proactively to increase awareness of VT and subthreshold PTSD and to decrease VT symptoms and subthreshold PTSD symptoms among practicing counselors. Counselor educators and supervisors can provide trainings on the signs and symptoms of VT and subthreshold PTSD experienced by counselors to raise awareness of these symptoms and ways to recognize and alleviate them before causing harm to the counselor or client.

 

This study denoted that counselors who work primarily with adolescents and sexual assault/domestic violence survivors are experiencing more subthreshold PTSD symptoms than counselors that do not work specifically with these populations. As counselor educators prepare CITs for practicum, internship, and employment as counselors, it is vital for counselor educators to acknowledge the unique challenges that may stem from working with adolescents and survivors of sexual assault/domestic violence. It is imperative that counselor educators and supervisors integrate specific educational material through coursework related to these populations to best prepare CITs. Evidence-based practices that are effective for counseling these populations should be implemented within counselor education programs, supervision, workshops, and trainings outside of the degree program (e.g., at conferences; Alpert & Paulson, 1990; Mailloux, 2014; Whitfield & Kanter, 2014).

 

Education on the significance of professional supports, such as adequate supervision and manageable caseloads, is fundamental for CITs to be prepared to lessen the hazard of developing VT symptoms and subthreshold PTSD symptoms. By providing sufficient supervision during practicum and internship, counselor educators and supervisors can prepare CITs for coping with VT symptoms and subthreshold PTSD symptoms should they develop. In addition, through modeling appropriate supervision, CITs will comprehend the supervisory process and seek post-degree supervision.

 

Directions for Future Research

     Future studies on VT symptoms and subthreshold PTSD symptoms need to focus solely on clinical mental health counselors or school counselors to develop implications specific to counseling sites. Further research devoted to the development of workshops and trainings to educate counselors on VT and subthreshold PTSD is needed.

 

A future study that compares counselors in rural settings and urban settings will be important to understand barriers to coping with and addressing VT symptoms and subthreshold PTSD symptoms. For example, in a rural setting, the counselor may not have adequate supervision and may be overloaded with cases, which can decrease the amount of self-care they are able to implement. It will be important for future research to explore what barriers to professional supports counselors face in these different demographic communities.

Because of this study’s finding that working primarily with adolescents and individuals who have experienced sexual assault or domestic violence increases counselors’ chances of experiencing VT symptoms and subthreshold PTSD symptoms, a qualitative or mixed-methods study focused on VT among counselors working with these populations is desirable. In an effort to best prepare students who will work with these populations, an understanding of exactly which aspects of working with these clients increase VT symptoms and subthreshold PTSD symptoms is essential.

 

 

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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Bethany A. Lanier, NCC, is an assistant professor at the University of West Georgia. Jamie S. Carney is a professor at Auburn University. Correspondence can be addressed to Bethany Lanier, 1601 Maple Street, Carrollton, GA 30116, blanier@westga.edu.

High School Counselor Contacts as Predictors of College Enrollment

Angela K. Tang, Kok-Mun Ng

 

Based on archival data from an urban school district, this retrospective correlational study examined the extent to which certain types of student–school counselor contacts, based on a student-report high school exit survey, could predict high school students’ postsecondary enrollment in 2- and 4-year colleges within 5 years of graduating from high school. In addition to these variables, information such as ethnicity, grade point average, and free and reduced lunch status were used to identify other trends in the data. Multiple logistic regression analysis showed that counselor contact regarding college planning and attendance and demographic information regarding free and reduced lunch status were significant predictors of postsecondary enrollment. Counselor contact regarding goal setting, concerns about grades, and needing more college information did not significantly predict postsecondary college enrollment. Findings suggest some school counselor duties can serve as sources of social capital, which can help increase student social capital.

 

Keywords: school counselor, postsecondary college enrollment, reduced lunch, free lunch, social capital

 

 

According to the American School Counselor Association (ASCA; 2012), the role of school counselors is to remove barriers to academic success through establishing a comprehensive counseling program and providing appropriate services. This includes, but is not limited to, developing and imparting counseling curriculum based on school need, intentional guidance lessons, connecting with other stakeholders, planning, and counseling students at all levels. Through these various functions, school counselors interact with and impact students they serve. Statewide studies focusing on school counseling programs have found that comprehensive school counseling programs assisted in increasing test scores, improving student grades, lowering suspension rates, and increasing feelings of school connectedness (Carey, Harrington, Martin, & Hoffman, 2012; Carey, Harrington, Martin, & Stevenson, 2012; Lapan, Gysbers, & Petroski, 2001; Lapan, Gysbers, & Sun, 1997).

 

According to the National Center for Education Statistics (NCES), only 66.2% of graduating high school students enrolled in a 2-year or 4-year college in Fall 2012 (NCES, 2015a, row 52). Recently, there have been increased efforts to matriculate students to higher education after high school as national attention focuses on the United States’ post-industrial society and its effects on enrollment (Clinedinst & Koranteng, 2017; Hill, 2012; NCES, 2015b). Former First Lady Michelle Obama launched the Reach Higher Initiative (n.d.), which introduced the idea of a national signing day to encourage and inspire all students, especially low-income and first-generation students, to attend college. Some key individuals who are primed to support all students in the transition from high school to postsecondary education, especially for lower socioeconomic status and minority populations, are high school counselors (Holcomb-McCoy, 2010). Elementary and middle school counselors play a crucial role in preparing students for high school, yet high school counselors are held the most responsible for ensuring students’ successful transitions to life after high school (Carey & Dimmitt, 2012). Through the present study, we sought to add to the literature by examining the extent to which school counseling contacts predict high school students’ postsecondary enrollment. We believe that such focus will help school counselors self-advocate for duties that support successful postsecondary enrollment.

 

Roles, Responsibilities, and Challenges of a High School Counselor

 

High school counselors, while meeting academic, career, personal, and social student needs, also play a crucial role in ensuring their students are on track for high school graduation, assisting in college applications, and filling out financial aid applications, especially for first-generation and marginalized students who rely more heavily on school counselors to complete the process (Lapan, 2012; Martinez, 2013; McDonough, 2005). Though increasing college and career services is a current focus in K–12 education, frequently, the college and career services that school counselors wish to provide are at odds with administration and school districts’ work expectations and emphasis for school counselors (Carey, Harrington, Martin, & Hoffman, 2012; Paolini & Topdemir, 2013). Instead of being able to wholly focus on providing personal, social, and college and career services, school counselors are oftentimes saddled with administrative tasks such as entering transcripts, grade verifications, and test proctoring. This has led to an internal push in the school counseling profession to provide data to support the positive impact school counselors have on their students (Brigman & Campbell, 2003; Hurwitz & Howell, 2014).

 

Impact of School Counselor Interventions on Postsecondary Outcomes

Most studies related to high school counseling have focused specifically on how school counselor caseload size influences school counseling duty outcomes. Whether it was assisting with college applications (Bryan, Moore-Thomas, Day-Vines, & Holcomb-McCoy, 2011), spending more than half their time on college-related topics (Engberg & Gilbert, 2014), increased opportunity for individual planning (Woods & Domina, 2014), or higher rates of 4-year college enrollment (Hurwitz & Howell, 2014), smaller school counselor caseloads were demonstrated to positively influence students’ postsecondary plans. One study specifically examined first-generation and low-income students. Pham and Keenan (2011) found that the lower the first-generation student–counselor ratio, the higher the likelihood that a qualified first-generation student would enroll in a 4-year university. This finding corroborates existing findings that show first-generation and low-income students tend to rely more heavily on school-provided services, and the degree to which school counselor support can improve student access to higher education. Belasco (2013) highlighted the association between school counselor meetings with students and subsequent postsecondary enrollment; however, the study only examined the first fall after high school graduation and excluded enrollment in 2-year institutions in the analysis.

 

The abovementioned studies support the argument that school counselors contribute to students accessing postsecondary planning and support. Specifically, findings in the studies indicate that specific contacts with school counselors contribute to students’ 4-year college postsecondary enrollment. With that said, despite the literature that supports school counseling and highlights the extent to which school counselors can positively impact students, there has been a lack of conversation regarding which specific counselor contacts may contribute most to postsecondary enrollment, as well as enrollment in both 2- and 4-year institutions (NCES, 2005). Thus, it is crucial to examine what exact contacts school counselors have with students that potentially influence student postsecondary enrollment in order to advocate for more time to do those activities.

 

Purpose of the Study

 

The focus of this study was to examine specific school counseling contacts and their influence on students’ postsecondary enrollment. Specifically, we wanted to know whether students’ contacts with school counselors influence students into matriculating to higher education. We hoped to fill a gap in the research by examining specific counselor contacts that support student achievement, in addition to expanding the examined postsecondary institution enrollment window beyond the fall immediately following graduation. The ultimate goal is that our findings will provide information to the profession and its advocates, such as ASCA, to assist with their advocacy efforts and policy recommendations.

 

Based on the gaps in the existing research, the primary research question that guided our study was: To what extent do the following student–school counselor contacts, as reported by graduating high school students, predict postsecondary institution enrollment (2- and 4-year inclusive): (1) contact related to attendance, (2) contact related to college planning/scholarship support, (3) contact related to concerns about grades, and (4) contact related to goal setting?

 

The secondary research question was: To what extent do culminating GPA in high school, free and reduced lunch (FRL) status, and a student’s ethnicity predict enrollment in a postsecondary institution (2- or 4-year inclusive)? In addition to the above student–school counselor contact variables, we included a predictor variable that assessed students’ perception of the college search and application process. This data came from student responses to the survey question: Were there parts of the college search and/or application process you felt you needed more assistance or information?

 

Method

 

Design

The present study was a retrospective study that used binary multiple logistic regression to analyze an archival dataset. The central data was high school students’ reported contacts with their school counselors as related to subsequent college enrollment.

 

Two types of data were collected for each student. The first type was data regarding students’ contacts with counselors while in high school. This data was drawn from a district database, which was comprised of data from 17 high schools. The data came from a Senior Exit Survey (required of all 12th-grade students) and general background information (GPA, FRL status, and ethnicity). The second type was data regarding student enrollment in a postsecondary course of study. This data was drawn from the National Student Clearinghouse (NSCH; n.d.) to ascertain if students enrolled in a 2- or 4-year college in any of the 5 years following graduation.

 

District Information

The school district studied is a large urban school district in a Western state in the United States. As an urban district, it encompasses both suburban and urban areas and at the time of this study, the total K–12 enrollment was 79,423. The district follows the ASCA National Model (ASCA, 2012) and encourages comprehensive school counseling program implementation at each site.

 

Participants

The target population studied was the 2,276 12th-grade students who were slated to graduate. We selected this cohort in order to include 5 years of postgraduate data regarding whether they enrolled or did not enroll in 2- or 4-year postsecondary institutions. Of the 2,276 students, 67 were excluded because of missing information necessary for the study. The final 2,209 in the study sample consisted of 0.04% Hawaiian/Pacific Islander, 0.09% Native American, 0.09% two or more races, 3.9% Asian, 20% African American/Black, 30% White, and 47.5% Hispanic/Latinx. This breakdown is representative of the district at large. Of the sample used, 1,181 (53%) students qualified for FRL, while 1,028 (47%) did not qualify.

 

Because of the small number (n = 19) of Native American, Hawaiian/Pacific Islander, and “two or more race” students, we did not use these ethnicities in our regression model. Representing all students is crucial in school counseling; however, with such small sample sizes, it might make the students personally identifiable (NCES, 2017). The Every Student Succeeds Act (ESSA) also has guidelines regarding minimum numbers of n-size requirements to make statistical inferences in state accountability systems, and 19 did not make the minimum (Alliance for Excellent Education, 2018).

 

Measures

Senior Exit Survey. This school district administers its Senior Exit Survey to each senior every school year between May 15 and June 15. The purpose of the survey is to assess the types of support services students accessed during their high school careers. The survey includes questions that directly answered the research questions posed for this study: whether students had met with their school counselor about (a) attendance; (b) college planning, applications, essays, and scholarships; (c) concerns about grades; and (d) goal setting (all responses coded as 0 for not met, and 1 for met). The survey also included a question that asked students, “Were there parts of the college search and/or application process you felt you needed more assistance or information?” We incorporated responses to this survey question into the current study as an additional predictor variable because we wanted to examine if the perception of needing more assistance resulted in students not enrolling in either a 2- or 4-year college (all responses coded as 0 for not attended, and 1 for attended).

 

National Student Clearinghouse data. NSCH data is collected from over 3,600 colleges and universities, both private and public. Membership in the Clearinghouse is open to any postsecondary institution that participates in the Federal Title IV program. The data includes degrees obtained and enrollment in postsecondary institutions (NSCH, n.d.). The specific information used as the outcome variable in our study was if students enrolled in a 2- or 4-year postsecondary institution at least once in the 5 years after graduating from high school (coded as 1 for yes, or 0 for no). We used the 5-year time frame because not all students enroll immediately in college upon graduation, and we wished to capture students who enrolled later (NCES, 2005; Rowan-Kenyon, 2007).

 

District data. Student data that has been known to reflect achievement and postsecondary enrollment were provided by the district as well. District data included in the data analysis was: (a) ethnicity, (b) GPA, and (c) FRL status.

 

Data Construction and Analysis

A de-identified dataset was obtained from the school district’s research department after receiving a research proposal. As the dataset was de-identified and had already been collected, the university IRB committee determined that an IRB application for human subjects was not required. A multiple logistic regression was performed, with binary and scale variables, using SPSS Statistics 22.0 to examine whether the set of school counseling duties (dependent variables) are statistically significant in predicting 2- or 4-year institution enrollment (independent variable). In addition to these, background supplemental independent predictor variables were included to assess their relative contribution to the outcome response. School counseling duties, FRL status, and ethnicity were coded as binary variables, and GPA was coded as a scale (A = 4, B = 3, C = 2, D = 1, F = 0).

 

Some data was recoded in order to condense some of the information. One piece of the dataset that was recoded was the NSCH data. As there were 5 years of postsecondary enrollment data, it was condensed and recoded to create one variable that indicated if the individual had been enrolled (yes or no) in a postsecondary institution, either 2- or 4-year, during those 5 years.

 

In order to ascertain the number of participants required to make for a robust study, G*Power (Heinrich, 2014) was used. According to the information, 89 individuals are the minimum number of participants required to ensure the results had enough power, and our sample size far exceeded the minimum requirement. In order to reduce the possibility of a Type II error, we used an alpha level of .05 to determine statistical significance.

 

Results

 

School Counselor Contacts

Multiple logistic regression was conducted to determine which dependent variables of school counselor contact (i.e., attendance, college planning, concerns about grades, goal setting) and demographic variables (i.e., FRL status, GPA, ethnicity, and perception of needed additional assistance with college topics) were statistically significant predictors of enrollment at least once in a 2- or 4-year postsecondary institution. Regression results indicated the overall model of eight predictors: four dependent variables (meeting with school counselors about college planning, concerns about grades, attendance, and goal setting) and four demographic variables (FRL status, GPA, ethnicity, and perception of needing more assistance with college-related topics). The model of eight predictors was statistically reliable in distinguishing between students who did not enroll in postsecondary institutions and those who did. The Nagelkerke R2 = .262 (p < .0001) indicated that the predictor variables accounted for about 26% of the variability in student outcomes. The Hosmer and Lemeshow test indicated the goodness-of-fit (p = .381, X2 = 8.559). Significance levels and odds ratios are presented in Table 1.

 

 

Table 1

 

Logistic Regression Analysis Predicting Postsecondary Enrollment at Least Once (N = 2,209)

  Sig.              Exp(B)

 

Weighted GPA                                                       .000               2.222

FRL Status (1)                                                         .021                 .771

College Planning (1)                                               .000               1.436

Concerns About Grades (1)                                     .659               1.049

Goal Setting (1)                                                      .687                 .754

Attendance                                                             .000                 .577

Needing More Assistance? (1)                                 .772               1.029

Ethnicity

White                                                         .873                 .924

Black                                                         .093               2.308

Asian                                                         .591               1.354

Hispanic/Latinx                                          .305                 .605

Constant                                                                .001                 .183                                                                            

Note. FRL = Free and reduced lunch; Needing More Assistance? = Were there parts of the college search and/or application process you felt you needed more assistance or information?; (1) = Student met with school counselor for indicated contact type, qualified for FRL, and/or felt they needed more assistance/information.

 

 

 

Of the variables, four did not have significant group differences: ethnicity, concerns about grades, goal setting, and perceptions of further need regarding postsecondary topics. But, FRL status, GPA, college planning contact, and attendance contact with school counselors all had significant group differences as to whether a student enrolled at least once in a postsecondary institution or not within 5 years of high school graduation. Specifically, students who participated in FRL programs were 22.9% less likely than those who did not participate in those programs to attend either a 2- or 4-year college. Students who met with their school counselor regarding attendance were 24.6% less likely to attend a postsecondary institution during the same time frame. The odds for students with higher GPAs (95% CIs [1.93, 2.55]) to enroll in a postsecondary institution at least once were 122% higher than for those with lower GPAs. The likelihood for students to attend a 2- or 4-year postsecondary institution at least once in the 5 years post-graduation was 43.6% higher for those who met with their school counselor concerning college planning than for those who did not.

 

Based on the variables, the analysis also predicted if a student would enroll in a postsecondary institution within 5 years of high school graduation. The model classified 69.8% of the cases correctly regarding if a student enrolled at least once in a postsecondary institution based on the variables introduced in our study.

 

Interesting information regarding postsecondary enrollment and GPA was uncovered during the data analysis portion of this process (see Table 2). There were a significant number of students who did not enroll in postsecondary institutions despite having above a 3.0 GPA. In addition to this, there were significantly more students who had a GPA between 2.0 and 3.0 who did not enroll in a postsecondary institution, even though their grades were more than sufficient to do so. It is possible that the students who had qualifying GPAs but did not appear to attend a college may have attended one that did not participate in National Clearinghouse data collection. It also is possible that students who participated in special education non-college classes artificially inflated the number of students with high GPAs.

 

 

 

Table 2

 

Variables and Average GPA

Weighted GPA Mean

Attendance                              Did Not Meet About Attendance                                    3.07

Met About Attendance                                                   2.34

College Planning                      Did Not Meet for College Planning                                2.63

Met for College Planning                                               3.06

FRL Status                               Not FRL                                                                        3.24

FRL                                                                              2.55

Enrolled at Least Once              Not Enrolled                                                                 2.45

Enrolled                                                                        3.15

Note. FRL = Free and reduced lunch.

 

 

 

Discussion

 

     It is not surprising that findings in this study support extant findings that suggest school counselor interventions positively impact student-related outcomes and constitute a source of student social capital (Bryan et al., 2011). Social capital can be defined as relationships and influencing connections that individuals have with others and the system in which they live (Coleman, 1988). In this context, our findings have important implications for school counselors, school administrators, and legislators. Additionally, the results also contribute much needed data to the existing literature examining strategic school counseling interventions and accountability in assisting students with matriculating to higher education.

 

This study supported previous findings about the influence of socioeconomic status and school-provided support in assisting students to enroll in postsecondary institutions (Martinez, 2013; Stanton-Salazar & Dornbusch, 1995). Findings indicate that students in this school district who met with their counselors for college planning were 1.4 times more likely to enroll in postsecondary institutions within 5 years of graduating high school compared to students who did not. It is reasonable to think that students who consult with their counselors for college planning have already decided they will attend a postsecondary institution; however, it is also reasonable to think that contact with counselors in relation to college planning might have encouraged some students who were not as motivated or resourceful to pursue postsecondary education. Regardless of students’ postsecondary institution intentions before school counselor contact, the fact that there is opportunity to discuss college-related information is beneficial. Either way, this finding can support the argument that school counselors need sufficient time to provide college-related services for students, which can impact their postsecondary enrollment.

 

This study further highlights that students who met with their school counselors regarding attendance were 24.6% less likely than their peers to attend a postsecondary institution within 5 years of graduating high school. It is within reason to expect that students who meet with their counselor regarding attendance are generally doing so because attendance is an issue that puts them in the “at-risk” category. This highlights the fact that students who miss school may be less engaged or have other personal and social factors occurring in their lives that hinder school performance and consequently derail them from pursuing a postsecondary college education. This information highlights the topics of prevention and intervention, both of which school counselors can and are expected to provide. However, with large caseloads and assigned duties outside of what ASCA specifies as appropriate for school counselors, they are unlikely to be able to provide adequate attention and intervention for students in need (McKillip, Rawls, & Barry, 2012). As such, this information can be useful in advocating for more time dedicated to the intentional interventions needed.

 

The other variables examined were goal setting, GPA, concerns about grades, ethnicity, and perceptions of needing more assistance with college-related items. None of these variables statistically predicted postsecondary enrollment. It is possible that because there are many different areas of goal setting, not just postsecondary goal setting, there was no correlation found. The same can be said for contact with school counselors regarding concerns about grades. It was interesting that the perception of needing more assistance with college-related items did not predict postsecondary enrollment. One reason might be that because it is a confusing process, even if students needed more assistance, it is possible they had already completed the correct steps for enrollment. Though ethnicity was not found to be statistically significant during post-hoc analysis, interesting patterns were observed.

 

Latinx students were much less likely to attend a postsecondary institution at least once, even though they did not meet with their school counselor at different rates than their peers (Stanton-Salazar & Dornbusch, 1995). This leads to discussion regarding specific school counselor interventions with Latinx students and their families. School counselors can be sources of social capital and more information is needed to identify school-based interventions that may successfully assist more Latinx students to enroll in postsecondary institutions.

 

Curiously, the mean GPAs of students who did not meet with school counselors regarding attendance and college planning, although they were lower than students who did meet, were still high enough to apply to 4-year colleges, and students would thus also have the opportunity to enroll in a 2-year institution. The same pattern was noticed between students who qualified for FRL and those who did not, and those who enrolled and those who did not. Although those who did qualify for FRL and those who did not enroll had an overall lower mean GPA, both groups still would have qualified for a 4-year institution based on mean GPAs. This leads to a discussion regarding successful school counseling interventions that can target students who qualify but do not enroll (Bozick & DeLuca, 2005; Kim, 2012; NCE, 2005; Pham & Keenan, 2011).

 

Overall, the data and the analyses supported the desired goal of this research study. In examining the variables, we were able to find supporting evidence that certain student–school counselor contacts had a statistically significant relationship to the students’ subsequent enrollment in a 2- or 4-year institution within 5 years of high school graduation. We also inadvertently discovered data that supports further research into tiered intentional interventions for students who qualify for postsecondary options but choose not to attend. Although this study highlights how school counselors are well-positioned to provide postsecondary preparation services and how students can benefit, we also hope it informs professional practice as an advocacy tool and in areas for subsequent research.

 

Limitations

It must be noted that our results are only representative of the individuals who took the Senior Exit Survey in the study sample. The results from this study cannot be directly generalized to other districts, as this district produces its own required core curriculum lessons in addition to its own exit survey. Though the number of participants is much larger than required by G*Power, there are advantages to this, as the study has the ability to detect smaller differences than if there were fewer participants. Another factor that must be mentioned is the varying degrees to which the ASCA National Model is implemented at each site. Though there were evaluations and a district push for comprehensive counseling programs at each site, some programs in the district were more fully implemented than others. It is uncertain how the level of comprehensive counseling program implementation confounds the results. Further research examining this topic and caseload size would be beneficial.

 

Additionally, a limitation that must be mentioned is that even though there are 3,600 2- and 4-year postsecondary institutions that participate in providing NSCH enrollment data, there are higher education institutions that do not participate. If institutions choose not to participate or if they do not receive federal financial aid, such as international institutions, students’ postsecondary enrollment data will not appear if they enroll in these institutions. Also, trade schools that help postsecondary students with skills are not included in this data. Hence, some of the students in this cohort who did not show up as having enrolled in postsecondary colleges might have enrolled in these other postsecondary institutions.

 

Furthermore, because of the limitations of the data collected, it was difficult to ascertain the quality of the contact that students had with their school counselor; for example, who initiated the meeting, how frequently and for how long did they meet, and what was the quality of their encounter? Related to data limitations, closer examination of small n-size student ethnicity groups should be conducted as well, as there may be factors unique to them. Lastly, as this was a correlational study, findings do not show causality. Future investigations should further explore the student–counselor dynamic and what characteristics may lead to more successful student outcomes related to postsecondary enrollment. Also, future studies should examine students’ experiences with counseling during high school as it relates to their persistence in college enrollment, which our study did not address.

 

Implications for School Counseling

     This study has some important implications regarding high school counselors and college counseling. For many students, school counselors serve as bridges to social capital in the college attainment process. Although there are a variety of factors that influence student postsecondary enrollment, two specific contacts with school counselors in this district were significantly related to the likelihood of attending a postsecondary institution. Specifically, contact with school counselors regarding attendance was associated with a decreased likelihood of postsecondary enrollment, while contact with school counselors about college planning was associated with a higher likelihood of postsecondary enrollment. Though the study was exclusive to one particular school district, the demographic makeup is not unique. The findings of this study point to the need for school counselors to meet with their students regarding college-related topics, and a need to pay attention to students who have attendance issues because of the likelihood of them being at risk for not succeeding academically. Also, our findings indicate that attention needs to be given to Latinx students and students from lower socioeconomic backgrounds in order to help improve their access to higher education.

 

The obstacles school counselors face with regard to caseload size and non-counseling administrative duties severely hinder their ability to meet the needs of their students. The fact that these students who had met with their school counselors for college planning showed a higher likelihood of attending a postsecondary institution clearly supports the fact that school counselors can play a significant role as sources of social capital for students in postsecondary enrollment.

 

Because this study only examined a limited number of college-related school counselor contacts, future studies should investigate the quality, type, and frequency of school counselor contact that positively influences students’ postsecondary success. Future studies should clearly operationalize each type of contact that goes beyond a binary data type. Researchers also should consider investigating associations among high school counselor–student contacts and college graduation rates and success, as the present study only examined college enrollment and was not explicitly related to college success. Quantitative research on tiered interventions, focused on the students with college-qualifying GPAs who chose not to attend, and qualitative research to examine reasons why, would be practical next steps.

 

Findings in this study bear implications for school counselor training. We believe that it is important to prepare school counselors-in-training to identify and become skillful in providing the types of school counseling services that contribute to students’ college and career readiness. For example, counselors-in-training should be trained to identify and intervene with students who have attendance issues and are at risk for not succeeding academically, and understand that the likelihood of attending college is significantly lower for those students than their peers. In preparing school counselors to collect data and create comprehensive programs that reach all students, counselor educators are training change agents who can provide evidence to administrators that school counselors positively influence students. An implication for school counselors is that data on their interactions with their students at the school site level are important sources of evidence, which they can use to advocate for themselves and their services to students.

 

Overall, it seems that school counselors can positively influence their students despite negative environmental factors outside of school. School counselors serve as sources of social capital for students, which helps student outcomes. Lastly, it is imperative that school counselors self-advocate and provide intentional interventions to at-risk populations who do not have as much social capital in the educational system as compared to their more advantaged counterparts.

 

 

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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Angela K. Tang, NCC, is an assistant professor at the University of San Francisco. Kok-Mun Ng is a professor at Oregon State University. Correspondence can be addressed to Angela Tang, 2130 Fulton St., San Francisco, CA 94117, atang15@usfca.edu.

Humanistic Learning Theory in Counselor Education

Katherine E. Purswell

 

The purpose of this paper is to explain how humanistic learning theory is applicable to current counselor education practices. A review of humanistic learning theory and the rationale for the application of the learning theory to counselor education provide a framework for application of these concepts to counselor education classrooms. Specifically, a person-centered framework is applied to the seeming incompatibility of external accreditation standards and humanistic learning theory. I propose suggestions for implementing humanistic, person-centered learning theory within counselor education programs and courses, focusing special attention on the attitudes and values of the counselor educator as these principles are applied.

 

Keywords: humanistic learning theory, person-centered theory, counselor education, accreditation, attitudes

 

 

With the philosophical shift in the mental health field from a meaning-making, holistic model of mental health toward a reductionistic, medical model of mental health, counselor preparation programs have adapted by increasing the emphasis on measuring outcomes, sometimes at the expense of focusing on aspects of counseling that are less easy to quantitatively assess (Hansen, 2009). Furthermore, external realities such as university policies and accreditation requirements have put pressure on programs and faculty members to focus more on measurable outcomes. In many counselor education programs, external requirements come in the form of the Council for Accreditation of Counseling and Related Educational Programs (CACREP; 2015) standards. With the advent of the 2009 standards, the focus in counselor education changed from program-level evaluation to directly assessing student outcomes (Barrio Minton & Gibson, 2012), a trend consistent in higher education (Penn, 2011). Although the admirable intention of accountability measures is to ensure quality programs and competent counselors, these systems do not provide incentives for counselor educators employing pedagogy that emphasizes process and critical thinking over product and knowledge retention.

 

Many counseling faculty ascribe to a humanistic way of viewing people, including students, and the increasing focus on outcomes over process may create dissonance for these counselor educators. They can feel internal as well as external pressure to adopt a more didactic or reductionistic form of teaching that does not fit with their philosophy of education (Hansen, 2009). This paper is directed at person-centered counselor educators who wish to teach in a more humanistic way but feel constrained by the current system. This paper also may be helpful for other counselor educators who wish to explore humanistic teaching. The purpose of this article is to demonstrate that counseling faculty can apply a person-centered learning philosophy to counselor preparation settings within the reality of external requirements intended to ensure quality in counselor preparation programs. Because the person-centered teaching literature is not sufficiently robust to accomplish this purpose, I will also draw from humanistic learning theory. First, I provide an overview and rationale for humanistic learning theory and then discuss the application of person-centered concepts, within the context of humanistic learning theory, to counselor preparation settings. When a view is specifically person-centered, I will use that term. Otherwise, I will refer to humanistic learning theory, which encompasses person-centered learning theory.

 

Humanistic Learning Theory

 

 Humanistic learning theory is grounded in the philosophy of humanistic theories of psychology, including person-centered theory (Gould, 2012). Primary contributors to humanistic learning theory include Arthur Combs, Carl Rogers, and Malcolm Knowles, all of whom believed the goal of education is to facilitate students’ development and self-actualization (Combs, 1982; Gould, 2012; Rogers, 1951). Therefore, humanist educators have an unwavering trust in the individual’s growth capacity and view self-directed learning as most facilitative of growth (Combs, 1982; Knowles, 1975; Rogers, 1951). Additionally, humanistic theorists hold a phenomenological view of humans in that they believe each person’s view of the world is reality for that person and that learning is motivated by personal need based on one’s internal frame of reference (Combs, 1986; Rogers, 1951). For example, a student with low self-efficacy might not attempt difficult projects because of a belief that “I am not capable,” whereas a student with a high level of self-trust can go beyond the direct instructions of an assignment to tailor the assignment to fit their learning needs. Highly self-actualized individuals view themselves as dynamic beings who are constantly growing and changing (Knowles, 1975; Tolan, 2017).

 

In general, humanistic learning theorists define learning as the holistic growth of the person, including cognitive, emotional, and interpersonal domains (Combs, 1986; Dollarhide & Granello, 2012; Rogers, 1957, 1989). They tend to focus less on accumulation of knowledge and more on how the learner’s way of being in the world impacts the integration of skills and knowledge (Combs, 1986; Kleiman, 2007). This view of knowing requires a paradigm shift for the person who tends to describe learning as the acquisition and application of knowledge. In particular, learners who have learned to approach assignments or classes with a grade-based mentality (e.g., “What do I need to do to get an ‘A’?”) may have difficulty changing, or even understanding the rationale for changing, their focus to a learning-based mentality (e.g., “What do I need to learn to positively impact my personal and professional development?”).

 

Humanistic learning theorists avoid teacher-directed learning, defined as transmission of knowledge, because they believe the most important learning and growth cannot be transmitted directly from person to person (Knowles, 1975; Rogers, 1957, 1989). Rather, they believe knowledge integration is a natural process occurring in a facilitative environment (Rogers & Freiberg, 1994). Because learning requires this environment, humanistic educators focus first on themselves and their ability to provide that environment (Combs, 1982; Rogers & Freiberg, 1994). In this article, the term educator is used in the broadest sense of the word to mean a facilitator of learning.

 

Rogers’s Conditions in Humanistic Learning Theory

Most humanistic learning theorists base their view of the educator–learner relationship on Rogers’s (1957) three therapist-provided conditions for personality change: congruence, empathic understanding, and unconditional positive regard (Combs, 1986; Mearns, 1997; Rogers & Freiberg, 1994). In an educational setting, empathic understanding, which Rogers (1951) considered a sensitive understanding of a person’s internal frame of reference, involves focusing on the person rather than only on course content (Mearns, 1997). For example, the educator also would value and empathize with learners’ reactions to course content as well as other circumstances in learners’ lives that might impact their experience in the class.

 

Unconditional positive regard is an experience of accepting and prizing another person regardless of whether one agrees or disagrees with the person’s behaviors or ideology (Rogers, 1957). Rogers and Freiberg (1994) described unconditional positive regard as “a basic trust—a belief that this other person is somehow fundamentally trustworthy” (p. 156). This trust differentiates unconditional positive regard from the common use of the term acceptance. In a classroom setting, unconditional positive regard for students can mean valuing and respecting students wherever they are in their growth processes and trusting they are moving toward growth as they are ready or able (Kunze, 2013). For example, if a student struggles to accept feedback in supervision, the counselor educator will accept the student in that moment and trust that there are valid reasons for the student’s difficulty. This acceptance is an attitude and does not mean educators abandon their professional gatekeeping roles.

 

Congruence, also called transparency in a classroom setting, involves openness to one’s experience within a relationship, including an acceptance of one’s own feelings or desires at any moment, even if one chooses not to act upon those feelings (Mearns, 1997; Rogers, 1951; Rogers & Freiberg, 1994). Transparency is closely tied to a non-defensiveness that promotes openness rather than debate as well as the formation of respectful, trusting relationships between educators and learners (Mearns, 1997). These trusting relationships form the basis for open dialogue.

 

The result of the interaction between these conditions can be transformational for students in the classroom. When an educator makes a genuine effort to help a learner feel understood rather than evaluated, the learner is more free to stop judging or evaluating oneself and to creatively explore the learning environment with the security of knowing that any ideas, even those that conflict with the educator’s views, will be respectfully acknowledged and discussed (Combs, 1982; Rogers & Freiberg, 1994). Meaningful learning can occur in an environment in which the contributions and ideas of learners are valued just as much as those of the educator (Kleiman, 2007). Humanistic educators strive to provide some level of Rogers’s (1957) three conditions to all learners.

 

Rationale for Use of Person-Centered Learning Theory

 

The goal of facilitating relationships in a learning environment characterized by the person-centered conditions of congruence, unconditional positive regard, and empathy is to provide learners with the opportunity for the growth and development of the whole person (Dollarhide & Granello, 2012; Rogers & Freiberg, 1994). Some of the results of such a learning environment are a deeper understanding and acceptance of oneself, a strong connection and openness to the experiences of others, and the development of skills and knowledge to facilitate the growth of both the individual and society. Because of these outcomes, a person-centered approach to learning is an appropriate match for counseling faculty and supervisors who believe these growth processes are key purposes of training counselors (Combs, 1986; Dollarhide & Granello, 2012).

 

One of the primary goals of counseling faculty is to develop the counselor-in-training’s (CIT’s) belief system about counseling and about oneself as a counselor (Combs, 1986; Gibson, Dollarhide, & Moss, 2010). From a phenomenological perspective, beliefs influence behavior; therefore, person-centered counseling faculty can focus on helping CITs develop their own beliefs about themselves in the context of counseling relationships (Combs, 1986; Dollarhide & Granello, 2012). When counseling faculty facilitate genuine, accepting, and empathic relationships between themselves and learners and among learners, they create an environment in which CITs are free to examine those beliefs that are both more and less accepted by society and then to modify those beliefs in ways that are more helpful (Mearns, 1997). For example, if a CIT holds stereotypical beliefs about a certain population, the CIT will be better able to express and challenge those beliefs in an open rather than judgmental environment.

 

Additionally, in a person-centered learning environment, CITs develop confidence in their abilities to find creative responses to difficult situations, such as client challenges and ethical dilemmas (Combs, 1986). Alternatively, when CITs feel they must act a certain way, they can learn to say the right words but fail to internalize a belief system that is meaningful to them. Therefore, when they are challenged or when the external evaluator is no longer present, they will quickly fall back into arguably less helpful ways of being with clients, such as giving advice. By offering a person-centered learning environment, counseling faculty help students meet CACREP standards related to facilitating a helping relationship (CACREP, 2015, 2.F.5.).

 

Relatedly, person-centered counseling faculty can utilize the learning environment as a microcosm of the helping relationship to allow CITs to experience the type of relationships counseling faculty hope they will provide their clients (Combs, 1986). Rogers (1957, 1989) argued that educators may foster the values and attitudes of a helping relationship by providing those same values and attitudes to learners. Although the professor–student relationship differs from the counselor–client relationship, the basic attitudes (care, warmth, prizing), values (worth of the person), and purpose of the relationship (growth) remain the same (Mearns, 1997). Most students in counselor education programs are intelligent and able to accomplish the academic work, but the relational skills necessary for an effective counselor cannot be memorized or studied for (McAuliffe, 2011; Nelson & Neufeldt, 1998). Therefore, it is critical that counseling faculty provide experiences that facilitate the development of relational abilities.

 

In addition to developing intrapersonally and interpersonally, CITs must develop good judgment and the ability to critically reflect on their counseling practice, including their work with clients and both current and future educational experiences (McAuliffe, 2011; Nelson & Neufeldt, 1998). Both the ACA Code of Ethics (American Counseling Association [ACA], 2014) and many state laws require new and experienced counselors to continue to seek professional development, and students need to be able to evaluate the training they are receiving. Additionally, in their analysis of extensive interviews with master therapists, Skovholt and Rønnestad (1992) found that those therapists considered continual reflection on their experiences and their growth process to be a key aspect of their professional growth. This finding supports King and Kitchner’s (2004) reflective judgment theory. They posited that as individuals progress in their development, they move on a continuum from viewing knowledge as truth that can readily be conferred by experts to seeing it as something that can be approximated based on what is known but can never be fully obtained because of the fallibility of human knowing. Counselors whose beliefs fall toward the reflective judgment end of this continuum will not assume that something must be true just because a professor or trainer told them it is the best way to do it. In addition, they will be more open to many views of the world and will also be able to critically yet nonjudgmentally evaluate those perspectives. Counselors are frequently required to tolerate ambiguous situations in which there is no clear right or wrong answer (McAuliffe, 2011; Skovholt, Jennings, & Mullenbach, 2004). Person-centered educators aim to foster a tolerance of ambiguity by encouraging learners and supervisees to examine the evidence themselves rather than implying that there is only one answer or one response to a given counseling concern or question (Rogers, 1951). The facilitation of open-mindedness in this way is relevant to CACREP standards related to diversity and advocacy.

 

CITs need to be able to address needs from clients with diverse backgrounds and expectations (CACREP, 2015, 2.F.2.; McAuliffe, 2011). One key aspect of multicultural competency is for counselors to be aware of their own attitudes, biases, and beliefs (Arredondo et al., 1996). Additionally, counselors must be able to think critically about the impact of their personal values on others (CACREP, 2015). A humanistic learning environment provides the opportunity for in-depth self-understanding and critical thinking (Combs, 1986; Dollarhide & Granello, 2012). Rogers (1951) described people moving toward self-actualization as “necessarily more understanding of others and . . . more accepting of others as separate individuals” (p. 520). This attitude embodies that of a multiculturally competent counselor (Arredondo et al., 1996).

 

Objectives of a Humanistic Learning Environment

When educators provide the environment described above and students begin to take responsibility for their own learning, certain results related to this self-actualization process can be expected. One key outcome of the humanistic approach to learning is a deeper understanding of self (Dollarhide & Granello, 2012), an important characteristic of a counselor. Increased self-understanding can lead to deeper learning. Learning can be enhanced when adult learners are able to accept themselves as they are while continuing to work toward growth (Knowles, 1959; Kunze, 2013). Similarly, Combs (1982) indicated that highly self-actualized individuals tend to view themselves in a positive way while honestly accepting their areas for growth, an attitude that leads to freedom to take more risks in educational settings. For example, learners who do not base their self-worth on grades might feel more free to focus on the meaning class material has for their future careers rather than on retaining facts in order to make a high grade in the class. In clinical classes, supervisees who have both a sense of self-worth and an openness to growth are more likely to be authentic with their clients and supervisors as well as less concerned about finding the “right” thing to say, and can focus more on what is most helpful in the context of that specific counseling relationship rather than being self-focused on performing well. Further, when learners are given substantial control over their own learning, they are better able to regulate their own processes of thinking and learning, leading to greater integration of the material (McCombs, 2013).

 

A humanistic learning environment also promotes a sense of care, acceptance, and respect toward individuals in society as well as a connection to the human condition (Combs, 1982; Knowles, 1959; Rogers, 1951). Combs (1982) argued that when learners feel a sense of belonging with those around them, they naturally become curious about their peers’ interests, and thus their learning opportunities are expanded. Rogers (1951) believed that when a person can accept one’s own experience, the person is free to be more open to and accepting of the experiences of others. Similarly, Combs (1982) wrote that highly self-actualized people can “confront the world accurately, realistically, and with a minimum distortion” (pp. 106–107). This openness to their experiences impacts their problem-solving abilities because they have more perceptual information from which to make decisions. In a classroom setting, this connection or sense of belonging can result in positive, in-depth group discussions that facilitate the learning of all involved beyond what an individual instructor could accomplish by sharing only one perspective. Further, an openness to the experience of others can lead to challenging one’s implicit or explicit beliefs about groups of people who have previously been seen as “other.” In clinical settings, supervisees will undoubtedly be exposed to individuals who hold differing beliefs, and an openness to their own experiences can help supervisees work better with these clients.

 

Concrete knowledge and skills are an outcome in humanistic learning theory, though they are generally considered more of a byproduct than the primary focus of learning. Rogers (1951) stated that one of the goals of learning is to develop knowledge relevant to the specific problem of focus, as well as to develop strategies for acquiring knowledge for new problems. Knowles (1959) noted the importance of acquiring skills that will aid a person in reaching their full potential and allow that person to positively influence society. Furthermore, Combs (1986) emphasized that knowledge leading toward self-actualization does not have to be academic. These humanists believed that learners who experience a facilitative learning environment will better retain knowledge and skills because they will have critically examined, applied, and connected it to their lives (McCombs, 2013).

 

Other Considerations in a Humanistic Learning Environment

Because application of humanistic learning theory requires a paradigm shift for both educators and learners, some learners may struggle to feel comfortable with the idea that the educator’s responsibility is to facilitate a learning environment and the learner’s responsibility is to pursue growth (Mearns, 1997). Many learners have grown up in educational environments where acquisition of knowledge was almost exclusively the goal of learning, and an educator who presents them with a different way of learning may induce stress. However, person-centered and humanistic learning theorists have emphasized that empathically helping students in the process of gaining self-responsibility helps the whole person develop (Knowles, 1975; Rogers & Freiberg, 1994; Smith, 2002).

 

Providing a warm, transparent, empathic environment does not preclude counselor educators from giving students feedback that may challenge them. When students struggle, person-centered and humanistic educators try to develop an empathic understanding of the struggling student’s view of oneself, to be accepting of that view, and to be transparently honest with the learner about his or her standing in the program. This conversation can involve counseling the student out of the program by communicating understanding that counseling may not be a good fit with the student’s current development. The educator attempts to make such discussions a collaborative effort in promoting the learner’s growth rather than a communication that the learner is failing (Dollarhide & Granello, 2012).

 

Application of Person-Centered Learning Theory in Counselor Education

    

     Counseling faculty today are not only tasked with helping students develop their growth potential and learn the process of becoming effective counselors, but are also required to engage in assessment activities in addition to many other roles (CACREP, 2015). The purpose of the following section is to describe some specific ways in which a humanistic theory of learning can be applied to teaching and accountability measures.

 

Teaching

Given that the educator–student relationship is a model for the counselor–client relationship, and that students must feel accepted and understood in order to learn, the person of the educator is crucial in a humanistic classroom (Combs, 1982; Rogers, 1951). Of utmost importance is the counseling faculty member’s belief in the growth tendency of the human being. The attitudes of congruence, unconditional positive regard, and empathic understanding for the learner’s perceptual world are predicated upon this foundation, and any practical intervention in the classroom must be firmly based in those attitudes rather than adherence to a specific technique. However, there are specific classroom practices that are more facilitative of a humanistic way of learning than others.

 

Lecturing and other forms of direct knowledge transmission are generally considered among the least person-centered methods for learning because they are typically based on a power differential in which the teacher is considered the expert (Rogers & Freiberg, 1994). Freire (2011) described this type of teaching as a banking system of education because it involves teachers “depositing” information in their students’ heads, and he compared it to a system of education in which the students are active participants in deciding what is most important to learn and how. He believed students who were more active and took more responsibility for their own learning were better able to critically question their own and others’ beliefs and thus promote growth. This assertion does not mean lecture is never used or valuable in a person-centered classroom (e.g., Cornelius-White, 2005), but the person-centered educator works to have an attitude of humility and collaborative exploration (Combs, 1982; Dollarhide & Granello, 2012; Freire, 2011; Nelson & Neufeldt, 1998). A person-centered theory of learning requires the counseling faculty to give up much of their power and trust the learners’ ability to contribute equally to the learning environment.

 

Person-centered counseling faculty might also relinquish power regarding learning objectives for individual learners (Knowles, 1975; Rogers & Freiberg, 1994). The educator can have broad goals for the course, but counseling faculty can engage CITs in developing their own specific learning objectives and in deciding how those objectives will be met. Although it is clearly not possible to meet the needs of every individual in a course, counseling faculty can address the most common learning needs within the structure of the course and provide resources for individuals with unique learning interests (Cornelius-White, 2005; Knowles, 1975; Mearns, 1997). Projects proposed by students exemplify a humanistic-oriented way of helping students meet their learning objectives because self-chosen projects tend to be based on problems that are of relevance to the students (Rogers & Freiberg, 1994). Humanistic counseling faculty give students responsibility for the creation and implementation of projects and act as a resource when assistance or experience is needed. Projects that provide a resource or service to the community can help students reach learning objectives in an experiential way (Burnett, Long, & Horne, 2005; Svinicki & McKeachie, 2011) and meet CACREP standards related to advocacy and diversity. In one classroom, student journal entries indicated that service learning increased the students’ “awareness, knowledge, responsibility, and skills related to cultural, social . . . and civic concerns of diverse communities” (Burnett et al., 2005, p. 166). Educators also may encourage the self-direction of students by engaging students in posing a large-scale problem and giving the students the responsibility to investigate and propose possible reasons for the problem and ways to address the problem (Rogers & Freiberg, 1994).

 

One way that person-centered counseling faculty help CITs develop critical thinking is to place responsibility for learning upon the learners (Combs, 1986; Mearns, 1997). Knowles (1975) described self-directed learning as students taking “the initiative, with or without the help of others, in diagnosing their learning needs, formulating learning goals, identifying human and material resources for learning, choosing and implementing appropriate learning strategies, and evaluating learning outcomes” (p. 18). However, he realized that the typical student was not socialized to learn this way; therefore, he emphasized the importance of using small steps to facilitate self-direction. Although person-centered counseling faculty do not take responsibility for CITs’ learning, they do feel much responsibility to students to provide a facilitative environment by developing meaningful relationships with CITs, serving as resources, providing needed supervision, and making necessary changes to the environment as learners pursue their growth process (Dollarhide & Granello, 2012; Mearns, 1997). Teaching CITs to think for themselves and helping them develop the basic attitudes toward people that are facilitative of change will give beginning counselors the tools to respond to difficult or unique counseling situations and to know how to find the type of supervision or support they need.

 

Ethical and legal issues are another important dimension for CITs (ACA, 2014, F.7.e., F.5.a.; CACREP, 2015, 2.F.1.), and one for which a humanistic approach to learning is particularly appropriate because of the focus on helping learners develop the ability to critically think through problems (Knowles, 1975). One way that person-centered counseling faculty can model ethical principles is by giving their students a full disclosure of what to expect from a humanistic-oriented learning environment. CITs need to be informed of expectations regarding their responsibility for learning, expectations for self-disclosure, and how grades will be assigned (ACA, 2014, F.9.a.; CACREP, 2015, 2.D.; Morrisett & Gadbois, 2006). Although these disclosures are necessary in any classroom, special clarification of the differences between a humanistic learning environment and a typical classroom may be necessary to help decrease learners’ anxiety about an unfamiliar learning environment (Knowles, 1975). Counseling faculty can emphasize that grades will not be reflective of learners’ self-disclosure, but they also note the role of honesty about one’s experience in facilitating growth (ACA, 2014, F.8.d.). Finally, counseling faculty can clarify appropriate faculty–student roles (ACA, 2014, F.10.; Morrisett & Gadbois, 2006). This may be particularly important in a humanistic classroom where the power differential between faculty member and student is decreased.

 

Teaching from a person-centered perspective is not an all-or-nothing endeavor. Just as each of the attitudes of a person-centered educator lie on a continuum, so do activities that may be utilized in the classroom (Rogers & Freiberg, 1994). For example, self-assessment and student-directed inquiry are on the more purely humanistic side of the spectrum while lecture and questioning are on the teacher-focused extreme. Projects, portfolios, and role-plays fall somewhere in the middle. Additionally, person-centered counseling faculty may choose to assign one self-directed project and several teacher-directed assignments for practical reasons or because of their personal comfort level.

 

     Accountability. One purpose of accountability measures, such as licensure and accreditation standards, is to confirm that individuals are qualified to provide the services they are offering, and institutions that make some statement to the public about the qualifications of an individual also have a responsibility to that public to graduate only those who meet such qualifications (Mearns, 1997). From a purely theoretical person-centered perspective, such external requirements as CACREP standards and the grades required by universities represent an external locus of control and could impede the process of learning by causing the learner to conform to external methods of evaluation (Gould, 2012; Rogers & Freiberg, 1994). Ideally, individuals would pursue learning solely out of an intrinsic desire for growth, and facilitators of learning would not have to worry with grades or formal assessments. Rogers disliked summative assessment because it implied that a person had reached an endpoint (Mearns, 1997), and person-centered educators believe growth is a dynamic process (Knowles, 1959; Rogers, 1957). However, from a practical perspective, accountability is necessary, both at the course level and the program level, to ensure CITs are adequately prepared and to protect students from programs that purport to train counselors but do not have sufficiently rigorous standards to adequately prepare their students for the work of effective counseling.

 

CACREP standards are aimed at ensuring that counseling programs produce competent counselors. Although many practices required to meet accreditation standards, such as the use of program-wide rubrics for specific classes, are not consistent with a person-centered and humanistic approach to learning (Hansen, 2009), person-centered educators can find ways to work within this context to maintain a facilitative learning environment. One possibility is for counseling faculty to give students the learning objectives for a certain course or rubric for a key assessment and allow students to create individual projects or products that will show their competency in the learning outcomes the standard or assessment is intended to address. Another option is the use of portfolios to measure some of the learning outcomes (Barrio Minton & Gibson, 2012). These alternate assignments are not intended to be viewed as ways of circumventing the CACREP standards, but as ways of meeting them via practices that are most meaningful for students and that best facilitate their learning.

 

Although person-centered counseling faculty have to operate in a learning environment that emphasizes external accountability requirements, they do not have to give up their approach to learning (Hansen, 2009; Mearns, 1997). Even if program policies require some specific assessments, counseling faculty have flexibility with other measures of learning outcomes. Furthermore, they can frame what they are already doing in terms that appeal to accreditation reviewers. Mearns (1997) argued that person-centered teachers use a great deal of diagnostic and formative assessment as they help CITs develop learning objectives and assess whether those are being met. The type of assessment must fit the outcome desired (Cobia, Carney, & Shannon, 2011). If counseling faculty value process over the product, then they will focus on both formative and summative assessment throughout the process, such as the use of embedded assessments (Svinicki & McKeachie, 2011). Contracts are one form of assessment that encompasses aspects of diagnostic, formative, and summative assessment and also rely on the self-direction of the individual (Knowles, 1975; Rogers & Freiberg, 1994). With the use of contracts, each learner creates individual learning objectives and a plan for accomplishing the objectives. Once the educator and the learner agree on the terms of the contract, it is used to guide the learner throughout the course. At the end of the course, the learner completes a self-assessment on whether the contract has been completed sufficiently. The counseling faculty member typically has final authority over the grade the student assigns themself (Mearns, 1997).  Although contracts can be helpful in bridging the gap between student-directed learning and the need for accountability, their use evolves into a completely behavioral method without the attitudes that embody a humanistic learning environment (Rogers & Freiberg, 1994). For example, if a faculty member engages students in creating learning contracts but does not simultaneously demonstrate respect and trust that the learners are capable of directing their own learning, the assignment is no longer humanistic. By including the students in all aspects of the assessment process, the counseling faculty member indicates a respect for the students’ input and facilitates an internalized locus of control. By involving students in their own assessment, counseling faculty model ethical assessment procedures (CACREP, 2015, 2.F.7.) in that counselors also should seek client input before evaluating client functioning (ACA, 2014, A.1.c.).

 

     Challenges. Regardless of how much an educator trusts the self-actualizing tendency in others, there are instances in which the timeline of the learning institution does not allow students sufficient time for their growth process (O’Leary, 1989). Person-centered counseling faculty do not see students as failing, but continuing their development in an environment that is more conducive to their current growth process. When a student needs to be counseled out of the program, counseling faculty are honest and empathic (Mearns, 1997). Maintaining an attitude of unconditional positive regard does not mean thinking everything a student does is fine. However, when dismissing a student from a program, counseling faculty work to maintain an empathic, caring relationship throughout the process in hopes that the student might continue to feel valued as a person by the counseling faculty.

 

     Limitations. This approach may not be a good fit for all counselor educators, particularly those who do not identify with more humanistic modes of learning. In addition, this approach to learning is not always appreciated by all students. Some students prefer the teacher tell them what they need to know and how to demonstrate their knowledge. The idea of taking responsibility for their learning can be stressful for some students. Counselor educators utilizing this theory of learning need to assess whether such stress levels are facilitative or debilitating for learners.

 

Conclusion

 

Humanistic learning theory is a way of approaching counselor education that emphasizes the humanistic underpinnings of the profession rather than the current reductionist approach of diagnosis and skills development (Hansen, 2009). Person-centered counseling faculty can utilize humanistic learning theory to facilitate an open, accepting, and understanding environment in which they engage CITs in directing their own learning. Counseling faculty can focus on CITs’ attitudes and beliefs about people in relation to knowledge and skills. Person-centered counseling faculty hope to foster CITs’ self-understanding, caring and accepting attitudes toward people, and the acquisition of concrete knowledge and skills needed in the counseling profession. Counseling faculty using humanistic learning theory engage learners in assessment of their learning as much as feasible, while honoring the realities of external evaluation through accreditation.

 

 

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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Katherine E. Purswell is an assistant professor at Texas State University. Correspondence can be addressed to Katherine Purswell, 601 University Dr., EDU 4019, San Marcos, TX 78666, kp1074@txstate.edu.

 

Neuroscience for Counselors: Recommendations for Developing and Teaching a Graduate Course

Deborah L. Duenyas, Chad Luke

 

In recent decades, professional counselors have increasingly focused on neuroscience to inform their case conceptualization and treatment planning with clients. With the additional lens of neuroscience, both the counselor and client can gain new understandings of the client’s issues and improve the quality of the therapeutic relationship. The benefits of integrating neuroscience into the profession of counseling (i.e., neuroscience-informed counseling) are being documented in the scholarly literature; however, information on integrating neuroscience-informed counseling into the counselor education curriculum is sparse. This article describes one teaching approach for a neuroscience-informed counseling course. The structure of the course, methods for effective instruction, and ethical and cultural considerations are discussed.

 

Keywords: neuroscience, counselor education, teaching, neuroscience-informed, instruction

 

 

Neuroscience-informed counseling is a growing force in the counseling profession (Beeson & Field, 2017). The integration of neuroscience into the profession of counseling has been evident over the past two decades. Examples include the development of neuroscience interest networks by the American Counseling Association (ACA), the American Mental Health Counselors Association (AMHCA), and the Association for Counselor Education and Supervision (ACES). There have been numerous books published that focus on neuroscience for counselors (Field, Jones, & Russell-Chapin, 2017; Luke, 2019) and an increased amount of scholarly literature focused on integrating neuroscience into counseling practice (Beeson & Field, 2017; Lorelle & Michel, 2017; Luke, Redekop, & Jones, 2018; Makinson & Young, 2012; Miller, 2016; Myers & Young, 2012).

 

Neuroscience is the study of the brain and nervous system (Kalat, 2019). Neuroscience-informed counseling involves integrating principles from the structure and function of the brain and nervous system to counseling practice (Russell-Chapin, 2016). This integrative work in counseling is being used to treat behavioral and mental health challenges (Field et al., 2017). According to Beeson and Field (2017), neurocounseling is a

 

specialty within the counseling field, defined as the art and science of integrating neuroscience
principles related to the nervous system and physiological processes underlying all human
functioning into the practice of counseling for the purpose of enhancing clinical effectiveness in the
screening and diagnosis of physiological functioning and mental disorders, treatment planning
and delivery, evaluation of outcomes, and wellness promotion. (p. 74)

 

Three methods for integrating neuroscience into the counseling profession have been identified in the scholarly literature, including neuroeducation (Fishbane, 2013), neurofeedback (Myers & Young, 2012), and the use of a metaphor-based approach (Luke, 2016).

 

The first method, neuroeducation, is defined by Miller (2016) as “a didactic or experiential-based intervention that aims to reduce client distress and improve client outcome by helping clients understand the neurological processes underlying mental functioning” (p. 105). Neuroeducation is essentially psychoeducation about the brain and nervous system. Neuroeducation can be used as an intervention to help clients understand the neurological processes that underlie their symptoms and development (Miller, 2016). Miller described various methods for integrating neuroeducation into counseling practice through the use of information on neuroplasticity, brain structures and functions, and memories.

 

     Plasticity is an object’s or organism’s ability to stretch and to be resilient. As applied to the brain and central nervous system, this is called neuroplasticity or neural plasticity, and involves “changes in the activity and connectivity of the various circuits within the nervous system [that] enable learning, encode memory, and drive behavior” (Li, Park, Zhong, & Chen, 2019, p. 44). Information on neuroplasticity and self-defeating patterns of thought and behavior may help demystify change processes.

 

Informing clients about the various brain structures and functions (e.g., brain stem, limbic, and cortical regions) can help with understanding the brain from a developmental perspective—that the brain is built to change and to be resilient (Luke, 2019). Educating clients about how their memories are encoded, stored, and accessed, drawn from the groundbreaking work of Eric Kandel (1976), can help clients gain a better understanding of their own brain and behavior (Miller, 2016). This knowledge can instill hope that although events of the past cannot be changed, the meaning of the memories associated with those events can be changed (Sweatt, 2016). Furthermore, the relational context in which change takes place can help clients’ brains overwrite rigid rules and threats about relationships learned from earlier dysfunctional relationships (Kandel, Dudai, & Mayford, 2014; Schore, 2010; Siegel, 2015).

 

A second method, neurofeedback, has been recognized as an effective treatment for reducing symptoms of various mental health concerns (Russell-Chapin, 2016). A specialized form of biofeedback, neurofeedback changes brain wave patterns to aid in the treatment of conditions such as attention-deficit/hyperactivity disorder, anxiety, depression, addiction, trauma, autism spectrum disorders, and personality disorders (Russell-Chapin, 2016). Neurofeedback is just one method that counselors can use with clients to help them understand and change the function of their brains. Additional examples include basic biofeedback tools and methods like those found on many “smart” watches and fitness trackers.

 

The third method for integrating neuroscience-informed counseling is described by Michael and Luke (2016) as using a metaphor-based approach to teaching the neuroscience of play therapy. This approach is an extension and application of that described in Luke (2016), wherein neuroscience concepts are used both as metaphors for the human experience, as well as understanding brain function. Tay (2017a) has identified the therapeutic value of metaphor and its utility in understanding language and the body. Relatedly, the practices of mindfulness and meditation often use imagery, a form of metaphor, to engage practitioners in engaging more fully in the experience (Tang, Hölzel, & Posner, 2015). As neuroscience-informed counseling continues to become integrated into the work of professional counselors, counselor educators must adapt in order to keep their coursework relevant.

 

Counselor Education and Neuroscience-Informed Counseling

 

Beeson and Field (2017), along with others (Field et al., 2017; Luke, 2017; Miller, 2016) have called for more training for counselors who seek to integrate neuroscience into their practice. They also have identified the challenges associated with infusing neuroscience into counseling courses. The Council for Accreditation of Counseling and Related Educational Programs (CACREP; 2015) standards now require competency in “the biological, neurological, and physiological factors that affect human development, functioning, and behavior” (p. 10). CACREP standards, along with growing momentum in the field, support the development of a course designed specifically for integrating neuroscience for counselors. The AMHCA clinical training standards include recommendations for competence in understanding and applying the biological bases of behavior. The AMHCA standards outline basic knowledge and skills, which include integrating research into practice, as well as clinical interventions.

 

Field et al. (2017) laid a foundation for incorporating neuroscience-informed counseling across the CACREP curriculum. This approach addresses neuroscience in pre-existent courses, yet there is limited availability of literature on how to teach a graduate content course in neuroscience-informed counseling. In the absence of established models for teaching a course in neuroscience-informed counseling, counselor educators and others can feel at a loss for how to proceed. The purpose of this article is to provide recommendations for developing a neuroscience-informed counseling course designed for graduate students. This includes the course structure (e.g., content and resources), methods for effective instruction (e.g., teaching approach and assignments), and ethical considerations.

 

Course Structure: Content and Resources

 

The Neuroscience for Counselors course builds on prior core counseling courses, including counseling theories and the fundamentals of counseling. As such, it represents an extension of counseling theory and fundamentals and is not intended to be a substitute or replacement. Neuroscience-informed counseling explores how different counseling theories and interventions influence and change neurobiology and help facilitate client wellness.

 

The Neuroscience for Counselors course was offered to master’s students enrolled in a CACREP-accredited counseling program at a mid-size university in the northeast region of the United States. The course was offered as an elective that fulfilled three graduate credits toward degree completion. The course was designed as an introduction to neuroscience research and clinical interventions for counselors. Specific attention was given to reviewing the structures, systems, and functions of the brain. Psychodynamic, behavioral, humanistic, and constructivist counseling theories were explored in relation to neuroscience research. The neuroscience of mental health disorders, such as anxiety, depression, stress, and addictions and substance use, were explored.

 

Course assignments included developing a neuroscience-informed guided metaphor; completing a brain resource book on structures, systems, and functions; dyads to practice using neuroscience-informed counseling interventions; reflection in a neuroscience process analysis log (N-PAL); and activities exploring neuroscience-informed technology. A final paper included a case conceptualization based on the 8-factor meta-model (Luke, 2017, 2019) of case conceptualization to explore their client’s presenting concerns.

 

The assigned textbook for this course was Luke’s (2016) Neuroscience for Counselors and Therapists: Integrating the Sciences of Mind and Brain, which focuses on client conceptualization, brain anatomy, various theoretical approaches, and an array of commonly diagnosed mental health concerns. The text also provides case vignettes highlighting how a student might use neuroscience-informed counseling interventions with a diverse population of clients. The first chapter of the text discusses ethical and philosophical issues related to integration. Chapter 2 presents an overview of the basic brain structures, systems, and functions, including neurons and synapses. Chapters 3 through 6 cover the major categories of counseling theories: psychodynamic, cognitive-behavioral, humanistic-existential, and postmodern and constructivist. Chapters 7 through 10 describe conceptualizing and treating anxiety, depression, stress-related disorders, and substance use disorders. The text is written for counselors and counselors-in-training who have little or no background in the physiological bases of behavioral and mental health concerns.

 

     The course instructor provided supplemental material, including magazine articles, peer-reviewed journal publications, apps, videos, websites, and links to neuroscience interest networks. For example, students were provided a link to the Neuroscience News website, which is an independent science news website that offers free cognitive science research papers, neuroscience resources, and a science social network. Also included were links to the Dana Foundation, an organization that supports brain research via grants, publications, and education, and the ACA’s Neurocounseling Interest Network. The supplemental material was selected as a method to broaden student understanding and support knowledge acquisition in neuroscience.

 

Methods: Teaching Approach and Assignments

 

Experiential education is not a new approach in higher education. Educational psychologists in the past, such as John Dewey (1938), Carl Rogers (1969), and David Kolb (1984), have laid the groundwork for the development of contemporary experiential education. Kolb (1984) defined learning as “the process whereby knowledge is created through the transformation of experience. Knowledge results from the combination of grasping and transforming experience” (p. 41). The Association for Experiential Education (AEE; 2019a) defined experiential education as a teaching philosophy “in which educators purposefully engage with learners in direct experience and focused reflection in order to increase knowledge, develop skills, clarify values, and develop people’s capacity to contribute to their communities” (para. 1). In essence, experiential education is the process of learning through experience and reflection.

 

Methods of instruction in the Neuroscience for Counselors course were consistent with the 12 principles of practice outlined by the AEE (2019b). For example, class assignments provided students with the opportunity for reflection, critical thinking, and personal application. The instructor’s teaching roles included “setting suitable experiences, posing problems, setting boundaries, supporting learners, insuring physical and emotional safety, and facilitating the learning process” (AEE, 2019b, para. 9). Sakofs (2001) cautioned that experiential activities can be misused by educators as a form of entertainment with no real educational value. The following six assignments were designed with the intention to deepen students’ understanding of neuroscience concepts as they relate to the profession of counseling.

 

Six Neuroscience Course Assignments

     Developing a neuroscience-informed guided metaphor. Historically, neuroscience has been considered the realm of the medical professional or psychiatrist who has studied the complex inner workings of the brain. Developing a neuroscience-informed guided metaphor provides counseling students the experiential opportunity of taking an unfamiliar concept or idea (i.e., using neuroscience-informed counseling) and making it more accessible by relating it to ideas they are already familiar with (Jamrozik, McQuire, Cardillo, & Chatterjee, 2016; Lawson, 2005). For this assignment, students were assigned to read the article “The Birth of the Neuro-counselor?” (Montes, 2013), in which the term neurocounselor was first used. The article introduces and encourages students to begin thinking about what it means to use neuroscience-informed counseling in practice and how it influences their professional identity as a counselor.

 

After reading the article, students illustrated a guided metaphor that could be used to inform their model of neuroscience-informed counseling practice. Students were provided with the prompt, “Neuroscience-informed counseling is _________” and then asked to fill in the blank with a noun. Students included a paragraph explaining their choice in metaphor and how they came to make that decision. Students were asked to share their metaphors with their peers in class. A student’s illustration could be a visual representation, in writing, or a combination of both. Metaphor is, simply put, the practice of describing one thing in terms of another (Tay, 2017b). More specifically, the use of metaphor increases understanding of a less well-understood concept or idea by describing it in terms of something that is better understood. In the assignment described above, students generated metaphors such as “neuroscience-informed counseling is the first mission to the moon,” “neuroscience-informed counseling is a penlight in a dark maze,” and “neuroscience-informed counseling is a puzzle” to be solved. Lawson (2005) extolled the virtues of metaphors in counseling, noting that they “can help the counselor connect to the client’s world” (p. 135). The use of neuroscience metaphors, whether generated by the client or the counselor, can aid in promoting empathy and therefore trust (Luke, 2017) and can aid in learning neuroscience concepts (Michael & Luke, 2016). For example, in the wildly popular “I Had a Black Dog, His Name Was Depression” World Health Organization video on YouTube (over 9 million views as of this writing), depression is compared to a black dog that affects every facet of an individual’s life (World Health Organization, 2012). The metaphor works by comparing an abstract concept like depression with something concrete like a black dog. It enables the client to experience their depression as something happening to them, not emerging from their core self. When incorporated with relevant neuroscience information, the metaphor takes on increased significance. This black dog hijacks a person’s will, leaving them with diminished options for meaningful action.

 

Developing metaphors for the counselor’s roles when using neuroscience-informed counseling can clarify and strengthen counselor identity. When introducing this assignment, it is important to note that neuroscience-informed counseling is not its own therapeutic orientation. Whereas many graduate counseling programs have courses focused on advanced therapeutic orientations, such as solution-focused therapy or motivational interviewing, a course in neuroscience for counselors can strengthen a counselor’s current theoretical framework (Luke, 2017). For example, counselors practicing cognitive behavior therapy who learn about Hebb’s rule (1949), which states that “neurons that fire together wire together,” along with the concept of neuroplasticity, have another avenue of support for clients working to make positive behavioral changes. In this example, neuroscience can help the client gain awareness of the neurological structures that reinforce their behavior and also provide hard evidence that change is possible (Li et al., 2019). Neuroscience-informed counseling is one of many tools in the counselor toolbox. In addition to conceptualizing neuroscience-informed counseling as part of their professional identity, students also learn content knowledge of the brain’s structures, systems, and functions.

 

     Brain structures, systems, and functions book. This assignment required students to research the basic structures, systems, and functions of the human brain and design their own book. The instructor provided students black and white images of various structures of the brain discussed in the class textbook. Images included lateral and dorsal views of the brain, the two hemispheres of the brain, the three divisions of the brain (i.e., forebrain, midbrain, and hindbrain), the four lobes of the brain (i.e., frontal, temporal, occipital, and parietal), the anatomy of a neuron, and a stem chart of the nervous system tasks, including the sympathetic and parasympathetic nervous system functions. This approach is supported by works such as the Wammes, Meade, and Fernandes (2016) investigation of the neural processes of storing and retrieving memory. The authors found that drawing important words and phrases improves one’s ability to remember important concepts. Students were asked to use various mediums, including colored pencils, crayons, and markers, to label and highlight the different neuroanatomy. Students also were asked to use their class textbook to write descriptions of the functions of these parts of the brain within their assignment.

 

Mental health diagnoses can be intimidating for clients, as can the symptoms of a disorder. Anchoring a client’s experience in their neurobiology can increase their understanding of what is happening. Basic neuroscience information can empower them to learn more about, and in some ways objectify, their experience. In other words, knowledge of the underlying brain function can encourage clients to reflect on mind and body and how they interact. For example, depression is a result of brain function, but the choices an individual makes in response can be a function of the mind. In practice, clients can be led through the process of identifying brain function and mind function.

 

The brain structures, systems, and functions book assignment helps to empower students by providing them with the language and imagery surrounding neuroanatomy. Once counselors feel confident in their knowledge of basic brain regions and systems they can use it to empower clients by providing them a physiological explanation of their experiences. For example, knowledge about the autonomic nervous system can help a client struggling with generalized anxiety disorder. According to the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5; American Psychiatric Association, 2013), generalized anxiety disorder is characterized by excessive anxiety and worry that is difficult to control, with symptoms that might include restlessness, feeling on edge, being easily fatigued, difficulty with concentration, muscle tension, and sleep disruptions. Clients struggling with generalized anxiety disorder can feel as if they are in a constant state of emergency. Understanding how the sympathetic nervous system prepares the body for emergencies can help a client understand what they are experiencing at a physiological level. This can make them more receptive to interventions that activate their parasympathetic nervous system functions and move them from “fight or flight” to “rest and digest.” Once students in the course obtained content knowledge regarding the brain’s structures, systems, and functions, they applied that knowledge in dyads.

 

     Dyads. Experiential learning takes careful planning, structuring of lessons, and intentionality in teaching practices (AEE, 2019). Experiential activities such as dyads can help students learn the material through the act of “doing.” Tollerud and Vernon (2011) described the benefits of experiential learning as “promoting interest in a topic, supporting student retention of the material, and involving students in their education” (p. 285).

 

Luke (2017) outlined neuroscience concepts that can be used as interventions with clients
(e.g., memory systems, Hebb’s rule, left and right brain processing, mirror neurons, attention, and mindfulness). In the neuroscience course, students practiced discussing neuroscience concepts in dyads where they took turns acting as counselor and client. The neuroscience concepts coincided with Chapters 3–10 in the textbook. This provided practice for students using the neuroscience concepts with specific theoretical approaches (e.g., contemporary psychodynamic, behavioral approaches, humanistic approaches, and constructivist approaches), but also could align with a particular mental health diagnosis (e.g., anxiety, depression, stress disorders, and substance use disorders). For example, discussion about Hebb’s rule may apply to counselors working from a behavioral approach or counselors working with clients struggling with specific issues such as substance use.

 

The instructor provided a dyad prompt for students relating to the chapter material for that class session. For instance, the prompt for Chapter 3, Contemporary Psychodynamic Approaches and Neuroscience, was, “Tell me more about your early memories pertaining to key relationships (i.e., parents, siblings, guardians)” and “How do you feel these early memories influence your key relationships today?” The discussion prompt provided the student counselor an avenue to discuss the neuroscience concepts identified in the chapter (i.e., relationships in the brain/interpersonal neurobiology, consciousness, and memory systems) with their mock client. Students were graded on their ability to use the neuro-concepts and attend to their fundamental counseling skills (e.g., unconditional positive regard and empathy).

 

The dyad activities also highlight the positive benefits of right hemisphere to right hemisphere connections validated through neuroscience. According to Badenoch (2008), right hemisphere to right hemisphere connections are at the root of change, as interpersonal connections are rooted in the neural processes of the right hemisphere. Practicing mock counseling sessions provides students the opportunity to develop healthy relationships with their peers in class. This experience can later become a parallel process by which they use the positive experience in class with their future clients.

 

In counseling, two approaches parallel the class experience. In the first, counselors can apply the same material described above with their clients, using process-based psychoeducation. For example, the counselor can present information on the neurobiology and role of early memories, relationships (past and present), and consciousness/unconsciousness in the client’s depression. They can then ask the questions described above directly to the client. The second approach involves a Gestalt technique wherein the client’s depression, their brain, and the client themselves all sit together in the room. The client is guided through a discussion with these constituent parts in order to better understand the role that each plays in the living of the client’s life. As students completed each dyad, a system was created for them to reflect on their experience as described below.

 

     The N-PAL (Neuroscience-Personal Analysis Log). According to Faiver, Brennan, and Britton (2012), the purpose of a personal analysis log (PAL) “is to help students track their progress over the semester in terms of self-awareness and comfort level with the counseling process” (pp. 292–293). Students completed nine neuroscience personal analysis logs (N-PALS) throughout the course. Entries were made in class after each dyad. Students were given the opportunity to analyze and express their feelings in relation to the dyad activities and course material. The purpose of the N-PAL was to help students reflect on their counseling work while integrating neuroscience concepts into the mock counseling sessions with their classmates.

 

N-PALs consisted of five questions: (a) On a scale from 1–10, how confident do you feel applying the assigned theoretical approach for this dyad? (b) On a scale from 1–10, how confident did you feel using neuroscience concepts in this dyad? (c) What were some new areas of growth and development during this dyad? (d) Assess your own performance during this dyad and provide specific examples, and (e) What is your reaction to the course material (i.e., assigned reading, class lecture, videos, discussion)? The N-PAL’s structure is consistent with the experiential education principle, which states that experiences are structured to require the learner to take initiative and make decisions and be accountable for results (AEE, 2019). The questions were developed to encourage students to reflect on their dyadic experiences and think critically about their neuroscience-informed interventions while being held accountable for areas of growth and development.

 

     Exploring neuroscience-informed technology. With the increased focus on neuroscience in popular culture and media, there has been an influx of new neuroscience-informed technology. Students were asked to find three technological tools that could inform their neuroscience-informed clinical work. The tools were to fall into three distinct categories: one app (e.g., mindfulness, anxiety, or brain information app), one video (e.g., YouTube, TedTalk), and one technological application (e.g., pulse oximeter, biofeedback equipment, EEG reader). After identifying the neuroscience-informed technology tools, students posted on an online discussion board describing how they would use their identified tools in a counseling session.

 

There is an abundance of neuroscience-informed technology on the market today. Counselors recommending meditation apps or assorted TedTalks to their clients may be using this technology without awareness of their neuroscientific implications. Counselors do not have to work from memory alone but can take advantage of the growing number of resources available today (e.g., journal articles, books, apps, videos). Counselors who take advantage of resources also must be savvy consumers. For example, prior to recommending apps or videos to clients with neuroscience-related material, counselors should check the source to confirm it is reputable and use the material themselves. Whereas the neuroscience-informed technology discussion post helped to build awareness of technological tools, the final case conceptualization paper served to showcase the content students gained throughout the course.

 

     Case conceptualization. As a summative assignment, students completed a three-part case write-up that demonstrated their ability to conceptualize client issues and apply neuroscience-informed interventions. The instructor provided students with a fictional client case vignette, including biopsychosocial information. The first part of the assignment required students to use an 8-factor meta-model (Luke, 2017, 2019) to conceptualize their client’s case. This 8-factor model is a holistic model identifying eight components that every counselor must consider when working with clients: thoughts, feelings, behaviors, environments, experiences, biology and genetics, relationships, and the socio-cultural context in which the client lives.

 

Students were asked to include neuro-concepts in their discussion of each of the factors. For example, if the student identified that the client was experiencing anxious thoughts, they would include a description of how the amygdala modulates the client’s reactions to events perceived as dangerous or scary. This part of the assignment demonstrated the counseling student’s mastery of case conceptualization in conjunction with their understanding of how neuroscience concepts can influence the client’s symptoms.

 

The second part required students to review their conceptualization and write a phenomenological description of the client across the eight factors of the model. A phenomenological description provides an opportunity for students to consider, beyond the prescribed clinical note, what it might be like to “walk in this client’s shoes.” Writing a phenomenological description uses right-brain processing skills of creativity and intuitiveness. Although the description is the student’s interpretation of the client’s experience, the exercise can strengthen skills in empathic awareness and creative thinking. Thinking about the phenomenology of a client (i.e., what would it be like to walk in the client’s shoes?) can deepen therapeutic rapport, strengthen conceptualization skills, and help build empathy.

 

The third part of the assignment was for students to select a theoretical approach, along with a rationale for their choice, and create a transcript of a session with the client. The transcript had to include a brain-based counseling intervention (e.g., discussion about Hebb’s rule, neuroplasticity, or memory storage). Neuroscience is an essential tool for helping clients understand what is happening to them. For example, a client who has suffered a trauma and is struggling to understand why they cannot remember events clearly may find respite in knowledge regarding how traumatic memories are stored in their brain. Knowledge about neuroscience can help normalize and validate clients’ experiences.

 

In summary, six assignments were described above: neuroscience-informed guided metaphor; brain systems, structures, and functions book; dyads; the N-PAL; exploring neuroscience-informed technology; and a case conceptualization paper. The assignments were developed to build students’ understanding of the material and improve their ability to integrate neuroscience into their case conceptualization, treatment planning, and counseling skills. With the growth of neuroscience integration into the counseling profession, best practice dictates that ethical and cultural considerations are addressed.

 

Ethical Considerations

 

With nascent developments in the counseling profession, such as neuroscience-informed counseling, come potential risks to clients’ well-being. The ACA Code of Ethics (2014) states that “Counselors practice only within the boundaries of their competence, based on their education, training, supervised experience, state and national professional credentials, and appropriate professional experience” (Standard C.2.a). Scholarly literature has recognized the need for professional counselors to work within their scope of practice (Luke, 2019). As the counseling profession continues to integrate neuroscience into practice, the boundaries of that practice are not always clear. For instance, at what level of integration must counselors be educated in neuroscience explicitly? Who governs the practice of integration and ensures that counselors are following best practice, especially when best practice has not been established?

 

Each of the three areas described above—neuroeducation, neurofeedback, and metaphor—present distinct ethical challenges. Neuroeducation, like psychoeducation, can become too didactic and place counselors in the role of content expert, as opposed to process expert. It may be easy for counselors to share brain information with their clients, becoming dependent on sharing facts instead of sharing a process. Studies have demonstrated the potential for harm in the helping relationship when clients view helpers as aloof related to neuro-speak, as clients may feel powerless to change their neurobiology (Kim, Ahn, Johnson, & Knobe, 2016; Lebowitz & Ahn, 2014).

 

Neurofeedback can require advanced knowledge in technological interventions. For example, neurofeedback often requires the use of technological equipment to read and equalize brainwave activity. The Biofeedback Certification International Alliance (n.d.) offers a training program specifically for neurofeedback certification. With certification comes a level of oversight and guidance that promotes proper training of practitioners. However, certification is not a legal requirement to use neurofeedback in counseling practice. Therefore, what is a counselor’s ethical responsibility to acquire education in the use of neurofeedback equipment with clients? How much education is enough to be considered competent? Also, in terms of counselor identity, can neurofeedback be considered counseling or is it an adjunct to counseling?

 

Given these concerns, the use of metaphor may be a reasonable middle ground wherein counselors are still integrating neuroscience into counseling, but not to the extent that it becomes something different. The use of metaphor is less about teaching clients and more about coming to a mutual understanding of the client’s experience using terms that make sense and matter to the client (Tay, 2012). However, this approach requires the counselor to understand brain function and to stay current in the literature to ensure that the metaphor is accurate and apropos to the client situation. For example, memory has been likened to a video recording of events, yet the function of memory has been demonstrated as far more constructed than a recording of facts. In this case, memory is more like a movie wherein the recordings have been edited to tell the story based on the movie-maker’s experience and desire. It is imperative for professional counselors to consider standards of ethical practice in order to meet the ethical principles of beneficence and nonmaleficence. Similarly, counselors also have a responsibility to be aware of cultural considerations when integrating neuroscience into their counseling practice.

 

Cultural Considerations

 

There is a power differential in the therapeutic relationship, in part because of the needs and vulnerabilities that can accompany clients when seeking counseling. Clients might feel disempowered in the counseling relationship because of intersections of race, gender, age, spirituality, and social and economic status (Ratts, Singh, Nassar-McMillan, Butler, & McCullough, 2016). In addition, if counselors use language about the brain that may be perceived as intimidating or unsafe by clients, it could harm the therapeutic relationship. Integrating neuroscience into the counseling profession requires counselors to develop self-awareness surrounding neuroscience terminology and power inequalities in the counseling relationship. It is vital for counselor educators to consider the ethical and cultural implications of teaching a neuroscience-informed counseling course in order to help students learn how to facilitate a therapeutic environment where clients feel safe to process their experiences.

 

Conclusion

 

Given the benefits of neuroscience-informed counseling to treat behavioral and mental health concerns, counselor educators must begin to integrate neuroscience-informed counseling into the curriculum. Developing a neuroscience for counselors course using the aforementioned recommendations for course structure and methods for instruction is one approach to meeting this need. Assignments included a neuroscience-informed guided metaphor; development of a brain structures, systems, and functions book; dyads to practice using neuroscience-informed counseling interventions; N-PALs for reflection; a neuroscience-informed technology discussion post; and a summative case conceptualization paper. Integrating neuroscience-informed counseling into the counseling curriculum, while simultaneously addressing ethical and cultural considerations, has the potential to improve graduate students’ case conceptualizations, treatment planning, and counseling skills.

 

 

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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Deborah L. Duenyas is an assistant professor at Kutztown University of Pennsylvania. Chad Luke is an associate professor at Tennessee Technical Institute. Correspondence can be addressed to Deborah Duenyas, OMA Wing – Room 412, P.O. Box 730, Kutztown, PA 19530, duenyas@kutztown.edu.

In My Own Words: Exploring Definitions of Mental Health in the Rural Southeastern United States

Allison Crowe, Paige Averett, Janeé R. Avent Harris, Loni Crumb, Kerry Littlewood

 

The following study assessed the utility of the U. S. Department of Health and Human Services’ definition of mental health among participants in the rural Southeastern United States. Using deductive coding, qualitative results revealed that participants do not conceptualize mental health in comprehensive terms. Rather, they tend to describe mental health with a focus on cognition. The sample articulated “well-being” to describe mental health; however, they most often connected it to cognition. The findings suggest that rural communities could benefit from mental health education with a holistic approach and that the use of the term well-being provides a pathway for clinical connections. Future research should consider interviewing rural participants to gather more detail on their definitions and understanding of mental health.

 

Keywords: mental health, education, cognition, rural, well-being

 

 

Mental illness is a pervasive health care concern in the United States. Even though approximately one fifth of adults experience mental health concerns in any year, only 70% of those in need of mental health services seek care (National Alliance on Mental Illness, 2015). Because of how common and widespread mental health conditions are in the United States, mental health professionals have become increasingly aware that educating the public about mental illness is of utmost importance. Mental health literacy (MHL; Jorm, 2012), or the knowledge and beliefs about disorders that assist in the recognition, prevention, or management of a mental health concern, is one way those who are struggling with mental health concerns can manage mental illnesses more effectively. Improving MHL can have the capacity to positively impact negative attitudes, biases, or assumptions that are associated with having a mental illness as well as assist with help-seeking so those who have a mental illness will receive necessary treatment (Crowe, Mullen, & Littlewood, 2018; Jorm, 2012; Kutcher, Wei, & Coniglio, 2016). Researchers have consistently demonstrated that a stigma still exists toward seeking help for mental health concerns and that reducing that stigma is of utmost importance (Kalkbrenner & Neukrug, 2018).

 

Increasing help-seeking behaviors might best be done through first exploring attitudes and perceptions, as cognitions are closely tied to emotions and behaviors. Therefore, the current study is framed through the theoretical lens of cognitive behavioral therapy (CBT; A. T. Beck, 1970). CBT is based on the notion that how one thinks, feels, and acts are all intertwined. Specifically, one’s thoughts impact how one feels and behaves. Because of this, negative or unrealistic thoughts may contribute to psychological distress. When a person feels distressed, the way that they interpret situations may become skewed or distorted, which then impacts their behavior. From the lens of CBT, one’s decision to not seek treatment for a mental health concern may be closely tied to the thoughts and feelings they hold about negative associations about mental illness. Counselors who practice from a CBT perspective work with clients to identify and eliminate cognitive distortions in order to minimize painful emotions and promote more adaptive behaviors. CBT has been applied to diverse populations and found to be effective with various presenting concerns (A. T. Beck, 1970; J. S. Beck, 2011; Crumb & Haskins, 2017).

 

Cognitive distortions exist as they relate to having a mental health concern, and researchers have shown that rural residents with mental health concerns fear being negatively labeled, stereotyped, and discriminated against and thus are apprehensive to seek mental health care services (Crumb, Mingo, & Crowe, 2019). Therefore, it is vital that counselors and other mental health providers consider how clients’ thoughts, beliefs, experiences, and other contextual factors contribute to their understanding of mental illness. Intentional acknowledgment of the factors that influence clients’ perceptions, attitudes, and behavior may enhance treatment efficacy for rural residents (Crumb & Haskins, 2017). Along with exploring negative thoughts related to mental health, researchers also have considered MHL, or one’s understanding of mental health, as it impacts behaviors.

 

Mental Health Literacy (MHL)

 

Health literacy researchers suggest low health literacy is related to a number of negative health outcomes, including higher instances of chronic illness, lower usage of health care programs, higher costs of health care, and premature death (Baker et al., 2007; Berkman, Sheridan, Donahue, Halpern, & Crotty, 2011). The World Health Organization (WHO; 2013) posits that health literacy is more important than demographic factors (e.g., income, employment, status, education, race, ethnicity) as they relate to health status. Perhaps because of this, the importance of health literacy is well established in the health professions.

 

In a 2011 literature review on health literacy outcomes, Berkman and colleagues found that lower levels of health literacy were related to more hospitalizations, increased emergency center use, misuse of medications, confusion with medication instructions, higher death rates, and poorer overall health among the elderly. Baker and colleagues (2007) had similar findings related to the impact of poor health literacy on health outcomes. In Baker et al.’s cohort study (N = 3,260), inadequate health literacy independently predicted mortality and death because of cardiovascular disease in elderly populations. They concluded that health literacy is an influential component of overall health.

 

Compared to general health literacy, the same cannot be said specifically for MHL in the field of mental health. In fact, knowledge of mental health concerns is greatly lacking and largely ignored (Jorm, 2012). The most current study related to MHL found that MHL had a negative relationship to self-stigma of mental health concerns and help-seeking, signifying that when a person knows more information about mental health, they have less stigma about mental health concerns and engage in more help-seeking behaviors (Crowe et al., 2018). In this same study, health outcomes (i.e., blood pressure and body mass index) were assessed to test whether MHL was related to improved physical health. Results were nonsignificant, suggesting that there was not a relationship between MHL and physical health outcomes.

 

Regional disparities and sociodemographic variations in treatment utilization and efficacy reflect a crucial need for increasing MHL in rural areas in particular (Smalley, Warren, & Rainer, 2012; Snell-Rood et al., 2017). Although prevalence rates of mental health concerns are similar to urban and suburban regions, the amount of and access to mental health services differ vastly in rural regions. Rural residents have fewer options for services, and in fact many rural areas have no health care services at all (Rural Health Information Hub, 2017). Residents in rural regions must travel greater distances for mental health services, are less likely to have health insurance, and have lower MHL (Rural Health Information Hub, 2017). Therefore, professional literature and research studies that assist with raising knowledge about MHL are warranted, as the current literature based on this topic is lacking, especially as it relates to types of settings and samples of the population. Thus, the current study was an attempt to address this gap in the literature. The following section focuses on what is known about mental health in rural areas and highlights the salient issues that are of importance to clinicians and researchers alike.

 

Mental Health in Rural Areas

The mental health of rural residents is of importance, as 16% of the U.S. population lives in rural areas (Rainer, 2012). Of those living in the rural United States, 90 million residents live in areas that have been designated as Mental Health Professional Shortage Areas and are lacking mental health professionals and resources (Health Resources & Services Administration, 2011). Researchers, practitioners, and recipients of mental health services purport the underutilization of mental health services and inadequacies in the quality of mental health care among rural populations (Smalley et al., 2012; Snell-Rood et al., 2017). Specifically, factors related to acceptability, accessibility, and availability intensify rural mental health disparities across the United States (Office of Rural Health Policy, 2005; Smalley et al., 2012).

 

A study completed in Australia sought to explore perceptions about mental health in a rural sample (Fuller, Edwards, Procter, & Moss, 2000). Themes revealed a reluctance to acknowledge mental health concerns and seek help from a professional. Results also demonstrated there is a mental health stigma that is particular to rural communities. Although the study provided an initial look at how mental health can be understood in rural areas, the sample consisted of mental health professionals and others who were knowledgeable about mental health issues rather than those from the general client population.

 

Mental health stigma is one of the most common reasons for unmet mental health needs in rural areas (Alang, 2015; Stewart, Jameson, & Curtin, 2015). For example, residents in rural communities report fear of taking psychotropic medications and that seeking treatment for mental health might adversely impact their employment (Snell-Rood et al., 2017; Stewart et al., 2015). Resultantly, rural clients who experience mental illness enter mental health care later, present with more serious symptoms, and often require more intensive treatment (Smalley et al., 2012). Insufficient MHL, such as misinformation related to common mental health disorders and treatment, can lead to lower rates of recognizing symptoms of depression, anxiety, and an array of other mental health concerns among rural residents in various ethnic and age groups (Kim, Saw, & Zane, 2015).

 

A quantitative study conducted by Alang (2015) investigating the sociodemographic disparities of unmet health care needs revealed men in rural areas were more likely to forgo mental health care because of gender stereotypes about mental health problems that encourage men to ignore mental health concerns and avoid help-seeking behaviors. Similarly, Snell-Rood et al. (2017) found that rural women face issues with mental health treatment quality and stigma related to specific disorders such as depression as well as a cultural expectancy of self-reliance, which impacts treatment efficacy. Study participants shared that the quality of counseling in their rural settings was unsatisfactory because of counselors recommending coping strategies that were “inconsistent” with their daily routines and beliefs, not offering adequate “direction” on how to approach treatment for their concerns, and having a lack of therapeutic interaction (Snell-Rood et al., 2017). Because of negative perceptions of the quality of mental health treatment, many women in the study were ambivalent in regard to seeking professional help. Rather, they relied on their personal approaches to symptom management (e.g., avoidance, reflection, and prayer).

 

Accessibility of mental health services is a significant concern in rural areas. Rural residents face challenges in finding transportation to facilities for professional care. Consequently, rural residents often forgo attaining adequate and timely mental health treatment (Alang, 2015; Hastings & Cohn, 2013). Rural residents often depend on alternative sources such as faith-based organizations to address mental health concerns (Bryant, Moore, Willis, & Hadden, 2015) or ignore the prevalence of mental health symptomology altogether (Snell-Rood et al., 2017). Unfortunately, researchers indicated that rural residents seek treatment for mental health disorders after they have become progressively worse, resulting in more extensive treatment, which is often unavailable or costly for rural clients (Gore, Sheppard, Waters, Jackson, & Brubaker, 2016; Hastings & Cohn, 2013; Snell-Rood et al., 2017). Deen and Bridges (2011) suggested these delays in seeking mental health treatment are associated with low MHL.

 

Treatment availability for mental health care in rural areas is fragmented because of critical shortages in mental health care providers in these communities (El-Amin, Anderson, Leider, Satorius, & Knudson, 2018; Snell-Rood et al., 2017). Practitioner shortage is attributed to difficulty in recruiting and retaining professionals for rural practice as well as practitioners’ limited understanding of cultural norms and effective interventions to address mental health needs in rural communities (Fifield & Oliver, 2016; Hastings & Cohn, 2013). Among practitioners who provide clinical services in rural areas, many report feeling incompetent to work with the population because of receiving fewer training opportunities to learn how to work with rural populations, less access to consultation resources, and professional isolation (Hastings & Cohn, 2013; Jameson & Blank, 2007). Fifield and Oliver (2016) found the most common need of rural-area mental health professionals was training opportunities specific to rural mental health counseling. Pointedly, rural mental health service providers are encouraged to tailor interventions and informational material to meet the needs of the specific communities in which they practice (Crumb, Haskins, & Brown, 2019; El-Amin et al., 2018). For example, a qualitative study examining the experience of rural mental health counselors found it was necessary for rural counselors to modify their interventions to include community-based interventions and expand their roles to include consulting, advocacy, and case management to effectively meet the needs of rural clientele (Crumb, Mingo, & Crowe, 2019). In 2012, rural-specific supplemental materials and curricula were integrated into the standard Mental Health First Aid program, a training course disseminated by the National Council for Behavioral Health to address gaps in MHL by teaching skills to help individuals identify, understand, and respond to mental illness (El-Amin et al., 2018; National Council for Behavioral Health, 2019). Based upon extant research evidence, cultural distinctions in rural living impact MHL and, subsequently, the quality of mental health care in rural regions of the United States.

 

Despite the above-mentioned disparities, there are opportunities for improving the mental health care of those in underserved rural areas. By becoming familiar with how rural residents in the United States define mental health and investigating the sociodemographic idiosyncrasies in the meaning of mental health for rural residents in specific regions of the United States, mental health practitioners can understand how to better address needs, counter structural barriers to treatment, and improve overall mental health care in rural areas. As far as we are aware, there are no studies that have examined how those in rural communities define and conceptualize mental health. Thus, the current study was designed to fill this gap in the literature.

 

This study sought to understand how individuals in the rural Southeast define and conceptualize mental health in order to explore MHL and serve as a guidepost to providing culturally relevant services to residents in these regions. Areas in the Southern United States have a high concentration of rural residents who potentially have less access to mental health services, which may influence their overall MHL (El-Amin et al., 2018). Furthermore, we know little about how rural populations define mental health and the knowledge and beliefs that undergird their understanding of mental health. Rather, we have definitions of mental health that are taken from large national and international entities (e.g., U.S. Department of Health and Human Services, Centers for Disease Control and Prevention [CDC], WHO) that offer broad ways of understanding the term. These definitions, although useful, may not capture distinctions associated with region, socioeconomic status, or cultural group differences. Understanding how groups of people view mental health has many benefits to enhancing MHL. A more specific understanding of mental health concepts can serve as a foundation to increase the utilization of mental health services, improve the quality of care, and enhance clients’ ability to communicate concerns. If there are to be greater gains in prevention, intervention, and management of mental health in rural, southern regions of the United States, we need a comprehensive understanding of aspects that are included in perceptions of mental health—using their own words.

 

Methods

 

Procedures

Prior to data collection, the Institutional Review Board at a Southeastern U.S. university granted approval to complete the study to explore MHL. Data were collected via a paper-and-pencil survey. Research team members approached patients waiting for a regularly scheduled medical appointment with their primary care physician to complete the survey. Paper copies were stored in a locked filing cabinet within a locked office. The family medical center was located in a rural area of a state in the Southeastern United States. The family medical center where the research took place also housed a mental health provider who received referrals from the medical doctors at the same site. The research team asked permission to collect data on-site, and the lead physician at the center agreed. The mental health provider provides services to many of the same patients who receive medical care at the office. This study was part of a larger, quantitative research investigation on mental health, mental health stigma, and MHL (Crowe et al., 2018). Because of the expansive nature of the dataset, however, this article only focuses on the qualitative components of the survey.

 

Participants

Using published guidelines for in-person recruitment, the research team approached patients as they waited in the waiting room and asked if they would be interested in joining the research study (Felsen, Shaw, Ferrante, Lacroix, & Crabtree, 2010). When participants elected to participate in the study, they completed an informed consent and survey in the waiting area or in an exam room while waiting for the medical professional. All data were collected over the course of approximately six months. Incentives were not offered to participants and all participants could choose to opt out of participation at any time.

 

Participants included 102 individuals, including 65 females (63.7%) and 37 males (36.3%). A total of 70 participants identified as White (68.6%), 25 identified as Black/African American (24.5%), four identified as multiracial (3.9%), two did not know or endorsed the “other” category (2%), and one identified as Asian (1%). Regarding age, 30 (29%) participants were age 60 and above, 21 (21%) were between the ages of 50–59, another 21 (21%) were between the ages of 40–49, 14 (14%) were between the ages of 30–39, 14 (14%) were between the ages of 19–29, and two (2%) were 18 or younger. Fifty-six participants (55%) were married, while 27 (26%) were single. A total of 15 (15%) were separated/divorced, and four (4%) were widowed. One hundred and twelve participants were asked to complete the survey, and102 individuals completed the materials, yielding a 91% useable response rate. Demographic information is summarized in Table 1.

 

Table 1

Demographic Information

Characteristic n %
Gender
     Male 37 36.3
     Female 65 63.7
Ethnicity
     African American/Black 25 24.5
     Caucasian/White 70 68.6
     Multicultural   4   3.9
     Other   2   1.9
     Asian   1   0.9
Age
     18 or younger   2   1.9
     19–29 14 13.7
     30–39 14 13.7
     40–49 21 20.6
     50–59 21 20.6
     60+ 30 29.4
Marital status
     Married 56 54.9
     Single 27 26.5
     Separated/Divorced 15 14.7
     Widowed   4   3.9
Seeking treatment for
     Physical health concerns 88 86.3
     Mental health concerns   3   2.9
     Both   2       2
Treatment status
     Never sought treatment 54 52.9
     Sought treatment in the past 48 47.1
Length of treatment
     1 year or less 18 17.6
     1–4 years 11 10.8
     5–10 years   9   8.8
     11–25 years   5   4.9
Description of treatment
     Not at all helpful   1       1
     Somewhat helpful   9   8.8
     Generally helpful 10   9.8
     Very/Extremely helpful 28 23.3
Family mental health
     No immediate family member with
a mental illness
       66      64.7
     Immediate family member with a
mental illness
26 25.4
     Not sure 10  9.8
Would you seek treatment for mental health concerns in the future?
     Yes         78    76.5
     No   3   2.9
     Not sure 21 20.5

 

 

 

Measures

For purposes of the current analysis, an open-ended question prompted participants: “In your own words, please describe what you believe the term mental health refers to.” Analysis was completed by comparing and contrasting the participant responses to this prompt with the U.S. Department of Health and Human Services (HHS; 2019) definition of mental health. This definition states that:

 

Mental health includes emotional, psychological, and social well-being. It affects how we think,
feel, and act. Mental health helps determine how we handle stress, relate to others, and make
choices. It is important at every stage of life, from childhood and adolescence through adulthood.
. . . Many factors contribute to mental health problems, including: biological factors, such as
genes or brain chemistry; life experiences, such as trauma or abuse; [and] family history of mental
health problems. (para. 1–2)

 

We elected to use this definition as opposed to similar definitions of mental health offered by WHO or the CDC because each member of the research team chose it as the most comprehensive of the three. Although there were many overlaps in the three definitions (i.e., all three descriptions mention well-being and handling or adjusting to stressors, and included some dimension of biological, psychological, and social aspects), the HHS definition also included the notion of life stages, past life experiences, and how these factors impact mental health.

 

Data Analysis

The deductive qualitative analysis method (Gilgun, 2011) was used to analyze participant responses to the open-ended prompt. In deductive coding, the researchers begin with existing codes, as deductive coding is utilized to test existing theories or frameworks. Because the current research was attempting to test the HHS definition, deductive analysis was considered the most fitting analysis method by the research team.

 

Deductive analysis attempts to understand how a particular theory or framework is useful or not (Gilgun, 2011). In deductive coding, data is sorted as it fits with existing concepts, or codes, within a framework. Deductive coding includes levels of analysis, including open coding, axial coding, and selective coding (Strauss & Corbin, 1990). According to Gilgun (2011), during open coding, the data is read line by line, sentence by sentence, and is placed as it is understood within the existing concept(s) with which it best aligns. Axial coding then occurs to refine the existing theory or framework via further analysis of data that is already placed within concepts. This data is then reconsidered to attend to groupings or subthemes within the concept to see if further details of a theory/framework are possible. Selective coding within deductive analysis is when the data is further examined to see if there is possible reduction to a single category or core concept. Selective coding is also an attempt to refine and further consider the existing framework to determine its utility and add to its use. As well, lines or sentences that do not fit existing concepts are noted. This is referred to as negative case analysis.

 

In the current research, the open coding analysis process was conducted repeatedly to consider and reconsider the data and its fit to the concepts within the HHS (2019) definition of “think, feel, and act.” These three concepts in the HHS definition were evident as the most salient. To aid in coding, these three HHS concepts were further understood by utilizing several online dictionaries (e.g., Google dictionary, Merriam-Webster, dictionary.com, and Cambridge English Dictionary) to define each concept. For example, the think code included all participant responses that are associated with this term via dictionaries, including intellectual, cerebral, brain, cognitive, and rational. The research team continually used several dictionaries to understand participant responses that were not exact or clear upon first reading. For example, state of mind was coded as think because of it being defined as a cognitive process and the condition of a person’s thoughts. Axial coding then occurred through the research team reconsidering the fit of the responses to the existing codes and if further codes could be developed via negative case analysis. As demonstrated below, axial coding produced a negative case analysis, that of overall well-being. Selective coding occurred through the team considering all codes and the utility of the original framework or, in this case, the HHS definition. This utility or lack thereof is further considered in the discussion below.

 

The entire analysis process was completed by two members of the research team independently. Independent coding enhances credibility in the analysis process, a technique promoted among qualitative researchers (Lincoln & Guba, 1985). The two researchers met on two occasions to discuss their findings and found consistency in their coding in both meetings. This consistency is often found when pre-existing codes with set definitions are utilized, as was the case in this analysis.

 

Results

 

The following section presents the results of the deductive coding of the data in comparison to the HHS definition of mental health, specifically the concepts of how we “think, feel, and act.” The existing concepts used as codes for analysis included the psychological, emotional, and social well-being—how we think, feel, and act. Sample quotes from participants (Ps) are provided. The research team also presents further points of possible refinement of the definition and sense of a core concept.

 

Concepts Used to Describe Mental Health

     Think, feel, and act. Only 15 participant responses provided support for a definition of mental health that encompassed all three aspects found in the HHS (2019) definition of “think, feel, and act.” One participant stated, “mental health to me personally is the state of one’s condition of emotional, mental, social and physical well-being” (P2), and another shared that mental health is the “ability to succeed, fully participate in social, emotional and occupational and recreational leisure” (P3). Thus, there was only a small subset of participants who viewed mental health as comprehensively as federally defined.

 

     Well-being. It should be noted that although most participants did not provide comprehensive definitions that specifically mentioned all three concepts of think, feel, and act, as used by HHS, there were 23 participants in the sample who used the term well-being. As indicated in the following, well-being was not seen as specific to one area but rather an overall experience. One participant stated, “More than a sense of psychiatric disease—overall well-being” (P4), and another shared, “Overall health of a person—their well-being” (P5). Thus, for many of our participants, a comprehensive definition of mental health they demonstrated was the general term well-being.

 

     Think. The most salient concept found among our participants was related to cognition, thinking, the mind or brain, or the term mental. Thirty-four responses focused solely on mental health as being how we think, including statements such as “state of mind” (P6), “mental health refers to your thoughts” (P7), and “brain imbalance” (P8). These responses suggest that the cognitive aspect of mental health is a primary way these rural participants conceptualize mental health. We also saw this demonstrated in other definitions provided by the participants that had think in combination with either feel or act.

 

     Think and feel. The next most salient conceptualization provided by participants included elements of both cognition and emotion—how we think and feel. Eighteen participants provided responses in this code, including “mental health is my ability to cope, how I think, rational thinking, and my emotional stability” (P9) and “state of mind and feeling of well-being” (P10). It is noteworthy that again when discussing cognition and emotion, there was frequent use of the phrase well-being, even when limited to just think and feel, thus further supporting the term well-being.

 

     Think and act. Cognition or thinking was further salient and used in connection with behavior, or how we think and act. Conceptualizations from these 10 participants included statements such as “condition of one’s mind and if any affect [sic] on behavior” (P11) and “well-being in thought and action” (P12). Again, also noted is the use of the term well-being, even when specifying think and act.

 

     Non-salient concepts within the HHS definition. There were other conceptualizations of the term mental health that supported aspects of the HHS definition. There were seven participants who focused solely on feelings—how you feel. Although there were five participants who only focused on mental health as behavior or how one acts, neither of the singular concepts were considered salient in participant responses because of infrequent responses.

 

     Other non-salient concepts. Also provided by participants were concepts focused specifically on a mental health diagnosis such as “depression” (P16, P17) and “depression, bipolar” (P18). Also, it is interesting to note that although not salient, a few participants saw mental health as a function of physical health. This was demonstrated in definitions such as “condition of health” (P19) and “special help for the sick or assist those that have some type of disease” (P20). It is important to note that a few responses were unclear or too vague and could not be categorized, such as “Don’t know” (P21, P22).

 

Summary

     Overall, participants’ responses suggest a strong tendency toward cognitive aspects of mental health rather than a comprehensive definition that can be found when looking in formal sources, such as the HHS definition (2019). However, a negative case that emerged was that these rural participants did provide the term well-being as an overall comprehensive definition for mental health. Frequency counts for each concept can be found in Table 2. In the following section, we discuss these findings.

 

Table 2

Frequencies According to HHS Definition Code

HHS Definition Codes              Participant Response Count

Think                                                   34

Think and Feel                                      18

Think, Feel, and Act                             15

Think and Act                                      10

Well-Being                                           23

 

 

 

Discussion

 

     In the current study, we explored MHL, specifically focusing on the efficacy of the HHS mental health definition in a rural, Southeastern U.S. sample. We sought to understand how this population conceptualized the term mental health. The current research literature provides very little information about this topic, so the following study offered initial findings to offer professional counselors and researchers implications and areas for further investigation.

 

It is important to reflect on the ways results from this sample of rural residents compare to the existing knowledge about the larger public’s MHL levels and ideas about mental health. Jorm (2000, 2012) noted that lack of MHL among individuals inhibits their ability to recognize mental health concerns when they arise. Although MHL may be an area for more intensive focus across all populations and settings (Jorm, 2000, 2012), results from this study suggest that there are a number of unique considerations in rural areas. Moreover, it is important to situate the current findings in the context of the challenges faced by rural residents. Knowing how those in rural communities define mental health, in their own words, will lend mental health practitioners information about how to communicate and connect effectively to increase the utilization of mental health services, improve the quality of care, and enhance clients’ ability to communicate concerns. If there are to be greater gains in prevention, intervention, and management of mental health in rural regions of the United States, a nuanced understanding of perceptions about mental health may offer a starting point.

 

Well-Being

In terms of the HHS definition, the current sample supported the concept of well-being. Although well-being was not necessarily connected concretely to the specific terms of think, feel, and act, it was often associated with one or two other concepts as well as used singularly as a holistic definition. Research on well-being has been of increasing interest in the past two decades (Dodge, Daly, Huyton, & Sanders, 2012), and many of the current national and international definitions of mental health refer to well-being (LaPlaca, McNaught, & Knight, 2013). Recent attempts have been made in the literature to more clearly articulate the definition of well-being (Dodge et al., 2012; LaPlaca et al., 2013), as this concept is being used to determine policy and practice on many national stages.

 

Current definitions of well-being combine elements of the psychological, social, and physical. However, these descriptions also focus on the ratio of resources to challenges that individuals and communities experience, and some have described well-being as the equilibrium between the two (Dodge et al., 2012). Thus, well-being should be considered within the context of social issues, economics, and service provision. This definition of well-being can be particularly useful for rural communities and populations, as resources and service provision are often lacking in rural communities (Health Resources & Services Administration, 2011). Our finding that participants connected with and utilized the concept of well-being suggests that both counseling practitioners and researchers should utilize the term and seek to better understand it, especially those working with rural communities and clients. However, participants in the current study did not provide an expansive level of detail in their conceptualization of well-being; rather, they focused on the cognitive or physical aspect of well-being.

 

Cognitive and Biological Focus

When comparing the current sample’s definitions to the HHS definition of mental health, the think/cognitive aspect of mental health was most supported and relevant to these rural participants. Most participants believed that mental health describes how individuals think, followed by those who described it as a combination of thoughts and feelings. As noted in the literature review, HHS (2019) considers mental health as impacting the way individuals think, feel, and act. In the current sample, however, only a small fraction of participants defined mental health as a combination of thoughts, feelings, and behaviors. Instead, participants considered mental health from a cognitive and biological perspective, focusing on the brain and chemical imbalances. Thus, results of this study suggest that individuals in rural communities might lack a holistic understanding of mental health.

 

Our findings add to the literature by providing context for rural individuals’ perceptions and possible explanations for treatment and help-seeking patterns. Rural residents may be especially vulnerable to misinformation about mental health disorders because of mental illness stigma, a cultural expectancy of self-reliance to resolve mental health concerns, and ascertaining mental health–related information from nonprofessionals (e.g., family members, religious leaders; Smalley et al., 2012; Snell-Rood et al., 2017), thus further underscoring the importance of improving MHL in rural communities. In the current study, for example, many participants listed only one component of mental health (e.g., brain imbalance, thoughts), suggesting that their understanding of the concept of mental health is lacking. The focus on the biological composition of the brain in mental health is consistent with definitions of mental illness promoted by organizations such as the National Institute of Mental Health. Thus, although participants’ definitions of mental health are not incorrect, in many ways the focus is narrow and not comprehensive. Study participants excluded emotions and when speaking about biology focused on the brain, which potentially discounts somatic manifestations of mental illness (e.g., stomach pains).

 

A more comprehensive understanding of mental health, with a specific focus on the connection between emotions, behaviors, and somatic symptoms, could potentially assist rural residents with becoming more conscious of signs and symptoms related to common mental health concerns such as anxiety and depression (Kim et al., 2015). It seems important for mental health educators, organizations, and counseling practitioners in rural communities to provide education that broadens the beliefs about the nature of mental health. Educational campaigns and direct work that are more inclusive and broadly focused could be of benefit.

 

Implications for Professional Counselors

     Professional counselors and related mental health practitioners in rural areas noted they need training opportunities focused on clinical issues that are important in rural settings (Fifield & Oliver, 2016). Thus, the results from this study may offer mental health professionals guidance for reaching residents in rural communities and providing efficacious mental health services. Foremost, counselor training programs could consider developing courses with a specific focus on rural populations, which can assist counseling students in increasing their understanding of the culture of rural settings, how rural residents comprehend mental illness, and effective counseling practices in rural communities (Crumb, Mingo, & Crowe, 2019; Rollins, 2010). For example, counselors in training would be privy to facts such as how many people living in rural areas across the United States face additional life stressors, including poverty and housing and food insecurities, that impact their mental health and well-being.

 

The results of this study also illustrate the importance of building partnerships and collaborative relationships in rural communities, as rural residents may present varied concerns (e.g., concerns about physical health, family members, finances, spirituality) to counselors when seeking help. Thus, building both informal and formal professional support networks in rural communities is vital. Counselors in rural communities may consider building resources with physicians, faith-based organizations, and other mental health providers for consultation purposes (Avent, Cashwell, & Brown-Jeffy, 2015; Crumb, Mingo, & Crowe, 2019).

 

El-Amin et al. (2018) suggested programs such as rural-focused Mental Health First Aid to help increase MHL in rural communities. Because access to mental health services is often limited and/or non-existent in rural communities, counselors and related mental health professionals should be more intentional in implementing these forms of programming because of the large number of residents who reside in rural communities who have not yet been helped (El-Amin et al., 2018). Trainings such as this may assist with MHL, as well as mental health stigma, which has been associated with MHL in rural areas (Crowe et al., 2018).

 

Last, the focus on cognition in participants’ definitions of mental health may indicate a positive response to more cognitive-based theories such as CBT (A. T. Beck, 1970) and rational emotive behavioral therapy (Ellis, 1962). As this study was framed through the lens of CBT and the notion that cognition impacts emotions and behaviors, this theory and related interventions may fit well when working with clients in the rural United States. This type of “matching” related to how clients in the rural parts of the United States understand mental health (with a more cognitive focus) might lead to increased participation in counseling and therapy in rural areas. This might be a way for practitioners to join with the client initially, at the beginning of the therapeutic relationship, in order to “speak the same language.” However, given the findings of the current study, although individuals may have a natural inclination toward more cognitively focused theories, it is incumbent upon mental health professionals to challenge individuals to consider the ways emotions and behaviors are connected to their mental health as well. CBT fits this model well; however, scholars have also found ways to integrate other theories to provide an even more comprehensive and culturally responsive theoretical framework for clients. For example, one of the suggested interventions in Crumb and Haskins’ (2017) integration of CBT and relational cultural theory is to “apply cognitive restructuring through relational resilience” (p. 268). This technique could be especially beneficial to rural communities, as it honors the focus of cognitions while also considering how these thoughts and messages may be related to a broader systemic and environmental influence (Crumb & Haskins, 2017).

 

In sum, counselors should be aware that many of their clients may present with low MHL. Thus, education and awareness about mental health, diagnoses, and symptomatology may be an integral part of the treatment process. Counselors should consider this intentionality in education as a part of their role as advocates for their clients (Crumb, Haskins, & Brown, 2019).

 

Limitations and Future Directions

As with all research, the current study is not without limitations. First, the qualitative responses received from participants were often brief. The study team was able to analyze responses, but future qualitative research on the topic of MHL in rural samples might include a focus group design or individual interviews rather than paper-and-pencil surveys to get an in-depth look at how those in rural areas define mental health. Also, future research could seek to further understand the concept of well-being as used by rural participants, looking more in depth at all components (cognition, emotion, and behavior). Future research studies could also investigate the reasons for a focus on cognitive aspects of mental health. As it is impossible to separate cognition from emotion and behavior, this study found that many participants seemed to focus on cognition rather than a more comprehensive understanding of cognition as it related to choices in behaviors and affect. The current study took place in a medical center, and participants who were approached to participate may have felt pressure to complete the survey or answer in a way that was socially desirable. The sample was a convenience sample and may not be representative of others in the rural Southeast.

 

Large scale quantitative studies might offer scholars interested in MHL the opportunity to use validated instruments to measure literacy and perceptions about mental health in rural samples. Assessments such as the Mental Health Knowledge Schedule (Evans-Lacko et al., 2010) have been used in recent research (Crowe et al., 2018) to measure mental health knowledge. The Revised Fit, Stigma, & Value Scale (Kalkbrenner & Neukrug, 2018) is another scale measuring barriers to counseling such as stigma, values, and personal fit. These types of assessments can measure levels of recognition, familiarity, and attitudes toward mental health conditions in order to measure MHL and perceptions of mental health stigma.

 

Conclusion

 

This qualitative study investigated the HHS definition of mental health to determine if it was representative of rural Southeastern participants’ definitions. This assisted with answering the call for more research on the mental health of rural residents (Simmons, Yang, Wu, Bush, & Crofford, 2015) in order to provide better services to this population. Most participants demonstrated a conceptualization that included cognition, as well as well-being, and were more concrete in their conceptualization of mental health when compared to the more comprehensive HHS definition. A promising result from this study was that many participants seemed willing to seek mental health treatment in the future. Rural communities could benefit from mental health education with a holistic approach. Future research should consider interviewing rural populations to gather more detail on their definitions and understanding of mental health. The results provided interventions for professional counselors and related mental health clinicians, particularly those in rural settings, to integrate into their present work, pointed to the need for educational campaigns on mental health in rural areas, and highlighted areas for future research exploration.

 

 

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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Allison Crowe is an associate professor at East Carolina University. Paige Averett is a professor at East Carolina University. Janeé R. Avent Harris, NCC, is an assistant professor at East Carolina University. Loni Crumb, NCC, is an assistant professor at East Carolina University. Kerry Littlewood is an instructor at the University of South Florida. Correspondence can be addressed to Allison Crowe, 225 Ragsdale Hall, Mailstop 121, College of Education, 5th St., Greenville, NC 27858, crowea@ecu.edu.

She’s Just a Prostitute: The Effects of Labels on Counselor Attitudes, Empathy, and Rape Myth Acceptance

Stacey Diane Aranez Litam

 

This study examined whether attitudes based on labels and counselor demographics predicted empathy and rape myth acceptance in counselors. A difference in attitudes based on the labels of either “prostitute” or “sex trafficking” was found. Attitudes based on labels and counselor demographics additionally predicted scores of empathy and rape myth acceptance. The importance of obtaining training on human sex trafficking was identified. The implications of these findings are discussed within the areas of counseling, counselor education, and counselor supervision, including challenging stigmatizing beliefs about individuals who have experienced commercial sexual exploitation, incorporating discussions about human sex trafficking into counselor education courses, and learning about resources and trauma-informed techniques that empower trafficked clients and support counseling supervisees.

 

Keywords: sex trafficking, human trafficking, prostitutes, rape myth, labels

 

 

Exploitation of humans through the use of force, fraud, and coercion is not a new phenomenon. Despite increased awareness to the social injustice of human trafficking and modern-day slavery, trading in human beings represents a current business enterprise well established prior to the colonization of North America (Johnson, 1997). Although the prevalence of human trafficking remains unknown (Andretta, Woodland, Watkins, & Barnes, 2016; Fedina, 2015), it occurs within the United States and across the globe, affecting all regions of the world (Davy, 2016; United Nations Office on Drugs and Crime, 2014). With an estimated 32 billion dollars accrued annually through the sexual exploitation of women, children, and men (Thompson & Haley, 2018), the United Nations identified human trafficking as the third largest criminal enterprise globally, just behind those involving drugs and weapons (Thompson & Haley, 2018).

 

Human trafficking encompasses both labor trafficking and sex trafficking. The Trafficking Victim Protection Act was passed by the U.S. Congress in 2000 to address the needs of trafficked survivors. This act, which applies to instances of sex and labor trafficking, defines human trafficking as the recruiting, harboring, transporting, supplying, or obtaining of a person for labor or services through the use of force, fraud, or coercion for the purpose of involuntary servitude or slavery (U.S. Department of State, 2016). Sex trafficking is a specific type of human trafficking characterized by scenarios in which commercial sex acts are induced by force, fraud, or coercion, and/or in which the person induced to perform sex acts is under 18 years of age (U.S. Department of State, 2016). The International Labour Organization (2012) reported 4.5 million people were victims of sex trafficking worldwide. In 2008, the National Human Trafficking Resource Center established a hotline service that provides information related to labor and sex trafficking cases reported in the United States (Gerassi, 2015). Since 2008, reports of trafficking through the hotline have increased at the rate of 259% per year, resulting in a total of 20,400 cases involving elements of trafficking and exploitation (Gerassi, 2015). Given these estimates, it is likely that counselors will work with sex trafficking survivors at some point during their career.

 

Whereas sex trafficking is characterized by commercial sex acts induced by force, fraud, and coercion (U.S. Department of State, 2016), sex work refers to the voluntary exchange of sexual services, performances, or products, provided without coercion, control, or force (Gerassi, 2015). Individuals who self-identify as sex workers consent to provide sex acts (Bettio, Della Giusta, & Di Tommaso, 2017; Gerassi, 2015). Conversely, sexual assault occurs when unwanted sexual behaviors are attempted or completed against a person’s will (National Institute of Justice, 2017). Yet, individuals participating in sex work are at increased risk for becoming victims of human sex trafficking and experiencing other types of abuse (Cole & Sprang, 2014). One study that examined the types of abuse experienced by sex trafficking victims found trafficked individuals experienced physical violence (88.9%), sexual violence (83.3%), and psychological violence (100%; Muftic & Finn, 2013). Although overlap exists, not all sex workers are trafficked, although all sex trafficked individuals are forced to perform sex work. Research suggests that the majority of sex trafficked individuals also experience some form of sexual assault.

 

Most narratives about sex workers and prostitutes do not adequately examine the influence of structural factors, such as poor economic and social conditions, which may perpetuate the choice to become sex workers (Schwarz, Kennedy, & Britton, 2017). Instead, existing studies focus on aspects of morality attributed to sex workers (Alvarez & Alessi, 2012). For example, a Nepalese-based study found prostitutes were viewed as immoral and were ostracized because of fear of HIV contagion (Alvarez & Alessi, 2012). Continuing to focus on labels based on the perception of individuals’ consent, agency, and choice perpetuates the presence of stigma (Bettio et al., 2017).

 

The presence of stigma is well-documented in sexual commerce research. The terms sex worker and prostitute are often used interchangeably in reference to individuals exchanging sex acts for compensation, and stigma exists based on which term is used (Alvarez & Alessi, 2012; Bettio et al., 2017; Gerassi, 2015; Schwarz et al., 2017). Specifically, rates of stigma are highest when applied to street prostitution compared to commercial stripping, pornography, and other sex acts (Schwarz et al., 2017; Weitzer, 2018). The effects of stigma based on labels negatively influence overall wellness. Sex workers who had been labeled prostitute reported lower levels of well-being (Bradley, 2007) and struggled with feelings of anger, confusion, frustration, and being misunderstood (Tomura, 2009).

 

Regardless of how people, including counselors, characterize the construct of human sex trafficking, the stigma associated with labeling clients as prostitutes negatively impacts sex trafficked survivors’ overall wellness. Misconceptions and stigma related to sex work negatively influence therapists’ abilities to successfully provide mental health services (Wolf, 2019). Many trafficked survivors feel shame and therefore avoid seeking help (Baldwin, Fehrenbacher, & Eisenman, 2015).

 

Barriers to Counseling Sex Trafficking Survivors

 

Counselors and mental health professionals often lack adequate knowledge and skills for counseling sex trafficking survivors (Domoney, Howard, Abas, Broadbent, & Oram, 2015). To provide successful mental health services, counselors should maintain appropriate attitudes and levels of empathy and have an understanding of rape myths.

 

Attitudes Based on Labels

Within the counseling setting, it is essential that counselors demonstrate empathy and unconditional positive regard and develop a strong therapeutic relationship with sex trafficking survivors. The language and labels used to describe clients can impact these necessary elements (Litam, 2017). According to the principle of linguistic relativity, language shapes perceptions of our world and significantly influences cognitive processes (Wolff & Holmes, 2011). Attitudes and perceptions toward groups of people vary depending on the labels ascribed to them (Szeto, Luong, & Dobson, 2013). For example, negative attitudes and perceptions exist when describing groups of people as “homeless” (Phelan, Link, Moore, & Stueve, 1997) and “fat” (Brochu & Esses, 2011) compared to “poor person” and “overweight,” respectively. Attitudes based on labels also influence rates of stigma for individuals receiving mental health services. Terms like “psycho,” “nuts,” and “crazy” may evoke feelings of danger and unpredictability about individuals with mental illness, ultimately contributing to increased rates of stigma (Szeto et al., 2013).

 

The use of labels to define people has been found to increase attitudes and stigma in the medical, legal, counseling, and social professions (McCoy & DeCecco, 2011; McLindon & Harms, 2011; Russell, Mammen, & Russell, 2005). To avoid marginalizing clients by referring to them by their diagnoses (e.g., schizophrenics, borderlines, autistics), person-first language was developed to separate an individual’s identity from their clinical diagnosis, disability, or chronic condition (Granello & Gibbs, 2016). Person-first language asserts that a person diagnosed with autism should be identified as a “person with autism” rather than “an autistic.” Thus, counselors must avoid labels to minimize the stigmatization of clients, especially when those labels are perceived as pejorative (American Psychological Association, 2010).

 

     A study conducted by Granello and Gibbs (2016) sought to examine the influence of person-first language on attitudes of tolerance for people with mental illness. Undergraduate students (n = 221), adults from a community sample (n = 211), and professional counselors and counselors-in-training (n = 269) were each given a measurement of tolerance. Tolerance was measured using the Community Attitudes Toward the Mentally Ill scale (Dear & Taylor, 1979), which measured four subscales of tolerance: Authoritarianism, Benevolence, Social Restrictiveness, and Community Mental Health Ideology (Dear & Taylor, 1979). These subscales respectively referred to participants’ views that people with mental illnesses need to be hospitalized; the belief that society should be sympathetic and kind to people with mental illnesses; the belief that people with mental illness are dangerous; and the belief that community-based mental health care is more beneficial than treatment in residential mental health care facilities (Dear & Taylor, 1979). Within each group, half of the participants received a tolerance measure that used the phrase “the mentally ill,” while the other half completed the same tolerance measure with the person-first language “people with mental illness.” The results of this study indicated that across all three groups, the measurement using “the mentally ill” yielded lower levels of the attitude of tolerance (Granello & Gibbs, 2016). These results indicate how attitudes are related to labels.

 

Empathy Within the Counseling Setting

In a meta-analysis of 224 studies examining empathy and outcomes in 3,599 clients, empathy was found to account for more outcome variance than specific treatment methods (Elliott, Bohart, Watson, & Greenberg, 2011). The results further indicated empathy was a medium-sized predictor of psychotherapy outcome across therapists’ theoretical orientation, treatment format, and severity of clients’ presenting concerns (Elliot et al., 2011). The results of these studies identified client-perceived therapist empathy as the strongest predictor of therapeutic outcomes.

 

Clients, including sex trafficking survivors, who experience a therapeutic environment characterized by counselor empathy feel more deeply understood (Clark, 2010), which promotes treatment satisfaction, likelihood of compliance, and involvement in the treatment process (Bohart, Elliott, Greenberg, & Watson, 2002). These findings provide evidence for the significant role of empathy as a catalyst for client change regardless of a counselor’s theoretical orientation, treatment format, or severity of client issues (Bohart et al., 2002; Elliot et al., 2011; Imel, Wampold, Miller, & Fleming, 2008; Moyers & Miller, 2013; Watson, Steckley, & McMullen, 2014). Based on the complex, multi-systemic, and unique needs of sex trafficking survivors, it is imperative that counselors working with this population demonstrate empathy to promote client compliance and treatment involvement (Litam, 2017). Counselors who work with sex trafficking survivors must obtain a deeper understanding of how the presence of rape myths may negatively impact their abilities to demonstrate empathy within the therapeutic setting.

 

Rape Myth Acceptance

The ways in which counselors conceptualize sexual violence may be a result of the acceptance of rape myths. Rape myths are complex sets of cultural beliefs, stereotypes, or prejudices about rape, victims of rape, or perpetrators of rape that support and perpetuate male violence against women (Burt, 1980). Common rape myths toward women include the prejudiced beliefs that victims are lying, a rape did not occur, the perpetrator was provoked by the victim, and that the victim deserved the rape in some way based on appearance, behavior, or style of dress (Edwards, Turchik, Dardis, Reynolds, & Gidycz, 2011; Wilson, Newins, & White, 2017). Additionally, the presence of benevolent sexism, or the set of beliefs that women should be protected by men, possess domestic qualities, and fulfill men’s romantic needs (Barreto & Ellemers, 2005), has been associated with rape myth acceptance (Chapleau, Oswald, & Russell, 2007). The concept of benevolent sexism explains why women who violate this stereotype by using drugs or alcohol, dressing “provocatively,” or trusting strangers are perceived as partially responsible for their rape because they are expected to be aware of risks and avoid precarious situations (Chapleau et al., 2007; Smette, Stefansen, & Mossige, 2009).

 

The extent to which rape victims are blamed for their own victimization has been associated with various factors, including the presence of traditional gender roles (Burt, 1980; Schechory & Idisis, 2006), sexual conservatism, and a tolerance for interpersonal violence (Burt, 1980). Additionally, society continues to hold prejudiced attitudes about “real” rape victims (Hockett, Smith, Klausing, & Saucier, 2016). According to Maier (2008) and Williams (1984), a “real” rape victim is characterized by a non-intoxicated woman who was unexpectedly and violently raped by a stranger in a deserted place, sustained obvious physical injuries, struggled with apparent emotional distress, and quickly reported the crime to law enforcement. In reality, few reported cases meet these criteria for the “real” rape victim stereotype (Hockett et al., 2016). Survivors of rape who do not meet the real victim stereotype are more likely to be blamed or perceived as responsible in some way for their attack (Lonsway & Fitzgerald, 1994). Survivors of human sex trafficking are raped by traffickers during their initiation into sex work and are continually raped by buyers during their captivity (Cianciarulo, 2008). Sex trafficking survivors are often misidentified as “prostitutes” and “sex workers” and are therefore not perceived to be “real” rape victims because of the presence of rape myths (Cianciarulo, 2008; Hockett et al., 2016).

 

Rape myth acceptance negatively influences the treatment modalities used by counselors and other mental health professionals. In a study conducted by Dye and Roth (1990), psychologists, social workers, and psychiatrists who held more prejudiced beliefs toward sexual assault victims were significantly more likely to use victim blaming interventions. A study conducted by McLindon and Harms (2011) indicated counselors who used biased or judgmental speech when conceptualizing clients who had been raped were more likely to adhere to rape myths. Counselors must understand the relationship between language/labels, empathy, and rape myth acceptance when supporting survivors of sexual trauma, including sex trafficking survivors.

 

When counselors accepted rape myths, sexual assault survivors were more likely to experience poor post-trauma outcomes (Wilson et al., 2017). Counselors who adhere to rape and human trafficking myths, or who engage in behaviors that reduce the amount of empathy afforded to clients, may lead to client re-traumatization, intensified feelings of client shame, and increased rates of early termination. Counselors must therefore understand how barriers to counseling sex trafficking survivors may negatively influence the success of client treatment (Wilson et al., 2017).

 

Human Trafficking Myths

Human trafficking myths are false beliefs about human trafficking and trafficking survivors that blame the victim, excuse the perpetrator, and deny or justify the sale or trade of human beings (Cunningham & Cromer, 2016). For example, human trafficking victims in the media are portrayed as young, innocent, and vulnerable children, when in reality, victims of all ages are trafficked (U.S. Department of State, 2001). Another misconception is the belief that victims are kidnapped and then trafficked, when more often than not they are exploited by a loved one such as a family member or an intimate partner (Gerassi, 2015). A study conducted by Cunningham and Cromer (2016) was the first to identify the presence of human trafficking myths in an undergraduate sample. The results of the study found human trafficking myths in 36.5% of the participants with 31% attributing blame to the victim. Men who perceived the vignette as an instance of sex trafficking were more likely to engage in victim blaming and were more accepting of human trafficking myths than their female counterparts (Cunningham & Cromer, 2016).

 

Purpose of the Study and Research Hypothesis

 

The present study sought to examine whether counselors’ attitudes differed based on labels
(i.e., prostitute and prostitution vs. sex trafficked women and sex trafficking). Additionally, the study explored whether attitudes based on labels and counselor demographics predicted levels of empathy and rape myth acceptance in counselors. Three research questions were identified: (1) Does a significant difference exist between Attitudes Toward Prostitutes and Prostitution Scale (APPS) and Attitudes Toward Trafficked Women and Sex Trafficking Scale (ATTS) scores? (2) Do APPS and ATTS scores and counselor attributes predict empathy scores on the Empathy Assessment Index (EAI)? and (3) Do APPS and ATTS scores and counselor attributes predict rape myth acceptance scores on the Illinois Rape Myth Acceptance Short Form (IRMA-SF)?

 

Method

 

Participants

Participants were licensed professional counselors and clinical counselors (N = 396) in Ohio. The mean age was 42.1 years (SD = 13.51). Participants self-identified as Caucasian/White (n = 364, 91.9%), African American/Black (n = 22, 5.6%), Hispanic/Latino(a) (n = 6, 1.5%), American Indian/Alaskan Native (n = 3, 0.8%), Asian American/Asian (n = 3, 0.8%), Arab American (n = 1, 0.3%), and Other (n = 1, 0.3%). The participant who selected Other self-identified as European American; some participants selected multiple items. Of the total 396 participants, there were more females (n = 341, 86.1%) than males (n = 53, 13.4%). Two participants (0.5%) identified as transgender. Years of counseling experience spanned from less than 1 year to 46 years with a mean of 11.1 years (SD = 10.43). The majority of participants had earned a master’s degree in counseling (n = 354, 89.4%). A smaller percentage of individuals sampled had earned a doctoral degree (n = 42, 10.6%). One participant indicated she or he had earned a master’s degree and an EdS degree (n = 1, 0.3%).

 

Instruments

Demographics/background form. A demographics/background form was used to collect respondents’ age, race, ethnicity, gender, work experience, and level of education. The form also collected whether participants had previously received training on human trafficking and prostitution. Following the demographics document, participants completed either the APPS or the ATTS. Once the appropriate scale was completed, all participants completed the IRMAS-SF, the EAI, and the Marlowe-Crowne Social Desirability Scale (MC-SDS) – Form A.

 

Attitudes Toward Prostitutes and Prostitution Scale (APPS). The APPS (Levin & Peled, 2011) is a 29-item instrument that uses a 5-point Likert scale ranging from 1 (fully disagree) to 5 (fully agree) and measures the degree to which participants agree with statements about prostitutes and prostitution. Specifically, the APPS measures Sexual Domination Discourse (SDD; Outshoorn, 2005) attitude, which views prostitution as a form of oppression (Barry, 1979). Individuals with high SDD attitudes believe women do not choose to engage in prostitution and are instead forced to participate in the sex industry as the result of early traumatic experiences (Hunt, 2013; Outshoorn, 2005). The theoretical background for the APPS emerged after an analysis of the existing literature found that views about prostitutes and prostitution could be roughly divided into normative and problem-oriented attitudes (Levin & Peled, 2011). According to Levin and Peled (2011), the normative attitude refers to the belief that prostitutes and prostitution are inherent and functional aspects of a normative society in which commercial sex work is an independent choice. Conversely, the problem-oriented attitude refers to the belief that prostitutes and prostitution are socially deviant in nature (Levin & Peled, 2011). Responses about prostitutes and prostitution are measured on two axes (“normative/deviant” and “choosing/victimized”) that can be further categorized into four subscales (Levin & Peled, 2011).

 

Two subscales assess the participants’ perception of prostitutes as people. Scores on the Prostitutes as Choosing/Victimized (PSCV) subscale measure whether respondents believe prostitutes choose to engage in prostitution (“Prostitutes enjoy the controlling of men”) or are victimized into the act of prostitution (“Prostitutes are unable to get out of the situation they are in”). The PSCV subscale has seven items. The Prostitutes as Normative/Deviant (PSND) subscale measures the extent to which respondents believe prostitutes, as people, are either normative (“Women become prostitutes because they were not properly educated”) or deviant (“Most prostitutes are drug addicts”). The PSND subscale has eight items.

 

Two additional subscales measure the act of prostitution itself. The Prostitution as Normative/ Deviant (PNND) subscale measures whether respondents perceive the act of prostitution to represent either social normativeness (“Prostitution provides men with stress relief”) or social deviance (“Prostitution harms the institution of marriage”). The PNND subscale has seven items. Finally, the Prostitution as Choosing/Victimized (PNCV) subscale measures whether respondents perceive prostitution represents either women’s choice (“Prostitution is a way for some women to gain power and control”) or the victimization of women (“Prostitution is a form of rape in which the victim gets paid”). The PNCV has seven items (Levin & Peled, 2011). Higher scores on the APPS reflect stronger adherence to the SDD attitude, which asserts that women engaged in sex work do not choose prostitution out of their own free will and prostitution is a deviant act that victimizes women (Farley et al., 2003; Hunt, 2013).

 

The APPS demonstrates sound psychometric properties for the measurement as a whole, across measures both about prostitutes and prostitution, and across all four subscales. The instrument was developed over two pilot studies using 392 male and female undergraduate and graduate students. As reported by Levin and Peled (2011), Cronbach’s alpha rendered an internal consistency for the entire scale (α = .81), on both subscales (α = .73; α = .73), and across all four subscales (α = .88; α = .81; α = .86; α = .83). The results of these analyses suggest satisfactory construct validity for a two- and four-dimensional model of the APPS (Levin & Peled, 2011). The APPS provides an overall score of attitudes about prostitutes and prostitution, scores related to attitudes about prostitutes and prostitution, and scores within each of the four subscales.

 

Attitudes Toward Trafficked Women and Sex Trafficking Scale (ATTS). The first author collaborated with the developers of the APPS (Levin & Peled, 2011) to alter the APPS wording to better reflect person-first language (e.g., “human trafficking survivor” and “sex trafficking”). The updated form was named the Attitudes Toward Trafficked Women and Sex Trafficking Scale (ATTS). Suggestions provided by the instrument’s original developers were followed to minimize the possibility that updating the APPS would interfere with its sound psychometric properties. The four subscales measured by the ATTS are the same as for the APPS. The reliability and validity information pertaining to the ATTS is unknown as this study was the first to use it, and we are in the process of measuring its psychometrics.

 

Illinois Rape Myth Acceptance Scale – Short Form (IRMA-SF). The 22-item Illinois Rape Myth Acceptance Scale – Short Form (IRMA-SF) was developed to allow brief assessment for the general factor of rape myth acceptance (Payne, Lonsway, & Fitzgerald, 1999). To examine the construct validity of the IRMA-SF, t-tests were conducted that compared participants’ gender on the IRMA-SF in relation to other variables with theoretical and/or empirically demonstrated relationships to rape myth acceptance; the other variables included sex-role stereotyping, adversarial sexual beliefs, hostility toward women, and attitudes toward violence. The results indicated men had higher means on these scales than women—IRMA: t (1174) = 6.23, p < .001 and IRMA-SF: t (174) = 6.09, p < .001 (Payne et al., 1999). Additionally, the previously mentioned variables (e.g., sex-role stereotyping) ranged from r (174) = .47, p < .001, to r (174) = .74, p < .001 (Payne et al., 1999). These results confirmed the construct validity of the IRMA-SF (Payne et al., 1999). The IRMA-SF possesses adequate construct validity, internal consistency, and reliability and allows for a quicker assessment for the general factor of rape myth acceptance (Payne et al., 1999). The 22-item IRMA-SF was selected for the study to limit the cognitive fatigue associated with lengthy questionnaire forms and to minimize the rate of non-response error for long surveys with many items (Groves, 1989). The IRMA-SF is a publicly available instrument, so no permission was needed to use it in the study. The IRMA-SF is scored by totaling the cumulative score, with higher scores indicating greater rejection of rape myths.

 

Empathy Assessment Index (EAI). The EAI was developed by Gerdes, Geiger, Lietz, Wagaman, and Segal (2012). The EAI incorporates both emotional and cognitive components of empathy and was developed over a 4-year period with eight different administrations to more than 3,500 participants (Gerdes & Segal, 2011; Gerdes, Segal, & Lietz, 2012). The EAI is a 22-item instrument that measures five subscales of neurologically identified components of empathy: (a) Affective Response (e.g., “When I see someone receive a gift that makes them happy, I feel happy”), (b) Self–Other Awareness (e.g., “I can tell the difference between someone else’s feelings and my own”), (c) Perspective Taking (e.g., “I can imagine what the character is feeling in a good movie”), (d) Emotion Regulation (e.g., “When I am upset or unhappy, I get over it quickly”), and (e) Affective Mentalizing (e.g., “When I see a person experiencing a strong emotion, I can describe what the person is feeling to someone else”). To control for social desirability and hide the link to empathy, the EAI is titled the “Human Relations Survey.” The typical time to complete the EAI is 5–10 minutes. The EAI is a publicly available instrument, so no permission was needed to include it in the study.

 

Marlowe-Crowne Social Desirability Scale (MC-SDS) – Form A. The Marlowe-Crowne Social Desirability Scale (MC-SDS) – Form A consists of 11 items and uses a true/false format to measure whether participants respond to survey items in a socially desirable way. The items on the MC-SDS –
Form A describe culturally approved behaviors with minimal implication of psychopathology (Crowne & Marlowe, 1960). The MC-SDS – Form A is used in conjunction with other self-report measures to assess the impact of social desirability on participants’ responses (Reynolds, 1982). The MC-SDS – Form A yielded .74 using the Kuder-Richardson Formula 20 for reliability with a significant correlation coefficient (r = .91; p < .001) and coefficient of determination (r2 = .83). Thus, the MC-SDS – Form A represents a reliable and valid form to assess social desirability (Reynolds, 1982).

 

Procedures

After receiving IRB approval, the Ohio Counselor, Social Worker, and Marriage and Family Therapist Board provided the email addresses of all licensed counselors in Ohio. As an incentive to participate in the study, three participants were randomly selected to receive one of three $75 Amazon gift cards. Email addresses were alphabetized and were sorted into two equal groups. The people in the first half (17,814), those whose names were toward the start of the alphabet, received a recruitment email with a link to the APPS. Those in the second half (17,814) received a recruitment email with a link to the ATTS.

 

Participants who received the APPS were presented with “prostitute” labels in the recruitment email and in the consent form. The APPS group was not exposed to “sex trafficking” labels. Conversely, the ATTS group was presented with “sex trafficking” labels in the recruitment email and in the consent form. The ATTS group was not exposed to “prostitute” language. After completing the demographics form, both groups completed either the APPS or ATTS surveys before moving on to the EAI, IRMA-SF, and MC-SDS – Form A. Statistical analysis indicated there were no significant differences between groups in their demographics.

 

Statistical Analysis

An alpha level of .05 and a medium effect size of .15 were maintained for all statistical procedures (Cohen, 1988). The .05 alpha level was maintained to mitigate the potential of a Type I error (Cowles & Davis, 1982). With a power of .80, a set beta of .20 was obtained, which was an acceptable mitigation of Type II errors (Lenth, 2001). A power analysis using G*Power was conducted for an independent samples t-test, which yielded a sample of 128. The study sample size was 396 participants. A total of 193 participants completed the APPS and 203 participants completed the ATTS.

 

Descriptive statistics of the criterion variables for the APPS and ATTS with the IRMA-SF, EAI, and MC-SDS – Form A were obtained and can be found in Tables 1 and 2. A series of t-tests were used to assess whether a significant difference existed between APPS and ATTS scores. To test for normality, univariate outliers were assessed and a Kolmogorov-Smirnov test was conducted. The assumption of independence was met from the random assignment of respondents and their lack of interaction within the study. The result of Levene’s test was not significant; thus, the assumption of homogeneity of variance was not violated.

 

To test the second research question, two hierarchical regressions were conducted to examine whether APPS and ATTS scores and counselor demographics predicted empathy scores on the EAI. To test the third research question, two hierarchical regressions were conducted to examine whether APPS and ATTS scores and counselor demographics predicted scores of rape myth acceptance on the IRMA-SF. For each of the two hierarchical regressions, counselor attributes were added in order of anticipated strength. After consulting research that examined the effects of variables on rape myth acceptance, the predictor variables were added in the following order: gender (Aosved & Long, 2006; Jimenez & Abreu, 2003; Suarez & Gadalla, 2010), race/ethnicity (Giacopassi & Dull, 1986; Lefley, Scott, Llabre, & Hicks, 1993; Suarez & Gadalla, 2010), level of education, years of experience, and age (Suarez & Gadalla, 2010). Each hierarchical regression analysis was conducted with an alpha level of .05 and power of .80. The assumption of independence was met from the random sorting of respondents and their lack of interaction within the study. The assumption for normality was tested by examining the distribution of the EAI and IRMA-SF scores. Observations more than two standard errors from the mean were removed. An analysis of EAI and IRMA-SF scores was plotted and demonstrated a normal shape. Residual plots from SPSS were examined to test for linearity. The variance inflation factor (VIF) was referenced within the multiple regressions with a heuristic value of four set as the upper bound for acceptable multicollinearity. The residuals appeared scattered around the zero horizontal line which indicated the assumption of homoscedasticity was not violated. Thus, none of the assumptions for conducting a multiple regression were violated.

 

 

Table 1

 

Descriptive Statistics of the Criterion Variables for the APPS

Variable          Mean             SD            Minimum           Maximum         Range

 

EAI                  4.73           0.428               3.59                    5.68                  2.09

AM                4.77           0.555               3.00                    6.00                  3.00

AR                 4.82           0.639               3.20                    6.00                 2.80

ER                  4.41           0.594                2.30                    6.00                  3.75

PT                  4.83           0.529               3.20                    6.00                  2.80

SOA               4.80           0.576               2.75                    6.00                 3.25

IRMA-SF         1.47           0.462               1.00                    2.73                  1.73

MC-SDS          5.17           2.490               0                       11.00                11.00


Note. EAI = Empathy Assessment Index, AM = Affective Mentalizing, AR = Affective Response,
ER = Emotion Regulation, PT = Perspective Taking, SOA = Self-Other Awareness,
IRMA-SF = Illinois Rape Myth Acceptance Short Form, MC-SDS = Marlowe-Crowne Social Desirability Scale.

 

 

 

Table 2

 

Descriptive Statistics of the Criterion Variables for the ATTS

Variable           Mean            SD           Minimum           Maximum        Range

 

EAI                  4.76            0.426               3.86                     5.86              2.00

AM               4.80            0.610               3.20                   6.00              2.75

AR                4.75            0.632               3.20                   6.00              2.80

ER                 4.46            0.483               3.00                   5.50              2.50

PT                 4.88            0.540               3.20                   6.00               2.80

SOA              4.87            0.540               2.75                     6.00              3.25

IRMA-SF         1.38            0.380               1.00                   2.50              1.50

MC-SDS          5.24            2.480               0                      11.00             11.00

 

Note. EAI = Empathy Assessment Index, AM = Affective Mentalizing, AR = Affective Response,
ER = Emotion Regulation, PT = Perspective Taking, SOA = Self-Other Awareness,
IRMA-SF = Illinois Rape Myth Acceptance Short Form, MC-SDS = Marlowe-Crowne Social Desirability Scale.

 

 

Results

 

Analysis of the Marlowe-Crowne Social Desirability Scale – Form A

Prior to analyzing the data, results from the MC-SDS – Form A were examined. The means for both groups were similar although the ATTS group (M = 5.24, SD = 2.48) scored slightly higher than the APPS group (M = 5.17, SD = 2.49). Based on these results, the responses provided by the study sample likely were trustworthy, indicated acceptable rates of social desirability, and likely reflect participants’ true attitudes based on labels.

 

Bivariate Results

Correlations were used to examine the strength of relationships between variables. The following section outlines significant correlations between counselor demographics and scales, subscales, and survey items on the APPS or ATTS, EAI, and IRMA-SF.

 

     Significant correlations between age and survey items. Bivariate correlational analyses were conducted to examine whether significant relationships existed between counselor age and the APPS/ATTS, EAI, and IRMA-SF. Age and PSCV were significantly correlated (r = .128, p < .05). Thus, as participants’ age increases, the belief that prostitutes are victimized also increases. Age was significantly correlated with the IRMA-SF (r = .101, p < .05) in addition to 11 items on the IRMA-SF. The results from the correlation analysis indicated as participant age increases, so too does acceptance of most rape myths. Thus, younger participants were less likely to accept rape myths than older participants. Age was significantly correlated with the Emotion Regulation (r = .200, p < .01) and Affective Mentalizing (r = -.137, p < .01) subscales on the EAI. The results from the bivariate correlational analysis indicated older participants were reportedly better able to regulate their emotions, whereas younger participants reported greater success in cognitively evaluating another person’s emotional state compared to their older counterparts.

 

     Significant correlations with gender. Bivariate correlational analyses were conducted to examine whether significant relationships existed between counselor gender and the APPS/ATTS, EAI, and IRMA-SF. Gender and previous training on prostitution and/or human trafficking were significantly correlated (r = -.112, p < .05). Based on the results of the correlation coefficient, males in the study were less likely to have received training on prostitution and human trafficking compared to females. Gender and years of counseling experience were significantly correlated (r = -.110, p < .05). Based on the results of the correlation coefficient, males reported more counseling experience than females.

 

Regarding the APPS/ATTS surveys, gender was significantly correlated to the PSCV subscale
(r = .102, p < .05), and the PNCV subscale (r = .102, p < .05). Thus, female counselors were more likely
than their male counterparts to perceive prostitutes as victims and were more likely to hold the attitude that prostitution occurred as the result of victimization. Gender and the IRMA-SF were significantly correlated (r = -.269, p < 01), with counselor gender significantly correlating with 19 out of 22 items (86%) on the IRMA-SF. Based on these results, male counselors were more likely to accept rape myths compared to female counselors.

 

On the EAI, gender was significantly correlated to the Perspective Taking (r = .161, p = < .01) and Affective Response (r = .142, p < .01) subscales, in addition to the overall EAI measure (r = .112, p < .05). Thus, female counselors reported greater success with imagining the experiences of others and were more likely to experience automatic reactions when observing the emotions of others. Compared to their male counterparts, females reported higher scores of empathy overall.

 

     Significant correlations with years of counseling experience. Bivariate correlational analyses were conducted to examine whether significant relationships existed between years of counselor experience and the APPS/ATTS, EAI, and IRMA-SF. Years of counseling experience and previous training on prostitution and/or human trafficking were significantly correlated (r = -.142, p < .01). The longer counselors had practiced, the less likely they were to have received training on prostitution and human trafficking. Years of counseling experience was also significantly correlated with the APPS/ATTS item, “Prostitutes/trafficked women earn a lot of money” (r = .153, p < .01). Thus, the longer counselors had practiced, the more they believed engaging in prostitution or being trafficked was a lucrative endeavor. Years of counseling experience were not significantly correlated with overall APPS/ATTS scores (r = .030, p > .05), overall IRMA-SF scores (r = .055, p > .05), or overall EAI scores (r = .025, p > .05).

 

     Significant correlations with training on prostitution and/or human trafficking. Bivariate correlational analyses were conducted to examine whether significant relationships existed between previous training on prostitution/human sex trafficking and the APPS/ATTS, EAI, and IRMA-SF. An examination between training and survey items revealed a significant relationship between previous training and the APPS/ATTS items “Most prostitutes/trafficked women are morally corrupt” (r = .157, p < .01), “Most prostitutes/trafficked women are ugly” (r = .150, p < .01), “Prostitutes/trafficked women spread AIDS” (r = .122, p < .05), Prostitutes/trafficked women enjoy the controlling of men” (r = -.125, p < .05), “Prostitution/sex trafficking is a way for some women to gain power and control” (r = -.113, p < .01), and “Prostitution/sex trafficking harms the institution of marriage” (r = .108, p < .05). Based on the bivariate correlations, participants who had not received training on prostitution/sex trafficking were more likely to believe prostitutes/trafficked women were morally corrupt, ugly, spread AIDS, and harmed the institution of marriage. Counselors who had not received training on prostitution/sex trafficking were less likely to believe that prostitutes/trafficked women engaged in sex acts to gain power and control and enjoyed the controlling of men.

 

Previous training was significantly correlated with the overall IRMA-SF scale (r = .127, p < .05) and the Self–Other Awareness subscale. Thus, counselors with no previous training on prostitution/sex trafficking were more likely to accept rape myths and less likely to successfully engage in the empathy construct of perspective taking.

 

     Significant correlations between survey items. Bivariate correlational analyses were conducted to examine whether significant relationships existed between items on the APPS/ATTS, EAI, and IRMA-SF. The APPS/ATTS survey item “Most prostitutes/trafficked women are ugly” was significantly correlated with 22 items (76%). The results revealed counselors’ perception that the “uglier” prostitutes/trafficked women were, the more likely they were to harm the institution of marriage, increase the rate of sexually transmitted diseases, spread AIDS, damage society’s morals, be morally corrupt, and have drug addictions. This APPS/ATTS item was of interest because of the presence of the label “ugly.”

 

The overall IRMA-SF scale was significantly correlated to 23 items on the APPS/ATTS (79%) and the overall mean score for SDD attitudes (r = -.132, p < .01). Thus, a relationship existed between higher scores of items indicating agreement with SDD and lower levels of rape myth acceptance. The more counselors in this study perceived prostitutes to be victims and prostitution as the result of victimization, the less likely they were to accept rape myths. The IRMA-SF scale was significantly correlated with the EAI subscales of Affective Response (r = -.169, p < .01) and Perspective Taking (r = -.181, p < .01). Counselors with lower levels of rape myth acceptance were better able to imagine and react to the emotions of others. Counselors who believed they were better able to imagine and subsequently experience themselves in other people’s shoes were less likely to accept rape myths.

 

Finally, a significant correlation was found between the APPS/ATTS item “Prostitutes/trafficked women are unable to get out of the situation they are in” and the overall mean score for SDD (r = .494, p < .01). Therefore, counselors who perceived that women who engaged in sex acts were victimized were more likely to believe that women in sex work did not choose it.

 

Research Question 1

A series of t-tests were conducted to examine whether differences existed between APPS and ATTS groups. The overall mean scores between APPS (M = 3.56, SD = .427) and ATTS groups (M = 3.80,
SD = .255), t (394) = -6.952, p < .01, were significantly different. The results of the t-test indicated participants who received “trafficking” labels were significantly more likely to perceive trafficked women as victims and sex trafficking as a form of victimization. Four additional t-tests determined significant differences existed between each of the APPS and ATTS subscales. The results of these t-tests can be found in Table 3 and are presented below.

 

 

Table 3

 

Independent t-Test Between APPS, ATTS, and Subscales

APPS                                  ATTS

M         SD        n                M       SD         n                 t            Sig (p < .01) 

 

Overall   3.56     0.427    193           3.80    0.255     203           -6.950          .000

PNCV     3.80    0.707    193           4.13    0.405     203           -5.830           .000

PNND     3.76    0.553    193           4.12    0.468     203           -6.905           .009

PSCV      3.80    0.575    193           4.33    0.390     203         -10.697           .000

PSND      2.95    0.410    193           2.79    0.276     203            4.500           .000

 

Note. PNCV = Prostitution as Choosing/Victimized, PNND = Prostitution as Normative/Deviant,
PSCV = Prostitutes as Choosing/Victimized, PSND = Prostitutes as Normative/Deviant.

 

 

 

     PNCV. An independent samples t-test was conducted between groups to examine if a significant difference existed on the PNCV subscale. The mean scores between APPS (M = 3.80 SD = .707) and ATTS groups (M = 4.13, SD = .405), t (394) = -5.830, p < .01, were significantly different. Based on the results, participants who received surveys with “trafficking” labels indicated significantly stronger beliefs that sex trafficking was an act of victimization.

 

PNND. An independent samples t-test was conducted between groups to examine if a significant difference existed on the PNND subscale. The mean scores between APPS (M = 3.76, SD = .553) and ATTS group, (M = 4.12, SD = .468), t (394) = -6.905, p < .01, were significantly different. Based on these results, participants who received the survey with “trafficking” labels indicated significantly stronger beliefs that sex trafficking represented a deviant rather than normative act.

 

PSCV. An independent samples t-test was conducted between groups to examine if a significant difference existed on the PSCV subscale. The mean scores between APPS (M = 3.80 SD = .575) and ATTS groups (M = 4.33 SD = .390), t (394) = -10.697, p < .01, were significantly different. Based on these results, participants who received the survey with “trafficking” labels indicated significantly stronger beliefs that trafficked women were victimized and did not choose to engage in sex acts.

 

PSND. An independent samples t-test was conducted between groups to examine if a significant difference existed on the PSND subscale. The mean scores between APPS (M = 2.95, SD = .410) and ATTS groups (M = 2.79, SD = .276), t (394) = 4.50 p < .01, were significantly different. Based on these results, participants who received the survey with “trafficking” labels indicated significantly stronger beliefs that trafficked women who engaged in sex acts were engaging in deviant rather than normative acts.

 

Research Question 2

A regression analysis for the APPS and ATTS was conducted to examine whether the linear combination of APPS or ATTS scores and counselor age, race/ethnicity, gender, work experience, and education significantly predicted participants’ overall scores of empathy on the EAI. Table A1 (see Appendix) outlines the regression analyses for the EAI overall and for each of the five subscales. The results of the regression overall indicated that race was a significant predictor of empathy (R2 = .07, F(6,186) = 2.357, p < .01) and explained 7% of the variance for empathy within the APPS group. The results of the regression were not significant (R2 = .05, F(6,194) = 1.829, p > .05) for the ATTS group.

 

APPS scores and counselor demographics did not predict scores of Affective Mentalizing on the EAI (R2 = .05, F(6,186)=1.952, p > .05). Within the ATTS group, age and attitude were significant predictors of Affective Mentalizing (R2 = .071) and explained 7% of the variance. APPS scores and counselor demographics did not predict scores of Affective Response on the EAI (R2 = .05, F(6,186) = 1.802, p > .05). Within the ATTS group, gender and attitude were significant predictors of Affective Response (R2 = .089) and explained 9% of the variance. When examining the linear combination of APPS scores and counselor demographics, the results of the regression were significant (R2 = .086) although there were no individually significant predictors for Emotion Regulation on the EAI. ATTS scores and counselor demographics did not predict scores on the Emotion Regulation subscale of the EAI (R2 = .089, F(6,194) = 3.14, p > .05). Within the APPS group, race and gender significantly predicted the empathy construct of Perspective Taking (R2 = .105) and explained 10% of the variance. ATTS scores and counselor demographics did not predict scores on the Perspective Taking subscale of empathy (R2 = .044, F(6,195) = 1.494, p > .05). Neither linear combinations of APPS scores and counselor demographics (R2 = .043, F(6,186)=1.401, p > .05) nor ATTS scores and counselor demographics
(R2 = .045, F(6,194) = 1.532, p > .05) predicted scores of Self–Other Awareness on the EAI.

 

Research Question 3

Two hierarchical regressions were conducted to test whether the linear combination of APPS or ATTS scores and counselor age, race/ethnicity, gender, work experience, and education significantly predicted participants’ overall scores of rape myth acceptance on the IRMA-SF. Table 4 outlines the regression analyses for the IRMA-SF. The results of the regression were significant within the APPS group (R2 = 156, F(6,186) = 5.717, p < .05). Gender significantly predicted rape myth acceptance (b = .272, p < .05), as did age (b = .236, p < .05) and attitude (b = -.175, p < .05). Based on these results, male counselors and participants exposed to prostitute labels were more likely to accept rape myths. The results also indicated that the older counselors were, the more likely they were to accept rape myths. Gender, age, and SDD attitudes explained 16% of the variance within the APPS group. The results of the regression were significant within the ATTS group (R2 = .065, F(6,194) = 2.231, p < .05). Gender significantly predicted rape myth acceptance (b = .178, p < .05) and explained 7% of the variance within the ATTS group. Within both groups, male counselors were more likely to accept rape myths compared to female counselors.

 

 

Table 4

Multiple Regression Analysis for APPS (N = 193) and ATTS (N = 203) With IRMA-SF

 

APPS

 

ATTS

Variable B SE B b t Sig. (p) B SE B b t Sig.(p)

 

IRMA-SF

   Constant

   Gender

   Race

   Education

   Age

   Experience

   Attitudes

 

1.807

.347

-.026

.013

.008

-.003

-.190

 

.290

.087

.104

.115

.003

.004

.074

 

 

.272

-.017

.008

.236

-.063

-.175

 

6.236

3.975

-.250

.116

2.358

-.630

-2.561

 

.000

.000**

.803

.908

.019*

.530

.011*

 

1.146

.212

-.184

.055

-.001

-.001

.119

 

.402

.087

.106

.085

.003

.004

.106

 

 

.178

-.128

.049

-.050

-.033

.080

 

2.850

2.444

-1.745

.645

-.435

-.291

1.119

 

.005

.015*

.083

.520

.664

.771

.265

 

Note. *p < .05. **p < .01.

 

 

 

Discussion

 

Based on the results from this study, exposure to “prostitute” and “sex trafficking” labels influenced a significant difference between attitudes in counselors. The combination of attitudes and counselor demographics additionally predicted scores of empathy and rape myth acceptance. Lack of training on sex trafficking was also linked to higher acceptance of rape myth acceptance. The results from this study are consistent with research that identified the stigmatizing effects of the prostitute label (Bradley, 2007; Tomura, 2009), but represent new findings as this study was the first to identify how sex trafficking labels influence empathy and rape myth acceptance in counselors. This study also is the first to illuminate how a lack of training on sex trafficking influences greater rates of rape myth acceptance.

 

Female counselors who completed surveys with sex trafficking labels scored higher on empathy compared to male counselors. This finding is consistent with a study conducted by Mestre, Samper, Frias, and Tur (2009), who confirmed women have a greater proclivity for empathic responses compared to men. According to the present study, male counselors in both groups were more likely to accept rape myths compared to female counselors. This finding is consistent with existing studies that identified greater rates of rape myth acceptance in males compared to females (Aosved & Long, 2006; Cunningham & Cromer, 2016; Suarez & Gadalla, 2010). Counselors exposed to prostitute labels scored significantly higher on Emotion Regulation compared to counselors who received sex trafficking labels. This may be explained by counselors’ need to mitigate the emotional responses required to understand the experiences of sexual violence and physical abuse that characterize prostitution. When counselors completed surveys with prostitute labels, race and gender predicted perspective taking. According to Seward (2014), people of color may demonstrate higher rates of empathy and racial acuity compared to their White counterparts. The effect of membership in a non-majority racial/ethnic group may have increased participant empathy for other marginalized groups. Compared to their male counterparts, women are also members of a disempowered group. Thus, a female gender identity may have influenced participants’ abilities to take perspective when imagining the experiences of others.

 

Implications for the Counseling Profession

The present study illuminates the importance for counselors to recognize that language matters; using “sex trafficked survivor” instead of “prostitute” in client conceptualization and within the therapeutic setting influences attitudes and several independent constructs of empathy and the presence of rape myth acceptance. Using a more strength-based term, such as sex trafficking survivor, may be more appropriate. Avoiding other stigmatizing labels, such as “ugly,” is also important within the counseling setting. As evidenced within this study, counselors perceived “uglier” prostitutes/trafficked women as more likely to harm the institution of marriage, increase the rate of sexually transmitted diseases, spread AIDS, damage society’s morals, be morally corrupt, and have drug addictions.

 

In a study conducted by Kushmider, Beebe, and Black (2015), counselors-in-training described feelings of professional helplessness and a desire for specialized coursework to learn how to better support clients who have survived all types of sexual assault. Obtaining training on sex trafficking represents an essential component of best practices when counseling sex trafficking survivors. As evidenced within this study, counselor educators may better support students by incorporating discussions about human sex trafficking as part of the Council for Accreditation of Counseling and Related Educational Programs (2015) required trauma curriculum. For example, social and cultural foundations courses can include a conversation about sex trafficking as part of a discussion on gender, gender equity, and working with refugee populations.

 

Counselors, counseling supervisors, and counseling students may benefit from receiving training on topics related to human trafficking and sex trafficking. Within this study, counselors in Ohio who had not received training on prostitution/sex trafficking were more likely to believe prostitutes/trafficked women were morally corrupt, were ugly, spread AIDS, and harmed the institution of marriage. Counselors with no previous training on prostitution/sex trafficking were also more likely to accept rape myths and were less likely to successfully engage in the empathy construct of perspective taking. Based on the results of this study, male counselors were less likely to have received previous training compared to females.

 

Counseling supervisors must become knowledgeable about resources, promote awareness, and recognize trauma-informed techniques that support their supervisee and empower the trafficked client. Counseling supervisors may normalize the stress, anxiety, and feelings of helplessness that many counselors experience when working with sex trafficked survivors. Engaging in healthy self-care practices is essential for counselors, counselor educators, and counseling supervisors who work with this challenging population.

 

Limitations and Future Research

Future studies may benefit from using a qualitative or mixed methods approach to explore the relationship between counselor beliefs and human trafficking myths. A detailed analysis of the influence of labels on attitudes across more diverse counselor demographics were not obtained because of an overrepresentation of White females in the study. Future areas of study may benefit from using a stratified sample. Obtaining a deeper understanding of the most common human trafficking myths that exist within the fields of counseling, counselor education, and counselor supervision may be helpful. Researchers could facilitate focus groups at various locations—including university settings, community mental health centers, agencies, and schools—to identify common human trafficking myths. A deeper understanding of trafficking myths is needed to develop effective training programs.

 

The development of competencies for human trafficking is needed. Presently, competencies for working with sex trafficking survivors have not yet been established. Experts on the topic of human trafficking may collaborate and document ways to identify trafficked survivors across school, clinical, and community settings. Evidence-based treatment for counseling sex trafficking survivors and trauma-informed techniques for supervising counselors working with sex trafficking survivors could be identified.

 

Conclusion

 

The results of this study illuminate the effect of labels on attitudes and how those attitudes predict empathy and rape myth acceptance in counselors. The presence of prostitute and sex trafficking labels influenced attitudes and predicted levels of empathy and rape myth acceptance in counselors. The importance of obtaining training on the topic of sex trafficking was also identified. The implications of this study related to the counseling profession were outlined and the study limitations were presented. Counselors must reflect on whether they hold stigmatizing beliefs about individuals who have engaged in commercial sex work or who have survived forced sexual exploitation. Additionally, counselors working with sex trafficking survivors may avoid using the prostitute label as this was linked to greater rates of rape myth acceptance and decreased rates of empathy. Future research areas may identify prevalent human trafficking myths and develop human trafficking competencies. The motivating factors and barriers to receiving training on human sex trafficking may also be explored.

 

 

Conflict of Interest and Funding Disclosure

Data collected in this study was part of a dissertation study.
The dissertation was awarded the 2019 Dissertation Excellence Award
by the National Board for Certified Counselors.

 

 

 

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Appendix

Table A1

 

Multiple Regression Analysis for APPS (N = 193) and ATTS (N = 203) With EAI
                                                            APPS                                                                                             ATTS

Variable B SE B b t Sig. (p) B SE B    b t Sig. (p)
EAI

   Constant

   Gender

   Race

   Education

   Age

   Experience

   Attitudes

 

4.169

-.150

.268

.060

.001

9.389

.085

 

.282

.085

.101

.112

.003

.004

.072

 

 

-.127

.039

.039

.033

.002

.085

 

14.801

-1.763

.2651

.533

.313

.022

1.186

 

.000

.080

.009**

.594

.594

.983

.237

 

4.169

-.193

-.098

-.069

-.005

.007

.227

 

.450

.097

.118

.096

.004

.005

.119

 

 

-.146

-.061

-.055

-.168

.175

.137

 

9.257

-1.993

-.830

-.718

-1.462

1.526

1.906

 

.000

.048

.408

.474

.145

.129

.058

EAI (AM)

   Constant

   Gender

   Race

   Education

   Age

   Experience

   Attitudes

 

4.629

-.132

.269

.271

-.005

.000

.032

 

.367

.111

.132

.146

.004

.006

.094

 

 

-.086

.148

.135

-.125

-.007

.024

 

12.611

-1.191

2.041

1.850

-1.184

-.066

.338

 

.000

.235

.043

.066

.238

.948

.736

 

3.849

-.209

.019

.081

-.013

.008

.371

 

.639

.138

.168

.136

.005

.007

.169

 

 

-.110

.008

.045

-.283

.135

.156

 

6.025

-1.519

.110

.600

-2.483

1.189

2.197

 

.000

.130

.912

.549

.014*

.236

.129*

EAI (AR)

   Constant

   Gender

   Race

   Education

   Age

   Experience

   Attitudes

 

4.082

-.252

.231

-.091

.000

.002

.163

 

.424

.128

.152

.169

.005

.006

.108

 

 

-.144

.111

-.039

-.007

.025

.109

 

9.630

-1.976

1.520

-.536

-.069

.235

1.509

 

.000

.050

.130

.593

.945

.815

.133

 

3.864

-.335

-.232

-.233

-.008

.006

.378

 

.663

.143

.174

.141

.005

.007

.175

 

 

-.169

-.097

-.124

-.166

.102

.152

 

5.832

-2.350

-1.336

-1.656

-1.475

.904

2.162

 

.000

.020*

.183

.099

.142

.367

.032*

EAI (ER)
Constant
   Gender   Race   Education   Age

   Experience

   Attitudes

 

3.353          .387                           8.658        .000            4.623           .512                          9.031            .000

.119          .117         .073          1.017        .311              .078           .110             .052        .710            .478

.202          .139         .104          1.454        .148             -.173           .134            -.095     -1.285           .200

-.068          .154        -.032          -.443         .148             -.179           .109           -.125      -1.643           .102

.008          .004         .191          1.831        .069               .003         .004             .086         .744            .458

.003          .006         .049             .469        .639               .005         .005             .112         .975            .331

.139          .099         .100          1.403        .162              -.045         .135            -.024       -.332            .740

EAI (PT)

   Constant

   Gender

   Race

   Education

   Age

   Experience

   Attitudes

 

4.442          .341                        12.024        .000              4.012         .575                           6.980            .000

-.273          .103       -.188         -2.654         .009*            -.239           .124           -.142     -1.935            .054

.412          .123        .238           3.361        .001*            -.093           .151           -.046       -.619             .537

.012          .136        .007             .091        .927               .016           .122            .010          .132            .895

-.002          .004       -.040           -.389         .698              -.005           .005           -.130     -1.128            .261

-.001          .005       -.102           -.117         .907               .005           .006             .096          .834            .406

.038          .087        .031             .435        .664               .302           .152             .143        1.990            .048

EAI (SOA)

   Constant

   Gender

   Race

   Education

   Age

   Experience

   Attitudes

 

4.292

-.153

.200

.225

.005

-.003

.047

 

.385

.116

.138

.153

.004

.006

.098

 

 

-.097

.106

.108

.114

-.055

.035

 

11.159

-1.323

1.448

1.465

1.074

-.516

.480

 

.000

.188*

.149

.145

.284

.607

.632

 

4.610

-.214

.022

-.009

-.003

.012

.070

 

.570

.123

.150

.121

.005

.006

.151

 

 

-.128

.011

-.006

-.078

.237

.034

 

8.082

-1.741

.147

-.075

-.672

2.057

.466

 

.000

.083

.883

.940

.503

.041

.642

Note. AM = Affective Mentalizing, AR = Affective Response, ER = Emotion Regulation, PT = Perspective Taking,
SOA = Self–Other Awareness, Attitudes = Mean Score on APPS or ATTS.
*p < .05. **p < .01.

Stacey Diane Aranez Litam is an assistant professor at Cleveland State University. Correspondence can be addressed to Stacey Litam, 2121 Euclid Avenue, Julka Hall 272, Cleveland, Ohio 44115, s.litam@csuohio.edu.