Behind the Curtain: Ballet Dancers’ Mental Health

J. Claire Gregory, Claudia G. Interiano-Shiverdecker 

Using Moustakas’s modification of Van Kaam’s systematic procedures for conducting transcendental phenomenological research, we explored ballet culture and identity and their impact on ballet dancers’ mental health. Participants included four current professional ballet dancers and four previous professionals. Four main themes emerged: (a) ballet culture—“it’s not all tutus and tiaras”; (b) professional ballet dancers’ identity—“it is a part of me”; (c) mental health experiences—“you have to compartmentalize”; and (d) counseling and advocacy—“the dance population is unique.” Suggestions for counselors when working with professional ballet dancers and professional athletes, such as fostering awareness about ballet culture and its impact on ballet dancers’ identity and mental health, are provided. We also discuss recommendations to develop future research focusing on mental health treatment for this population. 

Keywords: ballet dancers, culture, identity, phenomenological, mental health

 

“Dancers are the athletes of God.”—Albert Einstein

Professional ballet dancers’ mental health experiences are sparse within research literature (Clark et al., 2014; van Staden et al., 2009) and absent from the counseling literature. Most research including ballet dancers focuses primarily on eating disorders, performance enhancement (Clark et al., 2014), and injuries (Moola & Krahn, 2018). Although these topics are crucial to dancers’ wellness, explorations of ballet dancers’ mental health that do not primarily focus on eating disorders are also important. Increasing professional ballet dancer and athlete mental health research could provide counselors with deeper awareness of the populations’ needs. Further, counselors have access to the American Counseling Association’s (ACA; 2014) Code of Ethics, which is relevant for all clients, including athletic populations. However, the counseling profession lacks specific sports/athletic counseling ethical codes, competencies, and teaching guidelines (Hebard & Lamberson, 2017). The only mention of “athletic counseling guidelines” appears in a 1985 article from the Association for Counselor Education and Supervision (Hebard & Lamberson, 2017). In their initiative to increase counselor response to the need for athletic counseling, Hebard and Lamberson (2017) implored counselors to advocate for athletes’ mental health. Further, the researchers stated that it is common to view athletes as privileged and idolize them for their physical endurance; however, this perception may leave athletes vulnerable to mental health concerns. Recent examples of mental health difficulties experienced by formidable professional athletes include tennis player Naomi Osaka choosing to decline after-match news conferences to safeguard her mental health and gymnast Simone Biles removing herself from some events at the Tokyo 2020 Olympics in order to protect her mental health.

Moreover, scholars have been increasingly devoted to understanding the cultures within which performing artists are trained and developed and recognizing their role in supporting the health and well-being of the artist (Lewton-Brain, 2012; Wulff, 2008). For counselors, the ACA Code of Ethics (2014) promotes gaining knowledge, personal awareness, sensitivity, and skills pertinent to working with a diverse client population (C.2.a). However, this is difficult with limited current data or research seeking to advance knowledge of the culture of performing institutions and how they relate to artists’ mental health experiences. Therefore, an exploration of ballet culture and identity and their impact on ballet dancers’ mental health experiences could help inform counselors and counselor educators about the counseling needs of this population.

Mental Health Among Elite Athletes and Performing Artists
     Because of the scant literature focusing directly on professional ballet dancers’ mental health, we included research findings from articles examining mental health among athletes and performing artists. Although differences exist between professional ballet dancers, elite athletes, and performing artists, a professional ballet dancer straddles multiple environments. For example, an elite athlete trains to win a national title or medal, possesses more than two years of experience, and trains daily to develop talent (Swann et al., 2015). Rouse and Rouse (2004) suggested that performing artists’ goals or outcomes are to create art and achieve a high performance level with audience satisfaction. Similar to these groups, a professional ballet dancer trains almost every day, which requires extreme dedication. They must comply with high physical and mental demands to develop their ballet technique for performing and entertaining audiences.

Scholars have discovered that elite athletes experience a high prevalence of anxiety, eating disorders, and depression compared to the general population (Åkesdotter et al., 2020; Gorczynski et al., 2017). At the same time, eating disorders are overrepresented in elite athlete studies because of the requirement that elite athletes maintain a specific stature for their profession (Åkesdotter et al., 2020). Interestingly, few elite athletes reported anxiety disorders even though they scored in the moderate range on the General Anxiety Disorder-7 (GAD-7; Åkesdotter et al., 2020). This could indicate that elite athletes normalize their anxiety and eating concerns, even at a clinical level. Likewise, performing artists display disproportionately high reporting rates for mental health disorders, such as depression, anxiety, and stress, when compared to the general population (Van den Eynde et al., 2016; van Rens & Heritage, 2021). Given professional ballet dancers’ emotionally demanding performance levels as performing artists and their physicality as athletes, they may share similar mental health experiences with elite athletes and performing artists, yet these experiences remain unknown.

Ballet Culture and Professional Dancers’ Mental Health
     Literature exploring ballet dancers has focused on culture (Wulff, 2008), development (Pickard, 2012),  emotional harm (Moola & Krahn, 2018), injury prevention (Biernacki et al., 2021), and disordered eating (Arcelus et al., 2014). Ballet, with origins in the Italian and French courts, is an age-old culture that fuses beauty and athleticism (Kirstein, 1970; Wulff, 2008). Influenced by social and cultural forces in the Western world (Kirstein, 1970), ballet culture is synonymous with tradition and hierarchy (Wulff, 2008). Ballet culture holds steadfast to idealistic tenets in which dispositions (e.g., tenacity), perceptions of an ideal body, and actions (e.g., constant rehearsals) provide dancers the ability to illustrate a story through movements (Wulff, 2008). Exquisite sets, costumes, and movements create a unique experience and can produce a visceral reaction in the audience (Moola & Krahn, 2018).

Yet a strong commitment to the art form requires ballet dancers to work with their bodies for hours, sustain injuries, and work through chronic pain (Pickard, 2012), often leading to emotional distress (Moola & Krahn, 2018). Physical requirements also make dancers three times more vulnerable, compared to non-dancers, to suffer from eating disorders, particularly anorexia nervosa and those labeled by the Diagnostic and Statistical Manual of Mental Disorders as eating disorders not otherwise specified (Arcelus et al., 2014). van Staden et al. (2009) focused directly on ballet dancers’ mental health, finding that professional ballet dancers also experience mental health concerns due to negative body image and stress. The vast majority of these studies originated from countries outside the United States, including South Africa (van Staden et al., 2009), the United Kingdom (Pickard, 2012), and Canada (Moola & Krahn, 2018). The scarcity of scholarly attention on professional ballet dancers’ mental health within the United States is concerning given the evidence of emotional distress in similar populations. Counselors may be less than effective without a clear understanding of this population’s mental health needs. Understanding the cultural context and its impact on ballet dancers’ mental health in the United States, therefore, requires further exploration.

Purpose of the Present Study
     The purpose of this study was to explore ballet culture and identity and their impact on ballet dancers’ mental health experiences. The guiding research questions were (a) How do professional ballet dancers define ballet culture and identity? (b) What are the mental health experiences of professional ballet dancers? and (c) What are professional ballet dancers’ suggestions for counseling and advocating with this population?

Method

Given the purpose of this study, we chose a transcendental phenomenological approach as an appropriate method to discover and describe the essence of participants’ lived experiences. Both van Staden et al. (2009) and Moola and Krahn (2018) utilized phenomenological approaches to explore ballet dancers’ mental health and experiences of emotional harm. Originally introduced by Husserl (1970), this approach positions researchers to focus on the individual experience while also identifying commonalities across participants (Hays & Singh, 2012). Further, in transcendental phenomenology, researchers set aside preconceived ideas, seeking to add depth and breadth to people’s conscious experiences of their lives and the wider world. In Moustakas’s (1994) modification of Van Kaam’s method of transcendental phenomenology, researchers aim to collect the experiences of participants while consistently assessing and addressing their biases to produce a purer and transcended description of the researched phenomena. Because our lead author, J. Claire Gregory, possesses a background as a professional ballet dancer, the framework of transcendental phenomenology provided the needed structure for identification of biases and preconceived notions, allowing us to evaluate our positionality to the data.

Research Team Positionality
     Our research team consisted of Gregory, a doctoral candidate and licensed professional counselor, and Claudia Interiano-Shiverdecker, an assistant professor in counselor education and supervision in a CACREP-accredited counselor education program. Gregory is a Caucasian female and was a professional ballet dancer for 7 years. Interiano-Shiverdecker is a Honduran female with extensive experience conducting qualitative research and clinical experience primarily focused on trauma, crisis, and grief. We have a combined 13 years in clinical practice. Moustakas implored researchers to uphold epoché, “a Greek word meaning to refrain from judgment, to abstain from or stay away from everyday, ordinary ways of perceiving things” (1994, p. 85), by bracketing their own opinions, theories, and expectations. Bracketing is a defining characteristic of transcendental phenomenology in which researchers set aside their own assumptions, to the extent possible, to allow individual experiences to emerge and inform a new perspective on the phenomenon (Moustakas, 1994). Given the composition of the research team and the methodology employed, it was vital to engage in ongoing conversations about our collaboration, data collection and analysis, participants, and the data. Therefore, we addressed specific biases by engaging in virtual weekly bracketing meetings for over a year. Before meetings, Gregory would log memos about thoughts during data collection and analysis. Interiano-Shiverdecker would serve as a consultant to address biases. The biases discussed included a desire to not focus on mental health disorders typically discussed in the literature (e.g., eating disorders) and a desire to highlight professional ballet dancers’ strengths to balance out negative stereotypes. Throughout data analysis, we noted that participants discussed other presenting mental health issues and the connection of ballet culture to the development of those issues, including eating disorders. We operated from a social constructivist research paradigm in which multiple realities of a phenomenon exist (ontology), researchers and participants co-construct knowledge (epistemology), and context is valuable (axiology; Hays & Singh, 2012). This approach primarily focused on reflecting the participants’ voices while recognizing our roles as researchers, so we intentionally did not incorporate a theoretical framework to analyze our data.

Sampling Procedures and Participants
     The transcendental phenomenological research procedures we followed included (a) determining the phenomenon of interest, (b) bracketing researcher assumptions, and (c) collecting data from individuals who have directly experienced the phenomenon. Therefore, after receiving approval from our university’s IRB, we used purposive and snowball sampling to recruit professional ballet dancers in the spring and summer of 2020.

Purposive sampling allowed us to select participants for the amount of detail they could provide about the phenomenon (Hays & Singh, 2012). We intentionally recruited individuals who identified as a professional ballet dancer currently or in the past and were 18 years or older, aiming for a sample of at least five participants (Creswell, 2012). The parameters for “professional ballet dancer” were being a dancer with a professional ballet company and receiving financial payment. Gregory emailed potential participants, contacted professional ballet organizations to request distribution of the recruitment flyer among their members, and posted on Facebook groups used by professional ballet dancers. This email and post included an invitation to participate, a link to a demographic form, and an informed consent form. A total of seven eligible volunteers responded to recruitment emails and posts on Facebook groups. Through snowball sampling, we recruited one more participant. Seven of the dancers had worked with the same professional ballet company as Gregory, but only two had danced concurrently with her, which occurred 10 years prior to data collection.

All participants who contacted us about the study stayed enrolled and completed the interview session. Table 1 outlines the demographic information of each participant, with the use of pseudonyms. Five of the eight participants lived in a southern region of the United States, while three participants lived in northwest and eastern regions. All participants identified as Caucasian. Two participants currently worked as professional ballet dancers attached to a company; the other six were ballet teachers, office employees, freelance dancers, students, or nurses.

Data Collection Procedures
     Moustakas (1994) recommended lengthy and in-depth interactions with participants in transcendental phenomenology in order to understand participants’ experiences of the phenomenon and the contexts that influence those experiences. Participation required professional ballet dancers to complete a demographic questionnaire, take a picture that represented their perspective on mental health while dancing professionally, and complete an individual semi-structured interview. We chose to include the picture to include creative expression, a vital element in ballet culture. The use of pictures during the interview process facilitated a representative and safe discussion around mental health. Although we did not directly analyze the pictures, they served as catalysts for interview questions. In qualitative research, photography can supplement primary data collection methods when participants struggle to utilize words alone to capture an experience (Hays & Singh, 2012).

Table 1

Participant Demographic Information

Pseudonym Gender Age Race Professional Status
Abby F 31 Caucasian Former Professional
Cleo F 28 Caucasian Current Professional
Luna F 35 Caucasian Former Professional
Mica F 30 Caucasian Former Professional
Monica F 37 Caucasian Former Professional
Paul M 25 Caucasian Current Professional (Freelance)
Sophie F 33 Caucasian Current Professional
Zelda F 25 Caucasian Current Professional (Freelance)

 

We developed a 9-item open-ended interview protocol (see Appendix) intended to explore participants’ experiences with mental health, counseling, and advocacy. Gregory conducted all interviews, which lasted from 30 to 60 minutes with an average of 40 minutes, and transcribed each interview verbatim afterward. Three interviews were in person, while six interviews occurred over the phone because of the COVID-19 pandemic. During development, we decided to begin with a simple question to help the dancer feel more at ease. In the next five questions, we utilized their picture to discuss mental health. Because the term “mental health” may or may not be known to the dancers, or it may hold stigma, we felt the picture could produce more insight and depth of the concept. Question 6 asked the dancers to consider their social context and its relation to their mental health. We also chose to include a question asking about ballet dancers’ strengths, as this seems to be rare within performing artist and athlete literature. Next, we directly asked the dancers how counselors could help and then asked a final question that created space for any other relevant thoughts. Through these interviews with eight (seven female, one male) professional ballet dancers, we reached data saturation, meaning that no new information emerged in the data creating redundancy.

Data Analysis
     We followed Moustakas’s (1994) modification of Van Kaam’s steps for data analysis, which included (a) developing clusters of meaning, (b) using significant statements and themes to write a description of what participants experienced (textural description) and how they experienced it (structural description), and (c) describing the essence of participant experience from the textural and structural descriptions. First, Gregory engaged in member checking by emailing each participant their interview transcript to ensure accuracy and provide an opportunity to redact any statements. No participant changed their transcript.

Gregory then reviewed each transcript independently, highlighting significant statements or quotes that conveyed participants’ experience. This process is known as horizontalization (Moustakas, 1994). Then, we discussed each identified statement and assigned meaning to similar statements (i.e., clusters of meaning). We used NVivo software for data analysis to ensure consistency, transparency, and accuracy. NVivo, a qualitative data analysis software, aids researchers with consistency in assigning codes to similar topics and allows the research team to cross-check codes for accuracy.

We then determined the invariant constituents, or the final code list, from redundant and ancillary information through a process of reduction and elimination. For example, we eliminated codes that did not illustrate participants’ lived experiences in relation to the purpose of this study. Through the process of reduction, we merged codes if their meaning was similar. These processes allowed us to have a final list of codes that were not repetitive and aligned with the purpose of the study. Using the final codebook, we began the recursive coding process to recode every interview and reach final consensus. Recursive coding, a qualitative data analysis technique, is very useful when analyzing interview data, allowing researchers to compact the data into different categories and illuminating patterns within the data not otherwise apparent (Hays & Singh, 2012). For example, we noticed several codes that illustrated traditions or customs, both positive and negative, that ballet dancers embraced, so we decided to categorize codes about traditions and customs, in both negative and positive categories, to illustrate ballet culture.

Following this initial coding, we explored the latent meanings and clustered invariant constituents into themes, ensuring that all themes were representative of the participants’ experiences. We then synthesized themes into textural descriptions of participants’ experiences, including verbatim quotes and emotional, social, and cultural connections to create a textural-structural description of meanings and essences of experience (Moustakas, 1994). Using the individual textural-structural descriptions, we proceeded to create composite textural and structural descriptions of reoccurring and prominent themes. Finally, Gregory engaged in the member-checking process for a second time by sending the final themes to all participants via email. Four participants responded, all supporting the final themes.

Strategies for Trustworthiness
     To ensure quality, we engaged in multiple strategies to meet trustworthiness criteria, such as transferability, confirmability, dependability, and credibility. Specific strategies included using researcher triangulation, member checking, in-depth description of the analyses, and thick description of the data (Hays & Singh, 2012). Weekly meetings for a year helped reduce researcher bias through openly challenging each other with any conclusions. We also engaged in two rounds of member checking for dependability and confirmability. In addition, we utilized an external auditor with previous experience in qualitative research who was unfamiliar with ballet traditions and culture to aid in establishing confirmability of the results and credibility of our data analysis process (Hays & Singh, 2012). The auditor reviewed our NVivo file for data analysis and notes, and the final presentation of the results in a Microsoft Word document. Although the external auditor provided us with APA suggestions, she had no critical feedback regarding our analysis. Instead, she supported our findings on ballet culture that provided a new insight for counselors. Finally, we used thick description when reporting the study findings to increase trustworthiness. Utilizing thick description allowed us to depict deeper meaning and context of the data instead of only reporting the basic facts (Hays & Singh, 2012).

Results

We identified four prevalent themes about professional ballet dancers’ mental health experiences: (a) ballet culture—“it’s not all tutus and tiaras”; (b) professional ballet dancers’ identity—“it is a part of me”; (c) mental health experiences—“you have to compartmentalize”; and (d) recommendations for counseling and advocacy—“the dance population is unique.”

Ballet Culture—“It’s Not All Tutus and Tiaras”
     All eight participants described ballet as a unique culture with its own set of customs and ingrained traditions. One of the participants, Monica, further elucidated this point: “The traditions of ballet are very old-fashioned, but it’s beautiful when something endures and exists after hundreds of years.” Throughout their narratives, dancers mentioned patterns of “good” and “bad” sides to ballet culture. “It’s not all tutus and tiaras or the perfect life. There is so much beneath the surface,” explained Cleo. To clarify this theme, we divided it into two subthemes: negative aspects of ballet culture and positive aspects of ballet culture. Although we present this theme in two opposing subthemes for simplicity, dancers’ experiences existed along a continuum.

Negative Aspects of Ballet Culture
     All of the participants shared that customs of ballet culture focused primarily on requirements indispensable to successfully performing a job that was emotionally and physically demanding. The dancers’ comments centered around physical body requirements and arduous training, highlighting the need for extreme physical athleticism to perform at a professional level. Monica explained, “They [ballet dancers] have obvious physical strength, stamina, endurance, and mind over matter for what they need to do.” “We’re a very underrated athlete,” echoed Abby. Zelda added, “I would compare us to what the world knows a little bit better as gymnastics for the Olympics.”

Although no interview questions specifically asked about the negative side to ballet, participants shared feeling constant stress, pushing their bodies and minds to their limits, worrying about body image and injuries, and feeling pressure to find and keep employment. It was commonplace for participants to experience a sense of pressure and stress from internal and external forces. For example, Paul stated, “I think about my ballet career, and I think how I was tired all the time, because I would wake up and do so much.” Echoing this feeling, Zelda shared, “I was half thriving, half dying inside.” Other participant statements emphasized feeling mentally broken with the lack of time for any outside hobby and having no power as a dancer. Abby stated, “In ballet, everything was just so competitive and mind twisting. I was raised with the idea that every day is an audition.” She added, “This could be your day, or if you don’t work hard today then 3 months from now it is going to creep up on you. So, it’s this weird, like, permanence that is doomed upon us.” According to Abby, there was a daily pressure to achieve greatness, which at times caused injury. For Cleo, a current professional ballet dancer, employment pressure and injury were prevalent: “I actually had an injury where I was not able to dance for a year. . . . I managed to sprain my ankle in three places. I had spent the entire summer rehabbing and keeping it in a boot.” Yet she explained that because she was “scared [of not being asked to return to the dance school], I danced on it for weeks after the initial injury.” Cleo also saw her peers struggling with the same issue:

My friend had food poisoning yesterday. She is still sick today and they told her she has to come in because they were setting the Adagio scene . . . she literally left class to throw up and then came back to class and the whole time was trying not to throw up.

     Other professional dancers echoed these fears of financial stress and employment stability, which justified their reasons to push their minds and bodies to the limit, despite physical or mental injuries. Despite perceptions of glamour, Paul highlighted the financial strain that most ballet dancers experience by detailing how he made only “$100 a week and lived in a place that charged me $250 a month.” Even with their efforts, three participants had lost their dancing jobs. Luna believed it was her weight that got her fired, while Paul shared, “I would work super hard all day, back to the gym at night, eat super healthy, and I was still fired for not being good enough, according to my old boss.”

Positive Aspects of Ballet Culture
     Despite these intense demands, all participants also discussed positive qualities of ballet culture. These included connection to others, learned adaptability, and creating a story for the audience. Paul highlighted, “Even with the bad parts, there’s a lot more good than there was bad. . . . It’s one of those things, you’re like, I love it so I’ll do it for whatever money.” Monica reflected on her career, saying, “I see fond memories and really good times.” Several participants shared how long training hours and a common goal created a unique connection to others that was difficult to experience elsewhere. Monica passionately stated that “dancers thrive in the sense of community. When you are in a company you are exactly that—part of the greater company and you work together.” Mica shared, “You aren’t really your own person when you are dancing in a professional setting.” “It helps create friends and that was the beauty behind it, you had a support system,” added Luna. Three of the dancers shared their enjoyment of creating an onstage story for the audience. Mica enjoyed how ballet “uses the body to give meaning to stories, more so than other forms of dance.” Luna shared, “We were giving back to the community and being a part of the arts. That was great. I loved that.”

Professional Ballet Dancers’ Identity—“It Is a Part of Me”
     All dancers either directly or indirectly attested to a ballet identity and how it influenced their development. To display the range of experiences, we described this theme in two subthemes: ballet dancer traits and connections to their ballet dancer identities. The first subtheme illustrates aspects that ballet dancers might share, while the second theme discusses how participants connected these traits to their personal identity.

Ballet Dancer Traits
     All participants shared traits they felt were central to life as a professional dancer, such as tenacity and grit, that influenced their identity during and after dancing. Luna, Mica, Sophie, and Zelda mentioned the discipline a dancer must possess for a successful ballet career. “The level of discipline, I think, is unmatched,” Mica fervently stated. Sophie, Mica, Zelda, and Paul mentioned that their determination for continuous improvement represented their role on stage and ability to maintain their jobs. Sophie expressed, “Your determination, your artistic expression, all of those things include the whole person.” The dancers expressed an ability to push through any odds knowing that, eventually, their hard work would pay off. Sophie shared:

Delayed gratification I feel is a big one [strength], especially in a society with everything now being instant and we are always on our phones, but to work on something slowly over time and be patient. Just trust that hard work pays off.

     Dancers indicated a connection between their transformation as dancers and their development as adults. Cleo shared, “If you make it to a professional, you are one of the few that had a hard road, and it makes you have a very thick skin that can help in all matters of life.”

Connection to Their Ballet Dancer Identities
     All dancers expressed both positive and negative emotions about their ballet identity, ranging from gratitude to contempt. Four participants expressed that dancing was not just something they did, it was who they were. For them, ballet, and the culture of ballet, were integral parts of their identity. During her interview, Zelda paused after a question about why she continues to dance and simply stated, “It is a part of me.” Sophie shared, “Over the years, I think I stuck with it because it became wrapped up in my identity a bit. This is who I am, this is what I do, this is what makes me special.” Additionally, Cleo and Sophie identified the power and connection they felt while dancing on stage. This connection gave meaning to their dance career. Sophie shared, “Somehow dance felt like it gave me the most ability to participate in music in a way I really wanted to and a kind of level of expression I never really had.”

Yet four participants also felt that their identity had evolved past ballet. “It’s a picture that represented me at a point in time, but I don’t feel it represents me anymore,” shared Mica. Paul, a freelance professional, shared, “I feel like it definitely was how I viewed myself. But I’m not 100% sure if I do or don’t feel that way now.” Monica, a former professional, explained:

Our identity is who we were and what we had, but that is not my core identity. I know who I am in my identity, and it is in Christ who made me, and also just me as a person is more than what I did and what I do on my days at a job.

Mental Health Experiences—“You Have to Compartmentalize”
     Utilizing pictures to discuss mental health attended to participants’ preferred form of expression. As Zelda stated early in her interview, “I don’t know how to put it into words. It’s hard.” Despite their dedication and passion, all dancers spoke of the demanding nature of professional dancing and its impact on their mental health. Their conversation around mental health focused on two areas: perfectionism and the perfect body and compartmentalization.

Perfectionism and the Perfect Body
     All dancers felt they needed an additional picture to represent the darker side of ballet or related this darker side to imperfections within the picture. Figure 1 displays Paul’s picture of artwork, which the dancer felt represented the outward appearance of perfection but included lumps of paint (i.e., imperfections), a representation of his mental health.

Figure 1

Paul’s Picture of His Mental Health Experience as a Professional Ballet Dancer

 

 

 

 

 

 

 

 

 

     Despite there being no interview questions about their body image, seven of the eight dancers shared thoughts about body image concerns or pressure to develop a certain physique. Throughout their dancing career came numerous hours of practice in front of mirrors. Abby’s chosen picture displayed part of a bathroom mirror: “When I look into the mirror, a lot of judgments come back in, and ballet is all based off of opinions and judgments that really mess with your head.” She added, “Everything revolved around the mirror, and if the mirror said it was ok, then my brain said it was ok . . . with ballet and mental health, I feel like a lot of my mental health was based off the reflection.” Paul also shared, “I was going to the gym every single day and was in really good shape but was still told I was not in ballet shape.” Monica shared another company dancer’s experience: “Even though she was a gorgeous dancer and had the most incredible feet and legs, she was told she was overweight, and she did not know, in those days, how to deal with it.” Luna spoke openly about feelings of depression when she gained weight: “When I got fired, I would go into periods where I gained 20 pounds because of my depression. The whole reason I was fired was because I got too big.” She later added, “I started losing it when I got hired back but was not allowed to be in productions because I was too big. . . . The depression made me eat and go into a dark place.” However, Luna also spoke about current cultural changes regarding the “ideal” body shape for ballet dancers in the United States: “Nowadays I feel that they [ballet companies] have embraced differences in dancers.”

Although participants recognized the benefits of an unbreakable determination, discipline, and rigor toward their professional career, they also noted the emotional consequences of their dedicated work. Cleo best illustrated this point: “It just felt like it didn’t matter how hard I worked, it just took a toll. . . . I thought it [ballet] was beautiful, and 13 years ago I believed this, but then things started to turn darker mentally for me.” Mica shared, “I would say a lot of us, we have anxiety and depression, but we are also crazily mentally strong . . . like me, for example, I was told I was too fat from the age of 12.” With this constant stress, the dancers felt their mental health fluctuated with external forces (i.e., thoughts about not being good enough). Zelda stated, “I had constant anxiety of not being good enough.”

Compartmentalization
     Another prominent subtheme for all of the dancers was compartmentalization. The dancers described compartmentalization of thoughts and feelings as a healthy coping mechanism for some and a hindrance for others. Abby and Sophie spoke about their need to separate from their feelings and thoughts to perform well. Abby told herself, “Do not think that way. You work really hard and you can put all those thoughts into a little box and hopefully, eventually, get rid of it.” She added that “when the thoughts creep up, I try to put them into my little mental box and try not to open it.” Sophie also spoke in depth about how she maintained her mental health and navigated her negative feelings:

I have to separate myself from my feelings sometimes. I have to remember that my feelings aren’t me. . . . You have to believe you can make it happen and it’s going to work out and be resilient enough to take rejection and injuries, and the uncertainty of finances. You have to hold on and believe it will happen for you. . . . Over time I have become more resilient or grounded. My mental health is very dependent on how I take care of the situations I am in.

     However, several dancers also explained how this compartmentalization fostered a negative approach toward mental health, silenced their voice, and led them to bottle up their feelings. Abby described, “If you are sad and can’t handle it, then the director is going to see that, and consequences will happen . . . then it’s the worst . . . we are conditioned to accept whatever is given to us.” Cleo added, “You have to compartmentalize, to hold it in and aren’t allowed to talk about it . . . you’re not allowed to feel the validation of ‘I’m bothered by this.’ It’s almost wrong to feel bothered by this.” When analyzing the data, we noticed that the four participants who were former professional dancers noted an improvement in their mental health after their life in ballet. Sophie also illustrated changes in dancers’ mental health: “It is able to grow and change and be cultivated. So, I do not think mental health as a dancer is fixed.”

Recommendations for Counseling and Advocacy—“The Dance Population Is Unique”
     As the conversation turned toward mental health experiences, all participants expressed recommendations in two areas: counseling and society’s view of ballet dancers and advocacy. 

Counseling
     All participants discussed recommendations for counseling when working with professional ballet dancers. Regarding counseling, Mica shared, “The dance population is unique in itself. A counselor being able to counsel to this is very important.” She further explained, “It’s not the same as advising someone who’s on a basketball team, nor is it the same as advising someone who’s on a theatre crew. It’s just different. It’s an athlete and it’s an artist.”

Abby also urged counselors to recognize trauma among this population: “I think counselors should be aware of emotional abuse and treat dancers as such.” Monica described how ballet dancers joined voices with the MeToo movement: “It just seemed like the movement of women being able to finally express what had happened to them and the abuse they had been enduring was very empowering.” At the same time, she indicated that a lot of people responded with “well that’s just what ballet is.”

Participants highlighted dancers’ absence of mental health services in their work contracts. “Just having someone to talk to would be nice. I know it’s not covered on a lot of health insurances or dancers’ insurance,” said Cleo. “It would be really cool if it were in the context of the studio and dancers could have one session a month at least . . . individual session, group sessions . . . I think a lot of people would jump at the opportunity,” stated Abby. Monica further explained how a counselor could “do a lot to sustain dancers and maybe help their careers because they might be less prone to injury if they aren’t sad and depressed or feeling alone or pushing themselves beyond their breaking point.” She added how counselors may support company staff: “I think there is a lot on the shoulders of the artistic director or one of the ballet mistresses or ballet masters to be an emotional shoulder or a listening ear.”

Another prevalent tenet woven throughout the dancers’ interviews was counselors’ awareness of ballet culture. Three dancers specifically mentioned that if counselors increased their awareness of dance careers, it might help dancers open up to counselors. Paul stated, “I think about when I was dancing, if someone had just been like ‘oh well, you don’t have to be super skinny to dance.’ I’d be like, you don’t know anything, ya know?” Another dancer shared:

Counselors may not need dance experience, but it would be helpful for the dancers if counselors at least have an idea of what a rehearsal day is . . . how many hours we are dancing, how many dancers have second jobs, how often we perform, it adds context . . . having an understanding of the rigors and demands from within the profession.

Society’s View of Ballet Dancers and Advocacy
     At some point in their interviews, all participants described ballet dancers’ mental health as hidden or unknown to society, and therefore believed that the first step for advocacy required awareness. Participants explained that when people go to the theatre to watch The Nutcracker around the holiday season or attend Romeo and Juliet, they see a story, a real-time depiction of magic and narrative. Yet participants felt that this led society to view dancers as having “glamourous lifestyles” or, because of Hollywood, believe that dancers “are frail individuals that do not have a real job, throw their friends down the stairs, and steal husbands.” Cleo openly spoke about the hidden side of the ballet world when sharing her picture:

The idea is that it’s so glamorous and they have this perfect life, it’s like the same way they [society] perceive celebrities and they have these glamourous lives and everything is perfect when you see the surface and the smile you are forced to put on, but they do not see everything that goes on underneath. That’s why I love this photo: you don’t know what the person is actually feeling. . . . On the outside I am a very bubbly person, and people don’t know anything going on behind, I guess behind the curtain.

     Along these same lines, participants advocated for gender equality within the profession. Although no interview questions asked about gender differences, three dancers pointed out this discrepancy by sharing that women are under extreme pressure to maintain their dance careers. Cleo and Abby also identified how most directors were male. Abby expressed this always “trying to appease the person in charge, who is almost always a man.” For five of the participants, the company director played a vital role in how they viewed themselves. Although some dancers noted overall societal changes and awareness that dancers did not have to fit “this anorexic ballerina” stereotype, some felt that overcoming long-lasting traditions in ballet culture of “skinny equals better” required significant change.

Discussion

The purpose of this qualitative study was to provide a better understanding of ballet culture and its impact on dancers’ identity and mental health. More specifically, we sought to explore different facets of professional ballet dancers’ mental health, while also providing cultural context to professional ballet dancers’ lived experiences. Our attention to cultural context is parallel to trends over the past decade reflecting scholars’ increased focus on performing artists’ training environments to understand their experiences (Lewton-Brain, 2012). Using this perspective allowed us to offer recommendations for counseling and advocacy directly inspired by the ballet dancers’ viewpoints.

The findings from this study resemble descriptions of belief systems and practices entrenched in ballet culture previously discussed in the literature (Wulff, 1998, 2008). One overarching premise presented by the dancers was their need to acquire physical strength, stamina, and a “mind over matter” attitude to have successful ballet careers. The positive and negative qualities of ballet culture created a constant push and pull; however, the participants kept dancing. They recognized their hardships and yet believed enduring them was necessary to live their dreams. The ethos of ballet culture made going through hardships—restricting eating, dancing with injuries, and other stressors—worthwhile. Without providing a justification for these physical and emotional injuries, these new findings provide context to understand ballet dancers’ ideas on body, mind, and health. As some dancers shared, ballet was more than a career to them; it was a part of them, and life without it was hard to imagine.

Participant narratives revealed the ballet dancers’ numerous strengths, such as tenacity, grit, learned adaptability, and unbreakable discipline and rigor. At the same time, participants discussed several mental health hardships. To live up to their ballet dancing goals, dancers focused on their most highly used attribute—their bodies. Because of this, body concerns were prevalent in the findings. The dancers also relayed mental struggles and with them a will to succeed and compartmentalize, to carry on for the performance and the art despite physical and/or emotional pain and at times unsupportive or even abusive environments. Their experiences seemed to align with similar concerns shared by tennis player Naomi Osaka and gymnast Simone Biles. To illustrate, Biles withdrew from part of the 2021 Olympics because of a mind and body disconnect. Her decision earned criticism from the public. She later shared her struggles with mental health concerns (i.e., depression) and how stepping down from competition allowed her to prioritize her mental health and protect her body from potential serious injury.

Our findings also aligned with similar results found with elite athletes and performing artists (Åkesdotter et al., 2020; Gorczynski et al., 2017) and ballet literature in other countries that underscore concerns with disordered eating and body image issues that run deep within ballet culture (Clark et al., 2014; van Staden et al., 2009). Participants discussed anxiety, depression, trauma, abuse, and perfectionism. Their discussions indicated a connection, with anxiety and depression feeding into restrictive eating or other types of eating disorders, and an emotional turmoil following when they were unable to have control. Comorbidity between these mental health disorders and eating disorders is prevalent in the literature, and the present findings elucidate a similar connection among professional ballet dancers.

The findings from this study add to our understanding of professional ballet dancers’ mental health across the world by presenting, to the best of our knowledge, the only study within the United States to fully focus on a qualitative exploration of professional ballet dancer mental health experiences. Our findings expand on and reinforce Hebard and Lamberson (2017), whose work implored counselors to advocate for athletes’ mental health awareness. They stressed that athletes are idolized for their physical endurance, and this perception may leave them specifically vulnerable to mental health issues. Our participants expressed a similar concern and desired counseling services integrated into their schedule and provided by a counselor possessing an understanding of the ballet culture and its specific stressors. They believed that mental health services could not only address their mental health struggles and provide trained support, but also reduce physical injuries often caused by repressed feelings of sadness, loneliness, or insecurity. Participants expressed that advocating for this population should focus on increased access to mental health service providers with an awareness of ballet culture.

Lastly, these findings elucidate a need to evaluate aspects of ballet culture ingrained in tradition that can lead to physical and emotional injuries. Conversations about ballet culture and the emphasis on “petite ballerina dancers” are slowly becoming a part of current efforts to dismantle established perceptions of beauty, athleticism, and inclusion. As Pickard (2012) stated about herself as a dancer, “My body is ballet” (p. 25), and participants expressed that for counselors to advocate for and counsel this population, building awareness about this ongoing conversation while acknowledging the impact of ballet culture on professional ballet dancers’ mindset should be a requirement.

Implications for Counseling
     Because of ballet culture and traditions, ballet dancers experience intense physical and mental demands. Counselors must attempt to understand ballet culture as well as its impact on dancer identity and mental health. Counselors need to remain aware of ballet culture when broaching the topic of weight and body identity influences, requirements for a successful ballet dancer, and the relationship between ballet standards and mental health disorders. From the dancers’ perspective, their physical form is directly related to their mental state or how they view themselves. Dancers’ identities intertwine with their bodies from a young age. Although this creates many positive experiences for the dancers, they also expressed how this can lead to depression, anxiety, and other mental health disorders. Considering these experiences, we encourage counselors to support dancers with a client-centered approach and to create an atmosphere of understanding about the dancers’ physical form as integral to their identity and their profession. Utilizing a client-centered approach would allow counselors to inquire about the dancers’ professional experience and help them build an understanding of the professional demands of ballet. Additionally, we encourage counselors to help professional ballet dancers explore their internal self-talk around comparing themselves to others and their relationship with their body.

Although not as prevalent in the data, the dancer statements about abuse are just as vital for counselor awareness. As Monica stated, ballet is a culture with centuries-old traditions and, according to five of the dancers, artist leadership tends to be authoritative in nature. Ballet requires certain physical attributes and training to achieve professional status, which can manifest as abusive relationships and power struggles. We suggest that counselors help professional dancers learn when certain demands may be perceived as abuse by the world outside of the studio. Providing psychoeducation of abuse (e.g., different forms of abuse, power and control wheel) can help ballet dancers differentiate these behaviors and seek help, when needed.

Although many dancers in this study expressed wanting counseling, it seems as though they feared counselors would not understand them or why they committed to such an intense lifestyle. The central need, according to the dancers, is for counselors to be aware of the unique ballet culture. For many dancers, ballet was a part of them, their identity, and something they felt drawn to always be improving. It is not a sport or a hobby, though there seem to be some commonalities between professional ballet dancers and elite athletes. According to the literature (Åkesdotter et al., 2020; Gorczynski et al., 2017), elite athletes experience intense physical demands and elevated anxiety. Our current findings from the dancers are comparable to these features. Therefore, counselors working with dancers may find some similarities with sports counseling. However, counselors should remain aware that sports are for competition and winning, whereas ballet is an art that seeks to provide the audience enjoyment and entertainment.

Limitations and Suggestions for Future Research
     As with all research, limitations exist because of many factors. For example, this study engaged a small, homogenous sample of ballet dancers with limited opportunity to dive deeply into within-group differences. All participants identified as Caucasian and many of the dancers had resided in the same geographical location at one point. We recognize that racial and geographical differences, among others, can significantly impact participants’ mental health experiences.

In addition, seven of the eight participants had experienced a prior dance connection with Gregory. Although this may have contributed to trust and more candid interviews, it is also possible that this resulted in biases despite our measures to ensure trustworthiness (e.g., weekly research meetings in order to bracket).

Another limitation is the ballet dancers’ subjective representation of their own mental health. Their illustrations of their experiences provide an inner look at their mental health yet do not guarantee an accurate or clinical representation of their experiences.

Because of the limited research examining professional ballet dancer mental health experiences, many opportunities remain open for future research. One recommendation is for future researchers to consider within-group differences (e.g., race, gender) through recruitment of a heterogenous sample. Also, considering the study’s participants all identified as Caucasian, we recommend future researchers explore the mental health experiences of minority ballet dancers, as they tend to be underrepresented in professional ballet companies in the United States. Additionally, this study included both former and current professional ballet dancers. Researchers may discover insightful data using a longitudinal study, as this could display information about the career transition period from professional dancer to former professional dancer. Other recommendations for future research include quantitative studies focusing on counseling interventions or prevention. Finally, some participants discussed instances of trauma, depression, and anxiety. Future researchers could examine specific mental health disorders and their comorbidity among ballet dancers by using the GAD-7 (Spitzer et al., 2006) for assessing anxiety and the BDI-II (Beck et al., 1996) for depression.

Conclusion

     This qualitative study explored ballet culture and identity and their impact on professional ballet dancers’ mental health experiences, which resulted in the four themes of (a) ballet culture—“it’s not all tutus and tiaras”; (b) professional ballet dancers’ identity—“it is a part of me”; (c) mental health experiences—“you have to compartmentalize”; and (d) counseling and advocacy—“the dance population is unique.” A distinct culture exists for professional ballet dancers that includes traditions passed down since the 14th century. Hence, tradition, dedication, and commitment to their profession shape professional ballet dancers’ identities. Further, their identities straddle the environments of performing artists and elite athletes, creating contextually distinctive experiences. For counselors to adequately support professional ballet dancers, they must first build their awareness of ballet culture and the unique mental health needs and resiliencies of dancers.

 

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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J. Claire Gregory, MA, NCC, LPC, LCDC, is a doctoral candidate at the University of Texas at San Antonio. Claudia G. Interiano-Shiverdecker, PhD, is an assistant professor at the University of Texas at San Antonio. Correspondence may be addressed to J. Claire Gregory, Department of Counseling, 501 W. César E. Chávez Boulevard, San Antonio, TX 78207-4415, jessica.gregory@utsa.edu.

 

Appendix

Interview Protocol

 

  1. Tell me a little bit about yourself.
  2. Tell me about the picture you took and how this represents your understanding of mental health as a professional ballet dancer.
  3. Is this picture representative of your mental health? If so, how?
  4. What do you see here when you look at your picture?
  5. What are you trying to convey to someone who is looking at your picture?
  6. Describe how this image relates to society and what prevailing ideas about your mental health are present in this picture.
  7. What are some strengths about being a professional ballet dancer?
  8. What can we as counselors do about ballet dancers’ mental health?
  9. Is there anything else you would like to add?

Validation of the Adapted Response to Stressful Experiences Scale (RSES-4) Among First Responders

Warren N. Ponder, Elizabeth A. Prosek, Tempa Sherrill

 

First responders are continually exposed to trauma-related events. Resilience is evidenced as a protective factor for mental health among first responders. However, there is a lack of assessments that measure the construct of resilience from a strength-based perspective. The present study used archival data from a treatment-seeking sample of 238 first responders to validate the 22-item Response to Stressful Experiences Scale (RSES-22) and its abbreviated version, the RSES-4, with two confirmatory factor analyses. Using a subsample of 190 first responders, correlational analyses were conducted of the RSES-22 and RSES-4 with measures of depressive symptoms, post-traumatic stress, anxiety, and suicidality confirming convergent and criterion validity. The two confirmatory analyses revealed a poor model fit for the RSES-22; however, the RSES-4 demonstrated an acceptable model fit. Overall, the RSES-4 may be a reliable and valid measure of resilience for treatment-seeking first responder populations.

Keywords: first responders, resilience, assessment, mental health, confirmatory factor analysis

 

     First responder populations (i.e., law enforcement, emergency medical technicians, and fire rescue) are often repeatedly exposed to traumatic and life-threatening conditions (Greinacher et al., 2019). Researchers have concluded that such critical incidents could have a deleterious impact on first responders’ mental health, including the development of symptoms associated with post-traumatic stress, anxiety, depression, or other diagnosable mental health disorders (Donnelly & Bennett, 2014; Jetelina et al., 2020; Klimley et al., 2018; Weiss et al., 2010). In a systematic review, Wild et al. (2020) suggested the promise of resilience-based interventions to relieve trauma-related psychological disorders among first responders. However, they noted the operationalization and measure of resilience as limitations to their intervention research. Indeed, researchers have conflicting viewpoints on how to define and assess resilience. For example, White et al. (2010) purported popular measures of resilience rely on a deficit-based approach. Counselors operate from a strength-based lens (American Counseling Association [ACA], 2014) and may prefer measures with a similar perspective. Additionally, counselors are mandated to administer assessments with acceptable psychometric properties that are normed on populations representative of the client (ACA, 2014, E.6.a., E.7.d.). For counselors working with first responder populations, resilience may be a factor of importance; however, appropriately measuring the construct warrants exploration. Therefore, the focus of this study was to validate a measure of resilience with strength-based principles among a sample of first responders.

Risk and Resilience Among First Responders

In a systematic review of the literature, Greinacher et al. (2019) described the incidents that first responders may experience as traumatic, including first-hand life-threatening events; secondary exposure and interaction with survivors of trauma; and frequent exposure to death, dead bodies, and injury. Law enforcement officers (LEOs) reported that the most severe critical incidents they encounter are making a mistake that injures or kills a colleague; having a colleague intentionally killed; and making a mistake that injures or kills a bystander (Weiss et al., 2010). Among emergency medical technicians (EMTs), critical incidents that evoked the most self-reported stress included responding to a scene involving family, friends, or others to the crew and seeing someone dying (Donnelly & Bennett, 2014). Exposure to these critical incidents may have consequences for first responders. For example, researchers concluded first responders may experience mental health symptoms as a result of the stress-related, repeated exposure (Jetelina et al., 2020; Klimley et al., 2018; Weiss et al., 2010). Moreover, considering the cumulative nature of exposure (Donnelly & Bennett, 2014), researchers concluded first responders are at increased risk for post-traumatic stress disorder (PTSD), depression, and generalized anxiety symptoms (Jetelina et al., 2020; Klimley et al., 2018; Weiss et al., 2010). Symptoms commonly experienced among first responders include those associated with post-traumatic stress, anxiety, and depression.

In a collective review of first responders, Kleim and Westphal (2011) determined a prevalence rate for PTSD of 8%–32%, which is higher than the general population lifetime rate of 6.8–7.8 % (American Psychiatric Association [APA], 2013; National Institute of Mental Health [NIMH], 2017). Some researchers have explored rates of PTSD by specific first responder population. For example, Klimley et al. (2018) concluded that 7%–19% of LEOs and 17%–22% of firefighters experience PTSD. Similarly, in a sample of LEOs, Jetelina and colleagues (2020) reported 20% of their participants met criteria for PTSD.

Generalized anxiety and depression are also prevalent mental health symptoms for first responders. Among a sample of firefighters and EMTs, 28% disclosed anxiety at moderate–severe and several levels (Jones et al., 2018). Furthermore, 17% of patrol LEOs reported an overall prevalence of generalized anxiety disorder (Jetelina et al., 2020). Additionally, first responders may be at higher risk for depression (Klimley et al., 2018), with estimated prevalence rates of 16%–26% (Kleim & Westphal, 2011). Comparatively, the past 12-month rate of major depressive disorder among the general population is 7% (APA, 2013). In a recent study, 16% of LEOs met criteria for major depressive disorder (Jetelina et al., 2020). Moreover, in a sample of firefighters and EMTs, 14% reported moderate–severe and severe depressive symptoms (Jones et al., 2018). Given these higher rates of distressful mental health symptoms, including post-traumatic stress, generalized anxiety, and depression, protective factors to reduce negative impacts are warranted.

Resilience
     Broadly defined, resilience is “the ability to adopt to and rebound from change (whether it is from stress or adversity) in a healthy, positive and growth-oriented manner” (Burnett, 2017, p. 2). White and colleagues (2010) promoted a positive psychology approach to researching resilience, relying on strength-based characteristics of individuals who adapt after a stressor event. Similarly, other researchers explored how individuals’ cognitive flexibility, meaning-making, and restoration offer protection that may be collectively defined as resilience (Johnson et al., 2011).

A key element among definitions of resilience is one’s exposure to stress. Given their exposure to trauma-related incidents, first responders require the ability to cope or adapt in stressful situations (Greinacher et al., 2019). Some researchers have defined resilience as a strength-based response to stressful events (Burnett, 2017), in which healthy coping behaviors and cognitions allow individuals to overcome adverse experiences (Johnson et al., 2011; White et al., 2010). When surveyed about positive coping strategies, first responders most frequently reported resilience as important to their well-being (Crowe et al., 2017).

Researchers corroborated the potential impact of resilience for the population. For example, in samples of LEOs, researchers confirmed resilience served as a protective factor for PTSD (Klimley et al., 2018) and as a mediator between social support and PTSD symptoms (McCanlies et al., 2017). In a sample of firefighters, individual resilience mediated the indirect path between traumatic events and global perceived stress of PTSD, along with the direct path between traumatic events and PTSD symptoms (Lee et al., 2014). Their model demonstrated that those with higher levels of resilience were more protected from traumatic stress. Similarly, among emergency dispatchers, resilience was positively correlated with positive affect and post-traumatic growth, and negatively correlated with job stress (Steinkopf et al., 2018). The replete associations of resilience as a protective factor led researchers to develop resilience-based interventions. For example, researchers surmised promising results from mindfulness-based resilience interventions for firefighters (Joyce et al., 2019) and LEOs (Christopher et al., 2018). Moreover, Antony and colleagues (2020) concluded that resilience training programs demonstrated potential to reduce occupational stress among first responders.

Assessment of Resilience
     Recognizing the significance of resilience as a mediating factor in PTSD among first responders and as a promising basis for interventions when working with LEOs, a reliable means to measure it among first responder clients is warranted. In a methodological review of resilience assessments, Windle and colleagues (2011) identified 19 different measures of resilience. They found 15 assessments were from original development and validation studies with four subsequent validation manuscripts from their original assessment, of which none were developed with military or first responder samples.

Subsequently, Johnson et al. (2011) developed the Response to Stressful Experiences Scale (RSES-22) to assess resilience among military populations. Unlike deficit-based assessments of resilience, they proposed a multidimensional construct representing how individuals respond to stressful experiences in adaptive or healthy ways. Cognitive flexibility, meaning-making, and restoration were identified as key elements when assessing for individuals’ characteristics connected to resilience when overcoming hardships. Initially they validated a five-factor structure for the RSES-22 with military active-duty and reserve components. Later, De La Rosa et al. (2016) re-examined the RSES-22. De La Rosa and colleagues discovered a unidimensional factor structure of the RSES-22 and validated a shorter 4-item subset of the instrument, the RSES-4, again among military populations.

It is currently unknown if the performance of the RSES-4 can be generalized to first responder populations. While there are some overlapping experiences between military populations and first responders in terms of exposure to trauma and high-risk occupations, the Substance Abuse and Mental Health Services Administration (SAMHSA; 2018) suggested differences in training and types of risk. In the counseling profession, these populations are categorized together, as evidenced by the Military and Government Counseling Association ACA division. Additionally, there may also be dual identities within the populations. For example, Lewis and Pathak (2014) found that 22% of LEOs and 15% of firefighters identified as veterans. Although the similarities of the populations may be enough to theorize the use of the same resilience measure, validation of the RSES-22 and RSES-4 among first responders remains unexamined.

Purpose of the Study
     First responders are repeatedly exposed to traumatic and stressful events (Greinacher et al., 2019) and this exposure may impact their mental health, including symptoms of post-traumatic stress, anxiety, depression, and suicidality (Jetelina et al., 2020; Klimley et al., 2018). Though most measures of resilience are grounded in a deficit-based approach, researchers using a strength-based approach proposed resilience may be a protective factor for this population (Crowe et al., 2017; Wild et al., 2020). Consequently, counselors need a means to assess resilience in their clinical practice from a strength-based conceptualization of clients.

Johnson et al. (2011) offered a non-deficit approach to measuring resilience in response to stressful events associated with military service. Thus far, researchers have conducted analyses of the RSES-22 and RSES-4 with military populations (De La Rosa et al., 2016; Johnson et al., 2011; Prosek & Ponder, 2021), but not yet with first responders. While there are some overlapping characteristics between the populations, there are also unique differences that warrant research with discrete sampling (SAMHSA, 2018). In light of the importance of resilience as a protective factor for mental health among first responders, the purpose of the current study was to confirm the reliability and validity of the RSES-22 and RSES-4 when utilized with this population. In the current study, we hypothesized the measures would perform similarly among first responders and if so, the RSES-4 would offer counselors a brief assessment option in clinical practice that is both reliable and valid.

Method

Participants
     Participants in the current non-probability, purposive sample study were first responders (N = 238) seeking clinical treatment at an outpatient, mental health nonprofit organization in the Southwestern United States. Participants’ mean age was 37.53 years (SD = 10.66). The majority of participants identified as men (75.2%; n = 179), with women representing 24.8% (n = 59) of the sample. In terms of race and ethnicity, participants identified as White (78.6%; n = 187), Latino/a (11.8%; n = 28), African American or Black (5.5%; n = 13), Native American (1.7%; n = 4), Asian American (1.3%; n = 3), and multiple ethnicities (1.3%; n = 3). The participants identified as first responders in three main categories: LEO (34.9%; n = 83), EMT (28.2%; n = 67), and fire rescue (25.2%; n = 60). Among the first responders, 26.9% reported previous military affiliation. As part of the secondary analysis, we utilized a subsample (n = 190) that was reflective of the larger sample (see Table 1).

Procedure
     The data for this study were collected between 2015–2020 as part of the routine clinical assessment procedures at a nonprofit organization serving military service members, first responders, frontline health care workers, and their families. The agency representatives conduct clinical assessments with clients at intake, Session 6, Session 12, and Session 18 or when clinical services are concluded. We consulted with the second author’s Institutional Review Board, which determined the research as exempt, given the de-identified, archival nature of the data. For inclusion in this analysis, data needed to represent first responders, ages 18 or older, with a completed RSES-22 at intake. The RSES-4 are four questions within the RSES-22 measure; therefore, the participants did not have to complete an additional measure. For the secondary analysis, data from participants who also completed other mental health measures at intake were also included (see Measures).

 

Table 1

Demographics of Sample

Characteristic Sample 1

(N = 238)

Sample 2

(n = 190)

Age (Years)
    Mean 37.53 37.12
    Median 35.50 35.00
    SD 10.66 10.30
    Range 46 45
Time in Service (Years)
    Mean 11.62 11.65
    Median 10.00 10.00
    SD   9.33   9.37
    Range   41 39
n (%)
First Responder Type
    Emergency Medical
Technicians
67 (28.2%) 54 (28.4%)
    Fire Rescue 60 (25.2%) 45 (23.7%)
    Law Enforcement 83 (34.9%) 72 (37.9%)
    Other  9 (3.8%) 5 (2.6%)
    Two or more 10 (4.2%) 6 (3.2%)
    Not reported  9 (3.8%) 8 (4.2%)
Gender
    Women   59 (24.8%)   47 (24.7%)
    Men 179 (75.2%) 143 (75.3%)
Ethnicity
    African American/Black 13 (5.5%) 8 (4.2%)
    Asian American   3 (1.3%) 3 (1.6%)
    Latino(a)/Hispanic  28 (11.8%) 24 (12.6%)
    Multiple Ethnicities  3 (1.3%) 3 (1.6%)
    Native American  4 (1.7%) 3 (1.6%)
    White 187 (78.6%) 149 (78.4%)

Note. Sample 2 is a subset of Sample 1. Time in service for Sample 1, n = 225;
time in service for Sample 2, n = 190.

 

Measures
Response to Stressful Experiences Scale
     The Response to Stressful Experiences Scale (RSES-22) is a 22-item measure to assess dimensions of resilience, including meaning-making, active coping, cognitive flexibility, spirituality, and self-efficacy (Johnson et al., 2011). Participants respond to the prompt “During and after life’s most stressful events, I tend to” on a 5-point Likert scale from 0 (not at all like me) to 4 (exactly like me). Total scores range from 0 to 88 in which higher scores represent greater resilience. Example items include see it as a challenge that will make me better, pray or meditate, and find strength in the meaning, purpose, or mission of my life. Johnson et al. (2011) reported the RSES-22 demonstrates good internal consistency (α = .92) and test-retest reliability (α = .87) among samples from military populations. Further, the developers confirmed convergent, discriminant, concurrent, and incremental criterion validity (see Johnson et al., 2011). In the current study, Cronbach’s alpha of the total score was .93. 

Adapted Response to Stressful Experiences Scale
     The adapted Response to Stressful Experiences Scale (RSES-4) is a 4-item measure to assess resilience as a unidimensional construct (De La Rosa et al., 2016). The prompt and Likert scale are consistent with the original RSES-22; however, it only includes four items: find a way to do what’s necessary to carry on, know I will bounce back, learn important and useful life lessons, and practice ways to handle it better next time. Total scores range from 0 to 16, with higher scores indicating greater resilience. De La Rosa et al. (2016) reported acceptable internal consistency (α = .76–.78), test-retest reliability, and demonstrated criterion validity among multiple military samples. In the current study, the Cronbach’s alpha of the total score was .74.

Patient Health Questionnaire-9
     The Patient Health Questionnaire-9 (PHQ-9) is a 9-item measure to assess depressive symptoms in the past 2 weeks (Kroenke et al., 2001). Respondents rate the frequency of their symptoms on a 4-point Likert scale ranging from 0 (not at all) to 3 (nearly every day). Total scores range from 0 to 27, in which higher scores indicate increased severity of depressive symptoms. Example items include little interest or pleasure in doing things and feeling tired or having little energy. Kroenke et al. (2001) reported good internal consistency (α = .89) and established criterion and construct validity. In this sample, Cronbach’s alpha of the total score was .88.

PTSD Checklist-5
     The PTSD Checklist-5 (PCL-5) is a 20-item measure for the presence of PTSD symptoms in the past month (Blevins et al., 2015). Participants respond on a 5-point Likert scale indicating frequency of PTSD-related symptoms from 0 (not at all) to 4 (extremely). Total scores range from 0 to 80, in which higher scores indicate more severity of PTSD-related symptoms. Example items include repeated, disturbing dreams of the stressful experience and trouble remembering important parts of the stressful experience. Blevins et al. (2015) reported good internal consistency (α = .94) and determined convergent and discriminant validity. In this sample, Cronbach’s alpha of the total score was .93.

Generalized Anxiety Disorder-7
     The Generalized Anxiety Disorder-7 (GAD-7) is a 7-item measure to assess for anxiety symptoms over the past 2 weeks (Spitzer et al., 2006). Participants rate the frequency of the symptoms on a 4-point Likert scale ranging from 0 (not at all) to 3 (nearly every day). Total scores range from 0 to 21 with higher scores indicating greater severity of anxiety symptoms. Example items include not being able to stop or control worrying and becoming easily annoyed or irritable. Among patients from primary care settings, Spitzer et al. (2006) determined good internal consistency (α = .92) and established criterion, construct, and factorial validity. In this sample, Cronbach’s alpha of the total score was .91.

Suicidal Behaviors Questionnaire-Revised
     The Suicidal Behaviors Questionnaire-Revised (SBQ-R) is a 4-item measure to assess suicidality (Osman et al., 2001). Each item assesses a different dimension of suicidality: lifetime ideation and attempts, frequency of ideation in the past 12 months, threat of suicidal behaviors, and likelihood of suicidal behaviors (Gutierrez et al., 2001). Total scores range from 3 to 18, with higher scores indicating more risk of suicide. Example items include How often have you thought about killing yourself in the past year? and How likely is it that you will attempt suicide someday? In a clinical sample, Osman et al. (2001) reported good internal consistency (α = .87) and established criterion validity. In this sample, Cronbach’s alpha of the total score was .85.

Data Analysis
     Statistical analyses were conducted using SPSS version 26.0 and SPSS Analysis of Moment Structures (AMOS) version 26.0. We examined the dataset for missing values, replacing 0.25% (32 of 12,836 values) of data with series means. We reviewed descriptive statistics of the RSES-22 and RSES-4 scales. We determined multivariate normality as evidenced by skewness less than 2.0 and kurtosis less than 7.0 (Dimitrov, 2012). We assessed reliability for the scales by interpreting Cronbach’s alphas and inter-item correlations to confirm internal consistency.

We conducted two separate confirmatory factor analyses to determine the model fit and factorial validity of the 22-item measure and adapted 4-item measure. We used several indices to conclude model fit: minimum discrepancy per degree of freedom (CMIN/DF) and p-values, root mean residual (RMR), goodness-of-fit index (GFI), comparative fit index (CFI), Tucker-Lewis index (TLI), and the root mean square error of approximation (RMSEA). According to Dimitrov (2012), values for the CMIN/DF < 2.0,p > .05, RMR < .08, GFI > .90, CFI > .90, TLI > .90, and RMSEA < .10 provide evidence of a strong model fit. To determine criterion validity, we assessed a subsample of participants (n = 190) who had completed the RSES-22, RSES-4, and four other psychological measures (i.e., PHQ-9, PCL-5, GAD-7, and SBQ-R). We determined convergent validity by conducting bivariate correlations between the RSES-22 and RSES-4.

Results

Descriptive Analyses
     We computed means, standard deviations, 95% confidence interval (CI), and score ranges for the RSES-22 and RSES-4 (Table 2). Scores on the RSES-22 ranged from 19–88. Scores on the RSES-4 ranged from 3–16. Previous researchers using the RSES-22 on military samples reported mean scores of 57.64–70.74 with standard deviations between 8.15–15.42 (Johnson et al., 2011; Prosek & Ponder, 2021). In previous research of the RSES-4 with military samples, mean scores were 9.95–11.20 with standard deviations between 3.02–3.53(De La Rosa et al., 2016; Prosek & Ponder, 2021).

 

Table 2

Descriptive Statistics for RSES-22 and RSES-4

Variable M SD 95% CI Score Range
RSES-22 scores 60.12 13.76 58.52, 61.86 19–88
RSES-4 scores 11.66 2.62 11.33, 11.99 3–16

Note. N = 238. RSES-22 = Response to Stressful Experiences Scale 22-item; RSES-4 = Response
to Stressful Experiences Scale 4-item adaptation.


Reliability Analyses
     To determine the internal consistency of the resiliency measures, we computed Cronbach’s alphas. For the RSES-22, we found strong evidence of inter-item reliability (α = .93), which was consistent with the developers’ estimates (α = .93; Johnson et al., 2011). For the RSES-4, we assessed acceptable inter-item reliability (α = .74), which was slightly lower than previous estimates (α = .76–.78; De La Rosa et al., 2016). We calculated the correlation between items and computed the average of all the coefficients. The average inter-item correlation for the RSES-22 was .38, which falls within the acceptable range (.15–.50). The average inter-item correlation for the RSES-4 was .51, slightly above the acceptable range. Overall, evidence of internal consistency was confirmed for each scale. 

Factorial Validity Analyses
     We conducted two confirmatory factor analyses to assess the factor structure of the RSES-22 and RSES-4 for our sample of first responders receiving mental health services at a community clinic (Table 3). For the RSES-22, a proper solution converged in 10 iterations. Item loadings ranged between .31–.79, with 15 of 22 items loading significantly ( > .6) on the latent variable. It did not meet statistical criteria for good model fit: χ2 (209) = 825.17, p = .000, 90% CI [0.104, 0.120]. For the RSES-4, a proper solution converged in eight iterations. Item loadings ranged between .47–.80, with three of four items loading significantly ( > .6) on the latent variable. It met statistical criteria for good model fit: χ2 (2) = 5.89, p = .053, 90% CI [0.000, 0.179]. The CMIN/DF was above the suggested < 2.0 benchmark; however, the other fit indices indicated a model fit.

 

Table 3

Confirmatory Factor Analysis Fit Indices for RSES-22 and RSES-4

Variable df χ2 CMIN/DF RMR GFI CFI TLI RMSEA 90% CI
RSES-22 209 825.17/.000 3.95 .093 .749 .771 0.747 .112 0.104, 0.120
RSES-4    2    5.89/.053 2.94 .020 .988 .981 0.944 .091 0.000, 0.179

Note. N = 238. RSES-22 = Response to Stressful Experiences Scale 22-item; RSES-4 = Response to Stressful Experiences Scale 4-item adaptation; CMIN/DF = Minimum Discrepancy per Degree of Freedom; RMR = Root Mean Square Residual;
GFI = Goodness-of-Fit Index; CFI = Comparative Fit Index; TLI = Tucker-Lewis Index; RMSEA = Root Mean Squared Error of Approximation.

 

Criterion and Convergent Validity Analyses
     To assess for criterion validity of the RSES-22 and RSES-4, we conducted correlational analyses with four established psychological measures (Table 4). We utilized a subsample of participants (n = 190) who completed the PHQ-9, PCL-5, GAD-7, and SBQ-R at intake. Normality of the data was not a concern because analyses established appropriate ranges for skewness and kurtosis (± 1.0). The internal consistency of the RSES-22 (α = .93) and RSES-4 (α = .77) of the subsample was comparable to the larger sample and previous studies. The RSES-22 and RSES-4 related to the psychological measures of distress in the expected direction, meaning measures were significantly and negatively related, indicating that higher resiliency scores were associated with lower scores of symptoms associated with diagnosable mental health disorders (i.e., post-traumatic stress, anxiety, depression, and suicidal behavior). We verified convergent validity with a correlational analysis of the RSES-22 and RSES-4, which demonstrated a significant and positive relationship.

 

Table 4

Criterion and Convergent Validity of RSES-22 and RSES-4

M (SD) Cronbach’s α RSES-22 PHQ-9 PCL-5 GAD-7 SBQ-R
RSES-22 60.16 (14.17) .93 −.287* −.331* −.215* −.346*
RSES-4 11.65 (2.68) .77 .918 −.290* −.345* −.220* −.327*

Note. n = 190. RSES-22 = Response to Stressful Experiences Scale 22-item; RSES-4 = Response to Stressful Experiences Scale 4-item adaptation; PHQ-9 = Patient Health Questionnaire-9;
PCL-5 = PTSD Checklist-5; GAD-7 = Generalized Anxiety Disorder-7; SBQ-R = Suicidal Behaviors Questionnaire-Revised.
*p < .01.

 

Discussion

The purpose of this study was to validate the factor structure of the RSES-22 and the abbreviated RSES-4 with a first responder sample. Aggregated means were similar to those in the articles that validated and normed the measures in military samples (De La Rosa et al., 2016; Johnson et al., 2011; Prosek & Ponder, 2021). Additionally, the internal consistency was similar to previous studies. In the original article, Johnson et al. (2011) proposed a five-factor structure for the RSES-22, which was later established as a unidimensional assessment after further exploratory factor analysis (De La Rosa et al., 2016). Subsequently, confirmatory factor analyses with a treatment-seeking veteran population revealed that the RSES-22 demonstrated unacceptable model fit, whereas the RSES-4 demonstrated a good model fit (Prosek & Ponder, 2021). In both samples, the RSES-4 GFI, CFI, and TLI were all .944 or higher, whereas the RSES-22 GFI, CFI, and TLI were all .771 or lower. Additionally, criterion and convergent validity as measured by the PHQ-9, PCL-5, and GAD-7 in both samples were extremely close. Similarly, in this sample of treatment-seeking first responders, confirmatory factor analyses indicated an inadequate model fit for the RSES-22 and a good model fit for the RSES-4. Lastly, convergent and criterion validity were established with correlation analyses of the RSES-22 and RSES-4 with four other standardized assessment instruments (i.e., PHQ-9, PCL-5, GAD-7, SBQ-R). We concluded that among the first responder sample, the RSES-4 demonstrated acceptable psychometric properties, as well as criterion and convergent validity with other mental health variables (i.e., post-traumatic stress, anxiety, depression, and suicidal behavior).

Implications for Clinical Practice
     First responders are a unique population and are regularly exposed to trauma (Donnelly & Bennett, 2014; Jetelina et al., 2020; Klimley et al., 2018; Weiss et al., 2010). Although first responders could potentially benefit from espousing resilience, they are often hesitant to seek mental health services (Crowe et al., 2017; Jones, 2017). The RSES-22 and RSES-4 were originally normed with military populations. The results of the current study indicated initial validity and reliability among a first responder population, revealing that the RSES-4 could be useful for counselors in assessing resilience.

It is important to recognize that first responders have perceived coping with traumatic stress as an individual process (Crowe et al., 2017) and may believe that seeking mental health services is counter to the emotional and physical training expectations of the profession (Crowe et al., 2015). Therefore, when first responders seek mental health care, counselors need to be prepared to provide culturally responsive services, including population-specific assessment practices and resilience-oriented care.

Jones (2017) encouraged a comprehensive intake interview and battery of appropriate assessments be conducted with first responder clients. Counselors need to balance the number of intake questions while responsibly assessing for mental health comorbidities such as post-traumatic stress, anxiety, depression, and suicidality. The RSES-4 provides counselors a brief, yet targeted assessment of resilience.

Part of what cultural competency entails is assessing constructs (e.g., resilience) that have been shown to be a protective factor against PTSD among first responders (Klimley et al., 2018). Since the items forming the RSES-4 were developed to highlight the positive characteristics of coping (Johnson et al., 2011), rather than a deficit approach, this aligns with the grounding of the counseling profession. It is also congruent with first responders’ perceptions of resilience. Indeed, in a content analysis of focus group interviews with first responders, participants defined resilience as a positive coping strategy that involves emotional regulation, perseverance, personal competence, and physical fitness (Crowe et al., 2017).

The RSES-4 is a brief, reliable, and valid measure of resilience with initial empirical support among a treatment-seeking first responder sample. In accordance with the ACA (2014) Code of Ethics, counselors are to administer assessments normed with the client population (E.8.). Thus, the results of the current study support counselors’ use of the measure in practice. First responder communities are facing unprecedented work tasks in response to COVID-19. Subsequently, their mental health might suffer (Centers for Disease Control and Prevention, 2020) and experts have recommended promoting resilience as a protective factor for combating the negative mental health consequences of COVID-19 (Chen & Bonanno, 2020). Therefore, the relevance of assessing resilience among first responder clients in the current context is evident.

Limitations and Future Research
     This study is not without limitations. The sample of first responders was homogeneous in terms of race, ethnicity, and gender. Subsamples of first responders (i.e., LEO, EMT, fire rescue) were too small to conduct within-group analyses to determine if the factor structure of the RSES-22 and RSES-4 would perform similarly. Also, our sample of first responders included two emergency dispatchers. Researchers reported that emergency dispatchers should not be overlooked, given an estimated 13% to 15% of emergency dispatchers experience post-traumatic symptomatology (Steinkopf et al., 2018). Future researchers may develop studies that further explore how, if at all, emergency dispatchers are represented in first responder research.

Furthermore, future researchers could account for first responders who have prior military service. In a study of LEOs, Jetelina et al. (2020) found that participants with military experience were 3.76 times more likely to report mental health concerns compared to LEOs without prior military affiliation. Although we reported the prevalence rate of prior military experience in our sample, the within-group sample size was not sufficient for additional analyses. Finally, our sample represented treatment-seeking first responders. Future researchers may replicate this study with non–treatment-seeking first responder populations.

Conclusion
     First responders are at risk for sustaining injuries, experiencing life-threatening events, and witnessing harm to others (Lanza et al., 2018). The nature of their exposure can be repeated and cumulative over time (Donnelly & Bennett, 2014), indicating an increased risk for post-traumatic stress, anxiety, and depressive symptoms, as well as suicidal behavior (Jones et al., 2018). Resilience is a promising protective factor that promotes wellness and healthy coping among first responders (Wild et al., 2020), and counselors may choose to routinely measure for resilience among first responder clients. The current investigation concluded that among a sample of treatment-seeking first responders, the original factor structure of the RSES-22 was unstable, although it demonstrated good reliability and validity. The adapted version, RSES-4, demonstrated good factor structure while also maintaining acceptable reliability and validity, consistent with studies of military populations (De La Rosa et al., 2016; Johnson et al., 2011; Prosek & Ponder, 2021). The RSES-4 provides counselors with a brief and strength-oriented option for measuring resilience with first responder clients.

 

Conflict of Interest and Funding Disclosure
The authors reported no conflict of interest
or funding contributions for the development
of this manuscript.

 

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Warren N. Ponder, PhD, is Director of Outcomes and Evaluation at One Tribe Foundation. Elizabeth A. Prosek, PhD, NCC, LPC, is an associate professor at Penn State University. Tempa Sherrill, MS, LPC-S, is the founder of Stay the Course and a volunteer at One Tribe Foundation. Correspondence may be addressed to Warren N. Ponder, 855 Texas St., Suite 105, Fort Worth, TX 76102, warren@1tribefoundation.org.

Mental Health Epigenetics: A Primer With Implications for Counselors

David E. Jones, Jennifer S. Park, Katie Gamby, Taylor M. Bigelow, Tesfaye B. Mersha, Alonzo T. Folger

 

Epigenetics is the study of modifications to gene expression without an alteration to the DNA sequence. Currently there is limited translation of epigenetics to the counseling profession. The purpose of this article is to inform counseling practitioners and counselor educators about the potential role epigenetics plays in mental health. Current mental health epigenetic research supports that adverse psychosocial experiences are associated with mental health disorders such as schizophrenia, anxiety, depression, and addiction. There are also positive epigenetic associations with counseling interventions, including cognitive behavioral therapy, mindfulness, diet, and exercise. These mental health epigenetic findings have implications for the counseling profession such as engaging in early life span health prevention and wellness, attending to micro and macro environmental influences during assessment and treatment, collaborating with other health professionals in epigenetic research, and incorporating epigenetic findings into counselor education curricula that meet the standards of the Council for Accreditation of Counseling and Related Educational Programs (CACREP).

Keywords: epigenetics, mental health, counseling, prevention and wellness, counselor education

 

Epigenetics, defined as the study of chemical changes at the cellular level that alter gene expression but do not alter the genetic code (T.-Y. Zhang & Meaney, 2010), has emerging significance for the profession of counseling. Historically, people who studied abnormal behavior focused on determining whether the cause of poor mental health outcomes was either “nature or nurture” (i.e., either genetics or environmental factors). What we now understand is that both nature and nurture, or the interaction between the individual and their environment (e.g., neglect, trauma, substance abuse, diet, social support, exercise), can modify gene expression positively or negatively (Cohen et al., 2017; Suderman et al., 2014).

In the concept of nature and nurture, there is evidence that psychosocial experiences can change the landscape of epigenetic chemical tags across the genome. This change in landscape influences mental health concerns, such as addiction, anxiety, and depression, that are addressed by counseling practitioners (Lester et al., 2016; Provençal & Binder, 2015; Szyf et al., 2016). Because the field of epigenetics is evolving and there is limited attention to epigenetics in the counseling profession, our purpose is to inform counseling practitioners and educators about the role epigenetics may play in clinical mental health counseling.

Though many counselors and counselor educators may have taken a biology class that covered genetics sometime during their professional education, we provide pedagogical scaffolding from genetics to epigenetics. Care was taken to ensure accessibility of information for readers across this continuum of genetics knowledge. Much of what we offer below on genetics is putative knowledge, as we desire to establish a foundation for the reader in genetics so they may be able to have a greater understanding of epigenetics and a clearer comprehension of the implications we offer leading to application in counseling. We suggest readers review Brooker (2017) for more detailed information on genetics. We will present an overview of genetics and epigenetics, an examination of mental health epigenetics, and implications for the counseling profession.

Genetics
     Genetics is the study of heredity (Brooker, 2017) and the cellular process by which parents pass on biological information via genes. The child inherits genetic coding from both parents. One can think of these parental genes as a recipe book for molecular operations such as the development of proteins, structure of neurons, and other functions across the human body. This total collection of the combination of genes in the human body is called the genome or genotype. The presentation of observable human traits (e.g., eye color, height, blood type) is called the phenotype. Phenotypes can be seen in our clinical work through behavior (e.g., self-injury, aggression, depression, anxiety, inattentiveness).

Before going further, it is important to establish a fundamental understanding of genetics by examining the varied molecular components and their relationships (Figure 1). Deoxyribonucleic acid (DNA) is a long-strand molecule that takes the famous double helix or ladder configuration. DNA is made up of four chemical bases called adenine (A), guanine (G), cytosine (C), and thymine (T). These form base pairs—A with T and C with G—creating a nucleic acid. The DNA is also wrapped around a specialized protein called a histone. The collection of DNA wrapped around multiple histones is called the chromatin. This wrapping process is essential for the DNA to fit within the cell nucleus. Finally, as this chromatin continues to grow, it develops a structure called a chromosome. Within every human cell nucleus, there are 23 chromosomes from each parent, totaling 46 chromosomes.

 

Figure 1

Gene Structure and Epigenetics

From “Epigenomics Fact Sheet,” by National Human Genome Research Institute, 2020
(https://www.genome.gov/about-genomics/fact-sheets/Epigenomics-Fact-Sheet). In the public domain.

 

Beyond the chromosomes, chromatin, histones, DNA, and genes, there is another key component in genetics: ribonucleic acid (RNA). RNA can be a cellular messenger that carries instructions from a DNA sequence (specific genes) to other parts of the cell (i.e., messenger RNA [mRNA]). RNA can come in several other forms as well, including transfer RNA (tRNA), microRNA (miRNA), and non-coding RNA (ncRNA). In the sections below, we elaborate on mRNA and tRNA and their impact on the genetic processes. Later in the epigenetics section, we provide fuller details on miRNA and ncRNA.

Besides the aforementioned biological aspects, it is important to understand that a child inherits genes from both parents, but they are not exactly the same genes, (i.e., alternative forms of the same gene may have differing expression). Different versions of the same gene are called alleles. Variation in an allele is one reason why we see phenotypic variation between our clients—height, weight, eye color—and this variation can contribute to mental disease susceptibility. Although there are many potential causes of poor mental health, family history is often one of the strongest risk factors because family members most closely represent the unique genetic and environmental interactions that an individual may experience. We also see this as a function of intergenerational epigenetic effects, which are covered later in this paper.

Transcription and Translation
     Now that we have provided a foundation of the genetic components, we move toward the primary two-stage processes of genetics: transcription and translation (Brooker, 2017). The first step in the process of gene expression is called transcription. Transcription occurs when a sequence of DNA is copied using RNA polymerase (“ase” notes that it is an enzyme) to make mRNA for protein synthesis. We can liken transcription to the process of someone taking down information from a client’s voicemail message. In this visualization, DNA is the caller, the person writing down the message is the RNA polymerase, and the actual written message is the RNA.

A particular section of a gene, called a promotor region, is bound by the RNA polymerase (Brooker, 2017). The RNA polymerase acts like scissors to separate the double-stranded DNA helix into two strands. One of the strands, called the template, is where the RNA polymerase will read the DNA code A to T, and G to C to build mRNA. There are other modifications that must occur in eukaryotic cells such as splicing introns and exons. In short, sections of unwanted DNA, called introns, are removed by the process of splicing, and the remaining DNA codes are connected back together (exons).

Now that the mRNA has been created by the process of transcription, the next step is for the mRNA to build a protein necessary for the main functions of the body, in a process known as translation (Brooker, 2017). Here, translation is the process in which tRNA decodes or translates the mRNA into a protein in a mobile cellular factory called the ribosome. It is translating the language of a DNA sequence (gene) into the language of a protein. To do this, the tRNA uses a translation device called an anticodon. This anticodon links to the mRNA-based pairs called a codon. A codon is a trinucleotide sequence of DNA or RNA that corresponds to a specific amino acid, or building block of a protein. This process then continues to translate and connect many amino acids together until a polypeptide (a long chain of amino acids) is created. Later, these polypeptides join to form proteins. Depending on the type of cell, the protein may function in a variety of ways. For example, the neuron has several proteins for its function, and different proteins are used for memory, learning, and neuroplasticity.

Epigenetics
     There is a wealth of research conducted on genetics, yet the understanding of epigenetics is more limited when focusing on mental health (Huang et al., 2017). Though the term epigenetics has been around since the 1940s, the “science” of epigenetics is in its youth. Epigenetic research in humans has grown in the last 10 years and continues to expand rapidly (Januar et al., 2015). The key concept for counselors to remember about epigenetics is that epigenetics supports the idea of coaction. Factors present in the client’s external environment (e.g., stress from caregiver neglect, foods consumed, drug intake like cigarettes) influence the expression of their genes (transcription and translation) and thus cell activity and related behavioral phenotypes. In the sections below, we will dive deeper into the understanding of epigenetic mechanisms and define key terms including epigenome, chromatin, and chemical modifications.

To start, the more formal definition of epigenetics is the differentiation of gene expression via chemical modifications upon the epigenome that do not alter the genetic code (i.e., the DNA sequence; Szyf et al., 2007). The epigenome, which is composed of chromatin (the combination of DNA and protein forming the chromosomes) and modification of DNA by chemical mechanisms (e.g., DNA methylation, histone modification), programs the process of gene expression (Szyf et al., 2007). The epigenome differs from the genome in that the chemical actions or modifications are on the outside of the genome (i.e., the DNA) or “upon” the genome. Specifically, epigenetic processes act “upon” the genome, which may open or close the chromatin to various degrees to govern access for reading DNA sequences (Figure 1). When the chromatin is opened, transcription and translation can take place; however, when the chromatin is closed, gene expression is silenced (Syzf et al., 2007).

It is important for counselors to conceptualize their client’s psychosocial environment in conjunction with the observed behavioral phenotypes, in that the client’s psychosocial environment may have partially mediated epigenetic expression (Januar et al., 2015). For example, with schizophrenia, a client’s adverse environment (e.g., early childhood trauma) influences the epigenome, or gene expression, which may contribute up to 60% of this disorder’s development (Gejman et al., 2011). Other adverse environmental influences have been associated with the development of schizophrenia, including complications during client’s prenatal development and birth, place and season of client’s birth, abuse, and parental loss (Benros et al., 2011). As we highlight below, epigenetic mechanisms (e.g., DNA methylation) may mediate between these environmental influences and genes with outcomes like schizophrenia (Cariaga-Martinez & Alelú-Paz, 2018; Tsankova et al., 2007).

Epigenetic Mechanisms
     There are a variety of chemical mechanisms or tags that change the chromatin structure (either opening for expression or closing to inhibit expression). Some of the most investigated mechanisms for changes in chromatin structure are DNA methylation, histone modification, and microRNA (Benoit & Turecki, 2010; Maze & Nestler, 2011).

     DNA Methylation. Methylation is the most studied epigenetic modification (Nestler et al., 2016). It occurs when a methyl group binds to a cytosine base (C) of DNA to form 5-methylcytosine. A methyl group is three hydrogens bonded to a carbon, identified as CH3. Most often, the methyl group is attached to a C followed by a G, called a CpG. These methylation changes are carried out by specific enzymes called DNA methyltransferase. These enzymes add the methyl group to the C base at the CpG site.

Methylation was initially considered irreversible, but recent research has shown that DNA methylation is more stable compared to other chemical modifications like histone modification and is therefore reversible (Nestler et al., 2016). This DNA methylation adaptability evidence is important, conceivably supporting counseling efficacy across the life span. If methylation is indeed reversible beyond 0 to 5 years of age, counseling efforts hold promise to influence mental health outcomes across the life span.

Beyond noted stability, DNA methylation is also important in that it is tissue-specific, meaning it assists in cell differentiation; it may regulate gene expression up or down and is influenced by different environmental exposures (Monk et al., 2012). For example, DNA methylation represses specific areas of a neuron’s genes, thus “turning off” their function. This stabilizes the cell by preventing any tissue-specific cell differentiation and inhibits the neuron from changing into another cell type (Szyf et al., 2016), such as becoming a lung cell later in development.

When looking at up- or downregulation, Oberlander et al. (2008) provided an example from a study using mice. When examining attachment style in mice, they found that decreased quality of mothering to offspring increased risk of anxiety, in part, because of the methylation at the glucocorticoid receptor (GR) gene and fewer GR proteins produced by the hippocampus. This change may lead to lifelong silencing or downregulation with an increased risk of anxiety to the mouse over its life span. Stevens et al. (2018) also established a link between diet, epigenetics, and DNA methylation. They found an epigenetic connection between poor dietary intake with increased risk of behavioral problems and poor mental health outcomes such as autism. The authors also remarked that further investigation is required for a clearer picture of this link and potential effects.

     Histone Modification. Another process that has been extensively researched is post-translational histone modification, or changes in the histone after the translation process. The most understood histone modifications are acetylation, methylation, and phosphorylation (Nestler et al., 2016). Acetylation, the most common post-translational modification, occurs by adding an acetyl group to the histone tail, such as the amino acid lysine. The enzymes responsible for histone acetylation are histone acetyltransferases or HATs (Haggarty & Tsai, 2011). Conversely, histone deacetylases (HDACs) are enzymes that remove acetyl groups (Saavedra et al., 2016). The acetylation process promotes gene expression (Nestler et al., 2016).

Through histone methyltransferases (HMTs), histone methylation increases methylation, thereby reducing gene expression. Histone demethylases (HDMs) remove methyl groups to increase gene activity. Phosphorylation can increase or decrease gene expression. Overall, there are more than 50 known histone modifications (Nestler et al., 2016).

From a counseling perspective, it is important to note that histone modification is flexible. Unlike DNA methylation, which is more stable over a lifetime, histone modifications are more transient. To illustrate, if an acetyl group is added to a histone, it may loosen the binding between the DNA and histone, increasing transcription and thereby allowing gene expression across the life span (Nestler et al., 2016). Such acetylation processes have been found in maternal neglect to offspring (early in the life span) and mindfulness practices in adult clients (Chaix et al., 2020; Devlin et al., 2010). Yet, although histone modification can be changed across the life span (Nestler et al., 2016), it is still important for counselors to recognize the importance of early counseling interventions because of how highly active epigenetics mechanisms (e.g., DNA methylation) are in children 0 to 5 years of age.

     MicroRNA. Beyond histone modification, another known mechanism is microRNA (miRNA), which is the least understood and most recently investigated epigenetic mechanism when compared to DNA methylation and histone modification (Saavedra et al., 2016). miRNA is one type of non-coding RNA (ncRNA), or RNA that is changed into proteins. Around 98% of the genome does not code for proteins, leading to a supporting hypothesis that ncRNAs play a significant role in gene expression. For example, humans and chimpanzees share 98.8% of the same DNA code. However, epigenetics and specifically ncRNA contribute to the wide phenotypic variation between the species (Zheng & Xiao, 2016). Further, Zheng and Xiao (2016) estimated that miRNA regulates up to 60% of gene expression.

miRNA has also been found to suppress and activate gene expression at the levels of transcription and translation (Saavedra et al., 2016). miRNAs affect gene expression by directly influencing mRNA. Specifically, the miRNA may attach to mRNA and “block” the mRNA from creating proteins or it may directly degrade mRNA. This then decreases the surplus of mRNA in the cell. If the miRNA binds partially with the mRNA, then it inhibits protein production; but if it binds completely, it is marked for destruction. Once the mRNA is identified for destruction, other proteins and enzymes are attracted to the mRNA, and they degrade the mRNA and eliminate it (Zheng & Xiao, 2016). Moreover, when compared to DNA methylation, which may be isolated to a single gene sequence, miRNA can target hundreds of genes (Lewis et al., 2005). Researchers have discovered that miRNA may mediate anxiety-like symptoms (Cohen et al., 2017).

Human Development and Epigenetics

Over the life of an individual, there are critical or sensitive periods in which epigenetic modifications are more heavily influenced by environmental factors (Mulligan, 2016). Early life (ages 0 to 5 years) appears to be one of the most critical time periods when epigenetics is more active. An example of this is the Dutch Famine of 1944–45, also known as the Dutch Hunger Winter (Champagne, 2010; Szyf, 2009). The Nazis occupied the Netherlands and restricted food to the country, bringing about a famine. The individual daily caloric intake estimate varied between 400 and 1800 calories at the climax of the famine. Most notably, women who gave birth during this time experienced the impact of low maternal caloric intake, which impacted their child and the child’s health outcomes into adulthood. One discovery was that male children had a higher risk of adulthood obesity if their famine exposure occurred early in gestation versus a male fetus who experienced famine in late gestation. Findings suggested that fetuses who experienced restricted caloric intake during the development of their autonomic nervous system may have an increased risk of heart disease in adulthood. The findings of epigenetic mechanisms at work between mother and child during a famine are flagrant enough, yet epigenetic researchers have also discovered that epigenetic tags carry across generations, called genomic imprinting (Arnaud, 2010; Yehuda et al., 2016; T.-Y. Zhang & Meaney, 2010).

Genomic imprinting can be defined as the passing on of certain epigenetic modifications to the fetus by parents (Arnaud, 2010). It is allele-specific, and approximately half of the imprinting an offspring receives is from the mother. The imprinting mechanism marks certain areas, or loci, of offspring’s genes as active or repressed. For instance, the loci may exhibit increased or decreased methylation.

An imprinting example is evident in the IGF-2 (insulin-like growth factor II) gene and those fetuses exposed to the Dutch Hunger Winter (Heijmans et al., 2008). Sixty years after the famine, a decrease in DNA methylation on IGF-2 was found in adults with fetal exposure during the famine compared to their older siblings. Researchers also found these intergenerational imprinting effects associated with the grandchildren of women who were pregnant during the Dutch Hunger Winter. Similar imprinting is also apparent in Holocaust survivors (Yehuda et al., 2016) and children born to mothers who experienced PTSD from the World Trade Center collapse of 9/11 (Yehuda et al., 2005). These imprinting mechanisms are important for counselors to understand in that we see the interplay between the client and the environment across generations. The client becomes the embodiment of their environment at the cellular level. This is no longer the dichotomous “nature vs. nurture” debate but the passing on of biological effects from one generation to another through the interplay of nature and nurture.

Epigenetics and Mental Health Disorders
     Now we turn our focus to the influence of epigenetics on the profession of counseling. What we do know is that epigenetic mechanisms, (e.g., DNA methylation, histone modifications, miRNA) are associated with various mental health disorders. It is hypothesized that epigenetics contributes to the development of mental disorders after exposure to environmental stressors, such as traumatic life events, but it may also have positive effects based on salutary environments (Syzf, 2009; Yehuda et al., 2005). We will review only those mental health epigenetic findings that have significant implications relative to clinical disorders such as stress, anxiety, childhood maltreatment, depression, schizophrenia, and addiction. We will also offer epigenetic outcomes associated with treatment, including cognitive behavioral therapy (CBT; Roberts et al., 2015), meditation (Chaix et al., 2020), and antidepressants (Lüscher & Möhler, 2019).

Stress and Anxiety
     Stress, especially during early life stages, causes long-term effects for neuronal pathways and gene expression (Lester et al., 2016; Palmisano & Pandey, 2017; Perroud et al., 2011; Roberts et al., 2015; Szyf, 2009; T.-Y. Zhang & Meaney, 2010). Currently, research supports the mediating effects of stress on epigenetics through DNA methylation, especially within the gestational environment (Lester & Marsit, 2018). DNA methylation has been associated with upregulation of the hypothalamic-pituitary-adrenal (HPA) axis, increasing anxiety symptoms (McGowan et al., 2009; Oberlander et al., 2008; Romens et al., 2015; Shimada-Sugimoto et al., 2015; Tsankova et al., 2007). DNA methylation has also been linked with increased levels of cortisol for newborns of depressed mothers. This points to an increased HPA stress response in the newborn (Oberlander et al., 2008). Ouellet-Morin et al. (2013) also looked at DNA methylation and stress. They conducted a longitudinal twin study on the effect of bullying on the serotonin transporter gene (SERT) for monozygotic twins and found increased levels of SERT DNA methylation in victims compared to their non-bullied monozygotic co-twin. Finally, Roberts et al. (2015) examined the effect of CBT on DNA methylation for children with severe anxiety, specifically testing changes in the FKBP5 gene. Although the results were not statistically significant, they may be clinically significant. Research participants with a higher DNA methylation on the FKBP5 gene had poorer response to CBT treatment.

Beyond DNA methylation, other researchers have investigated miRNA and its association with stress and anxiety. A study by Harris and Seckl (2011) found that fetal rodents with increased exposure to maternal cortisol suffered from lower birth weights and heightened anxiety. Similarly, Cohen et al. (2017) investigated anxiety in rats for a specific miRNA called miR-101a-3p. The researchers selectively bred rats, one group with low anxiety and the other with high anxiety traits. They then overexpressed miR-101a-3p in low-anxiety rats to see if that would induce greater expressions of anxiety symptomatology. The investigators observed increased anxiety behaviors when increasing the expression of miR-101a-3p in low-anxiety rats. The researchers postulated that miRNA may be a mediator of anxiety-like behaviors. Finally, paternal chronic stress in rats has been associated with intergenerational impact on offspring’s HPA axis with sperm cells having increased miRNAs, potentially indicating susceptibility of epigenetic preprogramming in male germ cells post-fertilization (Rodgers et al., 2013). The evidence suggests that paternal stress reprograms the HPA stress response during conception. This reprogramming may begin a cascading effect on the offspring’s HPA, creating dysregulation that is associated with disorders like schizophrenia, autism, and depression later in adulthood.

Though some researchers have indicated a negative association between anxiety and epigenetics, others have found positive effects between epigenetics and anxiety. A seminal study by Weaver et al. (2005) illustrated the flexibility of an offspring’s biological system to negative and positive environmental cues. Weaver et al. looked at HPA response of rodent pups who received low licking and grooming from their mother (a negative environmental effect) who exhibited higher HPA response to environmental cues in adulthood. Epigenetically, they found lower DNA methylation in a specific promotor region in these adult rodents. They hypothesized that they could reverse this hypomethylation by giving an infusion of methionine, an essential amino acid that is a methyl group donor. They discovered the ability to reverse low methylation, which improved the minimally licked and groomed adult rodents’ response to stress. This connects with counseling in that epigenetic information is not set for life but reversible through interventions such as diet.

Others have investigated mindfulness and its epigenetic effects on stress. Chaix et al. (2020) looked at DNA methylation at the genome level for differences between skilled meditators who meditated for an 8-hour interval compared to members of a control group who engaged in leisure activities for 8 hours. The control group did not have any changes in genome DNA methylation, but the skilled meditators showed 61 differentially methylated sites post-intervention. This evidence can potentially support the use of mindfulness with our clients as an intervention for treatment of stress.

Childhood Maltreatment
     Childhood maltreatment includes sexual abuse, physical abuse and/or neglect, and emotional abuse and/or neglect. Through this lens, Suderman et al. (2014) examined differences in 45-year-old males’ blood samples between those who experienced abuse in childhood and those who did not, with the aim of determining whether gene promoter DNA methylation is linked with child abuse. After 30 years, the researchers found different DNA methylation patterns between abused versus non-abused individuals and that a specific hypermethylation of a gene was linked with the adults who experienced child abuse. Suderman et al. (2014) believed that adversity, such as child abuse, reorganizes biological pathways that last into adulthood. These DNA methylation differences have been associated with biological pathways leading to cancer, obesity, diabetes, and other inflammatory paths.

Other researchers have also found epigenetic interactions at CpG sites predicting depression and anxiety in participants who experienced abuse. Though these interactions were not statistically significant (Smearman et al., 2016), increased methylation at specific promoter regions was discovered (Perroud et al., 2011; Romens et al., 2015). Furthermore, in a hallmark study, McGowan et al. (2009) discovered that people with child abuse histories who completed suicide possessed hypermethylation of a particular promotor region when compared to controls. Perroud et al. (2011) noted that frequency, age of onset, and severity of maltreatment correlated positively with increased methylation in adult participants suffering from borderline personality disorder, depression, and PTSD. Yehuda et al. (2016) reported that in a smaller subset of an overall sample of Holocaust survivors, the impact of trauma was intergenerationally associated with increased DNA methylation. Continued study of these particular regions may provide evidence of DNA methylation as a predictor of risk in developing anxiety or depressive disorders.

Major Depressive Disorder
     Most studies of mental illness, genetics, and depression have used stress animal models. Through these models, histone modification, chromatin remodeling, miRNA, and DNA methylation mechanisms have been found in rats and mice (Albert et al., 2019; Nestler et al., 2016). When an animal or human experiences early life stress, epigenetic biomarkers may serve to detect the development or progression of major depressive disorder (Saavedra et al., 2016). Additionally, histone modification markers may also indicate an increase in depression (Tsankova et al., 2007; Turecki, 2014). Beyond animal models, Januar et al. (2015) found that buccal tissue in older patients with major depressive disorder provided evidence that the BDNF gene modulates depression through hypermethylation of specific CpGs in promoter regions.

Lastly, certain miRNAs may serve as potential biomarkers for major depressive disorder. miRNA may be used in the pharmacologic treatment of depressive disorders (Saavedra et al., 2016). Tsankova et al. (2007) and Saavedra et al. (2016) noted that certain epigenetic mechanisms that influence gene expression may be useful as antidepressant treatments. Medication may induce neurogenesis and greater plasticity in synapses through upregulation and downregulation of miRNAs (Bocchio-Chiavetto et al., 2013; Lüscher & Möhler, 2019). This points to the potential use of epigenetic “engineering” for reducing depression progression and symptomology where a counselor could refer a client for epigenetic antidepressant treatments.

Maternal Depression
     Maternal prenatal depression may program the postnatal HPA axis in infants’ responses to the caretaking environment. Such programming may result in decreased expression of certain genes associated with lesser DNA methylation in infants, depending on which trimester maternal depression was most severe, and increased HPA reactivity (Devlin et al., 2010). Further, Devlin et al. discovered that maternal depression in the second trimester affected newborns’ DNA methylation patterns. However, the authors offered key limitations in their study, namely the sample was predominantly male and depressive characteristics differed based on age. Conradt et al. (2016) reported that prenatal depression in mothers may be associated with higher DNA methylation in infants. However, maternal sensitivity (i.e., ability of mother to respond to infants’ needs positively, such as positive touch, attending to distress, and basic social-emotional needs) toward infants buffered the extent of methylation, which points to environmental influences. This finding highlights the risk of infant exposure to maternal depression in conjunction with maternal sensitivity. Yet, overall, the evidence suggests that epigenetic mechanisms are at play across critical periods—prenatal, postnatal, and beyond—that have implications for offspring. When a fetus or offspring experiences adverse conditions, such as maternal depression, there is an increased likelihood of “impaired cognitive, behavioral, and social functioning . . . [including] psychiatric disorders throughout the adult life” (Vaiserman & Koliada, 2017, p. 1). For the practicing counselor, we suggest that clinical work with expecting mothers has the potential to reduce such risk based on these epigenetic findings.

Schizophrenia
     Accumulated evidence suggests that schizophrenia arises from the interaction between genetics and the client’s environment (Smigielski et al., 2020). Epigenetics is considered a mediator between a client’s genetics and environment with research showing moderate support for this position. DNA methylation, histone modifications, mRNA, and miRNA epigenetic mechanisms have been linked with schizophrenia (Boks et al., 2018; Cheah et al., 2017; Okazaki et al., 2019).

DNA methylation is a main focus in schizophrenia epigenetic research (Cariaga-Martinez & Alelú-Paz , 2018). For example, Fisher et al. (2015) conducted a longitudinal study investigating epigenetic differences between monozygotic twins who demonstrated differences in psychotic symptoms; at age 12, one twin was symptomatic and the other was asymptomatic. Fisher et al. found DNA methylation differences between these twins. The longitudinal twin study design allowed for the control of genetic contributions to the outcome as well as other internal and external threats. Further, it pointed to a stronger association between epigenetics and schizophrenia.

From a clinical perspective, Ma et al. (2018) identified a potential epigenetic biomarker for detecting schizophrenia. The authors were able to identify three specific miRNAs that may work in combination as a biomarker for the condition. According to the authors, this finding may be helpful in the future for diagnosis and monitoring treatment outcomes. We speculate that future counselors may have biomarker tests conducted as part of the diagnostic process and in monitoring treatment effectiveness with alternation in miRNA levels.

Addiction
     In addictions, a diversity of epigenetic mechanisms have been identified (e.g., DNA methylation, histone acetylation, mRNA, miRNA) across various substance use disorders: cocaine, amphetamine, methamphetamine, and alcohol (Hamilton & Nestler, 2019). Moreover, these epigenetic processes have been hypothesized to contribute to the addiction process by mediating seeking behaviors via dopamine in the neurological system. Also, Hamilton and Nestler (2019) found that epigenetic mechanisms have the potential to combat addiction processes, but further research is needed.

Cadet et al. (2016) conducted a review of cocaine, methamphetamine, and epigenetics in animal models (mice and rats). Chronic cocaine use was linked with histone acetylation in the dopamine system and DNA methylation for both chronic and acute administrations. They concluded that epigenetics may be a facilitating factor for cocaine abuse. Others have supported this conclusion for cocaine specifically, in that cocaine alters the chromatin structure by increasing histone acetylation, thereby temporarily inducing addictive behaviors (Maze & Nestler, 2011; Tsankova et al., 2007). From a treatment perspective, Wright et al. (2015) reported, in a sample of rats, that an injected methyl supplementation appeared to attenuate cocaine-seeking behavior when compared to the control group associated with cocaine-induced DNA methylation.

Regarding methamphetamines, during their review, Cadet et al. (2016) discovered that there were only a few extant studies on epigenetics and methamphetamines. Numachi et al. (2004) linked extended use of methamphetamines to changes in DNA methylation patterns, which seemed to increase vulnerability to neurochemical effects. More recently, Jayanthi et al. (2014) discovered that chronic methamphetamine use in rats induced histone hypoacetylation, making it more difficult for transcription to occur and potentially supporting the addiction process. To counter this histone hypoacetylation, the authors treated the mice with valproic acid, which inhibited the histone hypoacetylation. This study may evidence potential psychopharmacological treatments in the future at the epigenetic level for methamphetamine addiction.

H. Zhang and Gelernter (2017) reviewed the literature on DNA methylation and alcohol use disorder (AUD) and found mixed results. The authors discovered that individuals with an AUD exhibited DNA hypermethylation and hypomethylation in a variety of promoter regions. They also noted generalization limitations due to small tissue samples from the same regions of postmortem brains. They suggested that DNA methylation may account for “missing heritability” (p. 510) among individuals with AUDs.

Histone deacetylation has also been connected to chromatin closing or silencing for chronic users of alcohol, which may be involved in the maintenance of an AUD. Palmisano and Pandey (2017) suggested that there are epigenetic mediating factors between comorbidity of AUDs and anxiety disorders. On a positive note, exercise has been found to have opposite epigenetic modifications when comparing a healthy exercise group to a group who experience AUDs in terms of DNA methylation at CpG sites (Chen et al., 2018). Thus, counselors may incorporate such aspects in psychoeducation when recommending exercise in goal setting and other treatment interventions.

To summarize, epigenetics has been linked to several disorders such as anxiety, stress, depression, schizophrenia, and addiction (Albert et al., 2019; Cadet et al., 2016; Lester et al., 2016; Palmisano & Pandey, 2017; Smigielski et al., 2020). DNA methylation and miRNA may have mediating effects for mental health concerns such as anxiety (Harris & Seckl, 2011; Romens et al., 2015). Additionally, epigenetic mediating effects have also been discovered in major depressive disorder, maternal depression, and addiction (Albert et al., 2019; Conradt et al., 2016; Hamilton & Nestler, 2019). Moreover, epigenetic imprinting has been associated with trauma and stress, as found in Holocaust survivors and their children (Yehuda et al., 2016). Overall, “evidence accumulates that exposure to social stressors in [childhood], puberty, adolescence, and adulthood can influence behavioral, cellular, and molecular phenotypes and . . . are mediated by epigenetic mechanisms” (Pishva et al., 2014, p. 342).

Implications

A key aim in providing a primer on epigenetics, specifically the coaction between a client’s biology and environment on gene expression, is to illuminate opportunities for counselors to prevent and intervene upon mental health concerns. This is most relevant based on the evidence that epigenetic processes change over a client’s lifetime because of environmental influences, meaning that the client is not in a fixed state per traditional gene theory (Nestler et al., 2016). Epigenetics provides an alternate view of nature and nurture, demonstrating that epigenetic tags may not only be influenced by unfavorable environmental influences (e.g., maternal depression, trauma, bullying, child abuse and neglect) but also by favorable environments and activities (e.g., mindfulness, CBT, exercise, diet, nurturing; Chaix et al., 2020; Chen et al., 2018; Conradt et al., 2016; Roberts et al., 2015; Stevens et al., 2018). Understanding the flexibility of epigenetics has the potential to engender hope for our clients and to guide our work as counselors and counselor educators, because our genetic destinies are not fixed as we once theorized in gene theory.

Bioecological Conceptualization: Proximal and Distal Impact and Interventions
     The impact of epigenetics on the counseling profession can be understood using Bronfenbrenner’s (1979) bioecological model. The bioecological model conceptualizes a client’s function over time based on the coaction between the client and their environment (Broderick & Blewitt, 2015; Jones & Tang, 2015). The client’s environment can have both beneficial and deleterious proximal and distal effects. These effects are like concentric rings around the client, which Bronfenbrenner called “subsystems.” The most proximate subsystem is the microsystem, the environment that has a direct influence on the client, such as parents, teachers, classmates, coworkers, relatives, etc. The next level is the mesosystem, in which the micro entities interact with one another or intersect with influence on the client (e.g., school and home intersect to influence client’s thinking and behavior). The next system, called the exosystem, begins the level of indirect influence. This may include neighborhood factors such as the availability of fresh produce, safe neighborhoods, social safety net programs, and employment opportunities. The last subsystem is the macrosystem. This system consists of the cultural norms, values, and biases that influence all other systems. The final aspect of this model, called the chronosystem, takes into account development over time. The chronosystem directs the counselor’s attention to developmental periods that have differing risks and opportunities, or what can be called “critical” developmental periods.

Below we conceptualize epigenetic counseling implications using Bronfenbrenner’s model but simplify it by grouping systems: proximal effects (micro/meso level) labeled as micro effects and distal effects (exo/macro level) labeled as macro effects. We will also apply the chronosystem by focusing on critical developmental periods that are salient when applying epigenetics to counseling. Ultimately, our central focus is the client and the concentric influences of micro and macro effects. To begin, we will first focus on the important contribution of epigenetics during the critical developmental period of 0 to 5 years of age with implications at the micro and macro levels.

Epigenetics Supports Early Life Span Interventions
     Though the evidence does support epigenetic flexibility across a client’s life span, we know that early adverse life events may alter a child’s epigenome with mediating effects on development and behavior (Lester & Marsit, 2018). We also know that epigenetic processes are most active in the first 5 years of life (Mulligan, 2016; Syzf et al., 2016). These early insults to the genome may elicit poor mental health into adulthood such as anxiety, depression, schizophrenia, and addiction. For example, a client who grew up in an urban environment with a traditionally marginalized group status and parents who experienced drug dependence has an increased risk for schizophrenia above and beyond the genetic, inherited risk. These adverse childhood experiences have the potential to modify the epigenome, increasing the likelihood of developing mental health concerns, including schizophrenia (Cariaga-Martinez & Alelú-Paz, 2018).

At the micro level, the caregiver can be a salutary effect against adverse environmental conditions (Oberlander et al. 2008; Weaver et al., 2005). Prenatally, counseling can work with parents before birth to generate healthy coping strategies (e.g., reduce substance abuse), flexible and adaptive caregiver functioning, and effective parenting strategies. An example of this is to use parent–child interactive therapy (PCIT) pre-clinically, or before the child evidences a disorder (Lieneman et al., 2017). Preventive services using PCIT have been documented as effective with externalizing behaviors, child maltreatment, and developmental delays. Additional micro-level interventions can be found in the use of home-visiting programs to improve child outcomes prenatally to 5 years of age where positive parenting and other combined interventions are utilized to improve the health of mother, father, and child (Every Child Succeeds, 2019; Healthy Families New York, 2021).

Clinically, epigenetics points to earlier care and treatment to prevent the emergence of mental disorders (e.g., major depressive disorder, schizophrenia). Also, epigenetic research has provided evidence that environmental change can be equally important as client change. Regarding treatment planning, examining the client’s individual level factors or microsystem (e.g., physical health, mental status, education, race, gender) as well as their macrosystem (e.g., social stigma, poverty, housing quality, green space, pollution) may be crucial before considering what kind of modifications and/or interventions are most appropriate. For example, if a 9-year-old White female presents to a counselor for behavioral concerns in school, it is important for the counselor to gather a holistic life history to build an informed picture of the many variables collectively impacting the child’s behavior at each level. At the micro level, a counselor will evaluate for childhood maltreatment, but from an epigenetic lens, other proximal environmental factors could be important to screen for such as poverty, maternal depression, nutrition, classroom dynamics, and exercise (McEwen & McEwen, 2017; Mulligan, 2016). If the 9-year-old child is experiencing parental neglect and food insecurity, the clinician can treat the client’s individual needs at the micro level (i.e., working with the family system to overcome any neglect by using treatments such as PCIT, and direct referral to social workers and other agencies to provide food and shelter to meet basic needs).

The science of epigenetics may also inform action taken during assessment and case conceptualization based on the coaction of environment with a client over time. Although intervention at 0–5 years of age is most preventative, it is not practical in all cases. Using assessments that collect information on an adult client’s early life may help inform case conceptualization and allow the integration of epigenetics into counseling theories to better understand the etiology of a client’s presenting problem(s). For example, using an adverse childhood experiences assessment may help identify individuals at higher risk of epigenetic concerns. Epigenetics highlights the impact of client–environment interaction and its influence (positive or negative) on overall health. Additionally, early life adversity increases the likelihood of poor health outcomes such as heart disease, anxiety, and depression. However, these poor consequences could be mediated by talking with clients about the importance of exercise and its benefit on epigenetics and, by extension, mental health.

At the macro level, examples could include the reduction of hostile environments (e.g., institutional racism, neighborhood violence, limited employment opportunities, low wages, air pollutants, water pollutants), advocacy for statutes, regulations to decrease instability such as unfair housing in low-income neighborhoods, establishing partnerships in the development of community-based and school-based prevention programs, and applying early interventions such as mindfulness to reduce the effects of stress (Chaix et al., 2020). To illustrate, postnatal depression symptom severity has been associated with residential stability (Jones et al., 2018). By developing policies that would increase housing security, a reduction in maternal depression symptom severity could potentially reduce the DNA methylation that is associated with upregulation of the HPA and child reactivity, but this would need to be investigated further for confirmation. According to Rutten et al. (2013), this change may also increase the resiliency of children by reducing their experience of chronic stress, as sustained maternal depression severity often impacts caregiving because of unstable housing.

Although members of the counseling profession have known the significance of early intervention for years, this epigenetic understanding confirms why human growth and development is a core component of our counseling professional identity (Remley & Herlihy, 2020) and provides a supporting rationale for our efforts. Additionally, epigenetic tags have the potential to cross generations via the process of imprinting (Yehuda et al., 2016). This has potential implications across the life span.

In summary, critical developmental periods must be a focal point for counseling interventions, necessitating upstream action rather than our current dominant approach of downstream activities and a shift toward primary prevention over predominantly tertiary prevention. Such primary prevention would reduce stress and trauma for children before signs and symptoms become apparent and attend to the development and sustainability of healthy environments that would increase both client and community wellness.

Epigenetics Supports Counseling Advocacy and Social Justice Efforts
     When reflecting on the implications of epigenetics, it is apparent that place, context, and the client’s environment are critical factors for best positioning them for healthy outcomes, engendering a push for advocacy and social justice for clients. Because environments have no boundaries, it is important to think of advocacy across many systems: towns, counties, states, countries, and the world. This reinforces the call for counselors and counselor educators to move beyond the walls of their workplaces in order to collaborate within the larger mental health field (e.g., clinical mental health, school, marriage and family, addiction, rehabilitation). Additionally, said knowledge compels connection with other professions—such as social workers, physicians, psychologists, engineers, housing developers, public health administrators, and members of nonprofit and faith-based organizations, etc.—to enact change on a wider scale and to improve the conditions for clients at a systemic level.

This collaboration also calls for engaging at local and international levels. Global human rights issues such as sex trafficking cross countries, regions, and local communities and necessitate collaboration to ameliorate these practices and the associated trauma. For starters, the American Counseling Association and the International Association for Counseling could partner with other organizations such as the Child Defense Fund to assist in meeting their mission to level the playing field for all children in the United States. At the local level, counselors and counselor educators could collaborate with local children’s hospitals and configure a plan to meet common goals to improve children’s health and wellness.

Counseling Research and Epigenetics
     Research primarily affects clients on a macro level but can trickle down to directly engage clients within our clinical work and practice. Counselors and counselor educators can partner with members of other disciplines to further the work with epigenetic biomarkers (e.g., depression and DNA methylation). Counseling researchers can also investigate how talk therapy and other adjuncts, such as diet and exercise, may improve our clients’ treatment outcomes. As counseling researchers, we can develop research agendas around intervention and prevention for those 0–5 years of age and create and evaluate programs for this age group while also creating community partnerships as noted above. An example of this partnership is The John Hopkins Center for Prevention and Early Intervention. The creators of this program developed sustainable partnerships with public schools, mental health systems, state-level educational programs, universities, and federal programs to focus on early interventions that are school-based and beyond. They collaborated to develop, evaluate, and deliver a variety of programs and research activities to improve outcomes for children and adolescents. They have created dozens of publications based on these efforts that help move the discipline forward. In one such publication, Guintivano et al. (2014) looked at epigenetic and genetic biomarkers for predicting suicide.

Counselor Education, CACREP, and Epigenetics
     The counselor educational system affects clients distally but also holds implications for the work counselors conduct at the client level. Counselor educators can provide a more robust understanding of epigenetics to counseling students across the counselor education curriculum. These efforts can include introducing epigenetics in theories, diagnosis, treatment, human and family development, practicum and internship, assessment, professional orientation, and social and cultural foundations courses. By assisting counseling students to comprehend the relationship between client and environment, as well as the importance of prevention, educators will increase their students’ ability to carry out a holistic approach with clients and attend to the foundational emphases of the counseling profession on wellness and prevention. Moreover, by learning to include epigenetics in case conceptualization, students can gain a more robust understanding of the determinants of symptomology, potential etiology at the cellular level, and epigenetically supported treatments such as CBT and mindfulness.

It is fairly simple to integrate epigenetics education into programs accredited by the Council for Accreditation of Counseling and Related Educational Programs (CACREP; 2015). To begin, counselor educators can integrate epigenetics education into professional counseling orientation and ethical practice courses. As counselor educators discuss the history and philosophy of the counseling profession, particularly from a wellness and prevention lens (CACREP, 2015, 2.F.1.a), counselor educators can discuss the connection between epigenetics and wellness. Wellness is a foundational value for the counseling profession and is a part of the definition of counseling (Kaplan et al., 2014). Many wellness models (both theoretical and evidence-based) are rooted in the promotion of a holistic balance of the client in a variety of facets and contexts (Myers & Sweeney, 2011). We can continue to support these findings by integrating epigenetics within our conversations about wellness, as we have epigenetic evidence that the positive or negative coaction between the individual and their environment can impact a person toward increased or decreased wellness.

Counselor educators can also integrate epigenetics education into Social and Cultural Diversity and Human Growth and Development courses. Within Social and Cultural Diversity courses, counselor educators can address how negative environmental conditions have negative influences on offspring. This is evidenced by the discrimination against Jews and its imprinting that crosses generations (Yehuda et al., 2016). Counselor educators can discuss how discrimination and barriers to positive environmental conditions can impact someone at the epigenetic level (CACREP, 2015, 2.F.2.h). Within Human Growth and Development, counselor educators can discuss how the study of epigenetics provides us a biological theory to understand how development is influenced by environment across the life span (CACREP, 2015, 2.F.3.a, c, d, f). In particular, it can provide an etiology of how negative factors change epigenetic tags, which are correlated with negative mental health that may become full-blown mental health disorders later in adulthood (CACREP, 2015, 2.F.3.c, d, e, g).

Additionally, counselor educators can integrate epigenetic education within specialty counseling areas. Several studies (Maze & Nestler, 2011; Palmisano & Pandey, 2017; Tsankova et al., 2007; Wong et al., 2011; H. Zhang & Gelernter, 2017) have noted how epigenetic mechanisms may support the addiction process and counselor educators can interweave this information when discussing theories and models of addiction and mental health problems (CACREP, 2015, 5.A.1.b; 5.C.1.d; 5.C.2.g). Counselor educators can also discuss epigenetics as it applies to counseling practice. Because epigenetics research supports treatments like CBT, mindfulness, nutrition, and exercise (Chaix et al., 2020; Chen et al., 2018; Roberts et al., 2015; Stevens et al., 2018), counselor educators can address these topics in courses when discussing techniques and interventions that work toward prevention and treatment of mental health issues (CACREP, 2015, 5.C.3.b).

Generally, CACREP (2015) standards support programs that infuse counseling-related research into the curriculum (2.E). We support the integration of articles, books, websites, and videos that will engender an understanding of epigenetics across the curriculum, so long as the integration supports student learning and practice.

Conclusion and Future Directions

In summary, there are numerous epigenetic processes at work in the symptoms we attend to as counselors. We have provided information that illustrates how epigenetics may mediate outcomes such as depression, anxiety, schizophrenia, and addiction. We have also illustrated how CBT, exercise, diet, and meditation may have positive epigenetic influences supporting our craft. We have discovered that epigenetic processes are most malleable in early life. This information offers incremental evidence for our actions as professional counselors, educators, and researchers, leading to a potential examination of our efforts in areas of prevention, social justice, clinical practice, and counseling program development. However, we must note that epigenetics as a science is relatively new and much of the research is correlational.

Based on the current limits of epigenetic science and a lack of investigation of mental health epigenetics in professional counseling, one of our first recommendations for future research efforts is to collaborate across professions with other researchers such as geneticists, as we did for this manuscript. From this partnership, our profession’s connection to epigenetics is elucidated. Interdisciplinary collaboration allows the professional counselor to offer their expertise in mental health and the geneticist their deep understanding of epigenetics and the tools to examine the nature and nurture relationships in mental health outcomes. We can also make efforts to look at our wellness-based preventions and interventions to document changes at the epigenetic level in our clients and communities. Ideally, as the science of epigenetics advances, we will have epigenetic research in our profession of counseling that is beyond correlation and evidences the effectiveness of our work down to the cellular level.

 

Conflict of Interest and Funding Disclosure
The development of this manuscript was supported
in part by a Cincinnati Children’s Hospital Medical
Center Trustee Award and by a grant from the
National Heart, Lung, and Blood Institute (HL132344).
The authors reported no conflict of interest.

 

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David E. Jones, EdD, NCC, LPC, is an assistant professor at Liberty University. Jennifer S. Park, PhD, NCC, ACS, LPC, is an assistant professor at Colorado Christian University. Katie Gamby, PhD, LPC, CWC, is an assistant professor at Malone University. Taylor M. Bigelow, PhD, is an assistant professor at the University of New Haven. Tesfaye B. Mersha, PhD, is an associate professor at the Cincinnati Children’s Hospital Medical Center (CCMHC), University of Cincinnati College of Medicine. Alonzo T. Folger, PhD, MS, is an assistant professor at the CCMHC, University of Cincinnati College of Medicine. Correspondence may be addressed to David E. Jones, 1971 University Blvd., Lynchburg, VA 24515, dejones14@liberty.edu.

Cross-Validation of the Mental Distress Response Scale: Implications for Counselors

Michael T. Kalkbrenner

 

College counselors work collaboratively with professionals in a variety of disciplines in higher education to coordinate gatekeeper training to prepare university community members to recognize and refer students in mental distress to support services. This article describes the cross-validation of scores on the Mental Distress Response Scale (MDRS), a questionnaire for appraising university community members’ responses to encountering a student in mental distress, with a sample of faculty members. A confirmatory factor analysis revealed the dimensions of the MDRS were estimated adequately. Results also revealed demographic differences in faculty members’ responses to encountering a student in mental distress. The MDRS has implications for augmenting the outreach efforts of college counselors. For example, the MDRS has potential utility for enhancing campus-wide mental health screening efforts. The MDRS also has implications for supporting psychoeducation efforts, including gatekeeper training workshops, for professional counselors practicing in college settings.

 

Keywords: Mental Distress Response Scale, mental health, college counselors, gatekeeper, outreach

 

 

College counselors play crucial roles in supporting students’ personal, social, and academic growth, as well as students’ success (Golightly et al., 2017). Outreach and prevention programming, including campus violence prevention and supporting college student mental health, are two key elements in the practice of college counselors (Brunner et al., 2014; Golightly et al., 2017). Addressing these two key areas has become increasingly challenging in recent years because of the prevalence of campus violence incidents, including mass shootings in the most severe cases, and the frequency of mental health distress among college students, which has increased substantially since the new millennium (Auerbach et al., 2016; Barrett, 2014; Vieselmeyer et al., 2017). In fact, supporting college student mental health has become one of the greatest challenges that institutions of higher education are facing (Reynolds, 2013).

 

Most college students suffering from mental health issues do not seek treatment (Downs & Eisenberg, 2012). In response, college counselors, student affairs professionals, and higher education administrators are working collaboratively to develop and implement mental health awareness initiatives and gatekeeper training workshops, which include training university community members (e.g., students, faculty, and staff) as referral agents to recognize and refer students who are showing warning signs for suicide or other mental health issues to support services (Albright & Schwartz, 2017; Hodges et al., 2017). Faculty members are particularly valuable referral agents, as they tend to interact with large groups of students on frequent occasions, and they generally report positive attitudes about supporting college student mental health (Albright & Schwartz, 2017; Kalkbrenner, 2016).

 

Despite the utility of faculty members as gatekeepers for recognizing and referring students to the university counseling center and to other resources, the results of a recent national survey indicated that a significant proportion of faculty members (63%) do not refer a student in mental distress to support services (Albright & Schwartz, 2017). The literature is lacking research on how faculty members are likely to respond to encountering a student in mental distress, including but not limited to making a faculty-to-student referral to mental health support services. The primary aim of this investigation was to confirm the psychometric properties of the Mental Distress Response Scale (MDRS), a screening tool for measuring university community members’ responses to encountering a student in mental distress. Past investigators validated the MDRS for use with 4-year university students (Kalkbrenner & Flinn, 2020) and community college students (Kalkbrenner, 2019). If found valid for use with faculty members, college counselors could find the MDRS useful for screening and promoting faculty-to-student mental health support. A review of the extant literature is provided in the following section.

 

Mental Health and the State of Higher Education

 

Active shooter incidents on college campuses are some of the most tragic events in American history (Kalkbrenner, 2016). The 2015 massacre that occurred on a college campus in Oregon received attention at the highest level of government; former President Barack Obama urged the nation to decide when voting “whether this cause of continuing death for innocent people should be a relevant factor.” (Vanderhart et al., 2015, section A, p. 1). Seung-Hui Cho was a perpetrator of another one of these tragedies at Virginia Polytechnic Institute in 2007. According to Cho’s mother, he had a history of social isolation and unresolved mental health issues (Klienfield, 2007). Without treatment, the effects of mental health disorders can be debilitating and widespread for students, including impairments in academic functioning, attrition, self-harm, social isolation, and suicide or homicide in the most serious cases (Kalkbrenner, 2016; Shuchman, 2007). The early detection and treatment of students who are at risk for mental health disorders is a harm-prevention strategy for reducing campus violence incidents and promoting college student mental health (Futo, 2011; Kalkbrenner, 2016). Consequently, the practice of college counselors involves deploying outreach and systems-level mental health support interventions (Albright & Schwartz, 2017; Brunner et al., 2014; Golightly et al., 2017).

 

The Role of College Counselors in Providing Systems-Level Interventions

Providing individual counseling is a key role of college counselors (Golightly et al., 2017). In recent years, however, the practice of college counselors has been extended to providing systems-level and preventative mental health interventions to meet the growing mental health needs of college student populations (Brunner et al., 2014; Golightly et al., 2017). In particular, college counselors and their constituents engage in both campus-wide and targeted prevention and outreach programs (Golightly et al., 2017; Lynch & Glass, 2019), including gatekeeper training workshops to prepare university community members as referral agents or train them to recognize and refer students at risk for suicide and other mental health issues to the university counseling center (Albright & Schwartz, 2017; Brunner et al., 2014). These collaborative, educative, and preventative efforts are particularly crucial given the increase in both the severity and complexity of mental health disorders among college students (Gallagher, 2015; Reetz et al., 2016). The findings of past investigators suggest that faculty members are particularly viable referral agents for recognizing and referring students in mental distress to the counseling center (Kalkbrenner, 2016; Margrove et al., 2014).

 

Faculty Members as Referral Agents

Faculty members have a propensity to serve as referral agents (i.e., recognize and refer students in mental distress to resources) because of their frequent contact with students and their generally positive attitudes and willingness to support their students’ mental and physical wellness (Albright & Schwartz, 2017). Albright and Schwartz (2017) found that approximately 95% of faculty members and staff considered connecting students in mental distress to resources as one of their roles and responsibilities. Similarly, Margrove et al. (2014) found that 64% of untrained university staff members expressed a desire to receive training to recognize warning signs of mental health disorders in students.

 

Past investigators extended the line of research on the utility of faculty members as gatekeepers by identifying demographic differences by gender and help-seeking history (previous attendance in counseling) in faculty members’ tendency to support college student mental health (Kalkbrenner & Carlisle, 2019; Kalkbrenner & Sink, 2018). In particular, Kalkbrenner and Sink (2018) identified gender as a significant predictor of faculty-to-student counseling referrals, with faculty who identified as female more likely to make faculty-to-student referrals to the counseling center compared to their male counterparts. Similarly, Kalkbrenner and Carlisle (2019) found that faculty members’ awareness of warning signs for mental distress in students was a significant positive predictor of faculty-to-student referrals to the counseling center. In addition, faculty members with a help-seeking history (previous attendance in counseling) were significantly more aware of warning signs for mental distress in their students compared to faculty without a help-seeking history (Kalkbrenner & Carlisle, 2019).

 

Faculty Members’ Responses to Encountering a Student in Mental Distress

Despite the growing body of literature on institutional agents’ participation in gatekeeper training (i.e., recognize and refer), research on the measurement and appraisal of how faculty members are likely to respond when encountering a student in mental distress is in its infancy. The results of a recent national survey of college students (N = 51,294) and faculty members (N = 14,548) were troubling, as 63% of faculty members did not refer a student in psychological distress to mental health support services (Albright & Schwartz, 2017). Making a referral to the university counseling center is one possible response of students and faculty members to encountering a peer or student in mental distress (Kalkbrenner & Sink, 2018). However, the findings of Albright and Schwartz (2017) highlight a gap in the literature regarding how university community members are likely to respond when encountering a student in mental distress, including but not limited to making a faculty-to-student referral to the college counseling center.

 

To begin filling this gap in the literature, Kalkbrenner and Flinn (2020) developed, validated, and cross-validated scores on the MDRS to assess 4-year university students’ responses to encountering a student in mental distress, including but not limited to making a referral to mental health support services. In a series of two major phases of psychometric analyses, Kalkbrenner and Flinn identified and confirmed two dimensions or subscales of the MDRS, including Diminish/Avoid and Approach/Encourage, with two large samples of undergraduate students. The Diminish/Avoid subscale measures adverse or inactive responses of university community members to encountering a student in mental distress (e.g., stay away from the person or warn the person that mental issues are perceived as a weakness). The Approach/Encourage subscale appraises facilitative or helpful responses of university community members when encountering a student in mental distress that are likely to help connect the person to resources (e.g., talking to a college counselor or suggesting that the person go to the campus counseling or health center). However, the psychometric properties of the MDRS have not been tested with faculty members. If found valid for such purposes, the MDRS could be a useful tool that college counselors and their constituents can use to screen and promote faculty-to-student referrals to mental health support services. In particular, the following research questions were posed: (1) Does the two-dimensional hypothesized MDRS model fit with a sample of faculty members? and (2) To what extent are there demographic differences in faculty members’ responses to encountering a student in mental distress?

 

Method

 

Participants and Procedures

Data were collected electronically from faculty members using Qualtrics, a secure e-survey platform. A nonprobability sampling procedure was used by sending a recruitment email message with an electronic link to the survey to 1,000 faculty members who were teaching at least one course at a research-intensive, mid-Atlantic public university at the time of data collection. A total of 221 faculty members clicked on the electronic link to the survey and 11 responses were omitted from the data set because of 100% missing data, resulting in a useable sample size of 210, yielding a response rate of 21%. This response rate is consistent with the response rates of other investigators (e.g., Brockelman & Scheyett, 2015; Kalkbrenner & Carlisle, 2019) who conducted survey research with faculty members. For gender, 58% (n = 122) identified as female, 41% (n = 86) as male, and 0.5% (n = 1) as non-binary or third gender, and 0.5% (n = 1) did not specify their gender. For ethnicity, 79.0% (n = 166) identified as Caucasian, 6.2% (n = 11) as African American, 3.8% (n = 8) as Hispanic or Latinx, 2.9% (n = 6) as Asian, 2.9% (n = 6) as multiethnic, 0.5% (n = 1) as Hindu, and 0.5% (n = 1) as Irish, and 5.2% (n = 11) did not specify their ethnic identity. Participants ranged in age from 31 to 78 (M = 50; SD = 11). Participants represented all of the academic colleges in the university, including 28.6% (n = 60) Arts and Letters, 22.9% (n = 48) Education, 18.1% (n = 38) Sciences, 12.9% (n = 27) Health Sciences, 9% (n = 19) Engineering and Technology, and 7.6% (n = 16) Business, while 1% (n = 2) of participants did not specify their college.

 

Instrumentation

Demographic questionnaire

     Following informed consent, participants were asked to indicate that they met the inclusion criteria for participation, including (1) employment as a faculty member, and (2) teaching at least one course at the time of data collection. Participants then responded to a succession of demographic items about their gender, ethnicity, age, academic college, and highest level of education completed. Lastly, respondents indicated their rank and help-seeking history (previous attendance in counseling or no previous attendance in counseling) and if they had referred at least one student to mental health support services.

 

Mental Distress Response Scale (MDRS)

     The MDRS is a screening tool comprised of two subscales (Approach/Encourage and Diminish/Avoid) for measuring university community members’ responses to encountering a student in mental distress (Kalkbrenner & Flinn, 2020). The items that mark the Approach/Encourage subscale appraise responses to mental distress that are consistent with providing support and encouragement to a student in mental distress (e.g., “suggest that they go to the health center on campus”). The Diminish/Avoid subscale measures adverse or inactive responses to encountering a student in mental distress (e.g., “try to ignore your concern”). Kalkbrenner and Flinn (2020) found adequate reliability evidence for an attitudinal measure (α > 0.70) and initial validity evidence for the MDRS in two major phases of analyses (exploratory and confirmatory factor analysis [CFA]) with two samples of college students. Kalkbrenner (2019) extended the line of research on the utility of the MDRS for use with community college students and found adequate reliability (α > 0.80) and validity evidence (single and multiple-group confirmatory analysis).

 

Data Analysis

A CFA based on structural equation modeling was computed using IBM SPSS Amos version 25 to cross-validate scores on the MDRS with a sample of faculty members (research question #1). Using a maximum likelihood estimation method, the following goodness-of-fit indices and thresholds for defining model fit were investigated based on the recommendations of Byrne (2016) and Hooper et al. (2008): Chi square absolute fit index (CMIN, non-significant p-value with an x2/df ratio < 3), comparative fit index (CFI > 0.95), incremental fit index (IFI > 0.95), Tucker-Lewis index (TLI > 0.95), goodness-of-fit index (GFI > 0.95), root mean square error of approximation (RMSEA < 0.07), and standardized root mean square residual (SRMR < 0.08). Based on the findings of past investigators (e.g., Kalkbrenner & Sink, 2018) regarding demographic differences in faculty members’ propensity to support college student mental health, a 2 X 2 (gender X help-seeking history) MANOVA was computed to investigate demographic differences in faculty members’ responses to encountering a student in mental distress (research question #2). The independent variables included gender (male or female) and help-seeking history (previous attendance in counseling or no previous attendance in counseling). Discriminant analysis was used as the post hoc procedure for significant findings in the MANOVA (Warne, 2014). The researcher examined both main effects and interaction effects and applied Bonferroni adjustments to control for the familywise error rate.

 

Results

 

CFA

The researcher ensured that the data set met the necessary assumptions for CFA (Byrne, 2016; Field, 2018). A missing values analysis revealed that less than 5% of data was missing for all MDRS items. Little’s Missing Completely at Random (MCAR) test revealed that the data was missing at random: χ2 (387) = 407.98, p = 0.22. Expectation maximization was used to impute missing values. Outliers were winsorized (Field, 2018) and skewness and kurtosis values for the MDRS items (see Table 1) were largely consistent with a normal distribution (+ 1; Mvududu & Sink, 2013). Inter-item correlations between the 10 items were favorable for CFA, and Mahalanobis d2 indices revealed no extreme multivariate outliers. The researcher ensured that the sample size was sufficient for CFA by following the guidelines provided by Mvududu and Sink (2013), including at least 10 participants per estimated parameter with a sample > 200.

 

Table 1

 

Descriptive Statistics for MDRS Items

 

Item Content   M SD Skew Kurtosis
1. I would stay away from this person 49.83 9.46 1.11 0.22
2. Suggest that they go to the health center on campus 50.15 9.48 -0.60 -0.08
3. Try to ignore your concern 49.74 9.08 1.07 1.08
4. Take them to a party 49.21 3.11 0.70 0.81
5. Tell them to “tough it out” because they will feel better over time 49.73 8.94 1.32 1.26
6. Suggest that they see a medical doctor on campus 50.00 9.98 -0.24 -0.06
7. Avoid this person 49.70 9.02 1.80 1.33
8. Suggest that they see a medical doctor in the community 50.00 9.98 -0.49 -0.10
9. Warn the person that others are likely to see their mental health issues as a weakness 49.31 7.14 1.90 1.59
10. Talk to a counselor about your concern 50.00 9.97 -0.83 0.15

SEKurtosis = 0.15, SESkewness = 0.17.

Note. Values were winsorized and reported as standardized t-scores (M = 50; SD = 10).

 

 

 

 

The 10 MDRS items (see Table 1) were entered in the CFA. A strong model fit emerged based on the GFI recommended by Byrne (2016) and Hooper et al. (2008). The CMIN absolute fit index demonstrated no significant differences between the hypothesized model and the data: χ2 (34) = 42.41, p = 0.15, CMIN/df = 1.25. In addition, the CFI = 0.98, GFI = 0.96, IFI = 0.98, TLI = 0.98, RMSEA = 0.03, 90% confidence interval  [<.00, .06], and SRMR = 0.05 also demonstrated a strong model fit. Internal consistency reliability analyses (Cronbach’s coefficient alpha) revealed satisfactory reliability coefficients for an attitudinal measure, Diminish/Avoid (α = 0.73) and Approach/Encourage (α = 0.70). In addition, the path model coefficient (-0.04) between factors supported the structural validity of the scales (see Figure 1).

 

Figure 1

Confirmatory Factor Analysis Path Diagram for the Mental Distress Response Scale

 

 

Note. CFA = confirmatory factor analysis, MDRS = Mental Distress Response Scale.

 

Multivariate Analysis

A 2 X 2 (gender X help-seeking history) MANOVA was computed to investigate demographic differences in faculty members’ responses to encountering a student in mental distress (research question #2). G*Power was used to conduct an a priori power analysis (Faul et al., 2007) and revealed that a minimum sample size of 151 would provide a 95% power estimate, α = .05, with a moderate effect size, F2(v) = 0.063. A significant main effect emerged for gender: F(3, 196) = 8.27, p < 0.001, Wilks’ λ = 0.92, = 0.08. The MANOVA was followed up with a post hoc discriminant analysis based on the recommendations of Warne (2014). The discriminant function significantly discriminated between groups: Wilks’ λ = 0.91, X2 = 18.85, df = 2, p < 0.001. The correlations between the latent factors and discriminant function showed that Diminish/Avoid loaded more strongly on the function (r = 0.98) than Approach/Encourage (r = 0.29), suggesting that Diminish/Avoid contributed the most to group separation in gender. The mean discriminant score on the function was -0.27 for participants who identified as female and 0.37 for participants who identified as male.

 

Discussion

 

The results of tests of internal consistency reliability (Cronbach’s coefficient alpha), CFA, and correlations between factors supported the psychometric properties of the MDRS with a sample of faculty members. The results of the CFA were promising as GFI demonstrated a strong model fit between the two-dimensional hypothesized MDRS model and a sample of faculty members (research question #1). In particular, based on one of the most conservative and rigorous absolute fit indices, the CMIN (Byrne, 2016; Credé & Harms, 2015), the researchers retained the null hypothesis—there were no significant differences between the hypothesized factor structure of the MDRS and a sample of faculty members. The strong model fit suggests that Approach/Encourage and Diminish/Avoid are two latent variables that comprise faculty members’ responses to encountering a student in mental distress. The findings of the CFA add to the extant literature about the utility of the MDRS for use with 4-year university students (Kalkbrenner & Flinn, 2020), community college students (Kalkbrenner, 2019), and now with faculty members.

 

An investigation of the path model coefficient between subscales (see Figure 1) revealed a small and negative association between factors, which supports the structural validity of the MDRS. In particular, the low and negative relationship between the Approach/Encourage and Diminish/Avoid subscales indicates that the dimensions of the MDRS are measuring discrete dimensions of a related construct. As expected, faculty members who scored higher on the Approach/Encourage subscale tended to score lower on the Diminish/Avoid subscale. However, the low strength of the association between factors suggests that faculty members’ responses to encountering a student in mental distress might not always be linear (e.g., a strong positive approach/encourage response might not always be associated with a strong negative diminish/avoid response). Haines et al. (2017) demonstrated that factors in the environment and temperament of a person showing signs of mental distress were significant predictors of mental health support staff’s perceptions of work safety. It is possible that under one set of circumstances faculty members might have an approach/encourage response to mental distress. However, under a difference set of circumstances, a faculty member might have a diminish/avoid response. For example, the extent to which a faculty member feels threatened or unsafe might mediate their propensity of having diminish/avoid or approach/encourage responses. Future research is needed to evaluate this possibility.

 

Consistent with the findings of previous researchers (Kalkbrenner & Carlisle, 2019; Kalkbrenner & Sink, 2018), the present investigators found that faculty members who identified as male were more likely to report a diminish/avoid response to encountering a student in mental distress compared to female faculty members. Similarly, Kalkbrenner and Sink (2018) found that male faculty members were less likely to make faculty-to-student referrals to the counseling center, and Kalkbrenner and Carlisle (2019) found that male faculty members were less likely to recognize warning signs of mental distress in college students. Similarly, the multivariate results of the present investigation revealed that male faculty members were more likely to report a diminish/avoid response to encountering a student in mental distress when compared to female faculty members. The synthesized findings of Kalkbrenner and Carlisle (2019), Kalkbrenner and Sink (2018), and the present investigation suggest that faculty members who identify as male might be less likely to recognize and refer a student in mental distress to mental health support services. The MDRS has valuable implications for enhancing the practice of professional counselors in college settings.

 

Implications for Counseling Practice

 

Outreach, consultation, and psychoeducation are essential components in the practice of college counselors (Brunner et al., 2014; Golightly et al., 2017). The findings of the present investigation have a number of practical implications for enhancing college counselors’ outreach and psychoeducation work—for example, gatekeeper workshops geared toward promoting faculty-to-student referrals to mental health support resources. The complex and multidimensional nature of college student mental health issues calls for interdisciplinary collaboration between college counselors and professionals in a variety of disciplinary orientations in higher education (Eells & Rockland-Miller, 2011; Hodges et al., 2017). College counselors can take leadership roles in coordinating these collaborative efforts to support college student mental health. In particular, college counselors can work with student affairs officials, higher education administrators, and their constituents, and attend new faculty orientations as well as department meetings to administer the MDRS, establish relationships with faculty, and discuss the benefits of gatekeeper training as well as supporting college student mental health. The results of the MDRS can be used to gain insight into the types of responses that faculty members are likely to have when encountering a student in mental distress. This information can be used to structure the content of gatekeeper training workshops aimed at promoting faculty-to-student referrals to mental health support services. Specifically, college counselors might consider the utility of integrating brief interventions and skills training components into gatekeeper training workshops. Motivational interviewing, for example, is an evidence-based, brief approach to counseling that includes both person-centered and directive underpinnings with utility for increasing clients’ intrinsic motivation to make positive changes in their lives (Iarussi, 2013; Resnicow & McMaster, 2012). Professional counselors who practice in higher education are already using motivational interviewing to promote college student development and mental health (Iarussi, 2013). Although future research is needed, integrating motivational interviewing principles (e.g., expressing empathy, rolling with resistance, developing discrepancies, and supporting self-efficacy; Iarussi, 2013) into gatekeeper training workshops might increase faculty members’ commitment to supporting college student mental health.

 

The MDRS has the potential to enhance college counselors’ outreach and mental health screening efforts (Golightly et al., 2017). College counselors can incorporate the MDRS into batteries of pretest/posttest measures (e.g., the MDRS with a referral self-efficacy measure) for evaluating the effectiveness of mental health awareness initiatives and gatekeeper training programs for faculty and other members of the campus community. If administered widely, the MDRS might have utility for assessing faculty members’ responses to students in mental distress across time and among various campus ecological systems, providing data to drive the prioritization and allocation of outreach efforts aimed at facilitating and maintaining referral networks for connecting students in mental distress to support services.

 

The results of the present study have policy implications related to campus violence prevention programming. The sharp increase in campus violence incidents has resulted in several universities implementing threat assessment teams as a harm-prevention measure (Eells & Rockland-Miller, 2011). Threat assessment teams involve an interdisciplinary collaboration of university faculty and staff for the purposes of recognizing and responding to students who are at risk of posing a threat to themselves or to others. College counselors can take leadership roles in establishing and supporting threat assessment teams at their universities. College counselors can administer the MDRS to faculty and staff and use the results as one way to identify potential threat assessment team members. University community members who score higher on the Approach/Encourage scale might be inclined to serve on threat assessment teams because of their propensity to support college student mental health. The brevity (10 questions) and versatility of administration (paper copy or electronically via laptop, smartphone, or tablet) of the MDRS adds to the practicality of the measure. Specifically, it might be practical for college counselors and their constituents to administer the MDRS during new faculty orientations, annual opening programs, or department meetings, or via email to faculty and staff. Results can potentially be used to recruit threat assessment team members.

 

Our findings indicate that when compared to their female counterparts, male faculty members might be more likely to have a diminish/avoid response when encountering a student in mental distress. College counselors might consider working collaboratively with student affairs professionals to implement gatekeeper training and mental health awareness workshops in academic departments that are comprised of high proportions of male faculty members. It is possible that male faculty members are unaware of how to identify warning signs of mental distress in their students (Kalkbrenner & Carlisle, 2019). College counselors might consider the utility of distributing psychoeducation resources for recognizing students in mental distress to faculty and staff. As just one example, the REDFLAGS model is an acronym of eight red flags or warning signs for identifying students who might be struggling with mental health issues (Kalkbrenner, 2016). Kalkbrenner and Carlisle (2019) demonstrated that the REDFLAGS model is a promising psychoeducational tool, as faculty members’ awareness of the red flags was a significant positive predictor of faculty-to-student referrals to the counseling center. The REDFLAGS model appears to be a practical resource for college counselors that can be distributed to faculty electronically or by paper copy, or posted as a flyer (Kalkbrenner, 2016; Kalkbrenner & Carlisle, 2019).

 

Limitations and Future Research

The findings of the present study should be considered within the context of the limitations. A number of methodological limitations (e.g., self-report bias and social desirability) can influence the validity of psychometric designs. In addition, the dichotomous nature of the faculty-to-student counseling referral variable (referred or not referred) did not provide data on the frequency of referrals. Future researchers should use a continuous variable (e.g., the number of student referrals to the counseling center in the past 2 years) to appraise faculty-to-student referrals. Future researchers can further test the psychometric properties of the MDRS through cross-validating scores on the measure with additional, unique populations of faculty members from a variety of different geographic and social locations. Invariance testing can be computed to examine the degree to which the MDRS and its dimensions maintain psychometric equivalence across different populations of faculty members. In addition, the criterion validity of the MDRS can be examined by testing the extent to which respondents’ MDRS scores are predictors of their frequency of student referrals to the counseling center and to other resources. Furthermore, future qualitative research is needed to investigate faculty members’ unique experiences around supporting college student mental health.

 

The low and negative association between the Approach/Encourage and Diminish/Avoid subscales suggests that faculty members might have an approach/encourage response to encountering a student in mental distress under one set of circumstances; however, they might have a diminish/avoid response under a difference set of circumstances. Future investigators might test the extent to which attitudinal variables mediate respondents’ MDRS scores—for example, the extent to which faculty members’ sense of safety predicts their MDRS scores. In addition, given the widespread public perception of individuals living with mental illness as violent and dangerous (Varshney et al., 2016), future researchers might identify demographic and background differences (particularly mental health stigma) among participants’ MDRS scores.

 

Summary and Conclusion

 

Mental health outreach and screening are essential components in the practice of college counselors, including training referral agents to recognize and refer students who might be struggling with mental health distress to support services (Golightly et al., 2017). Taken together, the results of the present study indicate that the MDRS and its dimensions were estimated sufficiently with a sample of faculty members. Our findings confirmed the two-dimensional hypothesized model for the types of responses that faculty might have when encountering a student showing signs of mental distress. In particular, the results of a CFA provided support for the MDRS and its dimensions, confirming a two-dimensional construct for the types of responses (approach/encourage and diminish/avoid) that faculty members might have when encountering a student in mental distress. Considering the utility of faculty members as gatekeepers and referral agents (Hodges et al., 2017; Kalkbrenner, 2016), researchers, practitioners, and policymakers may find the MDRS a useful screening tool for identifying the ways in which faculty members are likely to respond when encountering a student in mental distress. Results can be used to inform the content of mental health awareness initiatives and gatekeeper training programs aimed at promoting approach/encourage responses to connect students who need mental health support to the appropriate resources.

 

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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Michael T. Kalkbrenner, PhD, NCC, is an assistant professor at New Mexico State University. Correspondence can be addressed to Michael Kalkbrenner, 1220 Stewart St., OH202B, NMSU, Las Cruces, NM 88001, mkalk001@nmsu.edu.

The Medicare Mental Health Coverage Gap: How Licensed Professional Counselors Navigate Medicare-Ineligible Provider Status

Matthew C. Fullen, Jonathan D. Wiley, Amy A. Morgan

 

This interpretative phenomenological analysis explored licensed professional counselors’ experiences of turning away Medicare beneficiaries because of the current Medicare mental health policy. Researchers used semi-structured interviews to explore the client-level barriers created by federal legislation that determines professional counselors as Medicare-ineligible providers. An in-depth presentation of one superordinate theme, ineffectual policy, along with the emergent themes confounding regulations, programmatic inconsistencies, and impediment to care, illustrates the proximal barriers Medicare beneficiaries experience when actively seeking out licensed professional counselors for mental health care. Licensed professional counselors’ experiences indicate that current Medicare provider regulations interfere with mental health care accessibility and availability for Medicare-insured populations. Implications for advocacy are discussed.

 

Keywords: Medicare, interpretative phenomenological analysis, mental health, advocacy, federal legislation

 

 

Medicare is the primary source of health insurance for 60 million Americans, including adults 65 years and over and younger individuals with a long-term disability; the number of beneficiaries is expected to surpass 80 million by 2030 (Kaiser Family Foundation, 2019; Medicare Payment Advisory Commission, 2015). According to the Center for Medicare Advocacy (2013), approximately 26% of all Medicare beneficiaries experience some form of mental health disorder, including depression and anxiety, mild and major neurocognitive disorder, and serious mental illness such as bipolar disorder and schizophrenia. Among older adults specifically, nearly one in five meets the criteria for a mental health or substance use condition, and if left unaddressed, these issues may lead to consequences such as impaired physical health, hospitalization, and even suicide (Institute of Medicine, 2012).

 

Past research demonstrates that Medicare-eligible populations respond appropriately to counseling (Roseborough, Luptak, McLeod, & Bradshaw, 2012). Federal agencies such as the Substance Abuse and Mental Health Services Administration (SAMHSA) publish entire guides on how to use counseling to treat depression and related conditions in older adults (SAMHSA, 2011). However, researchers have noted specific challenges that Medicare-eligible populations, such as older adults, face when trying to access mental health services. Stewart, Jameson, and Curtin (2015) described acceptability, accessibility, and availability as three intersecting dimensions that may influence whether an older adult in need of help is able to access care. In contrast to acceptability, which focuses on whether older individuals are willing to participate in specific mental health services, accessibility and availability are both supply-side issues that impede older adults’ engagement with mental health services. Accessibility refers to factors like funding for mental health services and providing transportation support to attend appointments. Availability is used to describe the number of mental health professionals who provide services to older adults within a particular community.

 

Stewart et al.’s (2015) framework is useful when examining current Medicare policy and its impact on beneficiaries’ ability to participate in mental health treatment when needed. Experts have criticized Medicare for its relative inattention to mental health care (Bartels & Naslund, 2013), noting a remarkably low percentage of its total budget is spent on mental health (1% or $2.4 billion; Institute of Medicine, 2012), as well as a lack of emphasis on prevention services. In terms of accessibility, Congress has made efforts to remove restrictions to using one’s health insurance to access mental health treatment. For example, mental health parity laws were passed in 2008 to ensure that Medicare coverage for mental illness is not more restrictive than coverage for physical health concerns (Medicare Improvements for Patients and Providers Act of 2008, 2008). Yet current Medicare policy may restrict the availability of services at the mental health provider level. For example, the Medicare program has not updated its mental health provider licensure standards since 1989, when licensed clinical social workers were added as independent mental health providers and restrictions on services provided by psychologists were removed (H.R. Rep. No. 101-386, 1989). Although counseling is only one mental health care modality available to Medicare beneficiaries, counselors can play a prominent role in the mental health treatment of older adults and people with long-term disabilities.

 

Meanwhile, there are references in the literature to a provider gap that may influence the ability of Medicare beneficiaries, including older adults, to access mental health services. A 2012 Institute of Medicine report described the lack of mental health providers as a crisis, and experts on geriatric mental health care have decried the lack of mental health professionals who focus their work on older adults (Bartels & Naslund, 2013). Despite these concerns, relatively little attention has been given to the influence of Medicare provider regulations in limiting the number of available providers. Scholars have noted that a significant proportion of graduate-level mental health professionals are currently excluded from Medicare regulations, despite providing a substantial ratio of community-based mental health services (Christenson & Crane, 2004; Field, 2017; Fullen, 2016; Goodman, Morgan, Hodgson, & Caldwell, 2018). Licensed professional counselors (LPCs) and licensed marriage and family therapists (LMFTs) jointly comprise approximately 200,000 providers (Medicare Mental Health Workforce Coalition, 2019), which means that approximately half of all master’s-level providers are not available to provide services under Medicare. Since their recognition as independent mental health providers by Congress in 1989, only licensed clinical social workers and advanced practice psychiatric nurses have constituted the proportion of master’s-level providers eligible to provide mental health services through Medicare.

 

Despite current Medicare reimbursement restrictions, Medicare beneficiaries are likely to seek out services from LPCs. Fullen, Lawson, and Sharma (in press-a) found that over 50% of practicing counselors had turned away Medicare-insured individuals who sought counseling services, 40% had used pro bono or sliding scale approaches to provide services, and 39% were forced to refer existing clients once those clients became Medicare-eligible. When this occurs, the Medicare mental health coverage gap (MMHCG) impacts providers and beneficiaries in several distinct ways. First, some beneficiaries may begin treatment only to have services interrupted or stopped altogether once the provider is no longer able to be reimbursed by Medicare. This can occur because of confusion about whether a particular patient’s insurance coverage authorizes treatment by a particular provider type, or when beneficiaries who have successfully used one type of coverage to pay for services transition to Medicare coverage because of advancing age or qualifying for long-term disability.

 

Most Medicare beneficiaries (81%; Kaiser Family Foundation, 2019) have supplemental insurance, including 22% who have both Medicare and Medicaid. Medicare beneficiaries who are dually eligible for Medicaid may be particularly vulnerable to the MMHCG. In most states, Medicaid authorizes LPCs to provide counseling services; however, in certain cases when these individuals also qualify for Medicare, the inconsistency in provider regulations between these programs can interfere with client care. A similar problem occurs when the Medicare-insured attempt to use supplemental plans (e.g., private insurance, Medigap) because of Medicare functioning as a primary source of insurance, and supplemental plans requiring documentation that a Medicare claim has been denied. Regardless of the reason for having to terminate treatment prematurely, early withdrawal from mental health treatment has been described as inefficient and harmful to both clients and mental health providers (Barrett et al., 2008).

 

The MMHCG also can interfere with clients’ ability to access services because of a lack of Medicare-eligible providers in a particular geographical region. For example, beneficiaries who reside in rural localities can have more difficulty finding mental health providers because of a general shortage of providers in these areas (Larson, Patterson, Garberson, & Andrilla, 2016). Larson et al. (2016) found that rural communities were less likely to have licensed mental health professionals overall, although these localities were more likely to have a counseling professional than a clinical social worker, psychiatric nurse practitioner, or psychiatrist. Historically, older adults from rural and urban localities experience a comparable prevalence of mental health disorders (Center for Behavioral Health Statistics and Quality, 2018). However, studies consistently describe low rates of mental health services accessibility and availability within rural communities (Smalley & Warren, 2012). Establishing counselors as Medicare-eligible providers can reduce the disparities of mental health services accessibility and availability experienced by older adults in rural communities.

 

Although it is known that LPCs are currently excluded from Medicare coverage, it is not well understood what sort of impact this has on mental health providers and the Medicare beneficiaries who seek their services. Recent efforts to raise awareness of this issue have emerged in the literature (Field, 2017; Fullen, 2016; Goodman et al., 2018), but there has not yet been an investigation into the phenomenological experiences of mental health providers who are directly impacted by existing Medicare policy. The purpose of this study was to explore the lived experiences of mental health professionals who have turned away clients because of their status as Medicare-ineligible providers. The primary research question for this study was: How do Medicare-ineligible providers make sense of their experiences turning away Medicare beneficiaries and their inability to serve these clients?

 

Research Design and Methods

 

     This study was executed using interpretive phenomenological analysis (IPA) to guide both data collection and analysis. The study focused on the experiences of Medicare-ineligible mental health professionals as they navigated interactions with Medicare beneficiaries who sought mental health care from them. By using a hermeneutic approach to understand their unique perspectives on this phenomenon, we aimed to remain consistent with the philosophical approach of IPA, which is idiographic in nature (Smith, Flowers, & Larkin, 2009). This study received approval from the Western Institutional Review Board.

 

IPA focuses on the personal meaning-making of participants who share a particular experience within a specific context (Smith et al., 2009). We determined IPA to be the most appropriate method to answer our research question because of the personal impact on LPCs of turning away Medicare beneficiaries because of Medicare-ineligible provider status. Nationally, LPCs share the experience of being unable to serve Medicare beneficiaries because of the current Medicare mental health policy that establishes these licensed mental health professionals as Medicare-ineligible. IPA also is appropriate for this study because of the positionality of the researchers. The research team consisted of two LPCs and one LMFT who have denied services or had to refer clients because of the current Medicare mental health policy and have engaged in prior research and advocacy related to the professional and clinical implications of the current Medicare mental health policy. We selected IPA for this study because of the shared experience between the researchers and participants as Medicare-ineligible providers. A distinguishing feature of IPA, a variation of hermeneutic phenomenology, is the acknowledgment of a double-interpretative, analytical process: The researchers make sense of how the participants make sense of a shared phenomenon (Smith et al., 2009).

 

Participants

Participants were screened based on the inclusion criteria of having direct experience with turning away or referring Medicare beneficiaries and holding a mental health license as an LPC. Because states grant licenses to health care providers, we limited participation to LPCs who were practicing in a specific state in the Mid-Atlantic region. This allowed for consistency in licensure requirements, training provided, and current scope of practice across all participants. The nine participants interviewed all held the highest professional counseling license in this state, which allows these individuals to practice independent of supervision after completing 4,000 hours of supervised training. Post-license experience ranged from 6 months to 17 years, and participants practiced in both rural and non-rural settings. Pseudonyms were assigned by the research team (see Table 1 for participant information).

 

Table 1

 

Participant Information

 

Participant License Type Rural Statusa Years of Licensed Experience
Michelle LPC Rural   4 years
Cecelia LPC Non-rural   5 years
Mary LPC Non-rural 17 years
Roger LPC Non-rural   2 years
Aubrey LPC Rural   4 years
Donna LPC Rural   4 years
April LPC Non-rural   0.5 years
Robert LPC/LMFT Non-rural 22 years
Brandon LPC Rural   5 years

 

aThe table displays rural status as designated by the U.S. Department of Health and Human Services Health Resources and Services Administration (2016) according to the practice location of the participant. Non-rural includes metropolitan and micropolitan areas. Rural indicates any locality that is neither metropolitan or micropolitan.

 

 

 

Most participants were identified because of having completed a national survey of mental health providers unable to serve Medicare beneficiaries (Fullen et al., in press-a). Participants in the national survey were provided with a question in which they were able to indicate their openness to participating in follow-up individual interviews regarding their experiences with turning away clients as a result of Medicare policy. Two additional participants had not completed the national survey but were identified locally because of their unique experiences with the phenomenon under investigation. We selected nine participants in accordance with IPA participant selection and data saturation guidelines (Smith et al., 2009). Although the current Medicare policy excludes both LPCs and LMFTs, we chose to focus on the experiences of LPCs to ensure a purposive and homogeneous sample (Smith et al., 2009).

 

Data Collection

Semi-structured, in-depth interviews of the nine participants were conducted by the research team. All research team members are LPCs or LMFTs. Individual interviews were conducted by a single member of the team who digitally recorded and transcribed verbatim the interview procedure. Consent was obtained from the participants and pseudonyms were used to ensure participant confidentiality. Also, participants were given the option to stop the interview at any time. The elapsed time of each interview ranged between 47 and 66 minutes. The semi-structured interview protocol began with two initial questions to frame the interview: (a) Have you ever had to refer a potential client to another counselor/therapist/agency because of not being able to accept their Medicare insurance coverage? and (b) Have you ever established a working relationship with a client who later transitioned to Medicare insurance coverage?

 

Based on participant responses to these initial questions, two grand tour questions followed:
(a) Tell me about what typically occurs when someone with Medicare insurance contacts your office in search of counseling? and (b) Tell me about any times when you have had to alter a pre-existing working relationship with a client because of their Medicare coverage? Follow-up questions focused on the impact of current Medicare mental health policy on the interviewees, as well as their perceived impact on clients, local communities, other therapists in the area, and their employment contexts.

 

Data Analysis

The IPA process outlined by Smith et al. (2009) was employed to analyze the transcribed interview data. The following steps were employed throughout the analysis process: (a) reading and re-reading of transcripts, (b) initial noting, (c) developing emergent themes, (d) searching for connections across emergent themes, (e) moving to the next case, and (f) looking for patterns across cases. Codes and themes developed at each stage of the first transcript analysis required consensus agreement among the authors. After re-reading, initial noting, developing emergent themes, and clustering of superordinate themes for each of the remaining interviews, the authors proceeded to engage in a group-level analysis process of looking for patterns across all interviews. Patterns across all interviews were organized into a concept map to synthesize connections and relationships between the interviews. Connections and relationships identified through this cross-case analysis led to the identification of a group-level clustering of superordinate themes that resulted in the identification of the primary themes.

 

Trustworthiness

The authors attended to the credibility and trustworthiness of this analysis using four strategies. First, the authors have prolonged engagement in the fields of counseling and marriage and family therapy as licensed professionals. This prolonged engagement has allowed the authors to be situated to the contexts of the participants, account for abnormalities in the data, and transcend their own observations (Lincoln & Guba, 1985). Second, the authors engaged in a team-based reflexive process through the sharing of personal reflections and group discussions about emerging issues (Barry, Britten, Barber, Bradley, & Stevenson, 1999). Third, negative case analysis was used in the analytical process of this study to develop, broaden, and confirm themes that emerged from the data (Lincoln & Guba, 1985; Patton, 1999). The fourth strategy was analyst triangulation (Denzin, 1978; Patton, 1999). All three authors participated in the development of the study, data collection, and data analysis to reduce the potential bias that can emerge from a single researcher performing each of these tasks (Patton, 1999). Each researcher independently analyzed the same data and compared their findings throughout data analysis to check selective perception and interpretive bias.

 

Results

 

Three superordinate themes emerged from our interviews with nine mental health professionals who have experience with the Medicare coverage gap: ineffectual policy, difficult transitions, and undue burden. We will discuss one superordinate theme, ineffectual policy, with the emergent themes of confounding regulations, programmatic inconsistencies, and impediment to care. By presenting a single meta-theme, we hope to provide increased depth and the nuanced experiences that our participants shared (see Levitt et al., 2018 for a discussion on dividing qualitative data into multiple manuscripts).

 

All nine participants expressed concerns about the ineffectiveness of current Medicare policy when it comes to treating people with mental disorders who live in their communities. The disconnect between Medicare’s intended aim—to provide sound health care to beneficiaries—and the present outcome for clients seeking out counseling led us to describe the policy as ineffectual or not producing the intended effect. Our participants perceived that the policy had severe shortcomings in terms of providing access to mental health care, which they viewed as a serious problem with cascading consequences for their clients, communities, and themselves.

 

Confounding Regulations

Several participants described the Medicare coverage gap as “confusing” and “frustrating” for mental health providers and Medicare beneficiaries who are seeking mental health services. Brandon, an LPC who serves as a director within a Federally Qualified Health Center, stated, “Most people are pretty shocked to realize we are not part of Medicare.” He went on to explain that most medical providers, including psychiatrists, were not aware of LPCs’ Medicare ineligibility when making client referrals. Participants described how the confusion interferes with referrals between medical providers and clients seeking mental health services.

 

Other participants described how frustrating the policy is, both for themselves and their clients. Robert, an LPC who also is credentialed as an LMFT, stated that “as a provider, it’s frustrating to turn people away,” and “it’s especially concerning for older people who can’t afford to pay out of pocket.” Michelle, who works as an LPC in a rural community, described how the MMHCG influences clients’ views of the larger Medicare system, stating, “[Clients are] very angry—not directed towards me, just the system . . . they’re on Medicare now [and] they have to leave. They paid into a system and then still can’t see the clinician that they want to see.” According to interviewees like Michelle, current Medicare provider regulations do not account for the preponderance of LPCs who provide care, particularly in rural communities. Regulations are then perceived by clients as an additional barrier to getting help at a time when they may be vulnerable.

 

In fact, in certain cases, current Medicare policy may result in all Medicare beneficiaries within a particular community losing access to mental health care. Brandon described a 4-month period when his Federally Qualified Health Center was unable to serve any Medicare beneficiaries because of job turnover: “[It] took us four months to find an LCSW. . . . We specifically had to weed out some very qualified licensed mental health professionals because they weren’t LCSWs.” Brandon went on to explain that during this 4-month period, his clients were unable to access mental health care at the community clinic. He concluded, “It was pretty disruptive to their care.”

 

Brandon’s description elucidates the cascading impact of the current policy on clients, community agencies that provide mental health services, and counselors seeking work. When specific providers are excluded from servicing Medicare beneficiaries, older adults with mental health conditions are vulnerable to gaps in coverage, such as the 4-month period that Brandon described.

 

Programmatic Inconsistencies

Several interviewees referenced confusion about how Medicare interfaces with other insurance programs. Roger and Mary, a couple in joint practice, explained how confusion among clients and health providers in their community is exacerbated by inconsistencies between Medicare and Medicaid, including the fact that in their state LPCs are eligible for reimbursement from Medicaid, but not Medicare. Roger explained, “[The] confusion is not just with clients who have low SES. It’s agency people, it’s case managers in the community, doctors that would make referrals, there really is a misunderstanding . . . and sometimes a disbelief.” They went on to describe their frustration in having to explain to referral sources that Medicare ineligibility has nothing to do with a lack of training. Roger concluded, “Yes, we are trained and . . . virtually every other insurance company accepts licensed professional counselors.”

 

Mary’s and Roger’s statements are indicative of the confusion that current policy creates among providers and clients. Several interviewees expressed annoyance that they had to explain to prospective clients that they possessed the requisite license and training required by the state to provide counseling and that they were recognized providers by non-Medicare insurance providers (i.e., Medicaid, Tricare, private insurance providers).

 

Related to the inconsistency between Medicaid and Medicare, several interviewees alluded to the fact that the very circumstances that qualify individuals for government-funded insurance (e.g., poverty, disability) may inadvertently restrict the mental health care that is available to them. Michelle described this phenomenon in the context of having to address clients who were referred to work with her by the local community mental health agency. She alluded to a particularly challenging cycle in which clients who were diagnosed with schizophrenia would be referred to her for counseling while they were also applying for long-term medical disability. She described the challenges of working with these clients, only to have to refer them elsewhere once they became eligible for disability benefits (which include Medicare). Describing her clients, she stated, “[They] applied for disability, they received disability, and now they have to, even though they have established the relationship with me . . . transition over to a different therapist.” Michelle then highlighted what occurs after this transition is initiated: “[One] individual . . . has continued to see me because with that particular diagnosis, he doesn’t trust anyone else. . . . [Another] individual . . . just chooses not to see anyone . . . and then she ends up having to be hospitalized every so often.”

 

Beyond being discouraged or exasperated, Michelle’s capacity to remain stoic in the face of such a paradox was telling. As she described it, this sequence had happened on multiple occasions and would likely happen again save for a federal policy change. Michelle also alluded to the potential economic detriments of current policy. By foregoing outpatient counseling because of the barriers described above, her patient with schizophrenia must be intermittently hospitalized, which is a much more expensive form of treatment.

 

Policy-level inconsistencies were confusing to providers as well. April, an LPC who attained her independent license within the past year, stated, “It feels like handcuffs. It’s like here you have this credential that the state says you have earned, but it’s only a half credential because you can’t [accept] one of the main government sponsored programs.” Cecelia, an LPC working in a metropolitan area, expressed similar sentiments as she explained how clients with Medicare and secondary insurance plans are turned away: “I initially bill Anthem first and my claims continue to get denied.” She explained, “Basically what they want me to do is submit the claims to Medicare, allow Medicare to deny the claim, and then submit the claim to them with the denial from Medicare and then they’ll provide reimbursement.” However, Cecelia stated that this process has been halted when Medicare refuses to issue a denial letter because of her status as an LPC. She put it this way: “The struggle that I found with Medicare is that because I’m an LPC, Medicare won’t even recognize me to even allow me to submit a claim . . . so I cannot provide Anthem with the denial that they’re looking for.”

 

Cecelia’s description of the inconsistency between Medicare and private insurance reflects a particularly problematic experience for her clients. Although they had paid for supplemental private insurance plans to augment their Medicare coverage, they were unable to use these benefits without a denial letter from Medicare. Ironically, according to Cecelia, the Medicare office could not provide the denial to a Medicare-ineligible provider in the first place.

 

Brandon made a similar statement about the inconsistency in provider regulations between Medicare and Tricare, specifically referencing his own training levels: “I’m shocked. . . . We’re some of the most qualified licensed mental health professionals in the business to provide psychotherapy and treatment for psychiatric diagnoses . . . and yet somehow that doesn’t count . . . somehow we’re not included.” Citing the growing number of insurance providers that do recognize LPCs, including Tricare, he concluded, “So, literally Medicare is the last holdout that I’m aware of.” By describing Medicare as “the last holdout,” Brandon implies that Medicare is the only federal program that has not updated its provider regulations to match the current mental health marketplace. Echoing Brandon, the sentiment that Medicare provider regulations were not in line with the current state of mental health practice was common among our interviewees.

 

Impediment to Care

The therapeutic working alliance has been shown to be one of the key factors that positively impacts counseling treatment (Wampold, 2015). When existing clients become eligible for Medicare, whether because of increasing age or qualifying for a long-term disability, current policy appears to interfere with continuity of care. Aubrey, an LPC who practices in a rural locality, describes it this way: “I will tell you where the problem arises . . . if I’m assigned a client, and I have the rapport with them, and we’re working together and they become eligible for Medicare . . . then I have to transfer them.” Because of the emphasis within counseling on the working relationship, Aubrey suggested that after building a strong working relationship with a counselor, even referrals within an agency can be disruptive to patient care.

 

Additionally, several interviewees described the challenges associated with referring Medicare beneficiaries to alternative providers. Some alluded to clients who made an effort to continue working with an LPC, despite not being able to use their Medicare coverage. Eventually, disparities in clients’ financial circumstances resulted in some clients having to forego receiving mental health care. Brandon explained the difficulty that current Medicare policy brings to communities, particularly those in which there are relatively few Medicare-eligible providers relative to LPCs. He described monthly meetings with community private practice providers this way: “[They are] all booked up. There’s just not enough . . . licensed mental health providers in town to see everybody. And . . . because only half of those people can accept Medicare, it has a very particular impact on Medicare recipients.” Citing the shortage of providers, Brandon emphasized the additional burden faced by the Medicare-insured because of having a smaller available provider pool.

 

The shortage of alternative mental health providers was a common theme among interviewees, especially for those who practiced in rural communities. Michelle explained that there is a misperception that Medicare-eligible providers are available when Medicare beneficiaries seek out help: “I hear . . .
there are so many licensed clinical social workers in this area, but there aren’t.” As a consequence, “[individuals] that are trying to work themselves into the schedule of a licensed clinical social worker, they often wait months before they’re actually able to be seen.”

 

Donna, an LPC who also works in a rural community, expressed a similar concern about the lack
of options facing beneficiaries who live in rural areas: “I see such a shortage in rural areas of providers across the board. And then when you have to narrow it down even further to limit who they can see, then that makes it even more difficult for them to get the care that they need.”

 

In fact, the expense of mental health care when insurance coverage is unavailable was a factor that several interviewees described. Robert told the story of a client he had seen for several years who tried to pay out of pocket but could no longer make that financially viable: “[It] was really disappointing because she really wasn’t finished. . . . We had a great working relationship and it was sad to have her stop just because of reimbursement reasons.”

 

Brandon made a similar comment about an individual who was deterred from seeking treatment because of the cost of paying out of pocket when his Medicare insurance was unable to be used: “I let him know . . . I can’t accept Medicare. And he asked how much it would be. [I said] anywhere from $75 to $125, and . . . he was pretty disheartened by that.”

 

Mary noted how the MMHCG can result in Medicare beneficiaries not seeking out necessary services. She emphasized that turning people away at the point when they have elected to ask for help can be disconcerting: “Right at a time when they’re willing to reach out and ask for [help]. That’s the worst part. Because I think . . . that discourages clients from seeking services—they have to work too hard . . . finding a provider.” April added a similar sentiment: “It’s heartbreaking . . . [my] emphasis is on those most vulnerable and those most in need of services . . . it is my worst nightmare for a client to walk away . . . because I want them to know they are my priority.” In each of these examples, participants expressed concerns that current policy acted as a deterrent to accessing necessary mental health services because of the burdensome process of having to locate a Medicare-eligible provider.

 

Discussion

 

     Our findings illuminate how current Medicare mental health policy impacts Medicare beneficiaries’ access to counseling treatment for mental health conditions. Nine mental health providers who are not Medicare-eligible were interviewed to learn about their experiences interacting with Medicare beneficiaries who sought their services. The central phenomenon that all interviewees responded to—their inability to work with Medicare beneficiaries in the same manner that they work with clients who use other forms of insurance—has infrequently been referenced in the extant literature. This phenomenon provides a unique contribution to discussions about the accessibility and availability of mental health services to older adults (Stewart et al., 2015) and people with long-term disabilities. Particularly compelling about what was reported in these interviews is the fact that these individuals were actively seeking out or currently engaged in mental health treatment at the time when they were turned away. In the past, explanations about barriers to mental health care for Medicare-insured populations have focused on systemic factors such as rural geography (Kim et al., 2013) or stigma about mental health (Chapin et al., 2013). While these are certainly relevant factors that provide a broad explanation for why older people are less likely to receive mental health services, the current study illuminates several proximate point-of-service barriers that result in providers having to cease treatment with clients, deny care to clients who were actively seeking it out, or refer clients to relatively long wait-lists in lieu of more prompt treatment by available providers. Given the lack of scholarly attention focused on the MMHCG, the perspectives offered by these participants contributes to a broader discussion about how to increase access to mental health services for older adults, as well as for individuals with long-term disabilities.

 

Among our interviewees, there was a noticeable amount of concern for how the MMHCG impacts individuals in the community in need of mental health care. Participants’ concerns about the consequences of the MMHCG on their clients may be related to their awareness that mental illness influences other key indicators of well-being. For example, depression reflects a relatively common mental health condition that responds well to treatment but can be problematic for clients when left untreated. Although depression was only one of several types of mental illness described by participants, clinically relevant depressive symptoms affect 10% of males over 65 and 15% of females over 65, and the presence of depressive symptoms is correlated with greater functional disability, dementia, higher rates of physical illness, and higher health care resource utilization (Federal Interagency Forum on Aging-Related Statistics, 2016). As the number of Medicare beneficiaries grows, it is reasonable to assume that there will be corresponding growth in the number of people who meet the criteria for mental health conditions, including depression. Echoing the concern voiced by our participants, we state that the current Medicare policy extends the risk of mental health needs going unmet among Medicare-insured populations.

 

Additionally, the economic consequences of untreated or undertreated mental illness are worth considering. Each participant described instances of unmet client mental health needs because of a combination of (a) practitioner inability to submit for Medicare reimbursement, (b) client’s inability to pay a sliding scale rate, and (c) lack of follow-through on referrals to mental health providers eligible for Medicare coverage. For example, some participants described this undertreatment as resulting in potential inpatient psychiatric hospitalization because of clients’ inability to utilize their Medicare benefits to seek care within their local communities. Undertreatment of mental health conditions can lead to inefficient administration of health care, including an over-reliance on more expensive mental health services when outpatient services could have been more appropriate. For example, the reimbursement rate for 45 minutes of counseling is $84.74 for doctoral-level providers (see American Psychological Association, 2015, for a critique of this rate), and the rate for master’s-level providers is estimated at 75% of this amount ($63.56). This is in contrast to the cost of a single day in an inpatient psychiatric facility, which is $782.78, or approximately 12 times higher than a single counseling session (Centers for Medicare & Medicaid Services, 2019). Having adequate outpatient services available within a community is traditionally a sound strategy for reducing high-cost treatment; yet this is not occurring as regularly as is needed when Medicare beneficiaries are involved. Although not every person who may be at risk for inpatient hospitalization will benefit solely from weekly outpatient services, several cases referenced by our interviewees (e.g., Michelle’s work with clients with schizophrenia) fit this category. Considering that a single day of inpatient treatment costs the same as a 12-session course of counseling from a master’s-level provider, it stands to reason that there are economic benefits to re-examining current Medicare mental health policy.

 

The inefficiency of current Medicare policy was highlighted when several participants alluded to inconsistencies between insurance programs, including certain cases in which having Medicare precluded clients from using other forms of insurance (e.g., Medicaid, Tricare, private supplemental plans) that would otherwise cover mental health treatment by LPCs. This feature of the MMHCG has important ramifications given that 81% of Medicare beneficiaries possess a supplemental health plan (Kaiser Family Foundation, 2019), including more than 12 million Americans who are dually covered by Medicare and Medicaid (Centers for Medicare & Medicaid Services, n.d.). For this latter group, dual-eligible adults are more likely to have functional or cognitive impairments, chronic conditions, or conditions that frequently coincide with mental health conditions. In fact, among dual-eligible individuals, 59% of those with disabilities and 20% of those who are 65 years or older self-reported diagnosis of a mental health disorder (Donohue, 2006). This means that some of the most vulnerable Medicare beneficiaries are particularly burdened by current Medicare mental health policy.

 

Implications for Professional Advocacy

 

Regarding advocacy on behalf of clients, these findings suggest that Medicare reimbursement for LPCs is urgently needed in order to provide Medicare-insured populations with access to mental health services. Currently, efforts to change Medicare regulations through the legislative process have support from a broad range of professional interest groups, many of which comprise the Medicare Mental Health Workforce Coalition (Medicare Mental Health Workforce Coalition, 2019). Further, there is currently legislation under consideration in both the U.S. Senate (S. 286; Mental Health Access Improvement Act, 2019) and U.S. House of Representatives (H.R. 945; Mental Health Access Improvement Act, 2019) that would include LPCs and LMFTs as Medicare-eligible providers. As of November 2019, these bills had 29 and 96 cosponsors, respectively (U.S. Congress 2019a, 2019b). Despite these efforts, more than half of counseling professionals recently surveyed had not participated in advocacy related to Medicare reimbursement (Fullen, Lawson, & Sharma, in press-b). Therefore, additional work is needed to educate members of the counseling profession about the consequences of current Medicare mental health policy on clients from underserved populations. Fullen et al. (in press-a, in press-b) describe several strategies that can be used to strengthen advocacy efforts among members of the counseling profession, including counselor educators, master’s and doctoral students, and practicing counselors.

 

Limitations and Future Research

 

A primary limitation of this study relates to the generalizability of the results. This study reports on a specific and localized account of how Medicare mental health policy impacts Medicare beneficiaries’ access to counseling treatment in a single state. We intentionally focused on a homogenous sample purposefully selected to explore how LPCs are making sense of their inability to provide counseling services to Medicare beneficiaries based on their professional status as Medicare-ineligible. The findings present a narrative account of how these licensed mental health providers make sense of and respond to the experience of not being able to serve Medicare clients because of professional limitations contained within Medicare mental health policy. The utilization of IPA has allowed for the detection of nuance, subtlety, and complexity within the data from the semi-structured interviews with our participants. This specificity allows for an understanding that shows how the coverage gap created by the exclusion of counselors impacts Medicare beneficiaries’ access to counseling services.

 

An additional limitation of our study is the use of prolonged engagement as a strategy to establish credibility and trustworthiness. Prolonged engagement, traditionally employed in ethnography and
participant observation, requires that researchers spend sufficient time in the field to learn or understand the experiential phenomenon of the study (Lincoln & Guba, 1985). Though we did not spend time with participants within their specific practice settings, we each have practice experience as Medicare-ineligible providers within the field of professional counseling. In a more ethnographic study on the MMHCG, we would be able to employ a more traditional application of prolonged engagement.

 

Future research should focus on additional qualitative and quantitative data sets that allow for more generalizability of findings. By nature, Medicare policy is consistent across the United States, which leads us to believe that there are likely similarities between the phenomena described by our interviewees and what occurs in other states. Nonetheless, additional inquiry is needed to probe the impact of MMHCG more comprehensively. An empirical investigation into the perspectives of Medicare-insured individuals who have been unable to utilize their Medicare benefits because of the MMHCG may lend an additional lens toward understanding the impact of Medicare mental health policy on clients. Ultimately, this study and subsequent studies focusing on diminishing coverage gaps for Medicare beneficiaries can support progress toward diminishing health inequities because of health care policy restrictions.

 

Conclusion

 

This study highlights an existing gap in the administration of Medicare services for clients seeking counseling treatment for mental health conditions. By attending to the theme of ineffectual policy, we have attempted to illuminate how current policy impacts the Medicare-insured, as well as LPCs who are involved in their mental health care. Based on our analysis of the MMHCG, future revisions to Medicare policy allowing for the inclusion of LPCs to provide counseling treatment to Medicare-insured individuals may contribute to a more equitable health care system for Medicare beneficiaries.

 

 

Conflict of Interest and Funding Disclosure

This research was supported by the Virginia Tech
Institute for Society, Culture, and Environment.

 

 

 

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Matthew C. Fullen is an assistant professor at Virginia Tech. Jonathan D. Wiley, NCC, is a doctoral candidate at Virginia Tech. Amy A. Morgan is a doctoral candidate at Virginia Tech. Correspondence can be addressed to Matthew Fullen, School of Education, College of Liberal Arts and Human Sciences, 1750 Kraft Drive, Suite 2000, Room 2005, Blacksburg, VA 24061, mfullen@vt.edu.