2020 Dissertation Excellence Award

TPC received entries for the seventh annual Dissertation Excellence Award from across the United States. After great deliberation, the TPC editorial board committee selected Alison M. Boughn to receive the 2020 Dissertation Excellence Award for her dissertation, Child Psychological Maltreatment.

Alison M. Boughn, PhD, NCC, LPC (South Dakota), LMHC (Iowa), ATR-BC, TF-CBT, QMHP, earned a Bachelor of Fine Arts in painting from the University of South Dakota (2013), and both a Master of Science in mental health counseling and a Master of Science in art therapy counseling from Emporia State University (2015). In 2019, she was awarded a Doctor of Philosophy in counselor education and supervision from the University of South Dakota. Dr. Boughn is an assistant professor in Wayne State College’s counselor education program in Wayne, Nebraska. She is also a practicing clinician at the MercyOne Siouxland Child Advocacy Center (CAC) in Sioux City, Iowa, and the Family Education and Counseling Center in Yankton, South Dakota.

Dr. Boughn’s research interests began with concerns facing first responders and their relationship with fatigue and stress. She facilitated an art therapy project titled Shots After Work in 2013 with local law enforcement professionals integrating firearms and art-making into a therapeutic experience for participants. Shots After Work was shared on a national scale at the American Art Therapy Association’s 47th Annual Conference in Baltimore, Maryland, in 2016. Combining her clinical and art therapy professional identities, Dr. Boughn’s first responder work branched off into guest presentations with paramedic students and professionals during their educational and clinical training. The aim of these presentations was to implement awareness to the unique stresses first responders face in their professional and personal lives as well as to introduce self-care strategies.

Dr. Boughn practices trauma-focused art therapy and trauma-focused cognitive behavioral therapy with pediatric clients at the MercyOne Siouxland CAC. Her clients are typically involved in some form of child maltreatment case. She began her work there in 2016 where she developed trauma-focused mental health programming and policy as well as implementation of regular mental health screening procedures for all children entering the CAC. These screening processes provide evaluation for general trauma symptoms, sexual concerns, and suicidal ideations following a child’s forensic interview process. The implementation of these assessment protocols led to the ability to provide earlier interventions for children to access mental health and crisis services.

Dr. Boughn’s dissertation focus continues to be a critical aspect of her professional identity. Dr. Boughn has provided factual and expert testimony on child psychological maltreatment and recognizes the need for a comprehensive understanding of these experiences across professions, state and national laws, and varying cultural experiences. Dr. Boughn plans to continue her research goals by enhancing the integrity of the developed Psychological Maltreatment Inventory (PMI). Dr. Boughn hopes that the PMI may eventually act as a bridge between a child’s experiences with psychological maltreatment and an adult’s understanding of those experiences.

TPC looks forward to recognizing outstanding dissertations like Dr. Boughn’s for many years to come.

Read more about the TPC scholarship awards here.

“Take Your Kung-Flu Back to Wuhan”: Counseling Asians, Asian Americans, and Pacific Islanders With Race-Based Trauma Related to COVID-19

Stacey Diane Arañez Litam

Following the outbreak of COVID-19, reports of discrimination and violence against Asians and Asian Americans and Pacific Islanders (AAPIs) have increased substantially. The present article offers a timely conceptualization of how public and societal fears related to COVID-19 may contribute to unique mental health disparities and the presence of race-based trauma among AAPIs residing in the United States. The relationships between media, increasing rates of xenophobia and sinophobia, and racial discrimination are provided. Next, the deleterious effects of race-based discrimination on the emotional and physical well-being of people of color and Indigenous groups (POCI) and AAPIs are described. Finally, the article identifies the clinical implications of counseling AAPI clients, encourages a decolonization of current trauma-focused interventions, and presents specific strategies to heal race-based trauma in AAPI client populations.

Keywords: race-based trauma, discrimination, microinterventions, xenophobia, sinophobia

The outbreak of novel coronavirus (COVID-19) has led to unparalleled events across the United States and worldwide. Hospitals, nursing homes, and medical settings were quickly overwhelmed, and the vulnerability of these systems became apparent. A lack of federal consistency and political infrastructure resulted in differences across levels, quality, and types of state support. On January 31, 2020, the World Health Organization (WHO) declared COVID-19 a public health emergency of international concern. This sentiment was echoed by U.S. President Donald Trump on March 13, 2020, who warranted the pandemic an emergency for all states, tribes, territories, and the District of Columbia (Federal Emergency Management Agency [FEMA], 2020). A “shelter-in-place” order was instituted for many states and people were encouraged to stay home to prevent the spread of COVID-19. Indeed, the presence of COVID-19 has led to unprecedented times. However, the sociopolitical disparities illuminated by COVID-19 are not solely limited to institutional and political problems.

Asian Americans and Pacific Islanders (AAPIs) represent the fastest growing ethnic or racial group in the United States. In 2015, approximately 20.9 million people identified as AAPIs (Lopez et al., 2017). As a group, AAPIs encompass 40 distinct subgroups, each of which demonstrates heterogeneity across language, educational background, religion, immigration/migration history, beliefs about mental health, and attitudes toward help-seeking behaviors. For the purpose of this article, AAPIs are people who have origins rooted in East, South, and Southeast Asian countries. The present article offers a timely conceptualization of how public and societal fears related to COVID-19 may contribute to unique mental health disparities and race-based trauma in AAPIs residing in the United States. The relationships between media, increasing rates of xenophobia and sinophobia, and racial discrimination are provided. Next, the deleterious effects of race-based discrimination on the emotional and physical well-being of people of color and Indigenous groups (POCI) and AAPIs are described. Finally, the article identifies the clinical implications for counseling AAPI clients, encourages a decolonization of current trauma-focused interventions, and presents specific strategies to heal race-based trauma in AAPI client populations.

Xenophobia and Sinophobia in Media
The emergence of new infectious diseases historically has led to discrimination against groups of people of non-European descent (White, 2020). Indeed, the history of international infectious disease has predominantly been framed from a distinctly European perspective, which has focused on how disease negatively impacted post-colonial sites and affected trade (White, 2020). Experiences of fear and anxiety related to infectious disease often occur when people become threatened by an illness perceived as originating from outside one’s community (Taylor, 2019). Thus, the resurgence of attitudes characterized by xenophobia, or a fear of foreigners (Sundstrom & Kim, 2014), and sinophobia, which can be understood as the “intersection of fear and hatred of China” (Billé, 2015, p. 10), perpetuates a legacy of discrimination against non-White groups because of fear of illness. AAPIs have experienced a long tradition of blame and discrimination in the United States. Scapegoating AAPIs in light of COVID-19 echoes the racist “Yellow Peril” stereotype, which vilified Asian groups as a threat to job and economic security in Western nations (Kawai, 2005). The Chinese Exclusion Act of 1882, which effectively banned the immigration of Chinese persons to the United States for 10 years, further evidences historical anti-Chinese sentiments and an extensive history of discrimination against AAPIs in America (Lee, 2002).

The problematic, biased, and misleading media coverage of COVID-19 has led to increased rates of racial discrimination and sinophobic attitudes toward Chinese nationals and people of Asian origin (Wen et al., 2020). Health-related fears and phobia have been linked to misinformation fueled by sensationalist headlines (Taylor & Asmundson, 2004). Media, especially social media and the internet, are indispensable resources for information, communication, and entertainment. Following the outbreak of COVID-19, reports of discrimination and violence against Asian Americans have increased substantially across the United States (Congressional Asian American Pacific American Caucus [CAPAC], 2020).

COVID-19–related fears have resulted in the persecution of AAPIs through violent attacks (CAPAC, 2020), discrimination against their businesses, and sinophobic portrayals in media and from elected leaders (National Association for the Advancement of Colored People [NAACP], 2020). The dissemination of racially targeted content in media includes hate speech toward Chinese people, harassment, discriminatory stereotypes, and conspiracy theories (CAPAC, 2020; Schild et al., 2020; United Nations Human Rights, Office of the High Commissioner, 2020). A data analysis of two popular web platforms found a significant rise in racial slurs, invoking earlier attitudes of sinophobic propaganda. To better understand the emergence of sinophobic attitudes within online communities, Schild and colleagues (2020) collected and analyzed 222,212,841 tweets and 16,808,191 posts from Twitter and 4chan imageboards, respectively, from November 1, 2019, to March 22, 2020. The results revealed a significant increase in the presence of racial slurs that targeted Asians and Asian Americans, including “Kung-Flu,” “Ching Chong,” and “asshoe,” a term used to denigrate the accent of Chinese people speaking English (Schild et al., 2020). “Chink” was the most popular sinophobic slur and increased substantially after Donald Trump referred to COVID-19 as “the Chinese virus” (Schild et al., 2020).

Marginalized Groups Uniquely Affected
Social inequities and policies related to COVID-19 may disproportionately affect people of color and other marginalized groups, including individuals who are homeless, people with non-dominant racial and ethnic identities, undocumented individuals, people in lower socioeconomic groups, and individuals with limited access to health care. Individuals who lack shelter, reside in congregate living settings, or lack regular access to basic hygiene supplies may be at higher risk for exposure and transmission of COVID-19 (Devakumar et al., 2020; Tsai & Wilson, 2020). Given the increased prevalence of homelessness for lesbian, gay, bisexual, and transgender (LGBT) adolescents compared to their heterosexual counterparts (Cochran et al., 2002), persons with non-dominant sexual and gender identities additionally may be at greater risk. POCI may be disproportionately vulnerable to COVID-19 exposure because of greater rates of existing medical and mental health conditions. Higher rates of hypertension in African American and Black individuals (Go et al., 2014) and diabetes in South Asian populations (Unnikrishnan et al., 2018) have been identified as pre-existing health conditions that negatively affect the prognosis of COVID-19 treatment (Centers for Disease Control and Prevention, 2020). Undocumented persons may also face unique challenges because of fears associated with seeking medical assistance. Consequently, by the time undocumented persons arrive to medical settings, the disease has reached an advanced stage and physical health is significantly compromised (Devakumar et al., 2020).

Effects of Racial Discrimination on Wellness
Racial microaggressions are the everyday slights, insults, invalidations, and offensive behaviors experienced by POCI through interpersonal verbal and nonverbal communication, media, educational curriculum, mascots, monuments, and other forms (Sue et al., 2007). Indeed, the experiences of racism, discrimination, and microaggressions faced by POCI negatively affect their mental and physical health (Alvarez et al., 2016; American Psychological Association, 2016) and increase their risk factors for developing mental and physical health problems (Carter, 2007; Carter et al., 2005; Clark et al., 1999; Harrell, 2000; Pieterse et al., 2012). Although many Indigenous, Latinx, and Asian populations face racial discrimination and suffer from race-based stress, African American and Black individuals are disproportionately affected (Chou et al., 2012). Experiencing racial discrimination has been linked to increased rates of depression in African Americans (Chou et al., 2012; Jones et al., 2007), Pacific Islanders (Allen et al., 2017), Indigenous women (Benoit et al., 2016), and Latinx populations (Araújo & Borrell, 2006; Chou et al., 2012; Pieterse et al., 2012). Indeed, ongoing experiences of racial discrimination have been described as resulting in a chronic state of “racial battle fatigue” that taxes the mental and emotional resources of people of color (Smith et al., 2011, p. 64).

In one study of 12 common mental health disorders, including major depressive disorder, dysthymic disorder, panic disorder, separation anxiety disorder, social anxiety, generalized anxiety, post-traumatic stress, alcohol abuse, drug use, attention deficient hyperactivity disorder, oppositional defiant disorder, and conduct disorder, using a national sample (N = 5,191), perceived discrimination was positively associated with each mental health diagnosis in African American and Afro-Caribbean adults (Rodriguez-Seijas et al., 2015). Perceived racial discrimination also has deleterious effects on Asian Americans’ wellness. Studies have consistently linked race-related stress and perceived discrimination in AAPIs to increased rates of psychological distress, suicidal ideation, anxiety, and depression (Gee et al., 2007; Hwang & Goto, 2008; Wei, Alvarez, et al., 2010). Additional studies have evidenced how the presence of race-based stress significantly and negatively correlates to feelings of self-esteem (Liang & Fassinger, 2008), social connectedness (Wei et al., 2012), and overall well-being (Iwamoto & Liu, 2010) in Asian American populations. The daily experiences of racial microaggressions, combined with the current political climate (Potok, 2017), represent a source of significant stress for POCI and may lead to racial trauma.

Racial trauma refers to the events or danger related to real or perceived experiences of racial discrimination (Carter, 2007). These experiences include threats of harm and injury, humiliating and shameful events, and witnessing harm to other POCI because of real or perceived racism (Carter, 2007). The effects of racial trauma parallel symptoms of other trauma-based disorders, including acute stress disorder and post-traumatic stress disorder. POCI may experience hypervigilance, avoidance, flashbacks, and nightmares related to the events of racial discrimination (Comas-Díaz et al., 2019) and somatic expressions, including headaches, heart palpitations (Comas-Díaz et al., 2019), dizziness, confusion, and difficulty concentrating (Hinton & Jalal, 2019). Healing race-based trauma requires counselors to consider the intersectional identities that uniquely influence experiences of oppression and discrimination for marginalized groups. Because POCI experience race-based stress throughout their lives (Gee & Verissimo, 2016) and the nature of discrimination lies within sociocultural contexts (Comas-Díaz et al., 2019), healing these racial wounds can be difficult.

Although facing the daily onslaught of microaggressions and racial discrimination clearly contributes to the presence of race-based stress and trauma across POCI, specific strategies to address each of these racial groups is beyond the purview of this article. The increased rates of sinophobic attitudes, behaviors, and racial slurs fueled by COVID-19 fears, internet activity, and media misinformation are specific stressors that may uniquely affect AAPI groups. The following sections outline the clinical implications for counseling AAPIs who face racial discrimination resulting from COVID-19 fears and the current sociopolitical climate.

Clinical Implications for Counseling Asian Americans and Pacific Islanders

In the United States, an ideology of White supremacy exists, which justifies policies and practices that maintain the subordination of people of color through social arrangements using power and White privilege (Huber & Soloranzo, 2015). Addressing disparities in racial wellness thus requires counselors to challenge these existing inequalities embedded in the current social zeitgeist. The combined fear of infectious disease, misrepresentation in media, and current sociopolitical climate have illuminated the importance of identifying culturally sensitive strategies to heal race-based trauma in AAPIs. Beginning from initial assessment and intake, counselors must consider how intersectional identities such as ethnicity, country of origin, affectional identity, gender identity, age, socioeconomic status, and other statuses influence the social positioning, experiences, and worldview of their AAPI clients. Counselors must additionally be prepared to navigate language barriers, undocumented status, and challenges related to health care access with cultural humility.

As counselors prepare to screen for race-based trauma, it becomes of paramount importance to consider how Southeast Asian and Chinese populations are more likely to report somatic complaints that differ from Eurocentric trauma symptoms, including difficulty sleeping, dizziness, difficulty concentrating, and physical complaints such as headaches, stomach problems, and chronic pain (Dreher et al., 2017; Grover & Ghosh, 2014; Hinton & Good, 2009; Hinton et al., 2018). As with all clients, counselors are called to reflect on how their own internalized biases and attitudes may compromise treatment effectiveness and to avoid imposing their values onto clients (American Counseling Association, 2014). The experiences of racial oppression and discrimination toward AAPIs are often overlooked because of the model minority stereotype that portrays Asian Americans as achieving high educational and societal success (Ocampo & Soodjinda, 2016). In reality, AAPIs face explicit experiences of racism and physical and emotional harassment related to accents and physical appearance (Choi & Lim, 2014; Qin et al., 2008). Counselors are thus encouraged to pursue their own counseling and engage in dialogue with supervisors, friends, and colleagues to identify and challenge the presence of implicit biases or preconceived notions held about AAPI groups. Counselors must consider ways to deliver treatment within the cultural settings in which clients feel most safe and comfortable (Helms et al., 2012) to effectively heal race-based trauma in AAPIs.

Decolonizing Trauma-Based Interventions
Constructs related to trauma, traumatic stress, and trauma-based interventions are largely embedded in European perspectives and historically have failed to consider the influence of intersectional identities in trauma treatment and recovery (L. S. Brown, 2008; Hernández-Wolfe, 2013; Mattar, 2011). The importance of contextualizing trauma-based interventions when working with people of color has been identified in the literature (Helms et al., 2012), and the extant literature on trauma-based interventions has identified a lack of cultural relevance for most POCI (Bryant-Davis & Ocampo, 2006; Hinton & Good, 2016; Hinton & Lewis-Fernández, 2011). Many existing theories and trauma-based interventions may therefore lack cultural relevance for AAPI groups. Counselors must therefore decolonize trauma-based interventions and consider whether trauma treatments are culturally sensitive and appropriate for Asians and Asian Americans who present with COVID-19–related trauma symptoms.

Healing Race-Based Trauma in AAPIs
When racial discrimination occurs, people of color, including AAPIs, may experience rumination about the situation and negative self-evaluation because of lack of action (Shelton et al., 2006; Sue et al., 2007). POCI who respond passively, ignore, or do not stand up for themselves may experience greater feelings of helplessness or hopelessness, or be more likely to endorse the fatalistic belief that racism is normative and must be accepted (Williams & Williams-Morris, 2000). For many AAPI individuals, facing sinophobic attitudes and behaviors may result in problematic outcomes. Because Asian cultures tend to discourage conflict and demonstrate a preference for maintaining interpersonal harmony (Ting-Toomey et al., 2000; Yum, 1988), AAPIs may be more likely to employ the use of indirect and subtle approaches (Lee et al., 2012). Compared to other racial groups, AAPIs may be more likely to use maladaptive coping strategies linked to poorer mental health outcomes, including avoidance (Edwards & Romero, 2008), internalization of events in ways that lead to self-blame and self-criticism, social isolation (Wei, Heppner, et al., 2010), and substance use (Pokhrel & Herzog, 2014).

Promoting Mindfulness and Self-Compassion
Increasing self-compassion through mindfulness and compassion meditation represents a culturally sensitive strategy to heal race-based trauma in AAPIs. Originating from Buddhist psychology, compassion meditation helps people release feelings of anger and decrease suffering by cultivating compassion and unconditional regard toward the self and others (Germer & Neff, 2015). Increasing self-compassion may decrease feelings of guilt and shame following instances of racial discrimination by fostering feelings of love and kindness toward oneself. As an emerging clinical intervention, compassion meditation has yielded positive results in decreasing experiences of shame and self-criticism (Gilbert & Procter, 2006; Kuyken et al., 2010), reducing symptoms of depression (Graser et al., 2016; Kearney, 2015), and promoting overall psychological wellness (Hofmann et al., 2011; Shonin et al., 2015). Notably, compassion-based mindfulness interventions show promise as a culturally sensitive strategy to heal race-based trauma (Au et al., 2017; Germer & Neff, 2015; Kearney, 2015). Mindfulness interventions such as compassion meditation may additionally address societal limitations related to health care access and financial barriers. Compassion meditation can be practiced anywhere and does not require expensive books, seminars, or the use of tools.

Counselors can support AAPI clients who present with race-based trauma to cultivate self-compassion by encouraging them to focus on their immediate needs, without judgment, in the present. According to Germer and Neff (2015), the main question when cultivating self-compassion is “What do I need now?” (p. 50). This inquiry is intended to help people connect with their emotional wants, needs, and desires, in the moment, without judgment. Turning awareness toward oneself may illuminate the need for community support or peer support, or point to a physical need, such as fatigue or hunger. Counselors may promote self-compassion through the meditative Hawaiian prayer, Ho’oponopono. Clients may practice the Ho’oponopono meditation by directing four statements toward themselves: “I love you,” “I’m sorry,” “Thank you,” and “Forgive me.” Counselors may help clients begin to heal race-based trauma by empowering them to reflect on their phenomenological experiences as each statement was made. Counselors are encouraged to engage in their own experiences of mindfulness and self-compassion to deepen their understanding of how to modify the practices for clients (Germer & Neff, 2015).

Microinterventions
Counselors may empower AAPI clients facing racial discrimination by providing psychoeducation about microinterventions and creating opportunities for behavioral rehearsal using role plays. Microinterventions are everyday words, deeds, or actions that communicate validation of experiential reality, value as a person, affirmation of racial or group identity, support and encouragement, and reassurance that the receiver is not alone (Sue et al., 2019). Microinterventions seek to empower POCI, White allies, and bystanders to confront and educate perpetrators of microaggressions and have four major strategic goals: making the “invisible” visible, disarming the microaggression, educating the perpetrator, and seeking external reinforcement or support (Sue et al., 2019). Before engaging in microinterventions, it is important to consider the possible positive and negative consequences that may occur. Counselors should discourage AAPI clients from addressing microaggressions when doing so may threaten their physical safety. Engaging in microinterventions in scenarios where a strong power differential exists, such as in workplace or education settings, also requires special consideration (Sue et al., 2019). A full description of each microintervention strategy, goal, objective, rationale, and tactic are beyond the purview of this article, although a few examples for practical application for AAPI clients in counseling are provided below.

Making the “Invisible” Visible. Making the “invisible” visible represents an important component of healing race-based trauma. The first step to liberation necessitates naming the innuendo because it provides language for POCI to describe their experiences and seek mutual validation (Freire, 1970). Counselors may empower AAPI clients to make the “invisible” visible by bringing the microaggression to the perpetrator’s awareness, indicating to the perpetrator that they have spoken or behaved in an offensive way, or forcing the perpetrator to consider the impact and meaning of what has occurred (Sue et al., 2019). These tactics serve to undermine the metacognition, make the metacognition explicit, and broaden the ascribed trait (Sue et al., 2019) and may be helpful for AAPIs who experience race-based discrimination. For example, an Asian American who is accused of having “Kung-Flu” in public may make the metacognition explicit by stating, “You assume I am contagious because of the way I look.” In the same scenario, ascribed traits can be broadened and clarification can be obtained by using statements such as “Anyone can become infected with COVID-19; it is not solely limited to Asians,” and “Are you worried I will get you sick?” Each of these responses are intended to directly identify and address the microaggression while bringing awareness of the metacognition to the perpetrator.

Disarming the Microaggression. Disarming the microaggression may be employed to stop or deflect the microaggression, force the perpetrator to consider their actions, and communicate disagreement (Sue et al., 2019). Helpful tactics AAPIs can use to disarm microaggressions include expressing disagreement, using an exclamation, and stating values and setting limits (Sue et al. 2019). For example, a young Asian American who sees denigrating comments about AAPI individuals on a social media page may respond with the exclamation, “Ouch!” According to Aguilar (2006), this simple exclamation communicates that something offensive has occurred and forces the person to consider the impact and meaning of their behavior. In the same situation, AAPIs may state values and set limits by responding to an offensive comment with, “I have always been respectful of your values and recognize how people are free to hold different attitudes, but I hope you see that what you have written is offensive.”

Educate the Offender. Although it is inappropriate to ask POCI to educate and confront perpetrators, as it exclusively puts the onus of change onto the marginalized person, educating the offender may represent an important strategy to affect societal change. One powerful objective is to facilitate an enlightening conversation that indicates how what has occurred was offensive (Sue et al., 2019). This tactic helps perpetrators differentiate between their intent and the resulting impact (Sue et al., 2019). Because many people become defensive and shift from action to intention when a microaggression is pointed out (Sue, 2015), differentiating between good intent and harmful impact represents a powerful educational strategy (Sue et al., 2019). For example, a Chinese woman may hear COVID-19 incorrectly termed “the Chinese virus” in a conversation among colleagues. In this scenario, she may choose to engage in an enlightening dialogue to educate the offender about how the term “Chinese virus” perpetuates offensive sinophobic attitudes. A helpful conversation starter might be, “I know you may not realize this, but referring to COVID-19 as ‘the Chinese virus’ denigrates Asian individuals and is offensive.” In the same situation, it may additionally be helpful to point out how the term “Chinese virus” violates the WHO (2015) best practices policy for naming new human infectious diseases.

Seek External Reinforcement or Support. The final microintervention is aimed at the promotion of regular self-care, ensuring optimal levels of functioning, and communicating to perpetrators that bigoted behavior is unacceptable (Sue et al., 2019). Self-care and promoting wellness can be employed by pursuing counseling, reporting sinophobic behaviors to appropriate authorities, and seeking the support of one’s spiritual or religious communities (Sue et al., 2019). An increasing number of AAPIs are reaching out to crisis support hotlines. As of March 2020, approximately 13% of AAPIs had contacted crisis text lines compared to 5% of other U.S. callers, respectively (Filbin, 2020). Similar to other POCI, the presence of social support and collective gathering represents an effective coping strategy for Asian Americans (Wei, Alvarez, et al., 2010; Wei et al., 2012; Yoo & Lee, 2005). Indeed, seeking support represents an important strategy AAPIs employ to preserve mental health.

Cultural Proverbs and Analogies
Incorporating proverbs and analogies embedded in AAPI traditions are culturally sensitive strategies to empower clients and strengthen their ethnic identity. Cultural metaphors and stories may additionally strengthen the therapeutic alliance, as AAPI clients may feel their counselor understands and appreciates their cultural background (Hinton & Jalal, 2019). Strong identification with one’s ethnic group promotes wellness and serves as a protective factor in AAPI groups (Iwamoto & Liu, 2010) and Filipino Americans (Mossakowski, 2003). Counselors can empower clients to promote ethnic pride and increase cultural commitment by using proverbs and stories from client culture in counseling. Guiding AAPI clients to embrace their rich and important tradition of knowledge may promote self-esteem and decrease negative affect (Hinton & Jalal, 2019).

Two popular examples of Filipino proverbs may be helpful to promote the importance of social support and cultivate compassion when perpetrators are reluctant to recognize how their behaviors are offensive. A Filipino proverb posits, “A broom is sturdy because it is tightly bound” (in Tagalog, “Matibay ang walis, palibhasa’y magkabigkis”). This message aligns with a collectivistic mentality that people are stronger when standing together. Another Filipino proverb suggests, “It is hard to wake someone up who is pretending to be asleep” (in Tagalog, “Mahirap gisingin ang nagtutulog-tulugan”). This saying cultivates empathy and compassion for perpetrators of microaggressions and sinophobic behavior by reminding clients how it is difficult to educate others when they are not ready or willing to expand their worldviews. Similarly, a Chinese proverb states, “If you are planning for a year, sow rice; if you are planning for a decade, plant trees; if you are planning for a lifetime, educate people.” This saying may motivate clients to engage in dialogue with the people in their lives who have committed hurtful microaggressions. Because AAPI clients tend to terminate counseling at earlier rates compared to other racial groups (Sue & Sue, 2016), counselors can use appropriate cultural analogies to demystify the counseling process. For example, counselors may liken the therapeutic process to cooking a traditional noodle dish (Hinton & Jalal, 2019). Analogous to preparing japchae in Korean culture, pancit palabok in Filipino kitchens, or the Chinese dish zhajiangmian, healing from race-based trauma is a process that necessitates patience, creativity, commitment, and flexibility.

Discussion
The U.S. Surgeon General has recognized how racial and ethnic health disparities are strongly linked to the presence of systemic and ongoing cultural racism (U.S. Department of Health and Human Services, 2000). Counselors who hold dominant social identities (e.g., White, male, heterosexual) are uniquely positioned to use their power and privilege to advocate on behalf of AAPI clients, other POCI, and other marginalized groups by challenging systemic forms of oppression. Indeed, endorsing positive attitudes about diversity (Broido, 2000) and consciously committing to disrupting the cycle of injustice (Waters, 2010) are foundational characteristics of White allies, who seek to end disparity and work to promote the rights of oppressed groups (K. T. Brown & Ostrove, 2013). According to Sue and colleagues (2019), allies actively commit to engaging in actions that dismantle individual and institutional beliefs, practices, and policies that have created barriers for people of color.

AAPIs are facing greater rates of racial discrimination, harassment, violence, sinophobic attitudes, and racial slurs because of fears related to COVID-19 and the current sociopolitical climate. Counselors may help AAPI clients heal race-based trauma through the use of culturally adapted strategies such as promoting mindfulness and self-compassion, employing the use of microinterventions, and incorporating culturally appropriate proverbs and analogies in counseling treatment. Counselors are encouraged to adopt strategies to help AAPIs heal from race-based trauma because experiences of racial discrimination, microaggressions, and sinophobic behaviors are not limited to the current pandemic and instead represent longstanding forms of oppression embedded in American history and culture. AAPIs faced marginalization and racial discrimination before the presence of COVID-19 and will likely continue to experience race-related stress long after the discovery of a vaccination. Just as COVID-19 has illuminated disparities within medical, institutional, and political systems, it has also uncovered the enduring ethnocentric attitudes of many Americans. The proliferation of ongoing discrimination of all racial, ethnic, and marginalized groups is representative of a more insidious form of societal sickness.

Limitations and Future Areas of Research
Although the present article outlines the culturally alert strategies for healing race-based trauma among AAPIs, other marginalized groups face unique challenges related to the unprecedented effects of COVID-19 on social, institutional, and political levels. The deleterious effects of homelessness, social isolation, witnessing of real or perceived racial discrimination or violence, and issues related to LGBTQ individuals because of COVID-19–related issues and policies remain of paramount importance but were not explicitly discussed in this article. Future areas of research may examine the effects of racial discrimination during public health crises and other global events (Wen et al., 2020). Additionally, the ways in which AAPI groups respond to instances of racial discrimination and sinophobia because of COVID-19–related stress remain largely unknown. The manifestation of intergenerational trauma on AAPI families related to COVID-19 also represents an important area of future study. Finally, the national and global effects of COVID-19 on the mental health of diverse groups represents an essential topic of future study.

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

References

Aguilar, L. C. (2006). Ouch! That stereotype hurts: Communicating respectfully in a diverse world. The WALK THE TALK Company.
Allen, G. K., Conklin, H., & Kane, D. K. (2017). Racial discrimination and psychological health among Polynesians in the U.S. Cultural Diversity and Ethnic Minority Psychology, 23(3), 416–424.
https://doi.org/10.1037/cdp0000133
Alvarez, A. N., Liang, C. T. H., & Neville, H. A. (Eds). (2016). The cost of racism for people of color: Contextualizing experiences of discrimination. American Psychological Association.
American Counseling Association. (2014). ACA code of ethics. https://www.counseling.org/docs/default-source/default-document-library/2014-code-of-ethics-finaladdressc97d33f16116603abcacff0000bee5e7.pdf?sfvrsn=5d6b532c_0
American Psychological Association. (2016). Stress in America: The impact of discrimination.
Araújo, B. Y., & Borrell, L. N. (2006). Understanding the link between discrimination, mental health outcomes, and life chances among Latinos. Hispanic Journal of Behavioral Sciences, 28(2), 245–266.
https://doi.org/10.1177/0739986305285825
Au, T. M., Sauer-Zavala, S., King, M. W., Petrocchi, N., Barlow, D. H., & Litz, B. T. (2017). Compassion-based therapy for trauma-related shame and posttraumatic stress: Initial evaluation using a multiple baseline design. Behavior Therapy, 48(2), 207–221. https://www.doi.org/10.1016/j.beth.2016.11.012
Benoit, A. C., Cotnam, J., Raboud, J., Greene, S., Beaver, K., Zoccole, A, O’Brian-Teengs, D., Balfour, L., Wu, W., & Loutfy, M. (2016). Experiences of chronic stress and mental health concerns among urban Indigenous women. Archives of Women’s Mental Health, 19, 809–823. https://doi.org/10.1007/s00737-016-0622-8
Billé, F. (2015). Sinophobia: Anxiety, violence, and the making of Mongolian identity. University of Hawai’i Press.
Broido, E. M. (2000). The development of social justice allies during college: A phenomenological investigation. Journal of College Student Development, 41(1), 3–18.
Brown, L. S. (2008). Cultural competence in trauma therapy: Beyond the flashback. American Psychological Association.
Brown, K. T., & Ostrove, J. M. (2013). What does it mean to be an ally? The perception of allies from the perspective of people of color. Journal of Applied Social Psychology, 43(11), 2211–2222. https://doi.org/10.1111/jasp.12172
Bryant-Davis, T., & Ocampo, C. (2006). A therapeutic approach to the treatment of racist-incident-based trauma. Journal of Emotional Abuse, 6(4), 1–22. https://doi.org/10.1300/J135v06n04_01
Carter, R. T. (2007). Racism and psychological and emotional injury: Recognizing and assessing race-based traumatic stress. The Counseling Psychologist, 35(1), 13–105. https://doi.org/10.1177/0011000006292033
Carter, R. T., Forsyth, J. M., Mazzula, S. L., & Williams, B. (2005). Racial discrimination and race-based traumatic stress: An exploratory investigation. In R. T. Carter (Ed.), Handbook of racial-cultural psychology and counseling, Volume 2: Training and practice (pp. 447–476). Wiley.
Centers for Disease Control and Prevention. (2020). Coronavirus disease 2019: People who are at higher risk. https://www.cdc.gov/coronavirus/2019-ncov/need-extra-precautions/people-at-higher-risk.html
Choi, Y., & Lim, J. H. (2014). Korean newcomer youth’s experiences of racial marginalization and internalization of the model minority myth. Studies on Asia, 4(1), 44–78.
Chou, T., Asnaani, A., & Hofmann, S. G. (2012). Perception of racial discrimination and psychopathology across three U.S. ethnic minority groups. Cultural Diversity and Ethnic Minority Psychology, 18(1), 74–81. http://doi.org/10.1037/a0025432
Clark, R., Anderson, N. B., Clark, V. R., & Williams, D. R. (1999). Racism as a stressor for African Americans: A biopsychosocial model. American Psychologist, 54(10), 805–816. https://doi.org/10.1037/0003-066X.54.10.805
Cochran, B. N., Stewart, A. J., Ginzler, J. A., & Cauce, A. M. (2002). Challenges faced by homeless sexual minorities: Comparison of gay, lesbian, bisexual, and transgender homeless adolescents with their heterosexual counterparts. American Journal of Public Health, 92(5), 773–777. https://doi.org/10.2105/ajph.92.5.77
Comas-Díaz, L., Hall, G. N., & Neville, H. A. (2019). Racial trauma: Theory, research, and healing: Introduction to the special issue. American Psychologist, 74(1), 1–5. http://doi.org/10.1037/amp0000442
Congressional Asian American Pacific American Caucus. (2020). As coronavirus fears incite violence, CAPAC members urge colleagues to not stoke xenophobia. https://capac-chu.house.gov/press-release/coronavirus-fears-incite-violence-capac-members-urge-colleagues-not-stoke-xenophobia
Devakumar, D., Shannon, G., Bhopal, S. S., & Abubaker, I. (2020). Racism and discrimination in COVID-19 responses. The Lancet, 395(10231), 1194. https://doi.org/10.1016/S0140-6736(20)30792-3
Dreher, A., Hahn, E., Diefenbacher, A., Nguyen, M. H., Böge, K., Burian, H., Dettling, M., Burian, R., & Ta, T. M. T.
(2017). Cultural differences in symptom representation for depression and somatization measured by the PHQ between Vietnamese and German psychiatric outpatients. Journal of Psychosomatic Research, 102,
71–77. https://doi.org/10.1016/j.jpsychores.2017.09.010
Edwards, L. M., & Romero, A. J. (2008). Coping with discrimination among Mexican descent adolescents. Hispanic Journal of Behavioral Sciences, 30(1), 24–39. https://doi.org/10.1177/0739986307311431
Federal Emergency Management Agency. (2020). COVID-19 emergency declaration. https://www.fema.gov/news
-release/2020/03/13/covid-19-emergency-declaration
Filbin, B. (2020, March 20). Bob’s notes on COVID-19: Mental health data on the pandemic. Crisis Text Line. https://www.crisistextline.org/data/bobs-notes-on-covid-19-mental-health-data-on-the-pandemic
Freire, P. (1970). Pedagogy of the oppressed. Continuum.
Gee, G. C., Spencer, M., Chen, J., Yip, T., & Takeuchi, D. T. (2007). The association between self-reported racial discrimination and 12-month DSM-IV mental disorders among Asian Americans nationwide. Social Science & Medicine, 64(10), 1984–1996. https://doi.org/10.1016/j.socscimed.2007.02.013
Gee, G. C., & Verissimo, A. D. O. (2016). Racism and behavioral outcomes over the life course. In A. N. Alvarez, C. T. H. Liang, & H. A. Neville (Eds.), The cost of racism for people of color: Contextualizing experiences of discrimination (pp. 133–162). American Psychological Association.
Germer, C. K., & Neff, K. D. (2015). Cultivating self-compassion in trauma survivors. In V. M. Follette, J. Briere, D. Rozelle, J. W. Hopper, & D. I. Rome (Eds.), Mindfulness-oriented interventions for trauma: Integrating contemplative practices (pp. 43–58). Guilford.
Gilbert, P., & Procter, S. (2006). Compassionate mind training for people with high shame and self-criticism: Overview and pilot study of a group therapy approach. Clinical Psychology and Psychotherapy, 13(6), 353–379. https://doi.org/10.1002/cpp.507
Go, A. S., Mozaffarian, D., Roger, V. L., Benjamin, E. J., Berry, J. D., Blaha, M. J., Dai, S., Ford, E. S., Fox, C. S., Franco, S., Fullerton, H. J., Gillespie, C., Hailpern, S. M., Heit, J. A., Howard, V. J., Huffman, M. D., Judd, S. E., Kissela, B. M., Kittner, S. J. . . . Turner, M. B. (2014). Executive summary: Heart disease and stroke statistics—2014 update: A report from the American Heart Association. Circulation, 129(3), 399–410. https://doi.org/10.1161/01.cir.0000442015.53336.12
Graser, J., Höfling, V., Weßlau, C., Mendes, A., & Stangier, U. (2016). Effects of a 12-week mindfulness, compassion, and loving kindness program on chronic depression: A pilot within-subjects wait-list controlled trial. Journal of Cognitive Psychotherapy, 30(1), 35–49. https://doi.org/10.1891/0889-8391.30.1.35
Grover, S., & Ghosh, A. (2014). Somatic symptom and related disorders in Asians and Asian Americans. Asian Journal of Psychiatry, 7, 77–79. https://doi.org/10.1016/j.ajp.2013.11.014
Harrell, S. P. (2000). A multidimensional conceptualization of racism-related stress: Implications for the well-being of people of color. American Journal of Orthopsychiatry, 70(1), 42–57. https://doi.org/10.1037/h0087722
Helms, J. E., Nicolas, G., & Green, C. E. (2012). Racism and ethnoviolence as trauma: Enhancing professional and research training. Traumatology, 18(1), 65–74. https://doi.org/10.1177/1534765610396728
Hernández-Wolfe, P. (2013). A borderlands view on Latinos, Latin Americans, and decolonization: Rethinking mental health. Jason Aronson.
Hinton, D. E., & Good, B. J. (Eds.). (2009). Culture and panic disorder. Stanford University Press.
Hinton, D. E., & Good, B. J. (Eds.). (2016). Culture and PTSD: Trauma in global and historical perspective. University of Pennsylvania Press.
Hinton, D. E., & Jalal, B. (2019). Dimensions of culturally sensitive CBT: Application to Southeast Asian populations. American Journal of Orthopsychiatry, 89(4), 493–507. https://doi.org/10.1037/ort0000392
Hinton, D. E., & Lewis-Fernández, R. (2011). The cross-cultural validity of posttraumatic stress disorder: Implications for DSM-5. Depression & Anxiety, 28(9), 783–801. https://doi.org/10.1002/da.20753
Hinton, D. E., Pollack, A. A., Weiss, B., & Trung, L. T. (2018). Culturally sensitive assessment of anxious-depressive distress in Vietnam: Avoiding category truncation. Transcultural Psychiatry, 55(3), 384–404. https://doi.org/10.1177/1363461518764500
Hofmann, S. G., Grossman, P., & Hinton, D. E. (2011). Loving-kindness and compassion meditation: Potential for psychological interventions. Clinical Psychology Review, 31(7), 1126–1132. https://doi.org/10.1016/j.cpr.2011.07.003
Huber, L. P., & Soloranzo, D. G. (2015). Racial microaggressions as a tool for critical race research. Race, Ethnicity and Education, 18(3), 297–320. https://doi.org/10.1080/13613324.2014.994173
Hwang, W.-C., & Goto, S. (2008). The impact of perceived racial discrimination on the mental health of Asian American and Latino college students. Cultural Diversity and Ethnic Minority Psychology, 14(4), 326–335. https://doi.org/10.1037/1099-9809.14.4.326
Iwamoto, D. K., & Liu, W. M. (2010). The impact of racial identity, ethnic identity, Asian values, and race-related stress on Asian Americans and Asian international college students’ psychological well-being. Journal of Counseling Psychology, 57(1), 79–91. https://doi.org/10.1037/a0017393
Jones, H. L., Cross, W. E., Jr., & DeFour, D. C. (2007). Race-related stress, racial identity attitudes, and mental health among Black women. Journal of Black Psychology, 33(2), 208–231. https://doi.org/10.1177/0095798407299517
Kawai, Y. (2005). Stereotyping Asian Americans: The dialectic of the model minority and the Yellow Peril. Howard Journal of Communications, 16(2), 109–130. http://doi.org/10.1080/10646170590948974
Kearney, D. J. (2015). Mindfulness-based stress reduction and loving-kindness meditation for traumatized veterans. In V. M. Follette, J. Briere, D. Rozelle, J. W. Hopper, & D. I. Rome (Eds.), Mindfulness-oriented interventions for trauma: Integrating contemplative practices (pp. 273–283). Guilford.
Kuyken, W., Watkins, E., Holden, E., White, K., Taylor, R. S., Byford, S., Evans, A., Radford, S., Teasdale, J. D., & Dalgleish, T. (2010). How does mindfulness-based cognitive therapy work? Behaviour Research and Therapy, 48(11), 1105–1112. https://doi.org/10.1016/j.brat.2010.08.003
Lee, E. (2002). The Chinese exclusion example: Race, immigration, and American gatekeeping, 1882-1924. Journal of American Ethnic History, 21(3), 36–62.
Lee, E. A., Soto, J. A., Swim, J. K., & Bernstein, M. J. (2012). Bitter reproach or sweet revenge: Cultural differences in response to racism. Personality and Social Psychology Bulletin, 38(7), 920–932.
http://doi.org/10.1177/0146167212440292
Liang, C. T. H., & Fassinger, R. E. (2008). The role of collective self-esteem for Asian Americans
experiencing racism-related stress: A test of moderator and mediator hypotheses. Cultural Diversity and Ethnic Minority Psychology, 14(1), 19–28. https://doi.org/10.1037/1099-9809.14.1.19
Lopez, G., Ruiz, N. G., & Patten, E. (2017). Key facts about Asian Americans, a diverse and growing population. https://www.pewresearch.org/fact-tank/2017/09/08/key-facts-about-asian-americans
Mattar, S. (2011). Educating and training the next generations of traumatologists: Development of cultural competencies. Psychological Trauma: Theory, Research, Practice, and Policy, 3(3), 258–265. https://doi.org/10.1037/a0024477
Mossakowski, K. N. (2003). Coping with perceived discrimination: Does ethnic identity protect mental health? Journal of Health and Social Behavior, 44(3), 318–331. https://doi.org/10.2307/1519782
National Association for the Advancement of Colored People. (2020, March 17). Civil rights and racial justice organizations denounce discrimination against Asian Americans and urge unity in responding to coronavirus pandemic. https://www.naacp.org/latest/civil-rights-racial-justice-organizations-denounce-discrimination-asian-americans-urge-unity-responding-coronavirus-pandemic
Ocampo, A. C., & Soodjinda, D. (2016). Invisible Asian Americans: The intersection of sexuality, race, and education among gay Asian Americans. Race, Ethnicity, and Education, 19(3), 480–499.
https://doi.org/10.1080/13613324.2015.1095169
Pieterse, A. L., Todd, N. R., Neville, H. A., & Carter, R. T. (2012). Perceived racism and mental health among Black American adults: A meta-analytic review. Journal of Counseling Psychology, 59(1), 1–9.
https://doi.org/10.1037/a0026208
Pieterse, A., & Powell, S. (2016). A theoretical overview of the impact of racism on people of color. In A. N.
Alvarez, C. T. H. Liang, & H. A. Neville (Eds.), The cost of racism for people of color: Contextualizing experiences of discrimination (pp. 11–30). American Psychological Association.
Pokhrel, P., & Herzog, T. A. (2014). Historical trauma and substance use among Native Hawaiian college students. American Journal of Health Behavior, 38(3), 420–429. https://doi.org/10.5993/AJHB.38.3.11
Potok, M. (2017). The Trump effect. Intelligence Report. https://www.splcenter.org/fighting-hate/intelligence-report/2017/trump-effect
Qin, D. B., Way, N., & Rana, M. (2008). The “model minority” and their discontent: Examining peer discrimination and harassment of Chinese American immigrant youth. New Directions for Child and Adolescent Development, 2008(121), 27–42. https://doi.org/10.1002/cd.221
Rodriguez-Seijas, C., Stohl, M., Hasin, D. S., & Eaton, N. R. (2015). Transdiagnostic factors and mediation of the relationship between perceived racial discrimination and mental disorders. JAMA Psychiatry, 72(7), 706–713. https://doi.org/10.1001/jamapsychiatry.2015.0148
Schild, L., Ling, C., Blackburn, J., Stringhini, G., Zhang, Y., & Zannettou, S. (2020). “Go eat a bat, Chang!” An early look on the emergence of sinophobic behavior on web communities in the face of COVID-19. Computers and Society, 1–16. https://arxiv.org/pdf/2004.04046.pdf
Shelton, J. N., Richeson, J. A., Salvatore, J., & Hill, D. M. (2006). Silence is not golden: The intrapersonal consequences of not confronting prejudice. In S. Levin & C. van Laar (Eds.), Stigma and group inequality: Social psychological perspectives (pp. 65–81). Lawrence Erlbaum.
Shonin, E., Van Gordon, W., Compare, A., Zangeneh, M., & Griffiths, M. D. (2015). Buddhist-derived loving-kindness and compassion meditation for the treatment of psychopathology: A systematic review. Mindfulness, 6(5), 1161–1180. https://www.doi.org/10.1007/s12671-014-0368-1
Smith, W. A., Hung, M., & Franklin, J. D. (2011). Racial battle fatigue and the miseducation of Black men: Microaggressions, societal problems, and environmental stress. The Journal of Negro Education, 80(1), 63–82. https://doi.org/10.2307/41341106
Sue, D. W. (2015). Race talk and the conspiracy of silence: Understanding and facilitating difficult dialogues on race. Wiley.
Sue, D. W., Alsaidi, S., Awad, M. N., Glaeser, E., Calle, C. Z., & Mendez, N. (2019). Disarming racial microaggressions: Microintervention strategies for targets, White allies, and bystanders. American Psychologist, 74(1), 128–142. https://doi.org/10.1037/amp0000296
Sue, D. W., Capodilupo, C. M., Torino, G. C., Bucceri, J. M., Holder, A. M. B., Nadal, K. L., & Esquilin, M. (2007). Racial microaggressions in everyday life: Implications for clinical practice. American Psychologist, 62(4), 271–286. https://doi.org/10.1037/0003-066X.62.4.271
Sue, D. W., & Sue, D. (2016). Counseling the culturally diverse: Theory and practice (7th ed.). Wiley.
Sundstrom, R. R., & Kim, D. H. (2014). Xenophobia and racism. Critical Philosophy of Race, 2(1), 20–45.
https://doi.org/10.5325/critphilrace.2.1.0020
Taylor, S. (2019). The psychology of pandemics: Preparing for the next global outbreak of infectious disease. Cambridge Scholars Publishing.
Taylor, S., & Asmundson, G. J. G. (2004). Treating health anxiety: A cognitive-behavioral approach. Guilford.
Ting-Toomey, S., Yee-Jung, K. K., Shapiro, R. B., Garcia, W., Wright, T. J., & Oetzel, J. G. (2000). Ethnic/cultural identity salience and conflict styles in four US ethnic groups. International Journal of Intercultural Relations, 24(1), 47–81. https://doi.org/10.1016/S0147-1767(99)00023-1
Tsai, J., & Wilson, M. (2020). COVID-19: A potential public health problem for homeless populations. The Lancet, 5(4), e186–e187. https://doi.org/10.1016/S2468-2667(20)30053-0
United Nations Human Rights, Office of the High Commissioner. (2020, March 23). States should take action against COVID-19-related expressions of xenophobia, says UN expert. https://www.ohchr.org/EN/News
Events/Pages/DisplayNews.aspx?NewsID=25739&LangID=E
Unnikrishnan, R., Gupta, P. K., & Mohan, V. (2018). Diabetes in South Asians: Phenotype, clinical presentation, and natural history. Current Diabetes Reports, 18(30). https://doi.org/10.1007/s11892-018-1002-8
U.S. Department of Health and Human Services. (2000). Mental health: Culture, race and ethnicity: A supplement to Mental health: A report of the Surgeon General.
Waters, A. (2010). Book review: Injustice. Local Economy, 25(5–6), 523–525. https://doi.org/10.1080/02690942.2010.525995
Wei, M., Alvarez, A. N., Ku, T.-Y., Russell, D. W., & Bonett, D. G. (2010). Development and validation of a Coping with Discrimination Scale: Factor structure, reliability, and validity. Journal of Counseling Psychology, 57(3), 328–344. https://doi.org/10.1037/a0019969
Wei, M., Heppner, P. P., Ku, T.-Y., & Liao, K. Y.-H. (2010). Racial discrimination stress, coping, and depressive symptoms among Asian Americans: A moderation analysis. Asian American Journal of Psychology, 1(2), 136–150. https://doi.org/10.1037/a0020157
Wei, M., Wang, K. T., Heppner, P. P., & Du, Y. (2012). Ethnic and mainstream social connectedness, perceived racial discrimination, and posttraumatic stress symptoms. Journal of Counseling Psychology, 59(3), 486–493. https://doi.org/10.1037/a0028000
Wen, J., Aston, J., Liu, X., & Ying, T. (2020). Effects of misleading media coverage on public health crisis: A case of the 2019 novel coronavirus outbreak in China. Anatolia: An International Journal of Tourism and Hospitality Research. https://doi.org/10.1080/13032917.2020.1730621
White, A. I. R. (2020). The art of medicine: Historical linkages: Epidemic threat, economic risk, and xenophobia. The Lancet, 395, 1250–1251. https://doi.org/10.1016/S0140-6736(20)30737-6
Williams, D. R., & Williams-Morris, R. (2000). Racism and mental health: The African American experience. Ethnicity and Health, 5(3–4), 243–268. https://doi.org/10.1080/713667453
World Health Organization. (2015, May 8). WHO issues best practices for naming new human infectious diseases. https://www.who.int/mediacentre/news/notes/2015/naming-new-diseases/en
Yoo, H. C., & Lee, R. M. (2005). Ethnic identity and approach-type coping as moderators of the racial discrimination/well-being relation in Asian Americans. Journal of Counseling Psychology, 52(4), 497–506. https://doi.org/10.1037/0022-0167.52.4.497
Yum, J. O. (1988). The impact of Confucianism on interpersonal relationships and communication patterns in East Asia. Communication Monographs, 55(4), 374–388. https://doi.org/10.1080/03637758809376178

Stacey Diane Arañez Litam, PhD, NCC, CCMHC, LPCC, is an assistant professor of counselor education at Cleveland State University. Correspondence may be addressed to Stacey Litam, Cleveland State University, 2121 Euclid Avenue, Julka Hall 275, Cleveland, OH 44115, s.litam@csuohio.edu.

Attachment, Ego Resilience, Emerging Adulthood, Social Resources, and Well-Being Among Traditional-Aged College Students

Joel A. Lane

 

To improve conceptualizations of college student mental health, the present study (N = 538) compared predictors of well-being that comprise both well-established counseling theories (e.g., attachment) and newer models specific to the life experience of the millennial generation and Generation Z. Predictors included internal resources (i.e., attachment security, ego resilience), emerging adulthood identification, and social resources (i.e., social support, social media usage). Each variable set predicted significant variance. The emerging adulthood and social media variables accounted for approximately 7% of variance in both psychological well-being and life satisfaction. Identifying emerging adulthood as a time of negativity and instability was the second strongest predictor of psychological well-being, while identifying emerging adulthood as a time of experimentation and possibilities was the second biggest predictor of life satisfaction. Implications for conceptualizing and treating today’s students are discussed.

Keywords: college counseling, emerging adulthood, social media, attachment, social support

In recent years, higher education personnel have noticed declines in college student emotional health and corresponding increases in stress, depression, and anxiety (Watkins et al., 2012). The rates of students exhibiting frequent anxiety and depression symptoms have nearly doubled over a 30-year period and are now two to three times higher than those of the general population (American College Health Association [ACHA], 2015). Administrators have also described corresponding changes in college counseling services, especially regarding the increased need for crisis intervention and triage services (Watkins et al., 2012).

These trends roughly correspond to the millennial generation and Generation Z entering college. The societal forces that characterize these generational cohorts, including the proliferation of social media (Ellison et al., 2007; McCay-Peet & Quan-Haase, 2017) and increases in parental involvement and corresponding decreases in perceptions of college student maturity and autonomy (Watkins et al., 2012), seem to have substantially altered the psychosocial trajectories for today’s traditional-aged college populations (Arnett, 2004, 2016). The counseling profession has wrestled with how best to respond to these trends, and in many cases has relied on conceptual frameworks and theories of psychosocial development created long before the emergence of the millennial generation. It seems timely to attempt to develop a framework for mental health and well-being during the college years that incorporates theories specific to present generations of traditional-aged college students with more well-established theories of development. Such is the purpose of the present study, in which the contributions to college student well-being of attachment security (Bowlby, 1969/1997), ego resilience (Block & Block, 1980), and social support are integrated with and compared to the theory of emerging adulthood (Arnett, 2004), a conceptualization of psychosocial development occurring from the late teens through the 20s for contemporary generations.

Attachment and Ego Resilience

It is generally accepted that the constructs of attachment security and ego resilience play important roles in college student mental health and well-being (e.g., Lane, 2015; Taylor et al., 2014). According to Bowlby (1969/1997), the quality of our earliest interactions with caregivers provides us with relational templates, or types of attachment, that influence self-worth and interpersonal functioning throughout the life span. Ego resilience is a personality trait reflecting our ability to adapt and thrive amid stress and transition (Block & Block, 1980; Taylor et al., 2014). In the present study, attachment and ego resilience are conceptualized as internal resources because they are instilled early in life, relatively stable over time, and influential to mental health during the college years (Lane, 2016; Lane et al., 2017; Taylor et al., 2014).

Attachment and ego resilience also similarly impact functioning in times of challenge. With secure attachment, individuals are more likely to believe themselves capable of handling adversity and that others can be called upon in times of need (Brennan et al., 1998), presumably because of the consistent responsiveness of their caregivers earlier in life. Conversely, insecure attachment can lead individuals to doubt their own capabilities (i.e., attachment anxiety) or the intentions of others to provide them with support (i.e., attachment avoidance) in times of need. These internalized beliefs can lead to problematic outcomes during distressing situations (Wei et al., 2007), including maladaptive interpersonal dependence or isolation and a heightened focus on the distress (Brennan et al., 1998). Similarly, individuals high in ego resilience are generally able to respond to stressful situations with flexibility and an assortment of healthy coping behaviors (Taylor et al., 2014). Conversely, individuals low in ego resilience may lack the diversity of healthy coping strategies necessary to effectively persevere through a range of life challenges, and they may be prone to giving up when frustrated (Block & Block, 1980). Thus, individuals with attachment insecurity and low ego resilience are at an increased risk of accumulating stress during stressful situations rather than persevering through them (Brennan et al., 1998), which is a likely explanation for the associations of each construct with depression and anxiety symptoms (Taylor et al., 2014).

This latter point is especially important in the context of the present study. The college experience contains numerous life and role transitions, including leaving home, establishing independence, reconstructing social support networks, and developing professional goals (Lane, 2015). Each of these transitions pose opportunities for students high in internal resources to thrive and risks for those who are low in internal resources to accumulate stress and negative mental health symptoms (Lane, 2015). Accordingly, internal resources are conceptualized as the first set of constructs in the present model. That is, they seem to provide a foundation for college student mental health and well-being and perhaps do so by contributing to other potentially relevant aspects of well-being, such as identification with emerging adulthood (Schnyders & Lane, 2018) and social support (Galambos et al., 2006).

Emerging Adulthood

Although attachment and ego resilience have long been considered contributors to college student mental health and well-being, many of the aforementioned factors involved in declining mental health trajectories comprise social forces unique to present-day young adults. Emerging adulthood (Arnett, 2004) is a theory that describes the effects of such factors on psychosocial functioning between the ages of 18 and 29. Specifically, it suggests that this age range now represents a period of life distinct from both adolescence and adulthood. The theory describes several dimensions that are representative of the present-day emerging adult experience, including a prolonged period of identity exploration (i.e., using the emerging adulthood years to consider and audition preferences regarding career, worldviews, romantic relationships, and interpersonal characteristics), significant demographic and relational instability (e.g., increased likelihood of multiple residence changes with respect to previous generations, causing disruptions in social groups), subjectively feeling in between adolescence and adulthood, and idealistic thinking about future possibilities (Arnett, 2004). These dimensions suggest that emerging adulthood is a complex phenomenon with significant individual variation: One’s degree of identification with each dimension can shape their relative satisfaction with the overall emerging adulthood experience (Baggio et al., 2015). Moreover, some evidence suggests that parental attachment quality predicts one’s identification with the various themes of emerging adulthood (Schnyders & Lane, 2018).

Emerging adulthood theory has several implications in the context of college student well-being. First, life transition is a salient theme of emerging adulthood, given that the late teens and 20s are a time of leaving the parental household, creating new attachment and support networks, entering and persisting through college (for many emerging adults), and entering the world of work (Arnett, 2004). These transitions can leave emerging adults vulnerable to distress (Lane et al., 2017) and are central features of the college student experience. Second, emerging adulthood suggests that present traditional-aged college students are at an earlier stage of psychosocial development than prior generations, even though expectations placed on them have remained stable (Arnett, 2004). Thus, emerging adult college students are still expected to navigate the many transitions of the college experience regardless of whether or not they have developed the necessary maturity and life skills. Finally, the emerging adulthood years constitute a high degree of risk-taking behaviors, impulsivity, and psychiatric risk (Arnett, 2004; Baggio et al., 2015). That is, not only is emerging adulthood a time of vulnerability to stress, but also a time of elevated risk for maladaptive stress responses. Thus, in the context of the present study, it is possible that the emerging adult experience uniquely contributes to mental health and well-being with respect to the contribution of internal resources.

Social Resources

Like interpersonal resources and emerging adulthood, social support is a construct with implications for mental health. The degree to which an individual feels supported by their close relationships mitigates distress during stressful situations (Sarason et al., 1991). Individuals who are satisfied with their social support also report less depression, anxiety, and loneliness, and enhanced well-being compared to those low in social support (Galambos et al., 2006).

The aforementioned societal changes impacting emerging adulthood also have implications for college student social support. Today’s emerging adult social support networks have grown in complexity as psychosocial developmental trajectories have continued to evolve (Arnett, 2004) and social media has become an increasingly ingrained aspect of everyday life. These changes necessitate reconsideration of the construct of social support in the 21st century. That is, what are the implications for social support when interpersonal contact is increasingly conducted electronically? Is it possible for one to derive the benefits of social support from social media interactions? To address these questions, Manago et al. (2012) asked a sample of college students to respond to various support-related questions while browsing Facebook. Participants were able to use Facebook to meet certain intimacy needs, especially that of emotional disclosure, and the size of one’s Facebook friends list was positively associated with perceived social support and life satisfaction. Others have suggested that social media sites provide social capital and facilitate sustained connection with potentially beneficial relationships (Ellison et al., 2007). In light of these ideas, the present study conceptualizes social resources to include both social support and social media usage. Assessing the degree to which each construct impacts college student mental health and well-being is important given the ubiquity of social media on college campuses and the current disagreement among scholars regarding its benefits (Manago et al., 2012) and drawbacks (Twenge, 2013). Given that social support seems to facilitate the contributions of internal resources to mental health (Taylor et al., 2014) and emerging adulthood contributes to increasingly complex social networks (Arnett, 2004), social resources are conceptualized as a third level of constructs in the present model, after internal resources and emerging adulthood identification.

Present Study

The present study was designed to address several literature gaps concerning college student mental health and well-being. First, it combines several disparate threads of related research by testing a model including internal resources (i.e., attachment security and ego resilience), identification with the dimensions of emerging adulthood, and social resources (i.e., social support and social media usage). Although some research has examined the additive impact of more than one of these sets of constructs together (e.g., attachment and social support), no existing research has examined all three collectively. Second, the present study examined the mental health implications of emerging adulthood and social media usage: two constructs that are the result of 21st century societal forces. A primary hypothesis of the study was that each predictor variable set would explain unique and additive variance for two characteristics of college student mental health (i.e., psychological well-being [PWB] and life satisfaction). A secondary hypothesis was that emerging adulthood identification and social media usage would predict unique variance in each outcome variable even after accounting for the effects of all other predictor variables in the model.

Method

Participants and Procedure

Participants in this IRB-approved study were traditional-aged undergraduate students from a large, public university in a metropolitan area of the Pacific Northwest. Participants were recruited via a recruitment email sent to a random sample of students meeting the inclusion criteria (i.e., 18 to 25 years old and enrolled as a full-time undergraduate student). An a priori power analysis was conducted to determine appropriate sample size (Faul et al., 2007). Given the large number of variables in the model and the fact that Hypothesis 2 was based on semipartial correlations, a small-to-medium effect size was selected (f 2 = .08). Results suggested an ideal sample size of approximately 400 participants. Assuming an approximate 10% response rate (Manfreda et al., 2008), recruitment emails were sent to 4,000 undergraduates.

The recruitment email contained a link to an online survey containing all demographic and study variable items. Surveys were received from 616 undergraduates (15.4% response rate). Data were treated according to the recommendations for multivariate analysis by Meyers et al. (2013). That is, 56 cases (9.1%) were removed because they contained missing data on at least 50% of the items. An additional 17 cases (2.8%) were removed for indicating that they were no longer paying attention at the midpoint of the survey. The remaining missing values were replaced with their respective item mean because no item was missing more than seven cases (1.3%) and no variable contained more than two missing items for any remaining participant. Data were screened for multivariate outliers using Mahalanobis distance, resulting in the removal of five (0.9%) participants. Thus, the study sample consisted of 538 participants.

The study sample had a mean age of 21.72 years (SD = 2.05) and was predominantly female (n = 378, 70.3%), while other participants identified as male (n = 142, 26.4%) or other (n = 16, 3.0%), and two participants declined to answer. The sample was racially diverse, as 341 (63.4%) participants identified as White, 64 (11.9%) as Latinx, 63 (11.7%) as Asian or Pacific Islander, 14 (2.6%) as Black or African American, 11 (2.0%) as Arab American or Middle Eastern, eight (1.5%) as Native American, 27 (5.0%) as multiracial, and seven (1.3%) as other, while three participants declined to answer.

Instruments

Attachment security. As the first internal resources variable, attachment security was measured using the 12-item Experiences in Close Relationship Scale-Short Form (ECR-S; Wei et al., 2007). The items are evenly divided into two subscales: Attachment Anxiety (e.g., “I need a lot of reassurance that I am loved by my partner”) and Attachment Avoidance (e.g., “I am nervous when partners get too close to me”). Items are rated on a 7-point Likert scale. Scores were summed, with higher scores indicating higher attachment insecurity for each dimension. Internal consistencies in the present sample (α = .78 for attachment anxiety, α = .80 for attachment avoidance) mirrored those reported by the ECR-S authors (α = .77 and α = .78, respectively).

Ego resilience. Ego resilience served as the other internal resources variable. It was measured using an 11-item version of Block and Block’s (1980) Ego-Resiliency Scale (Taylor et al., 2014). Items (e.g., “I can bounce back and recover after a stressful or bad experience”) are rated on a Likert scale ranging from one (most undescriptive of me) to nine (most descriptive of me). Higher total scores indicate higher ego resilience. The 11-item version has demonstrated internal consistencies ranging from .63 to .81 across multiple time points with a sample of emerging adults (Taylor et al., 2014). Internal consistency in the present sample was .73.

Emerging adulthood. The second level of predictor variables comprised dimensions of emerging adulthood. Identification with emerging adulthood dimensions was assessed using the 8-item Inventory of Dimensions of Emerging Adulthood (IDEA-8; Baggio et al., 2015). The items are evenly divided into four subscales (i.e., Experimentation/Possibilities, Negativity/Instability, Identity Exploration, and Feeling In Between [adolescence and adulthood]) that each represent dimensions of emerging adult theory (Arnett, 2004). Participants rate the degree to which various statements represent the present time in their lives (e.g., “this is a time of deciding on your own beliefs and values”) on a 4-point scale (1 = strongly disagree, 4 = strongly agree). Scores for each subscale are summed to indicate how participants feel each dimension characterizes their emerging adulthood experience. The IDEA-8 subscales demonstrate internal consistencies ranging from .66 to .76 (Baggio et al., 2015), mirroring the range
found in the present sample (α = .69 to α = .77).

Social support. Social support served as the first social resources variable. It was measured using the 6-item Subjective Social Support subscale of the Duke Social Support Index (Blazer et al., 1990). Items (e.g., “Can you talk about your deepest problems with at least some of your family and friends?”) are rated on a 5-point scale (1 = none of the time, 5 = all of the time), with higher scores indicating higher perceived social support. Internal consistency in the present sample was .85, mirroring estimates found in prior studies (α = .82; Hawley et al., 2014).

Facebook usage. The other social resources variable was social media usage, measured using the 8-item Facebook Intensity Scale (FIS; Ellison et al., 2007). Although numerous social media platforms are popular among college students, developers of social media usage instruments have focused on Facebook. Given its recognizability and ubiquity, it remains the best proxy for assessing overall social media usage (Ortiz-Ospina, 2019). The first FIS item asks participants to approximate their number of Facebook “friends,” while the second item asks them to approximate time spent on Facebook each day. The remaining items ask participants to rate their agreement with various items assessing the importance of Facebook in their lives (e.g., “Facebook has become a part of my daily routine”). Items are first standardized and then summed to create an index of Facebook usage. The FIS authors reported strong convergent validity and internal consistency (α = .83), mirroring that found in the present sample (α = .87).

College student mental health. Operationalizing mental health is challenging given its many existing conceptualizations. Some authors have argued that mental health and mental illness are separate constructs entirely (e.g., Lent, 2004). Lent (2004) suggested that a complete understanding of mental health incorporates both PWB and subjective well-being (i.e., happiness) and added that subjective well-being is best conceptualized as a higher-order outcome of PWB. Others have argued that PWB and depression are opposite ends of the same construct (Bech et al., 2003), suggesting that PWB instruments also measure depressive affect and vice versa. Collectively, and in conjunction with the focus on depressive symptoms in the aforementioned college student mental health research, it seems useful to conceptualize mental health using indices of PWB and life satisfaction (Lent, 2004).

Psychological well-being. PWB was measured using the 5-item World Health Organization-Five Well-Being Index (WHO-5; Bech et al., 2003). Each item is a positively worded self-statement measuring the absence of various symptoms of depression (e.g., “I have felt calm and relaxed”). Because of its ability to measure both well-being and depression, it was selected as an ideal candidate for the present study. The presence of each statement over a 2-week period is rated on a 6-point scale (0 = not present,
5 = constantly present). Scores are multiplied by four to create a 0–100 scale, with higher scores indicating higher PWB, and scores below 28 indicating clinical depression (Bech et al., 2003). The authors reported strong evidence for reliability (α = .82) and validity. In the present sample, internal consistency was .81.

Life satisfaction. Life satisfaction was measured using the Satisfaction with Life Scale (SWLS; Diener et al., 1985). Participants rate agreement with five items (e.g., “In most ways my life is close to my ideal”) on a 7-point scale (1 = strongly disagree, 7 = strongly agree). Internal consistency in both the validation study and present sample was .87.

Results

Table 1 presents the descriptive statistics and intercorrelations for all study variables. With the exception of the emerging adult feeling in between variable, all variables were significantly correlated with each of the outcome variables. Significant correlations ranged from small to large for both PWB (r = .12, p < .05 for Facebook usage and r = .44, p < .001 for ego resilience) and life satisfaction (r = .12, p < .01 for identity exploration and r = .50, p < .001 for social support). Also, the outcome variables were significantly associated with three emerging adulthood variables in different directions. That is, they were positively correlated with experimentation/possibilities and identity exploration, and they were negatively and moderately correlated with negativity/instability; however, neither outcome variable was significantly associated with the feeling in between variable.

To reduce the possibility of confounds in the regression results, several potential covariates were tested for their relatedness to the outcome variables. Based on prior research, age, gender, and race were tested (Galambos et al., 2006; Schnyders & Lane, 2018). Gender and race were dummy coded so that a) 0 = non-woman (i.e., man or other) and 1 = woman, and b) 0 = non-White and 1 = White. Significant differences were present in the Satisfaction with Life Scale scores on the basis of gender: t(537) = -2.841, p < .01. The mean life satisfaction score for women in the sample was 1.91 points higher than for non-women. Thus, all subsequent analyses controlled for the effects of gender. No other significant associations involving the potential covariates were present.

 

Table 1

Pearson Intercorrelations Among Study Variables

 

Variables Intercorrelations
   M     SD 1 2 3 4 5 6 7 8 9 10
  1. AAn. 23.42 7.28       –
  2. AAv. 17.03 6.76      .07      –
  3. ER 69.10 11.94     -.33**   -.08      –
  4. EP  7.08 1.16     -.17**   -.04    .24**    –
   5. NI 6.90 1.24      .20**     .06   -.25** -.06    –
  6. IE 6.80 1.34     -.05    .04    .12*  .38**  .07     –
  7. IB 6.83 1.38      .06    .06   -.01  .22**  .12*   .41*   –
  8. SS 21.98 4.27     -.25**   -.27**    .32**  .21** -.19**   .07 .05   –
  9. FB 21.75 8.72      .13*   -.11*   -.05  .08 -.02   .08 .16** .14*   –
10. PWB 55.35 18.72     -.27**   -.14*    .44**  .32** -.34**  .16**  .03 .40** .12*   –
11. LS 21.72 7.21     -.25**   -.25**    .39**  .36** -.30**  .12* -.02 .50** .14* .61**

Note. N = 538. AAn. = attachment anxiety; AAv. = attachment avoidance; ER = ego resilience; EP = experimentation/possibilities; NI = negativity/instability; IE = identity exploration; IB = feeling in between; SS = social support; FB = Facebook usage; PWB = psychological well-being; LS = life satisfaction.
*p < .05. **p < .001

 

 

Hypothesis 1 predicted that internal resources, emerging adulthood identification, and social resources would each predict unique and additive variance in each outcome variable. Thus, two hierarchical regression analyses were conducted (one with PWB as the outcome variable and one with life satisfaction as the outcome). Each set of predictors was entered as an individual level in the hierarchical regression. Table 2 presents the results of these analyses. As can be seen in Table 2, Hypothesis 1 was fully supported. Each predictor variable set predicted significant additive variance in each outcome variable after accounting for the preceding predictor variable sets in the model. It is also useful to note that the social resources variables predicted over twice as much additive variance in life satisfaction (∆R2 = .08, p < .001) compared to that of PWB (∆R2 = .03, p < .001). The model accounted for 36% of the variance in PWB and 41% of the variance in life satisfaction.

 

Table 2

 

Summary of Hierarchical Regression Analyses Predicting PWB and Life Satisfaction

Step and Variable

∆R2 ∆F β t rsp
Outcome variable: PWB
Step 1 – Internal resources .22 38.619***
Attachment anxiety -.14         -3.438**   -.07*
Attachment avoidance -.09         -2.308* -.03
Ego resilience  .40          9.685***       .23***
Step 2 – Emerging adulthood .09   8.259***
Experimentation/possibilities  .19          4.677***       .14***
Negativity/instability -.23         -6.177***      -.20***
Identity exploration  .06          1.403  .05
Feeling in between  .00          0.03 -.02
Step 3 – Social resources .03   1.681***
Social support  .19          4.679***       .16***
Facebook usage  .09          2.361*   .08*
Outcome variable: Life satisfaction
Step 1 – Internal resources .22 32.966***
Attachment anxiety -.12         -2.960** -.03
Attachment avoidance -.20         -5.185***    -.11**
Ego resilience  .36          8.711***       .17***
Step 2 – Emerging adulthood .09   8.131***
Experimentation/possibilities  .26          6.571***       .20***
Negativity/instability -.19         -5.139***      -.15***
Identity exploration  .01          0.304  .02
Feeling in between -.05         -1.273  -.07*
Step 3 – Social resources .08   4.872***
Social support  .31          8.138***       .27***
Facebook usage  .08          2.176*    .07*

Note. N = 538. Results control for the effects of gender. rsp = semipartial correlation. rsp is reported for the
last step in each model.
* p < .05, ** p < .01, *** p < .001.

 

Hypothesis 2 predicted that the emerging adulthood variables and Facebook usage would each predict significant individual variance in each outcome variable after accounting for the effects of all other predictor variables. To test this hypothesis, semipartial correlations (rsp) were examined for all variables at the last step of the hierarchical regression (i.e., the step in which all variables are entered into the model). Semipartial correlations examine the unique variance explained by a single predictor after accounting for the collective variance explained by all other predictors (Meyers et al., 2013). As can be seen in Table 2, significant semipartial correlations predicting PWB included the negativity/instability (rsp = -.20, p < .001), experimentation/possibilities (rsp = .14, p < .001), and Facebook usage (rsp = .08, p < .05) variables. Of all the predictors of PWB in the model, negativity/instability made the second largest individual contribution. Of the predictors of life satisfaction, significant semipartial correlations included experimentation/possibilities (rsp = .20, p < .001), negativity/instability (rsp = -.15, p < .001), feeling in between (rsp = -.07, p < .05), and Facebook usage (rsp = .07, p < .05). The experimentation/possibilities variable made the second largest individual contribution to life satisfaction. However, because identity exploration was not significant for either outcome variable, and feeling in between was not significant for life satisfaction, Hypothesis 2 was only partially supported. Collectively, the emerging adulthood and Facebook variables accounted for 7.4% of unique variance in PWB and 7.1% of unique variance in life satisfaction.

Discussion

The present findings yield several useful contributions. First, they bridge disparate threads of research by comparing the contributions of well-established mental health predictors with those of constructs unique to present-day college students, each of which contributed uniquely to college student mental health. Although many of the effects of the individual variables were small, the emerging adulthood and Facebook variables collectively explained roughly 7% of unique variance in the mental health variables over and above that explained by the more well-established constructs. As such, the findings are consistent with the assertion that constructs like attachment, ego resilience, and social support, while useful to conceptualizing college student mental health, may nevertheless be aided by also considering factors unique to 21st-century students.

The positive associations between Facebook usage and college student mental health are noteworthy, given the current disagreement regarding the impact of social media use. Contrary to concerns regarding social media overuse (e.g., Twenge, 2013), the present study found that Facebook usage positively predicted PWB and life satisfaction, albeit with a small effect. This was true even after controlling for other predictor variables, suggesting that Facebook provided a small but unique contribution to college student mental health. This finding supports the conclusions of Manago et al. (2012) that Facebook can fulfill certain social support needs for students. There may also be negative implications for societal reliance on social media use (e.g., Twenge, 2013), including its promotion of unhealthy comparison behaviors and cyberbullying. Nevertheless, the present findings and those of Manago et al. demonstrate the positive contributions of social media to college student mental health.

The significance of some of the emerging adulthood variables also warrants discussion. The degree to which participants identified with emerging adulthood being a period of experimentation and possibilities was positively associated with PWB and life satisfaction, while the degree to which they identified with emerging adulthood being a period of negativity and instability was negatively associated with PWB and life satisfaction. Moreover, identifying emerging adulthood as a time of feeling in between adolescence and adulthood was negatively associated with life satisfaction. Even after accounting for all other control and predictor variables, emerging adult instability was the second strongest predictor of PWB (after ego resilience), while emerging adult experimentation/possibilities was the second strongest predictor of life satisfaction (after social support). These findings add important context to prior empirical conclusions that emerging adulthood is associated with negative mental health (Baggio et al., 2015). That is, while each of the dimensions of emerging adulthood represents important developmental processes toward reaching adulthood (Arnett, 2004), only some of these dimensions (especially viewing emerging adulthood as a period of experimentation or instability) seem relevant to college student mental health. Additionally, feeling in between adolescence and adulthood was negatively associated with life satisfaction but unassociated with PWB. This finding underscores the complex contributions of emerging adulthood to college student mental health. Previous research has indicated that life satisfaction decreases during adolescence (Goldbeck et al., 2007). Accordingly, it is plausible that subjectively identifying the emerging adult years as feeling in between adolescence and adulthood results in life satisfaction trajectories that more closely mirror those of adolescence compared to emerging adults who feel less in between adolescence and adulthood. Although such conclusions require further validation, it nevertheless can help college counselors understand which factors of the emerging adult experience are relevant foci of clinical attention.

Implications for Counselors

The present results yield several useful insights that can aid mental health counselors who work with college-aged populations. Most prominently, counselors are encouraged to conceptualize their clients using a blend of foundational and contemporary models. Life for 21st-century college-aged individuals is unprecedentedly complex (Arnett, 2004; Kruisselbrink Flatt, 2013). It is important for college counselors to acknowledge this complexity, as doing so may represent an important form of cultural competence working with millennial generation and Generation Z individuals (Lane, 2015). Counselors are encouraged to utilize emerging adulthood theory when conceptualizing their clients, as this framework contains important departures from other identity development models. For example, counselors are likely to be more familiar with Erikson’s (1959/1994) framework than emerging adulthood theory. The former model suggests that identity development occurs during the teenage years, while the latter model asserts that identity development is a process that now extends well into the 20s (Arnett, 2004). Emerging adulthood theory also suggests that, as a result of this prolonged identity development process, traditional-aged college students are likely to temporarily exhibit heightened self-focus and idealistic thinking. Acknowledging these factors could facilitate a more empathic understanding of the behaviors that contribute to some counselors and scholars endorsing negative stereotypes against millennials and Generation Z individuals (Lane, 2015). Incorporating emerging adulthood theory could help college counselors be more mindful of the evolving nature of the transition to adulthood and its contributions to mental health.

The findings involving the social resources variables also have novel implications for counseling college students. Although social support has long been established as an important target for improving mental health, counselors are encouraged to acknowledge both the unprecedented complexity of emerging adult social support networks (Arnett, 2004) and also the ability of emerging adults to receive social support from face-to-face and electronic interactions (Manago et al., 2012). Accordingly, it is important to continue exploring the potential therapeutic applications of social media and other forms of technology. For example, an exciting direction in this regard is the growing use of informal support groups via social media (Manago et al., 2012), which exist for many counseling-relevant issues. Such groups provide a sense of community and help members remember that they are not alone in their struggles. Moreover, present mental health trajectories among college students have necessitated a shift in focus for many college counseling centers toward crisis intervention and outreach (Watkins et al., 2012). For many college counseling centers, social media remains an underutilized tool, despite the recent development of social media and text-based initiatives for each of these objectives (Evans et al., 2013). Such programs might be especially useful in today’s higher education climate in which symptom severity seems to be increasing while budgetary resources for college counseling centers are often stagnant or decreasing (American College Health Association, 2015; Watkins et al., 2012).

Limitations

Several limitations in the present study warrant consideration. First, the results relied on a convenience sample, and it is impossible to know whether there are group differences between the 15.4% of invited college students who participated compared to those who did not. Second, the findings are correlational in nature, and the directionality of the relationships cannot be assured. Third, although the sample was racially diverse, it was predominantly female. Fourth, it should be noted that the social media variable in this study consisted solely of Facebook usage; the findings may have been different had other prominent social media platforms been represented.

Implications for Future Research

Future research efforts should continue to explore the mental health implications of the study’s variables. First, it would be useful to confirm the findings with a more gender-representative sample. The model should also be explored with a longitudinal sample to determine mental health trajectories through various transitions common during the college experience. It would also be useful to explore potential mediating effects among the variables in the model, which could provide further empirical support for the theoretical sequencing of the variable sets. Other research efforts could further explore the therapeutic applications of social media. Such efforts could aid understanding of the evolving needs of college-aged populations.

Conclusion

The college years constitute considerable mental health risks that seem particularly pronounced for current generations of traditional-aged college students. The present findings suggest that traditional models of college student mental health can be aided by also incorporating generation-specific factors, including emerging adulthood identification and social media usage. Such generation-specific factors seem to predict unique variance in college student mental health characteristics, namely PWB and life satisfaction. The findings underscore the importance that counselors consider contemporary models, including emerging adulthood theory, when conceptualizing and treating traditional-aged college student clients.

 

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

 

References

 

American College Health Association. (2015). Spring 2015 reference group executive summary. https://www.achaorg/documents/ncha/NCHA-II_WEB_SPRING_2015_REFERENCE_GROUP_
EXECUTIVE_SUMMARY.pdf

Arnett, J. J. (2004). Emerging adulthood: The winding road from the late teens through the twenties. Oxford University Press.

Arnett, J. J. (2016). College students as emerging adults: The developmental implications of the college context. Emerging Adulthood, 4(3), 219–222. https://doi.org/10.1177/2167696815587422

Baggio, S., Iglesias, K., Studer, J., & Gmel, G. (2015). An 8-item short form of the Inventory of Dimensions of Emerging Adulthood (IDEA) among young Swiss men. Evaluation & the Health Professions, 38(2), 246–254. https://doi.org/10.1177/0163278714540681

Bech, P., Olsen, L. R., Kjoller, M., & Rasmussen, N. K. (2003). Measuring well-being rather than the absence of distress symptoms: A comparison of the SF-36 Mental Health subscale and the WHO-Five Well-Being Scale. International Journal of Methods in Psychiatric Research, 12(2), 85–91. https://doi.org/10.1002/mpr.145

Blazer, D., Hybels, C., & Hughes, D. C. (1990). Duke Social Support Index. Educational Testing Service.

Block, J. H., & Block, J. (1980). The role of ego-control and ego-resiliency in the organization of behavior. In W. A. Collins (Ed.), Minnesota symposia on child psychology (Vol. 13, pp. 39–101). Erlbaum.

Bowlby, J. (1997). Attachment and loss: Vol. 1. Attachment (Original work published 1969). Basic Books.

Brennan, K. A., Clark, C. L., & Shaver, P. R. (1998). Self-report measurement of adult attachment: An integrative overview. In J. A. Simpson & W. S. Rholes (Eds.), Attachment theory and close relationships (pp. 46–76). Guilford Press.

Diener, E., Emmons, R. A., Larsen, R. J., & Griffin, S. (1985). The Satisfaction With Life Scale. Journal of Personality Assessment, 49(1), 71–75.

Ellison, N. B., Steinfield, C., & Lampe, C. (2007). The benefits of Facebook “friends”: Social capital and college students’ use of online social network sites. Journal of Computer-Mediated Communication, 12(4), 1143–1168. https://doi.org/10.1111/j.1083-6101.2007.00367.x

Erikson, E. H. (1994). Identity and the life cycle (Original work published 1959). W. W. Norton.

Evans, W. P., Davidson, L., & Sicafuse, L. (2013). Someone to listen: Increasing youth help-seeking behavior through a text-based crisis line for youth. Journal of Community Psychology, 41(4), 471–487. https://doi.org/10.1002/jcop.21551

Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175–191.
https://doi.org/10.3758/BF03193146

Galambos, N. L., Barker, E. T., & Krahn, H. J. (2006). Depression, self-esteem, and anger in emerging adulthood: Seven-year trajectories. Developmental Psychology, 42(2), 350–365. https://doi.org/10.1037/0012-1649.42.2.350

Goldbeck, L., Schmitz, T. G., Besier, T., Herschbach, P., & Henrich, G. (2007). Life satisfaction decreases during adolescence. Quality of Life Research, 16(6), 969–979. https://doi.org/10.1007/s11136-007-9205-5

Hawley, L. D., Leibert, T. W., & Lane, J. A. (2014). The relationship between socioeconomic status and counseling outcomes. The Professional Counselor, 4(4), 390–403. https://doi.org/10.15241/ldh.4.4.390

Kruisselbrink Flatt, A. (2013). A suffering generation: Six factors contributing to the mental health crisis in North American higher education. College Quarterly, 16(1).

Lane, J. A. (2015). Counseling emerging adults in transition: Practical applications of attachment and social support research. The Professional Counselor, 5(1), 15–27. https://doi.org/10.15241/jal.5.1.15

Lane, J. A. (2016). Attachment, well-being, and college senior concerns about the transition out of college. Journal of College Counseling, 19(3), 231–245. https://doi.org/10.1002/jocc.12046

Lane, J. A., Leibert, T. W., & Goka-Dubose, E. (2017). The impact of life transition on emerging adult attachment, social support, and well-being: A multiple-group comparison. Journal of Counseling & Development, 95(4), 378–388. https://doi.org/10.1002/jcad.12153

Lent, R. W. (2004). Toward a unifying theoretical and practical perspective on well-being and psychosocial adjustment. Journal of Counseling Psychology, 51(4), 482–509. https://doi.org/10.1037/0022-0167.51.4.482

Manago, A. M., Taylor, T., & Greenfield, P. M. (2012). Me and my 400 friends: The anatomy of college students’ Facebook networks, their communication patterns, and well-being. Developmental Psychology, 48(2), 369–380. https://doi.org/10.1037/a0026338

Manfreda, K. L., Bosnjak, M., Berzelak, J., Haas, I., & Vehovar, V. (2008). Web surveys versus other survey modes: A meta-analysis comparing response rates. International Journal of Market Research, 50(1), 79–104. https://doi.org/10.1177/147078530805000107

McCay-Peet, L., & Quan-Haase, A. (2017). What is social media and what can social media research help us answer? In L. Sloan & A. Quan-Haase (Eds.), The SAGE handbook of social media research methods (pp. 13–26). SAGE.

Meyers, L. S., Gamst, G., & Guarino, A. J. (2013). Applied multivariate research: Design and interpretation (2nd ed.). SAGE.

Ortiz-Ospina, E. (2019). The rise of social media. Oxford University. https://ourworldindata.org/rise-of-social-media

Sarason, B. R., Pierce, G. R., Shearin, E. N., Sarason, I. G., Waltz, J. A., & Poppe, L. (1991). Perceived social support and working models of self and actual others. Journal of Personality and Social Psychology, 60(2), 273–287. https://doi.org/10.1037/0022-3514.60.2.273

Schnyders, C. M., & Lane, J. A. (2018). Gender, parent and peer relationships, and identification with emerging adulthood among college students. Journal of College Counseling, 21(3), 239–251. https://doi.org/10.1002/jocc.12106

Taylor, Z. E., Doane, L. D., & Eisenberg, N. (2014). Transitioning from high school to college: Relations of social support, ego-resiliency, and maladjustment during emerging adulthood. Emerging Adulthood, 2(2), 105–115. https://doi.org/10.1177/2167696813506885

Twenge, J. M. (2013). Does online social media lead to social connection or social disconnection? Journal of College and Character, 14(1), 11–20. https://doi.org/10.1515/jcc-2013-0003

Watkins, D. C., Hunt, J. B., & Eisenberg, D. (2012). Increased demand for mental health services on college campuses: Perspectives from administrators. Qualitative Social Work, 11(3), 319–337. https://doi.org/10.1177/1473325011401468

Wei, M., Russell, D. W., Mallinckrodt, B., & Vogel, D. L. (2007). The Experiences in Close Relationship Scale (ECR)-Short Form: Reliability, validity, and factor structure. Journal of Personality Assessment, 88(2), 187–204. https://doi.org/10.1080/00223890701268041

 

Joel A. Lane, PhD, NCC, LPC, is an associate professor and department chair at Portland State University. Correspondence may be addressed to Joel Lane, 250G Fourth Avenue Building, 1900 SW 4th Ave., Portland, OR 97201, lanejoel@pdx.edu.

Serving Students in Foster Care: Implications and Interventions for School Counselors

Hannah Brinser, Addy Wissel

 

Students in foster care frequently experience barriers that influence their personal, social, and academic success. These challenges may include trauma, abuse, neglect, and loss—all of which influence a student’s ability to be successful in school. Combined with these experiences, students in foster care lack the same access to resources and support as their peers. To this end, school counselors have the opportunity to utilize their unique position within the school community to effectively serve and address the complex needs of students in foster care. This paper addresses the current research, presenting problems, implications, and interventions school counselors can utilize when working with this population.

Keywords: students, foster care, school counseling, support, interventions

 

In 2017, there were a total of 442,995 children and youth in the foster care system (U.S. Department of Health and Human Services, 2018). Given the number of these students in schools and communities, school counselors have the opportunity to utilize their position within the school system to identify, respond to, and advocate for the needs of students in foster care to ensure equity and access in all areas. Although all students need positive relationships and stability to be successful, students in foster care often lack the same access to support, resources, and opportunities as their peers (McKellar & Cowen, 2011; Palmieri & La Salle, 2017). These barriers and challenges contribute to gaps in achievement, relationships, and skills for these students (Palmieri & La Salle, 2017). Compared to their peers, students in foster care are more likely to be absent from school, repeat a grade, and change schools (Cutuli et al., 2013; Palmieri & La Salle, 2017; Unrau et al., 2012), which ultimately impacts their ability to establish and maintain relationships. Additionally, students in foster care are twice as likely to receive out-of-school suspensions, over three times as likely to receive special education services, and over 20% less likely to graduate from high school (National Working Group for Foster Care and Education [NWGFCE], 2018).

When it comes to higher education, students in foster care are less likely to enroll in college preparatory classes, attend college, and obtain a 4-year degree when compared to their peers (Kirk et al., 2013; Unrau et al., 2012). Research suggests that as little as 3%–10.8% of youth previously in foster care attain a 4-year degree, compared to the national college completion rate of 32.5% (NWGFCE, 2018). However, it is important for school counselors to realize that between 70%–84% of students in foster care desire going to college (Courtney et al., 2010; NWGFCE, 2018). Although students in foster care feel motivated to attend and complete college, academic achievement can easily become another barrier. On average, students in foster care receive both lower ACT scores and high school GPAs and perform lower on standardized tests compared to their peers—all of which influence one’s admission to college (O’Malley et al., 2015; Unrau et al., 2012).

Unfortunately, it is also common for students in foster care to experience other challenges that influence their success in school, such as trauma. Trauma can include abuse; neglect; and the loss of family members, friends, and communities (Scherr, 2014). Without adequate support, trauma can impact a student’s executive functioning and memory, ultimately affecting their ability to learn (Avery & Freundlich, 2009). Additionally, separation from family members, disrupted relationships, and frequent transitions lead to an increased risk for difficulties in expressing and regulating emotions, tolerating ambiguity, and problem-solving (O’Malley et al., 2015; Unrau et al., 2012). These interrelated and complex factors contribute to the achievement gap experienced by students in foster care as evidenced by lower academic achievement and less engagement in school (Pecora et al., 2006; Unrau et al., 2012).

Importance of Serving This Population

 

When considering interventions to support students in foster care, it is important to explore what they believe will be helpful for their growth and success. It is likely that the majority of students in foster care already feel a lack of control over what occurs in their lives (Scherr, 2014). Therefore, this is an opportunity to encourage student involvement while increasing student self-efficacy. Clemens et al. (2017) found that students in foster care emphasize the importance of having opportunities to connect with others in similar situations, learning practical skills, and implementing different strategies to better their lives. To provide a sense of normalcy and belonging, school counselors can advocate for interventions that promote connectedness and engagement with other students (Unrau et al., 2012).

Removing barriers, improving access to services, maintaining enrollment, improving attendance, and facilitating academic progress is critical in promoting success for students in foster care (Gilligan, 2007). Therefore, school counselors should be aware of the barriers related to access that exist for students in foster care and should be intentional in taking steps to remove any inequities. Working proactively and using a strengths-based approach that acknowledges the skills, strengths, and resiliency of students are ways in which school counselors can effectively meet the needs of students in foster care (Gilligan, 2007; Scherr, 2014). To illustrate, a strengths-based approach can be utilized with students who have anxious attachment patterns by acknowledging their ability to care for others, rather than focusing on the negative aspects of their attachment behaviors (e.g., being too “needy”). Although it can be easy to focus on the behaviors and disruptions that occur, school counselors have the opportunity to instead focus on these students’ accomplishments, strengths, and dreams. Ultimately, it is evident that students in foster care face many challenges that influence their ability to be successful. In an effort to address this need, the following section outlines interventions for school counselors to use when working with students in foster care.

Interventions

School Climate
Positive school relationships are an essential part of school climate and can serve as a protective factor for students experiencing adversity (Furlong et al., 2011; O’Malley et al., 2015). Therefore, focusing on school climate may be an effective approach in supporting students in foster care, as positive school relationships can also help close achievement gaps between these students and their peers (Clemens et al., 2017). For example, positive school climate decreases rates of disruptive behaviors, truancy, fights, and suspensions at school (Hopson & Lee, 2011). In addition, Voight et al. (2013) found that students’ positive school climate perceptions also contributed to academic achievement as indicated by state standardized test scores. School counselors can enhance school climate by allowing student voices, utilizing empowerment strategies, implementing evidence-based programs, providing adult mentoring (O’Malley et al., 2015), and working to create a positive peer culture (Bergin & Bergin, 2009).

School Culture
It is particularly important to pay attention to school culture, as these shared norms, beliefs, and behaviors affect perceptions of school climate (MacNeil et al., 2009). To create a positive school culture, Ziomek-Daigle et al. (2016) recommended that school counselors implement interventions using a multi-tiered system of supports. For example, providing classroom lessons on topics such as kindness, empathy, and acceptance are Tier 1 interventions that work to cultivate a positive school culture (Bergin & Bergin, 2009; Ziomek-Daigle et al., 2016). Additionally, school culture can be influenced by creating shared values and expectations for students throughout the school community (MacNeil et al., 2009). For example, school counselors can utilize empowerment strategies when teaching students in foster care to advocate for themselves and find autonomy in meeting their needs. The school counselor might say, “Last week, you worked so hard at learning to use ‘I statements’ when expressing your needs and feelings to others! In class, I even saw that you raised your hand to ask for a break when you started to get overwhelmed in math. How might you use similar skills to advocate for yourself when you get frustrated in social studies?” In this way, the school counselor is improving school culture by creating a shared expectation among students, teachers, and staff.

Educational Experiences
Moreover, school counselors can enhance school climate by facilitating enriching educational experiences that contribute to academic success (Gilligan, 2007). To ensure that students in the foster care system receive the same educational experiences as their peers, school counselors can screen, monitor, plan, communicate, and collaborate with other stakeholders (e.g., teachers, administration, staff, and foster families) to ensure equity and access for students in foster care (Palmieri & La Salle, 2017). Educating stakeholders about working with students in foster care can encourage inclusive assignments, promote an understanding of potential responses and reactions from students, and decrease negative behavioral perceptions (McKellar & Cowen, 2011). Additionally, including students in decisions about their education, where they attend school, and the support they receive can increase their self-efficacy, goal development, and self-advocacy skills (Palmieri & La Salle, 2017). This intentionality can also help them feel welcome, respected, and important—all of which increase their school connection.

Collaborating With Stakeholders
Planning
     School counselors should plan to accommodate and work with students who may enter school in the middle of the year, as 34% of students in foster care experience five or more school changes by the time they reach the age of 18 (NWGFCE, 2018). When these students arrive at school, it is important that school counselors welcome them, explain classroom and school procedures, show them around the school, and facilitate connections with other students (Palmieri & La Salle, 2017). From the beginning, school counselors can prioritize involving the foster family by calling to welcome them, answering any questions they have, providing them with helpful information (e.g., teacher contact information), and following up with them after a few weeks. For example, packets can be sent home with students so foster families have access to any relevant documents or previous newsletters containing helpful information (McKellar & Cowen, 2011). Additionally, it may be beneficial for school counselors to invite the foster family to meet with them in person to create a stronger foster family and school partnership. Furthermore, incomplete student records can have a significant effect on academic services for students in foster care. Therefore, school counselors should work diligently with other school districts to retrieve and maintain these records (McKellar & Cowen, 2011).

Training
Along with planning, school counselors can provide all stakeholders with evidence-based information to effectively serve and address the needs of students in foster care (Kerr & Cossar, 2014). With this purpose in mind, school counselors can provide training to stakeholders on topics such as reflective listening, creating secure attachments, recognizing and responding to feelings and behaviors, and setting limits and boundaries (Kerr & Cossar, 2014). Informed stakeholders can more effectively support and respond to the unique needs of students in foster care, and in turn, students may be more successful in managing their emotions and behaviors (Palmieri & La Salle, 2017). This awareness can also strengthen relationships that promote school success (Kerr & Cossar, 2014). Additionally, school counselors can be proactive in collaborating with stakeholders to create structured and supportive classroom environments where students in foster care feel safe while learning. For example, working with teachers to modify assignments that have the potential to be triggering (e.g., family-based assignments) is essential in promoting student–teacher relationships and academic achievement (C. Mitchell, 2010; Palmieri & La Salle, 2017).

Inclusion
     Students in foster care often experience triggers at school, whether it is from an assignment (e.g., family-based assignments), a topic discussed in class, or a community event that seems to be exclusively for biological parents (West et al., 2014). When these experiences occur, students in foster care do not always have the ability to self-regulate and utilize healthy coping skills (West et al., 2014). For this reason, it is essential to not only advocate for inclusive assignments and events but to also help students effectively manage their triggers so they can be academically and relationally successful. Additionally, it may be helpful to provide stakeholders with information about why certain activities lack inclusivity for students in foster care and offer possible alternatives or modifications for these experiences. To illustrate, events such as “Muffins with Moms” and “Donuts with Dads” can be altered for inclusivity by expanding the population to include anyone in the student’s support system (e.g., “Floats with Friends” or “Popcorn with Important People”).

Additionally, an assignment about creating a family tree could be modified for inclusivity by focusing on the diversity of family structures. C. Mitchell (2010) offers the alternative of creating “The Rooted Family Tree,” in which the roots represent one’s birth family, the student as the trunk, and the foster or adoptive family filling in the branches. Similarly, “The Family Houses Diagram” utilizes houses instead of trees to allow for multiple places of living and the option to form a connection between birth, foster, or other family types (C. Mitchell, 2010). Another common assignment given in schools is to bring a baby picture to share with the class. This lacks inclusivity for students in foster care, as they might not have these pictures or there may be difficult memories attached to them. Additionally, this puts the student in the painful position of having to explain why they do not have these pictures (C. Mitchell, 2010). As a result, C. Mitchell (2010) recommends framing the assignment as a choice: Bring a picture of yourself as a baby or at a younger age, on a vacation or holiday, or engaging in any activity that you enjoy.

Relationships
Knowing how to cultivate secure attachments with students in foster care is especially relevant for stakeholders, as positive student–adult relationships can influence other relationships in the student’s life by altering their internal working model (Bergin & Bergin, 2009; Sabol & Pianta, 2012). Although it can be difficult to create and maintain secure relationships with students who experience insecure attachment (Bergin & Bergin, 2009), stakeholders have the opportunity to fill in attachment gaps that may exist for students in foster care. Secure attachment is related to higher grades and standardized test scores, increased emotion regulation, and higher self-efficacy (Bergin & Bergin, 2009; Golding et al., 2013). Moreover, students with insecure attachment tend to show less curiosity (Granot & Mayseless, 2001), have poorer quality friendships, and exhibit behavior problems (Bergin & Bergin, 2009; Golding et al., 2013).

Importantly, attachment to teachers, rather than just biological parents, is linked to school success (O’Connor & McCartney, 2007; Sabol & Pianta, 2012). When students have healthy relationships with their teachers and perceive them as supportive, they show greater interest and engagement in school, which leads to improvements in academic achievement (Bergin & Bergin, 2009; Golding et al., 2013). Additionally, students who experience insecure attachment crave positive, warm, and trusting relationships but often lack the skills to create them. For this reason, stakeholders can help nurture secure relationships by being genuine, maintaining high expectations, and providing as much choice and autonomy as possible (Bergin & Bergin, 2009). Furthermore, noticing when these students are not at school, or when they return after an absence, can help them know they are valued and cared for.

To advocate, school counselors can help stakeholders understand why students with insecure attachment are behaving and reacting in certain ways, while also helping staff to respond in ways that disconfirm students’ insecure working models (Bergin & Bergin, 2009). In this way, staff can show that students’ particular beliefs about relationships with others may not always be true. To illustrate, not asking for help in the classroom, ignoring the teacher, or denying the need for assistance could be a manifestation of an insecure avoidant attachment style (Golding et al., 2013). This student does not want to become close or show vulnerability, as they fear that the teacher will reject or separate from them (e.g., their internal working model). For these students, it can be easier to not ask for help or engage in classroom projects at all than risk the hurt of rejection (Golding et al., 2013). A teacher who misunderstands this might believe they are unable to adequately support the student. As a result, they may stop trying to help, which confirms the student’s internal working model of fear and rejection. Instead, the teacher can disconfirm this student’s internal working model by providing reassurance of their consistency and availability (Golding et al., 2013). For example, the teacher conveying that they want to help, while also asking how they can help, offers healthy choice and autonomy. Encouraging small changes in how stakeholders respond to students in foster care provides a space for positive and secure relationships to develop.

Skill Development and Addressing Unique Experiences
Behavior Management, Emotion Regulation, and Social Skills
     Difficulties in behavior management, emotion regulation, and social skills are common among students in the foster care system, as they lack control over many events that occur in their lives (Octoman et al., 2014; Scherr, 2014). These students’ unique and complex experiences can impact their ability to appropriately manage their emotions, behaviors, and interactions with others. Unfortunately, these extreme emotions and behaviors often result in several different placements, the loss of relationships, and the loss of school and community connections (Octoman et al., 2014).

Given this information, school counselors can contribute to student success by collaborating with stakeholders to communicate appropriate behavior, identify boundaries, and explicitly state expectations. Providing behavioral support, management, and individual attention can help students engage in positive behaviors that facilitate their success at school and in the classroom (Palmieri & La Salle, 2017). Additionally, working with students to identify and manage emotions decreases externalizing behaviors, reduces stress levels, and improves relationships. Likewise, providing education about control, acceptance, coping skills, and distress tolerance are applicable emotion regulation interventions to utilize with students in foster care (Benzies & Mychasiuk, 2009). Groups and interventions on topics such as social skills, problem-solving, making and keeping friends, and appropriate behaviors can help students develop healthy interpersonal relationships (Scherr, 2014; Zins & Elias, 2007).

Grief and Loss
Additionally, it is crucial that school counselors intentionally address the unique and complex experiences of students in foster care. For example, these students often experience non-death losses that go unacknowledged, including the loss of parents, siblings, friends, and communities (M. B. Mitchell, 2018). These losses may involve a lack of clarity and create confusion about a loved one’s physical or psychological presence, commonly referred to as ambiguous loss (Boss, 1999; Lee & Whiting, 2007). To illustrate, being separated from one’s family and placed into foster care can generate grief and loss reactions, including confusion, isolation, distress, uncertainty, helplessness, denial, extreme behaviors, and guilt (Lee & Whiting, 2007; M. B. Mitchell & Kuczynski, 2010). Disenfranchised grief occurs when others disregard and do not acknowledge a loss (Doka, 1989; M. B. Mitchell, 2018). Unfortunately, it is common for the child welfare system and society to ignore experiences of grief and loss in foster care (M. B. Mitchell, 2018; M. B. Mitchell & Kuczynski, 2010).

In an effort to address this, school counselors can begin by identifying, acknowledging, and validating losses that are not caused by death but produce many similar grief responses (M. B. Mitchell, 2016, 2018). Additionally, school counselors can educate stakeholders about ambiguous loss and disenfranchised grief, as it is important for the entire school community to have an understanding about manifestations of grief and loss when working with these students (e.g., internalizing and externalizing). In general, school counselors can advocate for students in foster care by validating their experiences, equipping them with education and resources, helping others understand why their experiences embody grief and loss, and acknowledging the inherent confusion involved in their unique situations (Lee & Whiting, 2007).

Accessing School and Community Resources
School Engagement
     Students involved in their school community through extracurricular activities, leadership, and positions of responsibility often experience more motivation and engagement in learning (Gilligan, 2007). Additionally, such engagement is beneficial in creating a sense of normalcy, belonging, and community with other students. Unfortunately, these opportunities can seem limited to students in the foster care system because of cost, timing, and transportation barriers (Palmieri & La Salle, 2017). Therefore, it is critical that school counselors collaborate, advocate, and act to remove these barriers, as engagement in the school community can result in academic, social, and behavioral improvements (Scherr, 2014). School counselors can facilitate this involvement and engagement in the school community by collaborating with other stakeholders to provide opportunities. For example, encouraging and assisting students in foster care to navigate and obtain leadership positions (e.g., student government) will not only improve their engagement in school, but also increase their self-efficacy and sense of belonging within the school community. Additionally, school counselors can collaborate with other professionals (e.g., social workers, school psychologists, and school nurses) to identify and address different areas of support, resources, and opportunities for these students.

Group Counseling
With a national student–school counselor ratio of 455:1 (American School Counselor Association, 2019), group counseling is a promising approach to help school counselors meet the complex needs of students who are in foster care. Additionally, this is an effective way to encourage involvement and connectedness with students who have similar backgrounds, while providing these students with the skills that they need to be successful (Palmieri & La Salle, 2017). Involvement in group counseling can help create a sense of normalcy, belonging, and community with other students (Alvord & Grados, 2005) and can also result in academic, social, and behavioral improvements (Scherr, 2014).

Hambrick et al. (2016) found that children in foster care experienced improvements in behavior, academics, quality of life, attachment, placement stability, and emotion regulation following their participation in group-based interventions. Although participating in a small group with other students in the foster care system may provide the opportunity to feel understood and less alone, students may also benefit from engaging in group activities with typical peers. For example, students in foster care might participate in a “lunch bunch” group where they eat in community with the school counselor and other like-age peers. In these groups, students can play, learn from watching the interactions of peers, and develop the skills necessary for initiating and maintaining positive peer relationships.

Utilizing a reality therapy approach for group counseling seems particularly beneficial, as it addresses choice, control, and healthy ways of getting one’s needs met—all common issues students in foster care may struggle with (Benzies & Mychasiuk, 2009; Cameron, 2013; Kress et al., 2019). These components are essential in empowering students to choose how they respond to and face the challenges in their lives (Benzies & Mychasiuk, 2009). In this approach, school counselors can assume the roles of teacher, advocate, and encourager by educating about responsibility, choices, and the importance of meaningful relationships (Kress et al., 2019). Utilizing the WDEP system (i.e., wants, doing, evaluation, and planning) to explore questions, including “What do you want?”, “What are you doing?”, and “Is it working?”, helps students assess if their current behaviors are getting them what they desire, and if they are not, how they can change in healthy ways (Wubbolding, 2011).

Because behavior is intentional, it is beneficial to look at each student’s behavior as an attempt to satisfy their needs (Glasser, 1984, 2000). Additionally, focusing on the here and now is helpful in guiding and educating students about effective and appropriate ways to get their needs met by others (Glasser, 1992, 2000). As many students in foster care have not always had their needs met in the past, they must learn to have their needs met in healthy and effective ways (Octoman et al., 2014). For example, a student who is grabbing and touching other students might be trying to get their need of love and belonging met. In this situation, it would be a helpful learning experience to guide this student to meet this need in a different way, such as asking the peer permission for a hug or setting aside time to spend with them later (Octoman et al., 2014).

When using this approach, school counselors can reframe behavior to emphasize student strengths, identify and celebrate students’ acceptance of choice and responsibility, create anticipation for change, and communicate hope about success (Kress et al., 2019). School counselors can also prioritize rapport building; creating safety through rules, goals, and expectations; and helping students realize that they are not alone in their experiences (Alvord & Grados, 2005; Gladding, 2016; Kress et al., 2019). Other small groups that address issues such as social skills, making and keeping friends, and college and career exploration may also be helpful for students in foster care.

Mentorship Programs
Students in the foster care system experience many transitions and losses, which can result in disruptions to the adult and peer relationships that support educational success. In this way, mentorship programs work to reduce risk and provide protective support to students in foster care (Scherr, 2014). These students value having a mentor who provides support and encouragement on topics related to academics, college, and life (Clemens et al., 2017; Dworsky & Pérez , 2010) and benefit from having a consistent, trustworthy, and non-familial adult in their lives (Benzies & Mychasiuk, 2009). Mentorship programs contribute to fewer behavior referrals, less school mobility, and improved graduation rates (Salazar et al., 2016). Additionally, the accountability of mentorship can motivate students to improve their attendance, achievement, and engagement in school. Given this information, facilitating connectedness and mentorship for these students is crucial in providing them with the support, consistency, and encouragement they need to accomplish their goals.

The Check and Connect Model is evidence-based and targets students who show warning signs of disengaging from school such as poor attendance, behavioral issues, and low grades (Tilbury et al., 2014), all of which are particularly relevant for students in foster care. Potential mentors can be natural (e.g., someone already present and supportive in the student’s life) or someone from the community interested in volunteering (Salazar et al., 2016). Utilizing natural mentors, if available, is beneficial in acknowledging the natural supports that already exist in students’ lives. For example, if a student already has a trusting relationship with a staff member, it is important to utilize this connection to maintain stability. However, if a student is unable to identify any natural mentors, working with volunteers in the community is also an excellent option. Both are impactful in different ways, and the quality of the connection is what is really crucial (Salazar et al., 2016).

It is essential that mentors are consistent, empathetic, authentic, and committed to supporting students in foster care. Mentors not only serve as a relational connection for these students but also help youth expand their social support networks, set goals, explore postsecondary options, and increase involvement in the school community (Salazar et al., 2016). School counselors can work with mentors to monitor student performance variables, such as absences, behavioral referrals, and grades, while helping students solve problems, identify skills, and reach their goals (University of Minnesota, 2019). Mentorship programs should be flexible and tailored to the needs of each student and their mentor, as some pairs might benefit from more or less time to connect (Salazar et al., 2016). Ultimately, these programs can be helpful in providing students in foster care with the connection and support they need to be successful, while also contributing to the development of other secure relationships in their lives (Palmieri & La Salle, 2017).

Community Partnerships
     For students in foster care, it is essential that support extends beyond the school community. To do this, school counselors can establish relationships and collaborate with the student, foster family, school, and foster care system (Palmieri & La Salle, 2017). These home–school partnerships are critical in meeting the needs of students in foster care. Additionally, foster families feel more supported when they are involved and their input is valued (Palmieri & La Salle, 2017). Utilizing and forming plans around academic and behavioral expectations, attendance, flexibility with requirements, and communication with stakeholders can be helpful in promoting success (McKellar & Cowen, 2011). Furthermore, tangible and emotional support can act as protective factors and meet the needs of students through the provision of goods and services (Piel et al., 2017). For example, school counselors can create or utilize community-based food and nutrition programs to ensure that basic needs are being met.

Mental Health Services
Equally important, students in foster care often experience difficulties that affect their mental health. Evidence-based treatments such as trauma-focused cognitive behavior therapy (TF-CBT), behavior therapy, cognitive behavior therapy (CBT), and parent–child interaction therapy can be adapted for the school setting (Landsverk et al., 2009). These models of counseling are helpful in addressing symptoms, while also promoting healthy behavior and functioning. Combined with this, school counselors can also provide outpatient information to foster families and case workers about local resources and services available to students in foster care. In these cases, it is helpful to collaborate with the designated outpatient counselor to provide the most effective support and generalize learned skills across settings (Landsverk et al., 2009).

Conclusion

Students in foster care experience a number of barriers and challenges that influence their success in school, both academically and socially, as well as in adulthood. In addition, students in foster care lack the same access to resources and support as their peers, which contributes to gaps in academic achievement, relational success, and overall well-being. By enhancing school climate, planning, providing training to stakeholders, and promoting positive educational experiences, students in foster care can receive the foundational support they need to begin learning. Additionally, by utilizing group counseling, implementing mentorship programs, targeting specific behavior, addressing experiences of grief and loss, and accessing community resources, students in foster care can gain the skills they need to be successful in all areas. Despite the many challenges students in foster care face, school counselors have the opportunity to utilize their unique position in their schools and communities to advocate for these students, reach them through evidence-based interventions, remove barriers to learning, and ultimately equip them with the tools and skills they need to experience greater success.

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

 

References

Alvord, M. K., & Grados, J. J. (2005). Enhancing resilience in children: A proactive approach. Professional Psychology: Research and Practice, 36(3), 238–245. https://doi.org/10.1037/0735-7028.36.3.238

American School Counselor Association. (2019). State-by-state student-to-counselor ratio report: 10-year trends. https://www.schoolcounselor.org/asca/media/asca/Publications/ratioreport.pdf

Avery, R. J., & Freundlich, M. (2009). You’re all grown up now: Termination of foster care support at age 18. Journal of Adolescence, 32(2), 247–257. https://doi.org/10.1016/j.adolescence.2008.03.009

Benzies, K., & Mychasiuk, R. (2009). Fostering family resiliency: A review of the key protective factors. Child & Family Social Work, 14(1), 103–114. https://doi.org/10.1111/j.1365-2206.2008.00586.x

Bergin, C., & Bergin, D. (2009). Attachment in the classroom. Educational Psychology Review, 21(2), 141–170. https://doi.org/10.1007/s10648-009-9104-0

Boss, P. (1999). Ambiguous loss: Learning to live with unresolved grief. Harvard University Press.

Cameron, A. (2013). Choice theory and reality therapy applied to group work and group therapy. International Journal of Choice Theory and Reality Therapy, 32(2), 25–35.

Clemens, E. V., Helm, H. M., Myers, K., Thomas, C., & Tis, M. (2017). The voices of youth formerly in foster care: Perspectives on educational attainment gaps. Children and Youth Services Review, 79, 65–77. https://doi.org/10.1016/j.childyouth.2017.06.003

Courtney, M. E., Dworsky, A., Lee, J. S., & Raap, M. (2010). Midwest evaluation of the adult functioning of former foster youth: Outcomes at ages 23 and 24. Chapin Hall at the University of Chicago. https://rhyclearinghouse.acf.hhs.gov/sites/default/files/docs/18690-Midwest_Evaluation-Outcomes_at_Ages_23_and_24.pdf

Cutuli, J. J., Desjardins, C. D., Herbers, J. E., Long, J. D., Heistad, D., Chan, C.-K., Hinz, E., & Masten, A. S. (2013). Academic achievement trajectories of homeless and highly mobile students: Resilience in the context of chronic and acute risk. Child Development, 84(3), 841–857. https://doi.org/10.1111/cdev.12013

Doka, K. J. (Ed.). (1989). Disenfranchised grief: Recognizing hidden sorrow. Lexington Books.

Dworsky, A., & Pérez, A. (2010). Helping former foster youth graduate from college through campus support programs. Children and Youth Services Review, 32(2), 255–263. https://doi.org/10.1016/j.childyouth.2009.09.004

Furlong, M., Sharkey, J., Quirk, M., & Dowdy, E. (2011). Exploring the protective and promotive effects of school connectedness on the relation between psychological health risk and problem behaviors/experiences. Journal of Educational and Developmental Psychology, 1(1), 18–34. https://doi.org/10.5539/jedp.v1n1p18

Gilligan, R. (2007). Adversity, resilience and the educational progress of young people in public care. Emotional and Behavioural Difficulties, 12(2), 135–145. https://doi.org/10.1080/13632750701315631

Gladding, S. T. (2016). Groups: A counseling specialty (7th ed.). Pearson.

Glasser, W. (1984). Take effective control of your life. Harper & Row.

Glasser, W. (1992). The quality school: Managing students without coercion (2nd ed.). Harper Perennial.

Glasser, W. (2000). Counseling with choice theory: The new reality therapy. HarperCollins.

Golding, K. S., Fain, J., Frost, A., Mills, C., Worrall, H., Roberts, N., Durrant, E., & Templeton, S. (2013). Observing children with attachment difficulties in school: A tool for identifying and supporting emotional and social difficulties in children aged 5–11. Jessica Kingsley.

Granot, D., & Mayseless, O. (2001). Attachment security and adjustment to school in middle childhood. International Journal of Behavioral Development, 25(6), 530–541. https://doi.org/10.1080/01650250042000366

Hambrick, E. P., Oppenheim-Weller, S., N’zi, A. M., & Taussig, H. N. (2016). Mental health interventions for children in foster care: A systematic review. Children and Youth Services Review, 70, 65–77. https://doi.org/10.1016/j.childyouth.2016.09.002

Hopson, L. M., & Lee, E. (2011). Mitigating the effect of family poverty on academic and behavioral outcomes: The role of school climate in middle and high school. Children and Youth Services Review, 33(11), 2221–2229. https://doi.org/10.1016/j.childyouth.2011.07.006

Kerr, L., & Cossar, J. (2014). Attachment interventions with foster and adoptive parents: A systematic review. Child Abuse Review, 23(6), 426–439. https://doi.org/10.1002/car.2313

Kirk, C. M., Lewis, R. K., Nilsen, C., & Colvin, D. Q. (2013). Foster care and college: The educational aspirations and expectations of youth in the foster care system. Youth & Society, 45(3), 307–323.
https://doi.org/10.1177/0044118X11417734

Kress, V. E., Paylo, M. J., & Stargell, N. A. (2019). Counseling children and adolescents. Pearson.

Landsverk, J. A., Burns, B. J., Stambaugh, L. F., & Reutz, J. A. R. (2009). Psychosocial interventions for children and adolescents in foster care: Review of research literature. Child Welfare: Journal of Policy, Practice, and Program, 88(1), 49–69.

Lee, R. E., & Whiting, J. B. (2007). Foster children’s expressions of ambiguous loss. The American Journal of Family Therapy, 35(5), 417–428. https://doi.org/10.1080/01926180601057499

MacNeil, A. J., Prater, D. L., & Busch, S. (2009). The effects of school culture and climate on student
achievement. International Journal of Leadership in Education, 12(1), 73–84.
https://doi.org/10.1080/13603120701576241

McKellar, N., & Cowen, K. C. (2011). Supporting students in foster care. Principal Leadership, 12(1), 12–16.

Mitchell, C. (2010). Back to school: A guide to making schools and school assignments more adoption-friendly. Adoption Advocate, 27, 1–9. https://www.adoptioncouncil.org/images/stories/NCFA_ADOPTION_ADVOCATE_NO27.
pdf

Mitchell, M. B. (2016). The family dance: Ambiguous loss, meaning making, and the psychological family in foster care. Journal of Family Theory & Review, 8(3), 360–372. https://doi.org/10.1111/jftr.12151

Mitchell, M. B. (2018). “No one acknowledged my loss and hurt”: Non-death loss, grief, and trauma in foster care. Child and Adolescent Social Work Journal, 35, 1–9. https://doi.org/10.1007/s10560-017-0502-8

Mitchell, M. B., & Kuczynski, L. (2010). Does anyone know what is going on? Examining children’s lived experience of the transition into foster care. Children and Youth Services Review, 32(3), 437–444. https://doi.org/10.1016/j.childyouth.2009.10.023

National Working Group for Foster Care and Education. (2018). Fostering success in education: National fact sheet on the educational outcomes of children in foster care. http://www.fostercareandeducation.org/DesktopModules/Bring2mind/DMX/Download.aspx?portalid=0&EntryId=2100&Command=Core_Download

O’Connor, E., & McCartney, K. (2007). Examining teacher–child relationships and achievement as part of an ecological model of development. American Educational Research Journal, 44(2), 340–369. https://doi.org/10.3102/0002831207302172

Octoman, O., McLean, S., & Sleep, J. (2014). Children in foster care: What behaviours do carers find challenging? Clinical Psychologist, 18(1), 10–20. https://doi.org/10.1111/cp.12022

O’Malley, M., Voight, A., Renshaw, T. L., & Eklund, K. (2015). School climate, family structure, and academic achievement: A study of moderation effects. School Psychology Quarterly, 30(1), 142–157. https://doi.org/10.1037/spq0000076

Palmieri, L. E., & La Salle, T. P. (2017). Supporting students in foster care. Psychology in the Schools, 54(2), 117–126. https://doi.org/10.1002/pits.21990

Pecora, P. J., Williams, J., Kessler, R. C., Hiripi, E., O’Brien, K., Emerson, J., Herrick, M. A., & Torres, D. (2006). Assessing the educational achievements of adults who were formerly placed in family foster care. Child & Family Social Work, 11(3), 220–231. https://doi.org/10.1111/j.1365-2206.2006.00429.x

Piel, M. H., Geiger, J. M., Julien-Chinn, F. J., & Lietz, C. A. (2017). An ecological systems approach to understanding social support in foster family resilience. Child & Family Social Work, 22(2), 1034–1043. https://doi.org/10.1111/cfs.12323

Sabol, T. J., & Pianta, R. C. (2012). Recent trends in research on teacher–child relationships. Attachment & Human Development, 14(3), 213–231. https://doi.org/10.1080/14616734.2012.672262

Salazar, A. M., Roe, S. S., Ullrich, J. S., & Haggerty, K. P. (2016). Professional and youth perspectives on higher education-focused interventions for youth transitioning from foster care. Children and Youth Services Review, 64, 23–34. https://doi.org/10.1016/j.childyouth.2016.02.027

Scherr, T. G. (2014). Best practices in working with children living in foster care. In P. L. Harrison & A. Thomas (Eds.), Best practices in school psychology: Foundations (pp. 169–179). NASP Publications.

Tilbury, C., Creed, P., Buys, N., Osmond, J., & Crawford, M. (2014). Making a connection: School engagement of young people in care. Child & Family Social Work, 19(4), 455–466. https://doi.org/10.1111/cfs.12045

University of Minnesota. (2019, December 26). Check and connect student engagement intervention. Institute on Community Integration. http://checkandconnect.umn.edu/

Unrau, Y. A., Font, S. A., & Rawls, G. (2012). Readiness for college engagement among students who have aged out of foster care. Children and Youth Services Review, 34(1), 76–83.
https://doi.org/10.1016/j.childyouth.2011.09.002

U.S. Department of Health and Human Services. (2018). The AFCARS report: Preliminary FY 2017 estimates as of August 10, 2018 – No. 25. Administration for Children and Families, Administration on Children, Youth and Families, Children’s Bureau. https://www.acf.hhs.gov/sites/default/files/cb/afcarsreport25.pdf

Voight, A., Austin, G., & Hanson, T. (2013). A climate for academic success: How school climate distinguishes schools that are beating the achievement odds (Report Summary). WestEd.

West, S. D., Day, A. G., Somers, C. L., & Baroni, B. A. (2014). Student perspectives on how trauma experiences manifest in the classroom: Engaging court-involved youth in the development of a trauma-informed teaching curriculum. Children and Youth Services Review, 38, 58–65.
https://doi.org/10.1016/j.childyouth.2014.01.013

Wubbolding, R. E. (2011). Reality therapy: Theories of psychotherapy series. American Psychological Association.

Zins, J. E., & Elias, M. J. (2007). Social and emotional learning: Promoting the development of all students. Journal of Educational and Psychological Consultation, 17(2-3), 233–255.
https://doi.org/10.1080/10474410701413152

Ziomek-Daigle, J., Goodman-Scott, E., Cavin, J., & Donohue, P. (2016). Integrating a multi-tiered system of supports with comprehensive school counseling programs. The Professional Counselor, 6(3), 220–232. https://doi.org/10.15241/jzd.6.3.220

 

Hannah Brinser is a master’s candidate at Gonzaga University. Addy Wissel, PhD, is an associate professor and program director at Gonzaga University. Correspondence may be addressed to Hannah Brinser, 502 E. Boone Ave., Spokane, WA 99258, hannahbrinser@gmail.com.

Clinical Work With Clients Who Self-Injure: A Descriptive Study

Amanda Giordano, Lindsay A. Lundeen, Chelsea M. Scoffone, Erin P. Kilpatrick, Frank B. Gorritz

 

Nonsuicidal self-injury (NSSI) is a common clinical concern. We surveyed a national sample of 94 licensed clinicians to better understand their work with clients who self-injure. Our data revealed that over the past year, 95.7% (n = 90) of the sample reported working with at least one client who self-injured. Thirty-six clinicians (38%) reported that most or all of their clients who self-injured were adolescents, 61 (64.9%) reported that most or all clients who self-injured were female, and 43 (45.7%) reported that most or all clients who self-injured engaged in cutting as the primary NSSI method. About 35% (n = 33) of the clinicians in our sample indicated they have never asked clients who self-injured about their online activity related to NSSI. The majority of our participants (n = 78; 83%) supported the notion that NSSI could be an addictive behavior for some clients and less than half (n = 42; 44.7%) received NSSI training in their graduate coursework. 

Keywords: nonsuicidal self-injury, NSSI, licensed clinicians, training, behavioral addiction  

 

Nonsuicidal self-injury (NSSI) is a complex phenomenon. Favazza (1998) defined NSSI as “the deliberate, direct destruction or alteration of body tissue without conscious suicidal intent” (p. 260). The fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5; American Psychiatric Association [APA], 2013) noted that NSSI is intentional and self-inflicted body damage that is not socially sanctioned (e.g., piercings or tattoos) and lacks suicidal intent. The fact that NSSI is intentional and direct distinguishes it from unplanned or indirect forms of self-harm such as disordered eating or substance abuse (Favazza, 1998; Walsh, 2012). Furthermore, although a relationship exists, NSSI is distinct from suicide attempts in that it is a means of seeking relief and coping, thereby sustaining rather than ending one’s life (Walsh, 2012; Wester & Trepal, 2017). NSSI has been conceptualized as a behavioral addiction (Buser & Buser, 2013) given that some clients demonstrate a loss of control over NSSI, continued engagement despite negative consequences, craving to engage in NSSI, and compulsivity, which are hallmarks of addiction. Also, researchers have found evidence for NSSI contagion, in which the behavior is imitated by others in a specific community (Walsh, 2012; Walsh & Rosen, 1985). Given these complexities, it is imperative that clinicians are adequately trained to assess and treat NSSI.

In light of previously published prevalence rates, it is likely that most clinicians will work with clients who self-injure at some point in their careers. Indeed, 21%–80% of inpatient clients and 22%–40% of outpatient clients have reported engagement in self-injurious behavior (Wester & Trepal, 2017). Moreover, in a national sample of 74 clinical practitioners, 60 (81%) reported working with clients who self-injured (Trepal & Wester, 2007), and among 443 school counselors, 357 (81%) reported working with at least one student engaged in self-injury (Roberts-Dobie & Donatelle, 2007). Much has changed, however, in the social landscape related to self-injury, including the popularity of sharing NSSI images online; television shows, movies, and songs depicting NSSI; and celebrities disclosing NSSI behavior. Thus, we sought to investigate licensed clinicians’ experiences working with clients who self-injure to provide updated information and better inform the profession of counseling.

Terminology and Prevalence of NSSI

NSSI is not a new abnormal behavior. Indeed, it was documented in the gospel account of Mark written between A.D. 55 and 65, in which the author described a man cutting himself with stones (Mark 5:5; NIV Life Application Study Bible, 1984). Self-injurious behavior has been labeled self-mutilation, self-harm, deliberate self-harm, parasuicide, cutting, and non-suicidal self-directed violence (Wester & Trepal, 2017). In this paper, we use the term nonsuicidal self-injury (NSSI) as it is currently listed as the proposed diagnosis in the DSM-5 (Section III, Conditions for Further Study; APA, 2013).

Current prevalence rates indicate that NSSI affects a substantial portion of the population, particularly female adolescents (Nock, 2009; Wester & Trepal, 2017). For example, in a study of 665 adolescents, researchers determined that 8% engaged in NSSI at some point in their lives, which included 9% of the females in the sample and 6.7% of the males (Barrocas et al., 2012). Furthermore, Doyle and colleagues (2017) surveyed adolescents in Ireland and found that 12% had engaged in NSSI, the majority (72.8%) of which were female. Moreover, the examination of data from emergency room visits among youth in the United States (10–24 years of age) indicated a rise in non-fatal self-inflicted injury among females (with and without suicidal intent) from 2001 to 2015 (Mercado et al., 2017). Specifically, self-inflicted injuries with a sharp object rose from 261 incidents in 2001 to 1,021 incidents in 2015 (Mercado et al., 2017). Along with adolescent populations, NSSI is a growing concern among young adults. Wester et al. (2018) examined NSSI among three cohorts of freshman college students and found that lifetime NSSI increased from 16% in the 2008 cohort to 45% in the 2015 cohort. Additionally, current NSSI increased from 2.6% in the 2008 cohort to 19.4% in the 2015 cohort (Wester et al., 2018).

Motives for NSSI

The function of NSSI can be challenging to comprehend among those who do not engage in the behavior. Criterion B in the proposed criteria for NSSI Disorder in the DSM-5 (APA, 2013) highlighted three potential functions: (a) to relieve negative feelings and cognitions, (b) to address relational difficulties, and (c) to stimulate positive feelings. Indeed, emotion regulation is a primary motivation for NSSI (Nock, 2009). Among 108 adolescents in inpatient treatment who engaged in self-injurious thoughts or behaviors, Nock and Prinstein (2004) found 52.9% engaged in NSSI to relieve negative emotions, 34.1% engaged to feel something, and 30.6% engaged as a form of self-punishment. Doyle et al. (2017) found 79% of adolescents who engaged in NSSI did so to find relief from negative emotions or cognitions, 38% engaged to punish themselves, and 35% sought to communicate the extent of their distress. In light of the many means of emotion regulation that exist, Nock (2009) identified three reasons why some individuals choose NSSI: (a) as a result of social learning from the media, friends, and family; (b) as a form of punishment via self-directed abuse; and (c) as a means of social signaling, or communicating with others (particularly when other forms of communication were ineffective). Engaging in NSSI may be a more accessible, affordable, and easy-to-hide method of emotion regulation compared to other strategies such as substance abuse (Nock, 2009).

NSSI Social Contagion

One important consideration related to NSSI is social contagion, or the engagement in a behavior by at least two people in a group within 24 hours (Jarvi et al., 2013; Walsh, 2012; Walsh & Rosen, 1985; Wester & Trepal, 2017). Individuals can become exposed to NSSI through peers, family members, media, and song lyrics, which contribute to social learning (Jarvi et al., 2013; Nock, 2009) and potentially sensationalize the behavior (Walsh, 2012). In a review of the literature, researchers found 16 studies supporting the association between social contagion and NSSI (Jarvi et al., 2013). In a seminal work, Walsh and Rosen (1985) studied the behavior of 25 adolescents in treatment for various mental health diagnoses for one year. The researchers analyzed the frequency and timing of particular behaviors, including NSSI, and found significant clustering of self-injurious incidents, supporting contagion for NSSI among the group. Furthermore, researchers have found that a small portion of those who engage in NSSI do so to influence others (e.g., get the attention of a particular person, manipulate others, or elicit care; Doyle et al., 2017; Nock, 2008).

In light of the ubiquitous nature of the internet, NSSI social contagion may occur among online groups, as well as those that exist offline. Walsh (2012) noted that factors contributing to social contagion offline can also occur online within the context of social networking sites, message boards, chat rooms, and YouTube. Researchers have confirmed the prevalence of NSSI images and videos online. Lewis and colleagues (2011) investigated NSSI videos on YouTube and found that the top 100 NSSI videos were viewed over 2 million times. Miguel et al. (2017) found 770 NSSI-related images on three social media platforms in a 6-month period using one search term (#cutting). The researchers classified 59.5% of the images as graphic in nature (Miguel et al., 2017). Although there are potential benefits of online communication about NSSI, such as encouraging help-seeking and support, online NSSI-related images and videos pose risks as well. Lewis et al. (2012) noted that online mediums may provide reinforcement for NSSI, provide tips and strategies (such as first aid considerations), and trigger urges among users to engage in NSSI.

NSSI as a Behavioral Addiction

Given its seemingly compulsive nature, some authors have proposed the conceptualization of NSSI as a behavioral addiction (Buser & Buser, 2013; Davis & Lewis, 2019). Indeed, Buser and Buser (2013) posited that for some individuals, NSSI reflects the commonly used criteria for addiction, including compulsivity, loss of control, continuation despite negative consequences, relief from negative emotions, and tolerance. Specifically, tolerance to NSSI can develop as a result of frequent activation of the endogenous opioid system, to which the individual becomes less sensitive (Buser & Buser, 2013; Walsh, 2012). Tolerance among those who self-injure may manifest as increased frequency of NSSI, increased severity of skin tissue damage, or the use of additional NSSI methods (Wester & Trepal, 2017). In the content analysis of 500 posts on NSSI online message boards, Davis and Lewis (2019) determined six themes that underscored the addictive nature of NSSI: urge/obsession, relapse, can’t/don’t want to stop, coping mechanism, hiding shame, and getting worse/not enough. These themes indicate that some individuals who engage in NSSI experience cravings, a loss of control, urges, and relapse—all common features of addictive behaviors (American Society of Addiction Medicine, 2019). Given the growing acceptance of behavioral addictions, as evidenced by recent changes and additions to both the DSM-5 (APA, 2013) and the International Classification of Diseases (ICD-11; World Health Organization, 2018), it is important to assess whether clinicians working with clients who self-injure conceptualize the behavior as addictive.

Purpose of the Study

     Although some researchers have investigated the experience of clinicians addressing clients who self-injure (Roberts-Dobie & Donatelle, 2007; Trepal & Wester, 2007), the growing prevalence of NSSI (Mercado et al., 2017; Wester et al., 2018) warrants updated information. Therefore, we designed the current study to explore licensed clinicians’ experiences with clients who engage in self-injurious behaviors. Specifically, we sought to examine the frequency of addressing NSSI in clinical work, characteristics of clients who self-injure, NSSI assessment practices, the role of the internet in NSSI, clinicians’ beliefs pertaining to NSSI, and clinical training and competence.

Method

Sample

Our sample consisted of 94 licensed clinicians in the United States. Participants ranged in age from 26 to 70 years old with a mean age of 45 (SD = 11.06). Eighty (85.1%) participants identified as White, six (6.4%) as Black/African American, three (3.2%) as biracial/multiracial, three (3.2%) as other, and two (2.1%) as Latino(a)/Hispanic. With regard to gender, 79 (84%) participants identified as female, 13 (13.8%) as male, one (1.1%) as transgender, and one (1.1%) as other. Of the 94 participants, 82 (87.2%) identified as heterosexual, five (5.3%) as bisexual, three (3.2%) as queer, two (2.1%) as lesbian, and one (1.1%) each as gay and other.

In relation to professional background, the clinicians represented varying degree levels and educational fields of study. Most of the participants’ highest degree was a master’s (n = 86; 91.5%), while seven (7.4%) earned a doctoral degree, and one (1.1%) participant earned a specialist degree. Fifty-six (59.6%) of the participants reported that their highest degree was from a CACREP-accredited program, while 26 (27.7%) of the participants came from a non–CACREP-accredited program, and 12 (12.8%) did not answer the question. Some diversity existed among participants’ programs of study and licensure: 51 (54.3%) participants studied professional counseling or counselor education, 27 (28.7%) studied counseling psychology, seven (7.4%) studied clinical psychology, six (6.4%) studied other areas not listed, and three (3.2%) studied rehabilitation counseling. In terms of licensure, 47 (50%) participants were licensed professional counselors (LPCs), 19 (20.2%) were licensed mental health counselors (LMHCs), 15 (16%) were licensed professional clinical counselors (LPCCs), 11 (11.7%) held licensures not listed in our questionnaire, 11 (11.7%) were licensed clinical professional counselors (LCPCs), seven (7.4%) were licensed clinical mental health counselors (LCMHCs), four (4.3%) were licensed professional counselors of mental health (LPCMHs), three (3.2%) were licensed marriage and family therapists (LMFTs), and one (1.1%) was a licensed chemical dependency counselor (LCDC).

The participants had varying years of clinical experience. Eighteen (19.1%) participants had been counseling clients for 1–5 years, 43 (45.7%) for 6–10 years, 17 (18.1%) for 11–15 years, six (6.4%) for 16–20 years, three (3.2%) for 21–25 years, five (5.3%) for 26–30 years, and two (2.1%) for more than 30 years. All participants stated they were currently seeing clients. We asked participants to describe their typical client base by selecting all applicable responses: 84 (89.4%) of the participants counseled adults, 37 (39.4%) counseled adolescents, 37 (39.4%) counseled college students, 27 (28.7%) counseled couples, 19 (20.2%) counseled children, and 12 (12.8%) counseled families.

Instrument

Similar to the approach employed by Trepal and Wester (2007), our questionnaire consisted of two sections: participants’ demographics and clinical experiences with NSSI. In the demographics section, we assessed participants’ age, race, ethnicity, gender, sexual orientation, education, clinical license, and typical client base. Next, to better understand clinical work with clients who self-injure, we compiled a series of descriptive, Likert-type assessment items. Specifically, the questionnaire items explored how often clinicians addressed issues of NSSI in counseling, characteristics of clients who self-injured, methods of assessing NSSI, clients’ internet and social networking activity pertaining to self-injury, the extent to which clinicians conceptualized NSSI as an addiction and whether NSSI should be a formal diagnosis included in the DSM proper (rather than as an appendix), extent of clinical training pertaining to NSSI, and perceived clinical competence when working with issues of NSSI among clients. In sum, the questionnaire contained 22 items related to clinical work with NSSI.

Design

We acquired our national sample of licensed clinical participants using the clinician database on the Psychology Today website. Specifically, we conducted a search of clinicians with experience addressing a general clinical issue (i.e., anxiety) within each of the 50 states. We identified the names of the first 13 licensed clinicians from each state and searched the internet for their email addresses. If an email address could not be found, we replaced this clinician with the next licensed clinician listed on the Psychology Today website for that particular state. We continued this process until we had names and email addresses for 13 licensed clinicians from each state, yielding 650 potential participants.

We calculated a desired sample of 650 given that researchers purported an average response rate of 15.7% for online research surveys sent to professional counselors in the “other” category (members of state-level associations), which most closely reflected our sample (Poynton et al., 2019). After receiving approval from the Institutional Review Board, we emailed the questionnaire link utilizing the Qualtrics software program to the 650 potential participants. Fifty-two emails were undeliverable, resulting in 598 emails sent. We sent participants three reminder emails over the course of three weeks. We received 102 questionnaires (17.1% response rate) from our national sample of licensed clinicians. After removing eight unfinished questionnaires, our final sample consisted of 94 participants (adjusted response rate = 15.7%).

Results

To answer our research questions regarding licensed clinicians’ experiences with client NSSI, we assessed descriptive data resulting from responses to our questionnaire. The data fell into six broad categories: (a) frequency of NSSI in clinical work, (b) descriptions of clients who self-injure, (c) assessment of NSSI, (d) role of the internet, (e) clinicians’ beliefs about NSSI as an addiction and formal diagnosis, and (f) NSSI-related training and perceived competence.

Frequency of NSSI in Clinical Work

     We first sought to examine how frequently licensed clinicians worked with clients who self-injured. Specifically, we asked our sample how often in the totality of their clinical work they addressed client NSSI. Results indicated that only two (2.1%) clinicians had never worked with a client reporting NSSI, 37 (39.4%) addressed NSSI rarely (about 10% of the time), 33 (35.1%) addressed NSSI occasionally (about 30% of the time), 13 (13.8%) addressed NSSI a moderate amount (about 50% of the time), five (5.3%) addressed NSSI frequently (about 70% of the time), and four (4.3%) addressed NSSI almost always (about 90% of the time). Thus, among a national sample of 94 licensed clinicians, 92 (97.9%) reported working with NSSI at some point in their careers, with 55 (58.5%) reporting that they addressed NSSI 30% of the time or more.

We also assessed frequency of NSSI among clients in the past year. Only one (1.1%) clinician reported not having self-injuring clients in the previous 12 months. Fifty-one (54.3%) clinicians worked with 1–5 clients who self-injured, 24 (25.5%) worked with 6–10 clients who self-injured, six (6.4%) worked with 11–15 clients who self-injured, and nine (9.6%) worked with more than 15 clients who self-injured. Three (3.2%) participants did not respond to this item.

Descriptions of Clients Who Self-Injure

We then examined clinicians’ descriptions of clients who reported NSSI. Specifically, we inquired about age, gender, race, and method of self-harm by asking clinicians what portion of their clients who self-injured fell into various categories (Table 1). Sixty-one (64.9%) clinicians reported that most or all of their clients who self-injured were female, five (5.3%) reported that most or all of their clients who self-injured were transgender, and one (1.1%) reported that most or all clients who self-injured were male. With regard to race, 63 (67.0%) clinicians reported that most or all of their clients who self-injured were White and nine (9.6%) clinicians reported that most or all of their clients who self-injured were members of a marginalized racial group. With regard to age, 36 (38.3%) clinicians reported that most or all of their clients who self-injured were adolescents, 31 (33.0%) reported that most or all of their clients who self-injured were adults, and one (1.1%) reported that most or all of their clients who self-injured were children. In terms of method of self-injury, 43 (45.7%) clinicians reported that most or all of their clients who self-injured engaged in cutting and seven (7.4%) clinicians reported that most or all of their clients who self-injured engaged in self-injurious behavior other than cutting (e.g., burning, hitting, scratching, punching). Therefore, the experience of NSSI is diverse. Although a substantial portion of clinicians reported that the majority of clients presenting with NSSI were White female adolescents who engaged in cutting, numerous clinicians indicated some clients (up to 50%) were male or transgender, children or adults, clients of color, and engaged in methods other than cutting.

 

Table 1

Number of Clinicians Endorsing Each Response

 

Item: Among your clients who self-injure, what portion are:  None
(0%)
Some
(
< 50%)
About half (50%) Most
(
> 50%)
All
(100%)
Female 1 (1.1%) 17 (18.1%) 12 (12.8%) 43 (45.7%) 18 (19.1%)
Male 21 (22.3%) 57 (60.6%) 11 (11.7%) 1 (1.1%) 0
Transgender 39 (41.5%) 37 (39.4%) 9 (9.6%) 3 (3.2%) 2 (2.1%)
White 2 (2.1%) 20 (21.3%) 6 (6.4%) 45 (47.9%) 18 (19.1%)
Person of Color 25 (26.6%) 51 (54.3%) 7 (7.4%) 6 (6.4%) 3 (3.2%)
Children 64 (68.1%) 24 (25.5%)  0 0 1 (1.1%)
Adolescents 19 (20.2%) 22 (23.4%) 15 (16.0%) 31 (33.0%) 5 (5.3%)
Adults 7 (7.4%) 39 (41.5%) 13 (13.8%) 22 (23.4%) 9 (9.6%)
Engaged primarily in cutting 2 (2.1%) 32 (34.0%) 14 (14.9%) 35 (37.2%) 8 (8.5%)
Engaged primarily in self-injurious behavior other than cutting 19 (20.2%) 52 (55.3%) 14 (14.9%) 6 (6.4%) 1 (1.1%)

 Note. Numerical values refer to number of clinicians endorsing that response, followed by percent of clinicians out of the total (N = 94); percentages do not equate to 100 because of missing items: female (missing 3), male (missing 4), transgender (missing 4), White (missing 3), person of color (missing 2), children (missing 5), adolescents (missing 2), adults (missing 4), primarily cutting (missing 3), primarily other behavior (missing 2).

 

Assessment of NSSI

We also examined data related to the clinical assessment of NSSI. The most commonly endorsed form of assessing NSSI among clinicians was informal assessment through dialogue (n = 83, 88.3%), followed by the use of formal NSSI assessment instruments (n = 21, 22.3%). One (1.1%) clinician reported never assessing NSSI in their clinical work. We also inquired as to whether or not clinicians’ intake forms contained items related to NSSI. Forty-six (48.9%) reported yes, the NSSI item was separate from suicide items; 22 (23.4%) reported yes, the NSSI item was in conjunction with suicide attempts; 16 (17.0%) clinicians reported no, their intake form did not have an item related to NSSI; and 10 (10.6%) did not know or did not answer this question.

Role of the Internet in Client Self-Injurious Behavior

We investigated participants’ responses to items related to clients’ internet use related to NSSI. Specifically, we asked clinicians what portion of their clients engaging in NSSI utilized the internet or social networking sites (SNS) to share pictures of self-injury. Forty-two (44.7%) clinicians reported they did not know because they never discussed the issue with their clients who self-injured. Twenty-six (27.7%) clinicians reported that some (up to 50%) of their clients who self-injured shared NSSI pictures online, 20 (21.3%) reported none of their clients who self-injured shared NSSI pictures online, and three (3.2%) reported that half to all of their clients who self-injured shared NSSI pictures online. In response to the item assessing the frequency in which clinicians asked clients who self-injured about their internet and SNS use related to self-injury, 33 (35.1%) clinicians reported they never asked about this topic, 27 (28.7%) asked sometimes (less than 50% of the time), seven (7.4%) asked about half the time, 17 (18.1%) asked most of the time (more than 50%), and eight (8.5%) always asked. Therefore, it appears that clinicians do not consistently inquire about clients’ internet and SNS use as it relates to NSSI, but those who do find that some of their clients share pictures of self-injury online.

Clinicians’ Beliefs About NSSI

     In light of the current status of NSSI Disorder as a condition for further study in the DSM-5 (APA, 2013) and debate about the addictive nature of NSSI, we asked clinicians to share their beliefs on these two topics. With regard to diagnostic status, 32 (34%) clinicians believed NSSI Disorder should be a formal diagnosis in the next edition of the DSM, 24 (25.5%) did not have a preference, and 13 (13.8%) did not believe it should be a diagnosis. Twenty-five (26.6%) participants did not respond to this item. Pertaining to the conceptualization of NSSI as an addiction, 78 (83.0%) clinicians believed that for some individuals, NSSI can be an addiction; eight (8.5%) did not believe NSSI could be an addiction; six (6.4%) stated they did not know; and two (2.1%) did not answer this item. Thus, it appears that one third of the sample supported a formal diagnosis of NSSI Disorder in the DSM proper and a large majority of the sample agreed that NSSI could be an addictive behavior.

NSSI-Related Training and Competence

Finally, participants reported settings in which they received training to address NSSI in clinical work (participants could select all modalities that applied). The most common training modality was continuing education (e.g., conference presentations, workshops, seminars), which was endorsed by 55 (58.5%) clinicians. On-the-job training was the second most common modality, endorsed by 47 (50.0%) clinicians, followed by graduate school coursework, endorsed by 42 (44.7%) clinicians; self-study, endorsed by 38 (40.4%) clinicians; and graduate school internships, endorsed by 28 (29.8%) clinicians. Three (3.2%) clinicians reported that they had never received NSSI training. Clinicians further reported the extent to which they felt competent addressing NSSI in counseling. Four (4.3%) clinicians felt extremely incompetent, eight (8.5%) felt somewhat incompetent, 10 (10.6%) felt neither competent nor incompetent, 54 (57.4%) felt somewhat competent, and 17 (18.1%) felt extremely competent. One (1.1%) clinician did not respond to this item. Overall, clinicians primarily received NSSI training via continuing education workshops and on-the-job experiences. About half of our sample felt somewhat competent to address NSSI, indicating opportunities to improve NSSI training and competence among clinicians.

Discussion

Given the rising prevalence of NSSI (Mercado et al., 2017; Wester et al., 2018) and new considerations such as social contagion (Walsh, 2012; Walsh & Rosen, 1985) and sharing NSSI images online (Lewis et al., 2011; Miguel et al., 2017), continued research is needed related to clinical work with self-injury. We disseminated a questionnaire among a national sample of licensed clinicians to examine the prevalence of NSSI, descriptions of clients who engage in NSSI, means of assessing NSSI, role of the internet in NSSI behaviors, clinicians’ beliefs about NSSI, and NSSI training and perceived competence. Our results indicated that most clinicians surveyed (n = 92, 97.9%) have worked with at least one client who engaged in NSSI. This prevalence rate suggests a potential increase in the presenting concern since Trepal and Wester’s (2007) study, in which 81% of practicing counselors reported working with a client who self-injured during their careers. Furthermore, our results revealed that 95.7% (n = 90) of clinicians treated at least one client participating in NSSI within the past year. Although researchers have determined that 8% of adolescents (Barrocas et al., 2012) and 45% of college freshman (Wester et al., 2018) in naturalistic samples engaged in NSSI at some point in their lifetimes, it appears the frequency might be higher among clients seeking counseling services.

Previous researchers have established that NSSI is more prevalent among females than males (Barrocas et al., 2012; Doyle et al., 2017; Mercado et al., 2017). Our results confirmed these findings as 61 (64.9%) of the clinicians in our sample indicated that most or all of their clients who self-injured were female, as compared to only one (1.1%) who said most or all were male. It is important to note, however, the prevalence of clinicians who reported working with male clients who self-injured. Specifically, 57 (60.6%) noted that some of their clients who self-injured were male and 11 (11.7%) reported that about half of their clients who self-injured were male. Thus, these results indicate that although NSSI is more prevalent among females, it also occurs among male populations. Additionally, although NSSI typically begins in adolescence (Nock & Prinstein, 2004; Wester & Trepal, 2017), 31 (33%) of the clinicians in our sample reported that most or all of their clients who engaged in NSSI were adults. It is imperative, therefore, that clinicians who work with both adolescents and adults are prepared to effectively screen for and treat NSSI.

Regarding the assessment of self-injurious behaviors, our results revealed that only 21 (22.3%) clinicians utilized formal NSSI assessments. Although informal assessment measures often are effective, clinicians could benefit from reviewing psychometrically sound NSSI assessment instruments such as the Deliberate Self-Harm Inventory (Gratz, 2001), the Alexian Brothers Urge to Self-Injure Scale (ABUSI; Washburn et al., 2010), or the Non-Suicidal Self-Injury-Assessment Tool (Whitlock et al., 2014; see Wester & Trepal, 2017, for an extensive description of multiple NSSI assessments).White Kress (2003) summarized that clinicians should assess the function, severity, and dynamics of NSSI, including age of onset, emotions while engaging in NSSI, antecedents to NSSI, desire and efforts to stop or control NSSI, use of substances while self-injuring, medical complications, and changes over time.

We also sought to understand the role of the internet and SNS in NSSI behaviors. Specifically, we inquired of licensed clinicians the extent to which their clients utilized the internet or SNS to share NSSI images and the frequency in which they asked clients who self-injured about their internet behavior. According to the results of our survey, almost half of clinicians surveyed (n = 42; 44.7%) did not know about the role of the internet or SNS among clients who self-injured because they did not ask. Twenty-nine (30.9%) clinicians reported that at least some of their clients used the internet to share pictures. Furthermore, 33 (35.1%) of the clinicians in our study disclosed they had never asked about SNS or the internet when assessing and treating clients engaging in NSSI, and 27 (28.7% ) reported asking less than 50% of the time. These numbers indicate a need for clinicians to have access to current research related to the prevalence of viewing and sharing NSSI images online (Lewis et al., 2011; Miguel et al., 2017). For example, Lewis and Seko (2016) thematically examined 27 empirical studies investigating the perceived effects of online behavior among those who self-injure. The authors reported both perceived benefits of online NSSI activity (i.e., mitigation of social isolation, recovery encouragement, emotional self-disclosure, and curbing NSSI urges) as well as perceived risks (i.e., NSSI reinforcement, triggering NSSI urges, and stigmatization of NSSI; Lewis & Seko, 2016). In addition, previous researchers have found that a portion of individuals engaging in NSSI do so to influence others (Doyle et al., 2017; Nock, 2008), and thus may be particularly attracted to sharing NSSI images online. Given the complex role of the internet in self-injury, it seems imperative that clinicians broach the subject with clients who self-injure.

Our results also demonstrated a strong belief among clinicians (n = 78; 83%) that NSSI can be an addictive behavior for some clients, which supports the stance of previous researchers who conceptualize NSSI as a behavioral addiction (Buser & Buser, 2013). The conceptualization of NSSI as an addictive behavior, with particular emphasis on the stimulation of the endogenous opioid system, has important implications for treatment. Evidence-based addictions treatment strategies such as 12-step support group attendance (Connors et al., 2001) and motivational interviewing (Miller & Rollnick, 2013) can be helpful approaches for working with client NSSI.

Finally, we examined clinicians’ training experience and perceived competence related to NSSI. Less than half of our participants (n = 42; 44.7%) received NSSI training in their graduate-level coursework. The number of clinicians seeking NSSI training via continuing education (n = 55; 58.5%) and self-study (n = 38; 40.4%) is indicative of the desire for more knowledge related to self-injury. In addition, roughly 23% (n = 22) of our sample felt less than “somewhat competent” when addressing NSSI in their clinical work. This perceived incompetency reflects the reported lack of training related to NSSI treatment. Ultimately, this data highlights the opportunity to substantially improve NSSI training to increase clinical competence.

Implications for Counselors

The results of the current study have implications for clinical work with NSSI, specifically in the realms of assessment and treatment. Although many clinicians in our study reported effective assessment measures related to NSSI, an important step for improving assessment might be to include a separate NSSI item on intake forms distinct from suicidal behavior. Sixteen clinicians (17%) in our study said their intake form did not inquire about NSSI, and 22 (23.4%) said the item was written in conjunction with suicidal ideation and attempts. The combination of NSSI and suicidal thoughts or ideations on an intake form can make client conceptualization and treatment goals challenging. NSSI and suicide attempts have markedly different motives (Favazza, 1998; Walsh, 2012; Wester & Trepal, 2017); therefore, listing the behaviors as two separate intake items may best serve both clinicians and clients. Specifically, clinicians could provide a definition of NSSI (Favazza, 1998) on the form to help clients understand the terminology. For clients who indicate that they are engaging in NSSI, clinicians can then utilize formal assessment instruments or the proposed NSSI Disorder diagnostic criteria in the DSM-5 (APA, 2013) to gain a thorough understanding of the behavior. Additionally, clinicians may best serve clients by assessing NSSI with all individuals, regardless of gender, age, racial, or ethnic identification, by asking a broad question such as “Have you ever deliberately hurt yourself?” rather than “Have you ever cut yourself?” to be inclusive of multiple forms of NSSI.

With regard to treatment strategies for NSSI, several useful approaches exist. Dialectical behavior therapy (Linehan, 1993) is a counseling method combining cognitive-behavioral and mindfulness techniques for work with clients diagnosed with borderline personality disorder (BPD). NSSI can be associated with BPD given that self-mutilation is listed as a diagnostic criterion for the disorder (APA, 2013). Researchers have found empirical support for the efficacy of dialectical behavior therapy with regard to NSSI (Choate, 2012; Muehlenkamp, 2006); thus, this treatment approach may be useful for clients with BPD and NSSI. Self-injury also can exist apart from a BPD diagnosis (Muehlenkamp, 2005). In these instances, treatment for self-injurious behavior (T-SIB; Andover et al., 2015) may be a useful approach. T-SIB is a 9-week intervention designed for young adults who self-injure. The intervention includes providing psychoeducation, increasing motivation to change, conducting functional analysis, developing replacement behaviors, increasing distress tolerance, and cognitive restructuring (Andover et al., 2015, 2017). Some empirical support exists for the efficacy of T-SIB among young adults, and the treatment manual provides detailed information for clinicians using the approach (Andover et al., 2015, 2017).

Regardless of the therapeutic intervention, it would behoove clinicians to inquire about clients’ online activities related to NSSI to inform treatment plans and goals. Clients’ online activities could include watching NSSI videos; viewing NSSI images; posting and sharing NSSI images on SNS; communicating with others who self-injure via chatrooms and NSSI websites; or seeking information related to how to conceal, clean, or perform NSSI. As part of their recovery plan, it may be helpful for clients and counselors to develop strategies for healthy online behaviors to minimize triggers, urges, or the normalization of NSSI. Even for clients who describe using the internet to find support for their NSSI, clinicians have the opportunity to describe potential risks with NSSI online activity as well (Lewis & Seko, 2016).

Limitations and Future Research

This study is not without limitations. First, our final participant sample consisted of only 94 licensed clinicians, which reflected a 15.7% response rate. Although this is fairly typical for online surveys (Poynton et al., 2019), there were many potential respondents who did not participate, and we were unable to determine if non-respondents differed significantly from respondents. Additionally, in order to obtain a nationally representative sample, we utilized the clinician database found on Psychology Today. Thus, our participants were limited to only those clinicians who registered for that particular website. Furthermore, although our questionnaire was robust, we did not inquire about the nature of internet use among clients with NSSI. Future researchers may choose to assess whether clients primarily use the internet for education related to NSSI, to find support, to share images, or to read others’ accounts of NSSI behaviors. Finally, we utilized only licensed clinicians for this study. Future researchers may choose to replicate this study with specific types of counselors such as school counselors, inpatient counselors, and outpatient counselors to assess experiences with individuals who self-injure. In these various settings, researchers may inquire as to how clinicians code for NSSI, given that it is not included in the DSM-5 proper.

Conclusion

     Nonsuicidal self-injury is a prevalent concern among clients seeking clinical services. We sought to understand clinicians’ experiences working with NSSI by surveying a national sample of licensed practitioners (N = 94). As demonstrated by our results, NSSI affects individuals across age ranges and gender identifications, although it is most prevalent among White female adolescents. Our findings indicate that the majority of clinicians (97.9%) worked with at least one client who engaged in NSSI in the past year. Furthermore, the majority of our sample (83.0%) supported the stance that NSSI can be an addictive behavior. Finally, our study indicates a need for more training related to NSSI in graduate programs and an emphasis on differentiating between NSSI and suicide attempts on intake forms and in clinical work.

 

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

 

References

American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.).

American Society of Addiction Medicine (2019). Definition of addiction. https://www.asam.org/resources/definition-of-addiction

Andover, M. S., Schatten, H. T., Morris, B. W., Holman, C. S., & Miller, I. W. (2017). An intervention for nonsuicidal self-injury in young adults: A pilot randomized controlled trial. Journal of Consulting and Clinical Psychology, 85(6), 620–631. http://doi.org/10.1037/ccp0000206

Andover, M. S., Schatten, H. T., Morris, B. W., & Miller, I. W. (2015). Development of an intervention for nonsuicidal self-injury in young adults: An open pilot trial. Cognitive and Behavioral Practice, 22(4), 491–503. https://doi.org/10.1016/j.cbpra.2014.05.003

Barrocas, A. L., Hankin, B. L., Young, J. F., & Abela, J. R. Z. (2012). Rates of nonsuicidal self-injury in youth: Age, sex, and behavioral methods in a community sample. Pediatrics, 130(1), 39–45.
https://doi.org/10.1542/peds.2011-2094

Buser, T. J., & Buser, J. K. (2013). Conceptualizing nonsuicidal self-injury as a process addiction: Review of research and implications for counselor training and practice. Journal of Addiction & Offender Counseling, 34(1), 16–29. https://doi.org/10.1002/j.2161-1874.2013.00011.x

Choate, L. H. (2012). Counseling adolescents who engage in nonsuicidal self-injury: A dialectical behavior therapy approach. Journal of Mental Health Counseling, 34(1), 56–71.
https://doi.org/10.17744/mehc.34.1.506780307v16m402

Connors, G. J., Tonigan, J. S., & Miller, W. R. (2001). A longitudinal model of intake symptomatology, AA participation and outcome: Retrospective study of the Project MATCH outpatient and aftercare samples. Journal of Studies on Alcohol, 62(6), 817–825. https://doi.org/10.15288/jsa.2001.62.817

Davis, S., & Lewis, C. A. (2019). Addicted to self-harm? The case of online postings on self-harm message boards. International Journal of Mental Health and Addiction, 17, 1020–1035.
https://doi.org/10.1007/s11469-018-9975-8

Doyle, L., Sheridan, A., & Treacy, M. P. (2017). Motivations for adolescent self-harm and the implications for mental health nurses. Journal of Psychiatric and Mental Health Nursing, 24(2-3), 134–142. https://doi.org/10.1111/jpm.12360

Favazza, A. R. (1998). The coming of age of self-mutilation. The Journal of Nervous and Mental Disease, 186(5), 259–268. https://doi.org/10.1097/00005053-199805000-00001

Gratz, K. L. (2001). Measurement of deliberate self-harm: Preliminary data on the Deliberate Self-Harm Inventory. Journal of Psychopathology and Behavioral Assessment, 23, 253–263.
https://doi.org/10.1023/A:1012779403943

Jarvi, S., Jackson, B., Swenson, L., & Crawford, H. (2013). The impact of social contagion on non-suicidal self-injury: A review of the literature. Archives of Suicide Research, 17(1), 1–19.
https://doi.org/10.1080/13811118.2013.748404

Lewis, S. P., Heath, N. L., Michal, N. J., & Duggan, J. M. (2012). Non-suicidal self-injury youth and the internet: What mental health professionals need to know. Child and Adolescent Psychiatry and Mental Health, 6, 13–21. https://doi.org/10.1186/1753-2000-6-13

Lewis, S. P., Heath, N. L., St. Denis, J. M., & Noble, R. (2011). The scope of nonsuicidal self-injury on YouTube. Pediatrics, 127(3), e552–e557. https://doi.org/10.1542/peds.2010-2317

Lewis, S. P., & Seko, Y. (2016). A double-edged sword: A review of benefits and risks of online nonsuicidal self-injury activities. Journal of Clinical Psychology, 72(3), 249–262. https://doi.org/10.1002/jclp.22242

Linehan, M. M. (1993). Cognitive-behavioral treatment of borderline personality disorder. Guilford.

Mercado, M. C., Holland, K., Leemis, R. W., Stone, D. M., & Wang, J. (2017). Trends in emergency department visits for nonfatal self-inflicted injuries among youth aged 10 to 24 years in the United States, 2001–2015. JAMA, 318(19), 1931–1933. https://doi.org/10.1001/jama.2017.13317

Miguel, E. M., Chou, T., Golik, A., Cornacchio, D., Sanchez, A. L., DeSerisy, M., & Comer, J. S. (2017). Examining the scope and patterns of deliberate self-injurious cutting content on popular social media. Depression and Anxiety, 34(9), 786–793. https://doi.org/10.1002/da.22668

Miller, W. R., & Rollnick, S. (2013). Motivational interviewing: Helping people change (3rd ed.). Guilford.

Muehlenkamp, J. J. (2005). Self-injurious behavior as a separate clinical syndrome. American Journal of Orthopsychiatry, 75(2), 324–333. https://doi.org/10.1037/0002-9432.75.2.324

Muehlenkamp, J. J. (2006). Empirically supported treatments and general therapy guidelines for non-suicidal self-injury. Journal of Mental Health Counseling, 28(2), 166–185.
https://doi.org/10.17744/mehc.28.2.6w61cut2lxjdg3m7

NIV Life Application Study Bible. (1984). Tyndale House Publishers.

Nock, M. K. (2008). Actions speak louder than words: An elaborated theoretical model of the social functions of self-injury and other harmful behaviors. Applied and Preventive Psychology, 12(4), 159–168. https://doi.org/10.1016/j.appsy.2008.05.002

Nock, M. K. (2009). Why do people hurt themselves? New insights into the nature and functions of self-injury. Current Directions in Psychological Science, 18(2), 78–83.
https://doi.org/10.1111/j.1467-8721.2009.01613.x

Nock, M. K., & Prinstein, M. J. (2004). A functional approach to the assessment of self-mutilative behavior. Journal of Consulting and Clinical Psychology, 72(5), 885–890. https://doi.org/10.1037/0022-006X.72.5.885

Poynton, T. A., DeFouw, E. R., & Morizio, L. J. (2019). A systematic review of online response rates in four counseling journals. Journal of Counseling & Development, 97(1), 33–42. https://doi.org/10.1002/jcad.12233

Roberts-Dobie, S., & Donatelle, R. J. (2007). School counselors and student self-injury. Journal of School Health, 77(5), 257–264. https://doi.org/10.1111/j.1746-1561.2007.00201.x

Trepal, H. C., & Wester, K. L. (2007). Self-injurious behaviors, diagnoses, and treatment methods: What mental health professional are reporting. Journal of Mental Health Counseling, 29(4), 363–375.  https://doi.org/10.17744/mehc.29.4.d277t298667q5367

Walsh, B. W. (2012). Treating self-injury: A practical guide (2nd ed.). Guilford.

Walsh, B. W., & Rosen, P. (1985). Self-mutilation and contagion: An empirical test. The American Journal of Psychiatry, 142(1), 119–120. https://doi.org/10.1176/ajp.142.1.119

Washburn, J. J., Juzwin, K. R., Styer, D. M., & Aldridge, D. (2010). Measuring the urge to self-injure: Preliminary data from a clinical sample. Psychiatry Research, 178(3), 540–544.
https://doi.org/10.1016/j.psychres.2010.05.018

Wester, K., & Trepal, H. C. (2017). Non-suicidal self-injury: Wellness perspectives on behaviors, symptoms, and diagnosis. Routledge.

Wester, K., Trepal, H., & King, K. (2018). Nonsuicidal self-injury: Increased prevalence in engagement. Suicide and Life-Threatening Behavior, 48(6), 690–698. https://doi.org/10.1111/sltb.12389

White Kress, V. E. (2003). Self-injurious behaviors: Assessment and diagnosis. Journal of Counseling & Development, 81(4), 490–496. https://doi.org/10.1002/j.1556-6678.2003.tb00276.x

Whitlock, J., Exner-Cortens, D., & Purington, A. (2014). Assessment of nonsuicidal self-injury: Development and initial validation of the Non-Suicidal Self-Injury–Assessment Tool (NSSI-AT). Psychological Assessment, 26(3), 935–946. https://doi.org/10.1037/a0036611

World Health Organization. (2018). International statistical classification of diseases and related health problems (11th Revision). https://icd.who.int/en

 

Amanda Giordano, PhD, LPC, is an assistant professor at the University of Georgia. Lindsay A. Lundeen, MS, NCC, is a doctoral student at the University of Georgia. Chelsea M. Scoffone, MEd, is a doctoral student at the University of Georgia. Erin P. Kilpatrick, MS, NCC, LPC, is a doctoral student at the University of Georgia. Frank B. Gorritz, MS, NCC, is a doctoral student at the University of Georgia. Correspondence may be addressed to Amanda Giordano, 422G Aderhold Hall, 110 Carlton Street, Athens, GA 30602, amanda.giordano@uga.edu.