American Journal of Orthopsychiatry 2014, Vol. 84, No. 5, 545–556
© 2014 American Orthopsychiatric Association http://dx.doi.org/10.1037/ort0000008
A Compensatory Model of Risk and Resilience Applied to Adolescent Sexual Orientation Disparities in Nonsuicidal Self-Injury and Suicide Attempts Sari L. Reisner and Katie Biello
Nicholas S. Perry
This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
Harvard School of Public Health and Fenway Health, Boston, Massachusetts
Fenway Health, Boston, Massachusetts and University of Utah
Kristi E. Gamarel
Matthew J. Mimiaga
City University of New York
Harvard School of Public Health, Fenway Health, Boston, Massachusetts, and Harvard Medical School/ Massachusetts General Hospital, Boston, Massachusetts
This study investigated and applied a compensatory model of risk and resilience to differences in past-year nonsuicidal self-injury (NSSI) and suicide attempts by sexual orientation using representative data from the 2007 Massachusetts Youth Risk Behavior Survey (n ⫽ 3,131). Self-identified lesbian, gay, bisexual, and questioning (LGBQ) adolescents comprised 7% of the sample, but accounted for 67% of NSSI and 80% of suicide attempts. Compared with heterosexuals, LGBQ adolescents had an increased odds of NSSI (adjusted Odds Ratio (aOR) ⫽ 2.76; 95% Confidence Interval (CI) [2.00, 3.81] and suicide attempts (aOR ⫽ 2.73; 95% CI [1.47, 5.08]. NSSI was highly associated with suicidality (aOR ⫽ 10.87; 95% CI [6.17, 19.18]. Family support was independently associated with a decreased odds of both NSSI (aOR ⫽ 0.56; 95% CI [0.35, 0.89] and suicidality (aOR ⫽ 0.48; 95% CI [0.29, 0.79] supporting a compensatory model of resilience. Screening and preventive interventions for LGBQ adolescents are warranted, including at the family level. Sexual orientation should be included as a standard demographic to monitor health disparities.
I
Self-harming behavior has largely been considered a behavioral symptom associated with emotional distress, rather than a unique psychiatric diagnosis within the Diagnostic and Statistical Manual of Mental Disorders-Text Revised (American Psychiatric Association, 2000; DSM–IV–TR). Information about diagnostic correlates of deliberate self-harm is currently lacking (Nock, Joiner, Gordon, LloydRichardson, & Prinstein, 2006). Until very recently, the DSM had only listed nonsuicidal self-injury as a symptom of borderline personality disorder (American Psychiatric Association, 2000). However, research indicates that NSSI also frequently occurs in individuals with other psychopathology, such as major depression, leading some to call for its consideration as a distinct psychiatric syndrome (Muehlenkamp, 2005). Currently, the DSM-5 (American Psychiatric Association, 2013) lists NSSI as a syndrome in need of further empirical attention before it can be classified as a distinct disorder. Therefore, documenting its prevalence and psychosocial correlates in diverse populations is especially valuable.
n recent years, research on the broad symptom class of selfharming behaviors has both grown and become more sophisticated. As this body of literature has increased, scientists and clinicians have taken greater care to label and investigate such behaviors with more specificity. Within the overarching category of deliberate self-harm, researchers have begun to more clearly distinguish between self-harm with and without suicidal intent. Nonsuicidal selfinjury (NSSI) has been classified (Nock, Prinstein, & Sterba, 2009; p. 816) as “direct and deliberate destruction of body tissue in the absence of observable intent to die.” In contrast, suicidal phenomena can include thoughts (i.e., suicidal ideation), planning, and attempts, all of which encompass some intent to die.
This article was published Online First August 4, 2014. Sari L. Reisner and Katie Biello, Department of Epidemiology, Harvard School of Public Health and The Fenway Institute, Fenway Health, Boston, Massachusetts; Nicholas S. Perry, The Fenway Institute, Fenway Health and Department of Psychology, University of Utah; Kristi E. Gamarel, Basic and Applied Social Psychology, Graduate Center at the City University of New York (CUNY); Matthew J. Mimiaga, Department of Epidemiology, Harvard School of Public Health, The Fenway Institute, Fenway Health, and Department of Psychiatry, Harvard Medical School/ Massachusetts General Hospital, Boston, Massachusetts. Correspondence concerning this article should be addressed to Sari L. Reisner, The Fenway Institute, Fenway Health, 1340 Boylston Street, 8th Floor, Boston, MA 02215. E-mail: [email protected]
Nonsuicidal Self-Injury NSSI is a prevalent and complex behavioral problem (Klonsky, 2007; Klonsky & Muehlenkamp, 2007; Nock, 2010; Nock et al., 2006; Nock et al., 2009; Prinstein, 2008). Associated behaviors can include cutting, burning, severe scratching, and hitting, all without fatal intent (Favazza, 1998; Klonsky, 2007; Muehlen545
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kamp, 2005), although its definition specifically excludes culturally sanctioned body modification procedures, such as tattooing or piercing. In the United States, between 1% and 4% of adults and 13%–23% of adolescents report a lifetime history of NSSI (see Jacobson & Gould, 2007 for a review). Estimates of the prevalence of NSSI vary considerably depending on the definition and measurement used to assess self-harm behaviors, as well as on the study design and population sampled (Briere & Gil, 1998; Favazza, 1998; Gratz, 2001; Klonsky, Oltmanns, & Turkheimer, 2003; Muehlenkamp, 2005; Shaffer & Jacobson, 2009; Whitlock, Eckenrode, & Silverman, 2006). In the general population in the United States, the strongest correlates of NSSI are psychiatric disorders and other comorbid presenting mental health concerns, including but not limited to, depression (Klonsky & Olino, 2008; Muehlenkamp, 2005; Nock, 2010). Importantly, NSSI behaviors evidence considerable heterogeneity and do not appear to pattern along a single psychiatric disorder (Nock et al., 2006). This makes understanding the full complexity of NSSI especially difficult and encourages investigation across populations that may be at particular risk, such as adolescents, and in settings where risk can develop, such as in school systems. Nonprobability sample studies document high prevalence of NSSI behaviors among lesbian, gay, bisexual, and questioning (LGBQ; also referred to as sexual minority) adolescents (Blosnich & Bossarte, 2012; Deliberto & Nock, 2008; Liu & Mustanski, 2012; Whitlock et al., 2006). However, very little representative research (Skegg, Nada-Raja, Dickson, Paul, & Williams, 2003) to date has documented the prevalence of NSSI among LGBQ adolescent populations. One notable methodological weakness of such studies employing convenience sampling is the limitations placed on their generalizability. Further, few studies have been conducted with LGBQ teens, especially while comparing them to their nonsexual minority peers on prevalence of NSSI (Blosnich & Bossarte, 2012; Deliberto & Nock, 2008; Whitlock et al., 2006). Moreover, no studies using population-based samples to our knowledge have examined nonsuicidal self-injury disparities among LGBQ adolescents in relation to suicide attempts. Given these sampling concerns and the well-documented association between the two types of self-injurious behaviors (suicidal and nonsuicidal) in the general population, these are notable limitations of previous research. In addition to self-harming behaviors (i.e., NSSI, suicidality), sexual minority adolescents have been indicated to be at higher risk for a range of psychosocial problems, including depression, alcohol and substance misuse, and experiencing violence and bullying (Mustanski, Garofalo, Herrick, & Donenberg, 2007; Ryan, Huebner, Diaz, & Sanchez, 2009). These psychosocial health problems have been demonstrated to both frequently cooccur and interact with one another to negatively impact health among LGBQ individuals (Mustanski et al., 2007; Stall et al., 2003).
Suicide Attempts In the United States, suicide among young people represents a serious public health concern. This concern is clearly warranted as suicide is the third leading cause of death among youth ages 15–24 in the United States (CDC, 2010). A recent review of the research
further demonstrates that suicide is a global health problem among adolescents (Nock et al., 2008). Recently, both the scientific literature (Haas et al., 2010; Plöderl et al., 2013) and the popular media (Rovzar, 2010) have evidenced growing concern over the heightened risk for suicide among LGBQ young people. Sexual minority adolescents represent a critical population for understanding the occurrence of suicidal behaviors, given their vulnerability to both typical developmental stressors such as experimentation with substance use and psychological distress, and minority-specific stressors, such as discrimination or bullying (Meyer, 2003). A large number of studies with youth have documented elevated rates of suicidality among LGBQ individuals compared with heterosexuals, using a range of sampling methods. For example, using a representative sample of youth in Oregon, Hatzenbuehler (2011) found prevalence of suicide attempts to be elevated among LGBQ youths (21.5%) compared with heterosexual peers (4.2%). Although prevalence has varied across studies, both population-based (Bontempo & D’Augelli, 2002; Garofalo, Wolf, Kessel, Palfrey, & DuRant, 1998; Remafedi, French, Story, Resnick, & Blum, 1998; Russell & Joyner, 2001) and convenience samples (D’Augelli, 2002; Remafedi, Farrow, & Deisher, 1991; Safren & Heimberg, 1999) have consistently demonstrated large disparities for sexual minorities.
Need to Consider Protective Factors: Resilience Resources Despite a robust literature documenting increased risk for certain negative health outcomes in LGBQ adolescents, the vast majority of sexual minority youth are resilient to these risk factors and follow healthy developmental trajectories (Savin-Williams, 2001). To better explore the emergence of positive outcomes despite evident adversity, calls have been made to build research on how protective factors may encourage resilience and decrease risk among LGBQ youth (Herrick, Stall, Goldhammer, Egan, & Mayer, 2014; Mustanski, Newcomb, & Garofalo, 2011; Wexler, DiFluvio, & Burke, 2009). A fuller understanding of the social environment surrounding these processes may be particularly important for at-risk adolescents, as youth are uniquely dependent on and accountable to the social systems (e.g., families, schools, peer groups) surrounding them (Bronfenbrenner, 1994). However, few studies to date have examined how these risk and resilience factors simultaneously potentiate one another and interact with the environmental context LGBQ adolescents live in. Resilience resources have been defined as positive factors that are external to the individual and that help youth overcome risk (Fergus & Zimmerman, 2005). Examples of these external resources are having family support, having a supportive adult in school or adult mentor, community engagement (e.g., volunteering, participating in clubs and extracurricular activities), and positive peer engagement (e.g., sports team involvement), all of which have been found to moderate risk in youth generally (Blum, McNeely, & Nonnemaker, 2002). Indeed, there is evidence that various resilience resources positively influence the healthy development of sexual minority youth. For example, acceptance following adolescents disclosing their sexual orientation to their family has been associated with reduced depressive symptoms and suicidal ideation and increased self-esteem (Ryan, Russell, Huebner, Diaz, & Sanchez, 2010). Similarly, supportive school environ-
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LGBQ DISPARITIES IN NSSI AND SUICIDE
ments have been documented to support the well-being of sexual minority youth (Birkett, Espelage, & Koeing, 2009). Other commonly protective sources of resilience (e.g., positive peer relationships, community involvement) have not been as well explored among sexual minority youth (Saewyc, 2011). However, the converse of many of these (e.g., peer victimization, family rejection) has been examined as risk factors (Bontempo & D’Augelli, 2002; D’Augelli, Hershberger, & Pilington, 1998; D’Augelli, Pilington, & Hershberger, 2002; Ryan et al., 2009). This absence in the literature further highlights the need to expand our understanding of common resilience resources among minority youth in a fully contextualized risk and resilience perspective (Herrick et al., 2014; Savin-Williams, 2001). Resilience resources are defined as theoretically distinct from assets, which refer to promotive positive factors that reside within the individual (i.e., individual differences). Examples of promotive positive factors include competency, coping skills, and selfefficacy (Fergus & Zimmerman, 2005). We focus on resilience resources available to youth, as identifying such resources is consistent with an ecological approach and focuses on the contextual systems surrounding the adolescent that may be intervened upon. Further, individual differences in coping skills, such as emotion regulation, improve with cognitive development (Lewis & Stieben, 2004). These person-centered protective factors (i.e., skills) are also likely to be most protective in the presence of supportive environments where resilience resources are high (i.e., sensitivity to context; Belsky & Pluess, 2009). Therefore, identifying modifiable environmental influences (e.g., family, school, and peer support) for vulnerable adolescents that will promote healthy growth is likely to be a broadly beneficial strategy for youth.
Study Aims and Hypotheses The current study sought to address several gaps (noted above) in the current research literature. First, we examined evidence for disparities in nonsuicidal self-injury and suicidal behaviors among LGBQ adolescents using a large representative sample of high school students in Massachusetts. Past research has called for a better examination of the role of common developmental risk factors within LGBQ youth (Diamond, 2003), noting that sexual orientation is only one of several prominent individual differences that may influence health outcomes in young people. Acknowledging this concern, we further evaluated several broad risk factors for self-harm documented in the general literature on nonsuicidal self-injury in adolescents, namely sex, grade-level, psychological distress, alcohol use, and bullying (Prinstein, 2008). Additionally, we examined self-harm outcomes in relation to well-known sources of resilience, including school support, family support, community engagement, and peer groups (i.e., participation in athletics). Several models of resilience have been proposed in adolescent health (for review see Fergus & Zimmerman, 2005). In the current study, we test a compensatory model, defined as when a factor that increases resilience counteracts or operates in the opposite direction of a risk factor. Thus, conceptually and statistically (see Figure 1), compensatory models involve the direct effect of a promotive factor on an outcome independent of the direct effect of a risk factor. Lastly we examined nonsuicidal self-injury in relation to suicide attempts to explore the potential for intersecting dispar-
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Figure 1. Compensatory model of risk and resilience.
ities among LGBQ adolescents across the spectrum of selfinjurious behaviors and to clarify their specificity, as few studies have examined both behaviors together (Blosnich & Bossarte, 2012; House, Van Horn, Coppeans, & Steplman, 2011). We hypothesized that, relative to same-age heterosexual peers, LGBQ adolescents would evidence greater risk for nonsuicidal self-injury. We then anticipated that, when controlling for individual risk factors, resilience resources would be protective for deliberate self-harm behaviors among LGBQ teens. Lastly, we expected that nonsuicidal self-injury would be associated with increased risk for suicide attempts among LGBQ adolescents and, further, that NSSI would explain some of the increased risk for suicide attempts among sexual minority youth.
Method Study Sample and Procedures The Massachusetts Youth Risk Behavior Survey (MYRBS) is conducted every 2 years by the Massachusetts Department of Elementary and Secondary Education (ESE), in conjunction with the Massachusetts Department of Public Health, and with funding from the Centers for Disease Control and Prevention (CDC). The survey monitors risk behaviors related to the leading causes of morbidity and mortality in the United States among youth. This anonymous survey includes questions about tobacco use, alcohol and other drug use, sexual behaviors that might lead to unintended pregnancy or sexually transmitted diseases, dietary behaviors, physical activity, and behaviors associated with intentional or unintentional injuries. Since 1993, the MYRBS has surveyed public high school students from a scientifically selected random sample of schools across the Commonwealth of Massachusetts (CDC, 2013). The CDC selected a probability-proportionate-to-size random sample of public high schools (schools with at least one of Grades 9 through 12). In the sampled schools, six classes were randomly selected; three were then randomly assigned to receive the MYRBS. Trained survey administrators administered the surveys in the participating schools. Data were collected from over 3,000 high school students within 59 schools for the MYRBS. The overall response rate (Student Response Rate ⫻ School Response Rate) was 73% for the MYRBS. Data from the MYRBS, using appropriate weighted estimates, provide accurate estimates of the prevalence of risk behaviors among public high school students in the Commonwealth of Massachusetts (MDPH, 2008). Additional
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REISNER, BIELLO, PERRY, GAMAREL, AND MIMIAGA
documentation concerning weighting procedures have been described in detail elsewhere (CDC, 2007).
was summed to create an index of resilience resources (e.g., protective buffers) ranging from 0 to 4. Participants were classified as having low (0 or 1), medium (2), or high (3– 4) support.
Measures
Sociodemographic covariates. Factors adjusted for were sex (female/male), grade level (lower Grades 9th/10th vs. upper Grades 11th/12th), and race/ethnicity (White non-Hispanic vs. racial/ ethnic minority; American Indian/Alaskan Native, Asian, Black or African American, Native Hawaiian/other Pacific Islander, Hispanic/ Latino, and multiracial). Participants were classified as White nonHispanic or racial/ethnic minority to allow for adequate statistical power to examine differences by sexual orientation.
Deliberate self-harm behaviors and attempted suicide, last 12 months. Two indicators of deliberate selfharm were the focus of this article. First, participants were asked about NSSI in the past 12 months: “During the past 12 months, how many times did you do something to purposely hurt or injure yourself without wanting to die, such as cutting, burning, or bruising yourself on purpose?” Response options were 0 times, 1–2 times, 3–5 times, 6 –9 times, 10 –19 times, 20 or more times. Participants were dichotomized as having engaged in self-harm behaviors in the past 12 months (1 or more times) or not (zero times). This binary variable was created to indicate a positive screen for NSSI behavior and identify youth who may need additional psychosocial assessment and/or targeted interventions (Nixon & Heath, 2009). Second, a single item question queried respondents as to whether they had ever made a suicide attempt in the last 12 months. Sexual orientation identity. Sexual orientation was assessed using an identity question: “Which of the following best describes you?” Response options were heterosexual (straight), gay or lesbian, bisexual, or not sure. Because of sample size considerations, and to ensure adequate power for subsequent statistical modeling procedures (e.g., 80%⫹ power), students were categorized as having a sexual minority orientation (lesbian, gay, bisexual, or questioning; LGBQ) or not (heterosexual). Resilience resources: Supportive and protective factors. Four domains of resilience resources were investigated. (a) Family support—One item evaluated family support: “Can you talk with at least one of your parents or other adult family members about things that are important to you?” Youth who responded affirmatively were considered to have family support; those who responded negatively were considered to not have any family support. (2) School support—A single item assessed whether students felt they had a supportive adult in the school context: “Is there at least one teacher or other adult in this school that you can talk to if you have a problem?” Participants who responded “yes” were categorized as having a supportive adult in school; youth who responded “no” did not have school support. (c) Community engagement—To assess community engagement, participants were queried about their involvement in organized activities: “On how many of the past 7 days did you take part in organized afterschool, evening, or weekend activities (such as school clubs; community center groups; music, art, or dance lessons; drama; church; or other supervised activities)?” Participants who reported taking part in an organized afterschool, evening, or weekend activity on one or more of the past 7 days were considered to be community engaged; those who reported zero days of involvement in the past week were not. (d) Sports teams—To evaluate involvement in sports teams as a potential protective factor, students were asked: “During the past 12 months, on how many sports teams did you play?” Participants who responded they played on one or more teams were considered involved in sports; those who played on zero teams were not. The number of supports students endorsed
Risk factors. Three risk factors were included: (a) Binge drinking, last 30 days—“During the past 30 days, on how many days did you have 5 or more drinks of alcohol in a row, that is, within a couple of hours?” Responses ranged from 0 days to 20 or more days. A binary indicator of binge drinking was created, such that participants who reported 5 or more drinks of alcohol in a row on one or more days were classified as having binge drank in the past 30 days, whereas those who did not were not classified as having binge drank. (b) Bullying, past 12 months—“During the past 12 months, how many times have you been bullied at school?” Response options ranged from 0 times to 12 or more times. Participants were classified as having been bullied (1 or more times) versus not (zero times). (c) Depressive distress, past 12 months—Participants were asked a single-item screening question to assess depressed mood: “During the past 12 months, did you ever feel so sad or hopeless almost every day for 2 weeks or more in a row that you stopped doing some usual activities?” Response options given were dichotomous yes or no.
Data Analysis SAS® version 9.3 statistical software was used to analyze data. Distributions of individual items were assessed, including missingness. Although ⬍ 10% of the sample were missing on variables included in the analysis, LGBQ respondents were more likely to have missing item-level data than heterosexual respondents, violating the missing completely at random assumption required for valid statistical inferences using listwise deletion (Allison, 2001). Data were therefore multiply imputed. A fully conditional specification (FCS; Van Buuren, 2007; Van Buuren, Brand, Groothuis-Oudshoorn, & Rubin, 2006), or “chained equations” (Lee & Carlin, 2010), imputation method was used (20 burns), implemented in PROC MI with the FCS statement. FCS is a semiparametric and flexible imputation procedure that specifies the multivariable model by a series of conditional models, one for each incomplete variable (Van Buuren, 2007; Van Buuren, et al., 2006). All subsequent statistical analyses were conducted in the imputed dataset. The final data analytic sample was comprised of 3,131 high school youth. The primary outcomes dichotomously assessed were self-harm behaviors in the last 12 months and suicide attempt in the same timeframe. For all analyses, statistical significance was predetermined at ␣ ⬍ .05. Descriptive statistics were obtained for all variables included in the analysis. Bivariate associations were obtained for the primary independent variable of interest and all covariates and potential confounders by sexual orientation. Proportional differences were examined using chi square tests or Fisher’s exact test when appropri-
LGBQ DISPARITIES IN NSSI AND SUICIDE
ate. The PROC SURVEYLOGISTIC procedure in SAS was used to fit a taxonomy of regression models to investigate the proposed study hypotheses. PROC SURVEYLOGISTIC estimates binomial logistic regression models for discrete response survey data by the method of maximum likelihood and incorporates complex survey sample designs, including weighting to allow for statistically valid inferences. All estimated models were appropriately weighted to account for MYRBS survey design and sampling procedures. Additional documentation concerning YRBS weighting have been described in detail elsewhere (CDC, 2013; MDPH, 2008).
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Results Characteristics of the sample are shown in Table 1, stratified by sexual orientation identity. Overall, 7.2% of youth self-identified as LGBQ. A significantly higher proportion of LGBQ versus
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heterosexual adolescents reported past-year self-harm behaviors (46.4% vs. 15.3%) and suicide attempt (20.1% vs. 4.1%).
Nonsuicidal Self-Injury, Last 12 Months Table 2 presents bivariate and Table 3 presents multivariable models. LGBQ youth had an 4.59 increased odds of self-harm compared to heterosexual youth, adjusting for demographic characteristics (Model 1) and a 2.76 increased odds of self-harm when additionally controlling for known risk factors (Model 2). Family support was associated with a decreased odds of engaging in self-harm behaviors (Model 3), as was the number of supports (Models 4 and 5). However, the disparity in self-harm behaviors by sexual orientation identity remained robust, despite adjusting for protective factors.
Table 1. 2007 Massachusetts Youth Risk Behavior Survey (N ⫽ 3,131)
Resilience resources School support Family support Community engagement Sports teams Number resilience resources 0 1 2 3 4 Low, medium, high protective Low (0 or 1 buffers) Med (2 buffers) High (3 or 4 buffers) Self-harm behaviors, past 12 months No self-harm Any self-harm 1–5 episodes 6–20⫹ episodes Suicide attempts, past 12 months Any suicide attempt Covariates and confounders Grade Lower class (9th and 10th) Upper class (11th and 12th) Sex Female Male Race White Racial/ethnic minority Black Hispanic/Latino Asian/NH/PI Other race/ethnicity Bullying, binge drinking, distress Bullied Binge drinking Psychological distress
LGBQ 7.2%
Heterosexual 92.8%
p value
Total sample
58.2 62.6 50.8 39.8
70.0 84.7 51.8 60.8
.002 ⬍.0001 .806 ⬍.0001 ⬍.0001
69.1 83.1 51.7 59.3
6.0 22.8 37.3 21.7 12.2
2.7 12.4 25.9 32.9 26.1
28.8 37.3 33.9
15.1 25.9 59.0
Ref. .217 ⬍.0001
16.1 26.7 57.2
53.6
84.7
⬍.0001
82.5
21.9 24.5
10.7 4.5
⬍.0001 ⬍.0001
11.5 6.0
20.1
4.1
⬍.0001
20.1
57.4 42.6
52.6 47.4
60.8 39.2
48.4 51.6
64.2 35.8 7.6 15.2 5.4 7.7
73.1 26.9 8.3 12.0 3.2 3.3
Ref. .947 .045 .003 .081
72.5 27.5 8.3 12.2 3.4 3.7
39.5 43.3 54.4
21.3 27.1 21.9
⬍.0001 ⬍.0001 ⬍.0001
22.6 28.3 24.3
3.0 13.1 26.7 32.5 25.1
.309 52.9 47.1 .002 49.3 50.7
REISNER, BIELLO, PERRY, GAMAREL, AND MIMIAGA
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Table 2. Bivariable Models for Past 12-Month Self-Harm (N ⫽ 3,131)
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Unadjusted models
Sexual orientation identity LGBQ Demographic covariates Lower class (Grades 9th/10th) Female White race Risk factors Bullied Binge drinking Psychological distress Resilience resources School support Family support Community engagement Sports teams Number resilience resources (0–4) Number of resilience resources Support Low (0 or 1 buffers) Med (2 buffers) High (3 or 4 buffers) Note.
Crude OR [95% CI]
p value
4.81 [3.74, 6.19]
© 2014 American Orthopsychiatric Association http://dx.doi.org/10.1037/ort0000008
A Compensatory Model of Risk and Resilience Applied to Adolescent Sexual Orientation Disparities in Nonsuicidal Self-Injury and Suicide Attempts Sari L. Reisner and Katie Biello
Nicholas S. Perry
This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
Harvard School of Public Health and Fenway Health, Boston, Massachusetts
Fenway Health, Boston, Massachusetts and University of Utah
Kristi E. Gamarel
Matthew J. Mimiaga
City University of New York
Harvard School of Public Health, Fenway Health, Boston, Massachusetts, and Harvard Medical School/ Massachusetts General Hospital, Boston, Massachusetts
This study investigated and applied a compensatory model of risk and resilience to differences in past-year nonsuicidal self-injury (NSSI) and suicide attempts by sexual orientation using representative data from the 2007 Massachusetts Youth Risk Behavior Survey (n ⫽ 3,131). Self-identified lesbian, gay, bisexual, and questioning (LGBQ) adolescents comprised 7% of the sample, but accounted for 67% of NSSI and 80% of suicide attempts. Compared with heterosexuals, LGBQ adolescents had an increased odds of NSSI (adjusted Odds Ratio (aOR) ⫽ 2.76; 95% Confidence Interval (CI) [2.00, 3.81] and suicide attempts (aOR ⫽ 2.73; 95% CI [1.47, 5.08]. NSSI was highly associated with suicidality (aOR ⫽ 10.87; 95% CI [6.17, 19.18]. Family support was independently associated with a decreased odds of both NSSI (aOR ⫽ 0.56; 95% CI [0.35, 0.89] and suicidality (aOR ⫽ 0.48; 95% CI [0.29, 0.79] supporting a compensatory model of resilience. Screening and preventive interventions for LGBQ adolescents are warranted, including at the family level. Sexual orientation should be included as a standard demographic to monitor health disparities.
I
Self-harming behavior has largely been considered a behavioral symptom associated with emotional distress, rather than a unique psychiatric diagnosis within the Diagnostic and Statistical Manual of Mental Disorders-Text Revised (American Psychiatric Association, 2000; DSM–IV–TR). Information about diagnostic correlates of deliberate self-harm is currently lacking (Nock, Joiner, Gordon, LloydRichardson, & Prinstein, 2006). Until very recently, the DSM had only listed nonsuicidal self-injury as a symptom of borderline personality disorder (American Psychiatric Association, 2000). However, research indicates that NSSI also frequently occurs in individuals with other psychopathology, such as major depression, leading some to call for its consideration as a distinct psychiatric syndrome (Muehlenkamp, 2005). Currently, the DSM-5 (American Psychiatric Association, 2013) lists NSSI as a syndrome in need of further empirical attention before it can be classified as a distinct disorder. Therefore, documenting its prevalence and psychosocial correlates in diverse populations is especially valuable.
n recent years, research on the broad symptom class of selfharming behaviors has both grown and become more sophisticated. As this body of literature has increased, scientists and clinicians have taken greater care to label and investigate such behaviors with more specificity. Within the overarching category of deliberate self-harm, researchers have begun to more clearly distinguish between self-harm with and without suicidal intent. Nonsuicidal selfinjury (NSSI) has been classified (Nock, Prinstein, & Sterba, 2009; p. 816) as “direct and deliberate destruction of body tissue in the absence of observable intent to die.” In contrast, suicidal phenomena can include thoughts (i.e., suicidal ideation), planning, and attempts, all of which encompass some intent to die.
This article was published Online First August 4, 2014. Sari L. Reisner and Katie Biello, Department of Epidemiology, Harvard School of Public Health and The Fenway Institute, Fenway Health, Boston, Massachusetts; Nicholas S. Perry, The Fenway Institute, Fenway Health and Department of Psychology, University of Utah; Kristi E. Gamarel, Basic and Applied Social Psychology, Graduate Center at the City University of New York (CUNY); Matthew J. Mimiaga, Department of Epidemiology, Harvard School of Public Health, The Fenway Institute, Fenway Health, and Department of Psychiatry, Harvard Medical School/ Massachusetts General Hospital, Boston, Massachusetts. Correspondence concerning this article should be addressed to Sari L. Reisner, The Fenway Institute, Fenway Health, 1340 Boylston Street, 8th Floor, Boston, MA 02215. E-mail: [email protected]
Nonsuicidal Self-Injury NSSI is a prevalent and complex behavioral problem (Klonsky, 2007; Klonsky & Muehlenkamp, 2007; Nock, 2010; Nock et al., 2006; Nock et al., 2009; Prinstein, 2008). Associated behaviors can include cutting, burning, severe scratching, and hitting, all without fatal intent (Favazza, 1998; Klonsky, 2007; Muehlen545
This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
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REISNER, BIELLO, PERRY, GAMAREL, AND MIMIAGA
kamp, 2005), although its definition specifically excludes culturally sanctioned body modification procedures, such as tattooing or piercing. In the United States, between 1% and 4% of adults and 13%–23% of adolescents report a lifetime history of NSSI (see Jacobson & Gould, 2007 for a review). Estimates of the prevalence of NSSI vary considerably depending on the definition and measurement used to assess self-harm behaviors, as well as on the study design and population sampled (Briere & Gil, 1998; Favazza, 1998; Gratz, 2001; Klonsky, Oltmanns, & Turkheimer, 2003; Muehlenkamp, 2005; Shaffer & Jacobson, 2009; Whitlock, Eckenrode, & Silverman, 2006). In the general population in the United States, the strongest correlates of NSSI are psychiatric disorders and other comorbid presenting mental health concerns, including but not limited to, depression (Klonsky & Olino, 2008; Muehlenkamp, 2005; Nock, 2010). Importantly, NSSI behaviors evidence considerable heterogeneity and do not appear to pattern along a single psychiatric disorder (Nock et al., 2006). This makes understanding the full complexity of NSSI especially difficult and encourages investigation across populations that may be at particular risk, such as adolescents, and in settings where risk can develop, such as in school systems. Nonprobability sample studies document high prevalence of NSSI behaviors among lesbian, gay, bisexual, and questioning (LGBQ; also referred to as sexual minority) adolescents (Blosnich & Bossarte, 2012; Deliberto & Nock, 2008; Liu & Mustanski, 2012; Whitlock et al., 2006). However, very little representative research (Skegg, Nada-Raja, Dickson, Paul, & Williams, 2003) to date has documented the prevalence of NSSI among LGBQ adolescent populations. One notable methodological weakness of such studies employing convenience sampling is the limitations placed on their generalizability. Further, few studies have been conducted with LGBQ teens, especially while comparing them to their nonsexual minority peers on prevalence of NSSI (Blosnich & Bossarte, 2012; Deliberto & Nock, 2008; Whitlock et al., 2006). Moreover, no studies using population-based samples to our knowledge have examined nonsuicidal self-injury disparities among LGBQ adolescents in relation to suicide attempts. Given these sampling concerns and the well-documented association between the two types of self-injurious behaviors (suicidal and nonsuicidal) in the general population, these are notable limitations of previous research. In addition to self-harming behaviors (i.e., NSSI, suicidality), sexual minority adolescents have been indicated to be at higher risk for a range of psychosocial problems, including depression, alcohol and substance misuse, and experiencing violence and bullying (Mustanski, Garofalo, Herrick, & Donenberg, 2007; Ryan, Huebner, Diaz, & Sanchez, 2009). These psychosocial health problems have been demonstrated to both frequently cooccur and interact with one another to negatively impact health among LGBQ individuals (Mustanski et al., 2007; Stall et al., 2003).
Suicide Attempts In the United States, suicide among young people represents a serious public health concern. This concern is clearly warranted as suicide is the third leading cause of death among youth ages 15–24 in the United States (CDC, 2010). A recent review of the research
further demonstrates that suicide is a global health problem among adolescents (Nock et al., 2008). Recently, both the scientific literature (Haas et al., 2010; Plöderl et al., 2013) and the popular media (Rovzar, 2010) have evidenced growing concern over the heightened risk for suicide among LGBQ young people. Sexual minority adolescents represent a critical population for understanding the occurrence of suicidal behaviors, given their vulnerability to both typical developmental stressors such as experimentation with substance use and psychological distress, and minority-specific stressors, such as discrimination or bullying (Meyer, 2003). A large number of studies with youth have documented elevated rates of suicidality among LGBQ individuals compared with heterosexuals, using a range of sampling methods. For example, using a representative sample of youth in Oregon, Hatzenbuehler (2011) found prevalence of suicide attempts to be elevated among LGBQ youths (21.5%) compared with heterosexual peers (4.2%). Although prevalence has varied across studies, both population-based (Bontempo & D’Augelli, 2002; Garofalo, Wolf, Kessel, Palfrey, & DuRant, 1998; Remafedi, French, Story, Resnick, & Blum, 1998; Russell & Joyner, 2001) and convenience samples (D’Augelli, 2002; Remafedi, Farrow, & Deisher, 1991; Safren & Heimberg, 1999) have consistently demonstrated large disparities for sexual minorities.
Need to Consider Protective Factors: Resilience Resources Despite a robust literature documenting increased risk for certain negative health outcomes in LGBQ adolescents, the vast majority of sexual minority youth are resilient to these risk factors and follow healthy developmental trajectories (Savin-Williams, 2001). To better explore the emergence of positive outcomes despite evident adversity, calls have been made to build research on how protective factors may encourage resilience and decrease risk among LGBQ youth (Herrick, Stall, Goldhammer, Egan, & Mayer, 2014; Mustanski, Newcomb, & Garofalo, 2011; Wexler, DiFluvio, & Burke, 2009). A fuller understanding of the social environment surrounding these processes may be particularly important for at-risk adolescents, as youth are uniquely dependent on and accountable to the social systems (e.g., families, schools, peer groups) surrounding them (Bronfenbrenner, 1994). However, few studies to date have examined how these risk and resilience factors simultaneously potentiate one another and interact with the environmental context LGBQ adolescents live in. Resilience resources have been defined as positive factors that are external to the individual and that help youth overcome risk (Fergus & Zimmerman, 2005). Examples of these external resources are having family support, having a supportive adult in school or adult mentor, community engagement (e.g., volunteering, participating in clubs and extracurricular activities), and positive peer engagement (e.g., sports team involvement), all of which have been found to moderate risk in youth generally (Blum, McNeely, & Nonnemaker, 2002). Indeed, there is evidence that various resilience resources positively influence the healthy development of sexual minority youth. For example, acceptance following adolescents disclosing their sexual orientation to their family has been associated with reduced depressive symptoms and suicidal ideation and increased self-esteem (Ryan, Russell, Huebner, Diaz, & Sanchez, 2010). Similarly, supportive school environ-
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LGBQ DISPARITIES IN NSSI AND SUICIDE
ments have been documented to support the well-being of sexual minority youth (Birkett, Espelage, & Koeing, 2009). Other commonly protective sources of resilience (e.g., positive peer relationships, community involvement) have not been as well explored among sexual minority youth (Saewyc, 2011). However, the converse of many of these (e.g., peer victimization, family rejection) has been examined as risk factors (Bontempo & D’Augelli, 2002; D’Augelli, Hershberger, & Pilington, 1998; D’Augelli, Pilington, & Hershberger, 2002; Ryan et al., 2009). This absence in the literature further highlights the need to expand our understanding of common resilience resources among minority youth in a fully contextualized risk and resilience perspective (Herrick et al., 2014; Savin-Williams, 2001). Resilience resources are defined as theoretically distinct from assets, which refer to promotive positive factors that reside within the individual (i.e., individual differences). Examples of promotive positive factors include competency, coping skills, and selfefficacy (Fergus & Zimmerman, 2005). We focus on resilience resources available to youth, as identifying such resources is consistent with an ecological approach and focuses on the contextual systems surrounding the adolescent that may be intervened upon. Further, individual differences in coping skills, such as emotion regulation, improve with cognitive development (Lewis & Stieben, 2004). These person-centered protective factors (i.e., skills) are also likely to be most protective in the presence of supportive environments where resilience resources are high (i.e., sensitivity to context; Belsky & Pluess, 2009). Therefore, identifying modifiable environmental influences (e.g., family, school, and peer support) for vulnerable adolescents that will promote healthy growth is likely to be a broadly beneficial strategy for youth.
Study Aims and Hypotheses The current study sought to address several gaps (noted above) in the current research literature. First, we examined evidence for disparities in nonsuicidal self-injury and suicidal behaviors among LGBQ adolescents using a large representative sample of high school students in Massachusetts. Past research has called for a better examination of the role of common developmental risk factors within LGBQ youth (Diamond, 2003), noting that sexual orientation is only one of several prominent individual differences that may influence health outcomes in young people. Acknowledging this concern, we further evaluated several broad risk factors for self-harm documented in the general literature on nonsuicidal self-injury in adolescents, namely sex, grade-level, psychological distress, alcohol use, and bullying (Prinstein, 2008). Additionally, we examined self-harm outcomes in relation to well-known sources of resilience, including school support, family support, community engagement, and peer groups (i.e., participation in athletics). Several models of resilience have been proposed in adolescent health (for review see Fergus & Zimmerman, 2005). In the current study, we test a compensatory model, defined as when a factor that increases resilience counteracts or operates in the opposite direction of a risk factor. Thus, conceptually and statistically (see Figure 1), compensatory models involve the direct effect of a promotive factor on an outcome independent of the direct effect of a risk factor. Lastly we examined nonsuicidal self-injury in relation to suicide attempts to explore the potential for intersecting dispar-
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Figure 1. Compensatory model of risk and resilience.
ities among LGBQ adolescents across the spectrum of selfinjurious behaviors and to clarify their specificity, as few studies have examined both behaviors together (Blosnich & Bossarte, 2012; House, Van Horn, Coppeans, & Steplman, 2011). We hypothesized that, relative to same-age heterosexual peers, LGBQ adolescents would evidence greater risk for nonsuicidal self-injury. We then anticipated that, when controlling for individual risk factors, resilience resources would be protective for deliberate self-harm behaviors among LGBQ teens. Lastly, we expected that nonsuicidal self-injury would be associated with increased risk for suicide attempts among LGBQ adolescents and, further, that NSSI would explain some of the increased risk for suicide attempts among sexual minority youth.
Method Study Sample and Procedures The Massachusetts Youth Risk Behavior Survey (MYRBS) is conducted every 2 years by the Massachusetts Department of Elementary and Secondary Education (ESE), in conjunction with the Massachusetts Department of Public Health, and with funding from the Centers for Disease Control and Prevention (CDC). The survey monitors risk behaviors related to the leading causes of morbidity and mortality in the United States among youth. This anonymous survey includes questions about tobacco use, alcohol and other drug use, sexual behaviors that might lead to unintended pregnancy or sexually transmitted diseases, dietary behaviors, physical activity, and behaviors associated with intentional or unintentional injuries. Since 1993, the MYRBS has surveyed public high school students from a scientifically selected random sample of schools across the Commonwealth of Massachusetts (CDC, 2013). The CDC selected a probability-proportionate-to-size random sample of public high schools (schools with at least one of Grades 9 through 12). In the sampled schools, six classes were randomly selected; three were then randomly assigned to receive the MYRBS. Trained survey administrators administered the surveys in the participating schools. Data were collected from over 3,000 high school students within 59 schools for the MYRBS. The overall response rate (Student Response Rate ⫻ School Response Rate) was 73% for the MYRBS. Data from the MYRBS, using appropriate weighted estimates, provide accurate estimates of the prevalence of risk behaviors among public high school students in the Commonwealth of Massachusetts (MDPH, 2008). Additional
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documentation concerning weighting procedures have been described in detail elsewhere (CDC, 2007).
was summed to create an index of resilience resources (e.g., protective buffers) ranging from 0 to 4. Participants were classified as having low (0 or 1), medium (2), or high (3– 4) support.
Measures
Sociodemographic covariates. Factors adjusted for were sex (female/male), grade level (lower Grades 9th/10th vs. upper Grades 11th/12th), and race/ethnicity (White non-Hispanic vs. racial/ ethnic minority; American Indian/Alaskan Native, Asian, Black or African American, Native Hawaiian/other Pacific Islander, Hispanic/ Latino, and multiracial). Participants were classified as White nonHispanic or racial/ethnic minority to allow for adequate statistical power to examine differences by sexual orientation.
Deliberate self-harm behaviors and attempted suicide, last 12 months. Two indicators of deliberate selfharm were the focus of this article. First, participants were asked about NSSI in the past 12 months: “During the past 12 months, how many times did you do something to purposely hurt or injure yourself without wanting to die, such as cutting, burning, or bruising yourself on purpose?” Response options were 0 times, 1–2 times, 3–5 times, 6 –9 times, 10 –19 times, 20 or more times. Participants were dichotomized as having engaged in self-harm behaviors in the past 12 months (1 or more times) or not (zero times). This binary variable was created to indicate a positive screen for NSSI behavior and identify youth who may need additional psychosocial assessment and/or targeted interventions (Nixon & Heath, 2009). Second, a single item question queried respondents as to whether they had ever made a suicide attempt in the last 12 months. Sexual orientation identity. Sexual orientation was assessed using an identity question: “Which of the following best describes you?” Response options were heterosexual (straight), gay or lesbian, bisexual, or not sure. Because of sample size considerations, and to ensure adequate power for subsequent statistical modeling procedures (e.g., 80%⫹ power), students were categorized as having a sexual minority orientation (lesbian, gay, bisexual, or questioning; LGBQ) or not (heterosexual). Resilience resources: Supportive and protective factors. Four domains of resilience resources were investigated. (a) Family support—One item evaluated family support: “Can you talk with at least one of your parents or other adult family members about things that are important to you?” Youth who responded affirmatively were considered to have family support; those who responded negatively were considered to not have any family support. (2) School support—A single item assessed whether students felt they had a supportive adult in the school context: “Is there at least one teacher or other adult in this school that you can talk to if you have a problem?” Participants who responded “yes” were categorized as having a supportive adult in school; youth who responded “no” did not have school support. (c) Community engagement—To assess community engagement, participants were queried about their involvement in organized activities: “On how many of the past 7 days did you take part in organized afterschool, evening, or weekend activities (such as school clubs; community center groups; music, art, or dance lessons; drama; church; or other supervised activities)?” Participants who reported taking part in an organized afterschool, evening, or weekend activity on one or more of the past 7 days were considered to be community engaged; those who reported zero days of involvement in the past week were not. (d) Sports teams—To evaluate involvement in sports teams as a potential protective factor, students were asked: “During the past 12 months, on how many sports teams did you play?” Participants who responded they played on one or more teams were considered involved in sports; those who played on zero teams were not. The number of supports students endorsed
Risk factors. Three risk factors were included: (a) Binge drinking, last 30 days—“During the past 30 days, on how many days did you have 5 or more drinks of alcohol in a row, that is, within a couple of hours?” Responses ranged from 0 days to 20 or more days. A binary indicator of binge drinking was created, such that participants who reported 5 or more drinks of alcohol in a row on one or more days were classified as having binge drank in the past 30 days, whereas those who did not were not classified as having binge drank. (b) Bullying, past 12 months—“During the past 12 months, how many times have you been bullied at school?” Response options ranged from 0 times to 12 or more times. Participants were classified as having been bullied (1 or more times) versus not (zero times). (c) Depressive distress, past 12 months—Participants were asked a single-item screening question to assess depressed mood: “During the past 12 months, did you ever feel so sad or hopeless almost every day for 2 weeks or more in a row that you stopped doing some usual activities?” Response options given were dichotomous yes or no.
Data Analysis SAS® version 9.3 statistical software was used to analyze data. Distributions of individual items were assessed, including missingness. Although ⬍ 10% of the sample were missing on variables included in the analysis, LGBQ respondents were more likely to have missing item-level data than heterosexual respondents, violating the missing completely at random assumption required for valid statistical inferences using listwise deletion (Allison, 2001). Data were therefore multiply imputed. A fully conditional specification (FCS; Van Buuren, 2007; Van Buuren, Brand, Groothuis-Oudshoorn, & Rubin, 2006), or “chained equations” (Lee & Carlin, 2010), imputation method was used (20 burns), implemented in PROC MI with the FCS statement. FCS is a semiparametric and flexible imputation procedure that specifies the multivariable model by a series of conditional models, one for each incomplete variable (Van Buuren, 2007; Van Buuren, et al., 2006). All subsequent statistical analyses were conducted in the imputed dataset. The final data analytic sample was comprised of 3,131 high school youth. The primary outcomes dichotomously assessed were self-harm behaviors in the last 12 months and suicide attempt in the same timeframe. For all analyses, statistical significance was predetermined at ␣ ⬍ .05. Descriptive statistics were obtained for all variables included in the analysis. Bivariate associations were obtained for the primary independent variable of interest and all covariates and potential confounders by sexual orientation. Proportional differences were examined using chi square tests or Fisher’s exact test when appropri-
LGBQ DISPARITIES IN NSSI AND SUICIDE
ate. The PROC SURVEYLOGISTIC procedure in SAS was used to fit a taxonomy of regression models to investigate the proposed study hypotheses. PROC SURVEYLOGISTIC estimates binomial logistic regression models for discrete response survey data by the method of maximum likelihood and incorporates complex survey sample designs, including weighting to allow for statistically valid inferences. All estimated models were appropriately weighted to account for MYRBS survey design and sampling procedures. Additional documentation concerning YRBS weighting have been described in detail elsewhere (CDC, 2013; MDPH, 2008).
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Results Characteristics of the sample are shown in Table 1, stratified by sexual orientation identity. Overall, 7.2% of youth self-identified as LGBQ. A significantly higher proportion of LGBQ versus
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heterosexual adolescents reported past-year self-harm behaviors (46.4% vs. 15.3%) and suicide attempt (20.1% vs. 4.1%).
Nonsuicidal Self-Injury, Last 12 Months Table 2 presents bivariate and Table 3 presents multivariable models. LGBQ youth had an 4.59 increased odds of self-harm compared to heterosexual youth, adjusting for demographic characteristics (Model 1) and a 2.76 increased odds of self-harm when additionally controlling for known risk factors (Model 2). Family support was associated with a decreased odds of engaging in self-harm behaviors (Model 3), as was the number of supports (Models 4 and 5). However, the disparity in self-harm behaviors by sexual orientation identity remained robust, despite adjusting for protective factors.
Table 1. 2007 Massachusetts Youth Risk Behavior Survey (N ⫽ 3,131)
Resilience resources School support Family support Community engagement Sports teams Number resilience resources 0 1 2 3 4 Low, medium, high protective Low (0 or 1 buffers) Med (2 buffers) High (3 or 4 buffers) Self-harm behaviors, past 12 months No self-harm Any self-harm 1–5 episodes 6–20⫹ episodes Suicide attempts, past 12 months Any suicide attempt Covariates and confounders Grade Lower class (9th and 10th) Upper class (11th and 12th) Sex Female Male Race White Racial/ethnic minority Black Hispanic/Latino Asian/NH/PI Other race/ethnicity Bullying, binge drinking, distress Bullied Binge drinking Psychological distress
LGBQ 7.2%
Heterosexual 92.8%
p value
Total sample
58.2 62.6 50.8 39.8
70.0 84.7 51.8 60.8
.002 ⬍.0001 .806 ⬍.0001 ⬍.0001
69.1 83.1 51.7 59.3
6.0 22.8 37.3 21.7 12.2
2.7 12.4 25.9 32.9 26.1
28.8 37.3 33.9
15.1 25.9 59.0
Ref. .217 ⬍.0001
16.1 26.7 57.2
53.6
84.7
⬍.0001
82.5
21.9 24.5
10.7 4.5
⬍.0001 ⬍.0001
11.5 6.0
20.1
4.1
⬍.0001
20.1
57.4 42.6
52.6 47.4
60.8 39.2
48.4 51.6
64.2 35.8 7.6 15.2 5.4 7.7
73.1 26.9 8.3 12.0 3.2 3.3
Ref. .947 .045 .003 .081
72.5 27.5 8.3 12.2 3.4 3.7
39.5 43.3 54.4
21.3 27.1 21.9
⬍.0001 ⬍.0001 ⬍.0001
22.6 28.3 24.3
3.0 13.1 26.7 32.5 25.1
.309 52.9 47.1 .002 49.3 50.7
REISNER, BIELLO, PERRY, GAMAREL, AND MIMIAGA
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Table 2. Bivariable Models for Past 12-Month Self-Harm (N ⫽ 3,131)
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Unadjusted models
Sexual orientation identity LGBQ Demographic covariates Lower class (Grades 9th/10th) Female White race Risk factors Bullied Binge drinking Psychological distress Resilience resources School support Family support Community engagement Sports teams Number resilience resources (0–4) Number of resilience resources Support Low (0 or 1 buffers) Med (2 buffers) High (3 or 4 buffers) Note.
Crude OR [95% CI]
p value
4.81 [3.74, 6.19]
