Video Abstract

Video Abstract

Close modal
OBJECTIVES:

In this study, we examine reports of exposure to suicidal behavior by youth sexual and gender identity. We explore how exposure is related to depressed mood in the context of high social support while accounting for cumulative adversity.

METHODS:

Data from a large national sample of youth aged 14 to 15 years in the United States (N = 3979) were collected online in 2018–2019.

RESULTS:

Sexual- and gender-minority youth were more likely to know someone close to them who attempted suicide, relative to cisgender heterosexual youth. Cisgender heterosexual youth were buffered from recent depressed mood when they endorsed having high social support in the context of exposure to suicidal behavior; less social support did not provide such a buffer. For cisgender sexual-minority male and female youth, exposure to suicidal behavior was related to recent depressed mood regardless of the level of social support. For gender-minority youth assigned female at birth, the combination of exposure and high social support was significantly associated with elevated depressed mood. Cumulative adversity accounted for some but not all of these relationships, indicating the influential role of exposure to suicidal behavior on depressed mood for some youth.

CONCLUSIONS:

These findings illustrate the complexities of social support and raise questions about its potential to magnify stress rather than serve as a buffer for some youth. Although findings need to be replicated, suicide prevention efforts should carefully consider how to promote resilience among these suicide-exposed sexual- and gender-minority youth who may themselves be at risk for suicidal ideation and behavior.

What’s Known on This Subject:

Exposure to suicidal behavior may negatively impact youth in a variety of ways, including mental health. This is especially important to consider in the sexual- and gender-minority community, in which marginalized groups already experience elevated rates of trauma and adversity.

What This Study Adds:

For sexual- and gender-minority youth, social support may not be universally protective. Suicide prevention should consider how to promote resilience among these youth who may be at risk for mental health outcomes after suicide exposure.

Suicide, defined as injuring oneself with the intent to die,1  is a significant public health issue. According to the Centers for Disease Control, in 2017, 1642 youth aged 13 to 17 years (7.85 per 100 000) died by suicide; and 87 236 (417.07 per 100 000) had a nonfatal self-harm injury.2  Existing research indicates that many adolescents are exposed to suicidal behavior, including knowing someone who died by suicide or made a suicide attempt.37  Indeed, 18% of adolescents nationally have had a friend who attempted suicide,8  and 9% have had a schoolmate die by suicide9  in the past 12 months. Emerging evidence also suggests that exposure to suicidal behavior may negatively impact youth, including higher risk for substance use,10,11  personal suicidal ideation and attempts,1018  self-harm,17,19  aggressive behavior,10,11  and emotional distress.10,18,20,21 

Understanding the psychosocial consequences of exposure to suicidal behavior is especially important to consider in the sexual- and gender-minority (SGM) community; lived experiences of these youth are often different from heterosexual youth because of stigma and discrimination.22  Exposure to suicidal behavior may pose particular risk for such marginalized groups who already experience elevated rates of suicidal behavior23  and associated risk factors, including depression,24,25  substance use,24,2628  and victimization.29,30  In addition, suicide prevention efforts among SGM youth have been less effective than those for heterosexual youth.31 

One factor related to suicide risk among sexual-minority youth that may also be relevant to suicide exposure is social support. SGM youth have some unique stressors when it comes to social support compared to their heterosexual counterparts. Relationships with family can be disrupted for some SGM youth, particularly during the time period around disclosure of their sexual identity.32,33  This is critical because family support is an especially relevant and important source of support for this population, even when taking into account other sources of support, such as peers and significant others.34,35  From a protective angle, SGM youth with social support (especially from parents) have less depressive symptoms and higher self-esteem, according to one study.36  Research also suggests that peer social support can moderate negative family attitudes and anxiety, as well as the link between family victimization and depression.37  Given the crucial role of social support for SGM youth,29,34,35,3846  understanding how suicide exposure impacts SGM youth and how support may moderate relationships between exposure to suicidal behavior and psychosocial functioning, including depressed mood, is a critical element to informing future effective prevention efforts for this population.

Using data from a national sample of youth aged 14 to 15 years, we examine exposure to suicidal behavior by sexual and gender identity. In this study, we also explore how exposure to suicidal behavior is related to depressed mood in the context of social support and cumulative adversity for SGM and heterosexual youth.

Growing up with Media is a national, longitudinal survey of youth designed to study sexual violence in adolescence.47,48  In addition to the original cohort recruited in 2006, a cohort of 3979 new youth 14 to 15 years of age was recruited between October 2018 and August 2019, including an oversample of SGM youth to support subgroup analyses. Data from this new cohort comprise the analytic sample for the current article. Details of the demographic characteristics of the analytic sample by exposure to suicidal behavior are provided in Table 1. Although not a representative sample, we compared sexual behavior for sexual-minority and cisgender youth, stratified by sex assigned at birth between this new cohort and data from the Youth Risk Behavior Survey (YRBS). In general, youth in the YRBS reported higher rates of ever having sex than youth in this analytic sample, whereas among youth who had ever had sex, more youth in the current sample reported recent sex compared to those in the YRBS sample. Thus, there was not a consistent pattern of bias. In comparison with 2019 census data, this analytic sample is similar to the child population in the United States in terms of race and ethnicity.49 

TABLE 1

Characteristics of Youth by Lifetime Exposure to Suicidal Behavior

CharacteristicSubgroup, nNo Exposure to Suicidal Behavior, n = 2057, % (n)Exposure to Suicidal Behavior, n = 1922, % (n)X2P
Gender and sexual identity
 Cisgender heterosexual male 641 68.5 (439) 31.5 (202) <.001 
 Cisgender sexual-minority male 805 59.0 (475) 41.0 (330)a — 
 Cisgender heterosexual female 801 55.2 (442) 44.8 (359)a — 
 Cisgender sexual-minority female 850 44.0 (374) 56.0 (476)a,b,c — 
 Gender minority AMABd 108 49.1 (53) 50.9 (55)a,b — 
 Gender minority AFABd 737 33.9 (250) 66.1 (487)a,b,c,e,f — 
Race and ethnicity     
 White 2669 51.3 (1369) 48.7 (1300) .007 
 African American 214 58.9 (126) 41.1 (88)g — 
 Mixed racial background 547 46.3 (253) 53.7 (294)g,h — 
 Other race 435 54.3 (236) 45.7 (199)i — 
 Hispanic and/or Latino ethnicity (any race) 846 53.4 (452) 46.6 (394) .26 
Family income     
 Lower than average family 931 39.1 (364) 60.9 (567) <.001 
 Similar to average family 2170 53.1 (1152) 46.9 (1018)j,k — 
 Higher than average family 741 60.9 (451) 39.1 (290)j,k — 
 Decline to answer 137 65.7 (90) 34.3 (47)j,k — 
Child age, y     
 14 1507 51.1 (770) 48.9 (737) .55 
 15 2472 52.1 (1287) 47.9 (1185) — 
CharacteristicSubgroup, nNo Exposure to Suicidal Behavior, n = 2057, % (n)Exposure to Suicidal Behavior, n = 1922, % (n)X2P
Gender and sexual identity
 Cisgender heterosexual male 641 68.5 (439) 31.5 (202) <.001 
 Cisgender sexual-minority male 805 59.0 (475) 41.0 (330)a — 
 Cisgender heterosexual female 801 55.2 (442) 44.8 (359)a — 
 Cisgender sexual-minority female 850 44.0 (374) 56.0 (476)a,b,c — 
 Gender minority AMABd 108 49.1 (53) 50.9 (55)a,b — 
 Gender minority AFABd 737 33.9 (250) 66.1 (487)a,b,c,e,f — 
Race and ethnicity     
 White 2669 51.3 (1369) 48.7 (1300) .007 
 African American 214 58.9 (126) 41.1 (88)g — 
 Mixed racial background 547 46.3 (253) 53.7 (294)g,h — 
 Other race 435 54.3 (236) 45.7 (199)i — 
 Hispanic and/or Latino ethnicity (any race) 846 53.4 (452) 46.6 (394) .26 
Family income     
 Lower than average family 931 39.1 (364) 60.9 (567) <.001 
 Similar to average family 2170 53.1 (1152) 46.9 (1018)j,k — 
 Higher than average family 741 60.9 (451) 39.1 (290)j,k — 
 Decline to answer 137 65.7 (90) 34.3 (47)j,k — 
Child age, y     
 14 1507 51.1 (770) 48.9 (737) .55 
 15 2472 52.1 (1287) 47.9 (1185) — 

Row percentages. Numbers that do not add to column totals are due to missing demographic data. —, not applicable.

a

Significantly different from cisgender heterosexual male youth.

b

Significantly different from cisgender sexual-minority male youth.

c

Significantly different from cisgender heterosexual female youth.

d

Includes youth who identify their gender as transgender, gender queer, nonbinary, pangender, questioning, unsure, and some other identity. Gender-minority youth were not further categorized by their sexual identity because only a few (n = 8, 4.0%) identified as heterosexual, thereby resulting in unstable analytical cells.

e

Significantly different from cisgender sexual-minority female youth.

f

Significantly different from gender-minority AMAB youth.

g

Significantly different from white youth.

h

Significantly different from Black youth.

i

Significantly different from mixed-race youth.

j

Significantly different from lower than average family.

k

Significantly different from similar to average family.

Participants were recruited through study advertisements on social media, including Facebook and Instagram. Online ads encouraged youth to “have their voice heard” and “make a difference.” Survey aims were not mentioned to reduce self-selection bias based on interest in a particular topic. Those interested clicked on the online advertisement, which linked them to a secure survey Web site. The first page provided a study description and contact information for study staff. On the subsequent pages, youth were asked screening questions to determine eligibility. Those who were eligible (ie, 14–15 years of age, living in the United States, and English or Spanish speaking) were then asked to read an assent form and to indicate their willingness to participate in the survey before continuing with the main survey. We requested and were granted a waiver of parental permission for these youth, primarily because requiring parental consent could potentially place youth in situations in which their sexual experiences and/or sexual attraction could be unintentionally disclosed to their parents. In some families, this could pose physical or emotional danger for the child. A waiver also is necessary to avoid fatal sampling bias in the SGM sample that would occur by only including those who are out to their parents.50  Our protocol met the requirements for 45 Code of Federal Regulations 46 116.(f) and 45 Code of Federal Regulations 46.408(c). Appropriate mechanisms were in place to protect the youth, such as localized referrals to mental health supports. The protocol was reviewed and approved by Pearl Institutional Review Board.

Participants were given a $15 incentive as an Amazon gift card for completing the survey. Ineligible youth were directed to a Web page that included links to general resources for youth (eg, https://youngwomenshealth.org). To promote a diverse sample, demographic quotas were identified. Once the targeted number of youth in a particular group had been achieved (eg, white, non-Hispanic, cisgender girls), subsequent youth in this group who were otherwise eligible were deemed ineligible.

Sexual and Gender Identity

To measure gender identity, participants were first provided with the following question and definition: “What is your gender? Gender refers to cultural values (roles, behaviors, activities, and attributes) that a society associates with males and females. Gender also refers to how one defines oneself. For many people, there isn’t a difference between these terms, but for some people, their gender is different from their biological sex. Biological sex is determined by our chromosomes, our hormones, and reproductive organs. Typically, we are assigned the sex of male or female at birth.” Response options were (1) male; (2) female; (3) female to male, transgender male, and trans man; (4) male to female, transgender female, and trans woman; (5) gender queer, nonbinary, and pangender; (6) other (specify); (7) I don’t understand this question; and (8) decline to answer.

Sexual identity was measured with the following question: “Below is a list of terms that people often use to describe their sexuality or sexual orientation. How would you describe your sexuality or sexual orientation? Please select all that apply.” Response options included gay, lesbian, bisexual, straight/heterosexual, questioning, queer, pansexual, asexual, other (specify), unsure, and decline to answer. Participants were allowed to endorse multiple options.

Youth were categorized into 1 of 6 groups on the basis of their sexual and gender identities: (1) cisgender heterosexual male, (2) cisgender sexual-minority male, (3) cisgender heterosexual female, (4) cisgender sexual-minority female, (5) gender minority assigned male at birth (AMAB), and (6) gender minority assigned female at birth (AFAB). Cisgender refers to people who identify their gender as the same as the sex they were assigned at birth. Although the focus on this article is exposure to suicidal behavior among SGM youth, we include cisgender heterosexual male and female youth for comparison purposes.

Exposure to Suicidal Behavior

Youth were asked, “has someone close to you ever tried to kill him or herself on purpose (like by shooting or cutting him or herself or taking too many pills or drugs)?” Response options were yes, no, or decline to answer. Decline to answer responses (2.1%) were conservatively coded as no.

Nonvictimization Adversity

We measured nonvictimization adversity using 9 items, including lifetime exposure to nonviolent traumatic events (serious illnesses, accidents, and parental imprisonment) and chronic stressors (substance abuse by family members and homelessness).51,52 

Cumulative Victimization

Following the polyvictimization literature,53  cumulative victimization was assessed as a summary measure of the total number of different victimization types (of a possible 42) across 8 domains: sexual harassment (9 items), theft (1 item), assault (2 items), peer victimization (6 items), sexual victimization (4 items), emotional dating violence (4 items), physical dating violence (7 items), and witnessing violence (9 items) (range: 0–41, mean = 5.6, SD = 7.3).

Depressed Mood

Youth were asked an item developed for the study: “In the last month, was there ever a time of two weeks or longer when you were feeling unhappy, bummed out, depressed, or down most of the day or nearly every day?” Response options were no, yes, and not sure. Not sure (8.3%) and decline to answer (1.1%) responses were conservatively recoded as symptom absent. Indicators of depressed mood have been found to be a strong indicator of clinical depression in children and adolescents.54 

Social support55  was measured with 8 items (eg, “I have a special person who is around when I am in need,” and “I have a special person who is a real source of comfort to me.”). The response options ranged from very strongly disagree (1) to very strongly agree (7). Missing data were no higher than 1.9% and were replaced with individual item means. Reliability for the entire scale was excellent (α = .93). Items were summed and then dichotomized at 1 SD about the mean, with a positive value indicating high social support and a negative value indicating less support. This allowed for the creation of 4 groups for comparison purposes: (1) no suicidal behavior exposure + less support, (2) no suicidal behavior exposure + high support, (3) suicidal behavior exposure + less support, and (4) no suicidal behavior exposure + high support.

Demographic Characteristics

For multivariate analyses, age was included as a categorical variable given the small age range: 14 to 15 years old. Self-reported household income comprised 3 answer choices: lower than average, about average, and higher than average. For multivariate analyses, those who indicated their family income was lower than average were compared with all other youth. Youth reported their race (coded as white versus other for multivariate analyses) and ethnicity (coded as Hispanic versus other).

First, we compared youth characteristics (eg, sexual and gender identity, race, and ethnicity) by exposure to suicidal behavior using χ2 crosstabulations, with pairwise comparisons within characteristics. Next, we examined other nonvictimization adversity experiences by exposure to suicidal behavior (see Supplemental Table 4), as well as adversity experiences and total adversity count by sexual and gender identity, using χ2 statistics and mean comparisons (see Supplemental Table 5). Next, we compared reports of exposure to suicidal behavior, high social support, the interaction of exposure to suicidal behavior and high social support (2 × 2 = 4 groups: [1] no suicidal behavior exposure/less support, [2] no suicidal behavior exposure/high support, [3] suicidal behavior exposure/less support, and [4] suicidal behavior exposure/high support); total nonvictimization adversity count (mean and SE); total victimization count (mean and SE); and depressed mood by sexual and gender identity using χ2 crosstabulations and mean difference tests. Post hoc pairwise comparisons across sexual and gender identity subgroups were also conducted. Finally, to better understand how exposure to suicidal behavior relates to the depressed mood of youth, for each sexual and gender identity subgroup, the association between the interaction of exposure to suicidal behavior and social support with depressed mood was examined by using logistic regression procedures (with no suicidal behavior exposure/less support as the comparison group). In model 1, we display the associations, adjusting for age, race, ethnicity, and low income; in model 2, we display the associations, further adjusting for total adversity and cumulative victimization to understand how these experiences moderate any existing relationships.

Reports of lifetime exposure to suicidal behavior ranged from a low of 31.5% for cisgender heterosexual male youth to a high of 66.1% for gender-minority AFAB youth (Table 1). Indeed, all SGM youth were significantly more likely to have someone close to them engage in suicidal behavior than cisgender heterosexual male youth. Exposure to suicidal behavior also varied by race: more youth who identified as mixed race reported exposure to suicidal behavior (53.7%) than youth who identified as any other race. Youth who had been exposed to suicidal behavior were more likely to live in homes with a lower-than-average family income (60.9%) compared to youth living in homes with higher-than-average family incomes (39.1%) and similar-to-average family incomes (46.9%).

Overall, 14.3% of all youth reported having high social support, with no differences across sexual and gender identities (Table 2). Differences in high social support within the context of exposure to suicidal behavior were seen across identity however (P < .001). Youth who reported exposure to suicidal behavior but had less social support ranged from 26.7% for cisgender heterosexual male youth to 57.5% for gender-minority AFAB youth. Exposure to suicidal behavior by youth who had high social support ranged from 4.8% for cisgender heterosexual male youth to 13.9% for gender-minority AMAB youth.

TABLE 2

Bivariate Relationships Between Exposure to Suicidal Behavior and Social Support by Sexual and Gender Identity

ConstructsAll Youth, N = 3979Cisgender Heterosexual Male Youth, n = 641Cisgender Sexual-Minority Male Youth, n = 805Cisgender Heterosexual Female Youth, n = 801Cisgender Sexual- Minority Female Youth, n = 850Gender-Minority AMABa Youth, n = 108Gender-Minority AFABa Youth, n = 737X2P
High social support, % (n14.3 (567) 14.3 (92) 14.0 (113) 15.5 (124) 14.0 (119) 19.4 (21) 12.9 (95) .47 
Interaction of exposure to suicidal behavior and social support, % (n        
 No exposure and less support 44.5 (1772) 59.0 (378) 51.1 (411)b 46.7 (374)b 38.0 (323)b,c,d 43.5 (47)b,c 29.6 (218)b,c,d,e,f <.001 
 No exposure and high support 7.2 (285) 9.5 (61) 7.9 (64) 8.5 (68) 6.0 (51) 5.6 (6) 4.3 (32) — 
 Exposure and less support 41.2 (1640) 26.7 (171) 34.9 (281) 37.8 (303) 48.0 (408) 37.0 (40) 57.5 (424) — 
 Exposure and high support 7.1 (282) 4.8 (31) 6.1 (49) 7.0 (56) 8.0 (68) 13.9 (15) 8.5 (63) — 
Total adversity count, mean (SE) 3.1 (0.03) 2.4 (0.07) 2.8 (0.07)b 3.1 (0.07)b,c 3.4 (0.07)b,c,d 3.1 (0.23)b 3.8 (0.08)b,c,d,e,f <.001 
Total victimization count, mean (SE) 8.6 (0.12) 6.2 (0.21) 7.5 (0.24)b 7.9 (0.24)b 9.4 (0.26)b,c,d 9.1 (0.71)b,c 11.8 (0.32)b,c,d,e,f <.001 
Depressed mood, % (n70.9 (2821) 51.5 (330) 65.3 (526)b 70.3 (563)b,c 78.7 (669)b,c,d 75.0 (81)b,c 85.7 (632)b,c,d,e,f <.001 
ConstructsAll Youth, N = 3979Cisgender Heterosexual Male Youth, n = 641Cisgender Sexual-Minority Male Youth, n = 805Cisgender Heterosexual Female Youth, n = 801Cisgender Sexual- Minority Female Youth, n = 850Gender-Minority AMABa Youth, n = 108Gender-Minority AFABa Youth, n = 737X2P
High social support, % (n14.3 (567) 14.3 (92) 14.0 (113) 15.5 (124) 14.0 (119) 19.4 (21) 12.9 (95) .47 
Interaction of exposure to suicidal behavior and social support, % (n        
 No exposure and less support 44.5 (1772) 59.0 (378) 51.1 (411)b 46.7 (374)b 38.0 (323)b,c,d 43.5 (47)b,c 29.6 (218)b,c,d,e,f <.001 
 No exposure and high support 7.2 (285) 9.5 (61) 7.9 (64) 8.5 (68) 6.0 (51) 5.6 (6) 4.3 (32) — 
 Exposure and less support 41.2 (1640) 26.7 (171) 34.9 (281) 37.8 (303) 48.0 (408) 37.0 (40) 57.5 (424) — 
 Exposure and high support 7.1 (282) 4.8 (31) 6.1 (49) 7.0 (56) 8.0 (68) 13.9 (15) 8.5 (63) — 
Total adversity count, mean (SE) 3.1 (0.03) 2.4 (0.07) 2.8 (0.07)b 3.1 (0.07)b,c 3.4 (0.07)b,c,d 3.1 (0.23)b 3.8 (0.08)b,c,d,e,f <.001 
Total victimization count, mean (SE) 8.6 (0.12) 6.2 (0.21) 7.5 (0.24)b 7.9 (0.24)b 9.4 (0.26)b,c,d 9.1 (0.71)b,c 11.8 (0.32)b,c,d,e,f <.001 
Depressed mood, % (n70.9 (2821) 51.5 (330) 65.3 (526)b 70.3 (563)b,c 78.7 (669)b,c,d 75.0 (81)b,c 85.7 (632)b,c,d,e,f <.001 

Sexual and gender identity data not available for 37 participants. —, not applicable.

a

Includes youth who identify their gender as transgender, gender queer, nonbinary, pangender, questioning, unsure, and some other identity. Gender-minority youth were not further categorized by their sexual identity because only a few (n = 8, 4.0%) identified as heterosexual, thereby resulting in unstable analytical cells.

b

Significantly different from cisgender heterosexual male youth.

c

Significantly different from cisgender sexual-minority male youth.

d

Significantly different from cisgender heterosexual female youth.

e

Significantly different from cisgender sexual-minority female youth.

f

Significantly different from gender-minority AMAB youth.

Compared to cisgender heterosexual male youth, more youth with each of the other sexual and gender identities reported recent depressed mood (Table 2). Gender-minority AFAB youth had the highest reports of depressed mood (85.7%). Overall, the number of nonvictimization adversity experiences also significantly differed by sexual and gender identity (P < .001), as did cumulative victimization (P < .001), with the highest counts reported by gender-minority AFAB youth.

The association between the interaction of exposure to suicidal behavior and social support with depressed mood across each sexual and gender identity subgroup separately are depicted in Table 3. Youth with no exposure to suicidal behavior but with high social support did not have elevated odds of depressed mood compared with youth with no exposure and less support. This was true regardless of identity. Across all sexual and gender identity groups, exposure to suicidal behavior with less social support was associated with elevated odds of depressed mood compared to no exposure/less support. Cisgender heterosexual male and female youth with exposure to suicidal behavior and high social support did not have elevated odds of depressed mood. For cisgender sexual-minority male and female youth with this combination of exposure to suicidal behavior and high social support, we saw elevated odds of depressed mood compared to no exposure/less support youth. For gender-minority AFAB youth, we found the combination of exposure to suicidal behavior and high social support resulted in higher odds of depressed mood (adjusted odds ratio [aOR] = 8.09; P = .005) than that seen with suicidal exposure and less social support (aOR = 2.20; P = .001). When we further adjusted for cumulative adversity and victimization, some groups of youth continued to have elevated odds of depressed mood: cisgender sexual-minority male youth with less support, cisgender sexual-minority female youth with less support as well as those with high support, and cisgender heterosexual male youth with less support. For gender-minority AFAB youth, those with suicide exposure and high support continued to have elevated odds of depressed mood (but not those with less support). For gender-minority AMAB youth, the power to detect effects was limited because of a small sample size.

TABLE 3

Associations Between Lifetime Exposure to Suicidal Behavior and Depressed Mood by Sexual and Gender Identity

Lifetime Exposure to Suicidal BehaviorModel 1: Relative Odds of Depressed Mood Given Exposure to Suicidal Behavior and Social SupportModel 2: + Cumulative Adversity
aOR (95% CI)PaOR (95% CI)P
Cisgender sexual-minority male youth, n = 805     
 Interaction of exposure to suicidal behavior and social support     
  No exposure and less support (ref) 1.0 — 1.0 — 
  No exposure and high support 0.96 (0.56–1.64) .88 0.91 (0.51–1.61) .75 
  Exposure and less support 3.47 (2.41–4.99) <.001 1.78 (1.19–2.67) .005 
  Exposure and high support 3.07 (1.48–6.36) .003 1.31 (0.59–2.89) .51 
 Cumulative adversity — — 1.24 (1.11–1.37) <.001 
 Cumulative victimization — — 1.14 (1.10–1.18) <.001 
Cisgender sexual-minority female youth, n = 801     
 Interaction of exposure to suicidal behavior and social support     
  No exposure and less support (ref) 1.0 — 1.0 — 
  No exposure and high support 0.58 (0.34–0.98) .04 0.65 (0.37–1.13) .13 
  Exposure and less support 3.38 (2.31–4.96) <.001 2.32 (1.55–3.48) <.001 
  Exposure and high support 2.29 (1.17–4.51) .02 1.99 (0.99–4.01) .05 
 Cumulative adversity — — 1.09 (0.99–1.21) .09 
 Cumulative victimization — — 1.14 (1.10–1.19) <.001 
Gender-minority AMAB youth,an = 108     
 Interaction of exposure to suicidal behavior and social support     
  No exposure and less support (ref) 1.0 — 1.0 — 
  No exposure and high support 0.41 (0.07–2.42) .33 0.31 (0.05–1.99) .22 
  Exposure and less support 3.78 (1.07–13.39) .04 1.37 (0.28–6.67) .69 
  Exposure and high support 0.87 (0.24–3.20) .83 0.77 (0.16–3.71) .75 
 Cumulative adversity — — 0.78 (0.56–1.08) .13 
 Cumulative victimization — — 1.39 (1.16–1.67) <.001 
Gender-minority AFAB youth, n = 737     
 Interaction of exposure to suicidal behavior and social support     
  No exposure and less support (ref) 1.0 — 1.0 — 
  No exposure and high support 0.67 (0.29–1.58) .36 0.76 (0.32–1.83) .54 
  Exposure and less support 2.20 (1.40–3.46) .001 1.54 (0.96–2.48) .07 
  Exposure and high support 8.09 (1.90–34.52) .005 6.50 (1.50–28.11) .01 
 Cumulative adversity — — 1.03 (0.90–1.17) .68 
 Cumulative victimization — — 1.10 (1.06–1.14) <.001 
Cisgender heterosexual male youth, n = 641     
 Interaction of exposure to suicidal behavior and social support     
  No exposure and less support (ref) 1.0 — 1.0 — 
  No exposure and high support 0.86 (0.49–1.49) .59 0.94 (0.53–1.66) .83 
  Exposure and less support 1.93 (1.31–2.82) .001 1.52 (1.02–2.27) .04 
  Exposure and high support 1.10 (0.52–2.33) .80 0.73 (0.33–1.62) .43 
 Cumulative adversity — — 1.22 (1.09–1.35) <.001 
 Cumulative victimization — — 1.06 (1.03–1.10) .001 
Cisgender heterosexual female youth, n = 850     
 Interaction of exposure to suicidal behavior and social support     
  No exposure and less support (ref) 1.0 — 1.0 — 
  No exposure and high support 1.03 (0.53–2.02) .92 1.03 (0.51–2.04) .94 
  Exposure and less support 2.00 (1.38–2.89) <.001 1.22 (0.82–1.82) .32 
  Exposure and high support 1.21 (0.65–2.23) .55 0.92 (0.48–1.77) .81 
 Cumulative adversity — — 1.13 (1.01–1.25) .03 
 Cumulative victimization — — 1.11 (1.07–1.15) <.001 
Lifetime Exposure to Suicidal BehaviorModel 1: Relative Odds of Depressed Mood Given Exposure to Suicidal Behavior and Social SupportModel 2: + Cumulative Adversity
aOR (95% CI)PaOR (95% CI)P
Cisgender sexual-minority male youth, n = 805     
 Interaction of exposure to suicidal behavior and social support     
  No exposure and less support (ref) 1.0 — 1.0 — 
  No exposure and high support 0.96 (0.56–1.64) .88 0.91 (0.51–1.61) .75 
  Exposure and less support 3.47 (2.41–4.99) <.001 1.78 (1.19–2.67) .005 
  Exposure and high support 3.07 (1.48–6.36) .003 1.31 (0.59–2.89) .51 
 Cumulative adversity — — 1.24 (1.11–1.37) <.001 
 Cumulative victimization — — 1.14 (1.10–1.18) <.001 
Cisgender sexual-minority female youth, n = 801     
 Interaction of exposure to suicidal behavior and social support     
  No exposure and less support (ref) 1.0 — 1.0 — 
  No exposure and high support 0.58 (0.34–0.98) .04 0.65 (0.37–1.13) .13 
  Exposure and less support 3.38 (2.31–4.96) <.001 2.32 (1.55–3.48) <.001 
  Exposure and high support 2.29 (1.17–4.51) .02 1.99 (0.99–4.01) .05 
 Cumulative adversity — — 1.09 (0.99–1.21) .09 
 Cumulative victimization — — 1.14 (1.10–1.19) <.001 
Gender-minority AMAB youth,an = 108     
 Interaction of exposure to suicidal behavior and social support     
  No exposure and less support (ref) 1.0 — 1.0 — 
  No exposure and high support 0.41 (0.07–2.42) .33 0.31 (0.05–1.99) .22 
  Exposure and less support 3.78 (1.07–13.39) .04 1.37 (0.28–6.67) .69 
  Exposure and high support 0.87 (0.24–3.20) .83 0.77 (0.16–3.71) .75 
 Cumulative adversity — — 0.78 (0.56–1.08) .13 
 Cumulative victimization — — 1.39 (1.16–1.67) <.001 
Gender-minority AFAB youth, n = 737     
 Interaction of exposure to suicidal behavior and social support     
  No exposure and less support (ref) 1.0 — 1.0 — 
  No exposure and high support 0.67 (0.29–1.58) .36 0.76 (0.32–1.83) .54 
  Exposure and less support 2.20 (1.40–3.46) .001 1.54 (0.96–2.48) .07 
  Exposure and high support 8.09 (1.90–34.52) .005 6.50 (1.50–28.11) .01 
 Cumulative adversity — — 1.03 (0.90–1.17) .68 
 Cumulative victimization — — 1.10 (1.06–1.14) <.001 
Cisgender heterosexual male youth, n = 641     
 Interaction of exposure to suicidal behavior and social support     
  No exposure and less support (ref) 1.0 — 1.0 — 
  No exposure and high support 0.86 (0.49–1.49) .59 0.94 (0.53–1.66) .83 
  Exposure and less support 1.93 (1.31–2.82) .001 1.52 (1.02–2.27) .04 
  Exposure and high support 1.10 (0.52–2.33) .80 0.73 (0.33–1.62) .43 
 Cumulative adversity — — 1.22 (1.09–1.35) <.001 
 Cumulative victimization — — 1.06 (1.03–1.10) .001 
Cisgender heterosexual female youth, n = 850     
 Interaction of exposure to suicidal behavior and social support     
  No exposure and less support (ref) 1.0 — 1.0 — 
  No exposure and high support 1.03 (0.53–2.02) .92 1.03 (0.51–2.04) .94 
  Exposure and less support 2.00 (1.38–2.89) <.001 1.22 (0.82–1.82) .32 
  Exposure and high support 1.21 (0.65–2.23) .55 0.92 (0.48–1.77) .81 
 Cumulative adversity — — 1.13 (1.01–1.25) .03 
 Cumulative victimization — — 1.11 (1.07–1.15) <.001 

CI, confidence interval; ref, reference category; —, not applicable.

a

Low power to detect significant differences. All models are adjusted for age, race and ethnicity, low income, and survey process variables (ie, taking survey in a private place and honesty in responses).

The current study indicates that many young teenagers have someone they are close to who has tried to kill themselves. Being exposed to suicidal behavior was related to higher levels of recent depressed mood across all groups of youth in the current study at the bivariate level. This relationship was particularly strong for SGM youth and persisted even after taking into account other adversity and victimization experiences. These findings alone suggest SGM-inclusive prevention efforts are needed, in addition to broader environmental changes, to address adversity stress burden.

When taking a deeper look at the intersection of exposure to suicidal behavior and social support, results are complex. Cisgender heterosexual youth were buffered from recent depressed mood when they perceived themselves to have high social support in the context of exposure to suicidal behavior; less social support did not provide such a buffer. For cisgender sexual-minority male and female youth, exposure to suicidal behavior was related to recent depressed mood regardless of level of social support. Given the likelihood that participants who are exposed to suicidal behavior are also in environments in which they are exposed to other types of trauma, including victimization and nonvictimization adversity histories, it is possible they already have elevated negative psychosocial symptomatology, which should be taken into account to better understand any unique contribution of exposure to suicidal behavior. In the current study, relationships between exposure to suicidal behavior and depressed mood remained in the context of low support for cisgender sexual-minority male and female youth as well as cisgender heterosexual male youth even when taking into account cumulative adversity. This supports previous research which has documented relationships between exposure to suicidal behavior and personal suicidal ideation, thoughts of self-harm, and trauma symptomatology,18  but provides new data that suggests these relationships vary for different youth on the basis of sexual and gender identity. More research using longitudinal samples of SGM and heterosexual youth to further explore these complex relationships over time is necessary.

Gender-minority AFAB youth showed a different pattern when exposure to suicidal behavior was coupled with high social support. For these teenagers, exposure combined with high social support was related to a higher likelihood of recent depressed mood than was seen with gender-minority AFAB youth having less social support. Given previous work indicating transgender youth are particularly at risk for negative psychosocial outcomes,30,56,57  future research to explore these associations further seems warranted. For example, support networks may be particularly small and tight knit in the context of stigma, isolation, and adversity. Gender-minority youth may thus experience a greater burden of stress from providing intensive support to others, a point made in a systematic review of the “dark side” of social capital.58  Further, although the protective nature of social integration has been emphasized,5961  such high integration may promote the diffusion of negative behaviors as well.6265  It is possible this is more pronounced in gender-minority AFAB youth. At the same time, perhaps social support is more protective but losing someone from that social support network may be more adverse. It is also possible that these findings reflect a potential dose effect, whereby these groups had the highest suicide exposure. As with the construct of polyvictimization,66,67  there may be a tipping point of exposure beyond which protective factors like social support become less effective because comparisons of exposure to suicide to other stressors revealed augmented negative effects of the former.21 

Social support itself may need to be measured in different ways beyond whether support is perceived to be available. For example, understanding whether an individual actually uses the supports they perceive as available may add additional insight.68  Delineating online versus in-person support will also be useful to contextualize findings. Previous work suggests that SGM youth are more likely to have online friends and to perceive them as more emotionally supportive than in-person friends.56  And although some research suggests that online support can offer protective effects for SGM youth,69  we know relatively little about the possible vulnerabilities introduced by such online niches. It could be that within a tight-knit online community with more support, one is more likely to disclose, and therefore others may be more likely to know when someone attempts suicide. Density and diversity of the support networks, and the balance of support provided versus support received within an individual’s networks, will be important to explore in future work.

Gatekeeper training has gained considerable attention in suicide prevention.7072  Such suicide prevention programs focus on training peers and key adults as active bystanders, a model based in social support.70,71,7375  Gatekeeper training education is a strategy used within school settings to help staff identify at-risk youth and help them get the help they need.70  Such programs have demonstrated positive changes in knowledge and attitudes about suicide but have had less success in changing behaviors (ie, actual use of the skills learned to help others) in real-world settings.70,71,73,76  Some of this may be due, in part, to the fact that not all exposure to suicidal behavior results in bystander opportunity. Research has not yet delineated how much exposure is a result of hearing about suicide after the fact versus previous knowledge that someone is thinking about suicide. More research is needed to develop a better understanding of the factors that promote successful suicide prevention behaviors among SGM and heterosexual youth to inform more effective bystander actions.

Few studies gather information about the effects of helping that might produce unintended negative prevention consequences, such as suicide risk1118  or psychological distress,19,21  among youth bystanders. Current findings suggest that suicide prevention efforts need to pay particular attention to SGM youth not only to prevent suicide among this group but also to help cultivate resilience among SGM youth who are likely to be exposed to peer suicide attempts. We need more research to understand the lived experiences of these youth, including how they experience social support. This is particularly urgent given recent research that suggests that other evidence-based violence-prevention curricula for youth are less effective for SGM youth.77 

Our measure of exposure to suicidal behavior did not identify the relationship between the participant and the person with suicidal behavior beyond knowing that they were close. Therefore, researchers in future studies should examine varying relationships separately, such as family and friends, to understand contexts in which support might mitigate or exacerbate the adverse effects of exposure to suicidal behavior on personal psychosocial outcomes. We also were not able to determine when the participant became aware of the suicidal behavior (eg, before an attempt or after). Such information is important when considering prevention opportunities. The measure for depressed mood is broad and should not be considered as a marker for clinical depression or depressive symptomatology; more research is needed that includes a more thorough assessment of mental health indicators. The cross-sectional nature of this study limits inferences about temporal associations and direction of effects. We do not know, for example, the causal direction between exposure to suicidal behavior and depressed mood, although measuring depressed mood in the past month helped to mitigate this concern to some extent. Finally, although the sample is national, and therefore geographically diverse, it is not representative. Despite these limitations, the current study helps us better understand variability among youth in exposure to suicidal behavior and the complex role of social support as a factor that may not always help well-being.

Adolescent suicide is a heightened public health concern. Findings from the current study suggest that for some youth, social support may not always be protective or always associated with well-being. Although findings need to be replicated, suicide prevention efforts should carefully consider how to promote resilience among these youth who may themselves be at risk for suicidal ideation and other mental health concerns. The current findings also highlight the heterogeneity of SGM youth experiences and psychosocial functioning. Prevention efforts need to be equally heterogeneous in their offers to ensure that a diversity of youth have access to salient programming.

Dr Mitchell conceptualized and designed the manuscript, conducted the data analysis, interpreted the data, and drafted the manuscript; Drs Banyard and Goodman helped interpret the data and critically revised the manuscript for important intellectual content; Dr Stroem helped interpret the data and critically revised the manuscript for important intellectual content; Dr Ybarra acquired the data, helped interpret the data, and critically revised the manuscript for important intellectual content; and all authors ensure that questions related to the accuracy and integrity of the work were appropriately investigated and resolved, agree to be accountable for all aspects of the work, and approved the final version of the manuscript as submitted.

FUNDING: Funded by the National Institutes of Health grant R01 HD083072b. The funder did not participate in the work. Funded by the National Institutes of Health (NIH).

AFAB

assigned female at birth

AMAB

assigned male at birth

aOR

adjusted odds ratio

SGM

sexual and gender minority

YRBS

Youth Risk Behavior Survey

1
Crosby
AE
,
Ortega
L
,
Melanson
C
.
Self-Directed Violence Surveillance: Uniform Definitions and Recommended Data Elements
.
Atlanta, GA
:
Centers for Disease Control and Prevention, National Center for Injury Prevention and Control
;
2011
2
Centers for Disease Control and Prevention
. WISQARS–web-based injury statistics query and reporting system. Available at: https://www.cdc.gov/injury/wisqars/index.html. Accessed February 9, 2017
3
Evans
E
,
Hawton
K
,
Rodham
K
.
In what ways are adolescents who engage in self-harm or experience thoughts of self-harm different in terms of help-seeking, communication and coping strategies?
J Adolesc
.
2005
;
28
(
4
):
573
587
4
Fortune
S
,
Sinclair
J
,
Hawton
K
.
Help-seeking before and after episodes of self-harm: a descriptive study in school pupils in England
.
BMC Public Health
.
2008
;
8
(
1
):
369
5
Berger
E
,
Hasking
P
,
Martin
G
.
Adolescents’ perspectives of youth non-suicidal self-injury prevention
.
Youth Soc
.
2014
;
49
(
1
):
3
22
6
Michelmore
L
,
Hindley
P
.
Help-seeking for suicidal thoughts and self-harm in young people: a systematic review
.
Suicide Life Threat Behav
.
2012
;
42
(
5
):
507
524
7
Kalafat
J
,
Elias
M
.
Adolescents’ experience with and response to suicidal peers
.
Suicide Life Threat Behav
.
1992
;
22
(
3
):
315
321
8
Bearman
PS
,
Moody
J
.
Suicide and friendships among American adolescents
.
Am J Public Health
.
2004
;
94
(
1
):
89
95
9
Swanson
SA
,
Colman
I
.
Association between exposure to suicide and suicidality outcomes in youth
.
CMAJ
.
2013
;
185
(
10
):
870
877
10
Cerel
J
,
Roberts
TA
.
Suicidal behavior in the family and adolescent risk behavior
.
J Adolesc Health
.
2005
;
36
(
4
):
352.e9
-
16
11
Cerel
J
,
Roberts
TA
,
Nilsen
WJ
.
Peer suicidal behavior and adolescent risk behavior
.
J Nerv Ment Dis
.
2005
;
193
(
4
):
237
243
12
Burke
AK
,
Galfalvy
H
,
Everett
B
, et al
.
Effect of exposure to suicidal behavior on suicide attempt in a high-risk sample of offspring of depressed parents
.
J Am Acad Child Adolesc Psychiatry
.
2010
;
49
(
2
):
114
121
13
Randall
JR
,
Nickel
NC
,
Colman
I
.
Contagion from peer suicidal behavior in a representative sample of American adolescents
.
J Affect Disord
.
2015
;
186
:
219
225
14
Maple
M
,
Cerel
J
,
Sanford
R
,
Pearce
T
,
Jordan
J
.
Is exposure to suicide beyond kin associated with risk for suicidal behavior? A systematic review of the evidence
.
Suicide Life Threat Behav
.
2017
;
47
(
4
):
461
474
15
Insel
BJ
,
Gould
MS
.
Impact of modeling on adolescent suicidal behavior
.
Psychiatr Clin North Am
.
2008
;
31
(
2
):
293
316
16
Hill
NTM
,
Robinson
J
,
Pirkis
J
, et al
.
Association of suicidal behavior with exposure to suicide and suicide attempt: a systematic review and multilevel meta-analysis
.
PLoS Med
.
2020
;
17
(
3
):
e1003074
17
Chan
S
,
Denny
S
,
Fleming
T
,
Fortune
S
,
Peiris-John
R
,
Dyson
B
.
Exposure to suicide behaviour and individual risk of self-harm: findings from a nationally representative New Zealand high school survey
.
Aust N Z J Psychiatry
.
2018
;
52
(
4
):
349
356
18
Mitchell
KJ
,
Turner
HA
,
Jones
LM
.
Youth exposure to suicide attempts: relative impact on personal trauma symptoms
.
Am J Prev Med
.
2019
;
56
(
1
):
109
115
19
McMahon
EM
,
Corcoran
P
,
Keeley
H
,
Perry
IJ
,
Arensman
E
.
Adolescents exposed to suicidal behavior of others: prevalence of self-harm and associated psychological, lifestyle, and life event factors
.
Suicide Life Threat Behav
.
2013
;
43
(
6
):
634
645
20
Nanayakkara
S
,
Misch
D
,
Chang
L
,
Henry
D
.
Depression and exposure to suicide predict suicide attempt
.
Depress Anxiety
.
2013
;
30
(
10
):
991
996
21
Bottomley
JS
,
Abrutyn
S
,
Smigelsky
MA
,
Neimeyer
RA
.
Mental health symptomatology and exposure to non-fatal suicidal behavior: factors that predict vulnerability and resilience among college students
.
Arch Suicide Res
.
2017
;
22
(
4
):
596
614
22
Meyer
IH
.
Prejudice, social stress, and mental health in lesbian, gay, and bisexual populations: conceptual issues and research evidence
.
Psychol Bull
.
2003
;
129
(
5
):
674
697
23
Birkett
M
,
Espelage
DL
,
Koenig
B
.
LGB and questioning students in schools: the moderating effects of homophobic bullying and school climate on negative outcomes
.
J Youth Adolesc
.
2009
;
38
(
7
):
989
1000
24
Marshal
MP
,
Friedman
MS
,
Stall
R
, et al
.
Sexual orientation and adolescent substance use: a meta-analysis and methodological review
.
Addiction
.
2008
;
103
(
4
):
546
556
25
Veale
JF
,
Watson
RJ
,
Peter
T
,
Saewyc
EM
.
Mental health disparities among Canadian transgender youth
.
J Adolesc Health
.
2017
;
60
(
1
):
44
49
26
Coulter
RWS
,
Bersamin
M
,
Russell
ST
,
Mair
C
.
The effects of gender-and sexuality-based harassment on lesbian, gay, bisexual, and transgender substance use disparities
.
J Adolesc Health
.
2018
;
62
(
6
):
688
700
27
Johns
MM
,
Lowry
R
,
Andrzejewski
J
, et al
.
Transgender identity and experiences of violence victimization, substance use, suicide risk, and sexual risk behaviors among high school students—19 states and large urban school districts, 2017
.
MMWR Morb Mortal Wkly Rep
.
2019
;
68
(
3
):
67
71
28
Johns
MM
,
Lowry
R
,
Rasberry
CN
, et al
.
Violence victimization, substance use, and suicide risk among sexual minority high school students—United States, 2015–2017
.
MMWR Morb Mortal Wkly Rep
.
2018
;
67
(
43
):
1211
1215
29
Button
DM
,
O’Connell
DJ
,
Gealt
R
.
Sexual minority youth victimization and social support: the intersection of sexuality, gender, race, and victimization
.
J Homosex
.
2012
;
59
(
1
):
18
43
30
Sterzing
PR
,
Gartner
RE
,
Goldbach
JT
,
McGeough
BL
,
Ratliff
GA
,
Johnson
KC
.
Polyvictimization prevalence rates for sexual and gender minority adolescents: breaking down the silos of victimization research
.
Psychol Violence
.
2019
;
9
(
4
):
419
31
Mustanski
B
,
Espelage
DL
.
Why are we not closing the gap in suicide disparities for sexual minority youth?
Pediatrics
.
2020
;
145
(
3
):
e20194002
32
D’Augelli
AR
,
Grossman
AH
,
Starks
MT
.
Parents’ awareness of lesbian, gay, and bisexual youths’ sexual orientation
.
J Marriage Fam
.
2005
;
67
(
2
):
474
482
33
Ryan
C
,
Russell
ST
,
Huebner
D
,
Diaz
R
,
Sanchez
J
.
Family acceptance in adolescence and the health of LGBT young adults
.
J Child Adolesc Psychiatr Nurs
.
2010
;
23
(
4
):
205
213
34
McConnell
EA
,
Birkett
M
,
Mustanski
B
.
Families matter: social support and mental health trajectories among lesbian, gay, bisexual, and transgender youth
.
J Adolesc Health
.
2016
;
59
(
6
):
674
680
35
McConnell
EA
,
Birkett
MA
,
Mustanski
B
.
Typologies of social support and associations with mental health outcomes among LGBT youth
.
LGBT Health
.
2015
;
2
(
1
):
55
61
36
Watson
RJ
,
Grossman
AH
,
Russell
ST
.
Sources of social support and mental health among LGB youth
.
Youth Soc
.
2019
;
51
(
1
):
30
48
37
Parra
LA
,
Bell
TS
,
Benibgui
M
,
Helm
JL
,
Hastings
PD
.
The buffering effect of peer support on the links between family rejection and psychosocial adjustment in LGB emerging adults
.
J Soc Pers Relat
.
2018
;
35
(
6
):
854
871
38
Chang
CJ
,
Fehling
KB
,
Selby
EA
.
Sexual minority status and psychological risk for suicide attempt: a serial multiple mediation model of social support and emotion regulation
.
Front Psychiatry
.
2020
;
11
:
385
39
Coyle
S
,
Malecki
CK
,
Emmons
J
.
Keep your friends close: exploring the associations of bullying, peer social support, and social anxiety
.
Contemp School Psychol
.
2019
;
1
13
40
Friedman
MS
,
Koeske
GF
,
Silvestre
AJ
,
Korr
WS
,
Sites
EW
.
The impact of gender-role nonconforming behavior, bullying, and social support on suicidality among gay male youth
.
J Adolesc Health
.
2006
;
38
(
5
):
621
623
41
Frost
DM
,
Meyer
IH
,
Schwartz
S
.
Social support networks among diverse sexual minority populations
.
Am J Orthopsychiatry
.
2016
;
86
(
1
):
91
102
42
Hill
RM
,
Rooney
EE
,
Mooney
MA
,
Kaplow
JB
.
Links between social support, thwarted belongingness, and suicide ideation among lesbian, gay, and bisexual college students
.
J Fam Strengths
.
2017
;
17
(
2
):
1
23
43
Jones
CA
,
Raghavan
C
.
Sexual orientation, social support networks, and dating violence in an ethnically diverse group of college students
.
J Gay Lesbian Soc Serv
.
2012
;
24
(
1
):
1
22
44
Kaufman
TM
,
Baams
L
,
Dubas
JS
.
Microaggressions and depressive symptoms in sexual minority youth: the roles of rumination and social support
.
Psychol Sex Orientat Gend Divers
.
2017
;
4
(
2
):
184
45
McDonald
K
.
Social support and mental health in LGBTQ adolescents: a review of the literature
.
Issues Ment Health Nurs
.
2018
;
39
(
1
):
16
29
46
Liu
RT
,
Mustanski
B
.
Suicidal ideation and self-harm in lesbian, gay, bisexual, and transgender youth
.
Am J Prev Med
.
2012
;
42
(
3
):
221
228
47
Ybarra
ML
,
Petras
H
.
Groups of sexual violence perpetration in a national sample of youth 13–25 years of age
.
Prev Sci
.
2021
;
22
(
2
):
205
215
48
Ybarra
ML
,
Thompson
RE
.
Predicting the emergence of sexual violence in adolescence
.
Prev Sci
.
2018
;
19
(
4
):
403
415
49
The Annie E. Casey Foundation Kids Count
.
Data center
. Available at: https://datacenter.kidscount.org/. Accessed December 4, 2020
50
Cwinn
E
,
Cadieux
C
,
Crooks
CV
.
Who are we missing? The impact of requiring parental or guardian consent on research with lesbian, gay, bisexual, trans, two-tpirit, queer/questioning youth [published online ahead of print October 12, 2020]
.
J Adolesc Health
. doi:
10.1016/j.jadohealth.2020.07.037
51
Turner
HA
,
Finkelhor
D
,
Ormrod
R
.
The effect of lifetime victimization on the mental health of children and adolescents
.
Soc Sci Med
.
2006
;
62
(
1
):
13
27
52
Turner
HA
,
Butler
MJ
.
Direct and indirect effects of childhood adversity on depressive symptoms in young adults
.
J Youth Adolesc
.
2003
;
32
(
2
):
89
103
53
Haahr-Pedersen
I
,
Ershadi
AE
,
Hyland
P
, et al
.
Polyvictimization and psychopathology among children and adolescents: a systematic review of studies using the Juvenile Victimization Questionnaire
.
Child Abuse Negl
.
2020
;
107
:
104589
54
Cole
DA
,
Cai
L
,
Martin
NC
, et al
.
Structure and measurement of depression in youths: applying item response theory to clinical data
.
Psychol Assess
.
2011
;
23
(
4
):
819
833
55
Zimet
GD
,
Dahlem
NW
,
Zimet
SG
,
Farley
GK
.
The multidimensional scale of perceived social support
.
J Pers Assess
.
1988
;
52
(
1
):
30
41
56
Ybarra
ML
,
Mitchell
KJ
,
Palmer
NA
,
Reisner
SL
.
Online social support as a buffer against online and offline peer and sexual victimization among U.S. LGBT and non-LGBT youth
.
Child Abuse Negl
.
2014
;
39
:
123
136
57
Mitchell
KJ
,
Ybarra
ML
,
Korchmaros
JD
.
Sexual harassment among adolescents of different sexual orientations and gender identities
.
Child Abuse Negl
.
2014
;
38
(
2
):
280
295
58
Villalonga-Olives
E
,
Kawachi
I
.
The dark side of social capital: a systematic review of the negative health effects of social capital
.
Soc Sci Med
.
2017
;
194
:
105
127
59
Gunn
JF
 III
,
Goldstein
SE
,
Gager
CT
.
A longitudinal examination of social connectedness and suicidal thoughts and behaviors among adolescents
.
Child Adolesc Ment Health
.
2018
;
23
(
4
):
341
350
60
Tsai
AC
,
Lucas
M
,
Kawachi
I
.
Association between social integration and suicide among women in the United States
.
JAMA Psychiatry
.
2015
;
72
(
10
):
987
993
61
Tsai
AC
,
Lucas
M
,
Sania
A
,
Kim
D
,
Kawachi
I
.
Social integration and suicide mortality among men: 24-year cohort study of U.S. health professionals
.
Ann Intern Med
.
2014
;
161
(
2
):
85
95
62
Bastiampillai
T
,
Allison
S
,
Chan
S
.
Is depression contagious? The importance of social networks and the implications of contagion theory
.
Aust N Z J Psychiatry
.
2013
;
47
(
4
):
299
303
63
Prinstein
MJ
,
Boergers
J
,
Spirito
A
.
Adolescents’ and their friends’ health-risk behavior: factors that alter or add to peer influence
.
J Pediatr Psychol
.
2001
;
26
(
5
):
287
298
64
Dimant
E
.
Contagion of pro-and anti-social behavior among peers and the role of social proximity
.
J Econ Psychol
.
2019
;
73
:
66
88
65
Reiter
AMF
,
Suzuki
S
,
O’Doherty
JP
,
Li
S-C
,
Eppinger
B
.
Risk contagion by peers affects learning and decision-making in adolescents
.
J Exp Psychol Gen
.
2019
;
148
(
9
):
1494
1504
66
Turner
HA
,
Finkelhor
D
,
Ormrod
R
.
Poly-victimization in a national sample of children and youth
.
Am J Prev Med
.
2010
;
38
(
3
):
323
330
67
Finkelhor
D
,
Ormrod
RK
,
Turner
HA
.
Poly-victimization: a neglected component in child victimization
.
Child Abuse Negl
.
2007
;
31
(
1
):
7
26
68
Thoresen
S
,
Jensen
TK
,
Wentzel-Larsen
T
,
Dyb
G
.
Social support barriers and mental health in terrorist attack survivors
.
J Affect Disord
.
2014
;
156
:
187
193
69
Cole
DA
,
Nick
EA
,
Zelkowitz
RL
,
Roeder
KM
,
Spinelli
T
.
Online social support for young people: does it recapitulate in-person social support; can it help?
Comput Human Behav
.
2017
;
68
:
456
464
70
Isaac
M
,
Elias
B
,
Katz
LY
, et al.;
Swampy Cree Suicide Prevention Team
.
Gatekeeper training as a preventative intervention for suicide: a systematic review
.
Can J Psychiatry
.
2009
;
54
(
4
):
260
268
71
Wyman
PA
,
Brown
CH
,
Inman
J
, et al
.
Randomized trial of a gatekeeper program for suicide prevention: 1-year impact on secondary school staff
.
J Consult Clin Psychol
.
2008
;
76
(
1
):
104
115
72
Torok
M
,
Calear
AL
,
Smart
A
,
Nicolopoulos
A
,
Wong
Q
.
Preventing adolescent suicide: a systematic review of the effectiveness and change mechanisms of suicide prevention gatekeeping training programs for teachers and parents
.
J Adolesc
.
2019
;
73
:
100
112
73
Wyman
PA
,
Brown
CH
,
LoMurray
M
, et al
.
An outcome evaluation of the Sources of Strength suicide prevention program delivered by adolescent peer leaders in high schools
.
Am J Public Health
.
2010
;
100
(
9
):
1653
1661
74
Adams
LM
,
Nguyen
T
,
Morgan
KB
,
Gumbleton
CRUOK
.
Evaluating the effectiveness of a gatekeeper training program
.
J Coll Student Dev
.
2018
;
59
(
5
):
614
617
75
Tompkins
TL
,
Witt
J
.
The short-term effectiveness of a suicide prevention gatekeeper training program in a college setting with residence life advisers
.
J Prim Prev
.
2009
;
30
(
2
):
131
149
76
Cross
W
,
Matthieu
MM
,
Lezine
D
,
Knox
KL
.
Does a brief suicide prevention gatekeeper training program enhance observed skills?
Crisis
.
2010
;
31
(
3
):
149
159
77
Coker
AL
,
Bush
HM
,
Clear
ER
,
Brancato
CJ
,
McCauley
HL
.
Bystander program effectiveness to reduce violence and violence acceptance within sexual minority male and female high school students using a cluster RCT
.
Prev Sci
.
2020
;
21
(
3
):
434
444

Competing Interests

POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose.

FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.

Supplementary data