Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2026 Apr 1.
Published in final edited form as: Cultur Divers Ethnic Minor Psychol. 2024 Feb 8;31(2):347–355. doi: 10.1037/cdp0000641

Childhood adversity and racial discrimination forecasts suicidal and death ideation among emerging adult Black men: A longitudinal analysis

Steven M Kogan 1, Ava J Reck 1, Michael G Curtis 2, Assaf Oshri 1
PMCID: PMC11306413  NIHMSID: NIHMS1948422  PMID: 38330370

Abstract

Objectives:

Disproportionate exposure to childhood adversity and the effects of racial discrimination take a toll on Black American men’s mental health. Despite increasing rates of suicidal behaviors and thoughts among young adult, Black American men, few longitudinal studies examine their risk for suicidal and death ideation (SDI). We tested a developmental model linking childhood adversity (experiences of deprivation and threatening experiences) and emerging adult exposure to racial discrimination to increases in SDI and examined a potential mechanism for these effects, negative relational schemas.

Methods:

A sample of 504 Black men (mean age = 20.7) from rural Georgia were recruited with respondent driven sampling and completed a baseline survey. Men participated in 2 additional follow-up surveys (mean age 21.9 and mean age 23.5. Hypotheses were tested using structural equation modeling.

Results:

Analyses largely supported the proposed model. Childhood adversities were associated directly with reports of SDI. Childhood deprivation indirectly predicted SDI via negative schemas (β = 0.03, 95% CI [.014, .046]). Racial discrimination also indirectly predicted SDI via negative relational schemas (β = 0.01, 95% CI [.001, .018]).

Conclusion:

Study results suggest that clinical and preventive interventions for suicidality should target the influence of racism and adverse experiences and the negative relational schemas they induce.

Keywords: Black men, childhood adversity, racial discrimination, relationship schemas, suicidal and death ideation

INTRODUCTION

Emerging adults (ages 18 to 25 years) endorse increasing rates of suicidal thoughts and planning (Han et al., 2018). Although Black emerging adults are less likely than their White peers to engage in suicidal behavior, rates have steadily increased during the past two decades (Khan et al., 2018). Suicide is now the second leading cause of death for Black Americans, ages 15 to 24 (Centers for Disease Control and Prevention [CDC], 2020). Suicide disproportionately affects Black men in particular; in 2017, the death rate from suicide for Black men was more than four times greater than for Black women (CDC, 2017). Little research, however, has focused specifically on the risk factors for suicidality among emerging adult Black men (Emergency Taskforce on Black Youth Suicide and Mental Health, 2019).

Studies suggest that suicidal and death ideation (SDI) index an underlying vulnerability to suicidal behaviors (Scocco et al., 2001; Van Orden et al., 2013). Suicidal ideation involves thinking about, considering, or planning suicide or one’s death, while death ideation refers to general thoughts about death. Deykin and Buka (1994) found that suicide ideation, together with death ideation, was predictive of later suicide attempts among adolescents. Among Black adults, suicide deaths were more likely associated with death ideation and suicide ideation than accidental deaths (Castle et al., 2004). SDI is considered a symptom of depressive disorders and evinces a dose-response relationship with depression; more severe symptoms of depression are linked to a greater likelihood of experiencing SDI (Garlow et al., 2008). Notably, SDI can occur in the absence of depression (Casey et al., 2008; Joo et al., 2016), and treating depression may not reduce SDI (Batterham et al., 2019). SDI thus can be conceptualized not only as a component of a depressive syndrome but also as a unique indicator of significant emotional distress, independent of depressive symptomatology (Ribeiro et al., 2018).

Black American men in the United States are disproportionately exposed to social adversities, such as poverty and racial discrimination (Gilbert et al., 2016), that take a toll on their mental health and may increase their vulnerability to SDI (Walker et al., 2017). Among the multiple adversities attributable to historical and ongoing institutional and structural racism are childhood adversity (Umberson et al., 2014) and racial discrimination in men’s everyday lives (Goodwill et al., 2021). Little research examines how these experiences affect vulnerability to SDI. Informed by attachment (Langhinrichsen-Rohling et al., 2017; Palitsky et al., 2013) and cultural (Chu et al., 2010) perspectives on suicidality, we tested a model linking childhood adversity and emerging adult exposure to racial discrimination to increases in SDI and examined a potential mechanism for these effects. Cultural perspectives underscore the role of minority stressors, such as racial discrimination and disproportionate exposure to childhood adversity, in the etiology of SDI (Bernard et al., 2021; Chu et al., 2010). Attachment theory, specifies how interpersonal schemas act as proximal vulnerability factor for suicide related behavior (Wrath & Adams, 2019). Schemas refer to cognitive structures that represent an individual’s knowledge and expectations about relationships. Specifically, we investigated if relational schemas associated with vigilance and mistrust, a consequence of navigating aversive social contexts, mediated the effects of childhood adversity and racial discrimination on SDI. Support for testing these pathways follows.

Accumulating research implicates adverse childhood experiences in the emergence of SDI. Childhood adversity encompasses all types of abuse and neglect; exposure to community violence; economic deprivation; stress related to parental mental illness, substance use, divorce, or incarceration; and observation of domestic violence (Felitti et al., 1998). Adverse childhood experiences have a dose-response relationship with SDI (Serafini et al., 2015). For example, a recent national study found that, compared with participants who experienced no adversities, the odds of seriously considering suicide or attempting suicide in adulthood was more than three times greater among participants with histories of three or more adverse experiences (Thompson et al., 2019).

Although total exposure to childhood adversity is a robust predictor of SDI, recent research and theory suggest that there are distinct dimensions of adverse experiences with unique effects on the developing child (McLaughlin et al., 2014). Two dimensions are highlighted here: the absence of cognitive and social stimulation, termed deprivation, and the presence of experiences involving harm or risk thereof, termed threat (McLaughlin et al., 2014). Unique emotional, cognitive, and neurobiological pathways have been proposed that underlie the association of these dimensions of adversity with downstream outcomes (McLaughlin et al., 2014). Deprivation affects mental health via influences on the development of higher-order cognitive processes, such as linguistic processing and executive function. Threat in childhood affects mechanisms involved in the acquisition and extinction of fear, with downstream consequences on emotion processing. Although the consequences of both deprivation and threat have been linked to suicidal behavior (Bredemeier & Miller, 2015; Neacsiu et al., 2018), we are aware of no studies that consider the differences between these experiences in relation to SDI.

Recent research suggests that aspects of racism play a role in the development of SDI among young Black men. Racism in the US comprises a multi-level, multidimensional, and immersive context, systematically producing racial disparities in Black individuals’ health and wellbeing over the life course and across generations (Bernard et al., 2021; Harrell, 2000). We focus here on one aspect of racism, racial discrimination, an individual-level component of racism that indexes differential and unfavorable treatment in routine social interactions of members of marginalized racial groups by members of the dominant group (Black et al., 2015). Racial discrimination is associated with significant negative effects on physical health, mental health, and psychological well-being in populations of color (Williams & Mohammed, 2013). It has been found to increase the risks for depression, anxiety, and psychological distress among Black youth and adults (Assari et al., 2017b; Joesph, et al., 2021; Lee et al., 2020). Although links with SDI have been observed (Assari et al., 2017a; Polanco-Roman et al., 2019), results are inconsistent (Castle et al., 2011), and the existing evidence is drawn mainly from cross-sectional studies. One exception, however, was noted. Walker et al. (2017), with a sample of 722 Black American youth found that racial discrimination experienced at age 10 was linked to increases in SDI two years later.

Childhood adversity and emerging adult racial discrimination are hypothesized to affect SDI, both directly and indirectly, via changes in relational schemas during emerging adulthood. Relational schemas are cognitive structures that represent patterns of relating within interpersonal contexts (Baldwin, 1995). Relational schemas help individuals to define situations more efficiently by drawing attention to salient cues in the social environment, goals associated with response options, and consequences associated with particular responses (Simons et al., 2012). Positive relational schemas are characterized by beliefs that others are trustworthy, caring, and supportive. Negative relational schemas are characterized by beliefs that others are untrustworthy, uncaring, and/or hostile. Although childhood experiences are major contributors to relational schemas, they continue to be shaped by current circumstances throughout adulthood, and during emerging adulthood in particular (Scharfe, & Cole, 2006).

Changing relational schemas among Black men must be considered in light of their exposure, across the life course, to systemic racism, experiences of discrimination, and social inequality. In such circumstances, negative relational schemas will reflect the pervasive mistreatment Black men experience in their lives. Negative schema are often adaptive for dealing with challenging situations (Gaylord-Harden et al., 2018; Stern et al. 2022). At the same time, negative relational schemas may compromise mental health and successful adaptation in many social contexts.

We hypothesize that increases in negative relationship schemas during emerging adulthood may be a mechanism through which childhood adversity and current racial discrimination affects SDI. Empirical evidence supports these pathways. Childhood adversities have profound and enduring effects in shaping relational schemas (Cobb & Davila, 2009) and racial discrimination has been linked to avoidant attachment styles among youth (Stern et al., 2022) . Studies document the extensive effects of racial discrimination in undermining interpersonal relationships (Kerr et al., 2018; Lavner et al., 2018) and inducing feelings of suspicion, anger, and distress (Joseph et al., 2021), which promote negative relational schemas. In turn, negative relational schemas (Kogan et al., 2021), and closely related constructs such as attachment style (Boroujerdi et al., 2019; Palitsky et al., 2013) and early maladaptive schemas (Dale et al., 2010; Langhinrichsen-Rohling et al., 2017) may forecast SDI.

METHODS

Participants

We tested study hypotheses with three waves of data from the African American Men’s Project (AMP; N = 504), a study of health and well-being among emerging adult, Black men in rural Georgia. Eligibility requirements for participation included self-identifying as Black or African American, being male, being between the ages of 19 and 22 years. We recruited participants using respondent-driven sampling (RDS), a referral protocol designed to reduce bias associated with network-driven sampling (Heckathorn, 1997). RDS is a sampling method suggested for sampling from interconnected networks where no lists or consistent contact information is available such as young men whose employment and residences change frequently (Kogan et al., 2011).

Procedures

Community liaisons (CLs) identified 45 initial young men from 11 counties in rural Georgia who fit participant criteria. Research staff then contacted men interested in participating, determined if they were eligible, and scheduled a data collection visit at the participant’s home or another convenient, private location. After data collection, each of the initial participants provided contact information for three men within his network. Project staff then contacted these men to provide information on the study and determine eligibility. These participants then provided contact information for three other men within their networks. The referring participant received $25 for each referred participant who completed the study.

Participants provided written informed consent prior to completing self-report measures using audio computer-assisted self-interviewing (ACASI) technology on a tablet or laptop computer. ACASI is a computer-based program that provides audio and video enhancement, eliminating literacy concerns. All participants received $100 after data collection, and up to 75$ for referral at the baseline assessment. The University Institutional Review Board approved all study protocols.

The men were, on average, 20.7 years of age (SD = 1.22) at baseline (Time 1 [T1]). Of the sample, 15.2% had less than a high school diploma, 56.1% had completed high school or received a General Equivalency Diploma, and 28.7% had some college credits or a college degree. Half of the sample (50%) reported current enrollment in school, and 42% were employed. Approximately 18.30 months (SD = 4.19) after baseline data collection, a follow-up data collection visit (T2) was conducted when the sample’s average age was 21.9 years (SD = .27). A third data collection visit (T3) was conducted 19.68 months after T2, when the sample’s mean age was 23.5 years (SD = 1.21). At T1, 504 men participated, at T2, 422 (83.6%) participated, and at T3, 408 (80.2%) participated. Attrition analysis suggests that retention status was not associated with any study variables.

Measures

Suicidal and death ideation

SDI was assessed at T2 and T3 using two items, one indexing suicidal ideation and one indexing death ideation. The items with the stem “in the past week” were, “How often did you have thoughts about death?” And “How often did you think about killing yourself?” The response scale ranged from 0 (rarely or none of the time) to 3 (most or all of the time). If participants endorsed the presence of any level of SDI on either item, they were assigned a 1 (suicidal ideation present); if neither item was endorsed for SDI, the participants were assigned a 0 (suicidal ideation absent).

Childhood threat

A childhood threat composite score was created using retrospective measures of physical and emotional abuse, and observation of domestic violence against one’s maternal figure. Men completed the Adverse Childhood Experiences Scale (ACES; Felitti et al., 1998) at Wave 1 and the Childhood Trauma Questionnaire (CTQ; Bernstein et al., 1997) at Wave 2. Physical abuse was assessed at Wave 1 using a 4-item subscale from the ACES. Men were asked if they experienced, in their first 16 years of life, any of a list of occurrences (e.g., “A parent or other adult in the household often or very often pushed, grabbed, slapped or threw something at you”). Response options were yes (1) or no (0). Cronbach’s alpha was 0.80. Observation of domestic violence was measured using a 3-item subscale from the ACES (Felitti et al., 1998). Men were asked if they ever witnessed abusive events occuring to their mothers or stepmothers during the first 16 years of the men’s lives (e.g., “Pushed, grabbed, slapped, or had something thrown at her”). Response options were 1 (yes) or 0 (no). Cronbach’s alpha was 0.78. Emotional abuse was assessed using the 5-item emotional abuse subscale of the CTQ. Men were given a list of events and were asked if they experienced any of them before age 17. Example items included, “People in my family called me things like ‘stupid,’ ‘lazy,’ or ‘ugly,’“ and, “People in my family said hurtful or insulting things to me.” Responses ranged from 0 (never true) to 4 (very often true). Cronbach’s alpha was 0.73. The three measures were significantly intercorrelated; they were standardized and summed to create a childhood threat composite score.

Childhood deprivation

A composite score of childhood deprivation was created using retrospective measures of emotional neglect, physical neglect, and childhood poverty. Emotional neglect was measured using the 5-item emotional neglect subscale of the CTQ. Men were given a list of childhood experiences and were asked if they experienced the events before age 17. Example items include, “I felt loved” and “There was someone in my family who helped me feel that I was important or special.” Responses ranged from 0 (never true) to 4 (very often true). All items were reversed scored, and higher scores reflected higher emotional neglect. Cronbach’s alpha was 0.87. Physical neglect was measured using the five-item physical neglect subscale of the CTQ. Example items include “I didn’t have enough to eat” and “I had to wear dirty clothes.” Men were asked if they had experienced these events before turning 17 years of age. Cronbach’s alpha was 0.57. Lastly, childhood family poverty was measured using the 14-item childhood family poverty scale (Curtis et al., 2021). Examples include, “My family did not have a place of our own to live,” “There was not enough heat in the winter,” and “My family had problems getting medical or dental care.” Participants were asked if they had any of these experiences in childhood. Cronbach’s alpha was 0.81. All measures of childhood deprivation were significantly correlated; they were standardized and summed to create a composite childhood deprivation score.

Racial discrimination

We measured everyday discrimination at baseline using a 9-item scale adapted from the Schedule of Racist Events (Landrine & Klonoff, 1996) for rural Black adults by Brody et al. (2006). Minor wording changes were made and items with low base rates excluded. Men were asked how often events occurred in the past six months, such as, “Have you been treated rudely or disrespectfully because of your race?” and “Have others responded to you as if they were afraid because of your race?” The response scale ranged from 0 (never) to 3 (frequently). Cronbach’s alpha was 0.84.

Negative relational schemas

Negative relational schemas were assessed at T1 and T2 using 3 measures used in past research with Black American youth and young adults (Kogan et al., 2021; Simons et al., 2012). Insecure attachment was assessed using a six-item subscale from the Experiences in Close Relationships scale (Wei et al., 2007). Example items include, “I try to avoid getting too close to my romantic partners” and “I am afraid that I will lose my partner’s love in times of need.” Responses ranged from 1 (strongly disagree) to 4 (strongly agree). Cronbach’s alpha was 0.79. The Street Code measure (Stewart & Simons, 2006) is a 7-item scale developed to assess the extent to which an individual believes that aggression is a means of gaining respect in relationships. Example items were, “It is important not to back down from a fight or challenge because people will not respect you,” and “Being viewed as tough and aggressive is important for gaining respect.” Participants’ responses ranged from 1 (strongly disagree) to 4 (strongly agree). Cronbach’s alpha exceeded .70. Cynical views of romantic relationships were measured using a four-item scale (α = .67). Example items include, “When romantic partners are friendly, they usually want something from you,” and “Some romantic partners oppose you for no good reason.” Items were rated on a scale ranging from 1 (strongly disagree) to 4 (strongly agree). These measures were significantly correlated; they were standardized and summed to create a composite negative schema score.

Controls

Depressive symptoms were assessed using a 10-item version of the Center for Epidemiological Studies–Depression scale at T2 (Björgvinsson et al., 2013). Participants were given a list of symptoms and asked how often they experienced each during the past week. Example items include, “How often were you bothered by things that usually do not bother you?” and “How often did you feel like you could not ‘get going’?” The response scale ranged from 0 (rarely or none of the time) to 3 (most or all of the time). Cronbach’s alpha was 0.75.

Age at T1 and maternal education were controlled in all analyses. Maternal education was coded as 0 (less than high school diploma or equivalent), 1 (high school diploma or GED), or 2 (more than a high school diploma).

Plan of analysis

We tested study hypotheses with probit structural equation modeling as implemented in Mplus 8.0 (Muthén & Muthén, 1998–2017). Missing data due to skipped survey items were minimal (< 2% per variable). Attrition at T3 was not associated with any baseline measures, suggesting that the data met the requirements for “missing at random.” Missing data were thus managed with weighted least square mean and variance estimation (Enders, 2001). We ran the model presented in Figure 1 with levels of T1 negative schemas, T2 depressive symptoms, and T2 SDI controlled. We entered all direct and indirect pathways into the model simultaneously. Nonsignificant paths were removed post hoc to optimize model fit. Model fit was assessed per published criteria (Hu & Bentler, 1999). We tested the significance of the model’s indirect effects using bootstrapping procedures (Preacher & Hayes, 2008). Unstandardized indirect effects were computed for each of 5,000 bootstrapped samples, and we determined significance using a 95% confidence interval.

Figure 1.

Figure 1.

Open in a new tab

Study hypotheses

RESULTS

Sample descriptives by SDI status are presented in Table 1. Past-week prevalence of SDI was 35.5% at T2 and 33.6% at T3. Significant bivariate associations with SDI emerged for deprivation, threat, racial discrimination (T1), negative schemas (T2), and depressive symptoms (T2).

Table 1.

Sample Descriptive Statistics by Wave 3 Suicidal Ideation Status

Variables N (%) / M (SD) t/χ 2 p
Total Sample SDI+ SDI−
SDI T2 a 422 (100%) 150 (35.50%) 272 (64.50%) - -
SDI T3 a 408 (100%) 137 (33.60%) 271 (66.40%) - -
Age T1 b 20.07 (1.22) 20.08 (1.23) 20.05(1.30) 5.07 0.41
Maternal Education T1 a - - - 0.94 0.82
 Less than HS. 60 (11.91%) 16 (4.20%) 26 (6.80%) - -
 HS or GED 242 (48.10%) 68 (17.80%) 131 (34.40%) - -
 More than HS 165 (32.80%) 43 (11.20%) 97 (25.51%) - -
Depressive symptoms T2 b 7.99 (4.47) 9.20 (4.67) 7.37 (4.24) −3.83 0.00
Deprivation b −0.01 (2.36) 0.89 (2.40) −0.46 (2.22) −5.68 0.00
Threat b −0.06 (2.13) 0.86 (2.40) −0.52 (1.82) −6.44 0.00
Negative Schemas T1 b −0.01 (2.31) 0.59 (2.22) −0.40 (2.25) −4.21 0.00
Negative Schemas T2 b −0.05 (2.27) 0.55 (2.00) −0.355 (2.35) −3.70 0.00
Racial Discrimination T1 b 7.58 (5.27) 8.35 (5.69) 7.20 (5.00) −2.10 0.04
Open in a new tab

Note.

a

N (%).

b

M (SD). SDI+, Suicidal ideation; SDI-, No suicidal ideation; T1, Time 1; T2, Time 2; T3, Time 3; HS, high school; GED, general equivalency diploma.

Tests of the model presented in Figure 1 with standardized parameter estimates are presented in Figure 2.. The model fit the data as follows: χ2(2) = 5.75, p =.05 RMSEA = 0.06, CFI = 0.99. Childhood threat (β = 0.19, p < .001) and deprivation (β = 0.19, p < .001) directly predicted SDI at T3. Regarding the indirect pathways, deprivation significantly predicted negative schemas at T2 (β = 0.27, p < .01). We did not find, however, a significant association between childhood threat and negative relational schemas (β = 0.01, p = .88). Discrimination at T1 significantly predicted negative relational schemas at T2 (β = 0.09, p = .04). T2 negative schemas, in turn, forecast T3 SDI (β = 0.12, p = .03). T2 negative relational schemas significantly predicted T3 SDI (β = 0.12, p = .03), with T2 depressive symptoms and T2 SDI controlled.

Figure 2.

Figure 2.

Open in a new tab

Final model with standardized parameter estimates.

Abbreviations: T1, Time 1; T2, Time 2; T3, Time 3.

*p < .05, ** p <.01, *** p < .001.

Unstandardized indirect effects, along with their standard errors and confidence intervals, are presented in Table 2. The indirect effect is considered significant when the 95% confidence interval does not contain zero (Preacher & Hayes, 2008). Childhood deprivation indirectly predicted SDI via negative schemas (β = 0.03, p = .02, 95% CI [.014, .046]). Discrimination also indirectly predicted SDI via negative schemas (β = 0.01, p = .20, 95% CI [.001, .018]).

TABLE 2.

Standardized indirect effects, standard errors, and bootstrapped 95% confidence intervals.

Indirect effect Est. SE p 95% CI
Threat → Negative Schemas → SDI 0.00 0.00 0.86 −0.004, 0.001
Deprivation → Negative Schemas → SDI 0.03 0.01 0.02 0.014, 0.046
Discrimination → Negative Schemas → SDI 0.01 0.01 0.20 0.001, 0.018
Open in a new tab

Abbreviations: CI, confidence interval; SE, standard error; SDI, suicidal ideation

DISCUSSION

During the past 20 to 30 years, young Black men have evinced increasing levels of suicidal behavior and related cognitions (Emergency Taskforce on Black Youth Suicide and Mental Health, 2019). SDI, in particular, is both a component of depressive symptoms and an indicator of elevated emotional distress. By controlling for depressive symptoms in assessing increases in SDI over time, our study’s design directly informed the extent to which social adversities affect SDI independent of other depressive problems. Analyses largely supported the proposed model. Childhood adversities were associated directly with reports of SDI. Adversity characterized by deprivation, rather than threat, also affected SDI indirectly via influences on negative relational schemas. Racial discrimination during emerging adulthood also predicted an increase in negative schemas, which in turn predicted SDI.

Approximately one-third (33.6%) of participants reported suicidal or death ideation in the previous week. Elevated SDI is consistent with recent epidemiological data that document an alarming increase in suicidal cognitions and behavior among young Black men (Emergency Taskforce on Black Youth Suicide and Mental Health, 2019). Unfortunately, these trends are accompanied by many young Black men’s wariness regarding disclosing mental health concerns either to significant others or to professionals due to pervasive stigma associated with mental health concerns and mistrust of medical professionals (Mays et al., 2018).

Study findings underscore the impact of social adversities that disproportionately affect young Black men’s increases in SDI. Consistent with past research, a history of childhood adversity predicted increases in SDI during emerging adulthood (Enns et al., 2006). This was true in bivariate and model-based contexts in which direct effects emerged independently of other study variables. Experiences with deprivation and with threat evinced robust direct associations, suggesting that a broad range of adverse childhood experiences may affect SDI risk among Black American men.

In addition to direct effects on SDI, deprivation, but not threat, affected SDI via negative relational schemas. Research and theory suggest that deprivation will take a toll on processes associated with adult attachment, such as relationship schemas (Ahmadpanah et al., 2017) and attachment style (Stansfeld et al., 2008). Specifically, the combination of emotional neglect, physical neglect, and childhood poverty was associated with relational schemas characterized by mistrust and defensiveness, which in turn were associated with increased SDI. This is consistent with research linking high levels of early life adversity, a socially avoidant personal style, and suicidality (Rajalin et al., 2020). Negative childhood experiences have been linked to adults’ difficulty in cultivating robust support networks and mistrust of their romantic partners’ motives (Simons et al., 2012). Strained relationships, interpersonal conflicts, rejection, and isolation have been shown to be associated with suicidal behavior (King & Merchant, 2008). Men who experienced deprivation in childhood may be more likely to endorse mistrusting, cynical views of their relationships in emerging adulthood that affect their ability to develop engaged social networks.

Consistent with expectations and past research (Assari, Lankarani, et al., 2017), we documented an association between racial discrimination and elevated SDI. Moreover, the influence of racial discrimination was, in part, mediated by negative relational schemas. Racial discrimination is a pernicious and dehumanizing stressor that generates negative affect and can promote the development of a cynical, hostile view of people and relationships (Simons et al., 2006); past research suggests that this link is particularly pronounced among Black men compared with Black women (Simons et al., 2012). Pervasive experiences of racial discrimination also cultivate marginalizing environments wherein Black men may self-isolate or become openly hostile in their social interactions as a coping strategy for dealing with the realities of racism (Bernard et al., 2021; Lee & Bierman, 2019). Policy efforts designed to dismantle systemic racism are critically needed. For interventions that address SDI, including programming designed to support Black men through their experiences with racial discrimination and processing of childhood experiences of adversity, may help young Black men resist the psychological impacts of racism, expand their positive support networks, and decrease their risk of SDI.

Notably, the influence of study variables on SDI may generalize to experiences outside of the context of depressive symptomatology. This suggests that experiences with social adversity promote significant emotional distress for both depressed and nondepressed men. Suicidal and death related cognitions outside the context of depressive problems have significant consequences for suicidality, future mental health, and interpersonal functioning (Casey et al., 2008).

Limitations and constraints on generality

Key limitations of our study include the following. First, the study sample was recruited in rural areas in the southern state of Georgia, and findings may not generalize to Black men from other regions of the United States. However, we are aware of no studies suggesting that the effects of social adversity would operate differently in other samples. Second, retrospective measures of adversity are prone to recall biases. Studies support the accuracy and predictive validity, however, of young adults’ memories in recalling major, trauma-related events (Reuben et al., 2016). Moreover, measures such as the ACEs have been critique due to failing to include cultural level stressors such as racism. Thus our measurement of childhood adversity may be an underestimate. Third, use of self-report measures may increase the likelihood of Type 2 errors due to common method bias and recall bias associated with increased reports of childhood adversity among depressed individuals (Liu, 2017). This concern is obviated somewhat by the use of multiple measurement instruments for several constructs of interest. Finally, there are multiple exposures in childhood and adolescence not assessed in the current study that may affect emerging adult schemas. These limitations notwithstanding the present study identifies critical risk factors and processes linked to SDI among young Black men that may inform policy, prevention, and treatment in the future.

Supplementary Material

Supplemental Material

PUBLIC SIGNIFICANCE STATEMENT.

Black men report increasing vulnerability to suicide. Growing up in socioeconomically deprived environments and experiencing racial discrimination as a young adult increase risk for thoughts about suicide and death. Beliefs about relationships are an important factor explaining how these risks affect Black men.

REFERENCES

  1. Ahmadpanah M, Astinsadaf S, Akhondi A, Haghighi M, Bahmani DS, Nazaribadie M, Jahangard L, Holsboer-Trachsler E, & Brand S. (2017). Early maladaptive schemas of emotional deprivation, social isolation, shame and abandonment are related to a history of suicide attempts among patients with major depressive disorders. Comprehensive Psychiatry, 77, 71–79. 10.1016/j.comppsych.2017.05.008 [DOI] [PubMed] [Google Scholar]
  2. Assari S, Lankarani MM, & Caldwell CH (2017a). Discrimination increases suicidal ideation in Black adolescents regardless of ethnicity and gender. Behavioral Sciences, 7(4), Article 75. 10.3390/bs7040075 [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Assari S, Moazen-Zadeh E, & Caldwell CH (2017b). Racial discrimination during adolescence predicts mental health deterioration in adulthood: Gender differences among Blacks. Frontiers in Public Health, 5, Article 104. 10.3389/fpubh.2017.00104 [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Baldwin MW (1995). Relational schemas and cognition in close relationships. Journal of Social and Personal Relationships, 12(4), 547–552. 10.1177/0265407595124008 [DOI] [Google Scholar]
  5. Batterham PJ, van Spijker BAJ, Mackinnon AJ, Calear AL, Wong Q, & Christensen H. (2019). Consistency of trajectories of suicidal ideation and depression symptoms: Evidence from a randomized controlled trial. Depression and Anxiety, 36(4), 321–329. 10.1002/da.22863 [DOI] [PubMed] [Google Scholar]
  6. Bernard DL, Calhoun CD, Banks DE, Halliday CA, Hughes-Halbert C, & Danielson CK (2021). Making the “C-ACE” for a culturally-informed adverse childhood experiences framework to understand the pervasive mental health impact of racism on Black youth. Journal of Child & Adolescent Trauma, 14(2), 233–247. 10.1007/s40653-020-00319-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Bernstein DP, Ahluvalia T, Pogge D, & Handelsman L. (1997). Validity of the Childhood Trauma Questionnaire in an adolescent psychiatric population. Journal of the American Academy of Child and Adolescent Psychiatry, 36(3), 340–348. 10.1097/00004583-199703000-00012 [DOI] [PubMed] [Google Scholar]
  8. Björgvinsson T, Kertz SJ, Bigda-Peyton JS, McCoy KL, & Aderka IM (2013). Psychometric properties of the CES-D-10 in a psychiatric sample. Assessment, 20(4), 429–436. 10.1177/1073191113481998 [DOI] [PubMed] [Google Scholar]
  9. Boroujerdi FG, Kimiaee SA, Yazdi SAA, & Safa M. (2019). Attachment style and history of childhood abuse in suicide attempters. Psychiatry Research, 271, 1–7. 10.1016/j.psychres.2018.11.006 [DOI] [PubMed] [Google Scholar]
  10. Brody GH, Chen YF, Murry VM, Ge X, Simons RL, Gibbons FX, Gerrard M, & Cutrona CE (2006). Perceived discrimination and the adjustment of African American youths: A five-year longitudinal analysis with contextual moderation effects. Child Development, 77(5), 1170–1189. [DOI] [PubMed] [Google Scholar]
  11. Casey P, Dunn G, Kelly BD, Lehtinen V, Dalgard OS, Dowrick C, & Ayuso-Mateos JL (2008). The prevalence of suicidal ideation in the general population: Results from the Outcome of Depression International Network (ODIN) study. Social Psychiatry and Psychiatric Epidemiology, 43(4), 299–304. 10.1007/s00127-008-0313-5 [DOI] [PubMed] [Google Scholar]
  12. Castle K, Connor K, Kaukeinen K, & Tu X. (2011). Perceived racism, discrimination, and acculturation in suicidal ideation and suicide attempts among black young adults. Suicide and Life-Threatening Behavior, 41(3), 342–351. 10.1111/j.1943-278X.2011.00033.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Centers for Disease Control and Prevention. (2017). Leading Causes of Death, Males, Non-Hispanic Black, United States. CDC. https://www.cdc.gov/healthequity/lcod/men/2017/nonhispanic-black/index.htm [Google Scholar]
  14. Centers for Disease Control and Prevention. (2020). Web-based Injury Statistics Query and Reporting System (WISQARS). National Center for Injury Prevention and Control; Retrieved from https://www.cdc.gov/injury/wisqars/index.html [Google Scholar]
  15. Chu JP, Goldblum P, Floyd R, & Bongar B. (2010). The cultural theory and model of suicide. Applied and Preventive Psychology, 14(1–4), 25–40. 10.1016/j.appsy.2011.11.001 [DOI] [Google Scholar]
  16. Cobb RJ, & Davila J. (2009). Internal working models and change. In Obegi JH & Berant E. (Eds.), Attachment theory and research in clinical work with adults (pp. 209–233). The Guilford Press. https://psycnet.apa.org/record/2009-02347-000 [Google Scholar]
  17. Curtis MG, Oshri A, Bryant CM, Bermudez JM, & Kogan SM (2021). Contextual adversity and rural Black men’s masculinity ideology during emerging adulthood. Psychology of Men and Masculinity, 22(2), 217–226. 10.1037/men0000319 [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Dale R, Power K, Kane S, Stewart AM, & Murray L. (2010). The role of parental bonding and early maladaptive schemas in the risk of suicidal behavior repetition. Archives of Suicide Research, 14(4), 311–328. 10.1080/13811118.2010.524066 [DOI] [PubMed] [Google Scholar]
  19. Deykin EY, & Buka SL (1994). Suicidal ideation and attempts among chemically dependent adolescents. American Journal of Public Health, 84(4), 634–639. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Emergency Taskforce on Black Youth Suicide and Mental Health. (2019). Ring the Alarm: The Crisis of Black Youth Suicide in America. Congressional Black Caucus [Google Scholar]
  21. Enders CK (2001). The impact of nonnormality on full information maximum-likelihood estimation for structural equation models with missing data. Psychological Methods, 6(4), 352–370. 10.1037/1082-989X.6.4.352 [DOI] [PubMed] [Google Scholar]
  22. Enns MW, Cox BJ, Afifi TO, De Graaf R, Ten Have M, & Sareen J. (2006). Childhood adversities and risk for suicidal ideation and attempts: a longitudinal population-based study. Psychological Medicine, 36(12), 1769–1778. [DOI] [PubMed] [Google Scholar]
  23. Felitti VJ, Anda RF, Nordenberg D, Williamson DF, Spitz AM, Edwards V, Koss MP, & Marks JS (1998). Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults: The Adverse Childhood Experiences (ACE) Study. American Journal of Preventive Medicine, 14(4), 245–258. 10.1016/S0749-3797(98)00017-8 [DOI] [PubMed] [Google Scholar]
  24. Garlow SJ, Rosenberg J, Moore JD, Haas AP, Koestner B, Hendin H, & Nemeroff CB (2008). Depression, desperation, and suicidal ideation in college students: Results from the American Foundation for Suicide Prevention College Screening Project at Emory University. Depression and Anxiety, 25(6), 482–488. 10.1002/da.20321 [DOI] [PubMed] [Google Scholar]
  25. Gilbert KL, Ray R, Siddiqi A, Shetty S, Baker EA, Elder K, & Griffith DM (2016). Visible and Invisible Trends in Black Men’s Health: Pitfalls and Promises for Addressing Racial, Ethnic, and Gender Inequities in Health. Annual Review of Public Health, 37(1), 295–311. doi: 10.1146/annurev-publhealth-032315-021556 [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Goodwill JR, Taylor RJ, & Watkins DC (2021). Everyday discrimination, depressive symptoms, and suicide ideation among African American men. Archives of Suicide Research, 25(1), 74–93. 10.1080/13811118.2019.1660287 [DOI] [PubMed] [Google Scholar]
  27. Heckathorn DD (1997). Respondent-driven sampling: A new approach to the study of hidden populations. Social Problems, 44(2), 174–199. 10.2307/3096941 [DOI] [Google Scholar]
  28. Hu L. t., & Bentler PM (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55. 10.1080/10705519909540118 [DOI] [Google Scholar]
  29. Joo J, Hwang S, & Gallo JJ (2016). Death ideation and suicidal ideation in a community sample who do not meet criteria for major depression. Crisis, 37(2), 161–165. doi: 10.1027/0227-5910/a000365 [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Joseph NT, Peterson LM, Gordon H, & Kamarck TW (2021). The double burden of racial discrimination in daily-life moments: Increases in negative emotions and depletion of psychosocial resources among emerging adult African Americans. Cultural Diversity and Ethnic Minority Psychology, 27(2), 234–244. 10.1037/cdp0000337 [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Kerr J, Schafer P, Perry A, Orkin J, Vance M, & O’Campo P. (2018). The impact of racial discrimination on African American fathers’ intimate relationships. Race and Social Problems, 10(2), 134–144. 10.1007/s12552-018-9227-3 [DOI] [Google Scholar]
  32. Khan SQ, Berrington de Gonzalez A, Best AF, Chen Y, Haozous EA, Rodriquez EJ, Spillane S, Thomas DA, Withrow D, Freedman ND, & Shiels MS (2018). Infant and youth mortality trends by race/ethnicity and cause of death in the United States. JAMA Pediatrics, 172(12), Article e183317. 10.1001/jamapediatrics.2018.3317 [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. King CA, & Merchant CR (2008). Social and interpersonal factors relating to adolescent suicidality: A review of the literature. Archives of Suicide Research, 12(3), 181–196. 10.1080/13811110802101203 [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Kogan SM, Bae D, Cho J, Smith AK, & Nishitani S. (2021). Pathways linking adverse environments to emerging adults’ substance abuse and depressive symptoms: A prospective analysis of rural African American men. Development & Psychopathology, 33(4), 1496–1506. 10.1017/s0954579420000632 [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Kogan SM, Wejnert C, Chen Y-F, & Brody GH (2011). Respondent-driven sampling with hard-to-reach emerging adults: An introduction and case study with Rural African Americans. Journal of Adolescent Research, 26, 30–60. 10.1177/0743558410384734 [DOI] [Google Scholar]
  36. Landrine H, & Klonoff EA (1996). The Schedule of Racist Events: A measure of racial discrimination and a study of its negative physical and mental health consequences. Journal of Black Psychology, 22, 144–168. [Google Scholar]
  37. Langhinrichsen-Rohling J, Thompson K, Selwyn C, Finnegan H, & Misra T. (2017). Maladaptive schemas mediate poor parental attachment and suicidality in college students. Death Studies, 41(6), 337–344. 10.1080/07481187.2017.1280714 [DOI] [PubMed] [Google Scholar]
  38. Lavner JA, Barton AW, Bryant CM, & Beach SRH (2018). Racial discrimination and relationship functioning among African American couples. Journal of Family Psychology, 32(5), 686–691. 10.1037/fam0000415 [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Lee DB, Anderson RE, Hope MO, & Zimmerman MA (2020). Racial discrimination trajectories predicting psychological well-being: From emerging adulthood to adulthood. Developmental Psychology, 56(7), 1413. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Lee Y, & Bierman A. (2019). Loneliness as a mediator of perceived discrimination and depression: Examining education contingencies. International Journal of Aging and Human Development, 89(2), 206–227. 10.1177/0091415018763402 [DOI] [PubMed] [Google Scholar]
  41. Liu RT (2017). Childhood adversities and depression in adulthood: Current findings and future directions. Clinical Psychology, 24(2),140–153. doi: 10.1111/cpsp.12190. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Mays VM, Jones AL, Cochran SD, Taylor RJ, Rafferty JA, & Jackson JS (2018). Chronicity and mental health service utilization for anxiety, mood, and substance use disorders among Black men in the United States: Ethnicity and nativity differences. Healthcare, 6(2), Article 4. 10.3390/healthcare6020053 [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. McLaughlin KA, Sheridan MA, & Lambert HK (2014). Childhood adversity and neural development: Deprivation and threat as distinct dimensions of early experience. Neuroscience and Biobehavioral Reviews, 47, 578–591. 10.1016/j.neubiorev.2014.10.012 [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Muthén LK, & Muthén BO (1998–2017). Mplus user’s guide (8th ed.). Muthén & Muthén. [Google Scholar]
  45. Neacsiu AD, Fang CM, Rodriguez M, & Rosenthal MZ (2018). Suicidal behavior and problems with emotion regulation. Suicide and Life-Threatening Behavior, 48(1), 52–74. 10.1111/sltb.12335 [DOI] [PubMed] [Google Scholar]
  46. Palitsky D, Mota N, Afifi TO, Downs AC, & Sareen J. (2013). The association between adult attachment style, mental disorders, and suicidality: Findings from a population-based study. Journal of Nervous and Mental Disease, 201(7), 579–586. 10.1097/NMD.0b013e31829829ab [DOI] [PubMed] [Google Scholar]
  47. Polanco-Roman L, Anglin DM, Miranda R, & Jeglic EL (2019). Racial/ethnic discrimination and suicidal ideation in emerging adults: The role of traumatic stress and depressive symptoms varies by gender not race/ethnicity. Journal of Youth and Adolescence, 48(10), 2023–2037. 10.1007/s10964-019-01097-w [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Preacher KJ, & Hayes AF (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40(3), 879–891. 10.3758/BRM.40.3.879 [DOI] [PubMed] [Google Scholar]
  49. Rajalin M, Hirvikoski T, Renberg ES, Åsberg M, & Jokinen J. (2020). Exposure to early life adversity and interpersonal functioning in attempted suicide. Frontiers in Psychiatry, 11, Article 552514. 10.3389/fpsyt.2020.552514 [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Reuben A, Moffitt TE, Caspi A, Belsky DW, Harrington H, Schroeder F, Hogan S, Ramrakha S, Poulton R, & Danese A. (2016). Lest we forget: Comparing retrospective and prospective assessments of adverse childhood experiences in the prediction of adult health. Journal of Child Psychology and Psychiatry, 57(10), 1103–1112. 10.1111/jcpp.12621 [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Ribeiro JD, Huang X, Fox KR, & Franklin JC (2018). Depression and hopelessness as risk factors for suicide ideation, attempts and death: Meta-analysis of longitudinal studies. British Journal of Psychiatry, 212(5), 279–286. 10.1192/bjp.2018.27 [DOI] [PubMed] [Google Scholar]
  52. Scharfe E, & Cole V. (2006). Stability and change of attachment representations during emerging adulthood: An examination of mediators and moderators of change. Personal Relationships, 13(3), 363–374. doi: 10.1111/j.1475-6811.2006.00123.x [DOI] [Google Scholar]
  53. Scocco P, Meneghel G, Caon F, Dello Buono M, & De Leo D. (2001). Death Ideation and Its Correlates: Survey of an Over-65-Year-Old Population. The Journal of nervous and mental disease, 189(4). Retrieved from https://journals.lww.com/jonmd/Fulltext/2001/04000/Death_Ideation_and_Its_Correlates__Survey_of_an.2.aspx [DOI] [PubMed] [Google Scholar]
  54. Serafini G, Muzio C, Piccinini G, Flouri E, Ferrigno G, Pompili M, Girardi P, & Amore M. (2015). Life adversities and suicidal behavior in young individuals: A systematic review. European Child and Adolescent Psychiatry, 24(12), 1423–1446. 10.1007/s00787-015-0760-y [DOI] [PubMed] [Google Scholar]
  55. Simons RL, & Burt CH (2011). Learning to be bad: Adverse social conditions, social schemas, and crime. Criminology, 49(2), 553–598. 10.1111/j.1745-9125.2011.00231.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. Simons RL, Simons LG, Burt CH, Drummund H, Stewart EA, Brody GH, Gibbons FX, & Cutrona C. (2006). Supportive parenting moderates the effect of discrimination upon anger, hostile view of relationships, and violence among African American boys. Journal of Health and Social Behavior, 47(4), 373–389. 10.1177/002214650604700405 [DOI] [PubMed] [Google Scholar]
  57. Simons RL, Simons LG, Lei MK, & Landor AM (2012). Relational schemas, hostile romantic relationships, and beliefs about marriage among young African American adults. Journal of Social and Personal Relationships, 29(1), 77–101. 10.1177/0265407511406897 [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Stansfeld SA, Head J, Bartley M, & Fonagy P. (2008). Social position, early deprivation and the development of attachment. Social Psychiatry and Psychiatric Epidemiology, 43(7), 516–526. 10.1007/s00127-008-0330-4 [DOI] [PubMed] [Google Scholar]
  59. Stern JA, Barbarin O, & Cassidy J. (2022). Attachment perspectives on race, prejudice, and anti-racism: Introduction to the Special Issue. Attach Hum Dev, 24(3), 253–259. doi: 10.1080/14616734.2021.1976920 [DOI] [PMC free article] [PubMed] [Google Scholar]
  60. Stern JA, Jones JD, Nortey BM, Lejuez CW, & Cassidy J. (2022). Pathways linking attachment and depressive symptoms for Black and White adolescents: do race and neighborhood racism matter? Attachment & Human Development, 24(3), 304–321. doi: 10.1080/14616734.2021.1976924 [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Stewart EA, & Simons RL (2006). Structure and culture in African American adolescent violence: A partial test of the “code of the street” thesis. Justice Quarterly, 23(1), 1–33. 10.1080/07418820600552378 [DOI] [Google Scholar]
  62. Thompson MP, Kingree JB, & Lamis DA (2019). Associations of adverse childhood experiences and suicidal behaviors in adulthood in a U.S. nationally representative sample. Child: Care, Health and Development, 45(1), 121–128. 10.1111/cch.12617 [DOI] [PubMed] [Google Scholar]
  63. Umberson D, Williams K, Thomas PA, Liu H, & Thomeer MB (2014). Race, gender, and chains of disadvantage: Childhood adversity, social relationships, and health. Journal of Health and Social Behavior, 55(1), 20–38. 10.1177/0022146514521426 [DOI] [PMC free article] [PubMed] [Google Scholar]
  64. Van Orden KA, Simning A, Conwell Y, Skoog I, & Waern M. (2013). Characteristics and Comorbid Symptoms of Older Adults Reporting Death Ideation. The American Journal of Geriatric Psychiatry, 21(8), 803–810. doi: 10.1016/j.jagp.2013.01.015 [DOI] [PMC free article] [PubMed] [Google Scholar]
  65. Wei M, Russell DW, Mallinckrodt B, & Vogel DL (2007). The Experiences in Close Relationship Scale (ECR)–Short Form: Reliability, validity, and factor structure. Journal of Personality Assessment, 88(2), 187–204. 10.1080/00223890701268041 [DOI] [PubMed] [Google Scholar]
  66. Williams DR, & Mohammed SA (2013). Racism and health I: Pathways and scientific evidence. American Behavioral Scientist, 57(8), 1152–1173. 10.1177/0002764213487340 [DOI] [PMC free article] [PubMed] [Google Scholar]
  67. Wrath AJ, & Adams GC (2019). Self-injurious behaviors and adult attachment: A review of the literature. Archives of Suicide Research, 23(4), 527–550. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplemental Material
NIHMS1948422-supplement-Supplemental_Material.pdf (43.1KB, pdf)

RESOURCES