Discrimination Experiences and Violent Injury Risk Among Young Adults

Abstract

This study examines the frequency of specific discrimination experiences by attribution and social identities (i.e., race, gender) and quantifies if both frequent discrimination experiences and different types of discrimination are associated with violence exposure (i.e., victimization, aggression) and its behavioral and mental health risk factors for violent injury (e.g., substance use). We analyzed baseline survey data from a multi-site longitudinal study of emerging adults aged 18 to 24 recruited from emergency departments in Seattle, Philadelphia, and Flint (n = 1,506). We examined the frequency and attribution of discrimination experiences and assessed associations with violence exposure and its relevant behavioral and mental health risk factors, including suicidal ideation, substance use, and anxiety/depression. Overall, 79.1% reported experiencing discrimination in daily life and 31.2% experienced it more than weekly. Reports of more-than-weekly discrimination were highest among multiracial (40%) and non-gender conforming individuals (41.5%). Race, gender, and age were the most cited reasons. Participants reporting ≥weekly discrimination were more likely to report suicidal ideation in the past 2 weeks, drug misuse, firearm victimization, and recent mental health symptoms (depression and anxiety symptoms in the past 2 weeks; post-traumatic stress disorder symptoms in the past month) compared to those with less frequent or no discrimination. Of note, discrimination related to being treated as inferior, unintelligent, or with less courtesy showed the strongest associations with mental health symptoms, while more static associations, across discrimination types, were found with regard to substance use and violence outcomes. Given that types of discrimination experiences may be more strongly linked to mental health symptoms, highlighting the need to consider the specific nature of these experiences. Moreover, discrimination was more pervasive among some minoritized groups (e.g., multiracial, gender non-conforming), underscoring the need for an intersectional lens to understand and address this stressor effectively.

Keywords

aggression alcohol and drugs cultural contexts violence prevention mental health effects

Introduction

Violent injuries, including interpersonal injuries due to aggression and/or victimization and self-inflicted injuries, are the leading causes of death among emerging adults (ages 18–24, consistent with the definition of emerging adulthood; Arnett, 2000; Centers for Disease Control and Prevention [CDC], 2025). In recent national mortality data, suicide and homicide together account for roughly 30 deaths per day among emerging adults in the United States (e.g., ages 20–24), underscoring the significance of both self-directed and interpersonal violence in this age group (CDC, 2025). Interpersonal discrimination (hereafter, “discrimination”) is a significant psychosocial stressor pervasive in the lives of emerging adults, with a recent study showing that 93% of emerging adults reported experiencing discrimination on the basis of racial and ethnic identity or ancestry, sex, age, physical appearance, and other reasons (Lei et al., 2021).

Experiencing discrimination is associated with common risk factors for violent injury, including substance misuse (Lei et al., 2021), mental distress (Lee et al., 2020), and violent behaviors (Caldwell et al., 2004). Theoretically, the relationship between discrimination and violence exposure (hereafter, referring to violent victimization and aggression) can be understood through the Weathering Hypothesis (Geronimus, 1992), which suggests that chronic exposure to social discrimination erodes psychological and physiological health over time, contributing to risk factors linked with violent injury, such as substance misuse. Similarly, the Minority Stress Theory (Meyer, 2003), emphasizes the ways in which unique and compounding stresses experienced by individuals with marginalized identities deteriorates mental and physical health. Together, these and related theoretical models (e.g., stress and coping frameworks; Lazarus & Folkman, 1984), in conjunction with empirical studies (Emmer et al., 2024; Lee et al., 2020; Pascoe & Smart Richman, 2009; Schmitt et al., 2014), posit that routine experiences of discrimination impose a cumulative psychological burden that, over time, increases risk for maladaptive coping that puts individuals at-risk for violence toward oneself or others.

Discrimination also plays a critical role when considering the etiologies of persistent disparities in violent injuries (D. R. Williams & Mohammed, 2013). For example, researchers have documented that fatal and nonfatal firearm assault injuries are highest among Black males compared to males and females of other racial groups (CDC, 2025; Goldstick et al., 2021). There are higher suicidal ideation rates among LGBTQ+ emerging adults when compared to heterosexual peers (Ybarra et al., 2015). Scholars argue that these disparities reflect broader systems of oppression operating across both social processes (e.g., racial microaggressions, stereotypes, and implicit bias) and structural conditions (e.g., institutional policies and practices such as the school-to-prison pipeline; D. R. Williams & Mohammed, 2013). Importantly, discrimination and violence exposure may also co-occur rather than operate only through a downstream coping process. Overt manifestations of discrimination, such as being called a racial epithet or being physically threatened because of one’s race, may reflect forms of victimization rooted in prejudice (Díaz-Faes & Pereda, 2022). Thus, discrimination and violence exposure may arise from both prejudicial social environments, while discrimination may also contribute to violence-related risk through stress-related psychological and behavioral pathways (Lee et al., 2026; Lemke et al., 2022).

It is also important to recognize that victimization and aggression are often intertwined. Prior research documents substantial overlap between these experiences, making them difficult to treat as mutually exclusive categories (Goldstick, Carter, Whiteside, Delgado, & Cunningham, 2024; Jennings et al., 2012). For instance, Goldstick, Carter, Whiteside, Delgado, & Cunningham (2024) found that more than 90% of participants who experienced a firearm assault also reported firearm assault victimization. Discriminatory experiences may also heighten vigilance, retaliatory attitudes, and safety concerns (Copeland-Linder et al., 2012; Lee et al., 2022), which may increase risk for victimization and aggression by placing youth in more vulnerable environments or contributing to defensive responses, retaliation, or conflict escalation (Dong et al., 2020; Wiebe et al., 2015). Therefore, we examined violence involvement more broadly rather than stratifying analyses by victimization versus aggression.

In this study, we focus specifically on experiences of interpersonal discrimination in the lives of emerging adults. Interpersonal discrimination refers to unfair treatment enacted in social interactions (e.g., disrespect, harassment), whereas structural discrimination operates through institutional policies and broader social systems that shape unequal opportunities and exposures (e.g., residential racial segregation; Neblett, 2023). Structural forms of discrimination were not directly assessed in this study.

A substantial body of literature has established that discrimination is associated with poor mental health (Emmer et al., 2024; Schouler-Ocak & Moran, 2023; Shi et al., 2022), substance use (Lee et al., 2017; Rouhani et al., 2025), and other violent behaviors (Caldwell et al., 2004; Martin et al., 2011). This study seeks to extend this literature to violent injury-related risk factors by examining whether specific interpersonal discrimination experiences are associated with behavioral and mental health factors linked to violence involvement. This distinction is important because most studies in this area have relied on aggregated measures of discrimination, which may obscure whether particular types of discriminatory experiences are more strongly associated with risk. In addition, much of the firearm violence and injury literature has emphasized structural or place-based indicators of racism, with comparatively less attention to individuals’ lived experiences of interpersonal discrimination (Lee et al., 2026).

To date, few studies have examined discrimination and violent injury-related outcomes beyond the aggregation of multiple forms of discrimination, limiting insight into whether specific experiences relate to risk. Therefore, this study aims to: (1) characterize the prevalence of specific discrimination types, (2) examine attributions by race and gender, (3) examine the prevalence of more frequent (weekly) discrimination, and determine factors associated with more frequent discrimination experiences, and (4) evaluate if specific types of discrimination experiences relate to key behavioral and mental health risk factors for violence, including violence victimization and aggression.

Method

Study Design and Setting

Here, we present secondary data analysis from the Screening to Predict Young Adults at Risk for Firearm Violence (SPARK) study (Goldstick, Carter, Whiteside, Delgado, Stallworth, et al., 2024). Data for this study are from baseline assessments of a multi-site longitudinal study of risk factors that predict violence outcomes among emerging adults seeking treatment at four emergency departments that is, one in Seattle, one in Flint, and two in Philadelphia. The primary aim of SPARK was to externally validate the SaFETy score (Goldstick et al., 2017), the only clinical screening tool designed to assess risk for future firearm violence. Previous work from this study examined cross-sectional associations between the SaFETy score and firearm violence risk at baseline (Goldstick et al., 2024) and demonstrated the prospective predictive power of the SaFETy score with regard to firearm violence in the 12-month following baseline (Goldstick et al., 2026).

Eligible participants were those that were able to provide informed consent. Exclusions included sexual assault, psychosis, suicidal ideation, police custody, or—due to COVID-19 precautions—those requiring respiratory/droplet isolation. We selected these exclusion criteria because the goal of the study was to conduct prospective validation of a clinical screening tool for future firearm violence risk in a general sample of emerging adults presenting to the emergency department. Study staff used electronic health records to identify eligible patients and approached them in waiting or treatment areas. Consenting participants received $40 for completing the baseline survey and agreed to follow-up contact and 1-year chart review. The survey was self-administered and on rare occasions verbally administered by a research assistant. Participant recruitment began in Seattle, Philadelphia, and Flint sites on August 26, 2021; July 26, 2021; and January 24, 2022, respectively. Recruitment activities concluded on May 25, 2023 (Seattle), May 31, 2023 (Philadelphia), and May 9, 2023 (Flint). Overall, 25.4% refused/declined participation in the study. Additional recruitment details and the study flowchart are provided elsewhere (Goldstick, Carter, Whiteside, Delgado, Stallworth, et al., 2024). All study protocols were approved by the University of Michigan IRB.

Measures

We measured discrimination experiences using the Everyday Discrimination Scale (EDS; D. R. Williams et al., 1997). Participants rated the frequency of seven discriminatory experiences on a 6-point scale (1 = Never, 6 = Almost everyday). Items captured experiences such as being treated as less intelligent or receiving threats and experiencing harassment. The scale was slightly adapted for parsimony and to reduce redundancy: two items were combined (“treated with less courtesy or respect”) and another on name-calling was omitted. Participants reporting any discrimination also identified perceived reasons from a checklist of social identity categories, including ancestry/national origins, gender, race, age, religion, height, weight, some other aspect of physical appearance, sexual orientation, educational attainment, or other reasons.

In addition to demographic characteristics (age/gender/race), we measured violence experiences, mental health symptoms, and substance use outcomes. The modified conflict tactics scale separately measured past 6-month frequency of 11 violence behaviors, both as victim and aggressor; for this analysis, we collapsed the items to examine any violence, severe violence (e.g., weapon violence, beating up), and firearm violence (Straus et al., 1996), each stratified by victimization and aggression, and combined. We measured post-traumatic stress disorder (PTSD) symptoms in the past month using the PCL-17 (Lang & Stein, 2005), depressive symptoms in the past 2 weeks using the PHQ-9 (Richardson et al., 2010), and anxiety symptoms in the past 2 week using the GAD-7 (Spitzer et al., 2006); we determined positive screens using established clinical screening cut points of 10, 10, and 30, respectively. The Columbia Suicide Severity Scale measured past-2-week suicidal ideation (Posner et al., 2011). The NIDA-ASSIST measured the use of marijuana, illicit (e.g., cocaine, heroin, hallucinogens), and prescription (e.g., opioids, sedatives, stimulants) drugs, with a ≥4 score on any substance used as an indicator of drug misuse in the past 6 months (WHO ASSIST Working Group, 2002). The AUDIT-C (Bush et al., 1998) measured alcohol use frequency, with cut points of 3 and 4 indicating risky use in women, and men, respectively, in the past 6 months (Reinert & Allen, 2007).

Statistical Analysis

We descriptively summarized the frequency of each discrimination type in the sample; among those reporting ≥weekly discrimination, we examined reasons for discrimination, stratified by race and gender. Next, we contrasted those reporting ≥weekly discrimination with those who did not, by demographic characteristics, violence exposures, and substance use/mental health outcomes. Next, we used logistic regression to estimate odds ratios relating weekly discrimination to the binary indicators of violence exposure and substance use/mental health outcomes, adjusted for age, gender, race, and site. Finally, we examined whether each type of discrimination was associated with any violent aggression, violent victimization, and mental health/substance use outcomes, by estimating adjusted standardized mean differences (adjusted Cohen’s d) comparing participants who did and did not report each outcome, after controlling for age, gender, race, and site. We estimated adjusted Cohen’s d values as estimated marginal means, implemented in the R package emmeans. All analyses were completed using R version 4.4.1.

Results

Among 1,506 total participants across sites (61.3% female; 40.9% Black; 33.0% White), 79.1% reported experiencing discrimination. The most frequent experience was having other people act as though they are better than you, with 62.9% reporting having ever experienced it; 37.5% reported a history of discriminatory threats/harassment. Many (31.2%) participants reported experiencing discrimination more than weekly, with multiracial (40.0%) and non-gender conforming (41.5%) respondents reporting this most frequently. Table 1 presents discrimination frequencies by gender, and Table 2 presents discrimination experiences by race.

Table 1.

Frequency of Seven Different Types of Discrimination Among the SPARK Sample, Stratified by Gender.

Frequency by Response Category	DISCR1 (%)	DISCR2 (%)	DISCR3 (%)	DISCR4 (%)	DISCR5 (%)	DISCR6 (%)	DISCR7 (%)
Overall (n = 1,506)
Never	40.6	54.3	40.5	62.8	58.5	37.0	62.5
<1 per year	13.7	17.1	11.5	11.5	14.1	10.2	14.1
Few times per year	21.0	16.8	20.8	11.5	11.9	21.7	12.3
Few times per month	11.8	7.2	11.1	6.4	6.9	13.2	5.2
At least once a week	7.5	2.9	90.0	4.2	4.5	6.2	3.7
Almost everyday	5.4	1.6	7.1	3.7	40.0	11.7	2.3
Male (n = 540)
Never	38.7	54.7	42.7	52.1	54.5	35.3	61.9
<1 per year	13.1	14.8	11.2	13.3	13.2	9.2	15.0
Few times per year	20.7	18.0	18.7	12.9	13.2	24.2	12.3
Few times per month	12.5	7.5	10.3	8.0	7.0	10.9	3.6
At least once a week	9.2	3.2	9.9	6.9	6.8	7.5	3.7
Almost everyday	5.8	1.9	7.1	6.7	5.5	12.9	3.6
Female (n = 923)
Never	42.7	55.0	39.8	69.2	62.0	38.7	63.7
<1 per year	14.4	18.3	11.9	10.7	14.4	11.2	13.8
Few times per year	21.1	16.1	22.4	10.4	10.9	20.4	12.3
Few times per month	10.6	6.8	10.8	5.2	6.4	13.5	5.6
At least once a week	6.6	2.6	8.3	2.5	3.3	5.4	3.3
Almost everyday	4.6	1.3	6.9	2.0	3.0	10.8	1.3
Non-conforming (n = 41)
Never	17.5	35.0	22.5	57.5	32.5	20.0	40.0
<1 per year	5.0	20.0	7.5	7.5	20.0	0.0	12.5
Few times per year	22.5	20.0	15.0	17.5	20.0	20.0	10.0
Few times per month	27.5	15.0	27.5	10.0	17.5	37.5	17.5
At least once a week	7.5	5.0	15.0	5.0	2.5	7.5	12.5
Almost everyday	20.0	5.0	12.5	2.5	7.5	15.0	7.5

The columns are different questions about frequency of discriminatory experiences in day-to-day life:

DISCR1: You are treated with less courtesy or respect than other people are.

• 15 missing values; 9 among female, 5 among male, 1 among non-conforming

DISCR2: You receive poorer service than other people at restaurants or stores.

• 15 missing values; 8 among female, 6 among male, 1 among non-conforming

DISCR3: People act as if they think you are not smart.

• 13 missing values; 6 among female, 6 among male, 1 among non-conforming

DISCR4: People act as if they are afraid of you.

• 13 missing values; 7 among female, 5 among male, 1 among non-conforming

DISCR5: People act as if they think you are dishonest.

• 13 missing values; 4 among female, 8 among male, 1 among non-conforming

DISCR6: People act as if they are better than you are.

• 13 missing values; 5 among female, 7 among male, 1 among non-conforming

DISCR7: You are threatened or harassed.

• 14 missing values; 8 among female, 5 among male, 1 among non-conforming

Note. There were two missing values for the self-identified gender question. SPARK = Screening to Predict Young Adults at Risk for Firearm Violence.

Table 2.

Frequency of Seven Different Types of Discrimination Among the SPARK Sample, Stratified by Race.

Frequency by Response Category	DISCR1 (%)	DISCR2 (%)	DISCR3 (%)	DISCR4 (%)	DISCR5 (%)	DISCR6 (%)	DISCR7 (%)
Black (n = 616)
Never	50.1	55.0	47.9	61.6	61.8	44.8	73.2
<1 per year	14.6	16.3	10.7	9.3	13.9	10.6	9.7
Few times per year	15.1	16.6	18.0	12.5	7.9	16.0	7.9
Few times per month	9.9	7.6	7.0	6.7	7.0	10.0	4.3
At least once a week	4.9	3.1	8.0	4.1	3.8	4.1	2.6
Almost everyday	5.4	1.5	8.4	5.7	5.6	14.5	2.5
White (n = 497)
Never	33.6	60.9	35.2	66.8	57.9	30.4	53.1
<1 per year	13.0	15.4	10.7	12.3	14.8	10.3	17.6
Few times per year	24.9	15.6	24.3	9.5	14.8	26.6	16.8
Few times per month	14.6	5.5	15.2	6.7	6.7	16.0	6.5
At least once a week	9.3	1.2	9.9	30.0	3.4	7.7	3.7
Almost everyday	4.7	1.4	4.7	1.6	2.4	8.9	2.2
Multiracial (n = 145)
Never	29.8	40.8	22.5	47.9	40.8	26.1	44.4
<1 per year	10.6	17.6	13.4	12.0	11.3	7.7	21.8
Few times per year	20.6	19.0	24.6	16.9	21.8	20.4	17.6
Few times per month	16.3	12.7	16.9	9.2	11.3	20.4	6.3
At least once a week	14.9	6.3	11.3	9.2	9.9	12.0	5.6
Almost everyday	7.8	3.5	11.3	4.9	4.9	13.4	4.0
Other (n = 219)
Never	36.2	47.2	43.1	65.6	61.0	36.2	62.8
<1 per year	14.7	22.5	14.2	15.1	14.7	11.0	14.7
Few times per year	27.5	17.9	18.3	10.1	11.5	27.1	12.4
Few times per month	9.6	7.8	10.1	4.1	4.6	11.5	4.1
At least once a week	6.4	3.2	7.8	3.2	5.5	5.0	5.0
Almost everyday	5.5	1.4	6.4	1.8	2.8	9.2	0.9

The columns are different questions about frequency of discriminatory experiences in day-to-day life:

DISCR1: You are treated with less courtesy or respect than other people are.

• 15 missing values; 7 among Black, 3 among White, 4 among Multiracial, 1 among Other

DISCR2: You receive poorer service than other people at restaurants or stores.

• 15 missing values; 7 among Black, 4 among White, 3 among Multiracial, 1 among Other

DISCR3: People act as if they think you are not smart.

• 13 missing values; 6 among Black, 3 among White, 3 among Multiracial, 1 among Other

DISCR4: People act as if they are afraid of you.

• 13 missing values; 6 among Black, 3 among White, 3 among Multiracial, 1 among Other

DISCR5: People act as if they think you are dishonest.

• 13 missing values; 6 among Black, 3 among White, 3 among Multiracial, 1 among Other

DISCR6: People act as if they’re better than you are.

• 13 missing values; 6 among Black, 4 among White, 3 among Multiracial, 1 among Other, 1 with missing race

DISCR7: You are threatened or harassed.

• 14 missing values; 5 among Black, 4 among White, 3 among Multiracial, 1 among Other, 1 with missing race

Note. There were 33 missing values for the self-identified race question. SPARK = Screening to Predict Young Adults at Risk for Firearm Violence.

Supplemental Appendix Figure S1 shows frequency of perceived reasons for discrimination, among those reporting ≥weekly discrimination, stratified by gender/race. Race (44.6%), gender (44.4%), and age (42.4%) were most frequently cited as perceived discrimination reasons. Racialized minorities more frequently cited race as a perceived reason, non-gender conforming individuals cited gender and sexual orientation, and women cited gender.

Table 3 presents unadjusted contrasts of those reporting, and not reporting, ≥weekly discrimination. Across our sociodemographic variables, Women, younger adults, and multiracial respondents more frequently reported ≥weekly discrimination; those from Seattle reported ≥weekly discrimination most frequently, and those from Philadelphia reported least frequently. Table 4 presents adjusted contrasts of those reporting ≥weekly discrimination for violence exposure, mental health symptoms, and substance use. Violence exposure rates were uniformly higher among those reporting ≥weekly discrimination, including >4× the risk of past-6-month firearm victimization. Self-reported mental health symptoms were most common among those who experienced ≥weekly discrimination, ranging from ~4× higher rates (depression) to >6× higher rates (PTSD). Moreover, past-2-week suicidal ideation was >5× higher (8.6%-vs.-1.7%) among those reporting ≥weekly discrimination. Alcohol misuse was more common among those experiencing ≥weekly discrimination (34.9%-vs.-31.3%), but there were no significant differences in the odds of risky alcohol use.

Table 3.

Contrasts Between Those Who Report, and Do Not Report, Weekly or Greater Discrimination Experiences on Demographics, Violence Experiences, and Mental Health and Substance Use Symptoms.

Participant Characteristics	Total sample (n = 1,506)^a	Reporting >weekly discrimination (n = 462)^b	Not reporting >weekly discrimination (n = 1,021)^c	Unadjusted odds ratio [95% CI]
Age	21.3 (1.9)	21.1 (2.0)	21.4(1.9)	0.93 [0.88, 0.98]
Gender ^b
Male	540 (35.9%)	196 (42.4%)	335 (32.9%)	(Ref)
Female	923 (61.4%)	249 (53.9%)	661 (64.9%)	0.64 [0.51, 0.81]
Non-conforming	41 (2.7%)	17 (3.7%)	23 (2.3%)	1.26 [0.66, 2.42]
Race ^c
Black	616 (41.7%)	190 (42.1%)	412 (41.0%)	(Ref)
White	497 (33.6%)	146 (32.4%)	347 (34.6%)	0.91 [0.70, 1.18]
Multiracial	145 (9.8%)	58 (12.9%)	84 (8.4%)	1.49 [1.03, 2.18]
Other	219 (14.8%)	57 (12.6%)	161 (16.1%)	0.77 [0.54, 1.09]
Site
Seattle, WA	649 (43.1%)	229 (49.6%)	410 (40.2%)	(Ref)
Flint, MI	318 (21.1%)	99 (21.4%)	216 (21.2%)	0.82 [0.62, 1.09]
Philadelphia, PA	539 (35.8%)	134 (29.0%)	395 (38.7%)	0.61 [0.47, 0.78]
Past 6-month Violence Experience
Any violence	740 (50.0%)	322 (70.5%)	409 (40.7%)	3.48 [2.74, 4.41]
Any violent victimization	655 (44.0%)	300 (65.6%)	346 (34.3%)	3.66 [2.90, 4.62]
Any violent aggression	511 (34.6%)	235 (51.6%)	268 (26.7%)	2.93 [2.32, 3.69]
Any severe violence	580 (39.2%)	271 (59.3%)	300 (29.9%)	3.41 [2.71, 4.30]
Any severe violent victimization	508 (34.2%)	245 (53.7%)	254 (25.2%)	3.44 [2.73, 4.34]
Any severe violent aggression	367 (24.8%)	185 (40.7%)	174 (17.3%)	3.28 [2.56, 4.21]
Any firearm violence	87 (5.9%)	50 (11.0%)	32 (3.2%)	3.78 [2.39, 5.97]
Any firearm victimization	75 (5.0%)	47 (10.3%)	23 (2.4%)	4.73 [2.85, 7.84]
Any firearm aggression	30 (2.1%)	17 (3.8%)	12 (1.2%)	3.23 [1.53, 6.82]
Mental Health/Substance Use
Positive PTSD Screen	430 (29.6%)	257 (57.8%)	172 (17.4%)	6.50 [5.06, 8.35]
Positive Depression Screen	512 (34.7%)	263 (58.3%)	246 (24.4%)	4.33 [3.42, 5.48]
Positive Anxiety Screen	513 (34.7%)	279 (62.0%)	230 (22.7%)	5.54 [4.36, 7.05]
Past 2-week Suicidal Ideation	56 (3.8%)	38 (8.6%)	17 (1.7%)	5.47 [3.05, 9.80]
Positive Alcohol Misuse Screen	481 (32.2%)	160 (34.9%)	318 (31.3%)	1.17 [0.93, 1.48]
Positive Drug Misuse Screen	733 (48.9%)	290 (63.3%)	436 (42.7%)	2.31 [1.84, 2.90]

Note. The indicator of at least weekly discrimination experience is missing for 23 (1.5%) respondents.

PTSD: post-traumatic stress disorder.

Because of missing data, cell percentages may not be out of the column total. Age and site had no missing data. The number for the other variables ranged from 2 (0.1%: gender) to 55 (3.7%, PTSD screen).

Because of missing data, cell percentages may not be out of the column total. Age, site, and gender had no missing data. The number for the other variables ranged from 5 (1.1%: Past 6-month violence, Past 6-month victimization, and Past 6-month severe violence) to 19 (4.1%, Past 2-week suicidal ideation).

Because of missing data, cell percentages may not be out of the column total. Age and site had no missing data. The number for the other variables ranged from 2 (0.2%: gender) to 31 (3.0%, PTSD screen).

Table 4.

Odds Ratio, Adjusted for Age, Gender, Race, and Site, Relating Each Violence, Mental Health, and Substance Use Variable to Weekly (or Greater) Discrimination Experiences.

Types of Violence, Substance Use, and Mental Health	Adjusted odds ratio [95% CI]
Past 6-month Violence Experience
Any violence	3.36 [2.63, 4.30]
Any violent victimization	3.49 [2.75, 4.44]
Any violent aggression	2.88 [2.27, 3.66]
Any severe violence	3.24 [2.55, 4.12]
Any severe violent victimization	3.26 [2.56, 4.14]
Any severe violent aggression	3.16 [2.45, 4.09]
Any firearm violence	3.26 [2.03, 5.22]
Any firearm victimization	4.01 [2.39, 6.74]
Any firearm aggression	2.65 [1.22, 5.73]
Mental Health/Substance Use
Positive PTSD Screen	7.20 [5.51, 9.40]
Positive Depression Screen	4.56 [3.55, 5.84]
Positive Anxiety Screen	5.76 [4.48, 7.41]
Past 2-week Suicidal Ideation	5.19 [2.87, 9.41]
Positive Alcohol Misuse Screen	1.28 [1.00, 1.65]
Positive Drug Misuse Screen	2.14 [1.69, 2.71]

Note. Models adjusted for age, gender, race, and site.

PTSD: post-traumatic stress disorder.

Figure 1 shows adjusted Cohen’s d differentiating those with versus those without six behavioral and mental risk factors of violence, including violence, by each discrimination measure, controlling for gender, age, race, and site. Each type of discrimination showed similar effect sizes on drug misuse, risky alcohol use, violent victimization, and violent aggression, with overlapping confidence intervals indicating relatively small differences across discrimination types. Items on discrimination experiences related to perceptions of being treated less courteous, being treated as unintelligent, being treated as dishonest, and being treated as inferior showed larger effect sizes on anxiety and/or depression, and PTSD than items related to perceptions of others treating you as though they are afraid of you or giving you poorer service at stores/restaurants.

Figure 1.

Standardized mean difference in each of seven discrimination scores between those who do versus do not report six psychosocial outcomes.

Discussion

Our findings, in conjunction with other studies, show that discrimination is a common stressor, with nearly 1-in-3 participants reporting at least weekly discrimination experiences, and is strongly associated with a history of firearm victimization, recent suicidal ideation, drug misuse and mental health symptoms (Clark et al., 1999; Lei et al., 2021; Mattingly et al., 2025; Pascoe & Smart Richman, 2009). Importantly, consistent with the biopsychosocial model for perceived racism (Clark et al., 1999), we found that all of the different discrimination types were associated with positive screening for mental health symptomology. That said, the size of the association varied depending on the type of discrimination experienced. Consistent, robust associations were found between different discrimination types and violence exposure after controlling for gender, age, race, and site. One possible explanation is that mental health outcomes are more proximal, reflecting the immediate psychological toll of discriminatory encounters (Clark et al., 1999; Lee et al., 2018; Pascoe & Smart Richman, 2009). Because distress is thought to vary with the nature of the stressor, the stress and coping theory (Lazarus & Folkman, 1984) suggests that the psychological impact of a stressor depends not only on whether the event occurred but also on how the event is appraised. Therefore, stressors appraised as more degrading or threatening may show stronger associations with depression, anxiety, or PTSD (Lee et al., 2020). By contrast, alcohol/drug misuse and violent involvement may represent downstream coping responses or contextual consequences of sustained exposure, making them less sensitive to discrimination type and more uniform across forms. For instance, as per the tension reduction theory (Cappell & Greeley, 1987), mental health symptoms may represent a more proximal, emotional response to discriminatory stress to degrading or threatening encounters. By contrast, alcohol/drug misuse and violent involvement may represent more distal outcomes that represent coping behaviors to alleviate negative emotional responses. Nevertheless, the findings suggest that interventions addressing discrimination experiences broadly may be beneficial, while in some cases greater efficiency may be achieved by tailoring strategies to the specific type of discrimination experienced. For example, experiences involving perceived inferiority, such as being treated as less intelligent or with less courtesy, were more strongly associated with depression and/or anxiety, and PTSD than experiences like being feared or receiving poor service. Experiences that communicate devaluation of competence or social worth may be particularly salient for internalizing symptoms because they directly challenge core aspects of identity and self-evaluation. Such experiences may also be difficult to dismiss or attribute to situational factors, and often occur in subtle, but chronic forms across everyday interactions, which may cumulatively contribute to depressive and anxiety-related symptoms (D. R. Williams et al., 2019). Taken together, the strong associations we observed suggest that addressing discrimination-related stressors by expanding access to responsive services—such as, culturally responsive and accessible mental health care that addresses racism-related stress and trauma (M. T. Williams et al., 2023)—may help emerging adults manage its socioemotional consequences of discrimination.

Discrimination was particularly frequent among multiracial and gender non-conforming individuals. Consistent with intersectionality frameworks, our findings indicate that discrimination is patterned across intersecting social positions, and participants’ attributions for unfair treatment often reflect multiple marginalized identities (Crenshaw, 1997; Lam et al., 2024). These findings underscore the need for targeted, intersectional strategies to prevent interpersonal discrimination among emerging adults. Potential approaches include revising institutional and organizational policies and protocols in settings where emerging adults commonly interact with institutions (e.g., schools, workplaces, and healthcare environments) to reduce discriminatory discretion based on marginalized social identities (e.g., race. gender and age), implementing routine training focused on bias toward multiracial and gender-diverse individuals, and establishing accountability and feedback mechanisms to allow and address reports of discriminatory treatment (Crenshaw, 1997; Hebl et al., 2015; Roberson et al., 2020). Such efforts must center lived experiences of those with multiple marginalized identities and engage them in shaping equity efforts (e.g., gendered racism; Erving et al., 2022). Thus, prevention efforts must acknowledge and address the multifaceted systems of power such as racism and sexism that operate in tandem to enable and reinforce interpersonal discrimination experiences in the first place (Crenshaw, 1997).

This study has several limitations. First, its cross-sectional design precludes causal inference. Yet, it is among the first to examine whether specific discrimination experiences relate to violence exposure and its behavioral and mental health risk factors. Second, we recruited our sample from four emergency departments across three urban centers, which may limit generalizability. Furthermore, we excluded individuals presenting with sexual assault, psychosis, active suicidal ideation, police custody, or other ineligible conditions due to COVID-19 precautions. Still, its geographic diversity (Philadelphia, Flint, Seattle) enhances relevance specifically to urban populations and highlights the need for broader demographic representation. Third, while the EDS was modified, the scale retained strong coverage of both implicit (e.g., being seen as unintelligent) and overt (e.g., harassment) discrimination. Future research should examine the impact of omitted or combined items and explore other forms of discrimination to better identify those most strongly linked to violent injury. Fourth, we combined Asian, Hispanic, and American Indian individuals into an “other” category due to limited sample sizes, preventing reliable inference. Future research should recruit larger samples to allow disaggregation and examination across racial/ethnic groups. Lastly, this study did not evaluate the composite score of the EDS, as has been done in prior work. Instead, we intentionally focused on item-level associations to provide an initial, descriptive examination of whether specific discrimination experiences show differential relationships with violent outcomes and its related behavioral and mental health risk factors. Future research should build on this work using measures of interpersonal discrimination that capture a broader range of experiences across multiple settings (e.g., work, school) to examine which forms of discrimination have distinct associations with violent injury risk. Such work can help inform tailored violent injury prevention efforts by pinpointing which discrimination experiences are most strongly linked to violent injury risk.

Social determinants such as discrimination are correlated with violence exposure and relevant behavioral and mental health risk factors. Violence prevention efforts, thus, should consider mitigating the psychological consequences of discrimination and implement policies and practices to prevent its many forms. Our disaggregated findings also suggest value in tailoring responses by discrimination type, depending on the behavioral and mental health risk factors targeted by those activities. Taken together, our findings clarify our understanding of whether discrimination relates to violent injury risk and highlight pathways to optimizing prevention.

Supplemental Material

sj-docx-1-jiv-10.1177_08862605261459046 – Supplemental material for Discrimination Experiences and Violent Injury Risk Among Young Adults

Supplemental material, sj-docx-1-jiv-10.1177_08862605261459046 for Discrimination Experiences and Violent Injury Risk Among Young Adults by Daniel B. Lee, Sara F. Jacoby, Eugenio Weigend Vargas, Patrick M. Carter, Arleen Lopez Cruz, Mucio Kit Delgado and Jason E. Goldstick in Journal of Interpersonal Violence

Footnotes

ORCID iD

Daniel B. Lee

Funding

The authors disclosed receipt of the following financial support for the research and/or authorship of this article: This research was supported by the National Center for Injury Prevention and Control R01CE003294 (PI: Jason E. Goldstick).

Declaration of Conflicting Interests

The authors declared no potential conflicts of interests with respect to the authorship and/or publication of this article.

Supplemental Material

Supplemental material for this article is available online.

Author Biographies

Daniel B. Lee, PhD, is a research assistant professor at the University of Michigan Institute for Firearm Injury Prevention and the School of Social Work. His research focuses on socioecological factors that contribute to youth firearm violence, with particular attention to those living in communities facing concentrated disadvantage. Trained in clinical and quantitative psychology, as well as public health, he investigates how socioecological contexts influence psychological responses—such as retaliatory attitudes and hopelessness—that increase the risk of firearm carriage and aggression. His work also examines how the context and conditions in which youth reside contribute to downstream risk factors for violence. In parallel, he highlights protective factors, including organized activity participation, that buffer against these risks. He has evaluated violence prevention strategies such as Crime Prevention Through Environmental Design, the Say Something Anonymous Reporting System, Youth Empowerment Solutions, and public art installations.

Sara F. Jacoby, PhD, is an associate professor at the University of Pennsylvania School of Nursing in the Department of Family and Community Health. Her research focuses on the structural origins of racialized disparities in trauma and violence victimization and how opportunities for injury recovery, restoration, and health are constructed in American cities and the healthcare system. Her work combines qualitative, quantitative, and spatial research methods to advance a comprehensive understanding of the complex issues she studies. She values community partnerships and actively involves community-based organizations and public agencies in her research. One of her notable areas of expertise is in conducting in-depth qualitative research to elicit the lived experiences of individuals who have been impacted by individual and structural violence, notably gun violence, racism, residential segregation, and economic marginalization.

Eugenio Weigend Vargas, PhD, is a postdoctoral research fellow at the University of Michigan Institute for Firearm Injury Prevention. He has focused his work on preventing firearm-related violence in the United States and Mexico. His research has examined trends and disparities in rates of firearm deaths across states, racial/ethnic subpopulation, and gender.

Patrick M. Carter, MD, is a professor of Emergency Medicine (School of Medicine) and Health Behavior and Health Equity (School of Public Health) at the University of Michigan. He is the Co-Director of the University of Michigan Institute for Firearm Injury Prevention and the Co-Director of the CDC-funded University of Michigan Injury Prevention Center. His research is within the field of firearm injury prevention, specifically the development, testing, and implementation of emergency department (ED)-based interventions to decrease firearm violence, youth violence, and associated risk behaviors such as substance use among high-risk urban youth populations. He also has a line of research focused on using intensive longitudinal data, collected via innovative m-health applications, to characterize epidemiological and contextual factors underlying adolescent risky firearm behaviors.

Arleen Lopez Cruz, BS, earned a bachelor’s degrees in behavioral neuroscience and biology with a psychology minor and honors college concentration. She plans to pursue an MD/MPH to continue working for her communities. She is passionate about healthcare equity, patient satisfaction, and community service in underrepresented communities.

Mucio Kit Delgado, MD, is an associate professor of Emergency Medicine at the University of Pennsylvania’s Perelman School of Medicine. He is also the faculty director of the Penn Medicine Nudge Unit, the world’s first behavioral design team embedded within a health system. He is also an attending physician in the Emergency Department at Penn Presbyterian Medical Center, an associate director at the Center for Health Incentives and Behavioral Economics, co-chair of the Penn Medicine’s Opioid Task Force, and co-director of Penn PORTAL (Patient-Oriented Research and Training to Accelerate Learning), 1 of 16 U.S. Centers of Excellence in learning health system science. His research blends behavioral and data science with insights gleaned from practicing emergency medicine in an urban trauma center to guide patients and clinicians toward decisions that enhance personal safety and improve the quality of acute care. He is passionate about leading multidisciplinary teams to address pressing public health problems. His portfolio includes work to curb the opioid overdose crisis and the COVID-19 pandemic, reduce trauma and firearm injuries, and decrease distracted and alcohol-impaired driving.

Jason E. Goldstick, PhD, is director of Statistics and Methods in the CDC-funded University of Michigan Injury Prevention Center and a research associate professor of Emergency Medicine and Health Behavior and Health Equity at the University of Michigan. As a PhD-trained statistician and injury prevention researcher, he has extensive and varied applied expertise with analytically complex injury prevention research projects. He has been PI of several NIAAA, NIDA, and CDC grants all related to novel analytic approaches applied to injury and violence research and have been lead statistician on over a dozen federally funded studies, including RCTs, observational studies, and projects involving the complex spatial and longitudinal analyses. His largest ongoing projects he directs as PI are an opioid overdose surveillance system for the state of Michigan, and a prospective longitudinal study focused on applying machine learning methods to develop an optimal brief screen for future firearm violence.

References

Arnett

J. J.

(2000). Emerging adulthood. A theory of development from the late teens through the twenties. The American Psychologist, 55(5), 469–480.

Bush

Kivlahan

D. R.

McDonell

M. B.

Fihn

S. D.

Bradley

K. A.

& for the Ambulatory Care Quality Improvement Project (ACQUIP). (1998). The AUDIT Alcohol Consumption Questions (AUDIT-C): An effective brief screening test for problem drinking. Archives of Internal Medicine, 158(16), 1789–1795. https://doi.org/10.1001/archinte.158.16.1789

Caldwell

C. H.

Kohn-Wood

L. P.

Schmeelk-Cone

K. H.

Chavous

T. M.

Zimmerman

M. A.

(2004). Racial discrimination and racial identity as risk or protective factors for violent behaviors in African American young adults. American Journal of Community Psychology, 33(1), 91–105. https://doi.org/10.1023/B:AJCP.0000014321.02367.dd

Cappell

Greeley

(1987). Alcohol and tension reduction: An update on research and theory. In Blane

H. T.

Leonard

K. E.

(Eds.), Psychological Theories of drinking and alcoholism (pp. 15–54). Guilford Press.

Centers for Disease Control and Prevention (CDC). (2025). WISQARS (Web-based Injury Statistics Query and Reporting System). https://www.cdc.gov/injury/wisqars/index.html

Clark

Anderson

N. B.

Clark

V. R.

Williams

D. R.

(1999). Racism as a stressor for African Americans: A biopsychosocial model. American Psychologist, 54(10), 805–816. https://doi.org/10.1037/0003-066X.54.10.805

Copeland-Linder

Johnson

S. B.

Haynie

D. L.

Chung

Cheng

T. L.

(2012). Retaliatory attitudes and violent behaviors among assault-injured youth. Journal of Adolescent Health, 50(3), 215–220. https://doi.org/10.1016/j.jadohealth.2011.04.005

Crenshaw

(1997). Demarginalizing the intersection of race and sex: A black feminist critique of antidiscrimination doctrine, feminist theory and antiracist politics. University of Chicago Legal Forum, 1989(1), 139–167.

Díaz-Faes

D. A.

Pereda

(2022). Is there such a thing as a hate crime paradigm? An integrative review of bias-motivated violent victimization and offending, its effects and underlying mechanisms. Trauma, Violence, & Abuse, 23(3), 938–952. https://doi.org/10.1177/1524838020979694

10.

Dong

Morrison

C. N.

Branas

C. C.

Richmond

T. S.

Wiebe

D. J.

(2020). As violence unfolds: A space–time study of situational triggers of violent victimization among urban youth. Journal of Quantitative Criminology, 36(1), 119–152. https://doi.org/10.1007/s10940-019-09419-8

11.

Emmer

Dorn

Mata

(2024). The immediate effect of discrimination on mental health: A meta-analytic review of the causal evidence. Psychological Bulletin, 150(3), 215–252. https://doi.org/10.1037/bul0000419

12.

Erving

C. L.

Williams

T. R.

Frierson

Derisse

(2022). Gendered racial microaggressions, psychosocial resources, and depressive symptoms among black women attending a historically Black university. Society and Mental Health, 12(3), 230–247. https://doi.org/10.1177/21568693221115766

13.

Geronimus

A. T.

(1992). The weathering hypothesis and the health of African-American women and infants: Evidence and speculations. Ethnicity & Disease, 2(3), 207–221.

14.

Goldstick

J. E.

Carter

P. M.

Cunningham

R. M.

(2021). Current epidemiological trends in firearm mortality in the United States. JAMA Psychiatry, 78(3), 241–242. https://doi.org/10.1001/jamapsychiatry.2020.2986

15.

Goldstick

J. E.

Carter

P. M.

Delgado

M. K.

Whiteside

L. K.

Cunningham

R. M.

(2026). Multi-site external validation of a clinical screening tool for interpersonal firearm violence risk. Annals of Internal Medicine, 179(5), 645–655.

16.

Goldstick

J. E.

Carter

P. M.

Walton

M. A.

Dahlberg

L. L.

Sumner

S. A.

Zimmerman

M. A.

Cunningham

R. M.

(2017). Development of the SaFETy score: A clinical screening tool for predicting future firearm violence risk. Annals of Internal Medicine, 166(10), 707–714. https://doi.org/10.7326/M16-1927

17.

Goldstick

J. E.

Carter

P. M.

Whiteside

Delgado

M. K.

Cunningham

R. M.

(2024). Association between the SaFETy score and self-reported firearm violence among young adults presenting to emergency departments in three cities: A cross-sectional study. Annals of Internal Medicine, 177(6), 831–833. https://doi.org/10.7326/M24-0026

18.

Goldstick

J. E.

Carter

P. M.

Whiteside

Delgado

M. K.

Stallworth

Sullivan

Childs

Taga

Cunningham

R. M.

(2024). Firearm violence and associated factors among young adults presenting to emergency departments in three cities: Baseline results from Project SPARK. Preventive Medicine, 189, Article 108124. https://doi.org/10.1016/j.ypmed.2024.108124

19.

Hebl

Ruggs

Martinez

Trump-Steele

Nittrouer

(2015). Understanding and reducing interpersonal discrimination in the workplace. In Todd D. Nelson (Ed.), Handbook of prejudice, stereotyping, and discrimination (2nd ed.). Psychology Press.

20.

Jennings

W. G.

Piquero

A. R.

Reingle

J. M.

(2012). On the overlap between victimization and offending: A review of the literature. Aggression and Violent Behavior, 17(1), 16–26. https://doi.org/10.1016/j.avb.2011.09.003

21.

Lam

J. T. H.

Coret

Khalil

Butler

Giroux

R. J.

Martimianakis

M. A. T.

(2024). The need for critical and intersectional approaches to equity efforts in postgraduate medical education: A critical narrative review. Medical Education, 58(12), 1442–1461. https://doi.org/10.1111/medu.15425

22.

Lang

A. J.

Stein

M. B.

(2005). An abbreviated PTSD checklist for use as a screening instrument in primary care. Behaviour Research and Therapy, 43(5), 585–594. https://doi.org/10.1016/j.brat.2004.04.005

23.

Lazarus

R. S.

Folkman

(1984). Stress, appraisal, and coping. Springer Publishing Company.

24.

Lee

D. B.

Anderson

R. E.

Hope

M. O.

Zimmerman

M. A.

(2020). Racial discrimination trajectories predicting psychological well-being: From emerging adulthood to adulthood. Developmental Psychology, 56(7), 1413–1423. https://doi.org/10.1037/dev0000938

25.

Lee

D. B.

Contreras

L. M.

Rupp

Cook

S. H.

Zimmerman

M. A.

Carter

P. M.

Theall

K. P.

Bennett

Fleckman

J. M.

(2026). Racism and racial disparities in firearm violence: A scoping review. American Journal of Community Psychology. Advance online publication. https://doi.org/10.1002/ajcp.70064

26.

Lee

D. B.

Heinze

J. E.

Neblett

E. W.

Caldwell

C. H.

Zimmerman

M. A.

(2017). Trajectories of racial discrimination that predict problematic alcohol use among African American emerging adults. Emerging Adulthood, 6(5), 347–357. https://doi.org/10.1177/2167696817739022

27.

Lee

D. B.

Peckins

M. K.

Heinze

J. E.

Miller

A. L.

Assari

Zimmerman

M. A.

(2018). Psychological pathways from racial discrimination to cortisol in African American males and females. Journal of Behavioral Medicine, 41(2), 208–220. https://doi.org/10.1007/s10865-017-9887-2

28.

Lee

D. B.

Schmidt

C. J.

Heinze

J. E.

Carter

P. M.

Cunningham

R. M.

Walton

M. A.

Zimmerman

M. A.

(2022). Retaliatory attitudes as mediator of exposure to violence and firearm aggression among youth: The protective role of organized activity involvement. Developmental Psychology, 58(5), 990–1002. https://doi.org/10.1037/dev0001339

29.

Lei

Shah

Biely

Jackson

Dudovitz

Barnert

Hotez

Guerrero

Bui

A. L.

Sastry

Schickedanz

(2021). Discrimination and subsequent mental health, substance use, and well-being in young adults. Pediatrics, 148(6), Article e2021051378. https://doi.org/10.1542/peds.2021-051378

30.

Lemke

M. K.

Wolf

D. A.

Drake

S. A.

(2022). A call for complex systems and syndemic theory in firearm violence research. American Journal of Preventive Medicine, 62(3), 459–465. https://doi.org/10.1016/j.amepre.2021.08.026

31.

Martin

M. J.

McCarthy

Conger

R. D.

Gibbons

F. X.

Simons

R. L.

Cutrona

C. E.

Brody

G. H.

(2011). The enduring significance of racism: Discrimination and delinquency among Black American youth. Journal of Research on Adolescence, 21(3), 662–676. https://doi.org/10.1111/j.1532-7795.2010.00699.x

32.

Mattingly

D. T.

Diaby

Agbonlahor

Rose

S. W.

Oser

C. B.

Fleischer

N. L.

Leventhal

A. M.

Hart

J. L.

(2025). Disparities in discrimination distress among U.S. youth. AJPM Focus, 4(4), Article 100360. https://doi.org/10.1016/j.focus.2025.100360

33.

Meyer

I. H.

(2003). Prejudice, social stress, and mental health in lesbian, gay, and bisexual populations: Conceptual issues and research evidence. Psychological Bulletin, 129(5), 674–697. https://doi.org/10.1037/0033-2909.129.5.674

34.

Neblett

E. W.

(2023). Racism measurement and influences, variations on scientific racism, and a vision. Social Science & Medicine, Complex Effects of Racism and Discrimination on African Americans’ Health and Well-Being: Navigating the Status Quo, 316, Article 115247. https://doi.org/10.1016/j.socscimed.2022.115247

35.

Pascoe

E. A.

Smart Richman

(2009). Perceived discrimination and health: A meta-analytic review. Psychological Bulletin, 135(4), 531–554. https://doi.org/10.1037/a0016059

36.

Posner

Brown

G. K.

Stanley

Brent

D. A.

Yershova

K. V.

Oquendo

M. A.

Currier

G. W.

Melvin

G. A.

Greenhill

Shen

Mann

J. J.

(2011). The Columbia-Suicide Severity Rating Scale: Initial validity and internal consistency findings from three multisite studies with adolescents and adults. The American Journal of Psychiatry, 168(12), 1266–1277. https://doi.org/10.1176/appi.ajp.2011.10111704

37.

Reinert

D. F.

Allen

J. P.

(2007). The alcohol use disorders identification test: An update of research findings. Alcoholism: Clinical and Experimental Research, 31(2), 185–199. https://doi.org/10.1111/j.1530-0277.2006.00295.x

38.

Richardson

L. P.

McCauley

Grossman

D. C.

McCarty

C. A.

Richards

Russo

J. E.

Rockhill

Katon

(2010). Evaluation of the Patient Health Questionnaire-9 item for detecting major depression among adolescents. Pediatrics, 126(6), 1117–1123. https://doi.org/10.1542/peds.2010-0852

39.

Roberson

King

Hebl

(2020). Designing more effective practices for reducing workplace inequality. Behavioral Science & Policy, 6(1), 39–49. https://doi.org/10.1177/237946152000600104

40.

Rouhani

Bather

J. R.

Cuevas

A. G.

Omari

Harris

McSorley

A.-M.

Rhodes-Bratton

Goodman

M. S.

(2025). Racial discrimination and substance use: Results from a 2023 survey of racism and public health in the United States. Substance Use & Misuse, 60(14), 2225–2234. https://doi.org/10.1080/10826084.2025.2537836

41.

Schmitt

M. T.

Branscombe

N. R.

Postmes

Garcia

(2014). The consequences of perceived discrimination for psychological well-being: A meta-analytic review. Psychological Bulletin, 140(4), 921–948. https://doi.org/10.1037/a0035754

42.

Schouler-Ocak

Moran

J. K.

(2023). Racial discrimination and its impact on mental health. International Review of Psychiatry, 35(3–4), 268–276. https://doi.org/10.1080/09540261.2022.2155033

43.

Shi

Zhang

Martin

Chen

Han

Wen

Chen

Ramos

A. K.

King

K. M.

Michaud

(2022). Racial discrimination, mental health and behavioral health during the COVID-19 pandemic: A National Survey in the United States. Journal of General Internal Medicine, 37(10), 2496–2504. https://doi.org/10.1007/s11606-022-07540-2

44.

Spitzer

R. L.

Kroenke

Williams

J. B. W.

Löwe

(2006). A brief measure for assessing generalized anxiety disorder: The GAD-7. Archives of Internal Medicine, 166(10), 1092–1097. https://doi.org/10.1001/archinte.166.10.1092

45.

Straus

M. A.

Hamby

S. L.

Boney-McCoy

Sugarman

D. B.

(1996). The revised Conflict Tactics Scales (CTS2): Development and preliminary psychometric data. Journal of Family Issues, 17, 283–316. https://doi.org/10.1177/019251396017003001

46.

WHO ASSIST Working Group. (2002). The Alcohol, Smoking and Substance Involvement Screening Test (ASSIST): Development, reliability and feasibility. Addiction, 97(9), 1183–1194. https://doi.org/10.1046/j.1360-0443.2002.00185.x

47.

Wiebe

D. J.

Richmond

T. S.

Guo

Allison

P. D.

Hollander

J. E.

Nance

M. L.

Branas

C. C.

(2015). Mapping activity patterns to quantify risk of violent assault in urban environments. Epidemiology, 27(1), 32. https://doi.org/10.1097/EDE.0000000000000395

48.

Williams

D. R.

Lawrence

J. A.

Davis

B. A.

(2019). Understanding how discrimination can affect health. Health Services Research, 54(Suppl 2), 1374–1388. https://doi.org/10.1111/1475-6773.13222

49.

Williams

D. R.

Mohammed

S. A.

(2013). Racism and health I: Pathways and scientific evidence. American Behavioral Scientist, 57(8), 1152–1173. https://doi.org/10.1177/0002764213487340

50.

Williams

D. R.

Yan

Jackson

J. S.

Anderson

N. B.

(1997). Racial differences in physical and mental health: Socio-economic status, stress and discrimination. Journal of Health Psychology, 2(3), 335–351. https://doi.org/10.1177/135910539700200305

51.

Williams

M. T.

Holmes

Zare

Haeny

Faber

(2023). An evidence-based approach for treating stress and trauma due to racism. Cognitive and Behavioral Practice, 30(4), 565–588. https://doi.org/10.1016/j.cbpra.2022.07.001

52.

Ybarra

M. L.

Mitchell

K. J.

Kosciw

J. G.

Korchmaros

J. D.

(2015). Understanding linkages between bullying and suicidal ideation in a national sample of LGB and heterosexual youth in the United States. Prevention Science, 16(3), 451–462. https://doi.org/10.1007/s11121-014-0510-2

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.24 MB