Beyond Trauma Exposure: Discrimination and Posttraumatic Stress,Internalizing,and Externalizing Problems Among Detained Youth

Abstract

According to the race-based traumatic stress model, racial discrimination is proposed to comprise a traumatic experience that results in posttraumatic stress symptoms, as well as internalizing and externalizing problems among youth. Accordingly, a significant body of research has emerged that supports the associations among these constructs. However, the majority of these empirical studies have not accounted for the potential role of traditionally defined traumatic events in these associations. This study investigated whether self-reported racial discrimination was related to posttraumatic stress symptoms, internalizing, and externalizing symptoms above and beyond the impact of other trauma exposures in a sample of 266 detained youth (79% boys, 60% identified as an ethnic minority). Results of hierarchical linear regressions demonstrated that, after accounting for youths’ other trauma exposures, racial discrimination accounted for significant variance in the models predicting delinquency and risk-taking but no other externalizing and internalizing problems, or posttraumatic stress symptoms. These findings indicate that racial discrimination may be particularly important for understanding offending behavior among detained youth.

Keywords

trauma exposure racial discrimination PTSS internalizing problems externalizing problems justice-involved youth

Youth involved in the juvenile justice system represent a vulnerable population. Justice-involved youth exhibit heightened rates of posttraumatic stress symptoms (PTSS), internalizing problems (i.e., nonsuicidal self-injury [NSSI], anxiety, and depression), and externalizing problems (i.e., delinquency, physical aggression, risk-taking, and substance use; Becker & Kerig, 2011; Kerig et al., 2009; Mozley et al., 2018). One factor implicated in justice-involved youth’s high levels of mental health problems is exposure to traumatic events (Cisler et al., 2012; Hoeve et al., 2015; Kerig et al., 2009). Justice-involved youth report disproportionate exposure to traumatic events relative to their community-based peers (Wood et al., 2002). For example, in a state-wide study, Abram and colleagues (2004) found that 92% of justice-involved youth reported experiencing at least one type of traumatic event, with an average of 14 traumatic events. In turn, trauma exposure is a powerful predictor of mental health problems among justice-involved youth (Hoeve et al., 2015; Kerig et al., 2009; Mozley et al., 2018), particularly in the form of externalizing problems (see Kerig, 2017). Therefore, the current state of the field emphasizes the detrimental effects of trauma exposure on justice-involved youth’s mental health and behavior.

An additional relevant risk factor for justice-involved youth that has recently received attention is exposure to racial discrimination. Youth who are justice-involved are disproportionally from underserved populations (Huizinga et al., 2007) who experienced high rates of discrimination (Huynh & Fuligni, 2010; Stewart et al., 2009). Furthermore, a number of studies have investigated the impact of discrimination on youths’ mental health problems, and the research shows clear links between experiences of discrimination and a number of negative outcomes, including internalizing symptoms (e.g., Berkel et al., 2010; Bucchianeri et al., 2014; Lambert et al., 2014; Walker et al., 2017) and externalizing problems (e.g., Bogart et al., 2013; Copeland-Linder et al., 2011; Hartshorn et al., 2012; Martin et al., 2011; Roberts et al., 2012). Moreover, an important literature has emerged proposing the race-based traumatic stress model which argues that racial discrimination may comprise a form of trauma exposure (Carter, 2007; Carter et al., 2005), one that is not captured by traditional definitions of what comprises a traumatic stressor. The definitions of a traumatic event in the diagnostic criteria for posttraumatic stress disorder (PTSD) in the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5; American Psychiatric Association [APA], 2013) and the International Classification of Diseases–11 Revision are specific to life-threatening or physically harmful experiences, whereas racial discrimination may take the form of verbal harassment or hostility (Carter et al., 2005). However, Carlson (1997), in her seminal work on trauma assessment, proposed that experiences are likely to result in traumatic stress reactions when they are appraised as negative, appear suddenly, and feel uncontrollable. Based on this alternative definition of trauma, Carter (2007) posited the race-based traumatic stress model and hypothesized that racial discrimination may result in traumatic stress, regardless of whether is life-threatening or physically harmful, given that it is often experienced as an emotional or psychological injury that is appraised as “negative, sudden, and uncontrollable” (Carlson, 1997). In turn, scholars have hypothesized that the negative effects of race-based traumatic stress may manifest in the form of PTSS, as well as internalizing and externalizing problems (Carter, 2007; Carter et al., 2005). Consistent with this hypothesis, previous studies have established linkages between experiences of discrimination and PTSS (e.g., Ellis et al., 2008; Pascoe & Smart Richman, 2009). Thus, based on the race-based traumatic stress model proposed by Carter (2007), justice-involved youths’ experiences of discrimination may function as a traumatic event and negatively affect their mental health functioning.

The literature to date has not thoroughly tested the race-based traumatic stress model. In particular, an important limitation of the existing literature examining the association between discrimination and negative outcomes, especially PTSS, is that it has neglected to control for the potential contribution of other traumatic experiences (Kirkinis et al., 2018). In a notable exception, Kang and Burton (2014) found that experiences of racism resulted in increased delinquency above and beyond DSM-5 traumatic events in a sample of justice-involved African American boys. Similarly, in two studies of refugee youth, researchers examined how perceived discrimination related to PTSD and depression when traumatic events and immigration-related stressors were treated as covariates; however, these studies did not examine whether there were effects of discrimination above and beyond these other traumatic experiences (Ellis et al., 2008, 2010). Therefore, although these results are suggestive of support for the race-based traumatic stress model, the question still remains regarding whether racial discrimination can be conceptualized as a traumatic event and whether it has unique relations to mental health problems among youth. Accounting for trauma exposure that might be present or co-occurring in the lives of racially victimized youth would be a crucial step in testing the race-based traumatic stress model and would help establish whether discrimination exerts a unique effect, over and above other forms of trauma exposure (Kirkinis et al., 2018). Investigation of the unique impact of racial discrimination on justice-involved youth’s outcomes also has important theoretical and practical implications, given that parsing out the specific impacts of racial discrimination above and beyond the impacts of traumatic experiences may aid in tailoring treatment for youth in the justice system.

The Current Study

This study sought to examine whether racial discrimination was related to PTSS, internalizing problems (e.g., NSSI, anxiety, depression), and externalizing (e.g., delinquency, physical aggression, risk-taking, substance use) problems above and beyond the impact of other traditionally defined traumatic experiences in a sample of justice-involved youth. In addition, the study examined whether experiences of racial discrimination interacted with other trauma exposures to affect youth’s mental health functioning. Based on the previous empirical literature and the tenets of the race-based traumatic stress model, we hypothesized that (a) trauma exposure would be significantly related to PTSS, internalizing, and externalizing problems among justice-involved youth, and (b) racial discrimination would be related to these mental health and behavioral problems above and beyond the effect of other traumatic experiences. We also conducted exploratory analyses to determine if there was an interactive effect between trauma exposure and discrimination on PTSS, internalizing, and externalizing problems.

Method

Participants

This study included 266 youth (79% boys, 21% girls) recruited from a short-term juvenile detention center (the average length of stay is 3 days) in the Western United States. Youth were between the ages of 9 and 19 years old (M = 15.93, SD = 1.38). The ethnic breakdown was consistent with the demographics of the detention centers in this geographic region, with 40% of the sample identified as White/Caucasian, 38.5% as Latino(a)/Hispanic, 8.7% as Biracial/Multiracial, 5.8% as Black/African American, 2.5% as Native American, 2.5% identified as Pacific Islander/Native Hawaiian, and 1.8% as Asian/Asian American. Official juvenile justice records indicated that youth had incurred a range of legal charges. The most severe charges on participants’ records involved status offenses (13%), misdemeanor offenses (37%), non-violent felony offenses (36%), violent felony offenses (7%), and sexual offenses (7%).

Procedure

All study procedures were approved by the institutional review boards of the University of University of Utah and the Utah Department of Human Services. Informed consent was obtained by research assistants from youths’ legal guardians during visiting hours at the juvenile detention center. Following parental consent, youth’s informed assent was obtained. All legal guardians and youth were eligible to participate in the study as no inclusion or exclusion criteria were employed. Measures were administered during individual interviews in a private visiting room inside the detention center through a computer. Youth were not compensated for their participation.

Measures

Racial discrimination

To assess youths’ experiences of racial discrimination, three items were adapted from the Bias Attack Scale included in the Juvenile Victimization Questionnaire (JVQ; Finkelhor et al., 2005). Youth indicated whether or not (0 = no, 1 = yes) they had ever experienced three different types of discrimination: “Have you felt like people wouldn’t accept you because of your skin color or where your family comes from?”; “Have people insulted you or said mean things about you because of your skin color or where your family comes from?”; and “Have you been hit, attacked, or threatened because of your skin color or where your family comes from?” A total score was calculated ranging from 0 to 3.

Trauma exposure

To measure youths’ exposure to a wide range of traumatic events (0 = no, 1 = yes), we asked youth whether they had ever experienced 32 possible events (e.g., witnessing or experiencing community violence, domestic violence, physical abuse, sexual abuse, traumatic losses and separations from caregivers, accidents, medical traumas, disasters) derived from well-known trauma screening tools. We utilized questions from the University of California at Los Angeles Posttraumatic Stress Disorder Reaction Index for Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV; APA, 1994), Adolescent version (PTSD-RI; Pynoos et al., 1998; Steinberg et al., 2004) which has demonstrated excellent test–retest reliability and high internal consistency (Steinberg et al., 2013). In addition, we used questions from the JVQ which has demonstrated adequate test–retest reliability and good validity (Finkelhor et al., 2005). All items were summed to achieve a total trauma exposure score with a possible range of 0 to 32.

PTSS

Part II of the PTSD-RI (Pynoos et al., 1998; Steinberg et al., 2004) was utilized to assess youths’ posttraumatic symptoms in the past month. We use the criteria from the DSM-5 (APA, 2013) which resulted in 25 items. Responses were presented in a 4-point Likert-type scale (0 = none of the time, 4 = most of the time). All items were summed to create a total PTSS score (α = .94) ranging from 0 to 100.

NSSI

We assessed NSSI using a survey modified from the Lifetime Suicide Attempt Self-Injury Count (Linehan & Comtois, 1996) which has been found to have good reliability and validity (Linehan et al., 2006). Youth provided self-reports of whether or not they had ever engaged in various self-injurious events, such as scratching, burning, cutting, or carving themselves, without suicidal intent over their lifetime. The items were summed to create a total count score.

Anxiety

To assess youths’ anxiety, we used the short form of the Revised Children’s Manifest Anxiety Scale–Second edition (RCMAS-2; Reynolds & Richmond, 2008) which is composed of the first 10 items of the long-form. The RCMAS-2 is a well-validated measure of anxiety for ages 6 to 19 and has demonstrated good internal consistency and test–retest reliability (Reynolds & Richmond, 2008). The RCMAS-2 has also demonstrated good construct and external validity across age groups and samples that include people of color (Reynolds & Richmond, 2008). Youth were asked whether (0 = no, 1 = yes) they were currently experiencing anxiety symptoms including feeling sick to the stomach, worrying that others do not like them, and fearing that people will laugh at them. All items were summed to create count score.

Depression

To measure youths’ current depressive symptoms, we used the short-form of the Children’s Depression Inventory–Second edition (CDI-2; Kovacs & MHS Staff, 2010) which consists of 11 items. The items were answered using a 2-point Likert-type scale that varied by question. For example, “during the past two weeks I felt, 0 = I am sad once in a while, 1 = I am sad many times, 2 = I am sad all the time.” In addition, “during the past two weeks, 0 = I have plenty of friends, 1 = I have some friends but I wish I had more, 2 = I do not have any friends.” A total score was calculated (α = .87) and the possible range was 0 to 22.

Delinquency

To measure youths’ involvement in delinquency, we used 39 items from an adapted version of the Self-Report of Delinquency scale (SRD; Elliot et al., 1985) developed by Feiring et al. (2007) which includes additional items that assess low-level status offenses that are commonly seen among certain subsets of youth, including girls. Youth indicated whether (0 = no, 1 = yes) they had participated in specific activities (e.g., truancy, theft, robbery, property destruction, drug dealing) within the last year. A total score was obtained by summing all items (α = .90), responses range from 0 to 39.

Physical aggression

How Friends Treat Each Other (HFTEO; Bennett et al., 2011) is a measure of aggression against peers and intimate partners and focuses on four types of aggressive behavior: electronic aggression, psychological aggression, physical aggression, and coerced intimacy, although this study focused only on the physical aggression subscale. For each item, participants were asked in the past year “Have you done any of the following things to any of the following people?” Youth indicated on a 5-point Likert-type scale the number of times they participated in each event and responses ranged from 1 = never happened to 5 = happened more than 10 times. Physical aggression includes seven items such as “Kicked, hit, or punched someone.” All items were summed to create a total count score.

Risk-taking

We used an eight-item scale created by Delker and Freyd (2014) to assess risk-taking behavior. Youth indicated whether (0 = no, 1 = yes) they engaged in each of form of risk-taking in the past year, including: “Behaved in ways that put your safety at risk?”; “Made choices that other people might think are dangerous?”; and “Made choices that were risky for other people near you?” Delker and Freyd (2014) found the total score on the measure to have good internal reliability and showed that the items formed a single factor with 50% of the variance explained. In this study, a total sum was calculated with good internal reliability (α = .86) and scores range from 0 to 8.

Substance use

To assess youths’ substance use nine items regarding various activities related to the use of drugs or alcohol were adapted from the CRAFFT Screener for Substance Use (Knight et al., 2002). Youth indicated whether (0 = no, 1 = yes) they had participated in specific activities within the last year, such as drinking alcohol, smoking marijuana, or using illegal or prescription drugs to get high. A total score was obtained by summing all items (α = .86), responses range from 0 to 9.

Data Analysis

All analyses were conducted in SPSS version 25. All variables were inspected for normality and potential outliers. Diagnostic tests, scatterplots, and histograms indicated the dependent variable depression had a skewed distribution (skewness = 1.53, SE = .17), as well as several non-normally distributed dependent variables (e.g., NSSI, anxiety, and physical aggression). We transformed depression using the formula for moderate right-skewness with a constant, SQRT (X + 1), which improved its distribution. After inspecting NSSI, anxiety, and physical aggression, we concluded that these dependent variables were count variables with overdispersion. Missing data ranged from 1.8% to 25%. Systematic investigations of missing data and Little’s (1998) test of missing data patterns indicated that none of the study variables were associated with any identifiable pattern χ²(17) = 20.06, p = .271. Although we cannot determine that our data were missing completely at random (MCAR), the data were treated as though they were MCAR and dealt with through multiple imputation in SPSS, which is consistent with best statistical practices (Enders, 2010). Independent samples t tests and negative binomial regressions were conducted to examine whether there were significant differences in responding between youth who reported different types of racial discrimination experiences and those who did not.

Our hypotheses were tested with a series of hierarchical regressions. First, we conducted preliminary analyses, with demographic variables in the first step and discrimination in the second step of the hierarchical regression, to support the hypothesis that discrimination was related to mental health and behavior problems. Second, we conducted main analyses to test the race-based traumatic stress model. This hierarchy was comprised of four steps: (a) demographic variables (e.g., age, gender, and ethnicity), (b) trauma exposure, (c) racial discrimination, and (c) a two-way interaction (i.e., Trauma Exposure × Discrimination). For dependent variables that were normally distributed (PTSS, risk-taking, delinquency, substance use) or transformed (depression), we conducted hierarchical linear regressions. For these hierarchical linear regressions, we evaluated our hypotheses based on the R-square change (ΔR²) and the overall significance of the model. For dependent count variables with overdispersion (NSSI, anxiety, and physical aggression), we performed negative binomial regressions in a hierarchical manner with each model representing a step. In these analyses, the different steps were treated as null versus alternative (e.g., null = Model 1 [Step 1] vs. alternative = Model 2 [Step 2]). We evaluated the difference between the steps/models by using the chi-square (χ²) significance test based on the log–likelihood ratio and the Akaike information criterion (AIC; Akaike, 1974). A significant chi-square difference indicates that the alternative model fits better relative to the null model. A lower AIC represents improved fit relative to a higher AIC (Kline, 2011).

Results

Descriptive Statistics

Youth in our study experienced a range of 0 to 26 traumatic events on the PTSD-RI, with the majority of the youth (98.5%) endorsing at least one traumatic event. Youth in the sample reported a range of 0 to 3 (M = .58) discriminatory events. Among the youth in our study, 23% endorsed feeling as though they were not accepted, 29% reported experiencing insults or people saying mean things to them, and 6% reported being physically attacked. Thirty-seven percent of youth reported at least one traumatic event in conjunction with at least one experience of discrimination. Table 1
Table 1.
Means, Standard Deviations, and Intercorrelations of Study Variables.

Variables 1 2 3 4 5 6 7 8 9 10

1. Trauma exposure –

2. Discrimination 0.30 –

3. PTSS 0.47 0.19

4. Depression 0.32 0.04 0.41 –

5. NSSI 0.28 0.03 0.34 0.31 ––

6. Anxiety 0.33** 0.13* 0.47** 0.58* 0.45 –

7. Delinquency 0.36 0.24 0.17 0.16** 0.14* 0.07 –

8. Risk-taking 0.38* 0.25* 0.34* 0.23* 0.08 0.18 0.46* –

9. Substance use 0.43 0.17 0.29 0.21 0.21** 0.15* 0.21 0.48* –

10. Physical aggression 0.23** 0.08 0.15* 0.12* 0.00 0.10 0.32 0.34 0.24** –

M 10.71 0.58 27.28 1.89 1.35 2.50 11.15 4.42 4.58 1.98

SD 5.73 0.84 18.95 0.73 2.22 2.60 7.15 2.68 2.84 2.55

Note. PTSS = posttraumatic stress symptoms; NSSI = nonsuicidal self-injury.

p < .05. p < .01. p < .001.

displays the intercorrelations, means, and standard deviations of the study variables.

Differences of the Effect of Discrimination on Mental and Behavioral Outcomes

Results of independent samples t tests are presented in Table 2
Table 2.
Results of Independent t Tests Examining Differences Among Discrimination Experiences and Study Variables.

Variables
M
SD
M
SD t Test

Discriminatory Nonacceptance n = 57 No Discriminatory Nonacceptance n = 209

Trauma exposure 13.28 5.85 10.00 5.50 −3.93***

PTSS 31.65 18.32 26.09 18.98 −1.98*

Depression 1.92 0.79 1.89 0.72 −.35

Delinquency 12.95 7.57 10.66 6.97 −2.16*

Risk-taking 5.42 2.42 4.22 2.81 −2.73

Substance use 5.02 2.75 4.46 2.86 −1.32

Discriminatory Verbal Insults n = 74
No Discriminatory Verbal Insults n = 192

Trauma exposure 12.72 5.23 9.93 5.73 −3.63*

PTSS 33.68 18.92 24.81 18.42 −3.49

Depression 1.98 0.79 1.86 0.71 −1.24

Delinquency 13.97 7.60 10.06 6.68 −4.12*

Risk-taking 5.50 2.23 4.08 2.86 −3.55 *

Substance use 5.39 2.76 4.27 2.82 −2.94

Discriminatory Physical Attacks n = 14
No Discriminatory Physical Attacks n = 252

Trauma exposure 14.93 5.50 10.47 5.66 −2.87

PTSS 32.64 19.88 26.98 18.89 −1.09

Depression 1.75 0.93 1.90 0.72 0.78

Delinquency 16.93 7.95 10.83 6.98 −3.16

Risk-taking 6.23 2.17 4.39 2.77 −2.36*

Substance use 6.21 2.67 4.49 2.83 −2.23*

Note. Discriminatory experiences are based on skin color or family origin. PTSS = posttraumatic stress symptoms.

p < .05. p < .01. p < .001.

. Youth who endorsed discriminatory experiences of nonacceptance based on skin color or family origin reported significantly higher levels of trauma exposure, PTSS, delinquency, and risk-taking relative to those who did not endorse nonacceptance experiences. Furthermore, youth who endorsed experiencing verbal insults based on their skin color or family origins reported significantly higher levels of trauma exposure, PTSS, delinquency, risk-taking, and substance use relative to those who did not endorse verbal insults. Youth who endorsed discriminatory experiences of physical attacks based on skin color or family origin also reported significantly higher levels of trauma exposure, delinquency, risk-taking, and substance use relative to those who did not endorse physical attacks. Results of negative binomial regression analyses showed that endorsing discriminatory experiences of nonacceptance relative to not endorsing these experiences was related to decreased odds of NSSI, B = − 0.47, SE = .19, p = .012, odds ratio (OR) = .62, whereas discriminatory experiences of verbal insults or physical attacks were not related to NSSI. Anxiety and physical aggression were not associated with any type of discriminatory experiences.

Preliminary Hierarchical Regressions

For PTSS, the demographic variables entered on the first step contributed significantly to the model F(3, 262) = 5.56, p = .001, and accounted for 6% of the variance. Discrimination on the second step also contributed to the model F(1, 261) = 11.74, p = .001, demonstrated a significant R² change, explained 10% of the variance, and was significantly related to PTSS, β = .21, p = .001. Similarly, for substance use, the demographic variables entered on the first step contributed significantly to the model F(3, 262) = 4.52, p = .004, and accounted for 5% of the variance. Discrimination on the second step contributed to the model F(1, 261) = 8.40, p = .004, with a significant R² change; explained 8% of the variance; and was significantly related to substance use, β = .18, p = .004. For delinquency, the demographic variables entered on the first step were not significant to the model F(3, 262) = 1.48, p = .220. However, discrimination, entered on the second step, contributed to the model F(1, 261) = 14.14, p < .001, with a significant R² change; explained 8% of the variance; and was significantly related to delinquency, β = .25, p < .001. Furthermore, for risk-taking, the demographic variables entered on the first step were not significant to the model F(3, 262) = 2.14, p = .096. However, discrimination on the second step contributed to the model F(1, 261) = 14.04, p < .001, with a significant R² change; explained 9% of the variance; and was significantly related to delinquency, β = .25, p < .001. In contrast, for depression, the demographic variables on the first step contributed significantly to the model F(3, 262) = 9.10, p < .001, and accounted for 9% of the variance; yet, discrimination on the second step was not a significant contributor to the model F(1, 261) = 1.32, p = .252, did not evidence a significant R² change, and was not related to depression, β = .07, p = .252.

For anxiety, the model with demographics and discrimination (AIC = 1,106.96) had better relative fit than the model with only demographics, AIC = 1,110.35; χ²(1) = 5.39, p = .020. In addition, discrimination was related to anxiety (B = 0.21, p = .022, OR = 1.23). In contrast, for aggression, the model with demographics and discrimination (AIC = 1,014.24) did not have better fit relative to the model with only demographics, AIC = 1,015.54; χ²(1) = 3.30, p = .069. Similarly, for NSSI, the model with demographics and discrimination (AIC = 807.12) did not have better fit relative to the model with only demographics, AIC = 805.87; χ²(1) = .75, p = .386.

Main Hierarchical Regressions

The results of the hierarchical linear regressions are presented in Table 3
Table 3.
Results of Ordinary Least Square Hierarchical Regression Analyses Examining Demographic Variables, Trauma Exposure, and Discrimination on PTSS, Depression, Delinquency, Risk-Taking, and Substance Use in Detained Youth.

Step Variables PTSS
Depression
Delinquency
Risk-Taking
Substance Use

ΔR² β ΔR² β ΔR² β ΔR² β ΔR² β

Step 1 Gender .06** −.14* .09* −.27* .02 −.13* .03 −.11 .05 −.17

Ethnicity −.09 −.10 .02 .10 −.05

Age .17** −.09 .00 .12 .13*

Step 2 Gender .18* −.07 .08* −.23* .12* −.07 .15* −.02 .15* −.10

Ethnicity −.03 −.06 .06 .13* .00

Age .12* −.12* −.04 .07 .09

Trauma exposure .43* .29* .36* .40* .40*

Step 3 Gender .00 −.07 .00 −.22* .02* −.08 .02* −.03 .00 −.10

Ethnicity −.05 −.06 .03 .10 −.01

Age .12* −.12* −.05 .06 .08

Trauma exposure .41* .30* .31* .36* .39***

Discrimination .07 −.03 .15* .14* .05

Step 4 Gender .00 −.07 .00 −.22*** .01 −.09 .02* −.03 .00 −.10

Ethnicity −.05 −.06 .03 .10 −.01

Age .11* −.12* −.05 .05 .08

Trauma exposure .43* .31* .26** .44* .37*

Discrimination .14 .02 −.01 .44 .01

Trauma × Discrimination −.09 −.06 .20 −.36* .05

Note. For the best fitting model predicting PTSS, total R²= .24, p < .001; for the best fitting model predicting depression, total R²= .17, p < .001; for the best fitting model predicting delinquency, total R²= .16, p < .05; for the best fitting model predicting risk-taking, total R²= .21, p < .05; for the best fitting model predicting substance use, total R²= .20, p < .001. PTSS = posttraumatic stress symptoms; Trauma × Discrimination = two-way interaction between trauma exposure and discrimination.

p < .05. p < .01. p < .001.

. The best fitting model for the prediction of PTSS was the Step 2 model (other trauma exposure) which explained 24% of the variance. Similarly, the best fitting model for depression was the Step 2 model (other trauma exposure) which explained 17% of the variance. In contrast, the best fitting model for delinquency was the Step 3 model (racial discrimination) which explained 16% of the variance. The best fitting model for risk-taking was the Step 4 model (trauma exposure and racial discrimination interaction, see Figure 1
Figure 1.
The interaction between trauma exposure and discrimination in regards to risk-taking among justice-involved youth plotted at one standard deviation above and below the mean of each variable.
) which explained 21% of the variance. The simple slopes for both the low discrimination group, B = 0.21 t = 6.64, p < .001, and the high discrimination group, B = 0.10 t = 7.47, p < .001, which were plotted one standard deviation below and above the mean of the variables, were different from zero. The interaction indicated that at low levels of trauma exposure, youth reporting high discrimination demonstrated significantly higher risk-taking relative to those reporting low discrimination. However, as trauma exposure levels increased, risk-taking becomes similar for youth experiencing low or high discrimination.

The results of the negative binomial regressions conducted in a hierarchical manner are presented in Table 4
Table 4.
Results of Negative Binomial Hierarchical Regression Analyses Examining Demographic Variables, Trauma Exposure, and Discrimination on NSSI, Anxiety, and Aggression in Detained Youth.

Model Variables NSSI
Anxiety
Aggression

χ² (df) OR χ² (df) OR χ² (df) OR

Model 1 Gender 53.57 (3)* 0.31* 11.62 (3) 0.59 4.26 (3) 0.69*

Ethnicity 0.51* 0.78 0.99

Age 1.01 0.98 1.05

Model 2 Gender 16.30 (1)* 0.35* 16.17 (1)* 0.71 14.23 (1)* 0.78

Ethnicity 0.54* 0.80 1.05

Age 0.99 0.96 1.01

Trauma exposure 1.06* 1.06* 1.05

Model 3 Gender 0.21 (1) 0.35* 1.27 (1) 0.70 0.20 (1) 0.77

Ethnicity 0.55 0.76 1.04

Age 0.99 0.95 1.01

Trauma exposure 1.06* 1.05 1.05

Discrimination 0.95 1.11 1.04

Model 4 Gender 0.45 (1) 0.35* 0.06 (1) 0.70 0.77 (1) 0.76

Ethnicity 0.55 0.76 1.05

Age 0.99 0.95 1.01

Trauma exposure 1.06 1.05 1.04*

Discrimination 0.80 1.17 0.86

Trauma × Discrimination 1.01 1.00 1.02

Note. NSSI = nonsuicidal self-injury; χ² (df) = chi-square significance difference based on the likelihood ratio test; OR = odds ratio; Trauma × Discrimination = two-way interaction between trauma exposure and discrimination.

p < .05. p < .01. p < .001.

. The best fitting model for NSSI was the Step 2 model (other trauma exposure) with the lowest AIC = 791.57. Similarly, the best fitting model for anxiety was the Step 2 model (other trauma exposure) with the lowest AIC = 1,096.18. The best fitting model for aggression also was the Step 2 model (other trauma exposure) with the lowest AIC = 1,004.31.

Discussion

In this study, we examined whether racial discrimination was related to justice-involved youths’ PTSS, internalizing (i.e., NSSI, anxiety, and depression), and externalizing (i.e., delinquency, physical aggression, risk-taking, and substance use) symptoms above and beyond other traditionally defined traumatic experiences to test Carter’s (2007) race-based traumatic stress model. We found that youth who experienced discrimination reported on average four traumatic events more than youth who did not experience discrimination. These findings highlight the need to further examine the association between experiences of discrimination and trauma exposure. We also found that racial discrimination was not related to youth self-reports of PTSS above and beyond trauma exposure. This finding does not lend support for the race-based traumatic stress model (Carter, 2007), which conceptualizes discriminatory experiences as potential traumatic events that may result in posttraumatic reactions, particularly PTSS. In the current sample of justice-involved youth, it is possible that racial discrimination was not perceived as “negative, sudden, or uncontrollable,” which is a necessary component of the race-based traumatic stress model. Furthermore, regardless of whether justice-involved youth experienced discrimination as a traumatic stressor, it nonetheless comprises a significant and harmful form of general stress. The current criteria for PTSD require potentially traumatic experiences to be life-threatening or physically harmful (APA, 2013), whereas most experiences of racial discrimination (verbal harassment and hostility; Carter et al., 2005) do not place youth in life-threatening or harmful situations. Therefore, PTSS may not be the most appropriate outcome to measure the detrimental effects of racial discrimination (Kirkinis et al., 2018). Instead, the literature to date has demonstrated that racial discrimination is a salient factor for youth’s well-being and, even if not considered a traumatic event, it is an extremely stressful experience (Schmitt et al., 2014). Future research should continue to examine the consequences of racial discrimination among justice-involved youth, including heightened stress reactivity and poor physical health (Clark et al., 1999; Vines et al., 2007).

The findings also indicated that racial discrimination was not related to internalizing problems above and beyond trauma exposure, which also is not consistent with the race-based traumatic stress model (Carter, 2007). Moreover, these findings are inconsistent with previous research that has found an association among discrimination and depression, anxiety, and NSSI (e.g., Berkel et al., 2010; Walker et al., 2017). However, these earlier studies did not examine whether the associations between discrimination and negative outcomes remained after accounting for the effects of traumatic experiences. Therefore, the lack of associations found in the present sample may be due to the effects of racial discrimination being overshadowed by the elevated rates of overall trauma exposure. As a large literature attests, justice-involved youth report extremely high rates of trauma exposure (Abram et al., 2004), particularly in the form of polyvictimization, or the experience of multiple forms of interpersonal trauma (e.g., Ford et al., 2013). Accordingly, justice-involved youth also demonstrate high levels of PTSS and other mental health and behavioral problems (Finkelhor et al., 2007; Ford et al., 2010). It is possible that racial discrimination represents a distal stressor for justice-involved youth, in contrast to those forms of interpersonal victimization that occur proximally in close personal relationships, such as parental maltreatment and dating violence, which may have more direct effects on mental health outcomes such as anxiety, depression, NSSI, and PTSS. Future research would benefit from differentiating among the negative effects associated with these different sources of victimization and trauma in the lives of young people.

Similarly, the results of this study indicated that racial discrimination was not related to substance use or aggression beyond trauma exposure. Our initial results indicated that youth who experienced verbal insults and physical attacks because of their skin color or country of origin were more likely to report substance use relative to those who did not experience these types of discrimination. However, after accounting for trauma exposure, discrimination was not related to substance use in our sample of youth. Previous studies have highlighted the relevance of trauma exposure and posttraumatic reactions, particularly PTSS, on youth’s use of substances (Mendez et al., 2019), and therefore, the high levels of general trauma exposure in the present sample may also have overshadowed the effects of discrimination on substance use. Furthermore, our analyses did not confirm the expected association between discrimination and physical aggression before or after accounting for trauma exposure. However, an important consideration is that reports of physical aggression were extremely low in our sample which may have decreased the power to detect these effects. Future research should further investigate the relations among discrimination and physical aggression.

In contrast, discriminatory experiences were related to delinquency and risk-taking above and beyond other forms of trauma exposure. These findings contribute to the budding evidence supporting the unique contribution of racial discrimination to delinquency among justice-involved youth (Kang & Burton, 2014). These findings also extend the literature by providing support for the effect of discrimination on other types of behavioral problems, such as risk-taking. Furthermore, this finding may be relevant for informing prevention efforts for justice-involved youth, should experiences of discrimination provide the catalyst for risky behavior that brings youth into contact with the juvenile justice system. These findings are also consistent with general strain theory (Agnew, 2001, 2011), which conceptualizes discriminatory experiences as external stressors that increase strain (e.g., anger, frustration) and result in delinquency. Ultimately, these findings underscore the importance of considering a range of stressful experiences, including traumatic stressors and more general stressors such as discrimination, to better understand youths’ behavioral outcomes. Specifically, the present results suggest the importance of racial discrimination in understanding justice-involved youths’ offending or risk-taking behaviors.

Interestingly, we found an interaction effect between trauma exposure and discrimination in the prediction of youth’s risk-taking. At low levels of trauma exposure, youth who endorsed high discrimination reported more risk-taking relative to youth who endorsed low discrimination. In contrast, as the levels of trauma exposure increased, youths’ level of risk-taking became similar for the low- and high-discrimination groups. Thus, although racial discrimination appears to be a relevant factor for risk-taking, trauma exposure influences this association. These findings reinforce the idea that trauma exposure may have suppressed some of the effects of discrimination in the current sample of justice-involved youth. Future research should conduct comparisons between and within samples of youth with varying levels of trauma exposure and discrimination, such as youth in the justice-involved population and community settings, to further examine how interactions among these factors may affect youth’s mental health and behavioral outcomes.

Based on these findings, the results of this study suggest a number of avenues for future research. First, future investigations might benefit from focusing on examining various forms of racial discrimination (e.g., microaggressions, physical attacks, academic, and institutional racism) which may be particularly contributory to mental health problems (Huynh, 2012; Seaton et al., 2008). Future research should also focus on elucidating possible factors such as hopelessness and futurelessness that might explain the associations among discrimination and behavioral problems, especially in the aftermath of trauma exposure (Brezina et al., 2009). Future research should also focus on examining the effects of different sources of discrimination (e.g., based on sexual orientation, religion, and gender) on justice-involved youths’ functioning (Boutwell et al., 2017). Finally, an important contribution to the field would be to examine potential protective mechanisms that may attenuate the associations among racial discrimination and youths’ adverse outcomes, such as social support (e.g., family support versus community support; peer support versus adult support; Cooper et al., 2013) and civic engagement (i.e., prosocial behavior, volunteerism, social action, activism, and traditional political participation; Hope et al., 2015).

There are a number of clinical implications suggested by the results of this study, particularly for justice-involved youth. First, given the association between trauma exposure on all adverse outcomes examined in this study, it is pivotal that the juvenile justice system uses trauma-informed care and trauma-focused treatments for justice-involved youth (Ford et al., 2016; The National Child Traumatic Stress Network, 2016). In particular, screening should be used to identify youth with extensive histories of trauma exposure (Kerig et al., 2015) to provide them with access to evidence-based interventions that have been proven effective for traumatized, justice-involved youth (e.g., Cohen et al., 2016; Ford & Hawke, 2012). Second, given the role of racial discrimination in delinquency and risk-taking above and beyond trauma exposure, screening for youth in the juvenile justice system also should include inquiries about racial discrimination. Going forward, much-needed will be the development of interventions and services aimed at reducing the impact of discrimination on youth. Effective strategies might include intervening with parents to promote racial socialization, which refers to the process of preparing youth for racial bias and instilling prosocial ways to cope with experiences of discrimination (Hope et al., 2015). Finally, interventions that promote civic engagement as an adaptive mechanism following discriminatory experiences including the Youth Participation Action Research (Berg et al., 2009) may help transform the strain that results from these experiences into opportunities for change (Hope et al., 2015).

This study has a number of strengths including that it makes a fresh contribution to the literature by examining the association between racial discrimination and PTSS, internalizing, and externalizing problems beyond other forms of trauma exposure. In addition, this study included a justice-involved sample, which evidenced high rates of trauma exposure, as well as mental health and behavioral problems, making this an ideal sample to investigate these questions. However, a number of limitations should be noted. The sample used in this study included youth recruited from two detention centers in a specific geographic region, which limits the generalizability of these findings. In addition, in our samples the rates of discrimination were relatively lower than rates reported in other studies of vulnerable populations (Ellis et al., 2010; Kang & Burton, 2014). Moreover, the data were gathered through youth self-report, and each construct was assessed with a single measure which renders the results vulnerable to monoinformant and monomethod biases. Finally, the data were cross-sectional which precludes inferences about causal relations among the variables. Future research should focus on addressing these limitations.

To conclude, in a sample of justice-involved youth, this study found the trauma exposure was related to all adverse outcomes above and beyond demographic characteristics. In addition, racial discrimination was specifically related to delinquency and risk-taking above and beyond trauma exposure. The current results were not fully consistent with the race-based traumatic stress model but rather highlight the importance of focusing on youths’ complete histories of trauma exposure, including experiences of discrimination, in identifying risk factors for problem behavior. Thus, these findings highlight the importance of experiences of racial discrimination as risk factors for behavioral problems in justice-involved youth and suggest that experiences of racial discrimination may be important to address in prevention and efforts to reduce youth involvement in the justice system.

Variables	1	2	3	4	5	6	7	8	9	10
1. Trauma exposure	–
2. Discrimination	0.30**	–
3. PTSS	0.47**	0.19**
4. Depression	0.32**	0.04	0.41**	–
5. NSSI	0.28**	0.03	0.34**	0.31**	––
6. Anxiety	0.33**	0.13*	0.47**	0.58*	0.45**	–
7. Delinquency	0.36**	0.24**	0.17**	0.16**	0.14*	0.07	–
8. Risk-taking	0.38***	0.25***	0.34***	0.23***	0.08	0.18**	0.46***	–
9. Substance use	0.43**	0.17**	0.29**	0.21**	0.21**	0.15*	0.21**	0.48***	–
10. Physical aggression	0.23**	0.08	0.15*	0.12*	0.00	0.10	0.32**	0.34**	0.24**	–
M	10.71	0.58	27.28	1.89	1.35	2.50	11.15	4.42	4.58	1.98
SD	5.73	0.84	18.95	0.73	2.22	2.60	7.15	2.68	2.84	2.55

Variables	M	SD	M	SD	t Test
Trauma exposure	13.28	5.85	10.00	5.50	−3.93***
PTSS	31.65	18.32	26.09	18.98	−1.98*
Depression	1.92	0.79	1.89	0.72	−.35
Delinquency	12.95	7.57	10.66	6.97	−2.16*
Risk-taking	5.42	2.42	4.22	2.81	−2.73**
Substance use	5.02	2.75	4.46	2.86	−1.32
	Discriminatory Verbal Insults n = 74	No Discriminatory Verbal Insults n = 192
Trauma exposure	12.72	5.23	9.93	5.73	−3.63***
PTSS	33.68	18.92	24.81	18.42	−3.49**
Depression	1.98	0.79	1.86	0.71	−1.24
Delinquency	13.97	7.60	10.06	6.68	−4.12***
Risk-taking	5.50	2.23	4.08	2.86	−3.55 ***
Substance use	5.39	2.76	4.27	2.82	−2.94**
	Discriminatory Physical Attacks n = 14	No Discriminatory Physical Attacks n = 252
Trauma exposure	14.93	5.50	10.47	5.66	−2.87**
PTSS	32.64	19.88	26.98	18.89	−1.09
Depression	1.75	0.93	1.90	0.72	0.78
Delinquency	16.93	7.95	10.83	6.98	−3.16**
Risk-taking	6.23	2.17	4.39	2.77	−2.36*
Substance use	6.21	2.67	4.49	2.83	−2.23*

Step	Variables	PTSS	Depression	Delinquency	Risk-Taking	Substance Use
Step 1	Gender	.06**	−.14*	.09***	−.27***	.02	−.13*	.03	−.11	.05**	−.17**
Ethnicity	−.09	−.10	.02	.10	−.05
Age	.17**	−.09	.00	.12	.13*
Step 2	Gender	.18***	−.07	.08***	−.23***	.12***	−.07	.15***	−.02	.15***	−.10
Ethnicity	−.03	−.06	.06	.13*	.00
Age	.12*	−.12*	−.04	.07	.09
Trauma exposure	.43***	.29***	.36***	.40***	.40***
Step 3	Gender	.00	−.07	.00	−.22***	.02*	−.08	.02*	−.03	.00	−.10
Ethnicity	−.05	−.06	.03	.10	−.01
Age	.12*	−.12*	−.05	.06	.08
Trauma exposure	.41***	.30***	.31***	.36***	.39***
Discrimination	.07		−.03	.15*	.14*	.05
Step 4	Gender	.00	−.07	.00	−.22***	.01	−.09	.02*	−.03	.00	−.10
Ethnicity	−.05	−.06	.03	.10	−.01
Age	.11*	−.12*	−.05	.05	.08
Trauma exposure	.43***	.31***	.26**	.44*	.37***
Discrimination	.14	.02	−.01	.44**	.01
Trauma × Discrimination	−.09	−.06	.20	−.36*	.05

Model	Variables	NSSI	Anxiety	Aggression
Model 1	Gender	53.57 (3)***	0.31***	11.62 (3)**	0.59**	4.26 (3)	0.69*
Ethnicity	0.51***	0.78	0.99
Age	1.01	0.98	1.05
Model 2	Gender	16.30 (1)***	0.35***	16.17 (1)***	0.71	14.23 (1)***	0.78
Ethnicity	0.54***	0.80	1.05
Age	0.99	0.96	1.01
Trauma exposure	1.06***	1.06***	1.05**
Model 3	Gender	0.21 (1)	0.35***	1.27 (1)	0.70	0.20 (1)	0.77
Ethnicity	0.55**	0.76	1.04
Age	0.99	0.95	1.01
Trauma exposure	1.06***	1.05**	1.05**
Discrimination	0.95	1.11	1.04
Model 4	Gender	0.45 (1)	0.35***	0.06 (1)	0.70	0.77 (1)	0.76
Ethnicity	0.55**	0.76	1.05
Age	0.99	0.95	1.01
Trauma exposure	1.06**	1.05**	1.04*
Discrimination	0.80	1.17	0.86
Trauma × Discrimination	1.01	1.00	1.02

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This material is based upon work supported by a Graduate Diversity Scholar Fellowship to the first author, a National Science Foundation Graduate Research Fellowship to the second author (Grant No. 1256065), and a grant from the National Institute of Justice (2014-R2-CX-0020) to the third author.

ORCID iDs

Lucybel Mendez

Michaela M. Mozley

Author Biographies

Lucybel Mendez, MS, is a fourth-year graduate student in the Clinical Psychology program at The University of Utah. Her research interests focus on the experiences of underprivileged populations, in particular, the risk and resilience processes implicated in juvenile justice–involved youths’ developmental trajectories. Furthermore, she is committed to the promotion of culturally competent mental health care for underserved populations.

Michaela M. Mozley, MS, is a doctoral candidate in the Clinical Psychology program at The University of Utah. Her research focuses on the relation between traumatic experiences and youths’ involvement in juvenile delinquency, as well as factors that mitigate or exacerbate this association. Specifically, she is interested in callous–unemotional traits, factors related to race/ethnicity, and risk factors for aggressive behavior.

Patricia K. Kerig received her doctorate in clinical psychology from the University of California at Berkeley and currently is a Professor in the Department of Psychology at The University of Utah. Her research is devoted to understanding the factors that predict risk, recovery, and resilience among youth, adults, and families coping with adversity and traumatic stress. She is the Editor-in-Chief of the Journal of Traumatic Stress and serves as a Co-Director of the National Child Traumatic Stress Network’s Center for Trauma Recovery and Juvenile Justice whose mission is to develop, evaluate, and disseminate trauma-informed assessment and intervention strategies to the juvenile justice system and the youth and families it serves.

References

Abram

K. M.

Teplin

L. A.

Charles

D. R.

Longworth

S. L.

McClelland

G. M.

Dulcan

M. K.

(2004). Posttraumatic stress disorder and trauma in youth in juvenile detention. Archives of General Psychiatry, 61, 403–410. https://doi.org/10.1001/archpsyc.61.4.403

Agnew

(2001). Building on the foundation of general strain theory: Specifying the types of strain most likely to lead to crime and delinquency. Journal of Research in Crime and Delinquency, 38, 319–361. https://doi.org/10.1177/0022427801038004001

Agnew

(2011). Revitalizing Merton: General strain theory. In Cullen

F. T.

Jonson

C. L.

Myer

A. J.

Adler

(Eds.), The origins of American criminology (pp. 137–158). Transaction. https://doi.org/10.4324/9781315133683-7

Akaike

(1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19, 716–723. https://doi.org/10.1109/TAC.1974.1100705

American Psychiatric Association. (1994). Diagnostic and statistical manual of mental disorders (4th ed.).

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

Becker

S. P.

Kerig

P. K.

(2011). Posttraumatic stress symptoms are associated with the frequency and severity of delinquency among detained boys. Journal of Clinical Child & Adolescent Psychology, 40, 765–771. https://doi.org/10.1080/15374416.2011.597091

Bennett

D. C.

Guran

E. L.

Ramos

M. C.

Margolin

(2011). College students’ electronic victimization in friendships and dating relationships: Anticipated distress and associations with risky behaviors. Violence and Victims, 26, 410–429. https://doi.org/10.1891/0886-6708.26.4.410

Berg

Coman

Schensul

J. J.

(2009). Youth Action Research for Prevention: A multi-level intervention designed to increase efficacy and empowerment among urban youth. American Journal of Community Psychology, 43, 345–359. https://doi.org/10.1007/s10464-009-9231-2

10.

Berkel

Knight

G. P.

Zeiders

K. H.

Tein

J. Y.

Roosa

M. W.

Gonzales

N. A.

Saenz

(2010). Discrimination and adjustment for Mexican American adolescents: A prospective examination of the benefits of culturally related values. Journal of Research on Adolescence, 20, 893–915. https://doi.org/10.1111/j.1532-7795.2010.00668.x

11.

Bogart

L. M.

Elliott

M. N.

Kanouse

D. E.

Klein

D. J.

Davies

S. L.

Cuccaro

P. M.

Schuster

M. A.

(2013). Association between perceived discrimination and racial/ethnic disparities in problem behaviors among preadolescent youths. American Journal of Public Health, 103, 1074–1081. https://doi.org/10.2105/AJPH.2012.301073

12.

Boutwell

B. B.

Nedelec

J. L.

Winegard

Shackelford

Beaver

K. M.

Vaughn

Wright

J. P.

(2017). The prevalence of discrimination across racial groups in contemporary America: Results from a nationally representative sample of adults. PLOS ONE, 12, Article e0183356. https://doi.org/10.1371/journal.pone.0183356

13.

Brezina

Tekin

Topalli

(2009). “Might not be a tomorrow”: A multi-methods approach to anticipated early death and youth crime. Criminology, 47, 1091–1129. https://doi.org/10.1111/j.1745-9125.2009.00170.x

14.

Bucchianeri

M. M.

Eisenberg

M. E.

Wall

M. M.

Piran

Neumark-Sztainer

(2014). Multiple types of harassment: Associations with emotional well-being and unhealthy behaviors in adolescents. Journal of Adolescent Health, 54, 724–729. https://doi.org/10.1016/j.jadohealth.2013.10.205

15.

Carlson

E. B.

(1997). Trauma assessments: Clinician’s guide. Guilford.

16.

Carter

R. T.

(2007). Racism and psychological and emotional injury: Recognizing and assessing race-based traumatic stress. The Counseling Psychologist, 35, 13–105. https://doi.org/10.1177/0011000006292033

17.

Carter

R. T.

Forsyth

Mazzula

Williams

(2005). Racial discrimination and race-based traumatic stress. In Carter

R. T.

(Ed.), Handbook of racial-cultural psychology and counseling: Training and practice (Vol. 2, pp. 447–476). Wiley.

18.

Cisler

J. M.

Begle

A. M.

Amstadter

A. B.

Resnick

H. S.

Danielson

C. K.

Saunders

B. E.

Kilpatrick

D. G.

(2012). Exposure to interpersonal violence and risk for PTSD, depression, delinquency, and binge drinking among adolescents: Data from the NSA‐R. Journal of Traumatic Stress, 25, 33–40. https://doi.org/10.1002/jts.21672

19.

Clark

Anderson

N. B.

Clark

V. R.

Williams

D. R.

(1999). Racism as a stressor for African Americans: A biopsychosocial model. American Psychologist, 54, 805–816.

20.

Cohen

J. A.

Mannarino

A. P.

Jankowski

Rosenberg

Kodya

Wolford

G. L.

(2016). A randomized implementation study of trauma-focused cognitive behavioral therapy for adjudicated teens in residential treatment facilities. Child Maltreatment, 21, 156–167. https://doi.org/10.1177/1077559515624775

21.

Cooper

S. M.

Brown

Metzger

Clinton

Guthrie

(2013). Racial discrimination and African American adolescents’ adjustment: Gender variation in family and community social support, promotive and protective factors. Journal of Child and Family Studies, 22, 15–29. https://doi.org/10.1007/s10826-012-9608-y

22.

Copeland-Linder

Lambert

S. F.

Chen

Y. F.

Ialongo

N. S.

(2011). Contextual stress and health risk behaviors among African American adolescents. Journal of Youth and Adolescence, 40, 158–173. https://doi.org/doi.org/10.1007/s10964-010-9520-y

23.

Delker

B. C.

Freyd

J. J.

(2014). From betrayal to the bottle: Investigating possible pathways from trauma to problematic substance use. Journal of Traumatic Stress, 27, 576–584. https://doi.org/10.1002/jts.21959

24.

Elliott

D. S.

Huizinga

Ageton

S. S.

(1985). Explaining delinquency and drug use. SAGE Publications, 27, 91–92.

25.

Ellis

B. H.

MacDonald

H. Z.

Klunk‐Gillis

Lincoln

Strunin

Cabral

H. J.

(2010). Discrimination and mental health among Somali refugee adolescents: The role of acculturation and gender. American Journal of Orthopsychiatry, 80, 564–575. https://doi.org/10.1111/j.1939-0025.2010.01061.x

26.

Ellis

B. H.

MacDonald

H. Z.

Lincoln

A. K.

Cabral

H. J.

(2008). Mental health of Somali adolescent refugees: The role of trauma, stress, and perceived discrimination. Journal of Consulting and Clinical Psychology, 76, 184–193. https://doi.org/10.1037/0022-006X.76.2.184

27.

Enders

C. K.

(2010). Applied missing data analysis. Guilford Press.

28.

Feiring

Miller-Johnson

Cleland

C. M.

(2007). Potential pathways from stigmatization and internalizing symptoms to delinquency in sexually abused youth. Child Maltreatment, 12, 220–232. https://doi.org/10.1177/1077559507301840

29.

Finkelhor

Hamby

S. L.

Ormrod

Turner

(2005). The Juvenile Victimization Questionnaire: Reliability, validity, and national norms. Child Abuse & Neglect, 29, 383–412. https://doi.org/0.1016/j.chiabu.2004.11.001

30.

Finkelhor

Ormrod

R. K.

Turner

H. A.

(2007). Poly-victimization: A neglected component in child victimization. Child Abuse & Neglect, 31, 7–26. https://doi.org/10.1016/j.chiabu.2006.06.008

31.

Ford

J. D.

Elhai

J. D.

Connor

D. F.

Frueh

B. C.

(2010). Poly-victimization and risk of posttraumatic, depressive, and substance use disorders and involvement in delinquency in a national sample of adolescents. Journal of Adolescent Health, 46, 545–552. https://doi.org/10.1016/j.jadohealth.2009.11.212

32.

Ford

J. D.

Grasso

D. J.

Hawke

Chapman

J. F.

(2013). Poly-victimization among juvenile justice-involved youths. Child Abuse & Neglect, 37, 788–800. https://doi.org/10.1016/j.chiabu.2013.01.005

33.

Ford

J. D.

Hawke

(2012). Trauma affect regulation psychoeducation group and milieu intervention outcomes in juvenile detention facilities. Journal of Aggression, Maltreatment & Trauma, 21, 365–384. https://doi.org/10.1080/10926771.2012.673538

34.

Ford

J. D.

Kerig

P. K.

Desai

Feierman

(2016). Psychosocial interventions for traumatized youth in the juvenile justice system: Research, evidence base, and clinical/legal challenges. Journal of Juvenile Justice, 5, 31–49.

35.

Hartshorn

K. J. S.

Whitbeck

L. B.

Hoyt

D. R.

(2012). Exploring the relationships of perceived discrimination, anger, and aggression among North American indigenous adolescents. Society and Mental Health, 2, 53–67. https://doi.org/10.1177/2156869312441185

36.

Hoeve

Colins

O. F.

Mulder

E. A.

Loeber

Stams

G. J. J.

Vermeiren

R. R.

(2015). The association between childhood maltreatment, mental health problems, and aggression in justice‐involved boys. Aggressive Behavior, 41, 488–501. https://doi.org/10.1002/ab.21586

37.

Hope

E. C.

Hoggard

L. S.

Thomas

(2015). Emerging into adulthood in the face of racial discrimination: Physiological, psychological, and sociopolitical consequences for African American youth. Translational Issues in Psychological Science, 1, 342–351. https://doi.org/10.1037/tps0000041

38.

Huizinga

Thornberry

Knight

Lovegrove

Loeber

Hill

Farrington

D. P.

(2007). Disproportionate minority contact in the juvenile justice system: A study of differential minority arrest/referral to court in three cities: A report to the office of juvenile justice and delinquency prevention. U.S. Department of Justice, National Criminal Justice Reference Service.

39.

Huynh

V. W.

(2012). Ethnic microaggressions and the depressive and somatic symptoms of Latino and Asian American adolescents. Journal of Youth and Adolescence, 41, 831–846. https://doi.org/10.1007/s10964-012-9756-9

40.

Huynh

V. W.

Fuligni

A. J.

(2010). Discrimination hurts: The academic, psychological, and physical well‐being of adolescents. Journal of Research on Adolescence, 20, 916–941. https://doi.org/10.1111/j.1532-7795.2010.00670.x

41.

Kang

H. K.

Burton

D. L.

(2014). Effects of racial discrimination, childhood trauma, and trauma symptoms on juvenile delinquency in African American incarcerated youth. Journal of Aggression, Maltreatment & Trauma, 23, 1109–1125. https://doi.org/10.1080/10926771.2014.968272

42.

Kerig

P. K.

(2017). Self-destructive behavior. In Schreck

C. J.

(Ed.), The encyclopedia of juvenile delinquency and justice (pp. 1–5). John Wiley.

43.

Kerig

P. K.

Ford

J. D.

Olafson

(2015). Assessing exposure to psychological trauma and posttraumatic stress symptoms in the juvenile justice population. National Center for Child Traumatic Stress.

44.

Kerig

P. K.

Ward

R. M.

Vanderzee

K. L.

Moeddel

M. A.

(2009). Posttraumatic stress as a mediator of the relationship between trauma and mental health problems among juvenile delinquents. Journal of Youth and Adolescence, 38, 1214–1225. https://doi.org/10.1007/s10964-008-9332-5

45.

Kirkinis

Pieterse

A. L.

Martin

Agiliga

Brownell

(2018). Racism, racial discrimination, and trauma: A systematic review of the social science literature. Ethnicity & Health. Advance online publication. https://doi.org/10.1080/13557858.2018.1514453

46.

Kline

(2011). Principles and practice of structural equation modeling (3rd ed.). Guilford Press.

47.

Knight

J. R.

Sherritt

Shrier

L. A.

Harris

S. K.

Chang

(2002). Validity of the CRAFFT substance abuse screening test among adolescent clinic patients. Archives of Pediatrics & Adolescent Medicine, 156, 607–614.

48.

Kovacs

Staff.

MHS

(2010). Children’s depression inventory 2nd edition (CDI-2). Multi-Health Systems Inc.

49.

Lambert

S. F.

Robinson

W. L.

Ialongo

N. S.

(2014). The role of socially prescribed perfectionism in the link between perceived racial discrimination and African American adolescents’ depressive symptoms. Journal of Abnormal Child Psychology, 42, 577–587. https://doi.org/10.1007/s10802-013-9814-0

50.

Linehan

M. M.

Comtois

K. A.

(1996). Suicide attempt and self-injury count (SASI-count) (formerly lifetime parasuicide history). University of Washington.

51.

Linehan

M. M.

Comtois

K. A.

Brown

M. Z.

Heard

H. L.

Wagner

(2006). Suicide Attempt Self-Injury Interview (SASII): Development, reliability, and validity of a scale to assess suicide attempts and intentional self-injury. Psychological Assessment, 18, 303–312. https://doi.org/10.1037/1040-3590.18.3.303

52.

Little

R. J. A.

(1998). A test of missing completely at random for multivariate data with missing values. Journal of the American Statistical Association, 83, 1198–1202. https://doi.org/10.1080/01621459.1988.10478722

53.

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, 662–676. https://doi.org/10.1111/j.1532-7795.2010.00699.x

54.

Mendez

Cromer

K. D.

Villodas

M. T.

(2019). Pathways to drug delinquency among adolescents at high risk for victimization. Psychology of Violence, 9, 623–633. https://doi.org/10.1037/vio0000230

55.

Mozley

M. M.

Modrowski

C. A.

Kerig

P. K.

(2018). The roles of trauma exposure, rejection sensitivity, and callous‐unemotional traits in the aggressive behavior of justice‐involved youth: A moderated mediation model. Aggressive Behavior, 44, 268–275. https://doi.org/10.1002/ab.21749

56.

The National Child Traumatic Stress Network. (2016). Essential elements of a trauma-informed juvenile justice system. http://www.nctsn.org/sites/default/files/assets/pdfs/jj_ee_final.pdf

57.

Pascoe

E. A.

Smart Richman

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

58.

Pynoos

Rodriguez

Steinberg

Stuber

Frederick

(1998). UCLA PTSD index for DSM-IV. UCLA Trauma Psychiatry Service.

59.

Reynolds

C. R.

Richmond

B. O.

(2008). RCMAS-2-revised children’s manifest anxiety scale. Western Psychological Services.

60.

Roberts

M. E.

Gibbons

F. X.

Gerrard

Weng

C. Y.

Murry

V. M.

Simons

L. G.

Lorenz

F. O.

(2012). From racial discrimination to risky sex: Prospective relations involving peers and parents. Developmental Psychology, 48, 89–102. https://doi.org/10.1037/a0025430

61.

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, 921–948. https://doi.org/10.1037/a0035754

62.

Seaton

E. K.

Caldwell

C. H.

Sellers

R. M.

Jackson

J. S.

(2008). The prevalence of perceived discrimination among African American and Caribbean Black youth. Developmental Psychology, 44, 1288–1297. https://doi.org/10.1037/a0012747

63.

Steinberg

A. M.

Brymer

M. J.

Decker

K. B.

Pynoos

R. S.

(2004). The University of California at Los Angeles post-traumatic stress disorder reaction index. Current Psychiatry Reports, 6, 96–100. https://doi.org/10.1007/s11920-004-0048-2

64.

Steinberg

A. M.

Brymer

M. J.

Kim

Briggs

E. C.

Ippen

C. G.

Ostrowski

S. A.

Pynoos

R. S.

(2013). Psychometric properties of the UCLA PTSD reaction index: Part I. Journal of Traumatic Stress, 26, 1–9. https://doi.org/10.1002/jts.21780

65.

Stewart

E. A.

Baumer

E. P.

Brunson

R. K.

Simons

R. L.

(2009). Neighborhood racial context and perceptions of police‐based racial discrimination among black youth. Criminology, 47, 847–887. https://doi.org/10.1111/j.1745-9125.2009.00159.x

66.

Vines

A. I.

Baird

D. D.

Stevens

Hertz-Picciotto

Light

K. C.

McNeilly

(2007). Associations of abdominal fat with perceived racism and passive emotional responses to racism in African American women. American Journal of Public Health, 97, 526–530. https://doi.org/10.2105/ajph.2005.080663

67.

Walker

Francis

Brody

Simons

Cutrona

Gibbons

(2017). A longitudinal study of racial discrimination and risk for death ideation in African American youth. Suicide and Life‐threatening Behavior, 47, 86–102. https://doi.org/10.1111/sltb.12251

68.

Wood

Foy

D. W.

Layne

Pynoos

James

C. B.

(2002). An examination of the relationships between violence exposure, posttraumatic stress symptomatology, and delinquent activity: An “ecopathological” model of delinquent behavior among incarcerated adolescents. Journal of Aggression, Maltreatment & Trauma, 6, 127–147. https://doi.org/10.1300/J146v06n01_07

Variables	M	SD	M	SD	t Test
Variables	Discriminatory Nonacceptance n = 57		No Discriminatory Nonacceptance n = 209		t Test
Trauma exposure	13.28	5.85	10.00	5.50	−3.93***
PTSS	31.65	18.32	26.09	18.98	−1.98*
Depression	1.92	0.79	1.89	0.72	−.35
Delinquency	12.95	7.57	10.66	6.97	−2.16*
Risk-taking	5.42	2.42	4.22	2.81	−2.73**
Substance use	5.02	2.75	4.46	2.86	−1.32
	Discriminatory Verbal Insults n = 74		No Discriminatory Verbal Insults n = 192
Trauma exposure	12.72	5.23	9.93	5.73	−3.63***
PTSS	33.68	18.92	24.81	18.42	−3.49**
Depression	1.98	0.79	1.86	0.71	−1.24
Delinquency	13.97	7.60	10.06	6.68	−4.12***
Risk-taking	5.50	2.23	4.08	2.86	−3.55 ***
Substance use	5.39	2.76	4.27	2.82	−2.94**
	Discriminatory Physical Attacks n = 14		No Discriminatory Physical Attacks n = 252
Trauma exposure	14.93	5.50	10.47	5.66	−2.87**
PTSS	32.64	19.88	26.98	18.89	−1.09
Depression	1.75	0.93	1.90	0.72	0.78
Delinquency	16.93	7.95	10.83	6.98	−3.16**
Risk-taking	6.23	2.17	4.39	2.77	−2.36*
Substance use	6.21	2.67	4.49	2.83	−2.23*

Step	Variables	PTSS		Depression		Delinquency		Risk-Taking		Substance Use
Step	Variables	ΔR²	β	ΔR²	β	ΔR²	β	ΔR²	β	ΔR²	β
Step 1	Gender	.06**	−.14*	.09***	−.27***	.02	−.13*	.03	−.11	.05**	−.17**
	Ethnicity		−.09		−.10		.02		.10		−.05
	Age		.17**		−.09		.00		.12		.13*
Step 2	Gender	.18***	−.07	.08***	−.23***	.12***	−.07	.15***	−.02	.15***	−.10
	Ethnicity		−.03		−.06		.06		.13*		.00
	Age		.12*		−.12*		−.04		.07		.09
	Trauma exposure		.43***		.29***		.36***		.40***		.40***
Step 3	Gender	.00	−.07	.00	−.22***	.02*	−.08	.02*	−.03	.00	−.10
	Ethnicity		−.05		−.06		.03		.10		−.01
	Age		.12*		−.12*		−.05		.06		.08
	Trauma exposure		.41***		.30***		.31***		.36***		.39***
	Discrimination		.07		−.03		.15*		.14*		.05
Step 4	Gender	.00	−.07	.00	−.22***	.01	−.09	.02*	−.03	.00	−.10
	Ethnicity		−.05		−.06		.03		.10		−.01
	Age		.11*		−.12*		−.05		.05		.08
	Trauma exposure		.43***		.31***		.26**		.44*		.37***
	Discrimination		.14		.02		−.01		.44**		.01
	Trauma × Discrimination		−.09		−.06		.20		−.36*		.05

Model	Variables	NSSI		Anxiety		Aggression
Model	Variables	χ² (df)	OR	χ² (df)	OR	χ² (df)	OR
Model 1	Gender	53.57 (3)***	0.31***	11.62 (3)**	0.59**	4.26 (3)	0.69*
	Ethnicity		0.51***		0.78		0.99
	Age		1.01		0.98		1.05
Model 2	Gender	16.30 (1)***	0.35***	16.17 (1)***	0.71	14.23 (1)***	0.78
	Ethnicity		0.54***		0.80		1.05
	Age		0.99		0.96		1.01
	Trauma exposure		1.06***		1.06***		1.05**
Model 3	Gender	0.21 (1)	0.35***	1.27 (1)	0.70	0.20 (1)	0.77
	Ethnicity		0.55**		0.76		1.04
	Age		0.99		0.95		1.01
	Trauma exposure		1.06***		1.05**		1.05**
	Discrimination		0.95		1.11		1.04
Model 4	Gender	0.45 (1)	0.35***	0.06 (1)	0.70	0.77 (1)	0.76
	Ethnicity		0.55**		0.76		1.05
	Age		0.99		0.95		1.01
	Trauma exposure		1.06**		1.05**		1.04*
	Discrimination		0.80		1.17		0.86
	Trauma × Discrimination		1.01		1.00		1.02