Abstract
Prevalence of adverse childhood experiences (ACEs) and the extent to which they relate to health among young adults (ages 18–25) returning home from jail is underexamined. To build on the growing literature examining associations between ACE exposure among young people involved with carceral systems and health, we (1) measured ACE prevalence and (2) explored associations between ACEs and health/well-being indicators among young adults experiencing reentry. Using a telephone survey on reentry experiences, participants completed an ACE screening, single-item responses on health and social indicators, and five-item responses on substance misuse. Fisher’s exact tests and t tests compared sociodemographic and health-related factors by the levels of ACEs. Among the 85 participants, 66 (78%) reported four or more ACEs and 48 (56%) reported six or more ACEs, including divorced parents (n = 69, 81%), witnessing violence (n = 63, 74%), and household member incarceration (n = 60, 71%). Higher exposure to ACEs was associated with mental health diagnoses, psychiatric medication prescriptions, psychiatric hospitalizations, drug dependence, binge drinking, and cannabis misuse. High ACE exposure among young adults experiencing reentry portends worse mental health and high rates of substance use. Findings signify an opportunity to apply a trauma-focused developmental framework to support emerging adults during the crucial reentry period.
Keywords: reentry, young adults, adverse childhood experiences, behavioral health indicators, mental health, substance use
Introduction
Young adults (ages 18–25) experiencing reentry after jail are at high risk for adverse health outcomes based solely on their contact with criminal legal systems (Barnert et al., 2017). Reentry is a pivotal and challenging time that not only signifies a high risk of resumption of risky health behaviors and recidivism (defined as rearrest) but also provides an opportunity for transformation if appropriate supports are delivered (Altschuler & Brash, 2004). The challenges and opportunities of reentry are intensified by the key developmental phase of emerging adulthood (Abrams & Terry, 2017; Altschuler & Brash, 2004). Many young adults with histories of jail involvement face a revolving door of incarceration (Albertson et al., 2020). Furthermore, this population is known to have substantial mental and physical health care needs (Barnert, Abrams, et al., 2020; Barnert, Sun, et al., 2020).
An underexplored dimension of the experiences of young people during reentry is the prior exposure to childhood trauma. Adolescents in the juvenile legal system are disproportionately exposed to adverse childhood experiences (ACEs) such as abuse, neglect, or parental divorce or death (Baglivio et al., 2014). Half of youth in custody report four or more ACEs versus 17% in the general population (Baglivio et al., 2014; Swedo et al., 2023). A systematic review examining studies from 13 countries found that youth younger than 18 with current or prior juvenile justice involvement were 12 times more likely to have experienced an ACE than their peers (Malvaso et al., 2022).
Although most studies examining ACEs and mental health have focused on youth younger than 18 (Turner et al., 2021), young adults 18 and over released from jails may face a similarly high burden of ACEs while also navigating the challenges of emerging adulthood and reentry. ACEs have been associated with poorer mental health and long-term negative effects on health and well-being for youth (Turner et al., 2021) and adults with histories of criminal involvement (Van Duin et al., 2021). Taking this into account, it is likely that higher levels of ACE exposure may also be related to young people’s health-related behaviors during the challenging period of reentry. Yet, data are lacking to judge the prevalence of ACEs among young adults experiencing reentry or the extent to which ACEs are associated with an increased risk of adverse outcomes during reentry.
To inform reentry programming and policy that can support young people’s success, it is crucial to understand how prior childhood adversity exposure may influence health and well-being, particularly with regard to behavioral health, a key predictor of reentry success (Altschuler & Brash, 2004; Barnert et al., 2019). The gap in the measurement of ACEs among young adults experiencing reentry is notable. Young adults with high levels of ACEs may have a harder time “aging out” of criminal behavior, as desistance often occurs as adolescents mature neurodevelopmentally and socially (Abrams & Terry, 2017). Trauma-informed care and service delivery is paramount to successful custodial programming but is often lacking in the adult reentry conversation (Dierkhising et al., 2013; Substance Abuse and Mental Health Services Administration, 2014).
Therefore, to fill existing gaps, we sought (1) to measure the prevalence of ACEs and (2) to explore associations between ACEs and indicators of health and well-being among young adults experiencing reentry in a large urban setting.
Method
Design and Setting
The current study examined the prevalence of ACEs and the extent to which ACEs related to adverse health indicators among young adults returning home from incarceration. The research team partnered with the Whole Person Care–Los Angeles (WPC-LA) Reentry Program, a reentry intervention delivered by the Los Angeles County Department of Health Services, which assesses young adults’ reentry care needs before release to make appropriate linkages to health and social services after release.
The study also formed a community advisory board of six individuals from local community organizations who were separate from the intervention program. Community advisory board members were leaders, providers, and organizers with lived experiences of incarceration and who serve individuals with histories of incarceration. Community advisory board members and county partners were involved throughout the study and provided direct input and feedback on recruitment strategies, data collection instruments, and interpretation of data.
All study procedures and materials received approval from our university’s institutional review board and the Los Angeles County Department of Health Services.
Recruitment
The study recruited eligible young adults between April 2021 and May 2022. Recruitment occurred in two phases, due to changing safety protocols related to the COVID-19 pandemic. Eligibility criteria for both phases included (1) aged 18–25, (2) English fluency, (3) ability to provide informed consent (e.g., lack of cognitive impairment), and (4) history of at least one or more nights in jail. The phases of study recruitment are detailed below. In total, 86 participants responded to the survey; however, one participant did not complete several sections of the survey and was dropped from the sample, resulting in a sample size of 85.
Community-Partnered Recruitment
The WPC-LA Reentry Program assisted with recruitment; subsequent study activities occurred independently of the WPC-LA Reentry intervention. WPC-LA program staff conducted initial recruitment in Los Angeles County jails, explaining the study to eligible young adults during prerelease planning meetings and other program interactions. If eligible young adults expressed interest, providers obtained potential participants’ consent to securely share their names and contact information with the research team.
Researchers used the provided names to track releases using publicly available information, such as the Los Angeles County Sheriff’s Department’s Inmate Locator website, and attempted to contact interested individuals once they were released. If researchers successfully contacted young adults, they confirmed interest in participation and screened for eligibility before obtaining verbal consent and administering the survey.
Snowball Recruitment
In January 2022, the study team initiated snowball recruitment to circumvent barriers related to ongoing COVID-19 safety restrictions. Researchers contacted participants already enrolled in the current study or in a prior related study (Abrams et al., 2023; Barnert et al., 2024) to explain the referral process and gauge interest. If participants agreed to refer others, researchers provided them with a flier to share that included eligibility criteria and study contact information. Participants received a $20 incentive for each person they referred.
Newly enrolled participants were asked about their interest in referring others at the end of the survey. Individuals referred by participants contacted the study team using the information and instructions provided to referrers. Once contacted, the study team coordinated an initial phone call with the interested young adult to confirm interest and eligibility, obtain verbal consent, and administer the survey.
Data Collection
Participants completed closed-ended surveys that included questions about sociodemographics, childhood adversity exposure, physical health, mental health, substance use, and service utilization. Surveys were administered via telephone and took up to 30 minutes. Researchers conducted surveys in a private setting where conversations could not be overheard and encouraged participants to do the same. Participants received a $50 incentive for completing the survey.
Measures
Adverse Childhood Experiences
ACEs were measured using an adapted version of the Center for Youth Wellness Adverse Childhood Experiences Questionnaire (ACE-Q; Bucci et al., 2015). The original measure, typically given to a parent or guardian during a physician visit, asks how many of 17 items apply to the child being seen. For this study, the wording of items was altered to apply directly to the study participant. For example, “your children’s parents or guardians were separated or divorced” was changed to “your parents or guardians were separated or divorced.” Per prior studies, ACE-Q items related to abuse were removed to minimize retraumatization risks and reporting requirements, resulting in a 13-item scale (Bondoc et al., 2023; Meza, Bondoc, et al., 2023).
For each of the 13 items, participants indicated yes (coded as 1) or no (coded as 0); a cutoff of ACE exposure before age 18 was used for this study. The scale was then summed, with a possible range of 0 to 13. If participants failed to respond to one question in the ACE module, the item was coded 0 before calculating the total ACE score.
To examine ACEs’ relationships with indicators of health and well-being, responses were coded into two variables: having four or more ACEs (76.7% of the samples were in this category) and having six or more ACEs (55.8% of the samples were in this category). Due to the high prevalence of ACEs in the sample, we examined both the more traditional cutoff of four or more ACEs and a more extreme cutoff of six or more (Baglivio et al., 2014; Brown et al., 2009; Felitti et al., 1998).
Physical Health and Mental Health Measures
Participants were asked a series of questions regarding their physical and mental health status. These included if they have any physical health conditions, if a medical provider prescribed medication for a medical condition, if they have a mental health conditions or diagnosis, if they have been prescribed medication for a mental health condition, or if they have ever been hospitalized for a psychiatric disorder. These items were coded as “yes equals 1” and “no equals 0.”
Alcohol and Substance Use Measures
Participants were asked several yes or no questions regarding their alcohol and substance use, including if they had ever drunk alcohol, if they had ever used “marijuana,” if they had ever used any other type of drug—“such as crack, cocaine, speed, methamphetamines, prescription drugs, heroin, or inhalants”—and if they currently had an addiction or dependence to alcohol or drugs. Per prior studies, recent alcohol misuse was measured on a scale constructed by summing five dichotomous items of participants’ recent drinking over the prior 30 days: (1) if they had drunk alcohol more than 4 days, (2) felt sick because of their alcohol use, (3) felt sorry for something they did because of their alcohol use, (4) got in trouble at school or work because of their alcohol use, or (5) got in trouble at home because of their alcohol use (Edelen et al., 2009).
Recent cannabis misuse was measured in the same manner except that participants were asked if they used alcohol and cannabis on the same occasion rather than feeling sick from their use (Meza, Dudovitz, et al., 2023). Additionally, the number of days over the past month participants drank and used cannabis was recorded. If participants reported recent incarceration within the past 30 days, the items referred to the 30 days prior to incarceration. Lastly, an indicator of binge drinking during the past 30 days was created, coded as yes if participants had one or more occasions of having four or more drinks in one setting for females and five or more drinks in one setting for males (Edelen et al., 2009).
Criminal Legal System Measures
Participants were asked the number of times they had been arrested in their lifetime and the number of times they had been convicted in their lifetime.
Additional Measures
Participants were asked about their current living situation, coded as 1 equaling living in a homeless shelter or not having a place to stay and 0 if participants reported having housing arrangements. Also recorded were participants’ age (in years), gender (male, female, and nonbinary), race/ethnicity (Hispanic, non-Hispanic Asian American Pacific Islander, non-Hispanic Black, non-Hispanic White, and multiracial), employment status, if they have children, highest level of education, and mothers’ highest level of education status. Based on the distribution of responses, education variables were dichotomized into high school/GED or greater and less than high school.
Analysis
Differences were examined between ACE counts on sociodemographic characteristics and health and social indicators by using a t test for continuous variables and Fisher’s exact test for categorical variables. Since continuous variables were not normally distributed, a sensitivity analysis was conducted by using a nonparametric test (Wilcoxon rank-sum test) to assess differences between ACE counts.
Results
Most of the sample identified as male (75%) and members of minoritized racial or ethnic groups (92%). Of the sample, 54% identified as Hispanic, 29% as Black, 8% as White, 7% as multiracial, and 1% as Asian American/ Pacific Islander. Most of the sample had a high school degree or higher (89%) and 58% were currently employed.
Minimal missing data were observed. Two participants were missing values on a single ACE item, which we coded as 0 in the total ACE score. Participants’ mother’s highest education level had the greatest proportion of missing values (n = 9, 10.6%); the remaining variables had 0% to 3.5% missing values.
The prevalence of ACEs (i.e., before age 18) was high across the sample of young adults with legal system involvement, with 78% reporting four or more ACEs and 56% reporting six or more ACEs. The most frequently reported ACEs included having separated or divorced parents (81%), witnessing violence (74%), living with someone who had been in jail or prison (71%), and living with someone who had a problem with drinking or drugs (67%). A large portion of the sample also experienced feeling unloved (54%), going without food or shelter (54%), living with someone who was depressed, mentally ill, or attempted suicide (49%), being bullied at school (41%), living with a parent or guardian who died (40%), having a life-threatening illness (33%), and experiencing some type of discrimination (29%). Although less common, 8% of the sample had been in foster care and 5% reported having been separated from their primary caregiver through deportation or immigration (Table 1).
Table 1.
Prevalence of Adverse Childhood Experiences
| Reported ACEs | N | % |
|---|---|---|
| Your parents or guardians were separated or divorced. | 69 | 81.2 |
| You have often seen or heard violence in your neighborhood or in your school neighborhood. | 63 | 74.1 |
| You lived with a household member who served time in jail or prison. | 60 | 70.6 |
| You lived with someone who had a problem with drinking or using drugs. | 57 | 67.1 |
| You often felt unsupported or unloved. | 46a | 54.1 |
| More than once, you went without food, clothing, or a place to live. | 46 | 54.1 |
| You lived with a household member who was depressed, mentally ill, or attempted suicide. | 42 | 49.4 |
| You have experienced harassment or bullying at school. | 35 | 41.2 |
| You have lived with a parent or guardian who died. | 34 | 40.0 |
| You have had a serious medical procedure or life-threatening illness. | 28 | 32.9 |
| You have often been treated badly because of race, sexual orientation, place of birth, disability, or religion. | 25 | 29.4 |
| You have been in foster care. | 7 | 8.2 |
| You have been separated from your primary caregiver through deportation or immigration. | 4 | 4.7 |
N = 85.
Percentages do not total 100% as individuals could have marked more than one ACE.
The scale is based on the Center for Youth Wellness ACE-Q (Bucci et al., 2015). ACE-Q items related to abuse were removed to minimize retraumatization risks and reporting requirements.
aTwo participants did not indicate whether they felt supported or loved; therefore, of the 83 who responded to this item, 55.4% had felt unsupported or unloved.
ACEs, adverse childhood experiences prior to age 18.
We also examined associations between ACEs and demographic characteristics and indicators of health and well-being. As seen in Table 2, minimal differences were observed in the prevalence of ACEs based on demographic characteristics, with one exception: Participants whose mothers had lower educational attainment (less than high school versus high school or greater) were more likely to have six or more ACEs (p = 0.005).
Table 2.
Sociodemographic Characteristics by Adverse Childhood Experiences
| Overall | ACEs | ACEs | |||||
|---|---|---|---|---|---|---|---|
| N (%) | 0–3 (n = 19) | ≥4 (n = 66) | p a | 0–5 (n = 37) | ≥6 (n = 48) | p a | |
| Age in years—M (SD)b | 22.2 (1.9) | 21.9 (2.3) | 22.3 (1.8) | 0.442 | 21.9 (2.2) | 22.4 (1.5) | 0.164 |
| Gender—N (%) | 0.053 | 0.243 | |||||
| Male | 64 (75.3) | 18 (28.1) | 46 (71.9) | 31 (48.4) | 33 (51.6) | ||
| Female | 20 (23.5) | 1 (5.0) | 19 (95.0) | 6 (30.0) | 14 (70.0) | ||
| Nonbinaryc | — | — | — | — | — | ||
| Race | 0.086 | 0.161 | |||||
| Hispanic | 46 (54.1) | 8 (17.4) | 38 (82.6) | 16 (34.8) | 30 (65.2) | ||
| Non-Hispanic AAPIc | — | — | — | — | — | ||
| Non-Hispanic Black | 25 (29.4) | 8 (32.0) | 17 (68.0) | 14 (56.0) | 11 (44.0) | ||
| Non-Hispanic White | 7 (8.2) | 0 (0) | 7 (100) | 2 (28.6) | 5 (71.4) | ||
| Multiracial | 6 (7.1) | 2 (33.3) | 4 (66.7) | 4 (66.7) | 2 (33.3) | ||
| Highest level of education | 0.198 | 0.725 | |||||
| Less than high school | 9 (10.6) | 0 (0) | 9 (100) | 3 (33.3) | 6 (66.7) | ||
| High school or greater | 76 (89.4) | 19 (25.0) | 57 (75.0) | 34 (44.7) | 42 (55.3) | ||
| Has children | 20 (23.8) | 3 (15.0) | 17 (85.0) | 0.541 | 9 (45.0) | 11 (55.0) | >.99 |
| Currently employed | 49 (57.7) | 13 (26.5) | 36 (73.5) | 0.307 | 22 (44.9) | 27 (55.1) | 0.827 |
| Mother’s highest education level | 0.326 | 0.005 | |||||
| Less than high school | 18 (21.2) | 2 (11.1) | 16 (88.9) | 2 (11.1) | 16 (88.9) | ||
| High school or greater | 58 (68.2) | 16 (27.6) | 42 (72.4) | 30 (51.7) | 28 (48.3) | ||
| Missing | 9 (10.6) | 1 (11.1) | 8 (88.9) | 5 (55.6) | 4 (44.4) | ||
N = 85.
aWe used a t test to determine whether there were differences in means across ACE counts for continuous variables and Fisher’s exact test to determine whether there were associations between ACE counts and categorical variables.
bThe first row of the table displays means and standard deviations, and the remainder of the table displays counts and percentages.
For categories that had five or fewer individuals in them, cells were suppressed to reduce the risk of reidentification. This occurred for the variables gender and race in the annotated categories.
AAPI, Asian American Pacific Islander; ACEs, adverse childhood experiences prior to age 18.
Having a higher number of ACEs was associated with having a mental health diagnosis (≥4 ACEs, p = 0.046; ≥6 ACEs, p < 0.001), being prescribed psychiatric medication (≥4 ACEs, p = 0.035; ≥6 ACEs, p = 0.020), previously experiencing a psychiatric hospitalization (≥6 ACEs, p = 0.038), drug dependence (≥6 ACEs, p = 0.018), ever using cannabis (≥4 ACEs, p = 0.008; ≥6 ACEs, p = 0.013), engaging in binge drinking (≥6 ACEs, p = 0.027), and recent cannabis misuse (≥4 ACEs, t(82) = −2.22; ≥6 ACEs, t(82) = −2.79; see Table 3). The sensitivity analysis found no differences in the findings when assessed by the Wilcoxon rank-sum test.
Table 3.
Adverse Childhood Experiences With Health and Social Indicators
| Overall | ACEs | ACEs | |||||
|---|---|---|---|---|---|---|---|
| Indicators | N (%) | 0–3 (n = 19) | ≥4 (n = 66) | p a | 0–5 (n = 37) | ≥6 (n = 48) | p a |
| Physical conditions | 22 (26.2) | 6 (27.3) | 16 (72.7) | 0.562 | 10 (45.5) | 12 (54.6) | >0.99 |
| Medical medications | 14 (16.5) | 3 (21.4) | 11 (78.6) | >.99 | 5 (35.7) | 9 (64.3) | 0.570 |
| Mental illness | 26 (31.0) | 2 (7.7) | 24 (92.3) | 0.046 | 3 (11.5) | 23 (88.5) | <0.001 |
| Psychiatric medications | 20 (23.5) | 1 (5.0) | 19 (95.0) | 0.035 | 4 (20.0) | 16 (80.0) | 0.020 |
| Ever hospitalized for psychiatric disorder | 10 (11.8) | 0 (0) | 10 (100) | 0.108 | 1 (10.0) | 9 (90.0) | 0.038 |
| Currently unhoused | 20 (23.5) | 2 (10.0) | 18 (90.0) | 0.218 | 6 (30.0) | 14 (70.0) | 0.202 |
| Drug dependence | 25 (29.8) | 3 (12.0) | 22 (88.0) | 0.162 | 6 (24.0) | 19 (76.0) | 0.018 |
| Cannabis ever | 80 (94.1) | 15 (18.8) | 65 (81.3) | 0.008 | 32 (40.0) | 48 (60.0) | 0.013 |
| Other drug ever | 43 (50.6) | 7 (16.3) | 36 (83.7) | 0.201 | 14 (32.6) | 29 (67.4) | 0.050 |
| Binge drinking | 35 (41.2) | 6 (17.1) | 29 (82.9) | 0.431 | 10 (28.6) | 25 (71.4) | 0.027 |
| Mean (SD) | p a | Mean (SD) | p a | ||||
|---|---|---|---|---|---|---|---|
| Number of days drank alcohol (past 30 days) | 5.0 (7.8) | 4.0 (6.6) | 5.3 (8.1) | 0.509 | 3.6 (5.8) | 6.2 (8.9) | 0.124 |
| Recent alcohol misuseb | 0.8 (1.0) | 0.6 (0.7) | 0.9 (1.0) | 0.247 | 0.6 (0.8) | 1.0 (1.1) | 0.077 |
| Number of days used cannabis (past 30 days) | 16.5 (13.4) | 13.2 (14.9) | 17.4 (12.9) | 0.222 | 13.8 (14.0) | 18.6 (12.7) | 0.103 |
| Recent cannabis misusec | 1.3 (1.0) | 0.8 (1.0) | 1.4 (0.9) | 0.029 | 0.9 (0.9) | 1.5 (0.9) | 0.007 |
| Number of days used other drug (past 30 days) | 2.4 (6.9) | 4.6 (11.0) | 1.8 (5.1) | 0.113 | 3.4 (8.6) | 1.6 (5.2) | 0.235 |
| Lifetime number of arrests | 5.2 (11.4) | 7.5 (22.5) | 4.6 (5.2) | 0.338 | 6.1 (16.7) | 4.6 (4.5) | 0.545 |
| Lifetime number of convictions | 2.3 (3.2) | 1.8 (3.4) | 2.4 (3.2) | 0.505 | 2.1 (3.2) | 2.4 (3.3) | 0.666 |
N = 85.
We used a t test to determine whether there were differences in means across ACE counts for continuous variables and Fisher’s exact test to determine whether there were associations between ACE counts and categorical variables.
Recent alcohol misuse is the sum of five dichotomous items (30-day alcohol use [≥4 days], felt sick because of alcohol, felt sorry for something you did because of alcohol, trouble at school/work because of alcohol, and trouble at home because of alcohol).
Recent cannabis misuse is the sum of five dichotomous items (30-day cannabis use [≥4 days], felt sorry for something you did because of marijuana, trouble at school/work because of marijuana, trouble at home because of marijuana, and used alcohol with marijuana on the same occasion).
ACEs, adverse childhood experiences prior to age 18.
Discussion
Overall, our sample reported a high prevalence of ACEs. Exposure to ACEs was associated with worse mental health and high rates of substance use during reentry. Findings suggest that it may be worthwhile to devote greater attention to ACEs among young adults in addressing behavioral health needs during reentry, especially among young adults with higher numbers of ACEs.
Prevalence of ACEs
The high prevalence of ACEs among young adults experiencing reentry is striking and important to document. Compared with other reports of adolescents in the juvenile legal system, which have documented half having experienced four or more ACEs (Baglivio et al., 2014), our sample of young adults exceeded that, with three-quarters having experienced four or more ACEs and half having experienced six or more. The disproportionate burden of ACEs in the young adult reentry population emphasizes the need to prevent childhood trauma and to implement a trauma-informed approach that prioritizes healing rather than further punishment, which may contribute to their carceral pathways (Brown et al., 2009; Levenson & Willis, 2019; Meza, Bondoc, et al., 2023; Owen et al., 2020).
Our findings serve as a call to public health and policy action. Given the high prevalence of ACEs observed among the young adults with histories of carceral involvement in our study and others (Van Duin et al., 2021), researchers and practitioners might explore the potential for use of a higher cutoff of ACEs (e.g., six or more, rather than the more typical cutoff of four or more), which may reveal insights about individuals with the highest risk (Brown et al., 2009).
ACEs and Behavioral Health Indicators
High exposure to ACEs was associated with worse mental health and high rates of substance use. Although not surprising, the observed links between childhood adversity and health measured during reentry suggest a value in considering the implementation of ACE screening in jails, particularly for young people. The California ACEs Aware Initiative has catalyzed ACEs screening across the state by providing trainings, implementation grants, and clinical reimbursement for ACEs screening conducted in pediatric practices. Such initiatives could be extended to young adults and even older adults in custodial settings.
Findings also suggest the importance of understanding mechanistic pathways that might link behavioral health challenges to carceral involvement (Barnert et al., 2017). Finally, findings signify an opportunity to apply a trauma-focused developmental framework that supports emerging adults during reentry (Barnert et al., 2022).
Practitioners working in the reentry space might also consider a potentially novel approach of using ACE screening results for risk stratification, which can guide the funneling of more intensive resources and clinical and social interventions to the young adults with the highest ACE exposure. Although the high burden of ACEs can be overwhelming to practitioners, policymakers, and especially the young adults themselves, it is important to recognize that effective public health life course interventions exist that can mitigate the effects of ACEs and transform trajectories (Russ et al., 2022). Thus, we can open our eyes to the high prevalence of ACEs and their links to health for young adults during reentry while remaining diligent, concerned, and hopeful.
Limitations
Study limitations include potential response bias, as potential participants whom we were unable to reach may have had higher ACEs and/or worse behavioral health. The most sensitive ACE items asking about prior abuse or neglect were not included in the scale, which potentially underestimated counts of ACEs. Data were based on self-report, and we did not assess the lifetime duration of incarceration nor measure the number of days since last incarceration.
Participants were from Los Angeles, English fluent-only, and recruited via snowball sampling, which limits geographic generalizability. Additionally, only one-quarter of the sample was female and one participant identified as nonbinary. This indicates an opportunity for further research on gender differences in ACEs and incarceration. For example, adolescent females detained in the juvenile legal system are known to have higher rates of ACEs compared with their male peers (Baglivio et al., 2014).
Finally, lifetime health indicators limit our ability to comment on temporality. For example, in the case of ever using cannabis, we are uncertain whether ACEs preceded cannabis use, occurred subsequent to cannabis initiation, or both. Moreover, indicators may reflect behaviors or conditions that predate incarceration and reentry. Nonetheless, associations are relevant when considering young people’s current reentry needs, as ACEs were associated with health challenges reported during the reentry time period.
Overall, findings offer important insights that can guide new research, policy, and programming for young adults during reentry. ACEs have documented associations with anxiety, interpersonal distrust, emotional dysregulation, and using substances to cope (Bonta & Andrews, 2024). Thus, screening young adults for ACEs and using results to provide trauma-informed reentry care may improve health among youth undergoing reentry (Levenson & Willis, 2019).
Conclusion
The extremely high exposure to ACEs among many young adults experiencing reentry not only portends worse behavioral health, which is alarming, but also can guide policy action. ACEs are feasible to measure, and a trauma-informed framework may help advance the adult reentry field, especially for the care and reintegration of individuals 18–25 years old, who are at high risk but often overlooked. Addressing young adults’ prior trauma during the crucial period of reentry may be an important strategy for advancing health equity and disrupting cycles of incarceration early in a young adult’s life course.
Acknowledgments
The authors thank our partners in the WPC Reentry Program, the Whole Person Care team at the Department of Health Services, the Los Angeles County Sheriff’s Department, and the members of our community advisory board.
Authors’ Contributions
All authors contributed to the analysis and dissemination, including preparation of the article. E.B., D.M.A., C.Bo., C.G., and M.D.W. also contributed to study design and the data collection phase.
Disclaimer
The views in this article do not necessarily reflect the views of our funders or the Los Angeles County Department of Health Services.
Author Disclosure Statement
The authors disclosed no conflicts of interest with respect to the research, authorship, or publication of this article.
Funding Information
The project was funded by a National Institutes of Health/National Institute on Drug Abuse grant (K23DA045747), the California Community Foundation (BA-19-154836), and the National Center for Advancing Translational Science (UL1TR001881). The authors are responsible for the content.
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