Understanding adverse childhood experiences within the first decade of the ABCD study: A systematic review.

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Learn more: PMC Disclaimer | PMC Copyright Notice Dev Cogn Neurosci . 2026 May 9;80:101740. doi: 10.1016/j.dcn.2026.101740 Understanding adverse childhood experiences within the first decade of the ABCD study: A systematic review ☆ Abigail de Arellano a, ⁎ , Aren Tucker b , Andrew de Arellano c , Yvette Rother b , Catharine Mann b , Lauren Butler b , Matthew Albaugh d , Nicholas Allgaier e , Hugh Garavan e , Alexandra Potter e , Micah Johnson f , Ethan Hunt g , Priscila Gonçalves h , Kate Flory b Author information Article notes Copyright and License information a United States b University of South Carolina, United States c Virginia Tech, United States d University of South Carolina Columbia, United States e University of Vermont, United States f University of California Los Angeles, United States g University of Texas Health Science Center at Houston, United States h Columbia University, United States ⁎ Corresponding author. dearella@email.sc.edu Received 2025 Dec 16; Revised 2026 Apr 30; Accepted 2026 May 6; Collection date 2026 Aug. © 2026 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). PMC Copyright notice PMCID: PMC13234725  PMID: 42202720 This article has been corrected. See Dev Cogn Neurosci. 2026 Aug 6;80:101792 . Abstract Adverse childhood experiences (ACEs) are one of the most well-recognized constructs in the adversity literature and have been linked to poor developmental and health outcomes. Understanding the impact of ACEs on development is a major public health issue given the high levels of ACE exposure among US youth. The Adolescent Brain and Cognitive Development (ABCD) Study holds significant potential to elucidate developmental trajectories following exposure to ACEs within a large and geographically diverse sample. To understand how researchers have previously defined and measured ACEs within this sample, study findings and current gaps, the present systematic review covers 36 studies focused on the impact of ACEs across a range of domains within the ABCD Study. Findings suggest the need to standardize ACE measurement when using this sample as ACEs have been defined and measured heterogeneously. However, studies using the ABCD data consistently emphasize the negative effects of ACE exposure within adolescent populations, including outcomes related to physical and mental health (e.g., worse diet, overall mental health symptoms), neural and cognitive development (e.g., lower hippocampal volume, worse cognitive functioning), and family, social, and neighborhood functioning (e.g., greater peer victimization, school disengagement). The majority of reviewed studies utilize the Baseline appointment and focus on early adolescence. Findings from the present review also highlight that researchers should expand the range of developmental outcomes studied to include family and school factors and should prioritize the inclusion of protective childhood experiences, particularly using longitudinal designs and later study timepoints, in future studies using ABCD Study data. 1. Introduction The impact of childhood adversity (CA) on development across the lifespan is well-established, with a wealth of research supporting the negative impact of CA exposure on a range of outcomes during childhood and across adulthood, including neural and cognitive development ( McLaughlin et al., 2019 ), as well as mental and physical health outcomes ( McLaughlin et al., 2019 ). Here, we define CA as negative experiences in a child’s environment that likely require significant adaptation ( McLaughlin and Sheridan, 2016 ). As approximately half of youth in the United States (US) will experience one form of adversity by adulthood ( McLaughlin et al., 2019 ), it is critical to understand the potential consequences, as well as the mechanisms that link CA to outcomes. 1.1. Adverse childhood experiences Given the high proportion of youth in the U.S. who are exposed to CA and the wealth of related negative outcomes, researchers have long sought to conceptualize and measure CA. One of the most widely used measures of youth adversity is the Adverse Childhood Experiences (ACEs) scale, which was originally developed in the 1990s ( Felitti et al., 1998 ). This 10-item assessment includes questions related to physical and emotional neglect; verbal, physical, and emotional abuse; witnessing domestic violence in the home; parental divorce; and having a family member with a mental illness or substance misuse ( Felitti et al., 1998 ). Researchers often create an “ACE score” by considering individuals as exposed or not exposed to each event, and then summing the number of adverse experiences an individual reports during childhood (i.e., birth—age 18). Early research with the ACEs measure demonstrated that individuals’ likelihood of developing negative outcomes greatly increased with each ACE, with a significant jump in risk when four or more ACEs were endorsed ( Anda et al., 1999 , Dong et al., 2004 , Felitti et al., 1998 ). Additional research has indicated that this jump also exists at two or more ACEs ( Kelly-Irving et al., 2013 ). Due to the co-occurrence of many different types of adversity, evaluating the cumulative effect of these exposures may shed light on how chronic adversity shapes later outcomes. Recent estimates suggest that approximately two thirds of individuals in the US experience one or more ACEs and approximately one in six people reported four or more ACEs by age 18 ( Swedo et al., 2023 ). Nonetheless, there is a great deal of heterogeneity in findings across studies evaluating the impact of ACEs, which can be attributed to a variety of factors. These differences may be due to discrepancies between youth- and parent-reported ACEs, which may contribute to the inaccuracy of reports ( Licitis et al., 2024 ), and the lack of a standardized definition/measurement of ACEs across studies ( Sahle et al., 2022 ). The original ten ACE items have also been considered restrictive and too focused on an individual’s immediate environment. Expanded versions of the ACE questionnaire assess broader ecological impacts, including community violence and discrimination ( Zhen-Duan et al., 2023 ), as well as school violence/bullying, natural disasters, poverty, and hospitalization ( Kalmakis and Chandler, 2014 ). 1.1.1. ACEs and health, developmental, and psychosocial outcomes Among the most well-studied ACE outcomes are mental and physical health. ACEs, including both cumulative and individual exposures, have been linked to increased risk of mental health disorders and suicidality ( Petruccelli et al., 2019 , Sahle et al., 2022 ). For example, youth with ACE exposure report higher rates of internalizing symptoms ( Elmore and Crouch, 2020 , Lee et al., 2020 ), conduct problems ( Ray et al., 2020 , Turner et al., 2021 ), attention-deficit hyperactivity disorder ( Jimenez et al., 2017 , Walker et al., 2021 ), and substance use ( Afifi et al., 2020 , Shin et al., 2018 ). ACEs have also been associated with many negative physical health outcomes ( Kalmakis and Chandler, 2014 ). For instance, ACE exposure has been associated with poor global physical health ( Flaherty et al., 2013 , Luby et al., 2017 ), the onset of asthma ( Exley et al., 2015 , Ogbu et al., 2024 ), chronic illness ( Alhowaymel et al., 2023 , Barnes et al., 2020 ). Evidence also suggests a positive association between ACEs and later substance use ( Leza et al., 2021 ). Individuals exposed to multiple ACEs show elevated incidence of risk patterns for alcohol and/or cannabis use ( Gonçalves et al., 2023 ) and alcohol-related problems ( Shin et al., 2018 ). Further, specific ACE categories, such as household dysfunction, parental substance use, and childhood abuse, are associated with a higher likelihood of developing a substance use disorder ( Fuller-Thomson et al., 2016 , Gomez et al., 2018 , Kim et al., 2021 ). Childhood maltreatment has been linked to smaller prefrontal cortex (PFC) volume ( De Brito et al., 2013 , Kelly et al., 2013 ) and differences in hippocampal and amygdala volume ( Tottenham and Sheridan, 2010 ). In one of the few studies to examine the impact of cumulative ACEs on neural development, total ACE count was associated with smaller subcortical volumes and cortical thickness among early adolescents ( Buimer et al., 2022 ). Additionally, ACEs have been linked to deficits in global cognitive ability and executive functioning ( Guinosso et al., 2016 ). Cumulative ACEs have been linked to poorer later cognition, including delayed memory ( Hawkins et al., 2021 ). Further, ACEs may affect youths’ functioning across key developmental contexts, including family, peer, and school environments. Cumulative ACEs, as well as particular types of ACEs (e.g., economic hardship, exposure to life in a disrupted household, exposure to violence), have been linked to school absenteeism, repeated grades, and nonengagement in school ( Crouch et al., 2019 ). ACE exposure has also been negatively associated with peer relationship quality and peer status ( Wang et al., 2024 ) and worse family functioning ( Scully et al., 2020 ). Despite experiences of adversity, many youth thrive following experiences of CA. Many protective factors appear to buffer the impact of ACEs on later outcomes ( Geng, 2025 ), including intrapersonal characteristics (e.g., hope and future-oriented thinking; Sparks et al., 2021 ) and interpersonal and contextual factors (e.g., school and neighborhood safety, presence of at least one secure adult; Crouch et al., 2019 ; Moore and N. Ramirez, 2016 ). Protective factors operate through multiple pathways (e.g., reducing the activation of the stress-response system, teaching new learning) to stabilize youth development and mitigate the negative impact of CA. Understanding these protective factors is critical for shaping intervention design and policy reform ( Geng, 2025 ). Current ACE literature is limited by its use of retrospective reports ( Petruccelli et al., 2019 ), underscoring the need for more prospective research with children and adolescents to evaluate the impact of ACE exposure over time. Additionally, many studies have focused on the consequences of specific ACEs on neural development during adolescence ( Hackman and Farah, 2009 , Hart and Rubia, 2012 , Merz et al., 2019 , Merz and Noble, 2017 ). However, fewer have assessed the impact of cumulative ACE exposure on neural development. Furthermore, current research often focuses on deficit-based models rather emphasizing resilience. 1.1.2. ACE research in the ABCD study As previously mentioned, there is a need to assess the impact of ACEs using prospective cohort samples of youth to understand the role of CA in shaping development over time. Such investigations are possible utilizing data from large, prospective samples such as in the Adolescent Brain and Cognitive Development ℠ (ABCD) Study. The ABCD Study® is the largest U.S. National Institutes of Health (NIH)-funded study of adolescent development to date and includes assessments of neuroimaging, cognition, mental and physical health, and the youth’s family and environment. The ABCD Study follows youth from 21 geographically diverse sites for a decade, beginning at ages 9 or 10, as they progress through adolescence. As such, it provides the unique opportunity to assess the impact of ACEs across different domains of a youth’s life over time. Over 42 published scientific studies have used open-access ABCD datasets to examine the consequences of exposure to CA/ACEs. Within the ABCD Study, ACEs are assessed by several included assessment tools (e.g., interviews, parent- and self-report rating scales, neighborhood-level data) rather than one ACEs measure. Consequently, there has been a great deal of diversity in how studies using the ABCD dataset have defined and measured ACEs. Primary Investigators of the ABCD Study have published suggested guidelines for how to measure ACEs within the baseline assessment of the study ( Hoffman et al., 2019 ). However, researchers still diverge in how they categorize each ACE and what exposures (e.g., those in the broader environment) they include in their definition. In response, other researchers have developed further best practices to measure ACEs at ABCD baseline and follow-up appointments through synthesizing existing papers assessing ACEs using the ABCD sample ( Breslin et al., 2025 ). However, there are no existing reviews of studies linking ACEs to outcomes using ABCD Study data, nor summarizing the range of different methodological approaches to studying ACEs. A synthesis of this nature is critical, both to fully understand the impact of existing research, but also to guide future research on ACEs using existing and yet-to-be-released waves of ABCD Study data. Of note, the present review focuses on studies that explicitly define and operationalize adversity using the ACEs framework, as opposed to broader or related constructs (e.g., stressful life events, childhood adversity), to ensure conceptual consistency across the reviewed literature. 1.2. The present review The present review, therefore, addresses the following aims: Aim 1: Describe the differences in how ACEs have been defined and measured within the ABCD Study. Aim 2: Describe methodological approaches utilized in each study, including statistical methods and study time points. Aim 3: Synthesize key findings from the ABCD Study supporting the association between ACEs and a range of youth outcomes across multiple domains, including mental and physical health, neurodevelopmental, cognitive, and social domains. Aim 4: Report on any protective factors identified within included studies, as this has important implications for prevention and intervention. Aim 5: Describe gaps in the literature and future research directions to deepen our understanding of the impact of ACEs on development. In summary, the present review will describe how ACEs have been measured in studies using the ABCD data (e.g., ACE definition and statistical method), what outcomes have been found, and where researchers should go next to understand the impact of CA on development. 2. Methods 2.1. Search strategy A systematic search strategy was employed to identify relevant studies. Study selection and data collection were completed in Covidence (Covidence systematic review software, Veritas Health Innovation, Melbourne, Australia. Available at www.covidence.org ). To identify studies to be included in the present review, a systematic search was performed on August 7th, 2025 across PubMed, PsycINFO, and Web of Science using the following search terms: “Adolescent Brain Cognitive Development Study” OR “ABCD Study” AND keywords associated with childhood adversity broadly, such as “adverse childhood experiences”, “ACES”, “childhood trauma”, “early life stress”, “child abuse”, “child maltreatment”, “early adversity”, and “childhood adversity”. Search terms also included specific forms of adversity, such as “emotional abuse”, “sexual abuse”, “physical abuse”, “neglect”, “divorce”, “separation”, “incarceration”, “domestic violence”, “substance abuse”, and “mental illness”. Only studies published between January 2018 and August 2025 were included, as articles utilizing ABCD Study data were first published in 2018. This review followed PRISMA guidelines for systematic reviews and meta-analyses ( Page et al., 2021 ). 2.2. Study inclusion and exclusion criteria Predefined inclusion and exclusion criteria described below guided the study selection process once identified. This process was conducted in two stages: an initial screening of titles and abstracts, followed by a full-text review of studies that met preliminary eligibility criteria. Three reviewers independently performed the standardized study selection process (i.e., title and abstract screening, full-text review), four reviewers were involved in data extraction (i.e., two reviewer pairs completed independent data extraction, then data were compared to find discrepancies for each article). Studies were eligible for inclusion if they utilized data from the ABCD Study and included a cumulative measure of ACEs (“ACE” or “adverse childhood experiences”) as a main predictor as we sought to understand how different ABCD papers have defined and measured cumulative ACEs within the dataset to address our first study aim. Eligible studies were also required to examine at least one developmental outcome, including physical (e.g., body mass index), neural (e.g., brain structure), or mental health outcomes (e.g., internalizing or externalizing symptoms). Finally, studies had to be peer-reviewed, empirical, and published in English. Studies were excluded if they did not meet each of the criteria required for inclusion listed above. 2.3. Procedures for study selection Covidence is a web-based collaboration software platform that streamlines the production of systematic and other literature reviews. All decisions and the rationale for exclusions were documented within Covidence. The flow of article identification, screening, and inclusion throughout the review process is summarized in Fig. 1 . A total of 70 articles were retrieved from PubMed, 61 from PsycINFO, 74 from Web of Science, and 25 additional studies from the ABCD publication repository hosted at https://abcdstudy.org/publications/ . This database includes peer-reviewed studies from MEDLINE, Web of Science, Scopus, Directory of Open Access Journals, and NIH Library. Following the removal of 131 duplicate records, 99 unique studies were retained. Titles and abstracts were screened to identify potentially eligible studies, resulting in 68 articles selected for full-text review. Of these, one was excluded for not using ABCD data, three were excluded for lacking empirical data, one was excluded because the abstract was for a conference poster, 21 were excluded for lacking a measure of ACEs, three were excluded because ACEs was not the main predictor, and three were excluded for lacking cumulative ACEs measures, leaving 36 within the inclusion criteria for the review. During both title and abstract screening and full-text review, any disagreements between the two primary reviewers were discussed with a third reviewer until a consensus was met between all three reviewers. Fig. 1. Open in a new tab Prisma Diagram. 2.4. Procedures for data extraction For data extraction, each article was assigned a primary and secondary reviewer. For each article, after both reviewers independently extracted data, the primary reviewer identified and resolved discrepancies between reviewers. The extracted data included study authors, publication year, country of origin of the first author, sample size, sample characteristics (e.g., if studies only looked at Black or Latine youth), inclusion criteria, ABCD data release, time points included, analytical approach (e.g., moderation, mediation), covariates, ACE definition and measurement, outcome variables, and key findings. Any missing or unclear information was noted. 3. Results The ABCD Study will include 10 waves of data, following youth across adolescence. The baseline visit took place when youth were ages 9–10. The baseline appointment included 11,875 youth. Of these youth, 47.8% were female, 52.1% White, 20.3% Hispanic/Latine, 15.0% Black/African American, 0.1% Asian, and 10.5% other (including biracial; Karcher and Barch, 2021 ). As of spring 2025, the 6.0 data release ( Jernigan et al., 2025 ) was publicly available, which includes data from the entire year four appointment (youth ages 13–14) and half of the year five visit (youth ages 14–15). To understand the outcomes related to ACEs identified in the ABCD Study, we conducted a systematic review of papers using ABCD data. Across the 36 extracted studies, researchers examined the impact of ACEs on mental and physical health, neural development, cognitive functioning, substance use, and other family, school, and neighborhood outcomes. The majority of papers included a focus on mental health ( n = 20; 55.6%), followed closely by physical health ( n = 12; 33.3%). An additional five (13.9%) papers examined the association between ACEs and neural development. Furthermore, several studies included cognitive functioning ( n = 2; 5.5%) and substance use ( n = 3; 8.3%) as outcomes. Finally, three (8.3%) papers examined outcomes related to family, school, and youths’ neighborhoods and two (5.5%) papers included protective factors. See Table 2 for a full description of the papers and their findings related to ACEs and health and well-being outcomes in the ABCD Study, as well as Fig. 6 for a visualization of the represented domains. Table 2. Summary of full-text articles that examined direct effects. Authors and year Timepoints included Longitudinal (Y/N) Measurement type and scale Analysis type Main findings Mental Health Albertina et al., (2024) baseline, year one N ◆ Continuous summary score Generalized linear mixed models Potential overlap between resting-state functional connectivity associations with both ACEs and internalizing symptoms Baldwin et al., (2022) baseline, year one N ✚ Each of the 6 domains was dichotomized into exposed and unexposed Structural equation modeling Polygenic risk scores for mental health problems explained a very small proportion of the association between ACEs and internalizing problems as well as externalizing problems at Baseline Barnhart et al., (2022) baseline, year one, year two Y ◆ Continuous summary score Path analyses ACEs and low family economic status are risk factors for adolescent mental health symptoms Family conflict strengthens these associations Choi et al., (2025) baseline, year one N ▧ Four different ACE classes: Low ACE (reference group) ACEs: Household and Community Violence Class ACEs: Intersectional discrimination class ACEs other: Moderate ACE class ACEs other: Parent Behavioral Challenges class Latent class analysis and linear mixed models All latent class ACE exposures were significantly related to internalizing, externalizing, and total CBCL outcomes Chow et al., (2025) baseline, year one, year two, year three Y ▧ Continuously across the four domains Univariate and multivariate linear analyses Within the ABCD Study, ACEs can be characterized into parental threat, deprivation, victimization, and traumatic events All domains were significantly related to greater internalizing and externalizing symptoms Chu et al., (2022) baseline, year one, year two N ✚ Groups of 0, 1, 2, and 3 + ACEs Logistic regression with propensity weighting Exposure to 1, 2, and 3 + ACEs were each associated with greater odds of adolescent binge eating disorder Damme et al., (2024) baseline N ◀ Created three categories: 0 ACEs, Moderate (1−3), High (4 +) Generalized additive mixed model, Multilevel modeling ACEs predict lower hippocampal volume and greater PLEs Garcia et al., (2025) baseline, six-month follow-up, year one, year two Y ▧ Used first component of PCA as ACE measurement PCA and path analysis ACEs significantly predicted parent and youth-reported externalizing symptoms. Family functioning mediated the link but ethnic identity and community cohesion did not. ACEs significantly predicted lower ethnic identity and family functioning Hill et al., (2025) baseline, year one, year two, year three Y ○ Continuous summary score Neural network models, include propensity weights ACEs were in the top five strongest predictors of general psychopathology risk, following sleep disturbances and prosocial behaviors Karcher et al., 2024 baseline, year one, year two Y ☐ Continuous summary score Random forest classification ACEs were important predictors of persistent distressing PLEs when comparing them to low-level PLEs Karcher et al., (2020) baseline N ☐ Continuous summary score Hierarchical linear mixed models and mediation analyses Greater ACEs were associated with higher PLEs Bullying, financial adversity, domestic violence exposure, and traumatic grief were each associated with PLEs ACEs were positively associated with family history of psychosis, stress, internalizing symptoms, and suicidality and negatively associated with fluid cognition PLEs partially mediated the association between ACEs and internalizing symptoms, and ACEs and suicidality Liu et al., (2025) baseline, year two, year four Y ◀ Continuous; included individual items Linear mixed models and mediation analyses Greater ACEs and all ACE dimensions were associated with conduct problems Conduct problem-related neural connections partially mediated the association between ACEs and conduct problem scores at baseline, year-two follow-up and year-four follow-up Logan, Lewis-de Los Angeles (2025) baseline, year one, year two N ◉ Continuous summary score Multivariate linear regression analyses ACEs were associated with a higher score on the following CBCL scales: anxious/depressed, withdrawn, aggressive behavior, attention problems, rule-breaking behavior, social problems, somatic complaints, thought problems, and total problems Interaction between ACEs and positive childhood experiences significantly weakened the association between ACEs and the following subscales: Anxious/depressed, withdrawn, aggressive behavior, rule-breaking behavior, social problems, thought problems, and total problems Nagata 2023- cyber baseline, year one, year two N ◉ ACE groups of 0, 1, 2, 3, 4 + ; Evaluated individual items as well Logistic regression with propensity score weights 2, 3, and 4 + ACEs were associated with cyberbullying victimization Sexual abuse, physical neglect, and household mental health problems had the strongest associations with cyberbullying victimization Niu et al., (2025) baseline, year one, year two, year three Y ▧ Continuous summary score Mixed-effect linear models and longitudinal mediation models ACEs from baseline or the year-one follow-up significantly predicted greater school disengagement and lower school involvement ACEs significantly predicted internalizing and externalizing symptoms at the year-three follow-up School disengagement and involvement mediated the association between ACEs and later mental health problems Petti et al., (2025) baseline, year one, year two Y ▧ Continuous summary score PCA and mediation analyses; Experiences of discrimination, financial adversity, and adverse childhood events (ACEs) were added into a PCA ACEs predicted PLEs Cumulative stress, including ACEs, mediate the association between environmental stress and PLEs Environmental risk and cumulative stress were partially responsible for the association between racial/ethnic identity and PLEs among Black and Hispanic/Latine youth Senger-Carpenter, Zhang, et al., (2025) baseline, year one, year two, year three Y ✚Early exposures ranged from 0 to 9, and recent exposures ranged from 0 to 6. All domains were evaluated individually. Autoregressive cross-lagged panel model to estimate direct effects of early and recent ACE exposures on annual pain frequency scores and persistent/recurrent pain Indirect effects of early and recent ACE exposures on pain outcomes via interim anxiety and depression symptoms Higher levels of early ACE exposures were associated with increased odds of persistent/recurring pain (PRP) Early ACEs had indirect effects on PRP through anxiety and depression Early and recent ACEs were associated with higher pain frequency scores Youth with PRP had higher rates of sexual abuse, emotional abuse, physical neglect, parental mental health and substance use problems, witnessing interpersonal violence, and parental divorce/separation PRP youth also reported higher rates of physical neglect, parental mental health and substance use problems, and parental imprisonment Stinson et al., (2021) baseline, year one, COVID Impact Survey 1 Y ▧ Continuous summary score Linear mixed effect models; interaction terms ACE exposure prior to COVID-19 predicted greater sadness, less positive affect, greater fear and worry, greater anger and frustration, greater perceived stress ACE exposure did not predict pandemic-related worry Race and ethnicity did not moderate ACE exposure and later negative outcomes Trompeter 2024 baseline, year one, year two Y ◉ 0, 1, 2, 3, or 4 + ACEs Linear regressions, linear regressions with an interaction term, use of propensity score weights Exposure to ACEs (1, 2, 3, and 4 +) significantly predicted higher internalizing and externalizing problems. Bullying victimization did not moderate the association Vedechkina 2023 baseline, year one, year two N ▧ Possible 21 events- people with two or more events were assigned to the adversity group Participants were classified into an early life adversity (ELA) group or a no adversity (NOA) group using a Random Forest model. Within each group, subgroups were identified based on cognitive score and compared with t -tests. Moderate-to-severe early life adversity (ELA) showed lower cognitive performance and higher mental health difficulties Xiao, 2024 baseline, year two Y ▧ Continuous summary score; Subdimensions of threat (0−13) and deprivation (0−5) Linear regression and moderation analyses ACEs at baseline predicted psychiatric disorders at baseline and the year-two follow-up Brain-based markers of resiliency (i.e., connectome variate) weakened the association between ACEs and mental health diagnoses Moderation effect was stronger among females and among those exposed to threat Physical Health Al-Shoaibi et al. (2024) baseline, year one, year two Y ✚ 0, 1, 2, 3, or 4 + ACEs and individual ACEs Multivariate linear and logistic regression analyses with propensity weighting Exposure to ≥ 4 ACEs at baseline was significantly associated with systolic blood pressure (SBP) Household substance use and divorce/separation were significantly associated with higher SBP Household mental illness was significantly related to higher diastolic blood pressure Al-shoaibi et al. (2024) baseline, year one, year two N ◀ 0, 1, 2, 3, or 4 + ACEs and individual ACEs Linear regression with propensity weighting ACE exposure was significantly associated with fewer Fitbit steps Exposure to divorce, mental illness, physical neglect, and emotional abuse were significantlyassociated with less physical activity Lewis-de Los Angeles (2022) baseline, year one Y Ⓞ 0, 1, 2 + ACEs Linear regression, propensity score weighting 1 and 2 + ACEs significantly predicted diet and sleep in comparison to 0 ACEs, but not physical activity Lewis-de Los Angeles (2024) baseline, year two Y ⓄACE groups of 0, 1, and 2 + Multivariate linear regression 1 or 2 + ACEs significantly predicted sleep (sleep duration, REM duration) and physical activity (number of steps and moderate-to-vigorous physical activity) McCarthy et al., (2023) year two N ⧫ Continuous summary score Hierarchical linear regression ACEs significantly predicted sleep chronotype and relative social jetlag Raney et al., (2022) baseline, year one, year two; COVID Rapid Response Research Survey N ✚ Continuous summary score Linear regression analyses with propensity weighting Greater exposure to ACEs was positively related to screentime hours and negatively related to hours per week of physical activity; number of days youth completed ≥ 60 min of exercise in the past week Raney et al., (2023) baseline, year two Y ✚ ACE groups of 0, 1, 2, 3, 4 + Generalized logistic mixed effect models All levels of ACEs were associated greater likelihood of problematic video game and mobile phone use Saadi et al., (2024) baseline N ○ ACE groups of 0, 1, 2, 3, 4 + ; Evaluated individual items as well Logistic regression 2 and 4 + ACEs were associated with greater odds of head/neck injury and concussion 3 ACEs are associated with greater odds of head/neck injury Sexual abuse, parent domestic violence, parent mental illness, and parental criminal involvement were associated with increased risk of head or neck injury Parental mental illness was associated with increased risk of concussion Senger-Carpenter et al., (2025) baseline, year one, year two, year three Y ▧ Only included youth with ≥ 1 ACE; Dichotomized into two groups 1–2 and ≥ 3 ACEs Multilevel mixed effects logistic regression with interaction terms Exposure to ACEs significantly predicted sleep disturbances No interaction effect between ACEs and race/ethnicity Senger-Carpenter, Zhang, et al., (2025) See Mental Health. Smith et al., (2025) baseline, year one, year two N ✚ ACE groups of 0, 1, 2, 3, 4 + Multinomial logistic regression analyses 3 and 4 + ACEs significantly predicted regional and multisite pain Neural Development Albertina et al., (2024) See Mental Health. Breslin et al., (2024) baseline, year one, year two Y ◈ Continuous summary score Linear mixed effect models High adversity was associated with hippocampal change, as well as lower hippocampal volume at baseline and the year-two follow-up Damme et al., (2024) baseline N ◀ Created three categories: 0 ACEs, Moderate (1−3), High (4 +) Generalized additive mixed model, Multilevel modeling ACEs predict lower hippocampal volume and greater PLEs Liu et al., (2025) See Mental Health. Stinson et al., (2024) baseline, year one, year two N ▧ Continuous measurement Linear mixed-effects (LME) design with interaction terms Increased ACE exposure was associated with decreased BOLD response bilaterally in the pre-supplementary motor area and in the right opercular region of the inferior frontal gyrus Family conflict did not serve as a risk factor between ACE exposure and any outcomes Cognitive Functioning Karcher et al., (2020) See Mental Health. Vedechkina, Holmes (2024) See Mental Health. Substance Use Nagata et al., (2023) baseline N ✚ 0, 1, 2, 3, or 4 + ACEs and individual ACEs Weighted Poisson regression; propensity weights Exposure to 2, 3, and 4 + ACEs; Violence in the home and household alcohol misuse were associated with greater odds of sipping alcohol Johnson et al., (2023) baseline, year one N ⧫ Continuous summary score Mixed-effect regression models Exposure to a higher number of ACEs was significantly associated with positive alcohol expectancies Rodrigues et al., (2025) baseline, year three Y ▧ Continuous summary score Mixed-effect regression models Exposure to ACEs was associated with increased risk for future alcohol, cigarette/e-cigarette, and cannabis use Neither parent or youth-reported family conflict moderated association between ACEs and substance use Family, Peer, and Neighborhood Functioning Garcia et al., (2025) See Mental Health. Niu et al., (2025) See Mental Health. Open in a new tab CBCL= Child Behavior Checklist PLEs= Psychotic like experiences BOLD= Blood-Oxygen-Level-Dependent Fig. 6. Open in a new tab Prevalence of included studies examining each outcome category related to ACEs. 3.1. Definitions and measurement of ACEs within the ABCD study See Table 1 for a detailed description of the definitions and the measures used to assess these exposures. Additionally, see Fig. 2 for a visualization of the proportion of studies using each definition, as well as Table 2 to see which studies used each definition. The measures listed in four (11.11%) studies captured ACEs with 34 items from the PhenX Life Events Checklist (PhenX LEC; e.g., loss of a parent, exposure to violence at school, death of a friend) with an additional study assessing exposure to the events on the PhenX LEC, as well as seven questions about financial adversity. Two (5.6%) studies assessed ACEs through inquiring about exposures to bullying, financial adversity, and traumatic events through the KSADS PTSD module. Three (8.3%) studies examined exposure to family violence or threats directed at the child, witnessing domestic violence, sexual assault, unexpected family death, alcohol or drug misuse in a biological parent, mental illness in a biological parent, criminal behavior in a biological parent, and divorce or separation of a primary caregiver. Three (8.3%) measured exposure to physical and sexual abuse, physical and emotional neglect, substance misuse in the household, household violence, household mental illness, and divorce/separation. Two (5.6%) studies measured exposure to physical and sexual abuse, emotional neglect, divorce/separation, parental violence, household substance use, household mental illness, and household incarceration. Seven (19.4%) studies used nine different events (e.g., sexual and physical abuse, physical and emotional neglect, incarceration of household member, household substance use, household violence, household mental illness, and divorce or separation) and four (11.1%) studies used ten exposures (e.g., sexual, emotional, and physical abuse, physical and emotional neglect, incarceration of a household member, household substance use, household violence, household mental illness, and divorce or separation) to examine ACE exposure. Lastly, eleven (30.56%) papers used expanded definitions of ACEs that included many of the experiences listed above in addition to exposure to discrimination, community violence, and negative peer experiences. Around half of the studies ( n = 17; 47.2%) utilized both youth and parent reporters in their ACE measurements; however, six (16.7%) only relied on parent reports and four (11.1%) solely used youth reports (see Fig. 5 ). While many researchers created an adversity score by assessing if either the parent or youth positively endorsed having experienced an event, some created a total sum score of adversity based on youth and parent reports. Table 1. ACE measurement. ACE Assessment Conceptualization Measures Symbol Life events scale Exposure to up to 25 stressful life events that included questions related to familial exposure to the criminal justice system, separation from a caregiver, parental divorce/separation, exposure to violence at school PhenX Life Events Checklist ◆ Life events & financial insecurities Stressful life events and seven questions related to financial insecurity questions PhenX Life Events Checklist Financial adversity questionnaire (e.g., been evicted, could not afford: food, telephone services, rent/mortgage, gas/electric, medical care, and dental care) ◈ Trauma exposure, bullying, & financial insecurities Exposure to up to 17 questions about trauma exposure (e.g., car accident, serious accident requiring medical attention, exposure to a fire, present for an act of terrorism, witnessed death or mass destruction, shot/stabbed/beaten by a non-family member, death/serious injury of a family member, assaulted, threats against life, physical abuse, witnessing domestic violence, sexual abuse), exposure to bullying in the neighborhood or at school, and financial insecurity question KSADS-5 PTSD Module – Parent KSADS parent-report questionnaire on youth exposure to bullying Financial adversity questionnaire ☐ Eight exposures (1) Physical and sexual abuse, domestic violence, substance use in biological parent, mental illness in biological parent, criminal behavior in biological parent, caregiver divorce/separation, unexpected family death KSADS-5 PTSD Module – Parent Family history assessment Demographics Ⓞ Eight exposures (2) Physical and sexual abuse, physical and emotional neglect, domestic violence, substance misuse in the household, household mental illness, caregiver divorce/separation KSADS-5 PTSD Module – Parent Family Environment Scale- Parent Report Demographics survey – Parent CRPBI Acceptance Subscale – Youth Parental Monitoring Survey ◉ Eight exposures (3) Physical and sexual abuse, emotional neglect, domestic violence, household substance use, household mental illness, household incarceration, divorce/separation KSADS-5 PTSD Module – Parent CRPBI Acceptance Subscale–Youth PhenX Life Events Checklist – Parent Parent Demographics Family History Assessment Youth Life Events ○ Nine exposures Physical and sexual abuse, physical and emotional neglect, household violence, household substance use, household mental illness, incarceration of a household member, divorce or separation KSADS-5 PTSD Module – Parent Family Environment Scale–Parent Report Family History Assessment–Parent Demographics survey – Parent CRPBI Acceptance Subscale–Youth Parental Monitoring Survey ✚ Ten exposures Sexual, emotional, and physical abuse, physical and emotional neglect, household violence, household substance use, household mental illness, incarceration of a household member, and divorce or separation KSADS-5 PTSD Module–Parent Family Environment Scale–Parent Report Family History Assessment–Parent Demographics survey – Parent CRPBI Acceptance Subscale–Youth Parental Monitoring Survey ◀ Diverse exposures Expanded ACEs, including physical, emotional, and sexual abuse; physical and emotional neglect; domestic violence; parental divorce/separation; mental illness in the household; substance misuse; family involvement with the legal system; financial adversity; discrimination; bullying; grief; community violence; negative peer experiences; and/or trauma exposure KSADS-5 PTSD Module–Parent-report Family Environment Scale–Parent Report Family History Assessment–Parent Demographics survey – Parent CRPBI Acceptance Subscale–Youth Parental Monitoring Survey Unfair Treatment Survey Neighborhood Safety Questionnaire Financial adversity questionnaire PhenX Life Events Checklist Peer Experiences Questionnaire Cyberbullying Questionnaire Adult Self-Report ▧ Open in a new tab KSADS-5 = Kiddie Schedule for Affective Disorders and Schizophrenia for DSM-5 CRPBI = Children’s Report of Parental Behavior Inventory Fig. 2. Open in a new tab ACE definitions within the ABCD Study. Fig. 5. Open in a new tab Proportion of parent and child reports in each study. 3.2. Methodological approaches Regarding methodological approach, 34 (94.4%) studies utilized a variation of regression (e.g., linear, logistic, mixed-effect, generalized additive models), five (13.9%) studies used structural equation or path-based approaches, two (5.6%) studies incorporated principal component analysis, and three (8.6%) studies used machine learning approaches (e.g., random forest classification, neural network models). Further, 12 (33.3%) studies included a nested effect (e.g., study site, family). Analytic methods included linear and logistic regression, principal component analyses, mediation, latent class analyses, and random forest models. The ABCD Study will span across adolescence; its first timepoint is the baseline appointment when youth were ages 9–10 and the last scheduled adolescent timepoint is the year nine follow-up when youth will be ages 19–20. Many of the included studies utilized data collected at baseline (youth were ages 9–10; n = 35; 97.2%), as well as the year one (ages 10–11; n = 27; 75%) and year two follow-ups (ages 11–12; n = 24; 66.7%). Representing a smaller proportion of the included studies, six (16.7%) studies used data from the year three follow-up (ages 12–13), one (2.8%) study used data from the year four follow-up (ages 13–14), one (2.8%) study used data from the six-month follow-up (ages 9.5–10.5), and two (5.6%) studies used data from the COVID Rapid Report. Many studies collapsed ACE scores across multiple time points (e.g., an event was considered positively endorsed if a participant experienced an event at baseline, year one follow-up, or year two follow-up). See Fig. 3 , Fig. 4 , Fig. 5 , Fig. 6 for a visualization of the utilized timepoints. Approximately half of the studies ( n = 19; 52.8%) leveraged the longitudinal nature of the ABCD Study and evaluated the impact of ACEs on later outcomes. The majority of these longitudinal studies utilized a two time-point approach (e.g., ACEs at baseline predicting outcomes at the year two follow-up). A small proportion of studies ( n = 9; 25%) utilized propensity score weighting to account for potentially confounding factors (e.g., socioeconomic status, race) by matching youth who have been exposed to adversity to unexposed youth with matching demographics. Fig. 3. Open in a new tab Breakdown of timepoints utilized by each study. Fig. 4. Open in a new tab Proportion of longitudinal vs. cross-sectional studies. 3.3. Findings related to ACEs and developmental outcomes from the ABCD Study 3.3.1. Mental health All 21 (58.3%) studies that examined the impact of ACEs on mental health outcomes supported the deleterious effect of ACEs on adolescent mental health. Many of the studies focused on broad internalizing and externalizing symptoms, as well as overall mental health functioning (Albertina 2024; Baldwin et al., 2022 ; Barnhart, 2022; Choi et al., 2025 ; Chow et al., 2025 ; Garcia et al., 2025 ; Logan, Lewis-de Los Angeles, 2025 ; Niu et al., 2025 ; Vedechkina, Holmes, 2024 ; Xiao, 2024), supporting the association between increased exposure to ACEs and poorer mental health outcomes among youth. When examining the impact of ACEs across a range of mental health outcomes, studies supported the positive association between ACE exposure and withdrawal, anxiety/depression, attention problems, rule-breaking behavior, social problems, somatic complaints, and thought problems ( Logan, Lewis-de Los Angeles, 2025 ), as well as perceived stress and worry ( Stinson et al., 2021 ) and suicidality ( Karcher et al., 2020 ). Additionally, included studies demonstrated an increased risk for psychopathology among youth exposed to ACEs (Hill, 2025). Researchers also examined the association between ACEs and specific disorders, finding that exposure to ACEs increases the likelihood that youth demonstrate binge-eating disorder ( Chu et al., 2022 ). Additionally, ACEs were associated with increased risk for cyberbullying victimization ( Nagata et al., 2023 ), as well as conduct problems ( Liu et al., 2025 ). Several studies focused on the increased risk for psychotic-like experiences (PLEs) among youth exposed to ACEs ( Damme et al., 2024 , Karcher et al., 2020 , Petti et al., 2025 ). In sum, the association between exposure to ACEs and worse mental health functioning in youth was strongly supported across studies. 3.3.2. Health behaviors and outcomes Similarly, studies ( n = 11; 30.6%) provided broad support for the association between exposure to ACEs and poorer health behaviors and outcomes. Several studies of health focused on physical activity (PA), including youth-reported hours of exercise per week and number of days where youth exercised for more than 60 min a day ( Lewis-de Los Angeles, 2024 , Raney et al., 2022 ), as well as device-based Fitbit steps ( Al-Shoaibi et al., 2024 , Lewis-de Los Angeles, 2024 ). The majority of the reviewed studies asserted that higher exposure to ACEs was linked to worse physical health behaviors and related outcomes (e.g., less PA, higher screentime use), with the exception of one study. This study reported that youth with at least one ACE exposure did not significantly differ from youth who had not experienced ACEs on overall amount of exercise reported, although youth with two or more ACEs reported less aerobic exercise than youth with no ACEs ( Lewis-de Los Angeles, 2022 ). In evaluating the relation between ACEs and diet and sleep (e.g., overall duration and REM duration; Lewis-de Los Angeles, 2022 ; Lewis-de Los Angeles, 2024 ; sleep chronotype and relative social jetlag, McCarthy et al., 2023 ; sleep disturbances; Senger-Carpenter et al., 2025 ), studies indicated that greater ACE exposure predicts adverse sleep outcomes across multiple domains. Further, greater ACEs were associated with more problematic screen use, including problematic video game and mobile phone use ( Raney et al., 2023 , Raney et al., 2022 ). In addition to examining health-related behaviors, studies included in the current review highlighted the significant association between exposure to ACEs and adverse health outcomes. Specifically, individual ACEs such as exposure to household substance misuse or parental divorce/separation, as well as experiencing more than four ACEs, were positively linked with high systolic blood pressure, while exposure to household mental illness was linked to higher diastolic blood pressure ( Al-Shoaibi et al., 2024 ). Overall ACE exposure and individual ACEs (e.g., sexual abuse, parent domestic violence, parent mental illness, parental criminal involvement) were linked to increased risk for head/neck injuries and concussions (Saadi, 2024). Additionally, ACE exposures, both early and recent, were linked to persistent and recurrent pain among youth ( Senger-Carpenter, Zhang, et al., 2025 ), as well as regional and multisite pain ( Smith et al., 2025 ). 3.3.3. Substance use Three (8.3%) studies investigated the associations between ACE exposure and adolescent substance use. In a sample of youth who had not yet sipped alcohol, exposure to ACEs was associated with positive alcohol expectancies, indicating that youth with an ACE exposure were more likely to hold positive preconceptions about how the consumption of alcohol would make them feel or behave ( Johnson et al., 2023 ). Another study found that higher ACE exposure was linked to higher risk of alcohol sipping, with youth who had four or more ACEs being 1.27 times more likely to sip alcohol compared to youth with no ACEs; specifically, household violence and household alcohol abuse were the ACE subtypes significantly associated with higher risk of alcohol sipping ( Nagata, Smith, et al., 2023 ). Further, a recent study found a positive correlation between higher cumulative ACE scores at baseline and later risk for alcohol, cigarette/e-cigarette, and cannabis use at three-year follow-up ( Rodrigues et al., 2025 ). 3.3.4. Neural and cognitive outcomes Seven (19.4%) studies contributed neurodevelopmental findings related to ACEs. Increased ACE exposure was significantly associated with decreased blood oxygenation level dependent (BOLD) response in neural regions (e.g., pre-supplementary motor area, right opercular region of inferior frontal gyrus; Stinson et al., 2024 ), lower hippocampal volume (Damme, 2024), as well as alterations in resting-state functional connectivity (Albertina, 2024) and hippocampal size ( Breslin et al., 2024 ). ACE exposure was also significantly associated with smaller hippocampal size at baseline ( Breslin et al., 2024 ). Further, the conduct problem-related neural connections partially mediated the association between ACEs and conduct problems ( Liu et al., 2025 ). Regarding cognitive outcomes, ACEs were significantly associated with worse fluid cognition ( Karcher et al., 2020 ) and poorer overall cognitive performance ( Vedechkina, Holmes, 2024 ). 3.3.5. Family, neighborhood, and school outcomes Two (5.6%) studies incorporated family functioning, neighborhood environment, and school-related variables ( Garcia et al., 2025 , Niu et al., 2025 ). ACE exposure predicted a lower sense of ethnic identity and worse family functioning ( Garcia et al., 2025 ). Family functioning was a significant mediator in the association between ACEs and externalizing symptoms, such that this association was partially explained by family functioning. However, ethnic identity and community cohesion were not found to be significant mediators ( Garcia et al., 2025 ). Finally, ACE exposure in early adolescence significantly predicted greater school disengagement and lower school involvement two years later (Niu, 2025). School involvement also partially mediated the association between ACEs at baseline and internalizing and externalizing symptoms at the year three follow-up, subsequently decreasing levels of internalizing and externalizing symptoms among those exposed to ACEs ( Niu et al., 2025 ). 3.3.6. Protective factors Only two (5.56%) studies integrated protective factors into their work; however, those that did identified several factors that weakened the association between ACEs and later negative outcomes, including positive childhood experiences (PCEs; Logan, Lewis-de Los Angeles, 2025 ) and brain-based markers of resiliency ( Xiao et al., 2024 ). PCEs were measured by a total score reflecting how many of the positive experiences (e.g., having close friends, caring teachers, liking school) a child or their parents endorsed ( Logan, Lewis-de Los Angeles, 2025 ). Higher scores on this PCEs measure buffered the association between ACEs and several domains of mental health symptoms, including anxiety, depression, withdrawal, aggression, rule-breaking behavior, social problems, and thought problems ( Logan, Lewis-de Los Angeles, 2025 ). Further, neuroimaging evidence suggests that neural resiliency markers may weaken the association between ACEs and later mental health diagnoses, particularly among youth who have been exposed to threatening experiences (e.g., events involving harm or threat of harm; McLaughlin et al., 2014 ) and female participants ( Xiao et al., 2024 ). Of note, the majority of all reviewed papers reported effect sizes ranging from very small to moderate. Associations of moderate strength were more often linked to mental and physical health outcomes. The only large effect size reported among the reviewed articles was within the association between experiencing 3 + ACEs and increased odds of demonstrating binge eating disorder during adolescence ( Chu et al., 2022 ). Some effect sizes were larger as the number of reported ACEs increased (e.g., strength of association between ACEs and reporting cyberbullying victimization was greater at 4 + ACEs than at fewer than 4 ACEs; Nagata et al., 2023 ). 3.4. Summary In sum, our study has observed high heterogeneity in ACEs definitions in studies using data from ABCD, including using individual level data (e.g., parent- or self-report of an ACE) as well as community-level ACEs (e.g., child or parent reports on neighborhood safety, inclusion of discrimination). The majority of the reviewed studies utilized data from the baseline visit and approximately half of the studies were longitudinal. Additionally, there is a wealth of support for the negative consequences of ACEs on adolescent health and developmental outcomes, consistent with prior research, with few studies evaluating protective factors in this association. 4. Discussion The present review sought to identify what outcomes have been found to be associated with ACEs, as well as how researchers have measured ACEs within the ABCD Study. Findings revealed significant differences in how ACEs have been defined and measured within the ABCD Study (Aim 1). Additionally, researchers leverage a range of statistical methods to investigate the impact of ACEs on later developmental outcomes; however, there is a paucity of longitudinal research and studies past year two (Aim 2). Across all domains (e.g., mental and physical health, neuroimaging, cognitive, substance use, family, peer, and schooling), greater exposure to ACEs was associated with worse outcomes (Aim 3) and very few papers took a strengths-based lens to examine the interactions of ACEs and PCEs in shaping later outcomes (Aim 4). Several gaps and future directions for research are described below (Aim 5). These findings aim to shape future studies assessing ACEs within the ABCD sample by increasing standardization and accuracy of ACE measurements, thus allowing us to more effectively assess adversity exposure and aggregate study findings. Ultimately, this research can inform prevention and intervention development, as well as shape policy recommendations. 4.1. ACE measurement and other variations in study methodology As previously documented ( Breslin et al., 2025 ), ACEs measurements have not been standardized within the ABCD Study and researchers have used a breadth of measures (e.g., ACE events different items) reported by different individuals (e.g., self- vs. parent-report) to tap into ACE exposures. ABCD Study Consortium investigators have published guidelines on which available measures from the baseline appointment tap into the different ACE items ( Hoffman et al., 2019 ). Guidelines suggest the use of the Family Environment Scale (parent and youth report; Moos and Moos, 1976 ) and KSADS-5 PTSD module (parent-report; Kaufman et al., 2016 ) to measure physical abuse, the KSADS-5 PTSD module (parent-report; Kaufman et al., 2016 ) to measure sexual abuse and domestic violence, the Family History Assessment (parent-report; Rice et al., 1995 ) and Adult Self-report (parent-report; Achenbach et al., 2003 ) to measure household substance use and household mental illness, the Demographics Survey (parent-report; Barch et al., 2018 ) to measure parental separation/divorce, and the Family History Assessment (parent-report; Rice et al., 1995 ) to measure household criminality, the CRPBI Acceptance Subscale (youth-report; Schaefer, 1965 ) to measure emotional neglect, and Parental Monitoring (youth report; Chilcoat and Anthony, 1996 ; Karoly et al., 2016 ; Stattin and Kerr, 2000 ) and Demographics Surveys (parent-report; Barch et al., 2018 ) to measure physical neglect. Guidelines assert that there is no available measure for emotional abuse. While many studies (e.g., Al-shoaibi et al., 2024 ; Damme et al., 2024 ; Liu et al., 2025 ) utilized the measures above to assess ACEs, there is also a great deal of divergence from these recommendations. Several studies (e.g., Albertina et al., 2024 ; Barnhart et al., 2022 ; Johnson et al., 2023 ; McCarthy et al., 2023 ; Petti et al., 2025 ) exclusively utilized the PhenX Life Events Checklist ( Johnson, 1982 , Tiet et al., 1998 ), which assesses familial exposure to the criminal justice system, separation from a caregiver, parental divorce/separation, whether the youth was the victim of a crime or assault, and exposure to violence at school. However, this measure does not include many other ACE exposures that were also available through the study (e.g., sexual abuse, physical abuse). Further, while the measure assessed for child assault or abuse victimization, there is no differentiation in the type of abuse/assault and whether this happened within or outside the home, which has differential effects on child outcomes. Studies also included emotional abuse through measuring exposure to threats directed at the child (KSADS: “Family member or non-family member threatened to kill the child?”; Kaufman et al., 2016 ), thus, only capturing a limited type of emotional abuse. Additionally, several studies utilized the Family Conflict Scale ( Moos and Moos, 1976 , Zucker et al., 2018 ) to assess domestic violence while others used it to capture emotional abuse. These differences highlight the discordance in ACE measurement across studies using the ABCD data, which may impact our understanding of the way ACEs influence later outcomes. Additionally, some studies only considered caregiver substance misuse, mental illness, or engagement in the criminal justice system as an exposure, while others considered these events positive endorsements if displayed by anyone in the household. These measurements differences may contribute to discordance surrounding ACE prevalence rates across US youth. The majority of papers (18.9%) utilized a nine-event ACE assessment, including sexual and physical abuse, physical and emotional neglect, incarceration of a household member, household substance use, household violence, household mental illness, and divorce or separation. A large proportion of studies assessed eight events; however, there were three distinct versions of these assessments (e.g., differing across inclusion of unexpected family death, emotional neglect, and physical neglect). Ten studies assessed community-level ACEs, including discrimination, acculturation stress, neighborhood safety, and negative peer experiences. This expanded version of ACEs aligns with recommendations ( Bernard et al., 2020 , Cronholm et al., 2015 , Ellis and Dietz, 2017 , Zhen-Duan et al., 2023 ) to include a broader range of ACEs, capturing adverse events experienced by a diverse range of US youth. However, not all items used to assess community violence may be truly tapping into this construct. For example, assessing exposure through the PhenX Life Events Checklist items assessing if a child was a victim of a crime/violence/assault or saw a crime or accident may unintentionally capture other ACEs (e.g., sexual and physical abuse). The majority of studies included in the present review utilized data from the baseline appointment, with a large proportion also using year one and year two data. As such, findings largely represent the impact of ACEs on youth within early adolescence (i.e., ages 9–13). The majority of reviewed studies utilized a two-point approach to assess the longitudinal impact of ACE exposure (e.g, ACEs at baseline predicting mental health symptoms at year two). Of note, only one study ( Senger-Carpenter et al., 2025 ) included multiple measurements of adversity (e.g., early vs. recent) in its longitudinal analysis. The relative lack of research on ACEs across time in these studies may be due to the lack of a standardized ACE measure within the ABCD Study and differences in what measures are available at each time point. Although, this work begins to address the paucity of longitudinal research on the impact of ACEs on later outcomes, more work is needed to understand the chronicity and timing of ACEs through repeated measurements across childhood. Approximately 72% of studies used both parent and youth reporters to measure exposure to ACEs. The majority of these studies collapsed youth and parent reports such that a positive endorsement from either parent or child on an item was considered as an exposure to that adverse event. Future researchers should consider the advantages and disadvantages of this approach. In particular, we must weigh the utility of using parent reports as youth progress through adolescence, as parents may not be able to accurately report on their children’s experience (e.g., parents reporting the family environment may differ from the adolescent’s perception). 4.2. ACEs and health, developmental, and psychosocial outcomes The largest proportion of studies included in this review examined the association between ACEs and mental health outcomes. This research joins the wealth of existing work asserting the association between exposure to ACEs and greater mental health problems. ACEs were associated with suicide risk, which is one of the leading causes of death among adolescents ( Grossberg and Rice, 2023 ), as well as cybervictimization, mirroring previous work that found ACE exposure is linked to greater bullying victimization ( Miller et al., 2024 , Trompeter et al., 2024 ). ACEs were linked to specific mental health disorders and symptom clusters, including binge eating disorder ( Chu et al., 2022 ), anxiety, depression, withdrawal, aggression, attention problems, rule-breaking behaviors, social problems, somatic complaints, and thought problems ( Logan, Lewis-de Los Angeles, 2025 ). There is also a growing body of work within the ABCD Study finding that ACEs consistently predict PLEs ( Damme et al., 2024 , Karcher et al., 2020 , Petti et al., 2025 ). Following mental health outcomes, studies including physical health behaviors (e.g., physical activity, screentime) and outcomes (e.g., blood pressure, sleep duration) were the most common in the present review and contribute to the large body of prior work supporting the association between ACEs and physical health outcomes among adolescents ( Herzog and Schmahl, 2018 , Hughes et al., 2017 , Kalmakis and Chandler, 2015 , Monnat and Chandler, 2015 ). Findings in the included studies supporting the association between ACEs and substance use outcomes ( Johnson et al., 2023 , Nagata et al., 2023 , Rodrigues et al., 2025 ) are also consistent with previous research ( Crouch et al., 2018 , Dube et al., 2006 , Shin et al., 2018 ). Of note, the studies in the present review evaluated alcohol use expectancies ( Johnson et al., 2023 ), factors associated with risk of future alcohol, nicotine, and cannabis use (e.g., peer use; Rodrigues et al., 2025 ), and odds of sipping alcohol ( Nagata et al., 2023 ). No studies measured the consumption of full drinks, likely due to low substance use rates within early waves of the ABCD Study sample ( Lisdahl et al., 2021 ). In comparison to mental and physical health, research using neuroimaging methods to examine neural and cognitive development is underrepresented both within the studies included in this review and within the broader ACE literature (Albertina, 2024; Breslin et al., 2024 ; Damme, 2024; Stinson et al., 2024 ). Much of the existing literature is focused on individual ACEs, but the ABCD findings join several other studies emphasizing the association between cumulative ACE exposure and deleterious neurodevelopmental outcomes, including structural ( Buimer et al., 2022 , Luby et al., 2017 , Luby et al., 2019 ) and functional brain differences ( Woodley et al., 2025 ). While findings from two studies in the present review affirm the deleterious impact of ACEs on cognition, the review highlights a need for further research evaluating the association between ACEs and cognitive function, particularly in large prospective datasets. Two studies in the present review included outcomes related to family, neighborhood, and school functioning, finding that ACEs predict worse ethnic identity and family functioning but not neighborhood cohesion ( Garcia et al., 2025 ), and are associated with greater school disengagement and lower school involvement ( Niu et al., 2025 ). These findings highlight the importance of evaluating the impact of ACEs on ethnic identity, particularly when using inclusive ACE measures (e.g., assessing for discrimination). The relation between ethnic identity and ACEs is a relatively understudied area. Additionally, this study contributes to the wealth of research on ACEs and family functioning; however, researchers must consider the great deal of overlap between ACEs and family functioning since ACEs often occur in the home setting ( Scully et al., 2020 ). Garcia and colleagues somewhat address this concern through leveraging ABCD’s longitudinal data ( Garcia et al., 2025 ). Lastly, findings in the present review contribute to existing research linking ACEs to negative educational expectations among adolescents and lower school success ( Crouch et al., 2019 ). Although only a small subset of included studies examined protective factors, their findings underscore the importance of these factors in shaping adaptive developmental trajectories among children with histories of adversity. Identifying modifiable protective processes (e.g., emotion regulation, parent support, school involvement) at both neural and environmental levels may inform targeted prevention strategies aimed at strengthening resilience and reducing the burden of ACE-related challenges. 4.2.1. Limitations The present review is limited by its exclusion of studies that did not explicitly label their cumulative adversity indexes as ACEs. For example, they may not have used the terms “ACEs” or “adverse childhood experiences”, but they may have used other terminology (e.g., childhood adversity, stressful life events) to capture similar constructs. As such, we may be failing to consider other papers that meaningfully contribute to our understanding of ACEs within the ABCD Study. Additionally, we did not weight studies by sample size, methodological rigor, or completeness of ACE measurement. Further, while the ABCD Study sample is racially and ethnically diverse, it is not a nationally representative sample. As such, prevalence rates should not be interpreted as population-level estimates. Future reviewers should conduct formal meta-analysis and apply quality-rating frameworks. The reviewed articles also did not include any census-level data in their conceptualization of ACEs. The ABCD Study collects participant addresses and provides linked external data that allows researchers to use other indicators of adversity (e.g., Childhood Opportunity Index; Hoffman et al., 2019 ). As the ABCD Study offers the opportunity to measure ACEs at different levels of analysis, future researchers should consider including LED in their ACE measurements. 4.2.2. Summary of Recommendations Following the results from this review, future studies utilizing ABCD Study data should (1) prioritize the use recommended ways of measuring ACES when possible. Drawing on previous ABCD research, we have proposed an ACE definition and measurement system (see Fig. 7 , Fig. 8 ). This definition utilizes similar measurement systems to previous studies with an emphasis on items that explicitly measure whether an event happened during a child’s lifetime ( Breslin et al., 2025 , Hoffman et al., 2019 ). For example, this measurement system assesses whether a family member had a mental or emotional problem in a child’s lifetime through using the PhenX Life Events Scale, rather than the Family History Questionnaire, which is inclusive of the time before a child’s birth and may unintentionally capture events that the child was not exposed to. In addition to the core ACEs, we have drawn on the Pediatrics Adverse Childhood Experiences and Related Life Events Screener (PEARLS) to propose a list of expanded items, which includes additional system-level exposures ( Thakur et al., 2020 ). Previous ABCD papers have also effectively used the PEARLs to measure the impact of early life adversity ( Hunt et al., 2025 ). Researchers may consider using the expanded ACEs items depicted in Fig. 8 in addition to those shown in Fig. 7 if they are interested in evaluating adversity at across a range of contexts (e.g., neighborhoods, schools) and understanding broader forms of adversity (e.g., discrimination). Following these recommendations may ensure that future studies do not use measures that fail to tap into the construct that researchers are truly interested in. For example, utilizing the Family Conflict Scale (e.g., family members sometimes get so angry they throw things; family members sometimes hit each other”) may be assessing domestic violence or physical abuse, but it also may be capturing sibling conflict that does not reach the level of an adverse experience. Standardizing the items used to assess different ACE constructs will allow us to draw comparisons across studies using ABCD data to assess outcomes related to ACEs during adolescence and facilitate future meta-analyses. Of note, this measurement system is still limited by lack of consistent availability of each measure across study waves. Several of these exposures also have narrow definitions of adversity. For example, measuring emotional neglect through whether a child endorses that their parent “believes in showing their love for [them]” may fail to capture how parents provide emotional support across cultures ( Williams et al., 2024 ). Researchers should include this as limitation in future analyses. Fig. 7. Open in a new tab Recommended ACE items within the ABCD Study. Fig. 8. Open in a new tab Recommended ACE items within the ABCD Study- Expanded experiences. Additionally, (2) researchers should make use of longitudinal data as more time points of the ABCD Study are released, investigating predictive relations among variables and patterns of adversity exposure over time. Relatedly, researchers should seek to identify further methods of sequentially measuring ACE exposures to better understand the role of timing and chronicity of adversity exposure during adolescence. Next, (3) this review highlights a need to address the paucity of studies evaluating outcomes related to neuroimaging, cognitive development, substance use, family, neighborhood, and school functioning, thus representing a gap that should be filled by future research. As data from later timepoints is released, there will likely be more findings related to substance use as adolescents begin to engage in higher rates of use. Lastly, (4) future research should employ a strengths-based approach and seek to identify potential protective processes in the association between ACEs and later outcomes. It is imperative to understand what protective factors buffer the effects of ACEs, informing prevention and intervention strategies to promote positive outcomes across childhood and into adulthood. CRediT authorship contribution statement Yvette Rother: Writing – review & editing, Writing – original draft, Methodology, Conceptualization. Priscila Gonçalves: Writing – review & editing, Supervision, Conceptualization. Aren Tucker: Writing – review & editing, Writing – original draft, Formal analysis, Data curation. Kate Flory: Writing – review & editing, Supervision, Resources, Conceptualization. Andrew de Arellano: Writing – review & editing, Writing – original draft, Formal analysis, Data curation. Micah Johnson: Writing – review & editing. Ethan Hunt: Writing – review & editing. Abigail de Arellano: Writing – review & editing, Writing – original draft, Methodology, Formal analysis, Conceptualization. Hugh Garavan: Writing – review & editing. Alexandra Potter: Writing – review & editing. Matthew Albaugh: Writing – review & editing. Nicholas Allgaier: Writing – review & editing. Catharine Mann: Writing – review & editing, Writing – original draft, Formal analysis, Data curation. Lauren Butler: Writing – review & editing. Declaration of Competing Interest We have no competing interests to declare. Footnotes ☆ AA is supported by 7R25DA059073-03, T32GM145226, and Southern Regional Education Board AJT: T32GM145226 NA: 7R25DA059073, UVM ABCD U01: U01DA051039 ASP: 7R25DA059073, UVM ABCD U01: U01DA051039 MJ: 7R25DA059073, UVM ABCD U01: U01DA051039 PDG: K01DA057389; NARSAD/Brain Behavior Research Foundation Contributor Information Abigail de Arellano, Email: dearella@email.sc.edu. Aren Tucker, Email: ARENJT@email.sc.edu. Andrew de Arellano, Email: andrewd02@vt.edu. Yvette Rother, Email: YROTHER@email.sc.edu. Catharine Mann, Email: CAM73@email.sc.edu. Lauren Butler, Email: LVBUTLER@sc.edu. Matthew Albaugh, Email: matthew.albaugh@med.uvm.edu. Nicholas Allgaier, Email: nicholas.allgaier@uvm.edu. Hugh Garavan, Email: hugh.garavan@uvm.edu. Alexandra Potter, Email: alexandra.potter@uvm.edu. Micah Johnson, Email: micahjohnson@mednet.ucla.edu. Ethan Hunt, Email: ethan.t.hunt@uth.tmc.edu. Priscila Gonçalves, Email: priscila.dibgoncalves@nyspi.columbia.edu. 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