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. Author manuscript; available in PMC: 2026 Feb 11.
Published in final edited form as: Res Child Adolesc Psychopathol. 2025 Oct 30;53(12):2069–2085. doi: 10.1007/s10802-025-01386-y

The Longitudinal Effects of Exclusionary School Discipline on Adolescent Well-Being

Erin L Thompson 1, Sarah M Lehman 1,2, Ashley R Adams 1,2, Christine M Kaiver 1,2, Gabriella V Rizzo Scarfone 3, Angelica Gonzalez 1,2, Samuel W Hawes 1,2, Kristin M Scardamalia 4, Raul Gonzalez 1,2, Andy V Pham 5
PMCID: PMC12888457  NIHMSID: NIHMS2136045  PMID: 41166029

Abstract

Exclusionary school discipline practices (EDPs), such as school suspensions, are increasingly linked to poorer academic outcomes and increased contact with the legal system. However, the short-term effects of EDPs on other aspects of adolescent well-being, including mental health concerns and perceived unfair treatment, have received limited attention. Using five waves of data from the Adolescent Brain Cognitive DevelopmentSM Study® (n = 11,831, 48% female, 52% White, 15% Black, 19% Hispanic), the current study examined how EDPs predict changes in externalizing and internalizing symptoms as well as perceived unfair treatment by a teacher. After adjusting for baseline EDPs, externalizing concerns, and covariates, we found that EDPs reported at follow-up waves were associated with increased odds of youth- and caregiver-reported externalizing symptoms, youth-reported internalizing symptoms, and youth-reported perceived unfair treatment by a teacher at the subsequent wave. These associations were observed above and beyond each outcome’s predicted trajectory. However, baseline EDPs showed limited and inconsistent associations with overall symptom trajectories, suggesting that single time point EDP effects on adolescents’ overall trajectories may underestimate the cumulative impact of repeated discipline over time. This is particularly concerning given that most disciplined adolescents experienced repeated EDPs. Race and ethnicity did not consistently or robustly moderate these associations. Findings underscore the need for interventions that minimize the repeated use of exclusionary discipline.

Keywords: Adolescence, ABCD Study, School Discipline, Mental Health, Unfair Treatment

Cultivating safe school environments remains essential for healthy adolescent development. Although bullying and school violence has declined over the past 30 years, they remain persistent concerns (Wang et al., 2020), requiring ongoing prevention and intervention. In response to student misconduct, many schools rely on exclusionary disciplinary practices (EDPs), including detentions, suspensions, or expulsions. Nearly one-third of U.S. students experience EDPs during their K-12 education, with over 1.4 million suspensions each year (Shollenberger, 2015; U.S. Department of Education, 2023). EDPs are grounded in the belief that they (1) deter misconduct, (2) reduce classroom disruptions, and (3) prevent repeat offenses. Although such removals may yield short-term classroom benefits, a growing body of research suggests that EDPs have unintentional adverse consequences that limit their effectiveness (Duarte et al., 2022; Gerlinger et al., 2021; Noltemeyer et al., 2015; Welsh & Little, 2018a).

Although prior work has documented some of the long-term effects of EDPs on educational and health disparities, fewer studies have examined their short-term consequences during early- to mid-adolescence (ages 10-14), a critical developmental period. Adolescence is marked by rapid biological, psychological, and environmental change (Arain et al., 2013; Cicchetti & Rogosch, 2002). Neuromaturational imbalances between socioemotional reward systems (e.g., limbic structures) and cognitive control systems (e.g., prefrontal cortex) are thought to underlie increased risk-taking and emotional reactivity during adolescence (Arain et al., 2013). This period of development also coincides with the emergence of mood disruptions, conflict with caregivers, and externalizing behaviors (Cicchetti & Rogosch, 2002; Kieling et al., 2024). Contextually, early adolescence often involves transitioning to middle or junior high school, with more rigorous academic and behavioral expectations across multiple teachers (Eccles & Roeser, 2011). From a developmental perspective, normative adolescent behaviors may be misinterpreted as misconduct and disproportionately punished through EDPs, potentially contributing to the early onset and cumulative burden of mental health difficulties over the life course (Kieling et al., 2024).

Despite detailed national prevalence data (U.S. Department of Education’s Office for Civil Rights; 2023), less is known about how EDPs relate to individual outcomes in large, diverse adolescent samples. For example, Welsh and Little (2018a), in a systematic review, highlighted a lack of evidence on the short-term mechanisms by which EDPs contribute to long-term risks. Additionally, with growing calls for reform (Gregory et al., 2021), it is essential to continuously evaluate the consequences of EDPs. To address these gaps, the current study examined longitudinal associations between EDPs and key indicators of adolescent well-being, including externalizing and internalizing symptoms as well as perceived unfair treatment by a teacher, across four years of late childhood to early adolescence (ages 9–10 to ages 13–14) using data from the Adolescent Brain Cognitive DevelopmentSM (ABCD) Study®.

Emotional and Behavioral Concerns

Existing research on the effects of EDPs has focused primarily on academic outcomes (Noltemeyer et al., 2015; Welsh & Little, 2018a), with fewer studies examining their impact on adolescent behavioral concerns (Duarte et al., 2022). Although still emerging, evidence indicates that EDPs heighten risk for future disciplinary referrals (Gerlinger et al., 2021; Welsh & Little, 2018a), suggesting that EDPs may exacerbate, rather than merely reflect, problematic trajectories. For example, one study found that suspended youth were nearly three times more likely to be expelled and 40% more likely to be arrested within five years, even after accounting for similar background and behavioral characteristics (Rosenbaum, 2020). Mittleman (2018) similarly found that suspended students showed greater increases in behavioral concerns compared to matched peers.

Beyond externalizing symptoms, EDPs may also contribute to emotional distress, yet few studies have examined these links (for a review, see Duarte et al., 2023). Some evidence suggests that EDPs are concurrently associated with anger and depressive symptoms (Cottrell, 2018; Rushton et al., 2002). However, another study found no significant prospective associations (Cohen et al., 2023), suggesting that depression may be a pre-existing risk factor rather than a consequence. Additional work is needed to clarify whether EDPs contribute to changes in internalizing symptoms.

EDPs and Perceived Unfair Treatment

A deeper understanding of the consequences of EDPs remains a priority in the literature. Some have theorized that unsupervised time during out-of-school suspensions may increase exposure to peers with similar behavioral risks, reinforcing rather than deterring misconduct (Rosenbaum, 2020; Welsh & Little, 2018a). However, lack of supervision alone does not fully explain the link between EDPs and negative life outcomes (Cohen et al., 2023; Monahan et al., 2014; Noltemeyer et al., 2015; Smith et al., 2021). Increasingly, EDPs are conceptualized as social stressors that contribute to stigmatization, perceived unfair treatment, and deteriorating student-teacher relationships (Eyllon et al., 2022; Kennedy et al., 2019; Okonofua et al., 2016; Rosenbaum, 2020). Early adolescence is also a particularly salient period for examining perceived stigmatization, as youth begin to develop the cognitive capacity to detect and interpret social bias and unfair treatment, yet may lack the emotional regulation skills to effectively cope with these negative experiences (Brown & Bigler, 2005; Steinberg, 2005).

Despite strong theoretical support (e.g., social-identity threat), few studies have directly tested longitudinal associations between EDPs and perceived unfair treatment. Larson et al. (2019) found that greater racial disparities in school discipline predicted lower academic engagement for Black and White students, though they did not measure youth perceptions of unfair treatment directly. Assari and Zare (2024) observed concurrent associations between perceived unfair treatment and EDPs, whereas another study found that perceived unfair treatment by a teacher increased students’ odds of receiving EDPs one year later (Trovato & Zimmerman, 2024). However, we are not aware of any studies that have examined how EDPs influence changes in perceived unfair treatment over time, which have important implications for conceptualizing EDPs as stressful life events.

Racial Disparities in EDPs

Although overall EDP rates have declined, racial disparities persist (Welsh & Little, 2018b). Black students remain more than twice as likely as White students to experience EDPs, contributing to downstream disparities in educational, economic, and health-related outcomes (Duarte et al., 2023). Some studies also report disproportionate use of EDPs among Hispanic students (Peguero & Shekarkhar, 2011), though findings are less consistent than comparisons between Black and White youth (Welsh & Little, 2018b). Notably, these disparities have not been explained by behavior or family income differences but are instead linked to teacher-, school-, and broader contextual factors (Thompson et al., 2025; Welsh & Little, 2018b).

Given these inequities, as well as the potential connection between EDPs and perceived unfair treatment, EDPs’ adverse effects may be especially pronounced among Black and Hispanic adolescents. However, a meta-analysis found no racial or ethnic differences in the strength of the associations between EDPs and delinquency (Gerlinger et al., 2021). Similarly, Eyllon et al. (2022) reported no moderation by race-ethnicity within models examining discipline and depressive symptoms. These findings suggest that while emotional and behavioral responses to EDPs may be similar across subgroups, marginalized youth are disproportionality exposed. Yet, it remains unclear whether race-ethnicity moderates the associations between EDPs and other short-term outcomes, such as perceived unfair treatment.

Some research suggests that racial disparities in EDPs may be more pronounced among Black females, highlighting the importance of intersectionality in understanding adolescent experiences (Crenshaw et al., 2015). For example, Black girls represent 16% of the female student population but account for 55% of all out-of-school suspensions among girls (Inniss-Thompson, 2017). In contrast, Black boys comprise 15% of male students but receive 35% of male suspensions (U.S. Department of Education, 2023). Hispanic boys and girls also experience more EDPs than their White male peers (Peguero & Shekarkhar, 2011). While differences in prevalence rates in EDPs across race and sex subgroups are well documented, fewer studies have examined whether the effects of EDPs also vary by race and sex.

Current Study

EDPs are known to have cascading effects on academic performance and involvement in the legal system (Gerlinger et al., 2021; Noltemeyer et al., 2015; Welsh and Little, 2018), with growing interest in their impact on adolescent health (Duarte et al., 2023). The current study examined whether EDPs predicted changes in externalizing and internalizing symptoms, as well as changes in perceived unfair treatment by a teacher between ages 9-13 (Aim 1). We also explored whether these associations varied by race-ethnicity in the full sample and separately by sex (Aim 2). We hypothesized that EDPs would predict worse outcomes at the following wave, controlling for covariates, baseline EDPs, and each outcome’s overall trajectory. We considered our multiple group models examining subgroup differences in the effects of EDPs to be exploratory. The current study was not preregistered.

Methods

Sample

Data were drawn from the first five annual waves of data (T0-T4) from the Adolescent Brain Cognitive Development Study® (N = 11,868). Participants primarily between the ages of 9 and 10 (M = 9.71, SD = 0.51) were recruited between 2016 and 2018 across 21 sites within 17 U.S. states. Recruitment was primarily conducted through probability sampling of schools within the 21 catchment areas, stratified by sex, race, ethnicity, socioeconomic status, and urbanicity (Garavan et al., 2018). Less than 10% of the sample was recruited through additional means, including mailing lists, snowballing referrals, and summer programs (e.g., Boys and Girls clubs, summer meals programs). Of the total 11,868 participants, 4,050 (34.1%) were part of families with 2 or more participating siblings, resulting in 20.3% of families with multiple children in the study. Child assents and caregiver consents were collected at each wave.

Although the sample is broadly representative of U.S. 9- to 10-year-olds, participants were more likely to live in urban areas and have caregivers with higher income and education. More detailed information about the recruitment process and representativeness is available elsewhere (Garavan et al., 2018; Heeringa & Berglund, 2020). For the current study, 5.1 publicly available data was used (https://doi.org/10.15154/z563-zd24). The final analytic sample (n = 11,831) excluded 36 participants located at the 22nd site who were assessed only at the T0 wave as well as one participant missing their assessment date. Participants were assessed on an annual basis. Table 1 summarizes baseline characteristics and missingness.

Table 1. Participant Characteristics at Baseline (n = 11,831).

Total Sample Baseline School Discipline Group
Differences
by Discipline
Baseline Variables n (%) No
n (%)		 Yes
n (%)		 p
School Discipline
No 10,729 (90.69) -- -- --
Yes 1,086 (9.18) -- -- --
Missing 16 (0.14) -- -- --
Age .070
Mean (SD) 9.707 (0.51) 9.70 (0.61) 9.74 (0.60)
Missing 0 (0) -- --
Sex <.001
Female 5,655 (47.80) 5,345 (49.82) 302 (27.81)
Male 6,176 (52.20) 5,384 (50.18) 784 (72.19)
Missing 0 (0) -- --
Race-ethnicity < .001
Black 1,777 (15.02) 1,371 (12.80) 403 (37.14)
Multiracial Black 732 (6.19) 626 (5.84) 106 (9.77)
Hispanic 2,183 (18.45) 1,976 (18.44) 201 (18.53)
White 6,156 (52.03) 5,833 (54.44) 316 (29.12)
Other race(s)a 968 (8.18) 909 (8.48) 59 (5.44)
Missing 15 (0.13) -- --
School grade .286
3rd grade or below 2,101 (17.76) 1897 (17.68) 200 (18.42)
4th grade 5,396 (45.61) 4919 (45.85) 472 (43.46)
5th grade 3,971 (33.56) 3592 (33.48) 373 (34.35)
6th grade or above 361 (3.05) 320 (2.98) 41 (3.78)
Missing 2 (0.02) -- --
School type <.001
Charter 824 (6.96) 693 (6.46) 129 (11.89)
Private 594 (5.02) 549 (5.12) 45 (4.15)
Public 9,972 (84.29) 9,090 (94.79) 869 (80.09)
Other 430 (3.63) 388 (3.62) 42 (3.87)
Missing 11 (0.09) -- --
Caregiver education < .001
< High school diploma 603 (5.10) 495 (4.62) 107 (9.86)
High school diploma 1,438 (12.15) 1,190 (11.11) 242 (22.30)
Some college 3,477 (29.39) 3,032 (28.30) 441 (40.65)
Bachelor’s degree 3,319 (28.05) 3,127 (29.19) 191 (17.60)
Graduate degree 2,977 (25.16) 2,869 (26.78) 104 (9.59)
Missing 17 (0.14) -- --
Household income <.001
<$50,000 3,214 (27.17) 2,657 (26.93) 549 (58.65)
$50,000 to < $100,000 3,063 (25.89) 2,837 (28.75) 226 (24.15)
≥ $100,000 4,540 (38.37) 4,373 (44.32) 161 (17.20)
Missing 1,014 (8.57) -- --
One vs. Two Caregiver Households <.001
One 2,266 (19.15) 1,889 (17.77) 374 (35.28)
Two 9,440 (79.79) 8,743 (82.23) 686 (64.72)
Missing 125 (1.06) -- --
Child Opportunity Index <.001
Mean (SD) 60.06 (30.71) 62.06 (29.90) 39.64 (31.40)
Missing 1,092 (9.23) -- --
State-level racial attitudes <.001
Mean (SD) −0.18 (0.74) −0.20 (0.75) −0.02 (0.66)
Missing 3 (0.03) -- --
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Note. Missingness on baseline predictors is not cross-tabulated by school discipline status, as school discipline was missing for 16 participants, making group-level breakdowns of missingness ambiguous. M = Mean. SD = Standard Deviation. aThe “Other race(s)” category includes youth whose caregiver identified them as American Indian, Native American, Alaska Native, Native Hawaiian, Guamanian, Samoan, Other Pacific Islander, Asian Indian, Chinese, Filipino, Japanese, Korean, Vietnamese, Other Asian, Other Race, or as belonging to more than one race (excluding African American or Black youth).

Measures

EDPs

At each wave, youth were asked whether they had experienced a school detention or suspension in the past 12 months (yes/no).

Mental Health Symptoms

Externalizing and internalizing symptoms over the past seven days were assessed via youth and caregiver reports using the Brief Problem Monitor (BPM; Achenbach, McConaughy et al., 2011), which is a shortened version of the Child Behavior Checklist and Youth Self-Report. The seven-item externalizing subscale assesses behaviors related to aggression and rule-breaking, such as property destruction, disobedience, and threats towards others. The six-item internalizing subscale reflects symptoms of low self-worth, anxiety, and guilt. Response options were “Not True,” “Somewhat True,” and “Very True.” For the current study, mean subscale scores were computed. Caregiver reports were collected at all waves, whereas youth reports began at T1, resulting in 5 waves of data for caregiver data and 4 waves of youth data. Internal consistency was acceptable across waves for caregiver reports (externalizing symptoms α = .78-.80; internalizing symptoms α = .75-,78), and somewhat lower for youth reports (externalizing symptoms α = .56- .67, internalizing symptoms α = .67-.71). Each measure was zero–inflated, with 26%–42% of respondents reporting no symptoms at the first wave (T0 for caregivers and T1 for youth).

Perceived Unfair Treatment

Youth completed the Measure of Perceived Discrimination (Phinney et al., 1998). The current study focused on a single item assessing how frequently participants perceived unfair or negative treatment from teachers based on their ethnic background. Response items included Almost Never, Rarely, Sometimes, Often, and Very Often. The item does not specify a timeframe, although earlier items ask about experiences in the past 12 months. Responses were positively skewed, with 84%–90% reporting almost never perceiving unfair treatment across waves. Youth reported on perceived unfair treatment by a teacher at T1, T2, and T4.

Covariates

Models included both time-invariant (T0) and time-varying (T1-T3) covariates.

Baseline Demographics.

Time-invariant controls included T0 caregiver reports of sex (male/female), age in years, school grade, caregiver education, household income, and presence of a secondary caregiver (yes/no). Based on prior research examining the disproportionality of EDPs across subgroups (Thompson et al., 2025; Welsh & Little, 2018b), we also controlled for race and ethnicity using the following racial-ethnic categories based on T0 caregiver-reports: non-Hispanic/non-multiracial White youth, non-Hispanic/non-multiracial Black youth, Black youth identified as multiracial and/or Hispanic; non-Black Hispanic youth, and youth whose caregivers identified them as another race or races. Race and ethnicity were conceptualized as social and political constructs relevant to better understanding disparities in developmental outcomes.

Baseline Externalizing Symptoms from Another Reporter.

To further adjust for baseline behavior, models of youth-reported outcomes controlled for caregiver-reported externalizing symptoms at T0 via the BPM, and models of caregiver-reported outcomes controlled for the six-item BPM T0 teacher-reported externalizing symptoms. The teacher-reported externalizing subscale used the same items as the caregiver-reported subscale excluding an item related to assessing disobedience at home. Response options were the same: “Not True,” “Somewhat True,” and “Very True.” Internal consistency was good (α = .85-.88),

Baseline Place-Based Characteristics.

We included a state-level composite score of attitudes towards Black people (Hatzenbuehler et al., 2022), which compiled 31 items from various polling data between 1975 and 2014. Items assessed general attitudes toward Black people, the existence of racial prejudice, the impact of discrimination, and endorsement of racial stereotypes. The factor score showed high reliability (α = .87) and has been previously linked to health disparities (Hatzenbuehler et al., 2022) and differential EDP risk (Thompson et al., 2025).

We also controlled for participants’ score on the Child Opportunity Index (COI; Acevedo-Garcia et al., 2020), a multidimensional measure based on 29 neighborhood indicators relevant to child development, derived from 2010-2015 US census tract data. COI scores rank neighborhoods into 100 percentile groups, each representing 1% of the US child population. For the current study, we linked COI scores using participants’ zip codes at baseline.

Type of School.

Caregivers reported on the type of school participants attended at each wave. Options included public school, private school, charter school, and other types of schools including homeschooling. Prior work using the ABCD Study sample has shown that attending a charter school is associated with increased likelihood of EDPs (Thompson et al., 2025). We accounted for school type at T0-T3.

Assessment Timing.

Across the five waves, participants were assessed between September 1, 2016 and January 15, 2022. Starting in the third wave, assessments occurred at varying times relative to the COVID-19 pandemic, with data collection at each wave spanning two years. Therefore, to adjust for pandemic-related disruptions, we included a time-varying COVID-19 variable at T2 and T3 indicating the timing of EDP assessment in 6-month intervals beginning in March 2020 (i.e., pre-March 2020; March-August 2020; September 2020-February 2021; March-August 2021; and September 2021-January 2022).

Analytic Strategy

Data cleaning and missing data procedures were conducted using RStudio (Version 2023.09.1+949; Posit Team, 2023). Most T0 variables had less than 2% missing data, except household income (9%), neighborhood resources (9%), and teacher-reported externalizing symptoms (58%). Missingness on teacher-reported externalizing symptoms significantly differed by site, ranging from 91% at one site to 23% at another. Prior work using the ABCD Study sample (Feldstein Ewing et al., 2022) has shown that although formal withdrawal from the ABCD Study has been quite low across time (<5%), attrition has increased (5%, 8%, and 13% for T1-T3), Feldstein Ewing and colleagues (2022) showed that caregiver education and race-ethnicity were the strongest predictors of missed visits. Notably, only half of the sample had completed T4 by the time the 5.1 ABCD Study dataset was made publicly available. We addressed missingness across all waves using the multivariate imputation by chained equations package for hierarchical data in R (20 iterations; van Buuren, 2018), accounting for nesting within families but not sites due to complexities of three-level models (Audigier et al., 2018). Despite high missingness in some cases, multiple imputation has been shown to reduce bias relative to complete case analysis (Lee & Huber, 2021) and is recommended even in cases with 50% or more missingness (Li et al., 2025).

We then used Mplus Version 8.6 (Muthén & Muthén, 2017) for all subsequent analyses. To account for clustering within families and across sites, we specified stratification and cluster variables and used a sandwich estimator to compute robust standard errors that adjusted for stratification and non-independence. We used semicontinuous latent growth curve models (Olsen & Schafer, 2001) to examine linear trajectories of five outcomes: youth- and caregiver-reported externalizing and internalizing symptoms, and youth-reported perceived unfair treatment. The two-part model separated the likelihood of (a) having any symptoms (binary component) from (b) the severity or frequency of symptoms among those with symptoms (continuous component, log-transformed). This approach was selected to account for the large proportion of youth and caregivers who reported no symptoms, resulting in zero-inflated distributions. Based on recommendations by Muthén and Muthén (2017), we fixed the binary intercept and slope covariances to zero to stabilize the estimations.

We then examined whether prior EDPs predicted changes in mental health symptoms and perceived unfair treatment, accounting for covariates (Aim 1). Primary results are presented in three parts. First, we report unconditional trajectory models estimating change over time in the (a) presence (binary component) and (b) severity (continuous component) of symptoms prior to adding covariates. Youth-reported outcomes were modeled from T1 to T4, while caregiver-reported outcomes spanned T0 to T4. Second, we assessed whether T0 EDPs predicted the intercept and slope of these trajectories, reflecting the effect of early discipline exposure on initial symptom levels (intercept) and rates of change over time (slope) for both the binary and continuous trajectory models, accounting for covariates in the model. Third, consistent with Liu’s (2024) decomposition strategy, we tested whether EDPs at T1–T3 predicted the subsequent binary and continuous outcome indicators, accounting for covariates and overall symptom trajectories. To isolate the unique impact of later EDPs, we modeled T0 EDPs as a time-invariant predictor and T1-T3 EDPs as time-varying predictors. This allowed us to evaluate whether follow-up EDPs were associated with time-specific residual variance in the next wave’s outcomes, above and beyond the growth trajectory, early EDP exposure, and other covariates.

Final results are reported as odds ratios (ORs) and percent change in odds for the binary component (i.e., growth in the likelihood of reporting any symptoms over time) and exp(B) for the continuous component, reflecting percent change in symptom levels among those reporting symptoms (Olsen & Schafer, 2001). Figure 1 presents a conceptual diagram of the semicontinuous model for caregiver-reported externalizing concerns, illustrating the inclusion of both time-invariant and time-varying covariates. To evaluate whether EDP effects varied by wave, we also applied equality constraints to the T1-T3 EDP paths using the Likelihood Ratio Test (LRT) and the adjusted Bayesian Information Criterion (aBIC; Yang & Yang, 2007). Notably, we included externalizing symptoms reported by another reporter only at baseline rather than as a time-varying covariate, as these symptoms may serve as a mediator between EDPs and outcomes, potentially obscuring the effects of EDPs.

Figure 1. Conceptual Diagram of the Semi-Continuous Growth Curve Model for Caregiver-Reported Externalizing Symptoms.

Figure 1.

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Note. Although presented as a single figure for clarity, this conceptual model represents two parallel models: one for the binary component (presence/absence of symptoms) and one for the continuous component (severity/frequency among those with symptoms). Similar models were run for caregiver-reported internalizing symptoms, as well as youth-reported mental health symptoms and perceived unfair treatment by a teacher. Ext = Externalizing Symptoms. T= Time.

We then conducted multiple group models to test subgroup differences in the effects of EDPs on each outcome across race-ethnicity, controlling for covariates (Aim 2). Using model constraints, we tested whether the associations between EDPs and outcomes differed for White versus Black adolescents, multiracial Black adolescents, and Hispanic adolescents within three separate analyses using: (a) the full sample, (b) the male subsample, and (c) the female subsample. Individual Wald tests were conducted using the Model Constraint command in Mplus to evaluate group differences in the regression coefficients representing the effects of EDPs on the outcome indicators in both the binary and continuous components of the trajectory models.

After selecting the best-fitting model for each outcome, we applied the Benjamini-Hochberg (BH) procedure (Benjamini & Hochberg, 1995) to control for the false discovery rate (FDR) at α = .05 for our primary analyses examining the effects of EDPs on mental health symptoms and perceived unfair treatment (Aim 1). We did not apply the FDR correction to our Aim 2 moderation analyses. Despite the large overall sample (n = 11,831), the subgroup sizes were very unbalanced (White: 51%, Black: 15%, multiracial Black: 6%, and Hispanic: 19%), which limits statistical power and results in larger standard errors and reduced sensitivity to detect group differences (Aiken & West, 1991). Applying FDR correction would have further constrained the ability to identify meaningful patterns in these underrepresented groups. Nonetheless, these results are considered exploratory.

Given the large amount of missingness for the teacher-reported externalizing concerns covariate, we also conducted sensitivity analyses with two alternative specifications: (1) excluding externalizing concerns by another reporter as a time-invariant covariate, and (2) controlling for youth-reported externalizing symptoms at the Year 1 follow-up (T1) instead of using teacher-reports. Notably, youth-reports were not available at baseline. In the latter model, we shifted the intercept of the caregiver-reported externalizing outcome to T1 to align with the timing of the youth-reported covariate. Finally, to address potential pandemic-related bias, we also re-ran analyses using only the subsample of youth assessed prior to March 1, 2020.

Results

Preliminary Analyses

Table 1 presents baseline characteristics for the full sample and separately by T0 EDP status. Using independent t-tests and chi-square tests, we found that youth who reported T0 school discipline at baseline significantly differed by race/ethnicity, school type, caregiver education, household income, caregiver household status (one vs. two caregivers), neighborhood resources, and state-level racial attitudes (ps < .001). Age and grade did not significantly differ by discipline status at baseline.

To assess the likelihood of repeated disciplinary exposure, we examined patterns of repeated of EDPs across waves. Among youth who experienced an EDP at T0, 65% reported additional EDPs over the next three years. Additionally, 42%-48% of youth who reported an EDP at one wave also reported an EDP at the subsequent wave.

We also examined whether EDP prevalence varied by assessment timing relative to the COVID-19 pandemic. EDP rates at T2 and T3 significantly differed depending on when youth were assessed relative to the pandemic onset (T2: χ2[3, N = 10,896] = 33.10; T3: χ2[4, N = 10,223] = 169.08; ps < .001). At both time points, youth assessed 6 to 18 months post-onset of the pandemic were significantly less likely to report EDPs in the past year compared to those assessed pre-pandemic or within the first 6 months post-onset. Rates then appeared to increase slightly among youth assessed 18-24 months after the pandemic began. See Table S1 for detailed prevalence rates by COVID-19 timing group.

Model Comparisons and Main Effects (Aim 1)

Across all outcomes, both the LRT and aBIC favored the constrained models, indicating that the association between prior EDPs and subsequent symptoms was consistent across waves (see Table S2). For example, the regression coefficient for T1 EDPs predicting T2 caregiver-reported externalizing symptoms was constrained to equal those for T2 to T3 and T3 to T4 associations, after adjusting for covariates and symptom trajectories. Table 2 presents the full sample results. Figures 2 and 3 illustrate the cumulative effect of repeated school discipline, comparing symptom trajectories for youth who were never disciplined (grey line) versus those disciplined at every wave (black line). Tables S3-S7 provide covariate effects.

Table 2. Two-Part (Semi-Continuous) Model Results for Externalizing, Internalizing, and Unfair Treatment Outcomes.

Binary Component: Absence vs. Presence of Symptoms/Outcome
Rate of Change in Outcome
(Unconditional Model)		 Baseline Discipline → Intercept
of the Trajectory		 Baseline Discipline → Slope of
the Trajectory		 Follow-Up Discipline → Next
Wave Outcome Indicator
Outcome OR (95% CI) BH-
adjusted p 		OR (95% CI) BH-
adjusted p 		OR (95% CI) BH-
adjusted p 		OR (95% CI) BH-
adjusted p
YR-Ext 1.07 (1.02,1.13) .012 1.58 (1.33,1.88) <.001 0.95 (0.87,1.05) .411 1.72 (1.53,1.94) <.001
CR-Ext 0.94 (0.90,0.97) <.001 1.41 (1.21,1.65) <.001 0.94 (0.89,0.99) .038 1.48 (1.35,1.62) <.001
YR-Int 1.12 (1.07,1.17) <.001 1.22 (1.05,1.40) .018 0.98 (0.90,1.06) .698 1.11 (1.02,1.21) .038
CR-Int 0.98 (0.94,1.02) .320 1.01 (0.88,1.16) .990 1.01 (0.96,1.06) .964 1.03 (0.94,1.12) .651
YR-Unfair 1.11 (0.95,1.29) .290 1.51 (1.23,1.84) <.001 0.82 (0.70,0.97) .038 1.39 (1.17,1.65) .001
Continuous Component: Severity of Symptoms/Frequency of Outcome
Rate of Change in Outcome
(Unconditional Model)		 Baseline Discipline → Intercept
of the Trajectory		 Baseline Discipline → Slope of
the Trajectory		 Follow-Up Discipline → Next
Wave Outcome Indicator
Outcome exp(B) (95% CI) BH-
adjusted p 		exp(B) (95% CI) BH-
adjusted p 		exp(B) (95% CI) BH-
adjusted p 		exp(B) (95% CI) BH-
adjusted p
YR-Ext 1.02 (1.00,1.04) .042 1.20 (1.14,1.26) <.001 0.98 (0.95,1.00) .078 1.05 (1.03,1.08) <.001
CR-Ext 0.96 (0.96,0.97) <.001 1.16 (1.10,1.22) <.001 0.98 (0.96,1.00) .038 1.05 (1.02,1.08) .003
YR-Int 1.07 (1.06,1.09) <.001 1.14 (1.08,1.20) <.001 0.97 (0.94,1.00) .038 1.00 (0.97,1.03) .988
CR-Int 1.01 (1.00,1.01) .217 0.98 (0.93,1.03) .538 1.00 (0.98,1.02) .969 1.02 (0.99,1.05) .240
YR-Unfair 0.97 (0.95,0.99) .003 1.00 (0.94,1.06) .978 1.00 (0.96,1.05) .970 1.01 (0.93,1.09) .958
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Note. n = 11,831. The binary component of the two-part (semi-continuous) model was estimated using logistic regression. Odds ratios (ORs) reflect the change in odds of exhibiting any mental health symptoms or perceived unfair treatment. The continuous component modeled the log-transformed outcome; exponentiated coefficients (exp(β)) represent the multiplicative change in symptom severity/frequency (e.g., exp(B) of 1.05 indicates a 5% increase in symptom severity, not odds). Due to rounding, some confidence intervals include 1.00 despite being statistically significant. CI = Confidence Interval. BH = Benjamini-Hochberg procedure. YR-Ext = Youth-reported externalizing symptoms. CR-Ext = Caregiver-reported externalizing symptoms. YR-Int = Youth-reported internalizing symptoms. CR-Int = Caregiver-reported internalizing symptoms. YR-Unfair = Youth-reported perceived unfair treatment by a teacher.

Figure 2. Cumulative Effects of Repeated School Discipline on the Presence and Severity of Mental Health Concerns: Two-Part Model Results.

Figure 2.

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Note. Predicted trajectories are based on weighted averages across sex and race, with continuous covariates centered, representing the typical trajectory for an average youth in the sample by discipline status. T = Timepoint.

Figure 3. Cumulative Effects of Repeated School Discipline on the Presence and Frequency of Youth-Reported Perceived Unfair Treatment by a Teacher: Two-Part Model Results.

Figure 3.

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Note. Predicted trajectories are based on weighted averages across sex and race, with continuous covariates centered, representing the typical trajectory for an average youth in the sample by discipline status. T = Timepoint.

Aim 1: Externalizing Symptoms

Unconditional Model

Absence Versus Presence of Symptoms.

Prior to adding covariates, youth showed 7% increased odds of reporting any externalizing symptoms (versus no symptoms) per wave (OR = 1.07, 95% CI [1.02, 1.13], BH-adjusted p = .012). In contrast, caregivers showed 6% decreased odds of reporting adolescent externalizing symptoms per wave (OR = 0.94, 95% CI [0.90, 0.97], BH-adjusted p < .001).

Severity of Symptoms.

Among youth who reported any externalizing symptoms, frequencies increased by approximately 2% per wave (exp(B) = 1.02, 95% CI [1.00, 1.04], BH-adjusted p = .042). In contrast, caregiver-reported externalizing symptom frequencies decreased by approximately 4% per wave (exp(B) = 0.96, 95% CI [0.96, 0.97], BH-adjusted p < .001).

T0 EDPs Predicting Intercept and Slope

Absence Versus Presence of Symptoms.

After adjusting for covariates, T0 EDPs were associated with 58% increased odds of initial youth-reported externalizing symptoms versus no symptoms (OR = 1.58, 95% CI [1.38, 1.88], BH-adjusted p < .001) and 41% increased odds of initial caregiver-reported externalizing symptom versus no symptoms (OR = 1.41, 95% CI [1.21, 1.65], BH-adjusted p < .001).

Over time, the odds of any caregiver-reported externalizing symptoms decreased 6% faster for youth with reported EDPs compared to youth who did not report EDPs at T0 (OR = 0.94, 95% CI [0.89, 0.99], BH-adjusted p = .038). However, T0 EDPs were not significantly associated with changes in youth-reported externalizing symptoms over time.

Severity of Symptoms.

Among those with externalizing symptoms, T0 EDPs were associated with 20% greater severity in initial youth-reported symptoms (exp(B) = 1.20, 95% CI [1.14, 1.26], BH-adjusted p < .001) and 16% greater severity in initial caregiver-reported symptoms (exp(B) = 1.16, 95% CI [1.10, 1.22], BH-adjusted p < .001) at the initial wave.

T0 EDPs were also associated with a slightly steeper decline (2%) in caregiver-reported externalizing symptoms over time (exp(B) = 0.98, 95% CI [0.96, 1.00], BH-adjusted p = .038) but did not significantly predict changes in severity of youth-reported externalizing symptoms.

Follow-up EDPs Predicting Subsequent Outcome Indicators

Absence Versus Presence of Symptoms.

Follow-up EDPs were associated with 72% higher odds of youth-reported externalizing symptoms (OR = 1.72, 95% CI [1.53, 1.94], BH-adjusted p < .001) and 48% higher odds of caregiver-reported externalizing symptoms (OR = 1.48, 95% CI [1.35, 1.62], BH-adjusted p < .001) at the next wave. These effects were above what would be expected based on the externalizing trajectory and after controlling for covariates, including T0 EDPs and T0 externalizing symptoms reported by another reporter (i.e., caregiver or teacher).

Severity of Symptoms.

After accounting for T0 EDPs, covariates, and the overall externalizing trajectory, EDPs at a follow-up wave were associated with 5% higher odds of greater severity in both youth-reported (exp(B) = 1.05, 95% CI [1.03, 1.08], BH-adjusted p < .001) and caregiver-reported externalizing symptoms (exp(B) = 1.05, 95% CI [1.02, 1.08], BH-adjusted p = .003) at the next wave.

Aim 1: Internalizing Symptoms

Unconditional Model

Absence Versus Presence of Symptoms.

Prior to adding covariates, youth showed 12% increased odds in reporting any internalizing symptoms (versus no symptoms) per wave (OR = 1.12, 95% CI [1.07, 1.17], BH-adjusted p < .001). In contrast, the odds of caregiver-reported internalizing symptoms were stable across time (i.e., non-significant slope).

Severity of Symptoms.

The severity in youth-reported internalizing symptoms increased by approximately 7% per wave (exp(B) = 1.07, 95% CI [1.06, 1.09], BH-adjusted p < .001). In contrast, the severity in caregiver-reported internalizing symptoms were stable across time.

T0 EDPs Predicting Intercept and Slope

Absence Versus Presence of Symptoms.

After adjusting for covariates, T0 EDPs were associated with 22% increased odds in initial youth-reported internalizing symptoms versus no symptoms (OR = 1.22, 95% CI [1.05, 1.40], BH-adjusted p = .018) but did not predict the odds of initial caregiver-reported symptoms versus no symptoms. T0 EDPs did not predict changes in the trajectory of youth- or caregiver-reported internalizing symptoms (versus no symptoms).

Severity of Symptoms.

After accounting for T0 discipline and covariates, EDPs at a follow-up wave were associated with 14% higher odds of greater severity in youth-reported internalizing symptoms at the initial wave (exp(B) = 1.14, 95% CI [1.08, 1.20], BH-adjusted p < .001) and resulted in a 3% slower incline in youth-reported symptoms over time (exp(B) = 0.97, 95% CI [0.94, 1.00], BH-adjusted p = .038). T0 EDPs did not predict the continuous intercept or slope within the caregiver-reported model.

EDPs as a Time-Varying Predictor

Absence Versus Presence of Symptoms.

After accounting for T0 EDPs and covariates, EDPs at a follow-up wave were associated with 11% higher odds of youth-reported internalizing symptoms (versus no symptoms) at the next wave, above and beyond what would be expected based on the individual trajectory (OR = 1.11, 95% CI [1.02, 1.21], BH-adjusted p = .038). EDPs at follow-up waves did not significantly predict the odds of caregiver-reported internalizing symptoms at the next wave, accounting for covariates and the overall trajectory.

Severity of Symptoms.

After accounting for T0 EDPs and covariates, follow-up EDPs were not associated with changes in the severity in youth- or caregiver-reported internalizing symptoms at the next wave, above and beyond what the trajectory and covariates predicted.

Aim 1: Perceived Unfair Treatment by a Teacher

Unconditional Model

Absence Versus Presence of Perceived Unfair Treatment.

Within the binary component of the unconditional model, the slope was not significant, suggesting stability in the odds of youth reporting any perceived unfair treatment by a teacher over time.

Severity of Perceived Unfair Treatment.

The continuous component of the unconditional model included a nonsignificant slope, indicating stability in the frequency of perceived unfair treatment by a teacher over time.

T0 EDPs Predicting Intercept and Slope

Absence Versus Presence of Perceived Unfair Treatment.

T0 EDPs were associated with 51% higher odds of youth reporting any unfair treatment by a teacher at T1 versus no perceived unfair treatment (OR = 1.51, 95% CI [1.23, 1.84], BH-adjusted p < .001) but were also associated with an 18% steeper decline in the odds of unfair treatment over time (OR = 0.82, 95% CI [0.70, 0.97], BH-adjusted p = .038).

Severity of Perceived Unfair Treatment.

EDPs at T0 did not significantly predict the intercept or slope of the frequency of perceived unfair treatment by a teacher.

EDPs as a Time-Varying Predictor

Absence Versus Presence of Perceived Unfair Treatment.

EDPs at a follow-up wave were associated with 39% higher odds of reporting unfair treatment by a teacher (versus no unfair treatment) at the next wave, above and beyond what would be expected based on the individual trajectory and covariates (OR = 1.39, 95% CI [1.17, 1.65], BH-adjusted p = .001).

Severity of Perceived Unfair Treatment.

EDPs at a follow-up wave were not associated with changes in the severity in perceived unfair treatment by a teacher at the next wave, above and beyond what the trajectory and covariates would predict.

Aim 2: Moderation Analyses

We conducted multiple group analyses to examine whether the effects of EDPs differed (1) by race-ethnicity and (2) by race-ethnicity separately for males and females. Within the full sample, follow-up EDPs were more strongly associated with caregiver-reported externalizing symptoms (versus no symptoms) among White youth (OR = 1.67, 95% CI = 1.43-1.94; p <.001) than Black youth (OR = 1.24, 95% CI = 1.04-1.48; p = .016). This difference was statistically significant (Wald test p = .012). When examined separately by sex, significant associations emerged only among White girls compared to Black and multiracial Black girls (Wald test ps = .007 and .047, respectively). White girls who received follow-up EDPs had 97% increased odds of caregiver-reported externalizing symptoms versus no symptoms at the next wave (OR = 1.97, 95% CI = 1.51-2.57, p < .001), compared to a non-significant change for Black (OR = 1.19, 95% CI = 0.91-1.55, p = .207) and multiracial Black girls (OR = 1.17, 95% CI = 0.74-1.85; p = .509).

We also found significant differences in the associations between EDPs and caregiver-reported internalizing symptoms (Wald test p = .032) and youth-reported internalizing symptoms (Wald test p = .035). More specifically, among White girls, follow-up EDPs were more strongly associated with caregiver-reported internalizing concerns versus no symptoms (OR = 1.76, 95% CI = 1.01-1.76, p = .039) compared to non-significant changes among Black girls (OR = 0.88, 95% CI = 0.67-1.16, p = .377, Wald test p = .032). Follow-up EDPs were also more strongly associated with increased severity of youth-reported internalizing concerns (exp(B) = 1.10, 95% CI = 1.01-1.20, p = .037) compared to non-significant changes among Black girls (exp(B) = 0.95, 95% CI = 0.86-1.05, p = .316). No significant moderation effects were found for perceived unfair treatment by a teacher. Results are provided in Table S8-S10.

Sensitivity Analyses

Due to substantial missingness on the teacher-reported covariate, we re-ran models predicting caregiver-reported mental health symptoms using two alternative covariate specifications: (1) excluding T0 teacher-reported externalizing concerns, and (2) controlling for T1 youth-reported externalizing symptoms instead. The effect of follow-up school discipline on subsequent caregiver-reported symptom presence was strongest when no externalizing covariate was included and was attenuated but highly similar when controlling for either youth- or teacher-reported externalizing symptoms (i.e., EDPs predicting subsequent caregiver-reported externalizing symptoms ORs = 1.74, 150, and 1.48, respectively, all ps < .001). These results suggest that the high level of missingness in the teacher-reported variable did not substantially alter the findings. More detailed results are presented in Table S11.

Finally, to address potential pandemic-related bias, we re-ran analyses using only the subsample of youth assessed before March 1, 2020. A two-part growth curve model for caregiver-reported externalizing symptoms across Wave T0–T2 (n = 7,824) showed consistent results: baseline EDPs were associated with faster declines in symptom presence (p = .018), and follow-up EDPs were associated with increases in symptom presence and severity (ps < .007; Table S12). Comparable analyses could not be conducted for youth-reported outcomes, as these were not available at T0, and at least three waves are required to estimate growth trajectories.

Discussion

Using the large, diverse ABCD Study sample, we examined whether EDPs, including school detentions and suspensions, predicted short-term changes in externalizing and internalizing symptoms, as well as perceived unfair treatment by a teacher, across four years of late childhood to early adolescence. We found initially conflicting results when comparing EDPs as time-invariant (baseline) versus time-varying (multiple follow-up) predictors. However, overall findings point to cumulative, adverse effects of repeated EDPs on adolescent mental health and perceived unfair treatment, highlighting the importance of tracking EDPs over time.

EDPs as a Time-Invariant Versus Time-Varying Predictor

Similar to Liu’s (2024) decomposition approach, we modeled baseline EDPs as time-invariant (predicting the intercept and slope of each trajectory) and later EDPs as time-varying to disentangle their effects. While baseline EDPs predicted worse initial outcomes, they were at times associated with improvement in symptom trajectories over time (e.g., steeper decline in caregiver-reported externalizing symptoms). In contrast, follow-up EDPs predicted increased symptoms and perceived unfair treatment at the next wave, beyond what was expected based on prior trends, baseline EDPs, and covariates.

Several explanations may underlie this pattern. One possibility is that a single infraction corresponds to elevated short-term concerns but may contribute to symptom declines over time, consistent with EDPs functioning as corrective interventions. Alternatively, these patterns may reflect regression to the mean (Barnett et al., 2005), such that youth who experience an infraction initially exhibit worse outcomes but eventually converge with their peers over time. However, these explanations do not account for the relatively consistent negative effects of later EDPs.

We propose a third explanation: although experiencing EDPs at one wave may not negatively alter an adolescent’s overall trajectory, EDPs may have cumulative effects. This interpretation is supported by our time-varying findings, which showed that EDPs predicted elevated symptoms at subsequent waves even after accounting for baseline effects. Descriptive analyses showed that 65% of adolescents with baseline EDPs received additional EDPs, and almost half of those disciplined were disciplined again the following year. As such, youth with repeated EDPs were more likely to experience worsening symptoms and were more likely to perceive unfair treatment during the study period. As illustrated in our figures, these results suggest that the negative effects of EDPs may not manifest immediately but accumulate as adolescents receive additional EDPs over time, which is consistent with prior research showing that school suspensions compound risk over time (Mittleman, 2018). Targeted interventions for previously disciplined youth (along with staff who work with them) may help reduce the likelihood of future infractions and associated mental health consequences.

EDPs and Externalizing Concerns

Consistent with prior research (Gerlinger et al., 2021; Welsh & Little, 2018), EDPs were associated with higher odds and severity of externalizing symptoms, above and beyond the overall trajectories, baseline EDPs, and adolescent characteristics. Although the wave-to-wave effects were modest (e.g., 5% increases in severity), such increases could elevate risk for further EDPs, creating a feedback loop of worsening behavior and repeated discipline.

We also observed differences across reporters: youth-reported symptoms increased over time, whereas caregiver-reported symptoms declined. This is consistent with established discrepancies in multi-informant reports (De Los Reyes & Kazdin, 2005) and may reflect contextual changes, such as more behavior occurring outside of caregivers’ observation. Notably, internal consistency was higher for caregiver-reported symptoms than for youth-reported symptoms, although reliability for youth-reported externalizing symptom increased over time. This trend may reflect developmental gains in self-awareness and increased variability in self-reported symptoms as youth age. Additionally, follow-up EDPs predicted greater odds of youth-reported externalizing symptoms (72%) compared to caregiver-reported symptoms (48%). These differences may reflect stronger within-reporter associations or the possibility that EDPs are more closely tied to behavioral concerns that arise outside the home, such as in school. Nonetheless, the consistent effects across informants reinforce the robustness of the discipline to behavior changes relationship.

EDPs and Internalizing Symptoms

Youth who received EDPs at baseline reported higher initial internalizing concerns, whereas baseline EDPs were not associated with changes in adolescents’ trajectory over time. However, follow-up EDPs increased the likelihood (but not severity) of internalizing symptoms at the next wave. Notably, among youth with no EDPs, symptom severity increased over time; among those with EDPs, severity remained stable, resulting in similar levels of internalizing symptoms by the study’s end. The functional implications of elevated internalizing presence without increased severity remain unclear. Drawing on the Pathologic Adaptation Model (Gaylord-Harden et al., 2017), adolescents exposed to repeated stressors such as EDPs may become emotionally desensitized, leading to a plateau in internalizing symptoms while externalizing symptoms continue to escalate. However, further research is needed to test this hypothesis.

In contrast, EDPs were unrelated to caregiver-reported internalizing concerns, and caregiver-reported trajectories remained flat. These discrepancies may reflect limited caregiver awareness of internalizing symptoms (De Los Reyes & Kazdin, 2005), or misattribution of internalizing signs (e.g., irritability) as externalizing behavior (Humphreys et al., 2020). These findings underscore the importance of using multi-informant assessments to fully capture adolescents’ mental health status.

EDPs and Perceived Unfair Treatment

Although theory suggests that EDPs contribute to perceived unfair treatment (Eyllon et al., 2022; Kennedy et al., 2019; Okonofua et al., 2016), longitudinal evidence remains scarce. We found that baseline EDPs were associated with higher odds in reporting perceived unfair treatment at the next wave (i.e., the starting time point for reports of unfair treatment) but a steeper decline in the likelihood of perceived unfair treatment over time (via the overall trajectory). This aligns with our other findings: initial disruption, followed by a potential reduction. However, EDPs at follow-up waves predicted increased odds of reporting any unfair treatment at the next wave, accounting for covariates. These effects occurred within the binary but not continuous models, suggesting that EDPs may trigger whether adolescents perceive and experience unfair treatment rather than its frequency. Findings suggest that disciplined students may increasingly perceive interactions with teachers as unfair and biased, reinforcing a cycle of mistrust and social-emotional harm. Notably however, the ABCD Study does not include a timeframe for reporting perceived unfair treatment by a teacher, which may have played a role in the flat trajectories over time.

Subgroup Differences

We found limited evidence for racial-ethnic differences in the effects of EDPs, consistent with prior research (Eyllon et al., 2022; Gerlinger et al., 2021). Some exploratory patterns suggested that White females may be especially vulnerable to adverse effects of EDPs. Although they are less frequently disciplined than Black females, a disparity that cannot be explained by behavior (Thompson et al., 2025; Welsh & Little, 2018b), White girls may perceive EDPs as more stigmatizing (though not necessarily more unfair). This could produce more elevated internalizing concerns. Moreover, caregivers of White girls may interpret EDPs as more atypical and respond with heightened concern, contributing to greater reports of externalizing symptoms. While intriguing, these findings should be interpreted cautiously due to their exploratory nature. Replication and deeper investigation into mechanisms, such as family responses, are warranted. Nonetheless, despite some variation in the strength of these associations across subgroups, disciplined adolescents are ultimately more likely to experience negative consequences, underscoring the heightened vulnerability of youth at greater risk of receiving punishment regardless of behavior.

Future work

There are several promising avenues for additional research. First, future work should examine whether short-term effects of EDPs on externalizing symptoms, internalizing symptoms, and perceived unfair treatment help explain links to longer-term outcomes, including educational attainment, justice system involvement, and financial stability (Mittleman, 2018; Rosenbaum, 2020). According to Okonofua et al. (2016), perceived unfair treatment can trigger social-identity threat, fostering expectations of rejection that intensify distress, defiance, and aggression. When students view discipline as unfair or discriminatory, these experiences may compound developmental risk, reinforcing a cycle of misbehavior and punishment that could undermine positive development across the lifespan. Although the current study focused on ethnicity-related unfair treatment by a teacher, future studies may consider perceived unfair treatment due to other sociodemographic characteristics. Although the ABCD Study asks about unfair treatment due to skin color, country of origin, weight, sexual identity, and disability status, these items do not identify the potential perpetrator.

Importantly, the processes examined in the current study are also likely to be bidirectional. Increases in externalizing symptoms or perceptions of unfair treatment may, in turn, heighten the risk for future disciplinary action, creating a feedback loop (Mittleman, 2018). Understanding this dynamic interplay over time is critical for identifying intervention points that may disrupt these escalating cycles. These potential mediating and reciprocal pathways could be evaluated in the ABCD Study in the future as participants transition into later adolescence and beyond.

Our findings should be interpreted in the context of early adolescence, a period marked by heightened sensitivity to social cues, growing autonomy, and increasing awareness of fairness and identity (Brown & Bigler, 2005; Eccles & Roeser, 2011; Steinberg, 2005). These developmental factors may amplify the impact of EDPs on both behavioral outcomes and perceptions of unfair treatment. Thus, additional research should examine the effects of EDPs on outcomes at both younger and older ages when our outcome trajectories could take on other shapes (e.g., quadratic).

Future work should also examine school-level characteristics as potential moderators. Disciplined students may be more likely to report unfair treatment or engage in rule-breaking behaviors if (1) they attend a school with a high EDP rate and thus perceive peer discipline as unjust, or conversely, (2) they feel singled out in schools with lower EDP rates. Additionally, while our moderation analyses were exploratory, some patterns suggested that White female adolescents who received EDPs had higher odds of subsequent externalizing and internalizing symptoms compared to Black female adolescents. However, replication of these findings is needed prior to further interpretation of these findings. Finally, although other potential confounders (e.g., indicators of socioeconomic status, neighborhood resources) were included in the analyses, these same factors may also influence the strength of the observed associations. Future studies should explore whether other developmental or contextual characteristics intensify or mitigate the effects of EDPs on adolescent development.

Limitations

There are some limitations that warrant discussion. First, due to the observational design, unmeasured risk factors (e.g., behavioral or academic difficulties prior to ages 9 and 10) may influence both EDP exposure and later outcomes, making it difficult to isolate the unique impact of EDPs. Although we controlled for covariates, baseline externalizing symptoms, and outcome trajectories, we cannot draw causal conclusions. Additionally, because participants from the ABCD Study sample have relatively high levels of caregiver education and family income, our findings may not fully generalize to more socioeconomically disadvantaged populations. Caregiver education has also been shown to be a significant predictor of attrition within the ABCD Study (Feldstein Ewing et al., 2022). Although the use of multiple imputation is a strength of the study (Li et al., 2025), missingness may have affected our results. Nonetheless, our findings, alongside prior work (Mittleman, 2018; Okonofua et al., 2016; Rosenbaum, 2020; Welsh & Little, et al., 2018a) suggest that repeated use of EDPs are unlikely to serve as turning points toward positive outcomes. Instead, EDPs likely reinforce and exacerbate existing challenges.

The measurement of EDPs is also a limitation. In the ABCD Study, detentions and suspensions are combined into a single binary item, preventing us from distinguishing discipline types or frequency. An ABCD substudy (Brislin et al., 2024) separated these at five sites, but small subgroup sizes limit meaningful comparisons (e.g., only 21 youth reported a suspension without a detention at Wave 1). The ABCD Study also does not ask adolescents whether they perceived EDPs as unfair, nor does the measure of unfair treatment specify the nature or context of the experiences. Thus, it is unclear whether reports of unfair treatment are specifically related to disciplinary actions or reflect broader perceptions of the school environment.

Finally, the COVID-19 pandemic began during ABCD Study data collection. Due to site-level variation in start dates, each wave spanned a two-year window in which adolescents could have been assessed either before or after the onset of the pandemic. Although we accounted for this by controlling for 6-month assessment periods beginning in March 2020, we could not fully capture all pandemic-related disruptions to adolescents’ school and home environments. Preliminary analyses indicated that adolescents assessed 6-24 months after the pandemic onset were less likely to report EDPs. Nonetheless, model fit comparisons supported constraining the effects of EDPs across waves. Overall, the impact of EDPs on outcomes appeared consistent over time, even if likelihood of receiving EDPs was lower during certain periods. This pattern is conceptually similar to our findings on race-ethnicity. Although Black youth are more likely to receive EDPs (Fadus et al., 2021; Thompson et al., 2025; Welsh & Little, 2018b), the effects of EDPs on outcomes did not consistently differ by race, suggesting that differences in exposure do not necessarily reflect differences in effect. Additionally, sensitivity analyses restricted to youth assessed pre-pandemic yielded similar results to our full sample model.

Conclusion

The current study examined how EDPs predict externalizing and internalizing symptoms, as well as youth-reported unfair treatment by a teacher over four years of early adolescence. Baseline EDPs were associated with worse initial levels of most outcomes but generally converged toward the trajectories of non-disciplined youth over time. In contrast, follow-up EDPs showed more consistent associations with worse outcomes. There was little evidence that race or ethnicity robustly moderated these effects. Overall, our results highlight the cumulative nature of EDP exposure. Future work should examine whether these short-term consequences mediate the broader educational health, and economic disparities linked to school discipline.

Supplementary Material

Thompson et al., 2025 Supplementary Material

Funding:

Data used in the preparation of this article were obtained from the Adolescent Brain Cognitive DevelopmentSM (ABCD) Study (https://abcdstudy.org), held in the NIMH Data Archive (NDA). This is a multisite, longitudinal study designed to recruit more than 10,000 children ages 9-10 and follow them over 10 years into early adulthood. The ABCD Study® is supported by the National Institutes of Health and additional federal partners under award numbers U01DA041048, U01DA050989, U01DA051016, U01DA041022, U01DA051018, U01DA051037, U01DA050987, U01DA041174, U01DA041106, U01DA041117, U01DA041028, U01DA041134, U01DA050988, U01DA051039, U01DA041156, U01DA041025, U01DA041120, U01DA051038, U01DA041148, U01DA041093, U01DA041089, U24DA041123, U24DA041147. A full list of supporters is available at https://abcdstudy.org/federal-partners.html. A listing of participating sites and a complete listing of the study investigators can be found at https://abcdstudy.org/consortium_members/. ABCD consortium investigators designed and implemented the study and/or provided data but did not necessarily participate in the analysis or writing of this report. This manuscript reflects the views of the authors and may not reflect the opinions or views of the NIH or ABCD consortium investigators. The ABCD data repository grows and changes over time. The ABCD data used in this report came from [NIMH Data Archive Digital Object Identifier (http://dx.doi.org/10.15154/z563-zd24)].

Research reported in this publication was supported by the National Institute on Minority Health and Health Disparities of the National Institutes of Health under Award Number K01MD018069. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Footnotes

Ethical Approval: Given the use of publicly available secondary data, the current study did not meet the definition of human subject research. Therefore, IRB approval was not required.

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