Violence exposure is associated with adolescents' same‐ and next‐day mental health symptoms
Bibliographic record
Abstract
BACKGROUND: Young people exposed to violence are at increased risk for mental health and behavioral problems. However, very little is known about the immediate, or same-day, associations between violence exposure and adolescents' mental health symptoms or whether daily symptom or behavioral reactivity marks future problems. METHODS: Young adolescents were assessed three times a day for 30 consecutive days using mobile-phone-based Ecological Momentary Assessment (EMA) (N = 151 adolescents). Over 12,500 assessments and 4,329 person days were obtained via the EMA. Adolescents were recruited from low-income neighborhoods based on parent-reported risk for externalizing symptoms. Mental health symptoms were assessed via parent and child report at baseline, multiple times per day via EMA assessments of the adolescents, and again 18 months later when 93% of the adolescents were reinterviewed. RESULTS: Results from multilevel models illustrated that young adolescents were more likely to experience symptoms of anger (OR = 1.74, CI: 1.31-2.30), depression (OR = 1.66, CI: 1.26-2.19), and conduct problems (OR = 2.63, CI: 1.71-4.04) on days that they were exposed versus not exposed to violence. Increases in depressive symptoms were also observed on days following violence exposure (OR = 1.46, CI: 1.09-1.97). Adolescents with the highest levels of violence exposure across the 30-day EMA were less behaviorally reactive to violence exposures in daily life, and heightened behavioral reactivity predicted increased risk for substance use across early adolescence. CONCLUSIONS: Findings support the need to focus on both the immediate and long-term associations between violence exposure and adolescents' mental health and behavior. Results also suggest that heightened behavioral reactivity during early adolescence may signal emerging substance use problems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".