Impulsivity as a mechanism linking child abuse and neglect with substance use in adolescence and adulthood
Bibliographic record
Abstract
Emerging developmental perspectives suggest that adverse rearing environments promote neurocognitive adaptations that heighten impulsivity and increase vulnerability to risky behavior. Although studies document links between harsh rearing environments and impulsive behavior on substance use, the developmental hypothesis that impulsivity acts as mechanism linking adverse rearing environments to downstream substance use remains to be investigated. The present study investigated the role of impulsivity in linking child abuse and neglect with adult substance use using data from (a) a longitudinal sample of youth (Study 1, N = 9,421) and (b) a cross-sectional sample of adults (Study 2, N = 1,011). In Study 1, the links between child abuse and neglect and young adult smoking and marijuana use were mediated by increases in adolescent impulsivity. In Study 2, indirect links between child abuse and neglect and substance use were evidenced via delayed reward discounting and impulsivity traits. Among impulsivity subcomponents, robust indirect effects connecting childhood experiences to cigarette use emerged for negative urgency. Negative urgency, positive urgency, and sensation seeking mediated the effect of child abuse and neglect on cannabis and alcohol use. Results suggest that child abuse and neglect increases risk for substance use in part, due to effects on impulsivity. Individuals with adverse childhood experiences may benefit from substance use preventive intervention programs that target impulsive behaviors.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".