Associations between childhood adversity, adult stressful life events, and past-year drug use disorders in the National Epidemiological Study of Alcohol and Related Conditions (NESARC).
Bibliographic record
Abstract
Stress sensitization, whereby CA lowers tolerance to later stressors, has been proposed as a potential mechanism explaining the association between exposure to childhood adversities (CA) and drug use disorders in adulthood. However, this mechanism remains untested. This paper begins to address this gap through exploring associations between CA exposure and stressful events in adulthood for predicting drug use disorders. We used data drawn from Wave 2 of the U.S. National Epidemiological Survey of Alcohol and Related Conditions (n = 34,653) to explore whether the association between past-year stressful life events and the 12-month prevalence of disordered cannabis, stimulant, and opiate use varied by the number of types of CA that an individual was exposed to. Past-year stressful life events were associated with an increased risk of cannabis, stimulant, and opiate use disorders among men and women. Exposure to CA was associated with increased risk for disordered cannabis use among men and women and opiate use among men only. Finally, we found significant associations between exposure to CA and past-year stressful life events in predicting disordered drug use, but only for women in relation to disordered stimulant and opiate use. Findings are suggestive of possible stress sensitization effects in predicting disordered stimulant and opiate use among women. Implications of these findings for the prevention and treatment of drug use disorders and for future research are discussed.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".