Psychedelic use and intimate partner violence: The role of emotion regulation
Bibliographic record
Abstract
BACKGROUND: Recent evidence suggests that psychedelic use predicts reduced perpetration of intimate partner violence among men involved in the criminal justice system. However, the extent to which this association generalizes to community samples has not been examined, and potential mechanisms underlying this association have not been directly explored. AIMS: The present study examined the association between lifetime psychedelic use and intimate partner violence among a community sample of men and women. The study also tested the extent to which the associations were mediated by improved emotion regulation. METHODS: We surveyed 1266 community members aged 16-70 (mean age=22.78, standard deviation =7.71) using an online questionnaire that queried substance use, emotional regulation, and intimate partner violence. Respondents were coded as psychedelic users if they reported one or more instance of using lysergic acid diethylamide and/or psilocybin mushrooms in their lifetime. Results/outcomes: Males reporting any experience using lysergic acid diethylamide and/or psilocybin mushrooms had decreased odds of perpetrating physical violence against their current partner (odds ratio=0.42, p<0.05). Furthermore, our analyses revealed that male psychedelic users reported better emotion regulation when compared to males with no history of psychedelic use. Better emotion regulation mediated the relationship between psychedelic use and lower perpetration of intimate partner violence. This relationship did not extend to females within our sample. CONCLUSIONS/INTERPRETATION: These findings extend prior research showing a negative relationship between psychedelic use and intimate partner violence, and highlight the potential role of emotion regulation in this association.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".