The impact of childhood emotional abuse on violence among people who inject drugs
Bibliographic record
Abstract
INTRODUCTION AND AIMS: Childhood emotional abuse is a known risk factor for various poor social and health outcomes. While people who inject drugs (IDU) report high levels of violence, in addition to high rates of childhood maltreatment, the relationship between childhood emotional abuse and later life violence within this population has not been examined. DESIGN AND METHODS: Cross-sectional data were derived from an open prospective cohort of IDU in Vancouver, Canada. Childhood emotional abuse was measured using the Childhood Trauma Questionnaire. We used multivariate logistic regression to examine potential associations between childhood emotional abuse and being a recent victim or perpetrator of violence. RESULTS: Between December 2005 and May 2013, 1437 IDU were eligible for inclusion in this analysis, including 465 (32.4%) women. In total, 689 (48.0%) reported moderate to severe history of childhood emotional abuse, whereas 333 (23.2%) reported being a recent victim of violence and 173 (12.0%) reported being a recent perpetrator of violence. In multivariate analysis, being a victim of violence (adjusted odds ratio = 1.49, 95% confidence interval 1.15-1.94) and being a perpetrator of violence (adjusted odds ratio = 1.58, 95% confidence interval 1.12-2.24) remained independently associated with childhood emotional abuse. DISCUSSION AND CONCLUSIONS: We found high rates of childhood emotional abuse and subsequent adult violence among this sample of IDU. Emotional abuse was associated with both victimisation and perpetration of violence. These findings highlight the need for policies and programmes that address both child abuse and historical emotional abuse among adult IDU.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".