The relationship between non-consensual sex and risk of depression in female undergraduate students at universities in Maritime Canada
Bibliographic record
Abstract
Introduction Sexual victimization and depression are common on university campuses, especially among females, and both are associated with negative health outcomes. Most studies of relationships between non-consensual sex and depression have used broad definitions of victimization and/or have controlled poorly for confounding. Objectives This study examines whether there is an independent association between non-consensual sex and current risk of depression after controlling for related factors. Aims To better inform university health services about the psychological sequelae of non-consensual sex. Methods Cross-sectional data collected online from female students younger than age 30 at eight universities in Maritime Canada were analyzed. Non-consensual sex while at university was measured using one dichotomous item and risk of depression was measured using the Center for Epidemiologic Studies Depression (CES-D) Scale. All analyses were weighted and data were imputed using the Sequential Regression Multivariate Imputation (SRMI) Method. Analyses involved basic descriptive statistics, a series of unadjusted logistic regressions, and an adjusted multiple logistic regression. Results In total, 36.7% of students were at risk of depression and 6.8% had been victims of non-consensual sex while attending university. After adjusting for covariates and confounders, females who had been victimized were 2.11 times more likely to be at risk of depression than females who had not been victimized ( P Conclusions This study points to the need for more mental health support for victims of sexual victimization and more efforts to prevent sexual violence. These findings can be used to help inform university mental health services and health promotion activities.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".