Health status among women and men in Canada who reported experiences of non-physical intimate partner violence
Bibliographic record
Abstract
Introduction: Intimate Partner Violence (IPV) is recognized as a public health problem that has profound negative consequences for physical and mental health and well-being. Previous research has focused primarily on physical and sexual IPV; non-physical IPV has been understudied, particularly among men. Methods: Using data from Statistic Canada's 2018 Survey of Safety in Public and Private Spaces, we examined associations between non-physical IPV and nine heath status variables: fair/poor mental health, fair/poor general health, dissatisfaction with life, pain, use of medication, suicidal thoughts, mood disorder, anxiety disorder, and PTSD. Results: Women (13.3 %) and men (12.6 %) were equally likely to report non-physical IPV in the past year, often without co-occurring physical/sexual IPV. Bivariate analyses revealed that non-physical IPV increased the risk of reporting all negative health status variables except pain. When associations were examined in relation to the frequency of non-physical IPV, a gradient was observed. In multivariable analyses that controlled for potential confounders, most associations observed in the bivariate analyses persisted, but associations were somewhat attenuated when controlling for co-occurring physical/sexual IPV. Conclusions: Non-physical IPV, particularly if it happens frequently, is strongly associated with negative health, often independent of co-occurring physical/sexual IPV. Longitudinal studies have found that non-physical IPV is a predictor of subsequent physical/sexual IPV, further increasing the risk of negative health. This underscores the importance of specifically addressing non-physical IPV through public health prevention programs and the need for it to be recognized as a form of IPV that is as important as physical and sexual IPV.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".