Syndemic Factors and Lifetime Bidirectional Intimate Partner Violence Among Gay, Bisexual, and Other Sexual Minority Men
Bibliographic record
Abstract
Purpose:Bidirectional intimate partner violence (IPV), the reporting of both IPV victimization and perpetration, is likely the most common form of violence among gay, bisexual, and other sexual minority men (GBM) and is thought to be part of a larger syndemic of stressors. This purpose of this study was to examine associations between syndemic factors and lifetime bidirectional IPV among GBM in three Canadian cities to inform future interventions. Methods:Data from GBM (N = 2449) were used to fit three logistic regression models with lifetime bidirectional IPV as the outcome and four syndemic factors (i.e., depressive symptomatology, childhood sexual abuse [CSA], illegal drug use, and alcohol misuse) as independent variables. Model 1 examined syndemic factors individually. Model 2 employed a summative scale of syndemic exposure. Model 3 used marginal analysis to examine the relative excess risk of each potential iteration of the syndemic. Results:Thirty-one percent (N = 762) of respondents reported lifetime bidirectional IPV. Each of the syndemic factors were significantly associated with greater odds of reporting bidirectional IPV (Model 1). Model 2 exhibited a dose–response relationship between the number of syndemic factors reported and bidirectional IPV. Model 3 suggested that the specific combination of depressive symptomatology, CSA, and alcohol misuse resulted in the highest risk of lifetime bidirectional IPV. Conclusion:Bidirectional IPV was common in this sample and was associated with a complex interplay of stressors. However, there may be opportunities to target interventions to the specific syndemic issues in an effort to prevent and mitigate this form of IPV in GBM.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 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) | 0.002 | 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".