Cumulative lifetime violence severity, social determinants and anxiety in a national sample of Canadian men
Bibliographic record
Abstract
BACKGROUND: Despite anxiety disorders being the ninth leading cause of disability and associated with social inequities, little attention has been given to how intersections among social determinants of health and chronic stressors such as cumulative lifetime violence affect the likelihood of experiencing anxiety disorders. Our purpose was to explore the relationships among cumulative lifetime violence severity as target and perpetrator, social determinants of health and generalized anxiety disorder in Canadian men. METHODS: Using a community sample of 592 Canadian men who self-identified as having experienced violence, we developed and tested an evidence-based model of generalized anxiety disorder including indicators of cumulative lifetime violence, gender, social location, socio-economic disparity, personal resources and other chronic stressors using logistic regression. RESULTS: (8) = 264.43, p = .000). The prevalence of probable generalized anxiety disorder was 30.9%, a rate higher than that found among Canadian men in general in the same period. Remarkably, the likelihood of generalized anxiety disorder increased by a factor of 5.30 for each increase of 1 in cumulative lifetime violence severity, and six-fold for feeling overwhelmed by demands of everyday life (aOR = 6.26). Masculine discrepancy stress, having been born in Canada, unemployment, and food insecurity also contributed significantly to increasing the likelihood of generalized anxiety disorder. Both social support and mastery had significant aORs < 1, suggesting possible protective effects. Together these findings delineate characteristics and social determinants that may heighten vulnerability to generalized anxiety disorder and influence its progression among men who have experienced lifetime violence. CONCLUSIONS: These findings are the first evidence that Canadian men with lifetime violence histories are a sub-group disproportionately affected by chronic stressors and socio-economic disparities and that together the presence and/or severity of these factors increases their vulnerability to generalized anxiety disorder. Our results highlight the importance of strengths-based trauma- and violence-informed approaches to care, including practical resources to reduce the stress of everyday life, improve social support, and reinforce personal control and choice.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| 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".