Protective Factors for Mental Disorders Among Survivors of Military Sexual Trauma: A Canadian Population-Based Study: Facteurs de protection relatifs à l’apparition de troubles mentaux chez les survivantes et survivants de traumatismes sexuels liés au service militaire : une étude basée sur la population canadienne
Bibliographic record
Abstract
OBJECTIVES: Military sexual trauma (MST) is a prevalent issue among actively serving members and Veterans, and is associated with adverse health outcomes including mental disorders. This study sought to identify correlates and protective factors for the development of mental disorders among Canadian MST survivors. METHODS: = 455; 9.6%). A semi-structured diagnostic interview assessed MST and mental disorders in accordance with DSM-IV criteria. Multivariable logistic regressions examined associations between sample characteristics (2002 and 2018) and psychosocial factors (at baseline [i.e., 2002] and 2018) and any mental disorder since 2002. Analyses were run among the full subsample of MST survivors and additionally stratified by sex, when possible. RESULTS: Among MST survivors, 66.5% had a mental disorder since 2002. Among the total sample, those who were officers (odds ratio [OR] = 0.58) or on active duty (OR = 0.52) had reduced odds of any mental disorder since 2002. In addition, less frequent use of avoidance coping in 2002 and 2018 (adjusted odds ratio [AOR]: 0.86, 0.64), more frequent use of active coping in 2018 (AOR = 0.64), less frequent use of self-medication coping in 2018 (AOR = 0.79), greater perceived social support in 2018 (AOR = 0.94), and reduced work stress across various domains in 2018 (AOR: 0.67-0.87) were associated with reduced odds of any mental disorder since 2002. Some variability emerged according to sex (e.g., types of work stress or coping emerging as protective). CONCLUSIONS: Results highlight certain sample characteristics and psychosocial factors that illustrated a protective relationship with mental disorders among MST survivors. Findings may inform targeted intervention strategies that could help mitigate adverse mental health impacts of MST.
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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 | 0.002 | 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".