Intimate Partner Violence in the Canadian Armed Forces: Psychological Distress and the Role of Individual Factors Among Military Spouses
Bibliographic record
Abstract
Unique military demands can have a significant impact upon family life. Although most Canadian Armed Forces (CAF) families are able to cope effectively with the stressors of military life, some may experience marital conflicts, contributing to spousal violence. Moreover, there is evidence that certain personal resources can buffer the impact of spousal violence on psychological distress. The present study examined the roles of spousal violence and personal resources, including coping, mastery, and social support, in the psychological distress of CAF members' spouses (N = 1,892). Hierarchical regression analyses showed that violence significantly predicted psychological distress among spouses of CAF members; although physical violence was no longer significant, emotional violence remained a unique predictor. Coping, mastery, and perceived social support, entered together, significantly predicted psychological distress among spouses, over and above the role of violence. Specifically, emotion-focused coping, mastery, and social support remained unique predictors of distress. Furthermore, perceived social support buffered the negative impact of emotional violence on psychological distress. The study has important organizational implications, illuminating the risks related to the spousal violence in the military and the psychological consequences of such violence. These results can be used to improve treatment and prevention programs, enhancing the well-being of military families.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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; both teacher heads agree on what is shown here.
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".