Postmilitary Adjustment to Civilian Life: Potential Risks and Protective Factors
Bibliographic record
Abstract
BACKGROUND: Adjustment to civilian life in Canadian veterans after release from military service has not been well studied. OBJECTIVES: The objectives of this study were: (1) to explore dimensions of postmilitary adjustment to civilian life and (2) to identify demographic and military service characteristics associated with difficult adjustment. DESIGN: Data were analyzed from a national sample of 3,154 veterans released from the regular Canadian Forces during 1998 to 2007 in a cross-sectional survey conducted in 2010 called the Survey on Transition to Civilian Life. METHODS: The prevalence of difficult adjustment to civilian life for selected characteristics was analyzed descriptively, and confidence intervals were calculated at the 95% level. Multivariable logistic regression analysis was used to identify characteristics available at the time of release that were associated with difficult adjustment. RESULTS: The prevalence of difficult adjustment to civilian life was 25%. Statistically significant differences were found across indicators of health, disability, and determinants of health. In multivariable regression, lower rank and medical, involuntary, mid-career, and Army release were associated with difficult adjustment, whereas sex, marital status, and number of deployments were not. LIMITATIONS: Findings cannot be generalized to all veterans because many characteristics were self-reported, important characteristics may have been omitted, and causality and association among health, disability, and determinants of health characteristics could not be determined. CONCLUSIONS: Postmilitary adjustment to civilian life appears to be multidimensional, suggesting the need for multidisciplinary collaboration between physical therapists and other service providers to mitigate difficult transition. Potential risk and protective factors were identified that can inform interventions, outreach strategies, and screening activities, as well as further research.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".