Military to civilian transition challenges, caregiving activities, and well-being among spouses of newly released Canadian Armed Forces Veterans
Bibliographic record
Abstract
Introduction: Transition to civilian life may not only be highly challenging for service members, but also for their spouses, especially following a medical release. Often, the families of ill or injured service members must confront unexpected responsibilities related to caring for the member, while having to adjust to civilian life. This study was conducted to examine military to civilian transition challenges and engagement in caregiving among spouses of newly released Canadian Armed Forces (CAF) Veterans and their associations with spousal well-being. Methods: The Canadian Armed Forces Transition and Well-Being Survey (CAFTWS) was administered to spouses of CAF Veterans released in 2016 ( N = 595). The survey assessed spouses’ experiences with a range of military to civilian transition challenges and engagement in caregiving, as well as various indicators of their well-being (e.g., daily stress and psychological distress). Regression analyses were conducted to assess the associations of transition challenges and caregiving with well-being. Results: Results revealed that challenges related to finding educational opportunities and health care providers, and loss of military identity, as well as more frequent engagement in caregiving, were significantly associated with elevated levels of daily stress and psychological distress among spouses of Veterans. Discussion: This study is among the first to examine transition experiences, caregiving and well-being in a representative sample of Veterans’ spouses. Findings outline key challenges experienced and underline important predictors of well-being. Recommendations on services that could help facilitate or improve the experiences of families during the transition process are discussed.
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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 | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".