From Military to Civilian Primary Care: A Study of Veteran Transition
Bibliographic record
Abstract
Background: Military-to-civilian transition (MCT) is generally understood as the process of leaving military service and transitioning to civilian life. Each year, approximately 5000 Regular Force Canadian Armed Forces (CAF) members leave the military. During service, CAF members access the military health care system and, after release, must transition to provincial/territorial primary care. Since Veterans experience health problems at greater proportions and use primary care more than the general population, this is an important aspect of MCT. However, no research has investigated Canadian Veterans’ experience of transitioning from the military to the civilian primary care system or how primary care is provided to Veterans. Objectives: To understand the transition from the military to the civilian primary care system and to understand how interprofessional primary care is provided to Veterans in the civilian system. Methods: Three studies were conducted to address these objectives. First, a phenomenological analysis of previously collected qualitative data from CAF members with an upcoming release. Second, a phenomenological study conducted with Veterans after release. Third, a single mixed-methods exploratory case study focusing on how team-based primary care is provided to Veterans. Results: The transition to civilian primary care encompasses anticipation of and preparation for the change in primary care provider (PCP) before the release date, making the leap from military to civilian primary care in the months and years that follow the release date, and eventual landing in the care of a primary care team in the civilian system. Many participants were able to make the transition to civilian primary care with relative ease. However, for those with ongoing health issues requiring consistent access to care, the transition was challenging and had implications for health and well-being. The interprofessional primary care team examined in the case study revealed the importance of Veteran-friendly and culturally competent primary care. Conclusion: The transition to civilian primary care, like MCT more broadly, is complex and variable; continuous access to primary care throughout the transition is important. More research is needed to better understand this underexplored aspect of MCT to better serve transitioning Veterans in the future.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.014 | 0.005 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".