Identifying military family cultural competencies: experiences of military and Veteran families in Canadian health care
Bibliographic record
Abstract
Introduction: Military family life is characterized by mobility, separation, and increased risk for injury or death of the military member, which impacts the health and well-being of all family members. Additional stress is experienced when accessing and navigating a new health care system. Unknown to most Canadians is the reality that military and Veteran families (MVFs) access the civilian health care system; this indicates a need for military family cultural competency among health care providers. This current research identifies aspects of military family cultural competency to inform health care provision to MVFs. Method: A qualitative study using one-on-one interviews was completed with MVFs. Critical Incident Technique (CIT) was used to develop interview questions. Framework analysis was used for data analysis. Results: In total 17 interviews were completed including:1 family (female military spouse, male military member and child); 1 male Veteran; and 15 female military spouses (1 Veteran; 1 active member). Military family cultural competency domains such as cultural knowledge (characteristics of military families; impacts of mobility, separation, and risk) and cultural skills (building relationships; use of effective and appropriate assessments and interventions) were identified. The ecological context was also described as impacting the health care experience. Discussion: The reported experiences of MVFs in this study have highlighted the gaps in the military family cultural knowledge and military family cultural skills Canadian health care providers have when providing care. Results of this study can be used to develop continuing education for health professionals and inform future research.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.020 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".