Measuring life skills among Veterans: A systematic review of published instruments
Bibliographic record
Abstract
Introduction: Supporting the well-being of Canadian Veterans is a key policy objective of Veterans Affairs Canada, which led to the development of a seven-domain well-being construct: employment, finances, health, social integration, housing and physical environment, cultural and social environment, and life skills and preparedness. However, the usefulness of this construct depends on being able to reliably measure and operationalize each domain. This review addresses a gap by evaluating instruments measuring the life skills and preparedness domain, defined as knowledge and skills to navigate civilian life after military service. Methods: We conducted a systematic review of eight bibliographic databases, identifying instruments measuring life skills and preparedness. We used the COSMIN checklist and criteria to assess bias risk and evaluate instrument measurement performance. Veteran partners evaluated the instruments for applicability and clarity. Results: Of 1,472 records screened, 13 publications describing nine instruments were included - five measured life skills and preparedness among Veterans and four in the general community. Internal consistency among instruments was sufficient; however, other measurement properties were inconsistent. Only one, the Community Reintegration for Service Members - Community Adaptive Test, developed with and validated by Veterans, had high-quality evidence, but our partners were conflicted on its clarity and applicability. The Life Skills Development Inventory - College Form may be promising for younger Veterans; however, further validation is required including content validity and applicability to Veterans. Discussion: Further validation of some promising instruments is needed, or de novo creation of an instrument is required to measure life skills and preparedness for Canadian Veterans.
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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 | 0.021 | 0.112 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.020 | 0.022 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".