Disability and Mental Disorders in the Canadian Armed Forces
Bibliographic record
Abstract
OBJECTIVES: The initial goal was to validate the use of a self-report measure of disability in the Canadian Armed Forces (CAF). The main goal was to document the extent of disability in personnel with and without mental disorders. METHODS: Data were obtained from the 2013 Canadian Forces Mental Health Survey; the sample included 6700 Regular Forces personnel. Disability was measured with the 12-item version of the World Health Organization Disability Assessment Schedule (WHODAS-2); established cut points were used to demarcate severe, moderate, minimal, and no disability. The following recent (past-year) and remote (lifetime but not past-year) disorders were assessed with diagnostic interviews: posttraumatic stress disorder, major depressive episode, generalized anxiety disorder, panic disorder, and alcohol use disorder. RESULTS: The WHODAS-2 showed good internal consistency (α = 0.89) and a 1-factor structure. Most personnel had no disability (59.2%) or minimal disability (30.8%). However, an important minority had moderate or severe disability (8.4% and 1.6%, respectively). Individuals with recent disorders reported greater disability than those without lifetime disorders, although many had minimal or no disability (41.2% and 24.7%, respectively). Disability increased with the number of recent disorders. Relative to those without lifetime disorders, individuals with remote disorders showed slightly greater disability, but most had no disabilty (57.1%) or minimal disability (35.0%). CONCLUSIONS: The 12-item WHODAS-2 is a valid measure of disability in the CAF. Mental disorders may be important drivers of disability in this population, although limited residual disability is seen in individuals with remote disorders.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".