Prevalence of Past-Year Mental Disorders in the Canadian Armed Forces, 2002-2013
Bibliographic record
Abstract
OBJECTIVE: More than 40,000 Canadian Armed Forces (CAF) personnel have deployed in support of the mission in Afghanistan since 2002. Over the same period, the CAF strengthened its mental health system. This article explores the effect of these events on the prevalence of past-year mental disorders over the period 2002-2013. METHOD: The data sources were 2 highly comparable population-based mental health surveys of CAF Regular Force personnel done in 2002 and 2013 (n = 5155 and 6996, respectively). Data were collected via in-person interviews with Statistics Canada personnel using the World Health Organization's Composite International Diagnostic Interview to assess past-year disorders. RESULTS: In 2013, 16.5% had 1 or more of the 6 past-year disorders assessed in the survey, with the most common conditions being major depressive episode (MDE), posttraumatic stress disorder (PTSD), and generalized anxiety disorder (GAD), which affected 8.0%, 5.3%, and 4.7%, respectively. The prevalence of PTSD, GAD, and panic disorder has increased significantly since 2002 (adjusted odds ratios from logistic regression models = 2.1, 3.0, and 1.9, respectively), while no change was seen for MDE. The comorbidity of mood and anxiety disorders increased significantly over time, being seen in 27.4% and 41.0% of those with mental disorders in 2002 and 2013, respectively. CONCLUSION: There has been an increase in the prevalence of PTSD and other anxiety disorders and of the extent of comorbidity of mood and anxiety disorders in CAF personnel over the period 2002-2013.
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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 | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".