Panic Attacks and Panic Disorder in a Population-Based Sample of Active Canadian Military Personnel
Bibliographic record
Abstract
BACKGROUND: The factors contributing to psychiatric problems among military personnel, particularly for panic, are unclear. The objective of this study was to examine the prevalence and correlates of panic disorder and panic attacks in the Canadian military. METHOD: Statistics Canada and the Department of National Defense conducted the Canadian Community Health Survey-Canadian Forces Supplement in 2002 (May to December) with a representative sample of active Canadian military personnel (aged 16-54 years; N = 8,441; response rate, 81.5%). Comparisons were made between respondents with no past-year panic attacks, panic attacks without panic disorder, and panic disorder on measures of DSM-IV mental disorders, as well as validated measures of disability, distress, suicidal ideation, perceived need for mental health treatment, and mental health service use. Lifetime exposure to combat operations, witnessing of atrocities, and deployments were also assessed. RESULTS: Panic disorder and panic attacks were common in the military population, with past-year prevalence estimates of 1.8% and 7.0%, respectively. Both panic disorder and panic attacks were associated with increased odds of all mental disorders assessed, suicidal ideation, 2-week disability, and distress. Perceived need for mental health treatment and service use were common in individuals with panic attacks and panic disorder (perceived need: 46.3% for panic attacks, 89.6% for panic disorder; service use: 32.5% for panic attacks, 74.5% for panic disorder). CONCLUSIONS: Panic attacks and panic disorder in the military are associated with outcomes that could be detrimental to well-being and work performance, and early detection of panic in this population could help reduce these negative outcomes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".