Risk Factors, Clinical Presentations, and Functional Impairments for Generalized Anxiety Disorder in Military Personnel and the General Population in Canada
Bibliographic record
Abstract
OBJECTIVE: This study sought to examine differences in sociodemographic risk factors, comorbid mental conditions, clinical presentations, and functional impairments associated with past-year generalized anxiety disorder (GAD) between Canadian Armed Forces (CAF) Regular Force personnel and the Canadian general population (CGP). METHOD: Data were from 2 nationally representative surveys collected by Statistics Canada: 1) the Canadian Community Health Survey on Mental Health, collected in 2012 ( N = 25,113; response rate = 68.9%); and 2) the Canadian Forces Mental Health Survey, collected in 2013 ( N = 8,161; response rate = 79.8%). RESULTS: The prevalence of lifetime and past-year GAD was significantly higher in the CAF (12.1% and 4.7%) than in the CGP (9.5% and 3.0%). Comorbid mental disorders were strongly associated with GAD in both populations. Although the content area of worry and the GAD symptoms endorsed were similar, CAF personnel were significantly more likely to endorse specific types of worries (i.e., success at school/work, social life, mental health, being away from home or loved ones, and war or revolution) and specific symptoms of GAD (i.e., restless, keyed up, or on edge and more irritable than usual) than civilians, after adjusting for sociodemographic covariates and comorbid mental disorders. CAF personnel with past-year GAD reported significantly higher functional impairment at home than civilians with past-year GAD. CONCLUSION: GAD is a substantial public health concern associated with significant impairment and disability in both military and civilian populations. GAD in military and civilian populations shows similarities and differences: Key similarities include its extensive comorbidity and significant functional impairment, whereas key differences include the focus of worries and symptom profile.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".