Physical and Mental Comorbidity, Disability, and Suicidal Behavior Associated With Posttraumatic Stress Disorder in a Large Community Sample
Bibliographic record
Abstract
OBJECTIVE: To assess if posttraumatic stress disorder (PTSD), recognized as a common mental disorder in the general population and veteran samples, has a unique impact on comorbidity, disability, and suicidal behavior (after adjusting for other mental disorders, especially depression). METHODS: Data came from the Canadian Community Health Survey Cycle 1.2 (n = 36,984; age > or = 15 years; response rate 77%). All respondents were asked if they had been given a diagnosis of PTSD by a healthcare professional. A select number of mental disorders were assessed by the Composite International Diagnostic Interview. Chronic physical health conditions, measures of quality of life, disability, and suicidal behavior were also assessed. RESULTS: The prevalence of PTSD as diagnosed by health professionals was 1.0% (95% CI = 0.90-1.15). After adjusting for sociodemographic factors and other mental disorders, PTSD remained significantly associated with several physical health problems including cardiovascular diseases, respiratory diseases, chronic pain conditions, gastrointestinal illnesses, and cancer. After adjusting for sociodemographic factors, mental disorders, and severity of physical disorders, PTSD was associated with suicide attempts, poor quality of life, and short- and long-term disability. CONCLUSIONS: PTSD was uniquely associated with several physical disorders, disability, and suicidal behavior. Increased early recognition and treatment of PTSD are warranted.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".