Correlates of Perceived Need for Mental Health Care Among Active Military Personnel
Bibliographic record
Abstract
OBJECTIVE: There is increasing concern about mental health problems and need for mental health care among soldiers after deployment. This study examined correlates of self-perceived need for mental health care among active military personnel. METHODS: Data were from a 2002 cross-sectional population-based survey of 8,441 active Canadian military personnel (2,592 women) aged 16 to 54 (response rate 81%). A fully structured lay-administered interview for past-year DSM-IV mental disorders and perceived need for mental health care was conducted. Five domains of self-perceived need were assessed: information, medication, counseling, social intervention, and skills training. Several deployment factors were assessed (length of deployment, number of deployments, and exposure to deployment-related traumatic events), as were long-term restriction in activities because of disability and suicidal ideation. Multiple logistic regression models were used to determine correlates of perceived need. RESULTS: After adjustment for mental disorders, the strongest and most consistent correlates of perceived need were long-term restriction in activities, suicidal ideation, female gender, and regular service status (versus reserve status) (adjusted odds ratios ranging from 1.28 to 4.37). Deployment and exposure to combat and witnessing atrocities were moderately associated with an increase in self-perceived need for mental health care. CONCLUSIONS: The findings suggest that a range of issues beyond the presence of common mental disorders need to be considered in understanding the factors that contribute to a sense of need for mental health treatment. Postdeployment screening programs should consider systematically assessing self-perceived need for mental health treatment.
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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 | 0.000 | 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 | 0.001 | 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".