Mental Health Treatment Seeking by Military Members with Posttraumatic Stress Disorder: Findings on Rates, Characteristics, and Predictors from a Nationally Representative Canadian Military Sample
Bibliographic record
Abstract
OBJECTIVE: The goal of this study was to identify rates, characteristics, and predictors of mental health treatment seeking by military members with posttraumatic stress disorder (PTSD). METHOD: Our sample was drawn from the 2002 Canadian Community Health Survey-Canadian Forces Supplement (CCHS-CF) dataset. The CCHS-CF is the first epidemiologic survey of PTSD and other mental health conditions in the Canadian military and includes 8441 nationally representative Canadian Forces (CF) members. Of those, 549 who met the criteria for lifetime PTSD were included in our analyses. To identify treatment rates and characteristics, we examined frequency of treatment contact by professional and facility type. To identify predictors of treatment seeking, we conducted a binary logistic regression with lifetime treatment seeking as the outcome variable. RESULTS: About two-thirds of those with PTSD consulted with a professional regarding mental health problems. The most frequently consulted professionals, during both the last year and lifetime, included social workers and counsellors, medical doctors and general practitioners, and psychiatrists. Consultations during the last year most often took place in a CF facility. Treatment seeking was predicted by cumulative lifetime trauma exposure, index traumatic event type, PTSD symptom interference, and comorbid major depressive disorder. Those with comorbid depression were 3.75 times more likely to have sought treatment than those without. CONCLUSIONS: Although a significant portion of military members with PTSD sought mental health treatment, 1 in 3 never did. Trauma-related and illness and (or) need factors predicted treatment seeking. Of all the predictors of treatment seeking, comorbid depression most increased the likelihood of seeking 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".