Examining the Association between Psychiatric Illness and Suicidal Ideation in a Sample of Treatment-Seeking Canadian Peacekeeping and Combat Veterans with Posttraumatic Stress Disorder
Bibliographic record
Abstract
OBJECTIVE: Our study examines the association between suicidal ideation and and self-reported symptoms of posttraumatic stress disorder (PTSD), major depressive disorder (MDD), generalized anxiety disorder (GAD), and alcohol use disorder (AUD) in a sample of treatment-seeking Canadian combat and peacekeeping veterans; and identifies potential predictors of suicidal ideation. METHODS: Actively serving Canadian Forces and Royal Canadian Mounted Police members and veterans seeking treatment at the Parkwood Hospital Operational Stress Injury Clinic (n = 250) completed measures including the Primary Care Evaluation of Mental Disorders Patient Health Questionnaire, the Alcohol Use Disorder Identification Test, and the PTSD Checklist-Military Version (PCL-M) between January 2002 and December 2010. Regression analyses were used to determine the respective impact of PTSD, and self-reported symptoms of MDD, GAD, AUD, and anxiety on suicidal ideation. RESULTS: Most people met PCL-M screening criteria for PTSD (73.6%, n = 184), while 70.8% (n = 177) screened positively for a probable major depressive episode. PTSD symptom was significantly associated with suicidal ideation (β = 0.412, P < 0.001). After controlling for self-reported depressive symptom severity, AUD severity, and generalized anxiety, PTSD severity was no longer significantly associated with suicidal ideation (β = 0.043, P = 0.58). CONCLUSIONS: Although PTSD alone is associated with suicidal ideation, after controlling for common comorbid psychiatric illnesses, self-reported depressive symptom severity emerged as the most significant predictor of suicidal ideation. These findings support the importance of screening for comorbidities, particularly an MDD, as potentially modifiable conditions that are strongly related to suicidal ideation in military personnel's endorsing criteria for PTSD.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".