Illness-induced post-traumatic stress disorder among Canadian Armed Forces Members and Veterans
Bibliographic record
Abstract
OBJECTIVES: There is growing recognition of illness-induced post-traumatic stress disorder (PTSD), defined by illness being the index trauma that induces PTSD symptoms. This is the first study to examine 1) the lifetime prevalence of illness-induced PTSD among military personnel and veterans, and its 2) sociodemographic, military, trauma, and physical health condition correlates. METHODS: Participants completed the 2002 Canadian Community Health Survey-Mental Health and Well-being - Canadian Forces (N = 5155) and the 2018 Canadian Armed Forces Members and Veterans Mental Health Survey follow-up (n = 2941). A semi-structured clinical interview assessed PTSD, which we categorized as "illness-induced" or "other trauma-induced" PTSD based on the index trauma in those participating in both timepoints. To ensure representativeness of our study sample, we used baseline weights created by Statistics Canada to report weighted prevalence estimates and inferential statistics. RESULTS: The estimated lifetime prevalence of PTSD among the full sample was 22% and 1.5% had lifetime illness-induced PTSD. Among those with lifetime PTSD, the proportion of participants with illness-induced PTSD was 8.3% (91.7% met criteria for other trauma-induced PTSD). In an unadjusted model, the prevalence of illness-induced PTSD was greater for females (13.7%) than males (7.2%), and for those who were not deployed in both 2002 (5.7%) and 2018 (7.1%; unadjusted odds ratio (OR) range: 2.05-3.72). In a multinomial model adjusting for sociodemographic and military characteristics, compared to those with other trauma-induced PTSD, those with illness-induced PTSD had elevated rates of PTSD persistence (24.1% vs. 11.9%; RRR = 6.06, 95% CI [1.21-30.25]) and lower rates of remission (7.8% vs. 19.9%). CONCLUSION: Results highlight differences between illness-induced PTSD and other trauma-induced PTSD, primarily the potential chronicity of this manifestation. This may have implications for assessment strategies and targeted interventions.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".