Moral injury associated with increased odds of past-year mental health disorders: a Canadian Armed Forces examination
Bibliographic record
Abstract
Background: Potentially morally injurious experiences (PMIEs) are common during military service. However, it is unclear to what extent PMIEs are related to well-established adverse mental health outcomes.Objective: The objective of this study was to use a population-based survey to determine the associations between moral injury endorsement and the presence of past-year mental health disorders in Canadian Armed Forces (CAF) personnel and Veterans.Methods: Data were obtained from the 2018 Canadian Armed Forces Members and Veterans Mental Health Follow-up Survey (CAFVMHS). With a sample of 2,941 respondents, the weighted survey sample represented 18,120 active duty and 34,380 released CAF personnel. Multiple logistic regressions were used to assess the associations between sociodemographic characteristics (e.g. sex), military factors (e.g. rank), moral injury (using the Moral Injury Events Scale [MIES]) and the presence of specific mental health disorders (major depressive episode, generalized anxiety disorder, panic disorder, social anxiety disorder, PTSD, and suicidality).Results: While adjusting for selected sociodemographic and military factors, the odds of experiencing any past-year mental health disorder were 1.97 times greater (95% CI = 1.94–2.01) for each one-unit increase in total MIES score. Specifically, PTSD had 1.91 times greater odds (95% CI = 1.87–1.96) of being endorsed for every unit increase in MIES total score, while odds of past-year panic disorder or social anxiety were each 1.86 times greater (95% CI = 1.82–1.90) for every unit increase in total MIES score. All findings reported were statistically significant (p < .001).Conclusion: These findings emphasize that PMIEs are robustly associated with the presence of adverse mental health outcomes among Canadian military personnel. The results of this project further underscore the necessity of addressing moral injury alongside other mental health concerns within the CAF.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".