Adverse childhood experiences and mental health in military recruits: Exploring gender as a moderator
Bibliographic record
Abstract
Adverse childhood experiences (ACEs) have consistently been associated with adult psychopathology and are commonly reported among military populations, with women more likely to report many types of ACEs than men. Limited research has examined the role of gender in the association between ACEs and mental health in military populations. The current study assessed the significance of gender differences in ACEs and mental health and explored the associations among these variables in a sample of Canadian Armed Forces recruits/officer cadets. Analyses with cross-sectional Recruit Health Questionnaire (RHQ) data from 50,603 recruits/officer cadets indicated that women were more likely to report witnessing domestic violence, experiencing sexual abuse, and living with someone with mental health problems or alcohol misuse, odds ratios (ORs) = 1.22-4.35, ps < .001. Women were more likely to screen positive for depression, adjusted (aORs) = 1.25-1.49, p < .001-p = .002, and anxiety, aORs = 2.00-2.33, ps < .001, before basic military training. ACEs were associated with screening positive for probable mental health conditions, aORs = 1.54-6.13, p < .001-p = .017. A significant interaction suggested the association between childhood sexual abuse and depression was stronger for men, aOR = 2.49, p < .001, than women, aOR = 1.63, p = .002, as was the association between childhood sexual abuse and posttraumatic stress disorder, men: aOR = 6.06, p < .001, women: aOR = 3.36, p < .001. These results underscore the importance of considering gender and childhood trauma in mental health interventions with military personnel.
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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 | 0.000 | 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".