The home front: Operational stress injuries and veteran perceptions of their children’s functioning.
Bibliographic record
Abstract
The severity of depression and posttraumatic stress disorder (PTSD) reported by military parents appears to predict affective and behavioral symptoms presented by their children. Veteran’s symptoms also appear to hinder the relationship with their child. Accordingly, the present study examined the relationship between specific PTSD symptoms (i.e., reexperiencing, avoidance, numbing, hyperarousal) and the affective and behavioral concerns those veterans have regarding their own children, with depressive symptoms included as a covariate. A total of 1238 (95% men) Canadian Forces veterans completed self-report measures assessing mental health (i.e., PTSD Checklist – Military version; Center for Epidemiological Studies – Depression Scale) and questions regarding familial concerns (i.e., child affect and behavior) as part of a mail-out survey. Logistic regressions demonstrated that veterans with PTSD have greater concerns over the affect of their child (p .001) and behavior of their child (p .001) than veterans without PTSD. Logistic regressions also demonstrated that numbing and hyperarousal symptoms were related to both affective (p .008 and p .001, respectively) and behavioral concerns (p .001 and p .001, respectively) regarding the veteran’s children. Veteran’s PTSD symptoms may contribute to a familial environment conducive to the development of affective and behavioral concerns regarding children; however, PTSD symptoms may also alter a veteran’s ability to identify such concerns. Comprehensive results, implications, and future research are discussed.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".