Age differences in PTSD among Canadian veterans: age and health as predictors of PTSD severity
Bibliographic record
Abstract
Background:To date, few studies have investigated age differences in posttraumatic stress disorder (PTSD) symptoms and none has examined age differences across symptom clusters: avoidance, re-experiencing, and hyperarousal. The first objective of this study was to investigate age differences in PTSD and its three symptom clusters. The second objective was to examine age and indices of health as predictors of PTSD symptom severity.Methods:Participants were 104 male veterans, aged 22 to 87 years, receiving specialized mental health outpatient services. Assessments included measures of health-related quality of life, pain severity, number of chronic health conditions, and symptoms of PTSD, both in total and on the symptom clusters.Results:There were significant age differences across age groups, with older veterans consistently reporting lower PTSD symptom severity, both in total and on each of the symptom clusters. Hierarchical regression analyses indicated that the inclusion of health indices accounted for significantly more variance in PTSD symptoms over and above that accounted for by age alone. Pain severity was a significant predictor of PTSD total and the three symptom clusters.Conclusions: This is the first study to report lower levels of PTSD severity among older veterans across symptom clusters. These findings are discussed in relation to age differences in the experiencing and processing of emotion, autobiographical memory, and combat experiences. This study also emphasizes the importance of assessing pain in those with symptoms of PTSD, particularly older veterans who are less likely to receive specialized mental healthcare.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".