Relationships between health behaviors, posttraumatic stress disorder, and comorbid general anxiety and depression
Bibliographic record
Abstract
Poor health outcomes associated with posttraumatic stress disorder (PTSD) may reflect engagement in unhealthy behaviors that increase morbidity risk and disengagement in healthy behaviors that decrease morbidity risk. Although research supports this pattern, findings are not definitive, particularly for healthy behaviors. Many studies have not controlled for effects of concurrent generalized anxiety and depression, which might explain conflicting findings. To address this limitation, we used an online cross-sectional research design and multivariate multilevel modelling to evaluate associations between a multitude of health behaviors (i.e. sedentary behavior, sleep quality, physical activity, eating habits, alcohol use and substance use) and PTSD, while adjusting for comorbid generalized anxiety and depression, in a sample of trauma-exposed individuals (N = 246). Our results indicate that PTSD and comorbid generalized anxiety and depression symptoms were differentially associated with specific health constructs. Specifically, sedentary behavior and poor sleep quality were associated with PTSD, whereas low physical activity, poor sleep quality, and unhealthy eating habits were associated with depression. Both increased alcohol and substance use were associated with generalized anxiety. Results from our study highlight the need to conceptualize associations between health behaviors and specific psychological symptoms in a comprehensive manner as part of clinical presentations of PTSD.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".