Among Inpatients, Posttraumatic Stress Disorder Symptom Severity Is Negatively Associated With Time Spent Walking
Bibliographic record
Abstract
This study aimed to determine whether posttraumatic stress disorder (PTSD) symptom severity and psychological and functional variables were associated with physical activity (PA) upon admission to an inpatient facility. PTSD symptoms, depression, anxiety and stress, sleep quality, and PA participation were assessed among 76 participants (age, 47.6 ± 11.9 years; 83% male). Backward stepwise regression analyses identified variables independently associated with time spent walking and engaging in moderate-vigorous PA (MVPA). No significant correlations were found between any of the variables and MVPA. Total PTSD symptoms (r = -0.39, p < 0.001), combined symptoms of depression, anxiety, and stress (r = -0.31, p < 0.01), and sleep behavior (r = -0.24, p < 0.05) were significantly and negatively associated with total walking time. Total PTSD symptoms were the only significant predictor of walking time (B = -0.03, SE = 0.008, β = -0.4; t = -3.4; p < 0.001). Results indicate that increased PTSD symptoms are associated with lower levels of walking. Results highlight the importance of considering symptoms when designing PA programs for people with PTSD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| 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) | 0.002 | 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".