0936 Associations Between Sleep, Cognitive Flexibility, and Attention in Trauma-Exposed Veterans
Bibliographic record
Abstract
Abstract Introduction Post-traumatic stress disorder (PTSD) triggers disturbances in sleep such as prolonged sleep onset latency, decreased REM latency, higher amounts of REM sleep and lighter sleep. The impacts of these sleep difficulties on cognitive performance are clear. However, there is a limited understanding on how they may contribute to cognitive challenges that are affecting people living with PTSD. This study aimed to explore how attention and cognitive flexibility relate to sleep architecture in veterans with PTSD. Methods A group of thirty-six trauma-exposed veterans underwent psychiatric interviews, including the Clinician-Administered PTSD scale for DSM-5. Polysomnography was recorded on two nights: the first recording was used as an adaptation night and the second one was used for final analysis. On the morning following the experimental night, participants completed the Trail Making Test A and B, a task known to involve complex attention, visuospatial processing, working memory, and psychomotor coordination. Results Slower performance on the Trail Making Test A (i.e., attentional component of the task) correlated with longer sleep onset latency (r=.35, p=.037), higher amounts of light sleep (NREM1 and NREM2; r>.35, p<.037), and tended to correlate with longer REM sleep latency (r=.32, p=.056). In addition, non-significant trends suggested that higher number of errors committed on the Trail Making Test A were associated with longer sleep onset latency and higher amounts of NREM1 sleep (r=.30, p=.070). Slower performance on the Trail Making Test B (i.e., cognitive flexibility component of the task) tended to correlate with longer REM sleep latency (r=.33, p=.051) and lower sleep efficiency (r=-.31, p=.065). Conclusion These preliminary findings display some of the common abnormalities seen in people living with PTSD and how they relate to the severity of the cognitive challenges they are facing. Recognizing the active role of sleep for attentional processes and cognitive flexibility stresses the relevance of exploring whether sleep restoration may mitigate some of the debilitating symptoms of PTSD on cognition. Support (if any) This project was funded by a competitive grant from the Canadian National Defence (Innovation for Defence Excellence and Security (IDEaS)).
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.004 | 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".