Self-Reported Sleep Disturbance Mediates the Relationship Between PTSD and Cognitive Outcome in Blast-Exposed OEF/OIF Veterans
Bibliographic record
Abstract
OBJECTIVES: To examine the contribution of sleep disturbance to cognitive performance following blast exposure. DESIGN: Correlational research evaluating self-reported sleep disturbance as a mediator of the association between the primary blast-related comorbidities of mild traumatic brain injury (mTBI) and posttraumatic stress disorder and cognitive outcome. PARTICIPANTS: One hundred sixty Operation Enduring Freedom/Operation Iraqi Freedom Veterans with a history of blast exposure assigned to 1 of 3 groups (no TBI, mTBI without loss of consciousness, and mTBI with loss of consciousness). MAIN OUTCOME MEASURES: Neuropsychological measures and self-report of sleep disturbance. RESULTS: Increased posttraumatic stress disorder symptomatology was associated with worse performance in multiple cognitive domains. This association was mediated in part by self-reported sleep disturbance. Traumatic brain injury with loss of consciousness was associated with lower manual dexterity, but this association was not mediated by sleep disturbance. CONCLUSIONS: Our results highlight the importance of sleep disturbance as a factor contributing to cognitive outcome in individuals with posttraumatic stress disorder symptoms. They point to the importance of considering sleep problems in the diagnosis and treatment of cognitive deficits in veterans with blast exposure.
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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 | 0.003 |
| 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".