The Association Between Sleep Disturbance and Health Outcomes in Chronic Whiplash-associated Disorders
Bibliographic record
Abstract
OBJECTIVES: To investigate the association between sleep disturbance and clinical features of chronic whiplash-associated disorders (WAD). We also aimed to use a bootstrapped mediation analysis approach to systematically examine both direct and indirect pathways by which sleep disturbance may affect chronic pain and functional status. MATERIALS AND METHODS: One hundred sixty-five people (63% female) with chronic WAD and not taking medications for sleep disturbance completed questionnaires evaluating sleep disturbance, pain intensity, pain interference, disability, physical and mental health quality of life, stress, anxiety, depression, pain catastrophizing, and posttraumatic stress severity. RESULTS: Greater sleep disturbance was associated with increased duration of symptoms, higher levels of pain and disability, higher levels of emotional distress and pain catastrophizing, and functional impairment (reduced health-related quality of life). Mediation analyses demonstrated that sleep disturbance influenced chronic pain intensity and interference through both direct and indirect associations inclusive of stress, anxiety, and pain catastrophizing. Similarly, sleep disturbance was associated with higher levels of disability and poor health-related quality of life, both directly and also through its negative association with pain intensity and interference. DISCUSSION: Sleep disturbance in chronic WAD was associated with worse health outcomes and demonstrated both direct and indirect effects on both chronic pain and function.
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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 | 0.006 |
| 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 | 0.001 |
| 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".