Assessing Quality of Sleep in Patients with Rheumatoid Arthritis
Bibliographic record
Abstract
We sought to identify instruments assessing sleep quality that measure the domains of sleep applicable to rheumatoid arthritis (RA) patients and are feasible to use and have appropriate reliability, validity, and responsiveness properties. A systematic review of sleep instruments was conducted. In particular, domains related to sleep that were assessed in the instruments were identified and evaluated. Feasibility characteristics and psychometric properties of instruments were reviewed. At OMERACT 9, the preparatory work was described at the plenary session of the Patient Perspective Workshop, and the tasks of 3 breakout groups in ranking and scoring the domains and sleep instruments were outlined. Each breakout group considered different aspects of sleep: sleep domains, feasibility, and psychometric properties. The rapporteur for each breakout group reported back to the plenary on the domains and sleep instruments that achieved the highest rank/score. The systematic review identified 45 sleep instruments of interest. Based on these instruments, 14 domains of sleep were identified. The top ranked domains were: Sleep Adequacy (1), Sleep Maintenance (2), Sleep Initiation (3) and Daytime Functioning (4). The top ranked instruments on feasibility were: Athens Insomnia Scale (2.3), Medical Outcome Study (MOS) Sleep (4.0), Insomnia Severity Index (4.9), and Women's Health Insomnia Rating Scale (5.5). The highest scored instruments on psychometric properties were: Athens Insomnia Scale (13.6), Sleep Assessment Questionnaire (13), Pittsburgh Sleep Diary (12), and MOS Sleep (11). Sleep domains have been reviewed, and several sleep instruments have been identified. These instruments should be considered for use in planned clinical trials of RA patients to assess their applicability.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".