Measurement Properties of 4 Patient-Reported Outcome Measures to Assess Sleep Disturbance in Adults With Atopic Dermatitis
Bibliographic record
Abstract
BACKGROUND: The ideal patient-reported outcome measure to assess sleep disturbance in atopic dermatitis (AD) has not been determined. OBJECTIVE: We sought to determine the measurement properties of the Patient-Reported Outcomes Measurement Information System (PROMIS) Itch Questionnaire Mood and Sleep (PIQ-MS), Sleep Disturbance (SD), Sleep-Related Impairment (SRI), and Epworth Sleepiness Scale (ESS) in adults with AD. METHODS: A prospective dermatology practice-based study was performed using questionnaires and evaluation by a dermatologist (n=611). RESULTS: PIQ-MS, PROMIS SD, SRI, and ESS had good convergent validity with intensity and frequency of sleep disturbance, Patient-Oriented Eczema Measure, Eczema Area and Severity Index, total and objective-Scoring AD, Numerical Rating Scale of worst-itch and average-itch, and Dermatology Life Quality Index. PIQ-MS had significantly better correlations with other severity measures than the other sleep measures (Fisher z-scores, P≤0.007). PIQ-MS, and to lesser extent PROMIS SD, PROMIS SRI and ESS had good discriminant validity. All four sleep assessments showed fair responsiveness to change of severity of sleep-disturbance, AD and itch. PIQ-MS had the best reliability. PIQ-MS, PROMIS SD, SRI and ESS showed good internal consistency and were feasible for use in clinical practice. CONCLUSIONS: PIQ-MS, followed by PROMIS SD, had the best construct validity and reliability in adult AD.
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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 | 0.016 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".