Validity of the Skindex Mini in Patients With Atopic Dermatitis
Bibliographic record
Abstract
Quality of life (QOL) measures can help clinicians understand patients' experience of disease, judge the effectiveness of care, and facilitate shared decision making 1 .To be useful in clinical practice, instruments must be simple and quick to complete.The Skindex Mini (SDM), a three-item questionnaire, was derived from a longer previously validated instrument, Skindex-16, to serve this purpose.To date, two studies have demonstrated robust concurrent validity with strong correlations between SDM scores and Skindex-16 scores 2,3.In this study, we sought to further examine construct validity and responsiveness of the SDM in a cohort of patients with atopic dermatitis.As part of routine care, patients with atopic dermatitis (AD) seen by ES in a medical dermatology clinic at Oregon Health & Science University were given a questionnaire during the appointment check-in process.The questionnaire included the SDM, a patientreported global assessment of severity (PtGA), an itch numerical rating scale (NRS) 4 , and a question asking if the patient considered their disease well-controlled.ES included the investigator global assessment of severity (IGA).The SDM was completed by 132 AD patients on at least one occasion and 68 patients on two occasions.To evaluate construct validity, we examined median and interquartile ranges for SDM domain scores across levels of IGA, PtGA, NRS itch, and overall control, and calculated Spearman's rank correlation coefficients (r s ) of SDM scores with each measure.To evaluate responsiveness, the same approach was applied to changes in SDM domain scores across
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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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".