Measurement properties and interpretability of the Patient-Reported Impact of Dermatological Diseases (PRIDD) measure
Bibliographic record
Abstract
BACKGROUND: Patient-reported outcome measures (PROMs) are crucial in assessing the impact of dermatological conditions on people's lives, but the existing dermatology-specific PROMs are not recommended for use, according to COSMIN. We developed the Patient-Reported Impact of Dermatological Diseases (PRIDD) measure in partnership with patients. It has strong evidence of content validity, structural validity, internal consistency, acceptability and feasibility. OBJECTIVES: To test the remaining measurement properties of the PRIDD and establish the interpretability of scores against the COSMIN criteria, using classic and modern psychometric methods. METHODS: A global longitudinal study consisting of two online surveys administered 2-4 weeks apart was carried out. Adults (≥ 18 years of age) living with a dermatological condition were recruited via the International Alliance of Dermatology Patient Organizations' (GlobalSkin) membership network. Participants completed PRIDD, a demographics questionnaire and other related measures, including the Dermatology Life Quality Index. We tested the criterion validity, construct validity and responsiveness (Spearman's ρ, independent-samples t-tests and Anova); test-retest reliability [interclass correlation coefficient (ICC)]; measurement error [smallest detectable change or limits of agreement (LoA), distribution-based minimally important change (MIC)]; floor and ceiling effects (number of minimum and maximum scores and person-item location distribution maps), score bandings (κ coefficient of agreement) and the anchor-based MIC of the PRIDD. RESULTS: In total, 504 people with 35 dermatological conditions from 38 countries participated. Criterion validity (ρ = 0.79), construct validity (76% hypotheses met), test-retest validity (ICC = 0.93) and measurement error (LoA = 1.3 < MIC = 4.14) were sufficient. Floor and ceiling effects were in the acceptable range (< 15%). Score bandings were determined (κ = 0.47); however, the anchor-based MIC could not be calculated owing to an insufficient anchor. CONCLUSIONS: PRIDD is a valid and reliable tool to evaluate the impact of dermatological disease on people's lives in research and clinical practice. It is the first dermatology-specific PROM to meet the COSMIN criteria. These results support the value of developing and validating PROMs with a patient-centred approach and using classic and modern psychometric methods. Further testing of responsiveness and MIC, cross-cultural translation, linguistic validation and global data collection are planned.
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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 | 0.072 | 0.151 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".