Evidence of the content validity, acceptability, and feasibility of a new Patient-Reported Impact of Dermatological Diseases measure
Bibliographic record
Abstract
Background: The Global Research on the Impact of Dermatological Diseases (GRIDD) team is developing the new Patient-Reported Impact of Dermatological Diseases (PRIDD) measure of the impact of dermatological conditions on the patient's life, in partnership with patients. To develop PRIDD, we conducted a systematic review, followed by a qualitative interview study with 68 patients worldwide and subsequently a global Delphi survey of 1,154 patients to ensure PRIDD items were meaningful and important to patients. Objective: To pilot test PRIDD with patients with dermatological conditions, focusing on its content validity (comprehensiveness, comprehensibility, and relevance), acceptability, and feasibility. Methods: We conducted a theory-led qualitative study using the Three-Step Test-Interview method of cognitive interviewing. Three rounds of semi-structured interviews were conducted online. Adults (≥ 18 years) living with a dermatological condition and who spoke English sufficiently to take part in the interview were recruited through the International Alliance of Dermatology Patient Organizations' (GlobalSkin) global membership network. The topic guide met the gold-standard COSMIN (Consensus-based Standards for the Selection of Health Measurement Instruments) standards for cognitive interviewing. Analysis followed the thematic analytical model of cognitive interviewing. Results: Twelve people (58% male) representing six dermatological conditions from four countries participated. Overall, patients found PRIDD to be comprehensible, comprehensive, relevant, acceptable, and feasible. Participants were able to discern the conceptual framework domains from the items. Feedback resulted in: the recall period being extended from 1 week to 1 month; removal of the 'not relevant' response option; and changes to the instructions and item ordering and wording to improve clarity and increase respondents' confidence in their ability to respond. These evidence-based adjustments resulted in a 26-item version of PRIDD. Conclusion: This study met the gold-standard COSMIN criteria for the pilot testing of health measurement instruments. The data triangulated our previous findings, in particular the conceptual framework of impact. Our findings illuminate how patients understand and respond to PRIDD and other patient-reported measurement instruments. The results of comprehensibility, comprehensiveness, relevance, acceptability, and feasibility of PRIDD provide evidence of content validity from the target population. The next step in the development and validation of PRIDD is psychometric testing.
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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 | 0.177 | 0.368 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".