Patient prioritisation of impact items to develop the <scp>patient‐reported</scp> impact of dermatological diseases (<scp>PRIDD</scp>) measure: European Delphi data
Bibliographic record
Abstract
BACKGROUND: The Global Research on the Impact of Dermatological Diseases (GRIDD) project is developing a patient-reported measure of the impact of dermatological disease on the patient's life called Patient Reported Impact of Dermatological Diseases (PRIDD). We developed a list of 263 potential impact items through a global qualitative interview study with 68 patients. We next conducted a Delphi study to seek consensus on which of these items to prioritize for inclusion in PRIDD. This study aims to explore patterns in demographic (e.g. country) and clinical variables (e.g. disease group) across the impacts ranked as most important to European dermatology patients. METHODS: We conducted a modified, two rounds Delphi study, testing the outcomes from the previous qualitative interview study. Adults (≥18 years) living with a dermatological disease were recruited through the International Alliance of Dermatology Patient Organizations' (GlobalSkin) membership network. The survey consisted of a demographic questionnaire and 263 impact items and was available in six languages. Quantitative data were collected using ranking scales and analysed against a priori consensus criteria. Qualitative data were collected using free-text responses and a Framework Analysis was conducted. European data were obtained, and descriptive statistics, including multiple subgroup analyses, were performed. RESULTS: Out of 1154 participants, 441 Europeans representing 46 dermatological disease from 25 countries participated. The results produced a list of the top 20 impacts reported by European patients, with psychological impacts accounting for the greatest proportion. CONCLUSION: This study identified what patients consider to be the most important issues impacting their lives as a result of their dermatological disease. The data support previous evidence that patients experience profound psychological impacts and require psychological support. The findings can inform research, clinical practice and policy by indicating research questions and initiatives that are of most benefit to patients.
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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 | 0.079 | 0.082 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".