The Contact Dermatitis Quality of Life Index (CDQL): Survey Development and Content Validity Assessment
Bibliographic record
Abstract
BACKGROUND: There is limited measurement and reporting of quality of life (QoL) outcomes for patients with contact dermatitis (CD). OBJECTIVE: The purpose of this study is to develop a standardized Contact Dermatitis Quality of Life index (CDQL) for adult patients. METHODS: A list of 81 topics was compiled from a review of QoL measures used previously in CD research. A total of 2 rounds of web-based Delphi surveys were sent to physicians who registered to attend the 2018 American Contact Dermatitis Society meeting, asking that they rank the relevance of topics for measuring QoL in CD using a 4-point scale. Items met consensus for inclusion if at least 78% of respondents ranked them as relevant or very relevant, and their median score was ≥3.25. RESULTS: Of the 210 physicians contacted, 34 physicians completed the initial survey and 17 completed the follow-up survey. A total of 22 topics met consensus for inclusion in the CDQL, addressing symptoms, emotions, functions of daily living, social and physical functions, work/school functions, and treatment. CONCLUSIONS: This study was limited by the following factors: few open-ended questions in the initial survey, a lack of direct patient feedback, and long survey length, which likely contributed to lower survey participation. The CDQL is a comprehensive, CD-specific QoL measure developed on the basis of expert consensus via a modified Delphi process to be used by physicians and other health care professionals who care for adult patients with contact dermatitis.
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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 | 0.043 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 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".