Topical corticosteroid phobia in atopic dermatitis: International feasibility study of the <scp>TOPICOP</scp> score
Bibliographic record
Abstract
BACKGROUND: Adherence to topical corticosteroids (TCS) is essential for the effective treatment of atopic dermatitis but can be limited by concerns about their use. This study examined the feasibility of applying the validated TOPICOP score for assessing TCS phobia across different countries. METHODS: This was a prospective multicentre feasibility study conducted in 21 hospitals in 17 countries. Patients >3 months of age with atopic dermatitis or their parents or legal representatives completed a validated translation of the TOPICOP questionnaire in the country's native language. Respondents also completed questionnaires collecting opinions about the feasibility and acceptability of the TOPICOP questionnaire. RESULTS: A total of 1564 participants in 15 countries were included in the analysis. 81% of respondents considered the questions clear or very clear, and 79% reported that it took less than 5 minutes to complete. Each of the individual items in the TOPICOP questionnaire was considered to be not at all difficult to answer by 49% to 74% of participants. The mean global TOPICOP score was 44.7%±20.5. Mean TOPICOP subscores were 37.0±22.8% for knowledge and beliefs, 54.7±27.8% for fears and 50.1±29.1% for behaviours. Global scores and subscores differed between countries, although the subscores did not always vary in parallel, suggesting different levels of TCS phobia and different drivers for each country. CONCLUSIONS: The TOPICOP score can be feasibly applied across countries and may therefore be useful for obtaining qualitative and quantitative data from international studies and for adapting patient education and treatment.
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".