Prevalence and clinical impact of topical corticosteroid phobia among patients with chronic hand eczema—Findings from the Danish Skin Cohort
Bibliographic record
Abstract
BACKGROUND: Topical corticosteroid phobia (TOPICOP) is associated with poor treatment adherence and is common among patients with skin disease. Knowledge about corticosteroid phobia and treatment adherence among patients with chronic hand eczema (CHE) is limited. OBJECTIVES: To investigate patient-reported outcomes regarding topical corticosteroids (TCSs), and their impact on treatment adherence in patients with CHE. METHODS: Patients with CHE from the Danish Skin Cohort answered a questionnaire including the TOPICOP scale and Medication Adherence Report Scale. Response rate was 69.2%. RESULTS: Of 927 with CHE, 75.5% totally or almost agreed that TCS damage the skin, 48.9% totally or almost agreed that TCS would affect their future health and 36.3% reported some degree of fear of TCS although they were unaware of any TCS-associated risks. Most patients (77.9%) always or often stop treatment as soon as possible, whereas 54.8% always or often wait as long as possible before starting treatment. Overall, 38.8% reported that they had taken less medicine than prescribed and 54.0% had stopped treatment throughout a period. Treatment adherence decreased with increasing corticosteroid phobia (P = .004). LIMITATIONS: TOPICOP has not been validated in patients with CHE. CONCLUSIONS: Corticosteroid phobia is common among patients with CHE and negatively associated with treatment adherence.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".