Clinical Utilization of Repeated Open Application Test Among American Contact Dermatitis Society Members
Bibliographic record
Abstract
BACKGROUND: The repeated open application test (ROAT) provides useful information regarding allergens in suspected cases of allergic contact dermatitis; however, standardized methodology has not been established. OBJECTIVE: The aim of this study was to assess how ROAT is used in clinical and research settings. METHODS: We distributed a survey regarding ROAT practice to the American Contact Dermatitis Society and conducted a literature review of ROAT utilization in research. RESULTS: A total of 67 American Contact Dermatitis Society members participated in the survey. Respondents most frequently recommend application of leave-on products twice daily (46.0%) and rinse-off products once daily (43.5%). The most commonly used anatomical sites include the forearm (38.7%) and antecubital fossa (32.3%). Most respondents continue ROAT for 1 (49.2%) or 2 weeks (31.7%). Literature review of 32 studies (26 leave-on, 6 rinse-off) revealed that application frequency is most common at twice daily for both leave-on (96.2%) and rinse-off (50.0%) products. The most common anatomical site is the forearm (62.5%), with an overall study duration of 3 to 4 weeks (65.6%). CONCLUSIONS: When comparing ROAT clinical and research practice, the majority trend was consistent for leave-on product application frequency and anatomical site, but not for rinse-off product application frequency, or overall duration. Further research is needed to determine best practice recommendations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".