Canadian Patients’ Preferences in Topical Psoriasis Care: Insights From the PROPEL Surveys
Bibliographic record
Abstract
BACKGROUND: Patients with psoriasis of all severities employ topical treatment, either alone or in combination. Promoting Patient Engagement at the Leading Edge of Topical Psoriasis Treatment (PROPEL) surveyed Canadian dermatologists and their patients about their attitudes toward topical care. OBJECTIVES: To identify gaps between patients and dermatologists regarding the burden of psoriasis, the burden of treatment, and priorities for topical care to Canadian patients with psoriasis. METHODS: Two parallel surveys explored patient attitudes toward psoriasis and their experience with topical care, as expressed by patients or as perceived by their dermatologists. A third survey, addressed to patients, included additional questions regarding treatment adherence to current topical treatment regimens. RESULTS: PROPEL dermatologists underestimated the burden associated with psoriatic itch. Otherwise, they were well aligned with patients' views, including their preference for maintaining topical care of their psoriasis over other treatment modalities, the nature of good psoriasis control, and desirable features of topical medications. Despite holding generally positive views of topical therapy, many patients self-identified as poorly adherent. CONCLUSIONS: Long-term adherence to psoriasis topical care remains a challenge. Formulations with improved acceptability might help patients maintain good adherence.
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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".