A Patient Decision Aid for Psoriasis Based on Current Clinical Practice Guidelines
Bibliographic record
Abstract
OBJECTIVE: To develop a patient decision aid (PDA) for psoriasis with content derived from current clinical practice guidelines. DESIGN: This PDA was developed in accordance with international patient decision aid standards. Primary sources of treatment outcome information were English-language, evidence-based clinical practice guidelines for plaque psoriasis published between January 1, 2006, and December 31, 2010. SETTING: Patients with psoriasis from a private practice in Windsor, Ontario, Canada, and a focus group of dermatologists across Canada. PARTICIPANTS: Focus groups of dermatologists (n=5) and patients with psoriasis (n=7) were convened to provide feedback on balance, clarity, practicality, and items for inclusion and exclusion. MAIN OUTCOME MEASURES: Physician's global assessment, overall lesional assessment, and 75% reduction in Psoriasis Area and Severity Index. RESULTS: Efficacy measures selected to reflect good control in the PDA were physician's global assessment (clear or almost clear) or overall lesional assessment (none or very mild) for topical agents and 75% reduction in Psoriasis Area and Severity Index for phototherapy and systemic agents. Where available, outcomes for serious adverse effects were displayed figuratively with efficacy measures. Deliberative questions for self-completion and a values clarification exercise were also incorporated. CONCLUSION: This psoriasis PDA was developed according to international standards based on content derived from current clinical practice guidelines.
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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 | 0.030 | 0.098 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 0.005 |
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".