Standards for UNiversal reporting of patient Decision Aid Evaluation studies: the development of SUNDAE Checklist
Bibliographic record
Abstract
BACKGROUND: Patient decision aids (PDAs) are evidence-based tools designed to help patients make specific and deliberated choices among healthcare options. The International Patient Decision Aid Standards (IPDAS) Collaboration review papers and Cochrane systematic review of PDAs have found significant gaps in the reporting of evaluations of PDAs, including poor or limited reporting of PDA content, development methods and delivery. This study sought to develop and reach consensus on reporting guidelines to improve the quality of publications evaluating PDAs. METHODS: An international workgroup, consisting of members from IPDAS Collaboration, followed established methods to develop reporting guidelines for PDA evaluation studies. This paper describes the results from three completed phases: (1) planning, (2) drafting and (3) consensus, which included a modified, two-stage, online international Delphi process. The work was conducted over 2 years with bimonthly conference calls and three in-person meetings. The workgroup used input from these phases to produce a final set of recommended items in the form of a checklist. RESULTS: The SUNDAE Checklist (Standards for UNiversal reporting of patient Decision Aid Evaluations) includes 26 items recommended for studies reporting evaluations of PDAs. In the two-stage Delphi process, 117/143 (82%) experts from 14 countries completed round 1 and 96/117 (82%) completed round 2. Respondents reached a high level of consensus on the importance of the items and indicated strong willingness to use the items when reporting PDA studies. CONCLUSION: The SUNDAE Checklist will help ensure that reports of PDA evaluation studies are understandable, transparent and of high quality. A separate Explanation and Elaboration publication provides additional details to support use of the checklist.
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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 | 0.642 | 0.704 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.005 | 0.011 |
| Bibliometrics | 0.025 | 0.013 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.010 | 0.018 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".