Providing Balanced Information about Options in Patient Decision Aids: An Update from the International Patient Decision Aid Standards
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The objective of this International Patient Decision Aids Standard (IPDAS) review is to update and synthesize theoretical and empirical evidence on how balanced information can be presented and measured in patient decision aids (PtDAs). METHODS: A multidisciplinary team conducted a scoping review using 2 search strategies in multiple electronic databases evaluating the ways investigators defined and measured the balance of information provided about options in PtDAs. The first strategy combined a search informed by the Cochrane Review of the Effectiveness of Decision Aids with a search on balanced information. The second strategy repeated the search published in the 2013 IPDAS update on balanced presentation. RESULTS: Of 2450 unique citations reviewed, the full text of 168 articles was screened for eligibility. Sixty-four articles were included in the review, of which 13 provided definitions of balanced presentation, 8 evaluated mechanisms that may introduce bias, and 42 quantitatively measured balanced with methods consistent with the IPDAS criteria in PtDAs. The revised definition of balanced information is, "Objective, complete, salient, transparent, evidence-informed, and unbiased presentation of text and visual information about the condition and all relevant options (with important elements including the features, benefits, harms and procedures of those options) in a way that does not favor one option over another and enables individuals to focus attention on important elements and process this information." CONCLUSIONS: Developers can increase the balance of information in PtDAs by informing their structure and design elements using the IPDAS checklist. We suggest that new PtDA components pertaining to balance be evaluated for cognitive bias with experimental methods as well by objectively evaluating patients' and content experts' beliefs from multiple perspectives.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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 it