A Systematic Review and Meta-Analysis of Patient Decision Aids for Socially Disadvantaged Populations: Update from the International Patient Decision Aid Standards (IPDAS)
Bibliographic record
Abstract
Background The effectiveness of patient decision aids (PtDAs) and other shared decision-making (SDM) interventions for socially disadvantaged populations has not been well studied. Purpose To assess whether PtDAs and other SDM interventions improve outcomes or decrease health inequalities among socially disadvantaged populations and determine the critical features of successful interventions. Data Sources MEDLINE, CINAHL, Cochrane, PsycINFO, and Web of Science from inception to October 2019. Cochrane systematic reviews on PtDAs. Study Selection Randomized controlled trials of PtDAs and SDM interventions that included socially disadvantaged populations. Data Extraction Independent double data extraction using a standardized form and the Template for Intervention Description and Replication checklist. Data Synthesis Twenty-five PtDA and 13 other SDM intervention trials met our inclusion criteria. Compared with usual care, PtDAs improved knowledge (mean difference = 13.91, 95% confidence interval [CI] 9.01, 18.82 [I 2 = 96%]) and patient-clinician communication (relative risk = 1.62, 95% CI 1.42, 1.84 [I 2 = 0%]). PtDAs reduced decisional conflict (mean difference = −9.59; 95% CI −18.94, −0.24 [I 2 = 84%]) and the proportion undecided (relative risk = 0.39; 95% CI 0.28, 0.53 [I 2 = 75%]). PtDAs did not affect anxiety (standardized mean difference = 0.02, 95% CI −0.22, 0.26 [I 2 = 70%]). Only 1 trial looked at clinical outcomes (hemoglobin A1C). Five of the 12 PtDA studies that compared outcomes by disadvantaged standing found that outcomes improved more for socially disadvantaged participants. No evidence indicated which intervention characteristics were most effective. Results were similar for SDM intervention trials. Limitations Sixteen PtDA studies had an overall unclear risk of bias. Heterogeneity was high for most outcomes. Most studies only had short-term follow-up. Conclusions PtDAs led to better outcomes among socially disadvantaged populations but did not reduce health inequalities. We could not determine which intervention features were most effective. [Box: see text]
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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 | 0.074 | 0.174 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.026 |
| Bibliometrics | 0.014 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".