Scoping review of patient and family engagement interventions in diagnosis: a paradox of too much, yet so little
Bibliographic record
Abstract
INTRODUCTION: Actively engaging patients is essential for diagnostic excellence and patient safety. OBJECTIVES: To (1) identify and synthesise interventions facilitating patient and family engagement (PFE) across the diagnostic process, and (2a) assess patient involvement and (2b) equity considerations in their design or implementation. DESIGN: This scoping review followed Arksey and O'Malley's framework and PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Review) guidelines. An advisory panel guided the review. We searched Medline, Embase, CINAHL, PsycInfo and Northern Light for peer-reviewed literature and conducted grey literature searches using DuckDuckGo and targeted websites. Search terms focused on PFE and diagnostic error. Eligible interventions were published in English between January 1999 and July 2024 and supported PFE in at least one step of the National Academies of Sciences, Engineering, and Medicine (NASEM) diagnostic process. Narrative reviews, case studies and editorials were excluded. Interventions were mapped to the NASEM steps; data were extracted on patient involvement and equity. RESULTS: Of the 11 630 studies screened, 250 were included, representing 260 interventions. Most (n=213; 85.2%) were from the grey literature, and patients were primary users (n=166; 63.8%). Interventions spanned all diagnostic process steps but were most common in treatment (n=122; 46.9%) and history taking (n=100; 38.5%), with few in referrals (n=10, 3.8%) and physical examinations (n=6, 2.3%). The evidence base was weak: grey literature interventions lacked high-quality studies, and among the 37 peer-reviewed studies, three were randomised controlled trials, each limited by small samples or high attrition. Only 63 interventions (24.2%) were designed with patients, and 48 (18.5%) incorporated equity. CONCLUSION: PFE interventions exist across the diagnostic process, but few target referrals and physical examinations. The evidence remains weak, and current interventions cannot be considered effective. Future research should prioritise equity, patient involvement and rigorous evaluation.
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How this classification was reachedexpand
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".