Strategies to evaluate healthcare provider trainings in shared decision-making (SDM): a systematic review of evaluation studies
Bibliographic record
Abstract
DESIGN AND OBJECTIVES: We performed a systematic review of studies evaluating healthcare provider (HCP) trainings in shared decision-making (SDM) to analyse their evaluation strategies. SETTING AND PARTICIPANTS: HCP trainings in SDM from all healthcare settings. METHODS: We searched scientific databases (Medline, PsycInfo, CINAHL), performed reference and citation tracking, contacted experts in the field and scanned the Canadian inventory of SDM training programmes for healthcare professionals. We included articles reporting data of summative evaluations of HCP trainings in SDM. Two reviewers screened records, assessed full-text articles, performed data extraction and assessed study quality with the integrated quality criteria for review of multiple study designs (ICROMS) tool. Analysis of evaluation strategies included data source use, use of unpublished or published measures and coverage of Kirkpatrick's evaluation levels. An evaluation framework based on Kirkpatrick's evaluation levels and the Quadruple Aim framework was used to categorise identified evaluation outcomes. RESULTS: Out of 7234 records, we included 41 articles reporting on 30 studies: cluster-randomised (n=8) and randomised (n=9) controlled trials, controlled (n=1) and non-controlled (n=7) before-after studies, mixed-methods (n=1), qualitative (n=1) and post-test (n=3) studies. Most studies were conducted in the USA (n=9), Germany (n=8) or Canada (n=7) and evaluated physician trainings (n=25). Eleven articles met ICROMS quality criteria. Almost all studies (n=27) employed HCP-reported outcomes for training evaluation and most (n=19) additionally used patient-reported (n=12), observer-rated (n=10), standardised patient-reported (n=2) outcomes or training process and healthcare data (n=10). Most studies employed a mix of unpublished and published measures (n=17) and covered two (n=12) or three (n=10) Kirkpatrick's levels. Identified evaluation outcomes covered all categories of the proposed framework. CONCLUSIONS: Strategies to evaluate HCP trainings in SDM varied largely. The proposed evaluation framework maybe useful to structure future evaluation studies, but international agreement on a core set of outcomes is needed to improve evidence. PROSPERO REGISTRATION NUMBER: CRD42016041623.
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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 | 0.021 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".