Trust and world view in shared decision making with indigenous patients: A realist synthesis
Bibliographic record
Abstract
INTRODUCTION: How shared decision making (SDM) works with indigenous patient values and preferences is not well understood. Colonization has affected indigenous peoples' levels of trust with institutions, and their world view tends to be distinct from that of nonindigenous people. Building on a programme theory for SDM, the present research aims to refine the original programme theory to understand how the mechanisms of trust and world view might work differently for indigenous patients. DESIGN: We used a six-step iterative process for realist synthesis: preliminary programme theory development, search strategy development, selection and appraisal of literature, data extraction, data analysis and synthesis, and formation of a revised programme theory. DATA SOURCES: Searches were through Medline, CINAHL, and the University of Saskatchewan iPortal for grey literature. Medline and CINAHL searches included the University of Alberta Canada-wide indigenous peoples search filters. DATA SYNTHESIS: Following screening 731 references, 90 documents were included for data extraction (53 peer reviewed and 37 grey literature). Documents from countries with similar colonization experiences were included. RESULTS: A total of 518 context-mechanism-outcome (CMO) configurations were identified and synthesized into 21 CMOs for a revised programme theory. Demographics, indigenous world view, system and institutional support, language barriers, and the macro-context of discrimination and historical abuse provided the main contexts for the programme theory. These inspired mechanisms of reciprocal respect, perception of world view acceptance, and culturally appropriate knowledge translation. In turn, these mechanisms influenced the level of trust and anxiety experienced by indigenous patients. Trust and anxiety were both mechanisms and intermediate outcomes and determined the level of engagement in SDM. CONCLUSION: This realist synthesis provides clinicians and policymakers a deeper understanding of the complex configurations that influence indigenous patient engagement in SDM and offers possible avenues for improvement.
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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 | 0.016 | 0.080 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".