Nothing about me without me: a scoping review of how illness experiences inform simulated participants’ encounters in health profession education
Bibliographic record
Abstract
Person-centred simulation in health professions education requires involvement of the person with illness experience. To investigated how real illness experiences inform simulated participants' (SP) portrayals in simulation education using a scoping review to map literature. Arksey and O'Malley's framework was used to search, select, chart and analyse data with the assistance of personal and public involvement. MEDLINE, Embase, CINAHL, Scopus and Web of Science databases were searched. A final consultation exercise was conducted using results. 37 articles were within scope. Reporting and training of SPs are inconsistent. SPs were actors, volunteers or the person with the illness experience. Real illness experience was commonly drawn on in communication interactions. People with illness experience could be directly involved in various ways, such as through conversation with an SP, or indirectly, such as a recording of heart sounds. The impact on the learner was rarely considered. Authentic illness experiences help create meaningful person-centred simulation education. Patients and SPs may both require support when sharing or portraying illness experience. Patients' voices profoundly enrich the educational contributions made by SPs.
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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 | 0.026 | 0.099 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.024 | 0.026 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".