Creating psychological safety in interprofessional simulation for health professional learners: a scoping review of the barriers and enablers
Bibliographic record
Abstract
Interprofessional simulation-based education (IP-SBE) supports the acquisition of interprofessional collaborative competencies. Psychologically safe environments are necessary to address socio-historical hierarchies and coercive practices that may occur in IP-SBE, facilitating fuller student participation. A scoping review was conducted to understand the barriers and enablers of psychological safety within IP-SBE. Research papers were eligible if they included two or more undergraduate and/or post-graduate students in health/social care qualifications/degrees and discussed barriers and/or enablers of psychological safety within simulation-based education. Sources of evidence included experimental, quasi-experimental, analytical observational, descriptive observational, qualitative, and mixed-methodological peer-reviewed studies. English or English-translated articles, published after January 1, 1990, were included. Data were extracted by two members of the research team. Extraction conflicts were resolved by the principal investigators. In total, 1,653 studies were screened; 1,527 did not meet inclusion criteria. After a full-text review, 99 additional articles were excluded; 27 studies were analyzed. Psychological safety enablers include prebriefing-debriefing by trained facilitators, no-blame culture, and structured evidenced-based simulation designs. Hierarchy among/between professions, fear of making mistakes, and uncertainty were considered barriers. Recognition of barriers and enablers of psychological safety in IP-SBE is an important first step towards creating strategies that support the full participation of students in their acquisition of IPC competencies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.083 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.015 | 0.015 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".