Participant Perspectives on the Contributions of Physical, Psychological, and Sociological Fidelity to Learning in Interprofessional Mental Health Simulation
Bibliographic record
Abstract
INTRODUCTION: Simulation has been identified as a key training modality to enhance interprofessional care for patients with co-occurring physical and mental illnesses. Fidelity is an important instructional design consideration for interprofessional simulation; however, research examining the contribution of physical, psychological, and sociological fidelity in achieving learning outcomes remains limited. This qualitative study explored the relationship between fidelity and learning from the perspective of interprofessional simulation course participants. METHODS: Semistructured interviews were conducted with participants from the Interprofessional Simulations of Patient Experiences Across the Care Continuum - Child and Youth course. Consistent with grounded theory, data collection and analysis proceeded in an iterative fashion and emergent themes were identified by the research team through a process of constant comparative analysis. RESULTS: Data saturation was reached after 10 interviews. High psychological fidelity allowed participants to engage in the simulation scenarios in ways that were congruent with their professional roles, which supported individual practice change. Tasks that were too closely aligned with their clinical experiences sometimes, however, limited new learning opportunities. Selective manipulations of sociological fidelity seemed to support learning outcomes related to understanding and appreciating the roles and responsibilities of other health professionals. Physical fidelity was less essential. CONCLUSIONS: Psychological and sociological fidelity were perceived by participants as being most critical to learning in interprofessional mental health simulation. Improving our understanding of how simulation works in this context is important to effectively direct the efforts of learners, instructors, and designers toward maximizing the benefit of simulation-based learning in a cost-efficient manner.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".