Developing a grounded theory for interprofessional collaboration acquisition using facilitator and actor perspectives in simulated wilderness medical emergencies
Bibliographic record
Abstract
CONTEXT: Interprofessional collaboration is a complex process that has the potential to transform patient care for the better in urban, rural and remote healthcare settings. Simulation has been found to improve participants' interprofessional competencies, but the mechanisms by which interprofessionalism is learned have yet to be understood. A rural wilderness medicine conference (WildER Med) in northern Ontario, Canada with simulated medical scenarios has been demonstrated to be effective in improving participants' collaboration without formal interprofessional education (IPE) curriculum. ISSUES: Interprofessionalism may be taught through rural and remote medical simulation, as done in WildER Med where participants' interprofessional competencies improved without any formal IPE curriculum. This learning may be attributed to the informal and hidden curriculum. Understanding the mechanism by which this rural educational experience contributed to participants' learning to collaborate requires insight into the events before, during and after the simulations. The authors drew upon feedback from facilitators and patient actors in one-on-one interviews to develop a grounded theory for how collaboration is taught and learned. LESSONS LEARNED: Sharing emerged as the core concept of a grounded theory to explain how team members acquired interprofessional collaboration competencies. Sharing was enacted through the strategies of developing common goals, sharing leadership, and developing mutual respect and understanding. Further analysis of the data and literature suggests that the social wilderness environment was foundational in enabling sharing to occur. Medical simulations in other rural and remote settings may offer an environment conducive to collaboration and be effective in teaching collaboration. When designing interprofessional education, health educators should consider using emergency response teams or rural community health teams to optimize the informal and hidden curriculum contributing to interprofessional learning.
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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 | 0.049 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.007 | 0.021 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".