Interprofessional Training in Virtual Reality for Health Care: An Experimental Study on Procedural Knowledge and Willingness to Collaborate (Preprint)
Bibliographic record
Abstract
Abstract Background High-quality wound care requires early and effective interprofessional collaboration between medical, nursing, and pharmacy professionals. However, interprofessional education (IPE) in this context remains limited in higher education. Immersive virtual reality (iVR) seems to be a promising IPE tool, enabling a standardized, realistic, and safe learning environment that allows multiple learners from different professions to train together. However, its educational effectiveness likely depends on instructional design that supports learning while managing cognitive demands. Objective This study examined whether a newly developed interprofessional iVR wound-care training improves (1) procedural knowledge and (2) willingness to collaborate among medical, nursing, and pharmacy students, and how cognitive load relates to these outcomes. Methods A within-subjects design with a pre- and posttest was implemented with 116 students from medicine, nursing, and pharmacy. Students completed 2 iVR sessions (≈25 and 15 min) in interprofessional triads, addressing a pressure ulcer case. The training integrated step-by-step scaffolding for the wound care task and collaboration scripts to guide teamwork. Procedural knowledge and willingness to collaborate were assessed before and after the sessions, and cognitive load was measured after the sessions. Data were analyzed using repeated-measures analysis of covariances and a mediation model to test the preregistered effects. Results Procedural knowledge increased significantly from pre- to posttest ( F 1, 107 =26.19, P <.001, η² =.08). Cognitive load showed no significant effect on this gain. Willingness to collaborate did not change after the first session ( F 1, 80 =3.55, P =.063, η² =.01), and was unaffected by cognitive load. Exploratory analyses showed that willingness to collaborate was significantly higher after the second session ( t 64 =3.16, P =.007, mean difference=0.202). Effects on procedural knowledge and willingness to collaborate did not depend on the learner’s profession. Conclusions These findings suggest that the iVR training effectively supported learning by providing a clear structure and managing cognitive demands, enabling students from different professions to acquire procedural knowledge. The absence of cognitive load effects may suggest that the instructional design helped balance task complexity and guidance. The delayed increase in collaboration willingness further suggests that attitudinal change requires sustained, repeated engagement in interprofessional contexts rather than a single exposure. Notably, no profession-related differences emerged in either procedural knowledge or willingness to collaborate, indicating that the iVR training supported learners equally across professional backgrounds. This study highlights the potential of iVR as a scalable, theory-based approach to IPE that can support interprofessional learning and provide a structured environment for collaborative skill development. Future research should examine sustained effects and comparative effectiveness when iVR is implemented in routine curricular IPE settings beyond controlled study conditions.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".