Comparing Virtual Reality Trauma Training Across Diverse Clinical Backgrounds: A Mixed-Methods Study in Canada And India
Bibliographic record
Abstract
OBJECTIVE: Virtual reality (VR) simulation is increasingly used in trauma training as it offers an immersive, cost-effective alternative to traditional simulation; however, its impact may differ between low- and high-resource settings due to resource and training disparities. This study aims to assess the technology acceptance, effectiveness, usability, acceptability and confidence gains of a VR-based pediatric trauma training module in India and Canada, correlating demographics and prior experience to learning outcomes and cybersickness. DESIGN: A prospective quasi-experimental study was done. Participants completed assessments using the Technology Acceptance Model (assessing perceived usefulness, ease of use, and intention to adopt VR), System Usability Scale, VR Sickness Questionnaire, and a confidence survey. SETTING: Participants attended a virtual reality trauma training course. These courses were held at McGill University's Steinberg Center for Simulation and Interactive Learning, Canada in May and August 2024 and at the Christian Medical College Ludhiana, India in December 2024. PARTICIPANTS: Sixty participants aged 25-35 years old (paramedics, medical officers, nurses, emergency technicians, and medical students) participated in a VR-based pediatric trauma training simulation module in India (n = 27) and Canada (n = 33). RESULTS: 67% of participants had no VR experience and 48% had no previous trauma training. No significant interactions were seen by gender, age, or prior VR use. Novices without trauma training reported higher TAM scores in all categories. The SUS and VRSQ scores did not differ by prior trauma training. Confidence gains before and after simulation were significantly lower in the group with prior trauma training (p < 0.001). While previous VR experience was similar in both Canada and India (33%), formal simulation training was reported by 85% of Canadians, but only by 11.1% of Indians (p ≤ 0.0001). The mean perceived usefulness of the module was also much higher for Indians than for Canadians (82% vs. 65.6%, respectively; p ≤ 0.0011), while the mean ease of use scores were 57.8% and 70.4% (p ≤ 0.0201), respectively. Confidence in trauma management increased by 14.4% in Canada and by 30.6% in India (p ≤ 0.0001). The higher rate of usefulness, ease-of-use, and confidence increase in India suggest VR had a greater impact in that setting. CONCLUSION: VR is a feasible and accepted tool for pediatric trauma training, with the greatest benefit seen in resource-limited settings and among novices. Minimal cybersickness supports its use as an adjunct to standard methods. VR may help address gaps in trauma education, especially where prior simulation experience is limited.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".