Performance and Perceptions of Health Care Professionals Using an Immersive Virtual Reality Tool for Home Care Training: Observational Feasibility and Acceptability Study
Bibliographic record
Abstract
BACKGROUND: Informal caregivers play a crucial role in home care and many lack formal training, potentially compromising patient safety. Immersive virtual reality (VR) offers an innovative approach to training by simulating real-life caregiving scenarios in a risk-free environment. Prior to implementation, the environments and the technique's feasibility and acceptability must be assessed by the professionals who will use it to train caregivers, establishing a performance benchmark based on experienced health care professionals. OBJECTIVE: This study aims to test feasibility and develop exploratory benchmarks and acceptability of immersive VR training for home caregiving tasks, using experienced professionals to establish a reference standard for execution quality. METHODS: This observational study was conducted in health care centers in Andalusia, the Valencian Community, and Madrid (Spain). A structured process was followed, including the identification of key home care tasks, the development of best practice guidelines, creation of immersive VR training materials, and the design of a performance evaluation rubric. Health care professionals (n=75) were recruited using a convenience sampling approach. They performed caregiving tasks in VR, and their performance was recorded and assessed using a standardized rubric, which included 205 predefined errors. Participants also completed a posttraining survey evaluating usability, comprehension, and perceived applicability to real-world caregiving. RESULTS: A total of 75 professionals participated, completing 257 caregiving simulations in a fully immersive VR environment. A total of 417 errors were identified (417/3142, 13.3% of the maximum number of predefined errors), with a mean average of 5.6 (SD 6.8) errors per participant. The most frequent errors occurred in medication management, insulin administration, diaper changing, broncho aspiration prevention, blood pressure monitoring, and hand hygiene. The perceived usefulness of VR training was rated 8.1 out of 10 points (SD 1.9), with 98.7% (74/75) of the participants stating that the time spent in the simulation was worthwhile and 85.3% (64/75) agreeing that the tasks were appropriately represented. CONCLUSIONS: Immersive VR training for informal caregivers is a feasible and well-accepted approach, demonstrating high perceived usefulness among health care professionals. The study establishes a preliminary benchmark for home caregiving task execution, providing a basis for future research evaluating informal caregivers' performance and targeted training interventions to enhance patient safety. Further studies are needed to explore the long-term impact of VR training on caregiver competence and home care quality.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".