Extended Reality in Nursing Professional Development: A Scoping Review of Continuing Education Applications for Practicing Nurses
Bibliographic record
Abstract
BACKGROUND: Extended reality (XR), encompassing virtual, augmented, and mixed reality, creates immersive educational environments that connect theory with practice, and it is increasingly used in continuing professional development. This scoping review examines current literature on XR technologies for nursing professional development. METHOD: Literature published between January 2022 and March 2025 was synthesized from the MEDLINE, Scopus, and CINAHL databases. RESULTS: Twenty-five studies met the inclusion criteria, spanning 10 countries, with sample sizes ranging from seven to 1,868 nurses. Virtual reality was the predominant modality (84% of interventions), mostly in hospital settings. Five primary themes emerged: (1) learning outcomes and educational effectiveness, (2) technical and implementation challenges, (3) realism and fidelity considerations, (4) specialized clinical applications, and (5) user experience and engagement. CONCLUSION: Interventions that used XR improved clinical knowledge, confidence, and procedural skills, with some studies reporting advantages over traditional methods, despite challenges such as cybersickness, infrastructure limits, financial constraints, and limited haptic feedback.
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 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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".