Evaluation of Mixed reality in undergraduate nursing education. A systematic review
Bibliographic record
Abstract
Abstract Background Mixed Reality is becoming more widespread in the training of nursing students because it allows students to face situations that are difficult to manage or that rarely occur in their practice, but for which they must be prepared. Our objective is to evaluate whether mixed reality improves nursing students' learning outcomes and satisfaction compared to simulation. Material and methods This systematic review was performed according to the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) The generic keywords used were “(nurses OR nurse OR nursing) AND mixed reality AND simulation”. The literature search was carried out in the PubMed and CINAHL databases between 2011 and 2021. After the review, 4 references were selected. Based on the study title and abstract, two independent authors selected potential. Whenever a study meets the inclusion criteria, the authors access the full text. To assess potential bias, all studies included in the review were evaluated with the Newcastle-Ottawa Quality Assessment Scale Results The search produced 54 papers but after reviewing only 4 were selected. Two studies were pretest post-test with a control group, while the other 2 were post-test only with no control group. Mixed reality was used in several settings (Maternal Health, Mental Health, CPR, and hospital ward) to increase the realism of simulations, increase confidence, reduce anxiety and stress of students in clinical situations. The results of the studies are contradictory, with poor quality studies showing positive effects, while studies with better quality and design showed poorer results. Conclusions Mixed reality is a very recent technique in nursing education. It is necessary to carry out well-designed studies of adequate size to evaluate in which contexts it is effective. Key messages Mixed reality is an emerging technology in education, but very few evaluations have been conducted. It is necessary to carry out well-designed studies to evaluateif Mixed reality it is effective in nursing education.
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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 | 0.092 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".