SynthesisFrontiers in medicine2024
A systematic review of immersive educational technologies in medical physics and radiation physics.
Synthesis in Frontiers in medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Development and Educational Evaluation of a Radiation Visualization System in a Virtual Reality Training Module for Radiopharmaceutical Administration: Mixed Methods Study of Students' Learning Experiences.JMIR medical education · 2026Article
- Article
- A Comprehensive Review of Food and Drug Administration (FDA)-Cleared Virtual Reality Technologies in Radiology.Cureus · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: This systematic review aims to analyze and synthesize the current state of research on the role of immersive technologies, specifically augmented reality (AR), virtual reality (VR), and mixed reality (MR), in medical physics and radiation physics education. The primary focus is to evaluate their impact on learning outcomes, performance, and engagement across various educational contexts. Methods: We conduct a comprehensive search of four major databases: Scopus, Web of Science, PubMed, and IEEE Xplore, covering the period from 2012 to 2023. A total of 316 articles are initially identified. After removing duplicates and screening for relevance based on titles and abstracts, 107 articles are selected for full-text review. Finally, 37 articles met the inclusion criteria and are included in the analysis. The review follows the PRISMA guidelines and utilizes the PICOS framework to structure the research question. Analysis: Data extraction focuses on key variables such as the type of immersive technology used, educational context, study design, participant demographics, and measured outcomes. The studies are analyzed for their reported effects on learning outcomes, performance, and engagement. Results: The review found that immersive technologies significantly enhance learning outcomes and engagement. Specifically, 36.4% of the studies reported increased engagement, while 63.6% of studies focusing on practical skills noted performance improvements. The use of AR, VR, and MR showed broad applicability across different educational levels, from undergraduate courses to professional training programs. Conclusion: Immersive technologies have considerable potential to transform medical and radiation physics. They enhance student engagement, improve learning outcomes, and boost performance in practical skills. Nevertheless, future research should focus on standardizing methodologies, expanding participant demographics, and exploring long-term impacts on skill retention and clinical practice. This review provides a valuable resource for guiding future research and implementing innovative educational strategies in the dynamic fields of medical physics and radiation physics.
Indexed as
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.