ArticleBMC nursing2025
Modeling the evolution of virtual reality in nursing education: a BERTopic-based analysis of research trends and future directions.
Article in BMC nursing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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.
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Who cites it
2 citing papers in PubMed.
- Past, present, and future of virtual reality-based biological science education (2010-2025): a BERTopic-driven analysis.BMC medical education · 2026Article
- Mapping the evidence on virtual reality for dementia caregivers: a scoping review.Health education research · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study employs BERTopic, an advanced natural language processing (NLP) technique, to systematically analyze the thematic evolution and research hotspots of virtual reality (VR) applications in nursing education from 2008 to 2025. Using a corpus of 683 peer-reviewed articles from Web of Science, we applied BERTopic's transformer-based embedding and hierarchical clustering pipeline to identify latent topics, quantify their temporal trends, and visualize inter-topic relationships through uniform manifold approximation and projection (UMAP) dimensionality reduction. Three dominant research streams emerged: (1) technical applications, (2) humanistic skill development, and (3) specialized high-stakes training. The COVID-19 pandemic accelerated VR adoption, with publications surging by 95% in 2020. Topics evolution revealed a shift from feasibility studies (pre-2018) to outcome optimization (post-2020), particularly in AI-integrated virtual patients and haptic feedback systems. Instructors can leverage topic prominence data to prioritize VR curricular integration, while policymakers should address disparities in cultural adaptability research (only 12% of studies involved non-Western contexts). Notably, this study applies dynamic topic modeling in nursing education research, offering a data-driven framework for tracking technological adoption and predicting future trends.
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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.