ArticleNPJ digital medicine2026
The landscape of virtual simulation in undergraduate dental education with implications for artificial intelligence incorporation.
Article in NPJ digital medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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.
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Authors and funding
9 authors.
Funding
Abstract
Virtual simulation (VS) is pivotal in undergraduate dental education for cognitive and preclinical training. Expanding VS adoption and artificial intelligence (AI) incorporation necessitate an evidence synthesis to clarify current landscapes, challenges, and future directions. Following the PRISMA-ScR guidelines and Arksey and O'Malley's framework, this scoping review included 57 studies (2007-2025) to map the landscape of VS and its AI-driven future. The included VS systems could be broadly categorized into two generations, with first-generation systems supporting knowledge acquisition and second-generation systems supporting procedural skill development. VS applications spanned multiple dental subspecialties with uneven technological maturity and depth. With assessment of examinations, expert-rated performance, simulator-derived metrics, and learner-reported questionnaires, most studies reported that VS improved learner performance and confidence. Challenges persist regarding uncertain long-term knowledge retention, incomplete replication of clinical settings, resource-intensive implementation, and the limited role in education. This review further explored the implications of future AI-VS incorporation, including AI-driven virtual patients and tutors, fidelity enhancement, adaptive feedback, and personalized competency-based assessment.
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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.