Background Prediction of clinical training aptitude in medicine and dentistry is largely driven by measures of a student’s intellectual capabilities. The measurement of sensorimotor ability has lagged behind, despite being a key constraint for safe and efficient practice in procedure-based medical specialties. Virtual reality (VR) haptic simulators, systems able to provide objective measures of sensorimotor performance, are beginning to establish their utility in facilitating sensorimotor skill acquisition, and it is possible that they may also inform the prediction of clinical performance.
Methods A retrospective cohort study examined the relationship between student performance on a haptic VR simulator in the second year of undergraduate dental study with subsequent clinic performance involving patients 2 years later. The predictive ability was tested against a phantom-head crown test (a traditional preclinical dental assessment, in the third year of study).
Results VR scores averaged across the year explained 14% of variance in clinic performance, while the traditional test explained 5%. Students who scored highly on this averaged measure were ~10 times more likely to be high performers in the clinical crown test. Exploratory analysis indicated that single-trial VR scores did not correlate with real-world performance, but the relationship was statistically significant and strongest in the first half of the year and weakened over time.
Conclusions The data demonstrate the potential of a VR haptic simulator to predict clinical performance and open up the possibility of taking a data-driven approach to identifying individuals who could benefit from support in the early stages of training.
- virtual reality
- simulation-based education
- early warning score
- haptic simulation
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Contributors LMA-S, FM, MAM-W and MM initiated the project and designed the experiment. LMA-S, supported by IM, AB, CO and AK, acquired the data. LMA-S, FM and RPM analysed the data. FM, RPM and RH worked on interpreting the empirical data. All authors provided intellectual input in drafting and revising the paper.
Funding FM, RPM and MM-W hold Alan Turing Institute Fellowships. FM and MAM-W were supported by a research grant from the Engineering and Physical Sciences Research Council (EPSRC) (EP/R031193/1).
Competing interests None declared.
Ethics approval Ethical approval to access and analyse the students’ data following anonymisation (individual identifiers were replaced with unique random values) was obtained from DREC (Dental Research Ethics Committee) at the School of Dentistry, University of Leeds (DREC ref: 230915/LA/178).
Provenance and peer review Not commissioned; externally peer reviewed.
Data availability statement Data are available upon reasonable request.
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