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Early assessment with a virtual reality haptic simulator predicts performance in clinical practice
Loulwa M Al-Saud1,2, Faisal Mushtaq3, Richard P Mann4
1Operative Division, Department of Restorative Dental Sciences, King Saud University College of Dentistry, Riyadh, Saudi Arabia.
BMJ Simulation & Technology Enhanced Learning
|May 6, 2022
Summary
Virtual reality (VR) haptic simulators can predict dental student clinical performance, offering a data-driven approach to identify those needing early support. This technology surpasses traditional assessments in predicting future success in patient care.
Area of Science:
- Medical Education Technology
- Dental Simulation
- Sensorimotor Skill Assessment
Background:
- Clinical aptitude prediction traditionally relies on intellectual measures, neglecting crucial sensorimotor abilities.
- Sensorimotor skills are vital for safe and efficient practice in procedural medical and dental specialties.
- Virtual reality (VR) haptic simulators offer objective sensorimotor performance metrics and aid skill acquisition.
Purpose of the Study:
- To evaluate the predictive capability of VR haptic simulator performance for future clinical dental performance.
- To compare the predictive power of VR simulation against a traditional preclinical dental assessment.
Main Methods:
- A retrospective cohort study analyzed second-year dental students' performance on a haptic VR simulator.
- Student VR scores were correlated with their clinical performance involving patients two years later.
- Predictive ability was also assessed against a third-year phantom-head crown test.
Main Results:
- Averaged VR scores explained 14% of variance in clinic performance, significantly outperforming the traditional test (5%).
- High VR simulator performers were approximately 10 times more likely to excel in clinical assessments.
- VR scores showed predictive value, particularly in the first half of the academic year, with single-trial scores lacking correlation.
Conclusions:
- VR haptic simulators demonstrate significant potential for predicting clinical performance in dental education.
- This technology enables a data-driven strategy to identify students requiring early intervention and support.
- Objective sensorimotor assessment via VR can enhance the identification of training aptitude beyond cognitive measures.

