Predicting novice dental students' performances in conventional simulation: A prospective pilot study using haptic exercises
Year: 2024
Type: article
Study design: Observational Study
Abstract: Background/purpose: While haptic simulators in preclinical dentistry show promise, few studies predict novice dental students' performance in conventional simulations using haptic exercises. This study aimed to explore associations between (i) the number of failures in haptic exercises, (ii) the haptic performance index, and (iii) the quality of prosthetic preparation for cast crowns. Additionally, the students' perceptions regarding the use of the VirTeaSy Dental® haptic simulator was analyzed. Materials and methods: Forty novice students were randomly selected from the Dental Faculty of Nantes University in September 2022 (mean age: 19.7 ± 1.8 years). They completed four haptic exercises using the VirTeaSy Dental® simulator and prepared cast crowns on pedagogical phantom-mounted models. Data on haptic variables, prosthetic preparation quality scores, and the number of failed/successful haptic exercises were collected. Correlation analyses were conducted, and the mean preparation quality score was compared between students who failed and those who passed the haptic exercises. A questionnaire assessing the students' perceptions when using VirTeaSy Dental® was completed. Results: < 0.05). No correlation was observed for the haptic performance index. Students reported that the VirTeaSy simulator positively impacted their learning of milling gestures. Conclusion: The number of haptic exercise failures can predict performance in conventional simulations and help identify students with manual dexterity issues, guiding personalized preclinical training adjustments.
Source: Journal of Dental Sciences
Institutions: Inserm, Centre Hospitalier Universitaire de Nantes, Oniris, Laboratoire Motricité, Interactions, Performance, Université de Nantes, Université d'Angers, Nantes Université, Le Mans Université, Centre de Recherche en Éducation de Nantes, Université Laval, Laboratoire d’Informatique de l’Université du Mans
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $1,200
Funder: Agence Nationale de la Recherche
OpenAlex ID: W4404296633
