Efficacy of a Virtual 3D Simulation–Based Digital Training Module for Building Dental Technology Students’ Long-Term Competency in Removable Partial Denture Design: Prospective Cohort Study

队列 前瞻性队列研究 队列研究 医学 医学教育 医学物理学 物理疗法 外科 内科学 病理
作者
KeXin Liu,YaQian Xu,Chao-Yi Ma,Na Yu,Fa-Bing Tan,Yi Li,YaXin Bai,XiaoMing Fu,JiaWu Wan,DongQi Fan,HuBin Yin,M. Chen,HongJi Chen,Lin Jiang,Jinlin Song,Ping Ji,Xiaohan Zhao,MengWei Pang
出处
期刊:JMIR serious games [JMIR Publications Inc.]
卷期号:12: e46789-e46789
标识
DOI:10.2196/46789
摘要

Abstract Background Removable partial denture (RPD) design is crucial to long-term success in dental treatment, but shortcomings in RPD design training and competency acquisition among dental students have persisted for decades. Digital production is increasing in prevalence in stomatology, and a digital RPD (D-RPD) module, under the framework of the certified Objective Manipulative Skill Examination of Dental Technicians (OMEDT) system reported in our previous work, may improve on existing RPD training models for students. Objective We aimed to determine the efficacy of a virtual 3D simulation–based progressive digital training module for RPD design compared to traditional training. Methods We developed a prospective cohort study including dental technology students at the Stomatology College of Chongqing Medical University. Cohort 1 received traditional RPD design training (7 wk). Cohort 2 received D-RPD module training based on text and 2D sketches (7 wk). Cohort 3 received D-RPD module pilot training based on text and 2D sketches (4 wk) and continued to receive training based on 3D virtual casts of real patients (3 wk). RPD design tests based on virtual casts were conducted at 1 month and 1 year after training. We collected RPD design scores and the time spent to perform each assessment. Results We collected the RPD design scores and the time spent to perform each assessment at 1 month and 1 year after training. The study recruited 109 students, including 58 (53.2%) female and 51 male (56.8%) students. Cohort 1 scored the lowest and cohort 3 scored the highest in both tests (cohorts 1-3 at 1 mo: mean score 65.8, SD 21.5; mean score 81.9, SD 6.88; and mean score 85.3, SD 8.55, respectively; P <.001; cohorts 1-3 at 1 y: mean score 60.3, SD 16.7; mean score 75.5, SD 3.90; and mean score 90.9, SD 4.3, respectively; P <.001). The difference between cohorts in the time spent was not statistically significant at 1 month (cohorts 1-3: mean 2407.8, SD 1370.3 s; mean 1835.0, SD 1329.2 s; and mean 1790.3, SD 1195.5 s, respectively; P =.06) but was statistically significant at 1 year (cohorts 1-3: mean 2049.16, SD 1099.0 s; mean 1857.33, SD 587.39 s; and mean 2524.3, SD 566.37 s, respectively; P <.001). Intracohort comparisons indicated that the differences in scores at 1 month and 1 year were not statistically significant for cohort 1 (95% CI –2.1 to 13.0; P =.16), while cohort 3 obtained significantly higher scores 1 year later (95% CI 2.5-8.7; P =.001), and cohort 2 obtained significantly lower scores 1 year later (95% CI –8.8 to –3.9; P <.001). Conclusions Cohort 3 obtained the highest score at both time points with retention of competency at 1 year, indicating that progressive D-RPD training including virtual 3D simulation facilitated improved competency in RPD design. The adoption of D-RPD training may benefit learning outcomes.
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