Prediction of learning curves of wired and wireless intraoral scanners

Sci Rep. 2023 Dec 8;13(1):21661. doi: 10.1038/s41598-023-48855-2.

Abstract

This clinical study aimed to predict the learning curve of wireless and wired intraoral scanners (IOSs) and to compare the reduction patterns of working time. Overall, 14 participants were enrolled in the study. The intraoral scanning procedure was repeated four times, each using wireless and wired IOSs (i700; MEDIT). The work time from the first to the 600th iterations was predicted using the Wright model. Regarding statistical analysis, the Mann-Whitney U-test was performed for comparison between wireless and wired IOSs and between groups with and without an IOS usage experience, and the Friedman test was performed to evaluate the time reduction (α = 0.05). There was a significant difference between wireless and wired IOSs in the first (P = 0.008) and the third (P = 0.035) iterations. Moreover, the time for 600 iterations was statistically significantly different between wireless and wired IOSs (P < 0.05); however, there was no significant difference after the sixth iteration (e.g., seventh iteration: P = 0.062). In wireless IOS, no significant difference was found between participants with and without an IOS usage experience after the 34th iteration (P = 0.053). The difference in the learning effect between wireless and wired IOSs can be overcome by initial learning; however, an IOS usage experience can affect the learning time of wireless IOSs.

MeSH terms

  • Computer-Aided Design
  • Humans
  • Imaging, Three-Dimensional*
  • Learning Curve*
  • Models, Dental
  • Statistics, Nonparametric