Oral surgery, oral medicine, oral pathology and oral radiology · 2023
Interactive computer-assisted learning as an educational method for learning pediatric interproximal dental caries identification.
Многоцентровое исследованиеСтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
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Ошибки и ограничения
История · было → стало
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Goertzen Erin, Casas Michael J, Barrett Edward J, Perschbacher Susanne, Pusic Martin, Boutis Kathy
Аннотация
OBJECTIVE: We developed a web-based tool to measure the amount and rate of skill acquisition in pediatric interproximal caries diagnosis among pre- and postdoctoral dental students and identified variables predictive for greater image interpretation difficulty.
STUDY DESIGN: In this multicenter prospective cohort study, a convenience sample of pre- and postdoctoral dental students participated in computer-assisted learning in the interpretation of bitewing radiographs of 193 children. Participants were asked to identify the presence or absence of interproximal caries and, where applicable, locate the lesions. After every case, participants received specific visual and text feedback on their diagnostic performance. They were requested to complete the 193-case set but could complete enough cases to achieve a competency performance standard of 75% accuracy, sensitivity, and specificity.
RESULTS: Of 130 participants, 62 (47.7%) completed all cases. The mean change from initial to maximal diagnostic accuracy was +15.3% (95% CI, 13.0-17.7), sensitivity was +10.8% (95% CI, 9.0-12.7), and specificity was +15.5% (95% CI, 12.9-18.1). The median number of cases completed to achieve competency was 173 (interquartile range, 82-363). Of these 62 participants, 45 (72.6%) showed overall improvement in diagnostic accuracy. Greater numbers of interproximal lesions (P < .001) and the presence of noninterproximal caries (P < .001) predicted greater interpretation difficulty.
CONCLUSIONS: Computer-assisted learning led to improved diagnosis of interproximal caries on bitewing radiographs among pre- and postdoctoral dental students.
STUDY DESIGN: In this multicenter prospective cohort study, a convenience sample of pre- and postdoctoral dental students participated in computer-assisted learning in the interpretation of bitewing radiographs of 193 children. Participants were asked to identify the presence or absence of interproximal caries and, where applicable, locate the lesions. After every case, participants received specific visual and text feedback on their diagnostic performance. They were requested to complete the 193-case set but could complete enough cases to achieve a competency performance standard of 75% accuracy, sensitivity, and specificity.
RESULTS: Of 130 participants, 62 (47.7%) completed all cases. The mean change from initial to maximal diagnostic accuracy was +15.3% (95% CI, 13.0-17.7), sensitivity was +10.8% (95% CI, 9.0-12.7), and specificity was +15.5% (95% CI, 12.9-18.1). The median number of cases completed to achieve competency was 173 (interquartile range, 82-363). Of these 62 participants, 45 (72.6%) showed overall improvement in diagnostic accuracy. Greater numbers of interproximal lesions (P < .001) and the presence of noninterproximal caries (P < .001) predicted greater interpretation difficulty.
CONCLUSIONS: Computer-assisted learning led to improved diagnosis of interproximal caries on bitewing radiographs among pre- and postdoctoral dental students.