m+Medelevator.RU
← Поиск публикаций
The European journal of prosthodontics and restorative dentistry · 2025

Does the Learning Curve for Intraoral Scanning Vary Depending on the Device?

СтатьяРандомизированное исследованиеСравнительное исследованиеНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…

История · было → стало

Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.

Borges M S N, Cardoso L, Rea M T, Pedrazzi V, Tirapelli C

Аннотация

OBJECTIVES: Digital impressions using intraoral scanners (IOS) are replacing conventional impressions, requiring a learning process. This study compared the learning curves of 29 dentists with no prior IOS experience, randomly assigned to groups: Eagle, Omnicam- AF, and IS-3700.

METHODS: After a lecture, participants performed three full scans (maxilla, mandible, and occlusion record) on a phantom and completed a survey about their experience. Scanning times to achieve adequate scans were recorded, and Wright's model was used to estimate the number of trials required for proficiency. Statistical analyses used Kruskal-Wallis and Chi-Square tests.

RESULTS: Proficiency was achieved after 10 trials with Eagle and 11 trials with Omnicam-AF and IS-3700. Participants using IS- 3700 reached the plateau faster (167.9 s) than those using Eagle (245.5 s, P=0.041) and Omnicam-AF (260.6 s, P=0.014). While all groups appreciated the time-saving benefits over conventional impressions, 60-70% identified the need for further training.

CONCLUSION: Despite similar trials required for proficiency, differences in average scanning times suggest that IOS characteristics may influence learning efficiency and user perceptions.

CLINICAL RELEVANCE: Understanding learning curves and device-specific performance can help optimize IOS training programs and guide clinicians in adopting digital workflows effectively.

Предметные рубрики MeSH