Understanding Artificial Intelligence in Dental Nursing: An Online Survey on Familiarity, Attitudes, and Expectations

Abstract

To explore dental nurses' expectations and identify key factors influencing their familiarity, attitudes, and expectations regarding artificial intelligence, an anonymous online survey was conducted using a structured 23-item questionnaire, following Checklist for Reporting Results of Internet E-Surveys (CHERRIES) guidelines. Recruitment utilized purposive and snowball sampling methods, targeting nurses from diverse departments across public and private institutions. Statistical analyses, including χ 2 tests and generalized estimating equations, were used to explore associations between demographics, familiarity, and attitudes toward artificial intelligence. Questionnaires were collected from 14 different dental departments, including 5 public hospitals and 5 private stomatological clinics. A total of 816 valid responses were analyzed. Most respondents (68.9%) had limited exposure to artificial intelligence-based nursing tools. Familiarity with artificial intelligence was significantly associated with experience in artificial intelligence-related projects and work in specialized departments such as outpatient clinics. Although nurses acknowledged high costs and complexity as barriers, over 56.7% expressed a willingness to adopt artificial intelligence technologies, reflecting optimism about its future in nursing. Despite limited familiarity and accessibility, nurses demonstrate a positive attitude toward artificial intelligence applications. Addressing barriers such as cost, training, and usability will be critical to fostering broader adoption.

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