Attitude, perception, and knowledge toward artificial intelligence among dental hygiene students and alumni: a cross-sectional survey study

Introduction: As Artificial Intelligence (AI) becomes an integral part of modern education, understanding the perspectives of healthcare students on AI is vital for their adaptation and future success. This study investigates the attitudes, perceptions, and knowledge toward AI among dental hygiene students and alumni, as well as their educational needs related to AI integration. Methods: A cross-sectional survey used a validated instrument adapted from existing literature. The survey was distributed to dental hygiene students and alumni at the University of Doha for Science and Technology. The Attitude Toward AI (ATAI) Scale was used to assess AI acceptance and fear. Participants’ perceptions of AI in health education and their educational priorities for the health curriculum were also explored. Descriptive statistics and regression analysis were employed to evaluate participant responses and identify predictors of AI acceptance. Results: A total of 101 participants responded (84.87% response rate). The majority of participants reported only basic AI knowledge (77.2%), and a substantial portion (68.3%) had not received formal AI training. Using the Attitude Toward AI (ATAI) Scale, this study found moderate AI acceptance (6.56 ± 1.90) and neutral-to-slight fear (4.85 ± 2.26). AI perception in health education suggests that while participants recognize the potential benefits of AI in health education, some remain neutral or uncertain about its practical implications (2.38 ± 1.33). AI for health-related research was rated as the highest priority for inclusion in health curricula (93.07%). Regression analysis revealed that perceptions of AI in health education significantly predicted AI acceptance (p = 0.0073, β = 0.676). Conclusion: This study found that dental hygiene students and alumni demonstrated moderate acceptance of artificial intelligence, low-to-basic AI knowledge, and substantial gaps in formal AI training, with perceptions of AI in health education emerging as the strongest predictor of acceptance. Although the findings are limited by the single-institution design and cross-sectional methodology, they provide the first empirical evidence on AI acceptance among dental hygiene professionals in Qatar. These results support the need for structured, discipline-specific AI education and highlight the importance of shaping positive educational perceptions. Future research should employ multi-institutional and longitudinal designs to examine how AI attitudes evolve with training and professional experience.