Knowledge, Attitude and Practice of Artificial Intelligence Among Healthcare Professionals: An Online Cross-Sectional Survey

Abstract

Background: Deep learning-powered Artificial Intelligence-driven assistance offers enormous potential to improve healthcare by facilitating administrative work, diagnosis, and the treatment of chronic diseases. The gap between clinical values and the day-to-day realities of primary care practice might widen if AI is not successfully incorporated. Methods: A cross-sectional design was used to evaluate healthcare professionals' perceptions and understanding of AI within a clinical setting. The study was conducted among 456 Health care Workers from May to November 2024. Results: Among 456 participants, 55.7% were MBBS students/interns, and 37.9% were postgraduates/professionals. More than 50% supported AI integration, and 62.3% of MBBS students/interns believed AI would change their roles, compared to 30.3% of postgraduates. Additionally, 72.1% of MBBS students/interns felt AI might take over part of their roles, whereas 46.04% of postgraduates disagreed. AI usage varied, with 62% of MBBS students/interns rarely using it for research but 72.8% often using it for idea generation, while 60% of postgraduates found AI difficult to apply. The primary barrier to AI adoption was a lack of experience and understanding (59%), highlighting the need for improved AI literacy. Conclusion: Many participants had first-hand experience with AI tools and a basic comprehension of the technology, and the majority were aware of the expanding significance of AI in medicine. Despite respondents' favourable opinions of AI integration, questions concerning accuracy, dependability, and medicolegal implications persist, indicating the need for more study and approaches to deal with these problems.

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