Healthcare workers' knowledge and attitudes regarding artificial intelligence adoption in healthcare: A cross-sectional study

• Published in: Heliyon 2024-12, Vol.10 (23), p.e40775, Article e40775
• Main Authors: Khan Rony, Moustaq Karim, Akter, Khadiza, Nesa, Latifun, Islam, Md Tawhidul, Johra, Fateha Tuj, Akter, Fazila, Uddin, Muhammad Join, Begum, Jeni, Noor, Md. Abdun, Ahmad, Sumon, Tanha, Sabren Mukta, Khatun, Most. Tahmina, Bala, Shuvashish Das, Parvin, Mst. Rina
• Format: Article
• Language: English
• Subjects: Artificial intelligence; Attitude; Healthcare workers; Knowledge; Medical practice; Technology
• ISSN: 2405-8440; 2405-8440
• DOI: 10.1016/j.heliyon.2024.e40775

The convergence of healthcare and artificial intelligence (AI) introduces a transformative era in medical practice. However, the knowledge and attitudes of healthcare workers concerning the adoption of artificial intelligence in healthcare are currently unknown. The primary objective was to investigate the knowledge and attitudes of healthcare professionals in Dhaka city, Bangladesh, regarding the adoption of AI in healthcare. A cross-sectional research design was employed, incorporating a dual-method approach to select participants using randomness and convenience sampling techniques. Validity was ensured through a literature review, content validity, and reliability assessment (Cronbach's alpha = 0.85), and exploratory factor analysis identified robust underlying factors. Data analysis involved descriptive and inferential statistics, including Fisher's exact tests, multivariate logistic regression, and Pearson correlation analysis, conducted using STATA software, providing a comprehensive understanding of healthcare workers' AI adoption in healthcare. This study revealed that age was a significant factor, with individuals aged 18–25 and 26–35 having higher odds of good knowledge and positive attitudes (AOR 1.56, 95 % CI 1.12–2.43; AOR 1.42, 95 % CI 0.98–2.34). Physicians (AOR 1.08, 95 % CI 0.78–1.89), hospital workers (AOR 1.29, 95 % CI 0.92–2.09), and full-time employees (AOR 1.45, 95 % CI 1.12–2.34) exhibited higher odds. Attending AI conferences (AOR 1.27, 95 % CI 0.92–2.23) and learning through research articles/journals (AOR 1.31, 95 % CI 0.98–2.09) were positively associated with good knowledge and positive attitudes. This research also emphasized the strong correlations between knowledge and positive attitudes (r = 0.89, P