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
Master of Public Health, Bangladesh Open University, Gazipur, Bangladesh.
Master of Public Health, Daffodil International University, Dhaka, Bangladesh.
Heliyon. 2024 Nov 29;10(23):e40775. doi: 10.1016/j.heliyon.2024.e40775. eCollection 2024 Dec 15.
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 < 0.001), as well as negative attitudes with poor knowledge (r = 0.65, P < 0.001).
The study highlights the critical need for targeted educational interventions to bridge the knowledge gaps among healthcare professionals regarding AI adoption. The findings reveal that younger healthcare workers, those in full-time employment, and individuals with exposure to AI through conferences or research are more likely to possess good knowledge and hold positive attitudes towards AI integration. These results suggest that policies and training programs must be tailored to address specific demographic differences, ensuring that all groups are equipped to engage with AI technologies. Moreover, the study emphasizes the importance of continuous professional development, which could foster a workforce capable of harnessing AI's potential to improve patient outcomes and healthcare efficiency.
医疗保健与人工智能（AI）的融合开启了医疗实践的变革时代。然而，医护人员对在医疗保健中采用人工智能的知识和态度目前尚不清楚。
主要目标是调查孟加拉国达卡市医护人员对在医疗保健中采用人工智能的知识和态度。
采用横断面研究设计，结合随机和便利抽样技术的双重方法来选择参与者。通过文献综述、内容效度和可靠性评估（Cronbach's alpha = 0.85）确保效度，并通过探索性因素分析确定强大的潜在因素。数据分析涉及描述性和推断性统计，包括Fisher精确检验、多元逻辑回归和Pearson相关分析，使用STATA软件进行，以全面了解医护人员在医疗保健中采用人工智能的情况。
本研究表明，年龄是一个重要因素，18 - 25岁和26 - 35岁的个体具有良好知识和积极态度的几率更高（调整后比值比[AOR] 1.56，95%置信区间[CI] 1.12 - 2.43；AOR 1.42，95% CI 0.98 - 2.34）。医生（AOR 1.08，95% CI 0.78 - 1.89）、医院工作人员（AOR 1.29，95% CI 0.92 - 2.09）和全职员工（AOR 1.45，95% CI 1.12 - 2.34）的几率更高。参加人工智能会议（AOR 1.27，95% CI 0.92 - 2.23）和通过研究文章/期刊学习（AOR 1.31，95% CI 0.98 - 2.09）与良好知识和积极态度呈正相关。本研究还强调了知识与积极态度之间的强相关性（r = 0.89，P < 0.001），以及消极态度与知识匮乏之间的相关性（r = 0.65，P < 0.001）。
该研究强调了有针对性的教育干预对于弥合医护人员在人工智能采用方面知识差距的迫切需求。研究结果表明，年轻的医护人员、全职员工以及通过会议或研究接触过人工智能的个体更有可能拥有良好的知识并对人工智能整合持积极态度。这些结果表明，政策和培训计划必须针对特定的人口统计学差异进行调整，确保所有群体都有能力参与人工智能技术。此外，该研究强调了持续专业发展的重要性，这可以培养一支能够利用人工智能潜力改善患者治疗效果和医疗保健效率的劳动力队伍。
