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Public attitudes and practices toward using AI chatbots for healthcare assistance: a multinational cross-sectional study
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Public attitudes and practices toward using AI chatbots for healthcare assistance: a multinational cross-sectional study
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Public attitudes and practices toward using AI chatbots for healthcare assistance: a multinational cross-sectional study
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Journal Article
Public attitudes and practices toward using AI chatbots for healthcare assistance: a multinational cross-sectional study
2025
Overview
Background
Using artificial intelligence (AI) chatbots in healthcare can enhance patient care. However, misuse may lead to negative outcomes. Our study’s aim is to evaluate the practices and attitudes related to AI chatbots for healthcare assistance within the general population in the Arab region.
Methods
A population of 12 years old and above from 21 Arab countries was invited to complete a validated web-based questionnaire from 1 May to 1 June 2024. The survey consisted of four sections: demographics, identification, attitudes, and practices related to AI chatbots in healthcare assistance. We utilized Microsoft Excel and SPSS software for data entry and analysis. Descriptive statistics, chi-square tests, and binary logistic regression were used to analyze demographic associations and usage predictors for healthcare
Results
Among the 12,886 valid responses, the median age was 24 years (IQR: 21–31), with a female-to-male ratio of 2:1. Most were single (66.8%), from Egypt (11.2%), urban residents (81.2%), students (43.6%), university-educated (73.2%), or healthcare-affiliated (40.2%). While 72.5% were aware of AI chatbots, only 26.4% used them, primarily for health coaching (67.5%), self-medication (54.5%), self-diagnosis (44.1%), and mental support (48%). ChatGPT was the most used chatbot (22.65%) for healthcare assistance. Individuals with psychological or mental health issues had greater odds of chatbot use (Exp(B) = 1.343, 95% CI: 1.189–1.516,
p
< 0.001), while the strongest predictor was participation in AI-related training courses, which was associated with more than a threefold increase in odds (Exp(B) = 3.109, 95% CI: 2.715–3.559,
p
< 0.001).
Conclusion
This study highlighted varying attitudes and patterns regarding the use of AI-powered chatbots for healthcare assistance, from consultation to self-diagnosis and medication. The insights from this study can help policymakers, researchers, developers and healthcare professionals integrate AI chatbots more effectively into the existing healthcare system.
Clinical trial number
Not applicable.
