{"title":"Global ChatGPT interest across healthcare and education access","authors":"Amrit Kirpalani","doi":"10.1016/j.hlpt.2025.101061","DOIUrl":null,"url":null,"abstract":"<div><h3>Objectives</h3><div>The rapid adoption of AI tools like ChatGPT has transformed information access, particularly in healthcare. However, engagement with AI may be influenced by factors such as healthcare accessibility and educational resources, with potential implications for misinformation in low-resource settings. This study investigates the relationship between physician density, tertiary education enrollment, and national interest in ChatGPT.</div></div><div><h3>Methods</h3><div>A cross-sectional analysis was conducted using global datasets. Physician density, tertiary education enrollment, GDP, and internet penetration were sourced from WHO, UNESCO, and the World Bank, respectively. The primary outcome, ChatGPT interest scores, was derived from Google Trends. Pearson correlation and multiple linear regression analyses were used to explore associations, controlling for GDP and internet penetration. Logistic regression was employed as a sensitivity analysis, categorizing variables into high and low groups.</div></div><div><h3>Results</h3><div>Data from 100 countries were analyzed. A significant negative correlation was observed between physician density and ChatGPT interest (<em>r</em> = -0.32, <em>p</em> = 0.012). Multiple linear regression confirmed that lower physician density was significantly associated with higher ChatGPT interest (β = -0.2857, <em>p</em> = 0.045). Tertiary education enrollment showed no significant association with ChatGPT interest. Logistic regression supported these findings, with higher physician density significantly reducing the likelihood of high ChatGPT interest (OR = 0.214, <em>p</em> = 0.001).</div></div><div><h3>Conclusion</h3><div>Our study suggests that regions with fewer healthcare professionals may engage more with AI tools like ChatGPT, highlighting the need for careful integration of AI into healthcare systems to prevent misinformation and support equitable access to reliable health information.</div></div><div><h3>Public Interest Summary</h3><div>It is well known that people who have difficulty in accessing healthcare may turn to the internet for medical advice, but it is not yet known if artificial intelligence, like ChatGPT, is being adopted by users for this same purpose. Given the widespread use of ChatGPT, this study explored whether ChatGPT interest in different countries was related to the number of physicians in those countries. We found that in countries with fewer doctors per capita, public interest in ChatGPT tends to be higher. While this does not confirm that people are using ChatGPT specifically for medical advice, it raises important questions about how AI may be filling gaps in access to healthcare. Given the potential for AI to spread inaccurate information, these findings highlight the need for careful regulation to ensure AI tools are used responsibly and do not contribute to misinformation in healthcare.</div></div>","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"14 5","pages":"Article 101061"},"PeriodicalIF":3.7000,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Health Policy and Technology","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2211883725000899","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"HEALTH POLICY & SERVICES","Score":null,"Total":0}
引用次数: 0
Abstract
Objectives
The rapid adoption of AI tools like ChatGPT has transformed information access, particularly in healthcare. However, engagement with AI may be influenced by factors such as healthcare accessibility and educational resources, with potential implications for misinformation in low-resource settings. This study investigates the relationship between physician density, tertiary education enrollment, and national interest in ChatGPT.
Methods
A cross-sectional analysis was conducted using global datasets. Physician density, tertiary education enrollment, GDP, and internet penetration were sourced from WHO, UNESCO, and the World Bank, respectively. The primary outcome, ChatGPT interest scores, was derived from Google Trends. Pearson correlation and multiple linear regression analyses were used to explore associations, controlling for GDP and internet penetration. Logistic regression was employed as a sensitivity analysis, categorizing variables into high and low groups.
Results
Data from 100 countries were analyzed. A significant negative correlation was observed between physician density and ChatGPT interest (r = -0.32, p = 0.012). Multiple linear regression confirmed that lower physician density was significantly associated with higher ChatGPT interest (β = -0.2857, p = 0.045). Tertiary education enrollment showed no significant association with ChatGPT interest. Logistic regression supported these findings, with higher physician density significantly reducing the likelihood of high ChatGPT interest (OR = 0.214, p = 0.001).
Conclusion
Our study suggests that regions with fewer healthcare professionals may engage more with AI tools like ChatGPT, highlighting the need for careful integration of AI into healthcare systems to prevent misinformation and support equitable access to reliable health information.
Public Interest Summary
It is well known that people who have difficulty in accessing healthcare may turn to the internet for medical advice, but it is not yet known if artificial intelligence, like ChatGPT, is being adopted by users for this same purpose. Given the widespread use of ChatGPT, this study explored whether ChatGPT interest in different countries was related to the number of physicians in those countries. We found that in countries with fewer doctors per capita, public interest in ChatGPT tends to be higher. While this does not confirm that people are using ChatGPT specifically for medical advice, it raises important questions about how AI may be filling gaps in access to healthcare. Given the potential for AI to spread inaccurate information, these findings highlight the need for careful regulation to ensure AI tools are used responsibly and do not contribute to misinformation in healthcare.
期刊介绍:
Health Policy and Technology (HPT), is the official journal of the Fellowship of Postgraduate Medicine (FPM), a cross-disciplinary journal, which focuses on past, present and future health policy and the role of technology in clinical and non-clinical national and international health environments.
HPT provides a further excellent way for the FPM to continue to make important national and international contributions to development of policy and practice within medicine and related disciplines. The aim of HPT is to publish relevant, timely and accessible articles and commentaries to support policy-makers, health professionals, health technology providers, patient groups and academia interested in health policy and technology.
Topics covered by HPT will include:
- Health technology, including drug discovery, diagnostics, medicines, devices, therapeutic delivery and eHealth systems
- Cross-national comparisons on health policy using evidence-based approaches
- National studies on health policy to determine the outcomes of technology-driven initiatives
- Cross-border eHealth including health tourism
- The digital divide in mobility, access and affordability of healthcare
- Health technology assessment (HTA) methods and tools for evaluating the effectiveness of clinical and non-clinical health technologies
- Health and eHealth indicators and benchmarks (measure/metrics) for understanding the adoption and diffusion of health technologies
- Health and eHealth models and frameworks to support policy-makers and other stakeholders in decision-making
- Stakeholder engagement with health technologies (clinical and patient/citizen buy-in)
- Regulation and health economics