ChatGPT’s assessment of the social determinants of hypertension and chronic kidney disease

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ChatGPT’s assessment of the social determinants of hypertension and chronic kidney disease

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Co-author 1

Sara Ramdani sara.ramdani001@gmail.com Faculty of Medicine and Pharmacy of Oujda, Mohammed First University, Oujda Laboratory of Epidemiology, Clinical Research and Public Health Oujda Morocco -

Co-author 2

Sofía Sánchez soofiamoraless@gmail.com Faculty of Medicine, Autonomous University of Nuevo León Faculty of Medicine, Autonomous University of Nuevo León Nuevo León Mexico -

Co-author 3

Ismail Chergui ismachergui@gmail.com Laboratory of Epidemiology, Clinical Research and Public Health Faculty of Medicine and Pharmacy of Oujda, Mohammed First University Oujda Morocco -

Co-author 4

Intissar Haddiya intissarhaddiya@yahoo.fr Faculty of Medicine and Pharmacy of Oujda, Mohammed First University Department of Nephrology, Mohammed VI University Hospital, Faculty of Medicine and Pharmacy of Oujda, Mohammed First University Oujda Morocco * Faculty of Medicine and Pharmacy of Oujda, Mohammed First University Laboratory of Epidemiology, Clinical Research and Public Health Oujda Morocco

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Introduction

Hypertension (HTN) and Chronic Kidney Disease (CKD) remain two of the most prevalent and interlinked global health challenges, both deeply influenced by social determinants such as income, education, housing, and healthcare access. Despite their shared determinants, public communication on these issues remains limited, particularly in underserved populations.

Methods

Our cross-sectional study analyzed ChatGPT’s ability to explain the social determinants of HTN and CKD through a structured content evaluation. Sixty questions—thirty per condition—were developed across six key domains: socioeconomic status, education, environment, healthcare access, culture, and policy. Three experts independently assessed the responses using a seven-criteria rubric (0–5 scale) evaluating relevance, clarity, comprehensiveness, scientific accuracy, audience fit, internal consistency, and reproducibility. Comparative analysis examined potential differences in performance between HTN- and CKD-related outputs.

Results

ChatGPT demonstrated strong and consistent performance across both HTN and CKD domains, with an overall mean score above 90%. HTN-related responses scored highest in content relevance (96%) and internal consistency (96%), while CKD responses excelled in scientific language (95%) and comprehensiveness (94%). Minor variations in audience fit (91%) and reproducibility (92%) reflected contextual and terminology-specific nuances. Overall, no significant difference was observed between the two conditions, confirming ChatGPT’s robustness and reliability in explaining the social determinants of chronic diseases with clarity, precision, and scientific rigor.

Conclusion

ChatGPT showed strong and consistent performance in explaining the social determinants of HTN and CKD. Its clear, evidence-based, and accessible outputs highlight its promise as a scalable tool for health education. Nonetheless, expert validation and ethical oversight remain essential to ensure accuracy, equity, and contextual reliability.

Kewords