Proficiency, Clarity, and Objectivity of Large Language Models Versus Specialists’ Knowledge on COVID-19's Impacts in Pregnancy: Cross-Sectional Pilot Study

The study highlights varying knowledge levels of LLMs in relation to COVID-19 and pregnancy. ChatGPT-3.5 showed the least knowledge and alignment with scientific evidence. Readability and complexity analyses suggest that each AI's approach was tailored to specific audiences, with ChatGPT versions being more suitable for specialized readers and Microsoft Copilot for the general public. Sentiment analysis revealed notable variations in the way LLMs communicated critical information, underscoring the essential role of neutral and objective health care communication in ensuring that pregnant women, particularly vulnerable during the COVID-19 pandemic, receive accurate and reassuring guidance. Overall, ChatGPT-4, Microsoft Copilot, and Google Bard generally provided accurate, updated information on COVID-19 and vaccines in maternal and fetal health, aligning with health guidelines. The study demonstrated the potential role of AI in supplementing health care knowledge, with a need for continuous updating and verification of AI knowledge bases. The choice of AI tool should consider the target audience and required information detail level.

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Publication Details

Journal
JMIR Formative Research
Published
2025-01-09
DOI
https://doi.org/10.2196/56126
Citations
2
Primary Topic
COVID-19 Impact on Reproduction
Type
article
Field-Weighted Citation Impact
4.11
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article

Proficiency, Clarity, and Objectivity of Large Language Models Versus Specialists’ Knowledge on COVID-19's Impacts in Pregnancy: Cross-Sectional Pilot Study

Raymond Farah, Rola Khamisy‐Farah, Łukasz Szarpak, Ruba Tuma et al.
2 citations
JMIR Formative Research
COVID-19 Impact on Reproduction
4.11
article

Proficiency, Clarity, and Objectivity of Large Language Models Versus Specialists’ Knowledge on COVID-19's Impacts in Pregnancy: Cross-Sectional Pilot Study

Raymond Farah, Rola Khamisy‐Farah, Łukasz Szarpak, Ruba Tuma, Nicola Luigi Bragazzi, Francesco Chirico, Hisham Atwan, Michèle Buchinger
article en
2 citations

Abstract

The study highlights varying knowledge levels of LLMs in relation to COVID-19 and pregnancy. ChatGPT-3.5 showed the least knowledge and alignment with scientific evidence. Readability and complexity analyses suggest that each AI's approach was tailored to specific audiences, with ChatGPT versions being more suitable for specialized readers and Microsoft Copilot for the general public. Sentiment analysis revealed notable variations in the way LLMs communicated critical information, underscoring the essential role of neutral and objective health care communication in ensuring that pregnant women, particularly vulnerable during the COVID-19 pandemic, receive accurate and reassuring guidance. Overall, ChatGPT-4, Microsoft Copilot, and Google Bard generally provided accurate, updated information on COVID-19 and vaccines in maternal and fetal health, aligning with health guidelines. The study demonstrated the potential role of AI in supplementing health care knowledge, with a need for continuous updating and verification of AI knowledge bases. The choice of AI tool should consider the target audience and required information detail level.

JMIR Formative ResearchVol. 9
Università Cattolica del Sacro Cuore (IT), John Paul II Catholic University of Lublin (PL), University of Parma (IT), Bar-Ilan University (IL), Baylor College of Medicine (US), York University (CA), Hebrew University of Jerusalem (IL), Western Galilee Hospital (IL), Kaplan Medical Center (IL), Sol Plaatje University (ZA)
Gender equality
Openalex Percentile: Top 10%
COVID-19 Impact on Reproduction
4.11
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