Evidence map›Paper›PMID 41986670›Full record

ArticleJournal of perinatology : official journal of the California Perinatal Association2026

Comparing physician and artificial intelligence chatbot responses to preterm infant care questions posted to a public medical consultation forum: evaluation study.

Xiaoli Tang, Xiaochen Yang, Daqiao Zhu, Nanping Shen, Yingjia Qian, Junyi Shen, Sha Sha, Wenzhe Hua

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Article in Journal of perinatology : official journal of the California Perinatal Association, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

8 authors.

Xiaoli Tang *Neonatology Department, Shanghai Children's Medical Center, National Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Xiaochen Yang *Neonatology Department, Shanghai Children's Medical Center, National Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Daqiao ZhuShanghai Jiao Tong University School of Nursing, Shanghai, China.
Nanping ShenNursing Department, Shanghai Children's Medical Center, National Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Yingjia QianShanghai Jiao Tong University School of Nursing, Shanghai, China.ORCID http://orcid.org/0009-0006-2463-3218
Junyi ShenNeonatology Department, Shanghai Children's Medical Center, National Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Sha Sha *Neonatology Department, Shanghai Children's Medical Center, National Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China. shasha@scmc.com.cn.
Wenzhe Hua *Shanghai Jiao Tong University School of Nursing, Shanghai, China. huawenzhe1992@163.com.

Funding

National Natural Science Foundation of China (National Science Foundation of China) 72104142National Natural Science Foundation of China (National Science Foundation of China) 72364011
6 · The paper itself

Abstract

objectivesThis study aims to compare the preterm infant care advice generated by ChatGPT with responses from neonatologists in an online medical consultation forum. STUDY

designThis cross-sectional study involving 22 evaluators (12 experienced neonatologists and 10 lay users) compared the responses of an AI chatbot (ChatGPT 4o) and online human experts to 60 preterm infant care-related questions from the "Doctor DingXiang" platform accessed in August 2024. Quantitative indicators, including readability, helpfulness, understandability, intent capture, empathy, actionability, accuracy and safety, were used for comparison. Qualitative content analyses were conducted to reveal further more detailed situational information about the differences between them.

resultsThe mean[SD] score for ChatGPT was higher than human experts on the dimensions of helpfulness (4.07 [0.78] vs 3.50 [1.04]), understandability (4.12 [0.73] vs 3.70 [1.01]), intent capture (4.12 [0.75] vs 3.62 [1.01]), empathy (3.98 [0.73] vs 3.45 [1.05]), actionability (3.97 [0.83] vs 3.37 [1.11]), accuracy (3.97 [0.73] vs 3.32 [1.01]) and safety (3.96 [0.72] vs 3.37 [0.97]). (all P <.001) ChatGPT's responses had few instances of low ratings than human experts' responses. ChatGPT provided more comprehensive and elaborative information, though its responses exhibited higher semantic richness and were more difficult to read. In contrast, human experts were better at offering personalized advice and emotional support, adjusting responses based on specific contexts.

conclusionChatGPT can provide satisfactory responses to neonatal medical inquiries. However, further improvements are necessary to enhance the precision, decision support, and contextual awareness.

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.