Can large language models be trusted? Reliability and readability of responses to perinatal depression FAQs

Most LLMs demonstrated moderate to high reliability when responding to perinatal depression questions, supporting their potential as supplementary sources of health information. However, readability levels above recommended benchmarks suggest that current outputs may remain challenging for individuals with lower health literacy. While LLMs improve information accessibility, further improvements in readability, source attribution, and ethical transparency are needed to maximize public benefit and support equitable health communication. Future work should focus on defining and standardizing safety behaviors in high-risk mental health contexts to enable reliable clinical deployment.

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Publication Details

Journal
Frontiers in Public Health
Published
2026-02-23
DOI
https://doi.org/10.3389/fpubh.2026.1760872
Primary Topic
Health Literacy and Information Accessibility
Type
article
Field-Weighted Citation Impact
0.00
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article

Can large language models be trusted? Reliability and readability of responses to perinatal depression FAQs

Jingyi Huang, Hua Yu, Xinyue Wang, L Huang et al.
Frontiers in Public Health
Health Literacy and Information Accessibility
article

Can large language models be trusted? Reliability and readability of responses to perinatal depression FAQs

Jingyi Huang, Hua Yu, Xinyue Wang, L Huang, Hui Li, Junjian Chen, Junjie Wen
article en

Abstract

Most LLMs demonstrated moderate to high reliability when responding to perinatal depression questions, supporting their potential as supplementary sources of health information. However, readability levels above recommended benchmarks suggest that current outputs may remain challenging for individuals with lower health literacy. While LLMs improve information accessibility, further improvements in readability, source attribution, and ethical transparency are needed to maximize public benefit and support equitable health communication. Future work should focus on defining and standardizing safety behaviors in high-risk mental health contexts to enable reliable clinical deployment.

Frontiers in Public HealthVol. 14
Hope College (US), Harbin Medical University (CN), Guangxi Medical University (CN), University of Macau (MO), Guangxi University of Chinese Medicine (CN), Ruikang Affiliated Hospital of Guangxi Medical University (CN), Hope University (SO), Southwest Jiaotong University Hope College, Southwest Jiaotong University (CN)
Quality Education
Openalex Percentile: Top 49%
Health Literacy and Information Accessibility
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