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.
Authors
- Jingyi Huang (ORCID: https://orcid.org/0000-0002-1209-9699)
- Hua Yu
- Xinyue Wang
- L Huang
- Hui Li
- Junjian Chen
- Junjie Wen
Institutions
- 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)
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