Ensuring Accuracy and Equity in Vaccination Information From ChatGPT and CDC: Mixed-Methods Cross-Language Evaluation.

Background: In the digital age, large language models (LLMs) like ChatGPT have emerged as important sources of health care information. Their interactive capabilities offer promise for enhancing health access, particularly for groups facing traditional barriers such as insurance and language constraints. Despite their growing public health use, with millions of medical queries processed weekly, the quality of LLM-provided information remains inconsistent. Previous studies have predominantly assessed ChatGPT's English responses, overlooking the needs of non-English speakers in the United States. This study addresses this gap by evaluating the quality and linguistic parity of vaccination information from ChatGPT and the Centers for Disease Control and Prevention (CDC), emphasizing health equity.

Objective: This study aims to assess the quality and language equity of vaccination information provided by ChatGPT and the CDC in English and Spanish. It highlights the critical need for cross-language evaluation to ensure equitable health information access for all linguistic groups.

Methods: We conducted a comparative analysis of ChatGPT's and CDC's responses to frequently asked vaccination-related questions in both languages. The evaluation encompassed quantitative and qualitative assessments of accuracy, readability, and understandability. Accuracy was gauged by the perceived level of misinformation; readability, by the Flesch-Kincaid grade level and readability score; and understandability, by items from the National Institutes of Health's Patient Education Materials Assessment Tool (PEMAT) instrument.

Results: The study found that both ChatGPT and CDC provided mostly accurate and understandable (eg, scores over 95 out of 100) responses. However, Flesch-Kincaid grade levels often exceeded the American Medical Association's recommended levels, particularly in English (eg, average grade level in English for ChatGPT=12.84, Spanish=7.93, recommended=6). CDC responses outperformed ChatGPT in readability across both languages. Notably, some Spanish responses appeared to be direct translations from English, leading to unnatural phrasing. The findings underscore the potential and challenges of using ChatGPT for health care access.

Conclusions: ChatGPT holds potential as a health information resource but requires improvements in readability and linguistic equity to be truly effective for diverse populations. Crucially, the default user experience with ChatGPT, typically encountered by those without advanced language and prompting skills, can significantly shape health perceptions. This is vital from a public health standpoint, as the majority of users will interact with LLMs in their most accessible form. Ensuring that default responses are accurate, understandable, and equitable is imperative for fostering informed health decisions across diverse communities.