Age- and sex-related variation in ChatGPT-4o HPV vaccine recommendation style: A fixed-prompt audit

Information from the abstract

ChatGPT is increasingly consulted for vaccine information, but demographic variation in recommendation framing is understudied. We audited ChatGPT-4o (1-2 May 2025) using 720 prompt instances from 156 coded seed prompts: one eligibility anchor and 12 misconception-based prompts across six age bands and two sex framings, each with 4-5 lexical variants. Replies were classified as presumptive, strong, shared decision-making, or recommend-against. Bayesian mixed-effects logistic models were fitted at the seed-prompt cluster level, with sex, age band, and their interaction as fixed effects and random intercepts for prompt topic and age-by-topic cluster (inter-coder kappa = 0.93). Through age 26y, all instances were directive. At ages 27-45y, the adjusted probability of a strong recommendation was 14.0% for women vs. 68.7% for men (difference, -54.7% points [95% credible interval, -71.8 to -32.8]; adjusted odds ratio [aOR], 0.04 [95% CrI, 0.008-0.19]). After age 45y, the adjusted probability of a recommend-against response was 59.9% for women vs. 41.1% for men (difference, 18.8% points [95% CrI, -5.4 to 40.8]; aOR, 2.40 [95% CrI, 0.77-7.50]). The 27-45y contrast remained clear after cluster adjustment; the >45y contrast was imprecise. This study evaluated recommendation style, not factual accuracy, guideline adherence, or vaccination behavior.

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Related topics: Artificial Intelligence in Healthcare and Education · Vaccine Coverage and Hesitancy · Cervical Cancer and HPV Research