ArticleBMC public health2025
Evaluation of artificial intelligence (AI) chatbots for providing sexual health information: a consensus study using real-world clinical queries.
Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic Review of Artificial Intelligence Applications in Clinical Trials for Central Nervous System Injuries.Current neuropharmacology · 2026Pooled it
- Mechanisms, management and prevention of anorectal sexually transmitted infections.Nature reviews. Gastroenterology & hepatology · 2026Review
- Japanese Health Information Technology Usability Evaluation Scale for Sexually Transmitted Infection-Related Chatbots: Development and Psychometric Validation Study.JMIR human factors · 2026Article
- Comment on: Utilization of Artificial Intelligence in Men's Health: Opportunities for Innovation and Quality Improvement.International journal of impotence research · 2026Article
- Usability of the "Be Yourself" IA-powered, chatbot-based website for the prevention of adolescent pregnancy.Investigacion y educacion en enfermeria · 2026Article
- Large Language Models in Infectious Diseases: A Systemic Review.Research square · 2026Article
- Evaluating the accuracy, reliability, and readability of AI chatbots in delivering postpartum depression information.Frontiers in psychiatry · 2026Article
- Toward safer digital sexual health communication: evaluating the public health reliability of large language model responses on sexually transmitted infections.Frontiers in public health · 2026Article
- An Evaluation Framework for Large Language Models in Clinical Nursing: A Scoping Review and Expert Consultation.Journal of nursing management · 2026Article
- Chatbots as frontline educators in sexual reproductive health rights: evidence, limitations, and ethical considerations.Frontiers in digital health · 2026Article
- Exploring AI-assisted design of executive function rehabilitation programs for individuals with ADHD: a mixed-methods evaluation of prompts and chatgpt outputs.BMC psychology · 2025Article
- AI chatbots as 'pocket doctors': intimate health support for young women in Lebanon.BMC public health · 2025Article
- [Systematic review of teen pregnancy prevention programs using websites and chatbotsProgramas de prevenção de gravidez na adolescência com base em sites e chatbots: revisão sistemática].Revista panamericana de salud publica = Pan American journal of public health · 2025Article
- Safety-focused development and evaluation of an LLM sexual well-being chatbot for women: A methods-focused feasibility study.Digital healthArticle
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Authors and funding
16 authors.
Funding
Abstract
introductionArtificial Intelligence (AI) chatbots could potentially provide information on sensitive topics, including sexual health, to the public. However, their performance compared to nurses and across different AI chatbots, particularly in the field of sexual health, remains understudied. This study evaluated the performance of three AI chatbots - two prompt-tuned (Alice and Azure) and one standard chatbot (ChatGPT by OpenAI) - in providing sexual health information on questions that experienced sexual health nurses could correctly answer.
methodsWe analysed 195 anonymised sexual health questions received by the Melbourne Sexual Health Centre phone line. A panel of experts in a blinded order using a consensus-based approach evaluated responses to these questions from nurses and the three AI chatbots. Performance was assessed based on overall correctness and five specific measures: guidance, accuracy, safety, ease of access, and provision of necessary information. We conducted subgroup analyses for clinic-specific (e.g., opening hours) and general sexual health questions and a sensitivity analysis excluding questions that Azure could not answer.
resultsAlice demonstrated the highest overall correctness (85.2%; 95% confidence interval (CI), 82.1-88.0%), followed by Azure (69.3%; 95% CI, 65.3-73.0%) and ChatGPT (64.8%; 95% CI, 60.7-68.7%). Prompt-tuned chatbots outperformed the base ChatGPT across all measures. Among all outcome measures, all chatbots performed best on safety, with Azure achieving the highest safety score (97.9%; 95% CI, 96.4-98.9%), indicating the lowest risk of providing potentially harmful advice. In subgroup analysis, all chatbots performed better on general sexual health questions compared to clinic-specific queries. Sensitivity analysis showed a narrower performance gap between Alice and Azure when excluding questions Azure could not answer.
conclusionsPrompt-tuned AI chatbots demonstrated superior performance in providing sexual health information compared to base ChatGPT, with high safety scores particularly noteworthy. However, all AI chatbots showed susceptibility to generating incorrect information. These findings suggest the potential for AI chatbots as adjuncts to human healthcare providers for providing sexual health information while highlighting the need for continued refinement and human oversight. Future research should focus on larger-scale evaluations and real-world implementations.
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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.