ArticleDigital health
Feasibility of using an artificially intelligent chatbot to increase access to information and sexual and reproductive health services.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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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
8 citing papers in PubMed.
- Addressing Health Disparities through Community Engagement in Artificial Intelligence-Driven Prevention Science.Prevention science : the official journal of the Society for Prevention Research · 2026Review
- Dating Applications as HIV Prevention Ecosystems in the Era of Digital Sexual Networks.Infectious disease reports · 2026Article
- Trust-Centered Design and Feasibility Evaluation of an AI-Enabled Conversational Health Tool for Sexual and Reproductive Health Among Rural Young Adults: Protocol for a Mixed Methods Study.JMIR research protocols · 2026Article
- Usability of the "Be Yourself" IA-powered, chatbot-based website for the prevention of adolescent pregnancy.Investigacion y educacion en enfermeria · 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
- Chatbots as frontline educators in sexual reproductive health rights: evidence, limitations, and ethical considerations.Frontiers in digital health · 2026Article
- Acceptability and Use of Digital Health and Artificial Intelligence-Enabled Chatbots for Sexual and Reproductive Health Among Lesbian, Bisexual, and Queer Women of Color in the United States: Cross-Sectional Survey Study.Journal of medical Internet research · 2025Article
- Safety-focused development and evaluation of an LLM sexual well-being chatbot for women: A methods-focused feasibility study.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Following the US Supreme Court decision overturning Roe v. Wade, there is evidence of limitations in access to safe abortion care. Artificially intelligent (AI)-enabled conversational chatbots are becoming an appealing option to support access to care, but generative AI systems can misinform and hallucinate and risk reinforcing problematic bias and stigma related to sexual and reproductive healthcare. Method: A single arm pilot study describing the development of an AI chatbot focused on sexual and reproductive health and its deployment in a clinic setting and community-based organization over a nine-month period. Results: We adjusted chatbot content based on feedback from the medical director and clients of organizations where the system was deployed given updated medical guidelines and preferred language related to gender-affirming care. We deployed the system in two organizations and tracked use over nine months. In that time, there were 1749 queries from 425 unique users. One-tenth of users of the clinic based chatbot went on to schedule an appointment for care. Conclusions: Ongoing challenges in accessing sexual and reproductive health suggest having diverse mechanisms to facilitate access to accurate and updated medical information is warranted. Using an AI chatbot is feasible to accomplish this goal and shows promise in increasing opportunities to access care.
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Registered trials
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.