ArticlePLOS digital health2024
Achieving health equity through conversational AI: A roadmap for design and implementation of inclusive chatbots in healthcare.
Article in PLOS digital health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 2 of them syntheses that pooled it.
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Who cites it
31 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Interactive Conversational Agents to Improve Dietary Behaviors for Health Promotion: Mixed Systematic Review.Journal of medical Internet research · 2025Pooled it
- Community engagement, recruitment, and retention of minoritized participants in Alzheimer's disease and related dementia research: A systematic review of disparities.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Pooled it
- A Patient Simulation Framework for Risk Assessment of Conversational Health Care AI: Development and Evaluation Study.JMIR AI · 2026Article
- Artificial intelligence in health systems of the WHO European region: implementation, applications, opportunities, and barriers.International journal of medical informatics · 2026Article
- User needs and design opportunities for a conversational agent for tuberculosis treatment: A mixed-methods study.PLOS digital health · 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
- Metrics Used for the Evaluation of Chatbots Providing Cancer Genetic Risk Assessment and Education: Systematic Review.JMIR AI · 2026Review
- Coconstructing CHAMP, an Artificial Intelligence Chatbot for Pediatric Infectious Symptoms Management: Protocol for a Multiphase Participatory Study.JMIR research protocols · 2026Article
- Conversational AI and Personal Growth: Insights from a Critical Integrative Review.Behavioral sciences (Basel, Switzerland) · 2026Review
- AI chatbots for health information seeking among Chinese patients with precancerous ENT lesions: a descriptive qualitative study.BMJ open · 2026Article
- Current Landscape of Mental Health Conversational Agents From a Trauma-Informed Care Lens: Scoping Review.JMIR mental health · 2026Article
- Integrating Generative AI Into Patient-Centered Clinical Decision Support: Viewpoint on Research and Practice Considerations.Journal of medical Internet research · 2026Article
- Digital Health Solutions for Type 2 Diabetes and Prediabetes: Systematic Review of Engagement Barriers, Facilitators, and Outcomes.JMIR diabetes · 2026Review
- Participatory-informed preference optimization (PiPrO): A reinforcement learning simulation study.PLOS digital health · 2026Article
- "I Could Practice Flirting Without Pressure": A Proof-of-Concept Study of an AI Chatbot-Assisted Intervention for Men Facing Distressing Involuntary Singlehood.Archives of sexual behavior · 2026Article
- Article
- Artificial intelligence for predicting and preventing adverse pregnancy outcomes addressing bias and clinical translation.Frontiers in digital health · 2026Review
- Considerations for mHealth development: lessons learned from two diabetes education apps.mHealth · 2026Article
- Perspective on patient and non-academic partner engagement for the responsible integration of large language models in health chatbots.Research involvement and engagement · 2025Article
- Rethinking AI Workflows: Guidelines for Scientific Evaluation in Digital Health Companies.JMIR AI · 2025Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe rapid evolution of conversational and generative artificial intelligence (AI) has led to the increased deployment of AI tools in healthcare settings. While these conversational AI tools promise efficiency and expanded access to healthcare services, there are growing concerns ethically, practically and in terms of inclusivity. This study aimed to identify activities which reduce bias in conversational AI and make their designs and implementation more equitable.
methodsA qualitative research approach was employed to develop an analytical framework based on the content analysis of 17 guidelines about AI use in clinical settings. A stakeholder consultation was subsequently conducted with a total of 33 ethnically diverse community members, AI designers, industry experts and relevant health professionals to further develop a roadmap for equitable design and implementation of conversational AI in healthcare. Framework analysis was conducted on the interview data.
resultsA 10-stage roadmap was developed to outline activities relevant to equitable conversational AI design and implementation phases: 1) Conception and planning, 2) Diversity and collaboration, 3) Preliminary research, 4) Co-production, 5) Safety measures, 6) Preliminary testing, 7) Healthcare integration, 8) Service evaluation and auditing, 9) Maintenance, and 10) Termination. DISCUSSION: We have made specific recommendations to increase conversational AI's equity as part of healthcare services. These emphasise the importance of a collaborative approach and the involvement of patient groups in navigating the rapid evolution of conversational AI technologies. Further research must assess the impact of recommended activities on chatbots' fairness and their ability to reduce health inequalities.
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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.