ArticleJournal of medical Internet research2021
Utilization of Self-Diagnosis Health Chatbots in Real-World Settings: Case Study.
Article in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers, 2 of them syntheses that pooled it.
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Who cites it
53 citing papers in PubMed, 2 syntheses or guidelines pooled it, 143 citations in OpenAlex.
- Artificial intelligence (AI) for social innovation in health education: promoting health literacy through personalized ai-driven learning tools - a systematic review.BMC medical education · 2025Pooled it
- Stakeholder Perspectives of Clinical Artificial Intelligence Implementation: Systematic Review of Qualitative Evidence.Journal of medical Internet research · 2023Pooled it
- Importance of Prior Patient Interactions With the Healthcare System to Engaging With Pretest Cancer Genetic Services via Digital Health Tools Among Unaffected Primary Care Patients: Findings From the BRIDGE Trial.Health services research · 2026Trial
- Dynamics of Digital Support Platform Use Among Family Caregivers of Children With Disabilities: Longitudinal Study.JMIR mHealth and uHealth · 2026Article
- Discordance Between Textual Reasoning and Visual Interpretation in Large Language Models for Low Back Pain: Cross-Sectional Quantitative Evaluation and Exploratory Multimodal Stress Test.JMIR medical informatics · 2026Article
- Article
- Body Image and Eating Disorder Education Chatbot, JEM, in Australia and Canada: First 6-Month Real-World Survey Evaluation.JMIR human factors · 2026Article
- Accuracy and empathy of AI-based conversational chatbots in response to temporomandibular dysfunction related queries.PEC innovation · 2026Article
- Navigating ethical, regulatory, and implementation barriers to AI in healthcare: pathways toward inclusive digital health in low-resource settings-a scoping review.Frontiers in digital health · 2026Review
- Telemedicine and AI-Powered Chatbots: Potential and Challenges for Home Care Provided by Family Caregivers.Healthcare (Basel, Switzerland) · 2025Article
- Use of Artificial Intelligence-Assisted Conversational Agents to Improve Patient Experience Related to Physicians: Cross-Sectional Study in China.Journal of medical Internet research · 2025Article
- Factors Influencing the Use of Online Symptom Checkers in the United Kingdom: Cross-Sectional Study.JMIR formative research · 2025Article
- Advancements and Innovation Trends of Information Technology Empowering Elderly Care Community Services Based on CiteSpace and VOSViewer.Healthcare (Basel, Switzerland) · 2025Article
- Women's Preferences and Willingness to Pay for AI Chatbots in Women's Health: Discrete Choice Experiment Study.Journal of medical Internet research · 2025Article
- Investigating Whether AI Will Replace Human Physicians and Understanding the Interplay of the Source of Consultation, Health-Related Stigma, and Explanations of Diagnoses on Patients' Evaluations of Medical Consultations: Randomized Factorial Experiment.Journal of medical Internet research · 2025Article
- Exploring Older Adults' Perspectives and Acceptance of AI-Driven Health Technologies: Qualitative Study.JMIR aging · 2025Article
- Chatbot -assisted self-assessment (CASA): Co-designing an AI -powered behaviour change intervention for ethnic minorities.PLOS digital health · 2025Article
- AI education for clinicians.EClinicalMedicine · 2025Review
- Economics and Equity of Large Language Models: Health Care Perspective.Journal of medical Internet research · 2024Article
- Artificial intelligence in healthcare: a scoping review of perceived threats to patient rights and safety.Archives of public health = Archives belges de sante publique · 2024Article
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 at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundArtificial intelligence (AI)-driven chatbots are increasingly being used in health care, but most chatbots are designed for a specific population and evaluated in controlled settings. There is little research documenting how health consumers (eg, patients and caregivers) use chatbots for self-diagnosis purposes in real-world scenarios.
objectiveThe aim of this research was to understand how health chatbots are used in a real-world context, what issues and barriers exist in their usage, and how the user experience of this novel technology can be improved.
methodsWe employed a data-driven approach to analyze the system log of a widely deployed self-diagnosis chatbot in China. Our data set consisted of 47,684 consultation sessions initiated by 16,519 users over 6 months. The log data included a variety of information, including users' nonidentifiable demographic information, consultation details, diagnostic reports, and user feedback. We conducted both statistical analysis and content analysis on this heterogeneous data set.
resultsThe chatbot users spanned all age groups, including middle-aged and older adults. Users consulted the chatbot on a wide range of medical conditions, including those that often entail considerable privacy and social stigma issues. Furthermore, we distilled 2 prominent issues in the use of the chatbot: (1) a considerable number of users dropped out in the middle of their consultation sessions, and (2) some users pretended to have health concerns and used the chatbot for nontherapeutic purposes. Finally, we identified a set of user concerns regarding the use of the chatbot, including insufficient actionable information and perceived inaccurate diagnostic suggestions.
conclusionsAlthough health chatbots are considered to be convenient tools for enhancing patient-centered care, there are issues and barriers impeding the optimal use of this novel technology. Designers and developers should employ user-centered approaches to address the issues and user concerns to achieve the best uptake and utilization. We conclude the paper by discussing several design implications, including making the chatbots more informative, easy-to-use, and trustworthy, as well as improving the onboarding experience to enhance user engagement.
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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.