Source note2 min read
AI Healthcare Chatbots as Information Infrastructure: A Large-Scale Study of User-Reported Breakdowns
Source
arXiv
arxiv.org/abs/2606.27302v1
Source
- Source name: arXiv
- Source kind: paper
- Authors / organization: Muhammad Hassan, Ramazan Yener, Ece Gumusel, Masooda Bashir
- Venue: arXiv: cs.HC
- Published: 2026-06-25
- Collected: 2026-06-26
- URL: http://arxiv.org/abs/2606.27302v1
- PDF: https://arxiv.org/pdf/2606.27302v1
- DOI: UNKNOWN
Plain-Language Brief
Researchers analyzed over 15,000 user reviews from 59 AI healthcare chatbot apps to understand the performance of these systems in everyday use. They identified three main issues: access barriers and service unreliability, user experience and interaction quality, billing and customer support issues. Privacy and security concerns were associated with the most negative experiences.
What the Document Says
- The study explores the performance and impact of AI healthcare chatbots on users.
- The research analyzed user reviews from 59 AI healthcare chatbot apps, totaling over 15,000 reviews.
- Three recurring breakdowns were identified: access barriers and service unreliability, user experience and interaction quality, and billing and customer support issues.
- Privacy and security concerns were associated with the most negative experiences.
- The findings suggest that failures in access, usability, and trust affect users.
- The researchers frame AI healthcare chatbots as information infrastructures.
Key Concepts Mentioned
- AI healthcare chatbots
- user reviews
- performance
- impact
- information infrastructure
- breakdowns
- access barriers
- service unreliability
- user experience
- interaction quality
- billing issues
- customer support
- privacy
- security
Claims Made by the Document
- AI healthcare chatbots are increasingly used to support health information seeking and self-management.
Evidence Used
- The study examines over 15,000 user reviews from 59 AI healthcare chatbot apps.
Methods / Approach
UNKNOWN
Limitations Stated by the Authors
UNKNOWN
Limitations Noted by the Agent
Agent interpretation — not from the source.
UNKNOWN
Open Questions
UNKNOWN
Notes for Future Q&A
May include interpretation. Labeled where it does.
UNKNOWN
Raw Abstract / Excerpt
AI healthcare chatbots are increasingly used to support health information seeking and self-management, yet their performance and impact on users remains to be studied. This study examines over 15,000 user reviews from 59 AI healthcare chatbot apps to explore how these systems function in everyday informational and emotional contexts. Topic modeling and interpretive analysis identify three recurring breakdowns: access barriers and service unreliability, user experience and interaction quality, and billing and customer support issues. Privacy and security concerns are associated with the most negative experiences. By framing AI healthcare chatbots as information infrastructures, our findings highlight how failures in access, usability, and trust affect users, offering actionable insights for designers, policymakers, and information professionals aiming to improve digital health systems.
