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
This research study examines over 15,000 user reviews of AI healthcare chatbot apps to identify common breakdowns in their performance. The study found three main issues: access barriers, service unreliability, user experience and interaction quality, billing and customer support problems, and privacy concerns.
What the Document Says
- The study involves examining user reviews of AI healthcare chatbot apps
- There were over 15,000 user reviews from 59 AI healthcare chatbot apps
- 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.
Key Concepts Mentioned
- AI healthcare chatbots
- user reviews
- breakdowns
- access barriers
- service unreliability
- user experience
- interaction quality
- billing issues
- customer support issues
- privacy concerns
Claims Made by the Document
- AI healthcare chatbots are increasingly used for health information seeking and self-management
- The performance and impact on users of AI healthcare chatbots needs to be studied
- Three recurring breakdowns were identified in the study
Evidence Used
- examining over 15,000 user reviews from 59 AI healthcare chatbot apps
Methods / Approach
- topic modeling and interpretive analysis
Limitations Stated by the Authors
Not stated in source
Limitations Noted by the Agent
Agent interpretation — not from the source.
The study only analyzed user reviews which may not represent all experiences or issues with the AI healthcare chatbots.
Open Questions
- What were the specific details of the access barriers and service unreliability identified?
- How were user experience and interaction quality measured in the study?
Notes for Future Q&A
May include interpretation. Labeled where it does.
The text does not provide specific details about the access barriers, service unreliability, or how user experience and interaction quality were measured.
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.
