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
A study analyzing over 15,000 user reviews of AI healthcare chatbot apps found recurring issues with access barriers, service unreliability, user experience, interaction quality, billing, and customer support. Privacy and security concerns were associated with the most negative experiences.
What the Document Says
- The study examined 15,000 user reviews from 59 AI healthcare chatbot apps to explore their functionality in everyday informational and emotional contexts.
- 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 study suggests that AI healthcare chatbots can be framed as information infrastructures.
Key Concepts Mentioned
- AI healthcare chatbots
- User reviews
- Topic modeling
- Information infrastructure
Claims Made by the Document
- AI healthcare chatbots have performance and impact on users that need to be studied.
- Three recurring breakdowns were found in AI healthcare chatbot apps.
- Privacy and security concerns are associated with the most negative experiences with AI healthcare chatbots.
Evidence Used
- Over 15,000 user reviews from 59 AI healthcare chatbot apps were examined.
- Topic modeling and interpretive analysis were used to identify recurring breakdowns.
Methods / Approach
- topic modeling
- interpretive analysis
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.
