ArticleJournal of general internal medicine2026
What is Artificial Intelligence (AI) "Empathy"? A Study Comparing ChatGPT and Physician Responses on an Online Forum.
Article in Journal of general internal medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Digital compassion fatigue and digital empathy in healthcare: mapping the evidence and informing a human-centered clinical framework.Frontiers in psychology · 2026Pooled it
- The Use of Artificial Intelligence Chatbots by Newly Diagnosed Cancer Patients: A Descriptive Phenomenological Study.Current oncology (Toronto, Ont.) · 2026Article
- The Empathy Paradox: AI in Clinical Diagnosis.Journal of evaluation in clinical practice · 2026Article
- Eye-Tracked Visual Attention to Anthropomorphic Appearance and Empathic Responses in AI Medical Conversational Agents: Dissociating Trust Gains from Attentional Synergy.Journal of eye movement research · 2026Article
- The risk of empty empathy talk and challenges of automated empathy in healthcare communication.NPJ digital medicine · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
backgroundArtificial intelligence (AI) chatbots may be an asset to patient-provider communication, but not enough is known about how patients respond and how chatbots answer patients' questions.
objectiveHow perceptions of empathy, quality, trust, liking, and goodness vary by both the actual and perceived source of responses to patient questions (chatbot vs. actual physician). We also coded and compared key verbal elements in chatbot and physician responses.
designThis cross-sectional experimental study used chatbot and physician responses from Ayers et al. (2023) in a 2 (actual source: chatbot vs. physician) × 2 (perceived source: chatbot vs. physician) factorial design.
participantsU.S.-based, English-speaking participants were recruited online (N = 1454). MAIN MEASURES: Participants rated responses on empathy, quality, trust, liking, and goodness. Verbal content of the chatbot and physician responses was independently coded by trained research assistants to identify elements contributing to higher empathy ratings by participants. KEY
resultsReplicating Ayers et al. (2023), participants rated chatbot responses as more empathic than physician responses (Cohen's d = 0.56, p < 0.001). Chatbot responses received higher empathy ratings than physician responses regardless of what participants were told about authorship (η
conclusionsAI-generated responses, with human oversight, could enhance computer-mediated clinical communication, although patient awareness of AI contributions may reduce perceptions of empathy. Identification of the specific verbal elements in AI-generated responses could augment communication and increase perceptions of empathic care.
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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.