Evidence map›Paper›PMID 40360673›Full record

ArticleNPJ digital medicine2025

Patient perceptions of empathy in physician and artificial intelligence chatbot responses to patient questions about cancer.

David Chen, Kabir Chauhan, Rod Parsa, Zhihui Amy Liu, Fei-Fei Liu, Ernie Mak, Lawson Eng, Breffni Louise Hannon, Jennifer Croke, Andrew Hope and 3 more

Erratum issuedAbstract read
In one paragraph

Article in NPJ digital medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 31 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

31 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Staying Connected? Revaluing 'Relationship Goods' in Digital Health Ecologies.Health care analysis : HCA : journal of health philosophy and policy · 2026
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  20. The potential of artificial intelligence in clinical trials.European journal of clinical investigation · 2026
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

David ChenPrincess Margaret Cancer Centre, Radiation Medicine Program, Toronto, ON, Canada.
Kabir ChauhanPrincess Margaret Cancer Centre, Radiation Medicine Program, Toronto, ON, Canada.
Rod ParsaMichael G. DeGroote School of Medicine, McMaster University, Hamilton, ON, Canada.
Zhihui Amy LiuDepartment of Biostatistics, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.
Fei-Fei LiuPrincess Margaret Cancer Centre, Radiation Medicine Program, Toronto, ON, Canada.
Ernie MakDepartment of Supportive Care, University Health Network, Toronto, ON, Canada.
Lawson EngDivision of Medical Oncology and Hematology, Department of Medicine, Princess Margaret Cancer Centre/University Health Network Toronto, Toronto, ON, Canada.
Breffni Louise HannonDepartment of Supportive Care, University Health Network, Toronto, ON, Canada.
Jennifer CrokePrincess Margaret Cancer Centre, Radiation Medicine Program, Toronto, ON, Canada.
Andrew HopePrincess Margaret Cancer Centre, Radiation Medicine Program, Toronto, ON, Canada.
Nazanin Fallah-RadDivision of Medical Oncology and Hematology, Department of Medicine, Princess Margaret Cancer Centre/University Health Network Toronto, Toronto, ON, Canada.
Phillip WongPrincess Margaret Cancer Centre, Radiation Medicine Program, Toronto, ON, Canada.
Srinivas RamanPrincess Margaret Cancer Centre, Radiation Medicine Program, Toronto, ON, Canada. Srinivas.Raman@bccancer.bc.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence chatbots can draft empathetic responses to cancer questions, but how patients perceive chatbot empathy remains unclear. Here, we found that people with cancer rated chatbot responses as more empathetic than physician responses. However, differences between patient and physician perceptions of empathy highlight the need for further research to tailor clinical messaging to better meet patient needs. Chatbots may be effective in generating empathetic template responses to patient questions under clinician oversight.

Identifiers

PMID40360673
PMCPMC12075825

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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 Socratic graph.