ChatGPT vs. neurologists: a cross-sectional study investigating preference, satisfaction ratings and perceived empathy in responses among people living with multiple sclerosis

J Neurol. 2024 Jul;271(7):4057-4066. doi: 10.1007/s00415-024-12328-x. Epub 2024 Apr 3.

Abstract

Background: ChatGPT is an open-source natural language processing software that replies to users' queries. We conducted a cross-sectional study to assess people living with Multiple Sclerosis' (PwMS) preferences, satisfaction, and empathy toward two alternate responses to four frequently-asked questions, one authored by a group of neurologists, the other by ChatGPT.

Methods: An online form was sent through digital communication platforms. PwMS were blind to the author of each response and were asked to express their preference for each alternate response to the four questions. The overall satisfaction was assessed using a Likert scale (1-5); the Consultation and Relational Empathy scale was employed to assess perceived empathy.

Results: We included 1133 PwMS (age, 45.26 ± 11.50 years; females, 68.49%). ChatGPT's responses showed significantly higher empathy scores (Coeff = 1.38; 95% CI = 0.65, 2.11; p > z < 0.01), when compared with neurologists' responses. No association was found between ChatGPT' responses and mean satisfaction (Coeff = 0.03; 95% CI = - 0.01, 0.07; p = 0.157). College graduate, when compared with high school education responder, had significantly lower likelihood to prefer ChatGPT response (IRR = 0.87; 95% CI = 0.79, 0.95; p < 0.01).

Conclusions: ChatGPT-authored responses provided higher empathy than neurologists. Although AI holds potential, physicians should prepare to interact with increasingly digitized patients and guide them on responsible AI use. Future development should consider tailoring AIs' responses to individual characteristics. Within the progressive digitalization of the population, ChatGPT could emerge as a helpful support in healthcare management rather than an alternative.

Keywords: Artificial intelligence; Large language model; Machine learning; Multiple sclerosis.

MeSH terms

  • Adult
  • Artificial Intelligence*
  • Cross-Sectional Studies
  • Empathy* / physiology
  • Female
  • Humans
  • Male
  • Middle Aged
  • Multiple Sclerosis* / psychology
  • Neurologists* / psychology
  • Patient Preference
  • Patient Satisfaction
  • Personal Satisfaction
  • Physician-Patient Relations