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Comparing Physician and Artificial Intelligence Chatbot Responses to Patient Questions Posted to a Public Social Media Forum

Overview of attention for article published in JAMA Internal Medicine, April 2023
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#7 of 5,076)
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
235 news outlets
blogs
18 blogs
twitter
6172 tweeters
facebook
7 Facebook pages
wikipedia
4 Wikipedia pages
reddit
6 Redditors
video
1 video uploader

Citations

dimensions_citation
10 Dimensions
Title
Comparing Physician and Artificial Intelligence Chatbot Responses to Patient Questions Posted to a Public Social Media Forum
Published in
JAMA Internal Medicine, April 2023
DOI 10.1001/jamainternmed.2023.1838
Pubmed ID
Authors

John W. Ayers, Adam Poliak, Mark Dredze, Eric C. Leas, Zechariah Zhu, Jessica B. Kelley, Dennis J. Faix, Aaron M. Goodman, Christopher A. Longhurst, Michael Hogarth, Davey M. Smith

Abstract

The rapid expansion of virtual health care has caused a surge in patient messages concomitant with more work and burnout among health care professionals. Artificial intelligence (AI) assistants could potentially aid in creating answers to patient questions by drafting responses that could be reviewed by clinicians. To evaluate the ability of an AI chatbot assistant (ChatGPT), released in November 2022, to provide quality and empathetic responses to patient questions. In this cross-sectional study, a public and nonidentifiable database of questions from a public social media forum (Reddit's r/AskDocs) was used to randomly draw 195 exchanges from October 2022 where a verified physician responded to a public question. Chatbot responses were generated by entering the original question into a fresh session (without prior questions having been asked in the session) on December 22 and 23, 2022. The original question along with anonymized and randomly ordered physician and chatbot responses were evaluated in triplicate by a team of licensed health care professionals. Evaluators chose "which response was better" and judged both "the quality of information provided" (very poor, poor, acceptable, good, or very good) and "the empathy or bedside manner provided" (not empathetic, slightly empathetic, moderately empathetic, empathetic, and very empathetic). Mean outcomes were ordered on a 1 to 5 scale and compared between chatbot and physicians. Of the 195 questions and responses, evaluators preferred chatbot responses to physician responses in 78.6% (95% CI, 75.0%-81.8%) of the 585 evaluations. Mean (IQR) physician responses were significantly shorter than chatbot responses (52 [17-62] words vs 211 [168-245] words; t = 25.4; P < .001). Chatbot responses were rated of significantly higher quality than physician responses (t = 13.3; P < .001). The proportion of responses rated as good or very good quality (≥ 4), for instance, was higher for chatbot than physicians (chatbot: 78.5%, 95% CI, 72.3%-84.1%; physicians: 22.1%, 95% CI, 16.4%-28.2%;). This amounted to 3.6 times higher prevalence of good or very good quality responses for the chatbot. Chatbot responses were also rated significantly more empathetic than physician responses (t = 18.9; P < .001). The proportion of responses rated empathetic or very empathetic (≥4) was higher for chatbot than for physicians (physicians: 4.6%, 95% CI, 2.1%-7.7%; chatbot: 45.1%, 95% CI, 38.5%-51.8%; physicians: 4.6%, 95% CI, 2.1%-7.7%). This amounted to 9.8 times higher prevalence of empathetic or very empathetic responses for the chatbot. In this cross-sectional study, a chatbot generated quality and empathetic responses to patient questions posed in an online forum. Further exploration of this technology is warranted in clinical settings, such as using chatbot to draft responses that physicians could then edit. Randomized trials could assess further if using AI assistants might improve responses, lower clinician burnout, and improve patient outcomes.

Twitter Demographics

The data shown below were collected from the profiles of 6,172 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Attention Score in Context

This research output has an Altmetric Attention Score of 5175. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 June 2023.
All research outputs
#717
of 23,937,668 outputs
Outputs from JAMA Internal Medicine
#7
of 5,076 outputs
Outputs of similar age
#11
of 353,999 outputs
Outputs of similar age from JAMA Internal Medicine
#2
of 100 outputs
Altmetric has tracked 23,937,668 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,076 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 161.9. This one has done particularly well, scoring higher than 99% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 353,999 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 100 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.