Assessment of Artificial Intelligence Chatbot Responses to Top Searched Queries About Cancer
State University of New York · SUNY Downstate Health Sciences University · +2 more institutions
Abstract
Consumers are increasingly using artificial intelligence (AI) chatbots as a source of information. However, the quality of the cancer information generated by these chatbots has not yet been evaluated using validated instruments.
To characterize the quality of information and presence of misinformation about skin, lung, breast, colorectal, and prostate cancers generated by 4 AI chatbots. Design, Setting, and Participants: This cross-sectional study assessed AI chatbots' text responses to the 5 most commonly searched queries related to the 5 most common cancers using validated instruments. Search data were extracted from the publicly available Google Trends platform and identical prompts were used to generate responses from 4 AI chatbots: ChatGPT version 3.5 (OpenAI), Perplexity (Perplexity.AI), Chatsonic (Writesonic), and Bing AI (Microsoft). Exposures: Google Trends' top 5 search queries related to skin, lung, breast, colorectal, and prostate cancer from January 1, 2021, to January 1, 2023, were input into 4 AI chatbots. Main Outcomes and Measures: The primary outcomes were the quality of consumer health information based on the validated DISCERN instrument (scores from 1 [low] to 5 [high] for quality of information) and the understandability and actionability of this information based on the understandability and actionability domains of the Patient Education Materials Assessment Tool (PEMAT) (scores of 0%-100%, with higher scores indicating a higher level of understandability and actionability). Secondary outcomes included misinformation scored using a 5-item Likert scale (scores from 1 [no misinformation] to 5 [high misinformation]) and readability assessed using the Flesch-Kincaid Grade Level readability score.
Citation impact
- FWCI
- 8.85
- Percentile
- 100%
- References
- 9
Authors
5- APAlexander Pan
State University of New York, SUNY Downstate Health Sciences University
- DMDavid Musheyev
State University of New York, SUNY Downstate Health Sciences University
- DBDaniel Bockelman
State University of New York, SUNY Downstate Health Sciences University
- SLStacy Loeb
VA NY Harbor Healthcare System, New York University
- AKAbdo KabarritiCorresponding
State University of New York, SUNY Downstate Health Sciences University
Topics & keywords
- Misinformation
- Medicine
- Readability
- Chatbot
- Perplexity
- Artificial intelligence
- Computer science
- Quality Education