Attitudes and Perceptions of Generative Artificial Intelligence Chatbots in the Scientific Process of Traditional, Complementary, and Integrative Medicine Research: A Large-Scale, International Cross-Sectional Survey.

Authors

Jeremy Y Ng, Jamie Tan, Niveen Syed, Karthik Adapa, Prashant Kumar Gupta, Shao Li, Darshan Mehta, Melinda Ring, Manisha Shridhar, Joao Paulo Souza, Tetsuhiro Yoshino, Myeong Soo Lee, Holger Cramer

Published in

Journal of evidence-based medicine. Pages e70189. Sep 22, 2026. Epub Sep 22, 2026.

Abstract

Generative artificial intelligence (GenAI) chatbots have shown utility in assisting with various research tasks. Traditional, complementary, and integrative medicine (TCIM) is a patient-centric approach that emphasizes holistic well-being. The integration of TCIM and GenAI presents numerous key opportunities. However, TCIM researchers' attitudes toward GenAI tools remain less understood. This large-scale, international cross-sectional survey aimed to elucidate the attitudes and perceptions of TCIM researchers regarding the use of GenAI chatbots in the scientific process.
A search strategy in MEDLINE (via Ovid) identified corresponding authors who were TCIM researchers. Eligible authors were invited to complete an anonymous online survey administered via SurveyMonkey. The survey included questions on sociodemographic characteristics, familiarity with GenAI chatbots, and perceived benefits and challenges of using GenAI chatbots. Results were analyzed using descriptive statistics and thematic content analysis.
A total of 716 survey responses were received. Most respondents reported familiarity with GenAI chatbots (58.08%) and viewed them as very important to the future of scientific research (54.37%). The most acknowledged benefits included workload reduction (74.07%) and increased efficiency in data analysis/experimentation (71.14%). The most frequently reported challenges involved bias, errors, and limitations. More than half of the respondents (84.08%) expressed a need for training to use GenAI chatbots in the scientific process, alongside an interest in receiving training (72.07%). However, 43.67% indicated that their institutions did not offer these programs.
By deepening understanding of TCIM researchers' perspectives, these findings can inform future GenAI applications, policies, and collaborations in the field.

PMID:
42768952
Bibliographic data and abstract were imported from PubMed on 22 Sep 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.