Artificial Intelligence in the Editorial and Peer Review Process: A Protocol for a Cross-Sectional Survey of Traditional, Complementary, and Integrative Medicine Journal Editors’ Perceptions

This research protocol outlines a cross-sectional survey study, aimed at editors from traditional, complementary, and integrative medicine (TCIM) journals, regarding their perceptions of the use of artificial intelligence (AI) in the editorial and peer review process. The survey will be sent to editors-in-chief, associate editors, and editorial board members of TCIM journals (100-150). The research involves purposive sampling via manual collection of contact details from TCIM journal websites. The survey will include sections on demographics, current use and familiarity with AI, perceived benefits and challenges, ethical concerns, and the outlook for AI in publishing. Data collection will be conducted online using SurveyMonkey whereby email invitations and follow-up reminders will be sent to potential respondents. Quantitative data will be analyzed using descriptive statistics, and for qualitative data, thematic analyses will be employed. This protocol study aimed to devise a survey which could provide insight into the acceptance and potential barriers to AI adoption in TCIM publishing from an editor’s perspective. The results of which may later guide the development of AI tools in a way that aligns with the needs and values of the TCIM research community.

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Publication Details

Journal
Universität Zürich, ZORA
Published
2025-06-30
DOI
https://doi.org/10.5167/uzh-283712
Primary Topic
Complementary and Alternative Medicine Studies
Type
article
Field-Weighted Citation Impact
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article

Artificial Intelligence in the Editorial and Peer Review Process: A Protocol for a Cross-Sectional Survey of Traditional, Complementary, and Integrative Medicine Journal Editors’ Perceptions

Daivat Bhavsar, Tanuja Manoj Nesari, Neha Dhanvanthry, Ye-Seul Lee et al.
Universität Zürich, ZORA
Complementary and Alternative Medicine Studies
article

Artificial Intelligence in the Editorial and Peer Review Process: A Protocol for a Cross-Sectional Survey of Traditional, Complementary, and Integrative Medicine Journal Editors’ Perceptions

Daivat Bhavsar, Tanuja Manoj Nesari, Neha Dhanvanthry, Ye-Seul Lee, Linda Zhong, Thomas Ostermann, Myeong Soo Lee, Jeremy Y. Ng, Claudia M Witt
article en

Abstract

This research protocol outlines a cross-sectional survey study, aimed at editors from traditional, complementary, and integrative medicine (TCIM) journals, regarding their perceptions of the use of artificial intelligence (AI) in the editorial and peer review process. The survey will be sent to editors-in-chief, associate editors, and editorial board members of TCIM journals (100-150). The research involves purposive sampling via manual collection of contact details from TCIM journal websites. The survey will include sections on demographics, current use and familiarity with AI, perceived benefits and challenges, ethical concerns, and the outlook for AI in publishing. Data collection will be conducted online using SurveyMonkey whereby email invitations and follow-up reminders will be sent to potential respondents. Quantitative data will be analyzed using descriptive statistics, and for qualitative data, thematic analyses will be employed. This protocol study aimed to devise a survey which could provide insight into the acceptance and potential barriers to AI adoption in TCIM publishing from an editor’s perspective. The results of which may later guide the development of AI tools in a way that aligns with the needs and values of the TCIM research community.

Universität Zürich, ZORA
Openalex Percentile: Top 19%
Complementary and Alternative Medicine Studies
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