Jeremy Y. Ng, Daivat Bhavsar, Neha Dhanvanthry, Myeong Soo Lee, Ye-Seul Lee, Tanuja M. Nesari, Thomas Ostermann, Claudia M. Witt, Linda Zhong, Holger Cramer
Perspect Integr Med. 2025;4(2):121-124. Published online June 23, 2025
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.
Background Traditional, complementary, and integrative medicine (TCIM) has witnessed significant growth in interest globally. Despite its popularity, TCIM research encounters numerous challenges including funding, methodological issues, and risk of bias. Preprints (scientific manuscripts openly accessible before formal peer review) present a potential solution, and understanding the characteristics and impact of TCIM preprints could offer valuable insights.
Methods A bibliometric analysis will be conducted on all TCIM-related preprints, since inception, and posted on preprint servers with TCIM subject filters. Preprints will be sourced from servers listed in the Accelerating Science and Publication in Biology directory which allow filtering by TCIM-related categories. The preprint server and URLs, preprint server’s disciplinary scope, ownership type, screening processes, external content indexing, permanence of content, preservation of content, and comments will be extracted. The number of TCIM-related preprints yielded, and which TCIM-related term each preprint server uses will be noted. Data will be extracted from each eligible preprint: preprint server, title, DOI, preprint posted date, status of preprint, journal of final publication, final publication date, type of preprint, abstract of preprint, authors, author affiliation(s), country of corresponding author, funders, number of views, number of downloads, number of comments, number of citations, number of versions, and keywords. Descriptive statistics will be used to summarize the bibliometric characteristics, and trend analysis will identify publication patterns over time.
Conclusion This protocol was developed for a study to identify trends in TCIM research dissemination, and contribute to a better understanding of how preprints are being used to advance the field
Traditional, complementary, and integrative medicine (TCIM) encompasses a broad range of healthcare practices beyond conventional Western medicine. Despite its use globally and increased research, many TCIM research challenges persist impeding its progress and integration into clinical practice. Key challenges involve financial constraints, insufficient research training and educational support, and the methodological barriers which arise from a lack of standardization. Financial limitations hinder investment into crucial research limiting both the quantity and quality of TCIM research. Inadequate training in research and educational support limit the development of TCIM research, hindering growth and recognition of TCIM in academic and clinical settings. The inherent dynamic nature of TCIM therapies poses additional challenges for applying standardized biomedical research models. These challenges not only impede the advancement of TCIM research but also perpetuate negative attitudes and biases within the healthcare and research communities. To overcome these challenges, a comprehensive strategy is necessary to increase funding, improve literacy, and the promotion of open science practices in TCIM. Addressing these confounding factors will enable well-informed TCIM research literacy and the development of TCIM skills and facilitate the integration of evidence based TCIM therapies into a more inclusive healthcare domain, ultimately reducing negative attitudes and biases towards TCIM.
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