TY - JOUR
T1 - WHO global research priorities for traditional, complementary, and integrative (TCI) medicine
T2 - an international consensus and comparisons with LLMs
AU - Ahn, Sangyoung
AU - Zhou, Jiali
AU - Jiang, Denan
AU - Kerr, Steven
AU - Zhu, Yajie
AU - Song, Peige
AU - Rudan, Igor
AU - Hammerschlag, Richard
AU - Skoetz, Nicole
AU - Savrikar, Shriram
AU - Fong, Harry H.S.
AU - Shaoping, Li
AU - Akarasereenont, Pravit
AU - Cramer, Holger
AU - Salih, Sabah J.
AU - Wang, Mei
AU - Smith, Caroline
AU - Masiero, Stefano
AU - Jong, Miek
AU - Devarajan, Elanchezhiyan
AU - Hughes, John
AU - Tsang, William W.N.
AU - Chong, Lam Fu
AU - Xin, Chen
AU - Ming, Wang Chun
AU - Li, Zheng
AU - Qibiao, Wu
AU - Ting, Li
AU - Lu, Yang
AU - Stone, Jennifer A.M.
AU - Kessler, Christian
AU - Ng, Jeremy
AU - Sajdyk, Tammy J.
AU - Kunle, Olobayo
AU - Hanser, Suzanne B.
AU - Wiesner, Jacqueline
AU - Catabay, Alicia
AU - Elisabetsky, Elaine
AU - Barth, Juergen
AU - Shefer, Elena
AU - Soon, Goh Cheng
AU - Sanogo, Rokia
AU - Park, Sungmin
AU - Khan, Ikhlas A.
AU - Sklaviadis, Theodoros
AU - Witt, Claudia
AU - Bian, Zhaoxiang
AU - Lee, Sanghoon
AU - Xue, Charlie
AU - Skaltsa, Eleni
AU - Bensoussan, Alan
AU - Duez, Pierre
AU - Nielsen, Arya
AU - Liu, Jianping
AU - Sastry, Jataval Labha
AU - Yeh, Gloria
AU - das Gracas Lins, Maria
AU - Villar, Martha
AU - Che, Chun Tao
AU - Mo, Hui
AU - WHO TCI medicine CHNRI group
N1 - This work received partial financial support from the Ministry of Health and Welfare, Republic of Korea, with funds administered through the World Health Organization; and from the NIHR EQUI-RESP-AFRICA project (ref NIHR156234) using UK international development funding from the UK Government to support global health research. The views expressed are those of the author(s) and not necessarily those of the NIHR or the UK government.
Publisher Copyright:
© 2025 The Author(s)
Copyright © 2025 by the Journal of Global Health. All rights reserved.
PY - 2025/11/14
Y1 - 2025/11/14
N2 - Background Traditional, complementary, and integrative (TCI) medicine is an essential component of health systems worldwide, especially in low- and middle-income countries. Despite its widespread use, existing research on the safety, efficacy, and integration of TCI medicine within conventional healthcare systems is fragmented. This fragmentation highlights the urgent need for a clearly defined global research agenda to guide future studies, secure funding, and inform governance in this field. Methods The Traditional, Complementary, and Integrative Medicine Unit at the World Health Organization Headquarters in Geneva, Switzerland coordinated an international research priority-setting exercise using the Child Health and Nutrition Research Initiative (CHNRI) method between June and December 2023. We invited a purposive sample of 120 experts from established academic networks to participate; 53 experts (44.16% response rate) contributed, and 34 of them scored 157 unique research ideas according to five CHNRI criteria: feasibility, effectiveness, deliverability, equity, and potential for disease burden reduction. Additionally, we performed a comparative analysis by generating research priorities using large language models (LLMs), including ChatGPT-4o, Claude 3.5, and Grok 3, and these outputs were compared with the expert-derived priorities. Results Top-ranked research priorities focused on chronic disease management (e.g. diabetes, dyslipidemia), geriatric safety (e.g. herb-drug interactions), mental health (e.g. resilience and mood disorders), and integration of TCI into health systems. Priorities varied by income setting. Comparison with LLM-generated lists showed thematic overlap in efficacy and safety but divergence in focus, with LLMs emphasising research capacity, policy, and systems-level priorities. Conclusions We established a global, expert-informed research agenda to guide the future direction of TCI medicine and ensure alignment with public health needs. The comparison with LLMs highlights the complementary potential of artificial intelligence in research governance and agenda-setting.
AB - Background Traditional, complementary, and integrative (TCI) medicine is an essential component of health systems worldwide, especially in low- and middle-income countries. Despite its widespread use, existing research on the safety, efficacy, and integration of TCI medicine within conventional healthcare systems is fragmented. This fragmentation highlights the urgent need for a clearly defined global research agenda to guide future studies, secure funding, and inform governance in this field. Methods The Traditional, Complementary, and Integrative Medicine Unit at the World Health Organization Headquarters in Geneva, Switzerland coordinated an international research priority-setting exercise using the Child Health and Nutrition Research Initiative (CHNRI) method between June and December 2023. We invited a purposive sample of 120 experts from established academic networks to participate; 53 experts (44.16% response rate) contributed, and 34 of them scored 157 unique research ideas according to five CHNRI criteria: feasibility, effectiveness, deliverability, equity, and potential for disease burden reduction. Additionally, we performed a comparative analysis by generating research priorities using large language models (LLMs), including ChatGPT-4o, Claude 3.5, and Grok 3, and these outputs were compared with the expert-derived priorities. Results Top-ranked research priorities focused on chronic disease management (e.g. diabetes, dyslipidemia), geriatric safety (e.g. herb-drug interactions), mental health (e.g. resilience and mood disorders), and integration of TCI into health systems. Priorities varied by income setting. Comparison with LLM-generated lists showed thematic overlap in efficacy and safety but divergence in focus, with LLMs emphasising research capacity, policy, and systems-level priorities. Conclusions We established a global, expert-informed research agenda to guide the future direction of TCI medicine and ensure alignment with public health needs. The comparison with LLMs highlights the complementary potential of artificial intelligence in research governance and agenda-setting.
UR - https://www.scopus.com/pages/publications/105021764577
UR - https://scholars.hkbu.edu.hk/admin/workspace/editor/overview/
U2 - 10.7189/jogh.15.04336
DO - 10.7189/jogh.15.04336
M3 - Journal article
C2 - 41232122
AN - SCOPUS:105021764577
SN - 2047-2978
VL - 15
JO - Journal of Global Health
JF - Journal of Global Health
M1 - 04336
ER -
