@article{Li2025, 
author = {Xue-jing Li and Run-xi Tian and Xin-juan Wu and Doris Grinspun and Ning Gao and Xiao-yan Zhang and Liu Han and Yu-fang Hao},
title = {Leading change: developing, transforming and applying best practice guidelines for local use},
year = {2025},
journal = {Evidence-Based Chinese Medicine and Technology Assessment},
volume = {1},
number = {2},
pages = {9570008},
keywords = {localization, implementation science, best practice guidelines, patient guidelines, knowledge translation},
url = {https://www.sciopen.com/article/10.26599/eCMTA.2025.9570008},
doi = {10.26599/eCMTA.2025.9570008},
abstract = {This paper investigates the theoretical and methodological frameworks for adapting international evidence-based guidelines within integrated healthcare systems that merge Western medicine with traditional healing practices. It explores five key domains of guideline adaptation. First, it examines the necessity of cultural localization due to fundamental differences in healthcare values, decision-making paradigms, and medical epistemologies. Second, it analyzes methodological frameworks for guideline adaptation, emphasizing culturally progressive strategies that uphold scientific rigor while enhancing cultural relevance. Third, it reviews case studies of localized implementation, with a focus on diabetic foot care, to illustrate integration techniques for harmonizing divergent medical traditions. Fourth, comprehensive strategies for developing derivative products encompass de novo development and adaptation pathways, including patient guidelines and decision aids. Fifth, the implementation and de-implementation strategies are informed by behavioral change theories, particularly the capability-opportunity-motivation-behavior (COM-B) model. These investigations culminate in a proposed Clinical Transformation Model, which synthesizes the knowledge-to-action (KTA) framework with the COM-B model to create an integrated approach to cross-cultural guideline adaptation. This model establishes a structured methodology for adapting international guidelines to diverse healthcare settings while preserving local medical traditions. Future research directions include exploring the role of artificial intelligence in evidence translation, particularly within integrated medical systems. This study enhances the understanding of cross-cultural knowledge translation processes and provides methodological insights into the implementation of global evidence-based practices.}
}