Chinese General Practice Journal · Published 2026-06-01 · DOI 10.1016/j.cgpj.2026.100111
Yang Wang, Chuan Zou, Mengruo Guo, Liuhua He, Xuhang Lu, Xianzhong Gui, Zhijie Xu, Kai Lin, Hua Jin, Mi Yao, Hui Yang, Dehua Yu
General practitioners (GPs) in primary care—particularly in low- and middle-income countries (LMICs)—frequently encounter meaningful clinical problems but lack the methodological training to formalize them into research questions. This paper reports a five-stage, AI-assisted approach that embeds established frameworks—including the JBI Population–Concept–Context framework, scoping review methodology, and evidence-based questioning paradigms—into nine standardized AI prompts, guiding GPs through: practice observation and value assessment; information extraction and evidence-based transformation; literature search and knowledge summarization; research question prototype construction; and methodology selection and feasibility assessment. Built on human-AI collaboration with human primacy, the approach requires no prior methodological training. It was piloted through the Shanghai General Practice Research Network (SGPRN) and is most applicable in low evidence-density primary care settings.
Abstract from DOAJ. Public domain (CC0 1.0).
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Wang, Y., Zou, C., Guo, M., et al. (2026). A five-stage, AI-assisted approach for general practitioners to formulate practice-based research questions. Chinese General Practice Journal. https://doi.org/10.1016/j.cgpj.2026.100111