Formulating high-quality research questions is one of the most fundamental challenges facing general practice professionals in China. Although they are deeply embedded in frontline practice and accumulate rich experiential knowledge, many still lack systematic methodological training and sustained research support. To address this gap, this methodological study developed and preliminarily validated a five-step human-AI collaborative approach based on AI chatbots. The approach translates classic methodological theories—such as the JBI PCC framework, implementation science, On Contradiction, and On Practice—into a set of standardized prompts, and combines them with stepwise human input to support five core tasks: practice observation and value assessment, information extraction and evidence-based conceptualization, literature searching and knowledge synthesis, construction of a preliminary research question, and method selection with feasibility assessment. This study provides a practical and accessible toolkit for Chinese general practice professionals, especially those with limited research training, to refine practice-based research questions in a structured manner. By lowering the threshold for moving from practical confusion to research initiation, this approach may help frontline practitioners overcome the common "zero-to-one" difficulty in starting research. More broadly, it offers a feasible methodological pathway for strengthening the generation of locally grounded evidence and promoting a practice-theory cycle in China's primary health care system.
