WEI Xuehan, CHEN Xiaoying, WANG Runze, ZHANG Yingqian, LIU Xuehan, SUN Jin, YANG Guoyan, XIAO Wei, LU Chunli. Rapid Qualitative Analysis Methods and Their Application in Implementation ScienceJ. Medical Journal of Peking Union Medical College Hospital. DOI: 10.12290/xhyxzz.2025-1109
Citation: WEI Xuehan, CHEN Xiaoying, WANG Runze, ZHANG Yingqian, LIU Xuehan, SUN Jin, YANG Guoyan, XIAO Wei, LU Chunli. Rapid Qualitative Analysis Methods and Their Application in Implementation ScienceJ. Medical Journal of Peking Union Medical College Hospital. DOI: 10.12290/xhyxzz.2025-1109

Rapid Qualitative Analysis Methods and Their Application in Implementation Science

  • Implementation science(IS) aims to systematically analyze and address the real-world gaps from evidence to practice and the influencing factors of the context. It is necessary to carry out qualitative research to gather relevant implementation outcomes. Nevertheless, traditional qualitative analysis has issues such as consuming a great deal of time and energy, and it is unable to promptly provide the crucial data required for implementation science research. The Rapid Qualitative Analysis (RQA) method, through semi-structured interviews and the adoption of techniques such as immediate data condensation and matrix analysis, can effectively shorten the cycle of qualitative data collection and data processing. RQA can promptly identify social determinants of health such as structural barriers, facilitators, and the behavioral characteristics of target groups. Itprovides a real-time basis for public health decision-making, the interpretation of complex social phenomena, and the process and effectiveness evaluation of research projects. Although RQA is difficult to conduct in-depth theoretical analysis based on grounded theory, its efficiency and flexibility make it the preferred tool for large-scale and time-sensitive research. Thus, it has been widely applied in implementation science research. This paper sorts out the core concepts and commonly used technical methods of RQA, as well as the differences between RQA and traditional qualitative analysis. It also explores the applications of RQA in intervention optimization, process evaluation, and implementation outcome evaluation. By integrating specific cases, this paper clarifies its application value in the field of implementation science. In the future, it is advisable to explore the integration of RQA with technologies such as artificial intelligence and big data, in order to bridge the gap between the transformation of scientific research achievements into practice. Under circumstances of limited resources or tight time constraints, RQA can be used to efficiently conduct implementation science research, providing convenient and scientific methodological and technical support for accelerating evidence-based practice.
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