质性研究受访者样本量操作框架解读和案例解析OA

In qualitative research,data saturation is widely used to judge whether a respondent sample size is sufficient.Nevertheless,there remains no widely accepted definition of what constitutes"reaching saturation".Operational guidance for implementing and reporting saturation-based decisions is also limited.To address this methodological gap,Clarissa Hsu's team proposed the Qualitative Framework for Operationalizing Respondent Sample Size(Q-FORS)in 2025.Q-FORS synthesizes 11 domains,such as the study purpose,conceptual framework,sampling and recruitment strategies,and approaches to data collection and analysis,to support a structured appraisal of data adequacy and to promote more transparent sample-size decision-making in qualitative studies.This article introduces Q-FORS and illustrates its application using concrete examples.It aims to provide health-related qualitative researchers in China with a structured yet flexible tool for reasoning about sample size,thereby improving the transparency and rigor of sample-size decision-making and reporting in qualitative research.