Beyond saturation: A qualitative framework for operationalizing respondent sampling (Q-FORS) for data adequacy

Qualitative research differs fundamentally from quantitative research in the basic epistemological tenets underlying the rationale for sample size and data adequacy. Within qualitative methods, multiple approaches (e.g., phenomenology, ethnography, discourse analysis, framework analysis) each have their own logic for how many participants are enough. Grounded theory uses specific sampling strategies to achieve thematic and theoretical "saturation" for theory-building and examining multiple dimensions of a social process. However, in qualitative health research-where there often has been pressure to use methodologies that simulate quantitative methods-saturation has been problematically adopted by many as a general standard for assessing the quality or completeness of a qualitative dataset. We developed the Qualitative Framework for Operationalizing Respondent Sampling (Q-FORS) based on a narrative review of articles on qualitative sample size and saturation. Q-FORS builds on and clarifies the existing literature by focusing on data adequacy as the pivotal concept for determining a qualitative sample, especially with interviews and focus groups. Q-FORS is primarily intended for any researchers using qualitive methods, especially those publishing in medical and health related journals. It is a practical framework applicable across the spectrum of the research life cycle-from proposal writing and data collection to reporting, similar to the Consolidated Criteria for Report Qualitative Research (COREQ). We demonstrate the use of Q-FORS using two examples from our own research Our pragmatic approach to determining sample size and data adequacy respects the unique epistemologies of qualitative research, offering a transparent way to account for sampling choices.