Data Saturation in Qualitative Research: A One-Size-Fits-All Fallacy

Introduction 

In qualitative research, saturation has been used as a benchmark for determining sample sizes, justifying the conclusion of the analyses, and validating the findings. The idea of saturation has its roots in grounded theory. Meanwhile, saturation has become adapted to various qualitative methodologies as a guideline for determining the adequacy of data collection and inclusion of participants, and this has led to debates. Articles and textbooks have focused on the idea of saturation, its conceptualization, and operationalization; still there is a lack of clarity regarding the use saturation in specific qualitative methodologies. Since qualitative content analysis and phenomenology are frequently used in health and social sciences, in which publication quality standards require addressing saturation, it is essential to discuss the relevance of saturation.

Goals and Methods 

The goal is to question the idea of saturation in relation to qualitative content analysis and phenomenology and discuss its validity within these research approaches. The paper draws on literature regarding saturation, qualitative research, phenomenology, and content analysis. The sources are gathered from textbooks and scientific databases, e.g., Scopus and CINAHL, and from the authors’ methodological expertise gained through extensive research and supervision in qualitative content analysis and phenomenology.

Results 

In qualitative content analysis, the material should be relevant for the study aim, but saturation is not a quality criterion. In phenomenology, variation takes precedence over a specific numerical count, and the idea of saturation is considered invalid, as the inherent value of the data unfold during analysis.

Conclusions

The paper adds to the discussion on saturation by focusing on qualitative content analysis and phenomenology, arguing that saturation is not valid as an argument for data collection. Relevant criteria of quality are discussed, including reasoning for methodological choices related to material and analyses in studies using qualitative content analysis or phenomenology.