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Assessing Data Adequacy in Qualitative Research Studies
Summary
Qualitative researchers should move beyond data saturation, a concept misaligned with constructivist approaches. Instead, prioritize information power, conceptual depth, and theoretical sufficiency for robust qualitative research and data adequacy.
Area of Science:
- Qualitative Research Methodology
- Epistemology in Social Sciences
Background:
- The concept of data saturation is commonly used in qualitative research to determine sample size.
- This approach is often rooted in a positivist paradigm, which may conflict with the underlying philosophies of qualitative inquiry.
Purpose of the Study:
- To critique the use of data saturation in qualitative research.
- To propose alternative concepts for justifying sample size and data collection cessation.
Main Methods:
- Conceptual analysis of research paradigms and sampling strategies.
- Literature review and synthesis of existing qualitative research principles.
Main Results:
- Data saturation is philosophically incompatible with constructivist and interpretivist research paradigms.
- Alternative concepts like information power, conceptual depth, and theoretical sufficiency offer more appropriate frameworks.
Conclusions:
- Researchers should adopt information power, conceptual depth, and theoretical sufficiency over data saturation.
- Data adequacy should be iteratively assessed throughout the research process, from design to analysis.
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