How do I justify the sample size in a phenomenology study design used in my Ph. D. Thesis?
In qualitative phenomenology studies, sample size is typically determined through a process known as "data saturation" rather than using statistical formulas commonly used in quantitative research. Data saturation refers to the point at which collecting additional data no longer reveals new insights or information, indicating that the sample size is sufficient.
Qualitative phenomenology focuses on understanding the lived experiences and perspectives of a small number of participants in-depth rather than aiming for a large representative sample. The aim is to gather rich, detailed data that provides a deep understanding of the phenomenon under investigation.
Researchers typically continue collecting data and conducting interviews until they reach a point of saturation, where new interviews and data collection do not contribute significantly to the emerging themes and insights. Saturation can vary depending on the complexity of the phenomenon and the depth of analysis desired. Researchers often continue data collection until they are confident that they have captured a comprehensive understanding of the phenomenon.
Therefore, in qualitative phenomenology studies, there is no fixed or predetermined sample size formula. The focus is on the richness and depth of the data rather than the quantity of participants. Researchers should aim to include an adequate number of participants to achieve data saturation and capture the diverse perspectives and experiences related to the phenomenon of interest.
[1]Rameshwar Gupta*,
Research Scholar,
Department of Lifelong Learning & Extension
CSJM University, Kanpur, U.P. India
Email id: [email protected]
Whatsapp/Mobile: +918630831266
[1]Ph.D. Student, Department of Lifelong Learning & Extension, CSJM University, Kanpur, U.P., India, Email id: [email protected], Mobile: 8630831266
*Single author
As opposed to quantitative research, qualitative phenomenology studies do not determine sample size using conventional statistical formulas. Researchers frequently use a technique known as "purposive sampling" to establish the ideal sample size for a qualitative phenomenology study. In purposive sampling, participants must be carefully chosen in order to have the most pertinent and insightful data regarding the research questions.
The number of participants recruited may vary depending on the context of the study, the type of phenomenon being studied, and the degree of data saturation attained. Researchers typically aim to recruit 15 to 20 participants. Since, instead of aiming for a particular number determined by statistical calculations, the emphasis is on choosing a sample size that permits thorough investigation and saturation of the data. So as such, there is no set formula for determining sample size in qualitative phenomenology research. However, you may quote sample size used by published works in your research field as a reference to why you too have used a particular sample size.
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I do not think that phenomenological studies should rely on saturation, because the process of analysis is more intensive for this kind of research. For Interpretive Phenomenological Analysis. Smith, Flowers, and Larkins (2009) recommend sample sizes of 3 to 9.
Data saturation, not a formula, determines the sample size in qualitative studies. Researchers select participants based on their relevance and insights. The number of respondents depends on factors like complexity and data richness. Data saturation is reached when new participants do not provide substantially different insights. That said, Morse (2000) recommended 6–10 participants for phenomenological studies. Here are some helpful reads.
Morse, J. M. (2000). Determining sample size. Qualitative Health Research, 10(1), 3–5. https://doi.org/10.1177/104973200129118183
Sim, J., Saunders, B., Waterfield, J., & Kingstone, T. (2018). Can sample size in qualitative research be determined a priori? International Journal of Social Research Methodology, 21(5), 619-634. https://doi.org/10.1080/13645579.2018.1454643
Good luck,
In qualitative phenomenology studies, the determination of sample size is not guided by statistical formulas but rather by the principles of data saturation, which refers to the point at which collecting additional data no longer provides new insights or information. Therefore, the most appropriate approach for calculating sample size in a qualitative phenomenology study is to continue data collection until data saturation is achieved. To justify the sample size in your Ph.D. thesis, you can provide a clear description of your data collection process, including the number of participants, the criteria used for participant selection, and a comprehensive explanation of how data saturation was reached. This demonstrates rigor and transparency in your research design, ensuring that your sample size is appropriate and aligns with the goals and objectives of your phenomenological study.
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