Sample Size and Validity in Qualitative Studies Article Review

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Study Design LimitationsThe article Healing Faith: A Qualitative Exploration of Latina Breast Cancer Survivors by Barden et al. (2016) uses a qualitative design to explore the experiences of survivors of breast cancer. The qualitative method is useful in gaining insight into experiences, but it is limited in terms of generalizability and data robustness (McGinley et al., 2021).First off, sample size is a limitation. Qualitative studies necessarily use small samples (the research cannot be conducted otherwise as interviewing a large sample would be too much). The samples are typically purposive rather than random, which could limit the representativeness of the data. In this study, Latina breast cancer survivors\' experiences may not reflect those of broader populations or other ethnic groups, so the study might not have much external validity.Another limitation is the subjectivity that is necessarily inherent in qualitative research. Not only is data subjective (the self-reporting of individual people), but so too is the interpretation of the data (the researcher’s view of it). The researcher can explain how the interpretation was done (framed, analyzed, and so on), but the findings are interpreted through the lens of the researcher, which means there is the risk of researcher bias. In the case of the study by Barden et al. (2016), cultural factors regarding faith and healing are analyzed based on subjective interpretations.

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Also, recall bias is concern. Since the study relies on survivors\' memories, there may be some inaccurate or incomplete data.To address these limitations, triangulation would help by supporting the study\'s validity. This would involve using multiple data sources, such as quantitative data (statistics) along with qualitative interviews, to cross-verify findings. Expanding the sample size and including a wider range of participants from diverse backgrounds could improve generalizability. There is also the potential use of reflexivity—where the researcher reflects on his biases throughout the study—to reduce the risk of subjectivity influencing the findings......

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