Data Saturation

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For qualitative research methods, data saturation is a significant question, how much information is enough, too much, and sufficient. In the simplest context, sufficient when enough data is gathered to substantiate reliable and duplicatable findings are sufficient for meeting the rigor test in qualitative research. Verifying the saturation point for sufficient qualitative data rests with the inductive and deductive reasoning of the researcher. As data is acquired it must be coded and judged as relevant to the research question. Irrelevant data is discarded while relevant data is included. Once sufficient data is accumulated to make a reasonable analysis in a method duplicatable by other researchers in other similar situations is achieved the study has reached its point of saturation. 

The realization of sufficient data is arrived at using the grounded theory of qualitative data acquisition and analysis. “First, the aim of methodological coherence is to ensure congruence between the research question and the components of the method” (Morse et al., 2002, p. 18). Evaluating the appropriate sample, analyzing correctly, thinking theoretically, and developing a sound theory accounting for the numerous variables are essential to the validity of the qualitative study. This is all part of the “verification strategies” for qualitative research in clinical practice (Morse et al. 2002, p. 10). Above all else, the validity of the qualitative study’s findings is essential in data collection. 

Data saturation occurs when there is sufficient data to answer the research question in an irrefutable manner among researchers using this technique. Research design and theoretical approach may doom a qualitative study if its methods are not duplicatable. Therefore, only data that is acquired in a reasonable manner and properly analyzed is considered valid in a qualitative study. There must be a mechanism for the elimination of data collected that is theoretically biased or does not contribute to the answering of the research question. This is a subjective process that relies heavily on the researcher’s inductive and deductive abilities in grounded theory. Certainly, data that opposes the question is not eliminated per se, however, in qualitative methods, the discovery is the thing. Data may trend to other themes that motivate the researcher to reconsider the ultimate question. This is the nature of the qualitative study, and while it invites a quantitative critique, its advantages to humanistic or phenomenological inquiry out weight quantitative contributions to answering questions. 

References

Creswell, J. W. (2003). Research design: qualitative, quantitative, and mixed method approaches (2nd ed.). Thousand Oaks, Calif.: Sage Publications.

Morse, J., Barrett, M., Mayan, M., Olson, K., & Spiers, J. (2002). Verification strategies for establishing reliability and validity in qualitative research. International Journal of Qualitative Methods, 1(2), 13-22. Retrieved March 18, 2013, from https://ejournals.library.ualberta.ca/index.php/IJQM/article/viewArticle/4603