In Chapter 24, Polit and Beck (2017) present a discussion about the analysis of qualitative data, which is different from the quantitative one in relying on non-statistical approaches. The authors consider the key aspects of working with data, including its management, analysis, and findings interpretation. The key concepts include category scheme development and coding (data organization and indexation), thematic analysis (common themes search), and making meaning of findings (for example, through “living” the data). Also, the authors discuss specific approaches to analysis. For example, they report that the grounded theory research employs the constant comparative approach, which consists of comparing the content of one source with the rest of them. Also, ethnography favors the method of finding and comparing patterns, and phenomenology uses the “holistic” strategy, which presupposes taking into account the context of the text in its entirety.
The chapter does not contain a description of statistical methods, but it mentions quasi-statistics, which can be employed to validate chosen themes. It presupposes determining the frequency of the appearance of a particular theme, and this method can be used to discard the null hypothesis of the rarity (infrequency) of a phenomenon. The authors mention a 2009 study, which employed this approach to calculate the frequency of reported sexual behaviors. Similarly, Oyedele, Wright, and Maja (2014) use the method to consider the frequency of specific themes in the perceptions about teenage pregnancy in the population of interest (various stakeholders from a province in South Africa). For instance, they discover that a third of the participants discourage the use of contraceptives by teenagers; the authors also provide excerpts that explain their motivation (for example, religious considerations).
Statistical tests are used with numeric (quantitative) data. As demonstrated by Polit and Beck (2017) in other chapters, statistical tests can be utilized with qualitative (non-numeric) data if it is transformed into nominal variables. The tests that can work with this approach and that are mentioned by Polit and Beck (2017) in their chapter on inferential statistics include chi-square, Fisher’s and McNemar’s tests and Cochran’s Q for group comparisons and phi coefficient and Cramér’s V for correlational analysis. Eventually, this approach presupposes applying quantitative methods to the information that has been translated into quantitative data. Instead, qualitative research employs the narrative data analyses which Polit and Beck (2017) discuss in Chapter 24.
Oyedele, O., Wright, S., & Maja, T. (2014). Community participation in teenage pregnancy prevention based on the community-as-partner model. International Journal of Nursing and Midwifery, 6(6), 80-89. Web.
Polit, D. F., & Beck, C. T. (2017). Nursing research: Generating and assessing evidence for nursing practice (10th ed.). Philadelphia, PA: Wolters Kluwer.