What are predetermined categories in qualitative data analysis?

Predetermined categories in qualitative data analysis refer to classifications or themes that researchers establish before gathering data. This approach allows researchers to have a focused framework when analyzing qualitative data, as these categories guide the identification, organization, and interpretation of the information collected.

Using predetermined categories can be particularly beneficial in ensuring consistency and rigor in analysis, as the researcher is not starting with a completely open mind but rather is informed by existing theories or prior research. This method can help to streamline the coding process, making it easier to identify relevant patterns and insights within the data that align with the predefined categories.

In contrast, specific themes established after data collection would imply a more open and exploratory approach, where themes emerge organically from the data itself rather than being imposed beforehand. Theoretical frameworks used to interpret qualitative data typically come into play once the initial analysis has taken place and insights are being interpreted within established scholarly contexts. Randomly selected themes from the data set do not represent a methodical approach and lack the structured intent that predetermined categories embody, thus diminishing the rigor of the analysis.