Qualitative interpretative categorisation for efficient data analysis in a mixed methods information behaviour study

Introduction. This paper discusses the development of qualitative interpretative categorisation, a method of data analysis suitable for mixed methods information behaviour research. Method. The data analysis approach draws mainly on the work of Burnard, Sandelowski, and Miles and Huberman. The qualitative data was gathered from interviews (n=11) with nursing students at one site in the UK. Analysis. A start list of categories (from the research questions, and the quantitative findings) was modified through data reduction and clustering, with dendrograms used for data display and further interrogation of the data. Results. Of the seven initial categories, one was removed and another added. The title of one category was changed to reflect its new meaning. All categories were fully redefined. Conclusions. The method proposed offers a systematic approach to integrating qualitative data into a predominately quantitative mixed methods study.