Analysing Qualitative Data

This is the second in a series of three articles Contrary to popular perception, qualitative research can produce vast amounts of data. These may include verbatim notes or transcribed recordings of interviews or focus groups, jotted notes and more detailed “fieldnotes” of observational research, a diary or chronological account, and the researcher's reflective notes made during the research. These data are not necessarily small scale: transcribing a typical single interview takes several hours and can generate 20–40 pages of single spaced text. Transcripts and notes are the raw data of the research. They provide a descriptive record of the research, but they cannot provide explanations. The researcher has to make sense of the data by sifting and interpreting them. #### Summary points Qualitative research produces large amounts of textual data in the form of transcripts and observational fieldnotes The systematic and rigorous preparation and analysis of these data is time consuming and labour intensive Data analysis often takes place alongside data collection to allow questions to be refined and new avenues of inquiry to develop Textual data are typically explored inductively using content analysis to generate categories and explanations; software packages can help with analysis but should not be viewed as short cuts to rigorous and systematic analysis High quality analysis of qualitative data depends on the skill, vision, and integrity of the researcher; it should not be left to the novice In much qualitative research the analytical process begins during data collection as the data already gathered are analysed and shape the ongoing data collection. This sequential analysis1 or interim analysis2 has the advantage of allowing the researcher to go back and refine questions, develop hypotheses, and pursue emerging avenues of inquiry in further depth. Crucially, it also enables the researcher to look for deviant or negative cases; that is, …