Qualitative research: Data analysis

Different types of data analysis can be applied in qualitative research. A basic distinction is made between data analysis as inductive – i.e. analysis start from the collected data, which successively could lead to the discovery of themes or concepts –  or as deductive – the analysis starts from a framework, for instance predetermined themes or categories based on a theory or the literature, or the analysis is a mix of an inductive or deductive approach. This depends on the perspective or aims of the research.
There are several general principles in qualitative data analysis that lead to ‘good practices’, like the importance of transparency, validity, reliability, comparison and reflexivity (see Green & Thorogood, 2010, chapter 8). It is important to note down decisions and steps in a logbook. Frambach et al (2013) offer a useful overview of different quality criteria.

Read more:

  • Boeije, H. (2010) Analysis in Qualitative Research. London: Sage Publications.
    Written for anyone beginning a research project, this introductory book takes you through the process of analysing your data from start to finish. The author sets out an easy-to-use model for coding data in order to break it down into parts, and then to reassemble it to create a meaningful picture of the phenomenon under study. The book guides the reader through the last difficult integrating phase of qualitative analysis including diagramming, memoing, thinking aloud, and using one’s feelings, and how to incorporate the use of software where appropriate. (Also available in Dutch: Analyseren in kwalitatief onderzoek: Denken en doen. Tweede editie in 2014.)
  • Green, J. & Thorogood, N. (2010) Qualitative Methods for Health Research. Third Edition. London: Sage Publications.
    Chapter 8 provides information on analysing qualitative data.
  • Frambach, J. et al. (2013) AM Last Page: Quality Criteria in Qualitative and Quantitative Research. Academic Medicine, 88, 4, 552.
    While qualitative and quantitative research share similar standards for good evidence (quality criteria), the conception and operationalization of these quality criteria differ between the two. This page provides an overview of these criteria and a number of techniques that researchers can use to meet them.
  • Ranney, M.L. et al. (2015) Interview-based Qualitative Research in Emergency Care Part II: Data collection, Analysis and Results Reporting. Academic Emergency Medicine, 22, 1103-1112.
    Gives an outline the specific steps necessary to conduct a valid and reliable qualitative research project, with a focus on interview-based studies. These elements include building the research team, preparing data collection guides, defining and obtaining an adequate sample, collecting and organizing qualitative data, and coding and analyzing the data. With a discussion on potential ethical considerations unique to qualitative research as it relates to emergency care research.

Dutch references:

  • Wester, F. (2004) Analyse van kwalitatief onderzoeksmateriaal. Huisarts & Wetenschap, 47 (12), 565-570.
  • Mortelmans, D. (2009) Handboek kwalitatieve onderzoeksmethoden. Tweede druk. Leuven/Den Haag: Acco.
    Chapter 10 gives a detailed description of data analysis according to the grounded theory analysis approach with illustrative examples.

 

Approaches

There are many different approaches to qualitative data analysis, like content analysis, structural analysis or framework analysis. The choice is related to the aims of the study. The most basic form is content analysis, an approach in which the categorization of themes is central. Other approaches focus on, for instance, the context in which events are storied (how and why, see Riessman 2008), or the thematic framework in which data can be classified. Wertz et al. (2011) offer insightful examples of how different analytic lenses lead to different processes of analysis and specific outcomes.

Read more:

  • Braun, V. & Clarke, V. (2006) Using thematic analysis in psychology. Qualitative Research in Psychology, 3 (2), 77-101.
  • Green, J. & Thorogood N. (2010) Qualitative Methods for Health Research. Third Edition. London: Sage Publications.
    See chapter 8 on analysing qualitative data.
  • Hodges, B.D. & Reeves, S. (2008) Discourse analysis. BMJ, 337: a879.
    This article focuses on discourse analysis. It provides background information for those who will encounter this approach in their reading, rather than instructions for conducting such research.
  • Riessman, C.K. (2008) Narrative Methods for the Human Sciences. Los Angeles: Sage Publications.
    Book on narrative analysis, with chapters on thematic analysis, structural analysis, dialogic/performance analysis and visual analysis.
  • Smith, B. & Sparkes, A.C. (2005) Analyzing Talk in Qualitative Inquiry: Exploring Possibilities, Problems, and Tensions. Quest, 57: 213-242.
    The authors consider five ways in which narratives can be analysed to incorporate the hows and whats of their telling: an analysis of conversation, an analysis of discourse, an analysis of how narratives are performed, an analysis of content, and an analysis of structure. Includes strengths and weaknesses and exemplars of each approach.
  • Wertz, F.J. et al. (2011) Five ways of doing qualitative analysis. Phenomenological psychology, Grounded Theory, Discourse Analysis, Narrative Research, and Intuitive Inquiry. New York: the Guilford Press.
    Comparison of five types of analytic lenses, all applied to the same interview transcript. Exemplifies what each approach looks like in action and shows similarities and differences between the approaches.

 

Computer assisted qualitative data analysis software

There are various software programmes that support the analysis of qualitative data, such as Atlas.ti, MaxQDA and NVivo. These can be a useful tool in ordering the data efficiently, although you will need to order the data yourself. Currently, software developers of these programs are working on an exchange format, which makes it possible for qualitative researchers to shift between these programs (i.e. Atlas.ti, MaxQda, NVivo and other software) while working on their research project. This exchange software format will be available from 2018 on. See for more information on this project the website of Kwalon: www.kwalon.nl.
These software programmes offer more or less the same options. Please consult the Data Management Department for license information (datamanagement@vumc.nl).

 

V3.0: 20 Oct 2017: Revision guideline
V2.0: 12 May 2015: Revision format
V1.2: 1 Dec 2011: Removal of link kwalitatief sterk
V1.1: 1 Jan 2010: English translation
V1.0: 23 Nov 2006: Draft version has been rewritten in full