Book reviews

Using Software in Qualitative Research: a step-by-step guide, by Christina Silver and Ann Lewins. 2nd edition. Sage 2014.

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    Dr Mike Lambert
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    There are two main reasons for reading a book on research: either you wish to examine how it confirms your already substantial knowledge in the chosen field, or you know relatively little about its topic and hope that the book will help you advance from your ‘novice’ status.  This review comes from the latter perspective: a wish to know more about computer analysis of qualitative data, in order to be better able to use relevant software in research activity.

     

    First impressions of this book are not wholly encouraging: an uninviting cover and a rather weighty feel overall.  However, the ‘step-by-step’ in the subtitle and ‘essential introduction’ in the blurb both sound helpful.  The book’s several reprints and now this second edition are evidence of its continuing popularity, and the authors’ expertise (both are supremely experienced in the relatively short history of this field) gives further reassurance.

     

    The topic is CAQDAS – ‘Computer Assisted Qualitative Data AnalysiS’ – software which aids and supports the often laborious process of analysing qualitative data.  The main aim is ‘to enable ambitious yet secure use of any CAQDAS package and the moulding of its functions to your needs’ (p.8), allowing researchers ‘to be more transparent in how we go about analysis’ (p.11).  Seven software types are covered in detail in the book: ATLAS.ti, Dedoose, HyperRESEARCH, MAXQDA, NVivo, QDA Miner and Transana. 

     

    The ‘step-by-step’ element refers not to gradual growth in understanding of the whole field, but rather to the stages of undertaking a research project. The first focus is therefore on preparation of data and early practical tasks; followed by data-level work, coding, retrieval of data and working with coding schemes; then finally to writing, mapping ideas, and organizing and interrogating the dataset.  Three case studies, available on the Internet (http://bit.ly/1uk2FoB), provide material for scrutiny of how CAQDAS can serve these different parts of the research process.

     

    I found the topic as a whole difficult going at times, but the book’s scope is wide and deep, its text clear, authoritative and practical in nature.  In particular, I appreciated the early summary of the strengths of each software package for particular research tasks, also the parts dealing with visual data, for which CAQDAS seems particularly suitable.  Using software will, of course, mean that you and your project colleagues may spend much time in front of a computer screen – it was good therefore to see the authors suggesting a return to the ‘basics’ of printed sheets and manual writing of codes, when the situation warrants it. 

     

    Another key point further stresses this kind of flexibility: ‘Our central message is that you should determine what is useful … Experimentation is what makes it fun’ (p.338).  It is a helpful reminder that CAQDAS is best employed when informed by thorough understanding of research processes in general, including, but not only, those related to data analysis.

     

    This is a full and varied book, which will reward close reading and frequent returns to sections of particular interest.  If you are serious about your wish to understand CAQDAS and to use such software in your research, as an individual or in a project team, then this is a book I would thoroughly recommend.

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