By Debra Morgan
Qualitative data analysis has been criticised for a lack of credibility over recent years when vagueness has been afforded to the reporting of how findings are attained. In response, there has been a growing body of literature emphasising a need to detail methods of qualitative data analysis. As a seasoned academic in nurse education, comfortable with the concept of evidence-based practice, I was concerned as a PhD researcher (exploring student nurse experiences of learning whilst studying abroad) to ensure I selected a sound approach to data analysis that would ensure transparency at each stage of the analysis process; so avoiding the aforementioned criticism from being levelled against my research.
The analytical journey began well, with the selection of the ‘phenomenological hermeneutical method for interpreting interview texts’ (Lindseth and Norberg, 2004). This method appeared ideally suited to my research methodology (hermeneutic phenomenology) and the process is well described by the authors, so offering the level of transparency desired. Briefly, this analysis method comprises three stages: naïve reading: the text must be read many times in an open-minded manner so that a first ‘naïve understanding’ is arrived at; structural analysis: commences with the identification of ‘meaning units’ from the text, these are condensed and sub-themes and themes emerge; comprehensive understanding: themes are further considered in relation to the research question and wider texts and a comprehensive understanding emerges (Lindseth and Norberg, 2004).
Analysis of each individual research participant’s data progressed well following these stages. However, I found it difficult to understand how I could then combine individual data to develop core phenomenon themes and yet not lose the individual student voice and learning experiences which were embedded in diverse contexts. This was concerning to me as my research comprised gathering student experiences of their learning in multiple contexts. For example, student experiences ranged from short placements in low and middle income countries in Africa and Asia, to longer placements in high income countries in Europe. Whilst the phenomenon of learning may exist in each diverse context, each experience is unique, therefore illuminating and preserving experiences in context was important to me. I was concerned to ensure that each individual ‘lived experience’, within each of these different contexts, were explored so that an understanding of learning in each type of placement could be revealed prior to developing a comprehensive understanding of the phenomenon more generically.
Whilst Lindseth and Norberg suggest reflecting on the emergent themes in relation to the context of the research (such as different study abroad types) at the final ‘comprehensive understanding’ stage, I felt it was important to preserve experiences specific to each study abroad type throughout each stage of data analysis in order they were not ‘lost’ during this process. To capture such contextual elements, Bazeley (2009) recommends describing, comparing and relating the characteristics or situation of the participants during analysis. I therefore incorporated these aspects into Lindseth and Norberg’s approach so that the varied study abroad types could be explored individually before then combining with the other types. In order to achieve this, I developed a modified approach to analysis. In particular, I further differentiated at the stage of structural analysis. Accordingly, I introduced two sub-stages, these are: ‘individual structural analysis’ and an additional ‘combined structural analysis’. This development represents a refinement in relation to moving from the individual participant experience (which I have termed ‘the individual horizonal perspective’ or ‘individual horizon’) to combined experiences of the phenomenon (respectively termed ‘the combined horizonal perspective’ or ‘combined horizon’).
This modified qualitative data analysis method ensures that the subjective origins of student, or research participant, experience and contexts remain identifiable throughout each stage of the data analysis process. Consequently, I feel this modification to an existing qualitative data analysis method permits greater transparency when dealing with data that relates to multiple contexts. I have called this approach the ‘Modified Phenomenological Hermeneutical Method of Data Analysis For Multiple Contexts’ and I have also developed a visual model to further illuminate this modified approach.
The ‘modified phenomenological hermeneutical method of data analysis for multiple contexts’ holds utility, and whilst my research is focused upon student nurse education it is transferable to other subject and research areas that involve multiple research contexts. To this effect, I have shared a reflexive review, and in this I include data extracts, of the development and application of this approach in my article: ‘Analysing complexity: Developing a modified phenomenological hermeneutical method of data analysis for multiple contexts’ published in‘The International Journal of Social Research Methodology’. This paper also presents the developed visual model. Additionally, an exploration of the underpinning theoretical basis to this data analysis method, and modification is provided, so adding to the expanding body of evidence and reflecting the ethos of transparency in qualitative data analysis.
Read the full IJSRM article here.
Bazeley, P. (2009). Analysing qualitative data: More than ‘identifying themes’. Malaysian Journal of Qualitative Research 2, 6-22. Lindseth, A. & Norberg, A. (2004). A phenomenological hermeneutical method for researching lived experience. Scandinavian Journal of Caring sciences 18(2), 145-153.