Challenges and solutions during analysis in a longitudinal narrative case study
Qualitative analysis Previous     Next

Challenges and solutions during analysis in a longitudinal narrative case study

Charlotte Jane Whiffin Senior lecturer, Faculty of Education, Health and Science at the University of Derby, Chesterfield, UK
Chris Bailey Acting director of programmes, researcher development, Faculty of Health Sciences, at the University of Southampton, UK
Caroline Ellis-Hill Senior lecturer, School of Health and Social Care at Bournemouth University, UK
Nikki Jarrett Lecturer, Faculty of Health Sciences, at the University of Southampton, UK

Aim To describe the challenges faced by those performing complex qualitative analysis during a narrative study and to offer solutions.

Background Qualitative research requires rigorous analysis. However, novice researchers often struggle to identify appropriately robust analytical procedures that will move them from their transcripts to their final findings. The lack of clear and detailed accounts in the literature that consider narrative analysis and how to address some of the common challenges researchers face add to this problem.

Data sources A longitudinal narrative case study exploring the personal and familial changes reported by uninjured family members during the first year of another family member’s traumatic brain injury. Review methods This is a methodological paper.

Discussion The challenges of analysis included: conceptualising analysis; demonstrating the relationship between the different analytical layers and the final research findings; interpreting the data in a way that reflected the priorities of a narrative approach; and managing large quantities of data. The solutions explored were: the mapping of analytic intentions; aligning analysis and interpretation with the conceptual framework; and the use of matrices to store and manage quotes, codes and reflections.

Conclusion Working with qualitative data can be daunting for novice researchers. Ensuring rigorous, transparent, and auditable data analysis procedures can further constrain the interpretive aspect of analysis. Implications for research/practice The solutions offered in this paper should help novice researchers to manage and work with their data, assisting them to develop the confidence to be more intuitive and creative in their research.

Nurse Researcher. 21, 4, 20-26. doi: 10.7748/nr2014.03.21.4.20.e1238

Peer review

This article has been subject to double blind peer review

Conflict of interest

None declared

Received: 23 March 2013

Accepted: 28 August 2013

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