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Optimising qualitative longitudinal analysis: Insights from a study of traumatic brain injury recovery and adaptation
Author(s) -
Fadyl Joanna K,
Chan Alexis,
Theadom Alice,
McPherson Kathryn M
Publication year - 2017
Publication title -
nursing inquiry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.66
H-Index - 49
eISSN - 1440-1800
pISSN - 1320-7881
DOI - 10.1111/nin.12170
Subject(s) - qualitative research , adaptation (eye) , grounded theory , psychological intervention , coding (social sciences) , health care , rehabilitation , psychology , data science , applied psychology , computer science , sociology , political science , psychiatry , social science , neuroscience , law
Knowledge about aspects that influence recovery and adaptation in the postacute phase of disabling health events is key to understanding how best to provide appropriate rehabilitation and health services. Qualitative longitudinal research makes it possible to look for patterns, key time points and critical moments that could be vital for interventions and supports. However, strategies that support robust data management and analysis for longitudinal qualitative research in health‐care are not well documented in the literature. This article reviews three challenges encountered in a large longitudinal qualitative descriptive study about experiences of recovery and adaptation after traumatic brain injury in New Zealand, and the strategies and technologies used to address them. These were (i) tracking coding and analysis decisions during an extended analysis period; (ii) navigating interpretations over time and in response to new data; and (iii) exploiting data volume and complexity. Concept mapping during coding review, a considered combination of information technologies, employing both cross‐sectional and narrative analysis, and an expectation that subanalyses would be required for key topics helped us manage the study in a way that facilitated useful and novel insights. These strategies could be applied in other qualitative longitudinal studies in healthcare inquiry to optimise data analysis and stimulate important insights.