Open AccessGenerating best evidence from qualitative research: the role of data analysis
Author(s) -
Green Julie,
Willis Karen,
Hughes Emma,
Small Rhonda,
Welch Nicky,
Gibbs Lisa,
Daly Jeanne
Publication year - 2007
Publication title -
australian and new zealand journal of public health
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.946
H-Index - 76
eISSN - 1753-6405
pISSN - 1326-0200
DOI - 10.1111/j.1753-6405.2007.00141.x
Subject(s) - thematic analysis , data collection , clarity , qualitative analysis , data science , data analysis , coding (social sciences) , data quality , qualitative property , process (computing) , transparency (behavior) , qualitative research , computer science , psychology , data mining , sociology , mathematics , statistics , engineering , social science , biochemistry , chemistry , metric (unit) , operations management , computer security , machine learning , operating system
Objective:To outline the importance of the clarity of data analysis in the doing and reporting of interview‐based qualitative research.Approach:We explore the clear links between data analysis and evidence. We argue that transparency in the data analysis process is integral to determining the evidence that is generated. Data analysis must occur concurrently with data collection and comprises an ongoing process of ‘testing the fit’ between the data collected and analysis. We discuss four steps in the process of thematic data analysis: immersion, coding, categorising and generation of themes.Conclusion:Rigorous and systematic analysis of qualitative data is integral to the production of high‐quality research. Studies that give an explicit account of the data analysis process provide insights into how conclusions are reached while studies that explain themes anchored to data and theory produce the strongest evidence.