Making the most of big qualitative datasets: a living systematic review of analysis methods: Front. Big Data

Abinaya Chandrasekar; Sigrún Eyrúnardóttir Clark; Sam Martin; Samantha Vanderslott; Elaine C Flores; David Aceituno; Phoebe Barnett; Cecilia Vindrola-Padros; Norha Vera San Juan

doi:10.3389/fdata.2024.1455399

Making the most of big qualitative datasets: a living systematic review of analysis methods: Front. Big Data

Abinaya Chandrasekar, Sigrún Eyrúnardóttir Clark, Sam Martin, Samantha Vanderslott, Elaine C Flores, David Aceituno, Phoebe Barnett, Cecilia Vindrola-Padros, Norha Vera San Juan

Research output: Contribution to journal › Article › peer-review

2 Citations (Scopus)

Abstract

IntroductionQualitative data provides deep insights into an individual's behaviors and beliefs, and the contextual factors that may shape these. Big qualitative data analysis is an emerging field that aims to identify trends and patterns in large qualitative datasets. The purpose of this review was to identify the methods used to analyse large bodies of qualitative data, their cited strengths and limitations and comparisons between manual and digital analysis approaches.MethodsA multifaceted approach has been taken to develop the review relying on academic, gray and media-based literature, using approaches such as iterative analysis, frequency analysis, text network analysis and team discussion.ResultsThe review identified 520 articles that detailed analysis approaches of big qualitative data. From these publications a diverse range of methods and software used for analysis were identified, with thematic analysis and basic software being most common. Studies were most commonly conducted in high-income countries, and the most common data sources were open-ended survey responses, interview transcripts, and first-person narratives.DiscussionWe identified an emerging trend to expand the sources of qualitative data (e.g., using social media data, images, or videos), and develop new methods and software for analysis. As the qualitative analysis field may continue to change, it will be necessary to conduct further research to compare the utility of different big qualitative analysis methods and to develop standardized guidelines to raise awareness and support researchers in the use of more novel approaches for big qualitative analysis.Systematic review registrationhttps://osf.io/hbvsy/?view_only=.

Original language	English
Journal	Frontiers in Big Data
Volume	7
DOIs	https://doi.org/10.3389/fdata.2024.1455399
Publication status	Published - 25 Sept 2024

Keywords

big qual data
Research Methods
healthcare
digital tools
artificial intelligence
machine learning
# Read it
5. Publications

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10.3389/fdata.2024.1455399Licence: CC BY

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abstract = "IntroductionQualitative data provides deep insights into an individual's behaviors and beliefs, and the contextual factors that may shape these. Big qualitative data analysis is an emerging field that aims to identify trends and patterns in large qualitative datasets. The purpose of this review was to identify the methods used to analyse large bodies of qualitative data, their cited strengths and limitations and comparisons between manual and digital analysis approaches.MethodsA multifaceted approach has been taken to develop the review relying on academic, gray and media-based literature, using approaches such as iterative analysis, frequency analysis, text network analysis and team discussion.ResultsThe review identified 520 articles that detailed analysis approaches of big qualitative data. From these publications a diverse range of methods and software used for analysis were identified, with thematic analysis and basic software being most common. Studies were most commonly conducted in high-income countries, and the most common data sources were open-ended survey responses, interview transcripts, and first-person narratives.DiscussionWe identified an emerging trend to expand the sources of qualitative data (e.g., using social media data, images, or videos), and develop new methods and software for analysis. As the qualitative analysis field may continue to change, it will be necessary to conduct further research to compare the utility of different big qualitative analysis methods and to develop standardized guidelines to raise awareness and support researchers in the use of more novel approaches for big qualitative analysis.Systematic review registrationhttps://osf.io/hbvsy/?view_only=.",

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AU - Flores, Elaine C

AU - Aceituno, David

AU - Barnett, Phoebe

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Making the most of big qualitative datasets: a living systematic review of analysis methods: Front. Big Data

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