Chandrasekar, Abinaya;
Clark, Sigrún Eyrúnardóttir;
Martin, Sam;
Vanderslott, Samantha;
Flores, Elaine C;
Aceituno, David;
Barnett, Phoebe;
... Vera San Juan, Norha; + view all
(2024)
Making the most of big qualitative datasets: a living systematic review of analysis methods.
Frontiers in Big Data
, 7
, Article 1455399. 10.3389/fdata.2024.1455399.
Preview |
Text
fdata-07-1455399 (1).pdf - Published Version Download (2MB) | Preview |
Abstract
Introduction Qualitative 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. Methods A 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. Results The 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. Discussion We 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 registration https://osf.io/hbvsy/?view_only=.
| Type: | Article |
|---|---|
| Title: | Making the most of big qualitative datasets: a living systematic review of analysis methods |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.3389/fdata.2024.1455399 |
| Publisher version: | http://dx.doi.org/10.3389/fdata.2024.1455399 |
| Language: | English |
| Additional information: | Copyright © 2024 Chandrasekar, Clark, Martin, Vanderslott, Flores, Aceituno, Barnett, Vindrola-Padros and Vera San Juan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
| Keywords: | big qualitative data, research methods, healthcare, digital tools, artificial intelligence, machine learning |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Surgery and Interventional Sci UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Surgery and Interventional Sci > Department of Targeted Intervention |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10197957 |
Archive Staff Only
 |
View Item |
