Investigating change across time in prevalence or association: the challenges of cross-study comparative research and possible solutions

Cross-study research initiatives to understand change across time are an increasingly prominent component of social and health sciences, yet they present considerable practical, analytical and conceptual challenges. First, we discuss the key challenges to comparative research as a basis for detectin...

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Bibliographic Details
Published in:Discover social science and health 2022-01, Vol.2 (1), p.18-14, Article 18
Main Authors: Bann, David, Wright, Liam, Goisis, Alice, Hardy, Rebecca, Johnson, William, Maddock, Jane, McElroy, Eoin, Moulton, Vanessa, Patalay, Praveetha, Scholes, Shaun, Silverwood, Richard J., Ploubidis, George B., O’Neill, Dara
Format: Article
Language:English
Subjects:
Age
Associations
Biomedicine
Cohort analysis
Comparative analysis
Comparative research
Confounding (Statistics)
Cross-sectional studies
Cross-study analysis
Health disparities
Health sciences
Investigations
Measurement
Missing data
Mitigation
Newcomers
Perspective
Social mobility
Social Sciences
Syntax
Teaching
Time trends
Trends
Upward mobility
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Summary:Cross-study research initiatives to understand change across time are an increasingly prominent component of social and health sciences, yet they present considerable practical, analytical and conceptual challenges. First, we discuss the key challenges to comparative research as a basis for detecting societal change, as well as possible solutions. We focus on studies which investigate changes across time in outcome occurrence or the magnitude and/or direction of associations. We discuss the use and importance of such research, study inclusion, sources of bias and mitigation, and interpretation. Second, we propose a structured framework (a checklist) that is intended to provide guidance for future authors and reviewers. Third, we outline a new open-access teaching resource that offers detailed instruction and reusable analytical syntax to guide newcomers on techniques for conducting comparative analysis and data visualisation (in both R and Stata formats).
ISSN:2731-0469
2731-0469
DOI:10.1007/s44155-022-00021-1