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

  • David Bann
  • , Liam Wright
  • , Alice Goisis
  • , Rebecca Hardy
  • , William Johnson
  • , Jane Maddock
  • , Eoin McElroy
  • , Vanessa Moulton
  • , Praveetha Patalay
  • , Shaun Scholes
  • , Richard J. Silverwood
  • , George B. Ploubidis
  • , Dara O’Neill

Research output: Contribution to journalArticlepeer-review

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Abstract

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).

Supplementary Information: The online version contains supplementary material available at 10.1007/s44155-022-00021-1.

Original languageEnglish
Article number18
JournalDiscover Social Science and Health
Volume2
Issue number1
Early online date27 Oct 2022
DOIs
Publication statusPublished online - 27 Oct 2022

Bibliographical note

© The Author(s) 2022.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being
  2. SDG 10 - Reduced Inequalities
    SDG 10 Reduced Inequalities

Keywords

  • Perspective
  • Comparative research
  • Time trends
  • Cross-study analysis
  • Measurement
  • Missing data

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