Causal assessment in evidence synthesis: a methodological review of reviews

Shimonovich, M. , Pearce, A. , Thomson, H. and Katikireddi, S. V. (2022) Causal assessment in evidence synthesis: a methodological review of reviews. Research Synthesis Methods, 13(4), pp. 405-423. (doi: 10.1002/jrsm.1569) (PMID:35560730) (PMCID:PMC9543433)

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In fields (such as population health) where randomised trials are often lacking, systematic reviews (SRs) can harness diversity in study design, settings and populations to assess the evidence for a putative causal relationship. Some SRs incorporate causal assessment approaches (CAAs), sometimes called ‘causal reviews’, but there is currently no consensus on how these should be conducted. We conducted a methodological review of self-identifying ‘causal reviews’ within the field of population health to establish: 1) which CAAs are used; 2) differences in how CAAs are implemented; 3) how methods were modified to incorporate causal assessment in SRs. Three databases were searched and two independent reviewers selected reviews for inclusion. Data were extracted using a standardised form and summarised using tabulation and narratively. 53 reviews incorporated CAA: 46/53 applied Bradford Hill viewpoints/criteria, with the remainder taking alternative approaches: Medical Research Council guidance on natural experiments (2/53, 3.8%); realist reviews (2/53, 3.8%); horizontal systematic reviews (1/53, 1.9%); ‘sign test’ of causal mechanisms (1/53, 1.9%); and causal cascade model (1/53, 1.9%). Though most SRs incorporated Bradford Hill, there was variation in application and transparency. There was considerable overlap across the CAAs, with a trade-off between breadth (BH viewpoints considered a greater range of causal characteristics) and depth (many alternative CAAs focused on one viewpoint). Improved transparency in the implementation of CAA in SRs in needed to ensure their validity and allow robust assessments of causality within evidence synthesis.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Katikireddi, Professor Vittal and Thomson, Dr Hilary and Pearce, Dr Anna and Shimonovich, Ms Michal
Authors: Shimonovich, M., Pearce, A., Thomson, H., and Katikireddi, S. V.
College/School:College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > MRC/CSO SPHSU
University Services > Learning and Teaching Services Division
Journal Name:Research Synthesis Methods
ISSN (Online):1759-2887
Published Online:13 May 2022
Copyright Holders:Copyright © 2022 The Authors
First Published:First published in Research Synthesis Methods 13(4): 405-423
Publisher Policy:Reproduced under a Creative Commons License

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
3048230071Inequalities in healthAlastair LeylandOffice of the Chief Scientific Adviser (CSO)SPHSU17HW - MRC/CSO Social and Public Health Sciences Unit
3048230021Inequalities in healthAlastair LeylandMedical Research Council (MRC)MC_UU_00022/2HW - MRC/CSO Social and Public Health Sciences Unit
172690Understanding the impacts of welfare policy on health: A novel data linkage studySrinivasa KatikireddiOffice of the Chief Scientific Adviser (CSO)SCAF/15/02SHW - Public Health
174091Improving life chances & reducing child health inequalities: harnessing the untapped potential of existing dataAnna PearceWellcome Trust (WELLCOTR)205412/Z/16/ZSHW - MRC/CSO Social & Public Health Sciences Unit