Causal Assessment in Evidence Synthesis: A Methodological Review of Reviews

Autor/inn/en	Shimonovich, Michal; Pearce, Anna; Thomson, Hilary; Katikireddi, Srinivasa Vittal
Titel	Causal Assessment in Evidence Synthesis: A Methodological Review of Reviews
Quelle	In: Research Synthesis Methods, 13 (2022) 4, S.405-423 (19 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Shimonovich, Michal)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1759-2879
DOI	10.1002/jrsm.1569
Schlagwörter	Evidence; Synthesis; Causal Models; Public Health; Research Design; Evaluation Criteria; Experiments; Meta Analysis + Suchen Sie Ihr Suchwort? Evidenz; Kausalanalyse; Gesundheitswesen; Forschungsdesign; Erprobung; Meta-analysis; Metaanalyse
Abstract	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. SRs may 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. Fifty-three reviews incorporated CAAs: 46/53 applied Bradford Hill (BH) 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 SRs (1/53, 1.9%); 'sign test' of causal mechanisms (1/53, 1.9%); and a causal cascade model (1/53, 1.9%). Though most SRs incorporated BH, 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. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01