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Current trends in the application of causal inference methods to pooled longitudinal non-randomised data: a protocol for a methodological systematic review.
Yeboah, Edmund; Mauer, Nicole Sibilla; Hufstedler, Heather; Carr, Sinclair; Matthay, Ellicott C; Maxwell, Lauren; Rahman, Sabahat; Debray, Thomas; de Jong, Valentijn M T; Campbell, Harlan; Gustafson, Paul; Jänisch, Thomas; Bärnighausen, Till.
  • Yeboah E; Heidelberg Institute of Global Health, Heidelberg University, Heidelberg, Germany.
  • Mauer NS; Heidelberg Institute of Global Health, Heidelberg University, Heidelberg, Germany.
  • Hufstedler H; Heidelberg Institute of Global Health, Heidelberg University, Heidelberg, Germany heather.hufstedler@uni-heidelberg.de.
  • Carr S; Heidelberg Institute of Global Health, Heidelberg University, Heidelberg, Germany.
  • Matthay EC; Center for Interdisciplinary Addiction Research, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
  • Maxwell L; Center for Health and Community, University of California San Francisco, San Francisco, California, USA.
  • Rahman S; Heidelberg Institute of Global Health, Heidelberg University, Heidelberg, Germany.
  • Debray T; University of Massachusetts Medical School, University of Massachusetts, Worchester, Massachusetts, USA.
  • de Jong VMT; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Campbell H; Cochrane Netherlands, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Gustafson P; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Jänisch T; Department of Statistics, University of British Columbia, Vancouver, British Columbia, Canada.
  • Bärnighausen T; Department of Statistics, University of British Columbia, Vancouver, British Columbia, Canada.
BMJ Open ; 11(11): e052969, 2021 11 12.
Article in English | MEDLINE | ID: covidwho-1515303
ABSTRACT

INTRODUCTION:

Causal methods have been adopted and adapted across health disciplines, particularly for the analysis of single studies. However, the sample sizes necessary to best inform decision-making are often not attainable with single studies, making pooled individual-level data analysis invaluable for public health efforts. Researchers commonly implement causal methods prevailing in their home disciplines, and how these are selected, evaluated, implemented and reported may vary widely. To our knowledge, no article has yet evaluated trends in the implementation and reporting of causal methods in studies leveraging individual-level data pooled from several studies. We undertake this review to uncover patterns in the implementation and reporting of causal methods used across disciplines in research focused on health outcomes. We will investigate variations in methods to infer causality used across disciplines, time and geography and identify gaps in reporting of methods to inform the development of reporting standards and the conversation required to effect change. METHODS AND

ANALYSIS:

We will search four databases (EBSCO, Embase, PubMed, Web of Science) using a search strategy developed with librarians from three universities (Heidelberg University, Harvard University, and University of California, San Francisco). The search strategy includes terms such as 'pool*', 'harmoniz*', 'cohort*', 'observational', variations on 'individual-level data'. Four reviewers will independently screen articles using Covidence and extract data from included articles. The extracted data will be analysed descriptively in tables and graphically to reveal the pattern in methods implementation and reporting. This protocol has been registered with PROSPERO (CRD42020143148). ETHICS AND DISSEMINATION No ethical approval was required as only publicly available data were used. The results will be submitted as a manuscript to a peer-reviewed journal, disseminated in conferences if relevant, and published as part of doctoral dissertations in Global Health at the Heidelberg University Hospital.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Research Design / Delivery of Health Care Type of study: Cohort study / Experimental Studies / Observational study / Prognostic study / Randomized controlled trials / Reviews / Systematic review/Meta Analysis Limits: Humans Country/Region as subject: North America Language: English Journal: BMJ Open Year: 2021 Document Type: Article Affiliation country: Bmjopen-2021-052969

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Research Design / Delivery of Health Care Type of study: Cohort study / Experimental Studies / Observational study / Prognostic study / Randomized controlled trials / Reviews / Systematic review/Meta Analysis Limits: Humans Country/Region as subject: North America Language: English Journal: BMJ Open Year: 2021 Document Type: Article Affiliation country: Bmjopen-2021-052969