Tools to assess the risk of bias of evidence syntheses: a scoping review protocol

Author:

Hasanoff Sabira12,Pollock Danielle2,Barker Timothy2,Munn Zachary2

Affiliation:

1. JBI, School of Public Health, Faculty of Health and Medical Science, The University of Adelaide, Adelaide, SA, Australia

2. Health Evidence Synthesis, Recommendations, and Impact (HESRI), School of Public Health, Faculty of Health and Medical Science, The University of Adelaide, Adelaide, SA, Australia

Abstract

Objective: The aim of this scoping review is to identify and examine risk of bias tools, critical appraisal tools, and/or assessment of methodological quality tools (including their items and domains) developed to assess all types of evidence syntheses. Introduction: Evidence synthesis is often the basis for policies, procedures, decisions, and evidence-based practice. It is imperative that evidence syntheses are of good quality, reproducible, and reliable. Despite methodological advancements, there remains a substantial risk that bias is present in the conduct of an evidence synthesis project, hindering the validity and reliability of the findings. One way to assess bias is through formal tools and assessments for assessing the risk of bias and/or methodological quality. Inclusion criteria: Published and unpublished papers presenting a risk of bias, critical appraisal, or methodological quality assessment tool for assessing an evidence synthesis will be included. Individual umbrella reviews proposing a de novo tool or modified tool will be excluded from the review, as will texts that do not present a tool. Methods: A 3-step search strategy will be conducted to locate both published and unpublished documents. An initial search of PubMed was developed with a librarian, which identified keywords and MeSH terms. A second search of MEDLINE (Ovid), CINAHL (EBSCOhost), Embase (Ovid), Scopus, and Compendex will follow. Websites and databases, including Google, Cochrane, and JBI, will be searched for difficult-to-locate and unpublished literature. Documents will be independently screened, selected, and extracted by 2 researchers, and the data will be presented narratively and in tables. Review registration: Open Science Framework osf.io/mjcfy

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

General Nursing

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