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The revised JBI critical appraisal tool for the assessment of risk of bias for analytical cross-sectional studies

  • Timothy H. Barker
  • , Sabira Hasanoff
  • , Edoardo Aromataris
  • , Jennifer C. Stone
  • , Jo Leonardi-Bee
  • , Kim Sears
  • , Miloslav Klugar
  • , Catalin Tufanaru
  • , Sandeep Moola
  • , Xian Liang Liu
  • , Zachary Munn

Research output: Contribution to journal › Article › peer-review

168 Citations (Scopus)

Abstract

Cross-sectional studies are a useful observational study design that provide a snapshot of a population’s health status at a specific moment in time. Analytical cross-sectional studies are often included in systematic reviews investigating the etiology or risk of diseases, and descriptive cross-sectional studies are often used to determine the prevalence of a disease. As required of all studies that meet eligibility criteria for a systematic review, analytical cross-sectional studies should be subjected to appropriate critical appraisal of their methodological quality to determine the risk of bias. The JBI Effectiveness Methodology Group is currently undertaking a comprehensive revision of the entire suite of JBI critical appraisal tools to align with recent advances in risk of bias assessment. This paper presents the revised critical appraisal tool for risk of bias assessment of analytical cross-sectional studies. Applying tools such as the revised JBI tools within systematic reviews allows end users to make informed decisions using the evidence. We discuss major changes from the previous iterations of this tool and justify these changes within the context of the broader advancements to risk-of-bias assessment science. We also offer practical guidance for the use of this revised tool, and provide examples for interpreting the results of risk-of-bias assessment for analytical cross-sectional studies to support reviewers including these studies in their systematic reviews.

Original languageEnglish
Pages (from-to)401-408
Number of pages8
JournalJBI Evidence Synthesis
Volume24
Issue number3
DOIs
Publication statusPublished - Mar 2026

Keywords

  • bias assessment
  • cross-sectional studies
  • methodology
  • risk of bias
  • systematic review

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