Cited by 212Meta-analysis and systematic reviewsAdvanced Causal Inference TechniquesStatistical Methods in Epidemiology

The Evidence Project risk of bias tool: assessing study rigor for both randomized and non-randomized intervention studies

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Kennedy, Caitlin E., Fonner, Virginia A., Armstrong, Kevin A., Denison, Julie A., Yeh, Ping Teresa, O’Reilly, Kevin R., Sweat, Michael D.·2019·Systematic Reviews

Abstract

Different tools exist for assessing risk of bias of intervention studies for systematic reviews. We present a tool for assessing risk of bias across both randomized and non-randomized study designs. The tool was developed by the Evidence Project, which conducts systematic reviews and meta-analyses of behavioral interventions for HIV in low- and middle-income countries. We present the eight items of the tool and describe considerations for each and for the tool as a whole. We then evaluate reliability of the tool by presenting inter-rater reliability for 125 selected studies from seven published reviews, calculating a kappa for each individual item and a weighted kappa for the total count of items. The tool includes eight items, each of which is rated as being present (yes) or not present (no) and, for some items, not applicable or not reported. The items include (1) cohort, (2) control or comparison group, (3) pre-post intervention data, (4) random assignment of participants to the intervention, (5) random selection of participants for assessment, (6) follow-up rate of 80% or more, (7) comparison groups equivalent on sociodemographics, and (8) comparison groups equivalent at baseline on outcome measures. Together, items (1)–(3) summarize the study design, while the remaining items consider other common elements of study rigor. Inter-rater reliability was moderate to substantial for all items, ranging from 0.41 to 0.80 (median κ = 0.66). Agreement between raters on the total count of items endorsed was also substantial ( κ w = 0.66). Strengths of the tool include its applicability to a range of study designs, from randomized trials to various types of observational and quasi-experimental studies. It is relatively easy to use and interpret and can be applied to a range of review topics without adaptation, facilitating comparability across reviews. Limitations include the lack of potentially relevant items measured in other tools and potential threats to validity of some items. To date, the tool has been applied in over 30 reviews. We believe it is a practical option for assessing risk of bias in systematic reviews of interventions that include a range of study designs.

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  • A coding matrix was modified from the Evidence Project risk of bias tool and the Critical Appraisal Skills Program checklist for qualitative studies to facilitate data extraction related to quality assessment.

    “A coding matrix was modified from the Evidence Project risk of bias tool23 and the Critical Appraisal Skills Program checklist for qualitative studies to facilitate data extraction related to quality assessment.”

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Cited by

Sorted by citations

Authors
Kennedy, C. E., Fonner, V. A., Armstrong, K. A., Denison, J. A., Yeh, P. T., O’Reilly, K. R., & Sweat, M. D.
Affiliations
  • Johns Hopkins University (US)
  • Medical University of South Carolina (US)
Corresponding author
Kennedy, Caitlin E.
Venue
Systematic Reviews
Published
2019-01-03
Volume
8
Issue
1
Pages
3-3
ISSN
2046-4053 (ISSN-L)
OpenAlex
W2939489030
Cited by
212
References
7
Citations by year
2026: 19 · 2025: 26 · 2024: 39 · 2023: 30 · 2022: 37 · 2021: 35 · 2020: 15 · 2019: 11
FWCI
16.39
Type
journal article
Language
en
Open access
Locations
  • Systematic Reviews (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • National Institute of Mental Health (R01MH071204, R01MH090173)
  • United States Agency for International Development (HRN-A-00-97-00012-00)
Topics
  • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
  • Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
Keywords
risk of bias assessment, quasi-experimental design, observational studies, inter-rater reliability, low- and middle-income countries, systematic review methodology
MeSH terms
Systematic Reviews as Topic, Humans, Reproducibility of Results, Observer Variation, Bias, Randomized Controlled Trials as Topic, Risk Assessment, Observational Studies as Topic, Non-Randomized Controlled Trials as Topic

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