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Principles and framework for assessing the risk of bias for studies included in comparative quantitative environmental systematic reviews

Affiliation
Southampton Health Technology Assessments Centre (SHTAC), Faculty of Medicine, University of Southampton, Southampton, UK
Frampton, Geoff;
Affiliation
Lancaster Environment Centre, Lancaster University, Lancaster, UK ; Evidence-Based Toxicology Collaboration at Johns Hopkins Bloomberg School of Public Health, Baltimore, USA
Whaley, Paul;
Affiliation
U.S. Environmental Protection Agency, Region 5, Chicago, USA
Bennett, Micah;
Affiliation
School of Environment and Technology, University of Brighton, Brighton, UK
Bilotta, Gary;
Affiliation
Scientific Committee and Emerging Risks Unit, European Food Safety Authority, Parma, Italy
Dorne, Jean-Lou C. M.;
Affiliation
European Centre for Environment and Human Health, College of Medicine and Health, University of Exeter, Truro, UK
Eales, Jacqualyn;
Affiliation
Centre for Evidence Based Agriculture, Harper Adams University, Newport, UK
James, Katy;
GND
1024181847
Affiliation
Julius Kühn-Institute (JKI), Institute for Biosafety in Plant Biotechnology, Germany
Kohl, Christian;
Affiliation
Formas, Stockholm, Sweden
Land, Magnus;
Affiliation
Freelance Consultant, Coopaname, France
Livoreil, Barbara;
Affiliation
UMR518, University Paris-Saclay, INRAE, AgroParistech, France
Makowski, David;
Affiliation
Centre for Anthropological Research, University of Johannesburg, Johannesburg, South Africa
Muchiri, Evans;
Affiliation
Oxford Long‑Term Ecology Lab, Department of Zoology, University of Oxford, Oxford, UK
Petrokofsky, Gillian;
Affiliation
Centre for Evidence‑Based Agriculture, Harper Adams University, Newport, Shropshire, UK
Randall, Nicola;
Affiliation
Office of Research and Development, U.S. Environmental Protection Agency, Washington, USA
Schofield, Kate

The internal validity of conclusions about effectiveness or impact in systematic reviews, and of decisions based on them, depends on risk of bias assessments being conducted appropriately. However, a random sample of 50 recently-published articles claiming to be quantitative environmental systematic reviews found 64% did not include any risk of bias assessment, whilst nearly all that did omitted key sources of bias. Other limitations included lack of transparency, conflation of quality constructs, and incomplete application of risk of bias assessments to the data synthesis. This paper addresses deficiencies in risk of bias assessments by highlighting core principles that are required for risk of bias assessments to be fit-for-purpose, and presenting a framework based on these principles to guide review teams on conducting risk of bias assessments appropriately and consistently. The core principles require that risk of bias assessments be Focused, Extensive, Applied and Transparent (FEAT). These principles support risk of bias assessments, appraisal of risk of bias tools, and the development of new tools. The framework follows a Plan-Conduct-Apply-Report approach covering all stages of risk of bias assessment. The scope of this paper is comparative quantitative environmental systematic reviews which address PICO or PECO-type questions including, but not limited to, topic areas such as environmental management, conservation, ecosystem restoration, and analyses of environmental interventions, exposures, impacts and risks.

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