Universität zu Köln

Weibel, Stephanie, Popp, Maria, Reis, Stefanie, Skoetz, Nicole, Garner, Paul and Sydenham, Emma . Identifying and managing problematic trials: A research integrity assessment tool for randomized controlled trials in evidence synthesis. Res. Synth. Methods. HOBOKEN: WILEY. ISSN 1759-2887

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Abstract

Evidence synthesis findings depend on the assumption that the included studies follow good clinical practice and results are not fabricated or false. Studies which are problematic due to scientific misconduct, poor research practice, or honest error may distort evidence synthesis findings. Authors of evidence synthesis need transparent mechanisms to identify and manage problematic studies to avoid misleading findings. As evidence synthesis authors of the Cochrane COVID-19 review on ivermectin, we identified many problematic studies in terms of research integrity and regulatory compliance. Through iterative discussion, we developed a research integrity assessment (RIA) tool for randomized controlled trials for the update of this Cochrane review. In this paper, we explain the rationale and application of the RIA tool in this case study. RIA assesses six study criteria: study retraction, prospective trial registration, adequate ethics approval, author group, plausibility of methods (e.g., randomization), and plausibility of study results. RIA was used in the Cochrane review as part of the eligibility check during screening of potentially eligible studies. Problematic studies were excluded and studies with open questions were held in awaiting classification until clarified. RIA decisions were made independently by two authors and reported transparently. Using the RIA tool resulted in the exclusion of >40% of studies in the first update of the review. RIA is a complementary tool prior to assessing Risk of Bias aiming to establish the integrity and authenticity of studies. RIA provides a platform for urgent development of a standard approach to identifying and managing problematic studies.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Weibel, Stephanie UNSPECIFIED UNSPECIFIED UNSPECIFIED Popp, Maria UNSPECIFIED UNSPECIFIED UNSPECIFIED Reis, Stefanie UNSPECIFIED UNSPECIFIED UNSPECIFIED Skoetz, Nicole UNSPECIFIED UNSPECIFIED UNSPECIFIED Garner, Paul UNSPECIFIED UNSPECIFIED UNSPECIFIED Sydenham, Emma UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-680147
DOI:	10.1002/jrsm.1599
Journal or Publication Title:	Res. Synth. Methods
Publisher:	WILEY
Place of Publication:	HOBOKEN
ISSN:	1759-2887
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language SEQUENTIAL-ANALYSIS; COVID-19 INFECTION; IVERMECTIN; METAANALYSIS; PREVENTION Multiple languages Mathematical & Computational Biology; Multidisciplinary Sciences Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/68014