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A new classification of spin in systematic reviews and meta-analyses was developed and ranked according to the severity

  • Amélie Yavchitz
  • , Philippe Ravaud
  • , Douglas G Altman
  • , David Moher
  • , Asbjørn Hrobjartsson
  • , Toby Lasserson
  • , Isabelle Boutron
  • Centre de Recherche Épidémiologie et Statistique Sorbonne
  • Hôpital Hôtel-Dieu de Paris
  • Paris Descartes University
  • University of Oxford
  • Columbia University
  • Ottawa Hospital Research Institute
  • University of Ottawa
  • Cochrane Denmark
  • Cochrane Editorial Unit

Research output: Contribution to journal › Journal article › Research › peer-review

Abstract

Objectives We aimed to (1) identify and classify spin (i.e., a description that overstates efficacy and/or understates harm) in systematic reviews and (2) rank spin in abstracts of systematic reviews according to their severity (i.e., the likelihood of distorting readers' interpretation of the results). Study Design First, we used a four-phase consensus process to develop a classification of different types of spin. Second, we ranked the types of spin in abstracts according to their severity using a Q-sort survey with members of the Cochrane Collaboration. Results We identified 39 types of spin, 28 from the main text and 21 from the abstract; 13 were specific to the systematic review design. Spin was classified into three categories: (1) misleading reporting, (2) misleading interpretation, and (3) inappropriate extrapolation. Spin ranked as the most severe by the 122 people who participated in the survey were (1) recommendations for clinical practice not supported by findings in the conclusion, (2) misleading title, and (3) selective reporting. Conclusion This study allowed for identifying spin that is likely to distort interpretation. Our classification could help authors, editors, and reviewers avoid spin in reports of systematic reviews.

Original languageEnglish
JournalJournal of Clinical Epidemiology
Volume75
Pages (from-to)56-65
ISSN0895-4356
DOIs
Publication statusPublished - Jul 2016

Keywords

  • Bias
  • Classification
  • Data interpretation
  • Distortion
  • Spin
  • Systematic reviews
  • Epidemiologic Research Design
  • Meta-Analysis as Topic
  • Review Literature as Topic
  • Humans
  • Research Report/standards
  • Evidence-Based Medicine/methods

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