Literature DB >> 24560088

Blinded interpretation of study results can feasibly and effectively diminish interpretation bias.

Teppo L N Järvinen1, Raine Sihvonen2, Mohit Bhandari3, Sheila Sprague3, Antti Malmivaara4, Mika Paavola5, Holger J Schünemann6, Gordon H Guyatt7.   

Abstract

OBJECTIVE: Controversial and misleading interpretation of data from randomized trials is common. How to avoid misleading interpretation has received little attention. Herein, we describe two applications of an approach that involves blinded interpretation of the results by study investigators. STUDY DESIGN AND SETTINGS: The approach involves developing two interpretations of the results on the basis of a blinded review of the primary outcome data (experimental treatment A compared with control treatment B). One interpretation assumes that A is the experimental intervention and another assumes that A is the control. After agreeing that there will be no further changes, the investigators record their decisions and sign the resulting document. The randomization code is then broken, the correct interpretation chosen, and the manuscript finalized. Review of the document by an external authority before finalization can provide another safeguard against interpretation bias.
RESULTS: We found the blinded preparation of a summary of data interpretation described in this article practical, efficient, and useful.
CONCLUSIONS: Blinded data interpretation may decrease the frequency of misleading data interpretation. Widespread adoption of blinded data interpretation would be greatly facilitated were it added to the minimum set of recommendations outlining proper conduct of randomized controlled trials (eg, the Consolidated Standards of Reporting Trials statement).
Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Keywords:  Bias; Data interpretations; Double-blind method; Drug evaluation/methods; Randomized controlled trials as topic/methods; Research design

Mesh:

Year:  2014        PMID: 24560088     DOI: 10.1016/j.jclinepi.2013.11.011

Source DB:  PubMed          Journal:  J Clin Epidemiol        ISSN: 0895-4356            Impact factor:   6.437


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