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A Meta-analysis of the Effects of Presenting Treatment Benefits in Different Formats

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  • Judith Covey

    (Department of Psychology, Durham University, Stockton, United Kingdom)

Abstract

Purpose. The purpose of this article is to examine the effects of presenting treatment benefits in different formats on the decisions of both patients and health professionals. Three formats were investigated: relative risk reductions, absolute risk reductions, and number needed to treat or screen. Methods. A systematic review of the published literature was conducted. Articles were retrieved by searching a variety of databases and screened for inclusion by 2 reviewers. Data were extracted on characteristics of the subjects and methodologies used. Log-odds ratios were calculated to estimate effect sizes. Results. A total of 24 articles were retrieved that reported on 31 unique experiments. The meta-analysis showed that treatments were evaluated more favorably when the relative risk format was used rather than the absolute risk or number needed to treat format. However, a significant amount of heterogeneity was found between studies, the sources of which were explored using subgroup analyses and metaregression. Although the subgroup analyses revealed smaller effect sizes in the studies conducted on physicians, the metaregression showed that these differences were largely accounted for by other features of the study design. Most notably, variations in effect sizes were explained by the particular wordings that the studies had chosen to use for the relative risk and absolute risk reductions. Conclusions. The published literature has consistently demonstrated that relative risk formats produce more favorable evaluations of treatments than absolute risk or number needed to treat formats. However, the effects are heterogeneous and seem to be moderated by key differences between the methodologies used.

Suggested Citation

  • Judith Covey, 2007. "A Meta-analysis of the Effects of Presenting Treatment Benefits in Different Formats," Medical Decision Making, , vol. 27(5), pages 638-654, September.
  • Handle: RePEc:sae:medema:v:27:y:2007:i:5:p:638-654
    DOI: 10.1177/0272989X07306783
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    References listed on IDEAS

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    1. Heiner Bucher & Alfredo Morabia, 1998. "Teaching physicians about different measures of risk reduction may alter their treatment preference," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 43(2), pages 67-72, March.
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    Cited by:

    1. Luca Iaboli & Luana Caselli & Angelina Filice & Gianpaolo Russi & Eleonora Belletti, 2010. "The Unbearable Lightness of Health Science Reporting: A Week Examining Italian Print Media," PLOS ONE, Public Library of Science, vol. 5(3), pages 1-6, March.
    2. Garcia-Retamero, Rocio & Hoffrage, Ulrich, 2013. "Visual representation of statistical information improves diagnostic inferences in doctors and their patients," Social Science & Medicine, Elsevier, vol. 83(C), pages 27-33.
    3. Lyndal J. Trevena & Carissa Bonner & Yasmina Okan & Ellen Peters & Wolfgang Gaissmaier & Paul K. J. Han & Elissa Ozanne & Danielle Timmermans & Brian J. Zikmund-Fisher, 2021. "Current Challenges When Using Numbers in Patient Decision Aids: Advanced Concepts," Medical Decision Making, , vol. 41(7), pages 834-847, October.
    4. Sandro Zacher & Birte Berger-Höger & Julia Lühnen & Anke Steckelberg, 2022. "Development and Piloting of a Web-Based Tool to Teach Relative and Absolute Risk Reductions," IJERPH, MDPI, vol. 19(23), pages 1-18, December.
    5. Michael Sobel & David Madigan & Wei Wang, 2017. "Causal Inference for Meta-Analysis and Multi-Level Data Structures, with Application to Randomized Studies of Vioxx," Psychometrika, Springer;The Psychometric Society, vol. 82(2), pages 459-474, June.

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