Current Best Practice for Presenting Probabilities in Patient Decision Aids: Fundamental Principles

Author:

Bonner Carissa12ORCID,Trevena Lyndal J.12ORCID,Gaissmaier Wolfgang3ORCID,Han Paul K. J.45ORCID,Okan Yasmina6ORCID,Ozanne Elissa7ORCID,Peters Ellen8,Timmermans Daniëlle9ORCID,Zikmund-Fisher Brian J.10ORCID

Affiliation:

1. Faculty of Medicine and Health, School of Public Health, The University of Sydney, Sydney, NSW, Australia

2. ASK-GP NHMRC Centre of Research Excellence, The University of Sydney, Australia

3. University of Konstanz, Konstanz, Baden-Wurttemberg, Germany

4. Center for Outcomes Research and Evaluation, Maine Medical Center Research Institute, Portland, ME, USA

5. School of Medicine, Tufts University, USA

6. Centre for Decision Research, University of Leeds, Leeds, UK

7. University of Utah, Salt Lake City, UT, USA

8. Center for Science Communication Research, University of Oregon, Eugene, OR, USA

9. Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, North Holland, The Netherlands

10. University of Michigan, Ann Arbor, MI, USA

Abstract

Background Shared decision making requires evidence to be conveyed to the patient in a way they can easily understand and compare. Patient decision aids facilitate this process. This article reviews the current evidence for how to present numerical probabilities within patient decision aids. Methods Following the 2013 review method, we assembled a group of 9 international experts on risk communication across Australia, Germany, the Netherlands, the United Kingdom, and the United States. We expanded the topics covered in the first review to reflect emerging areas of research. Groups of 2 to 3 authors reviewed the relevant literature based on their expertise and wrote each section before review by the full authorship team. Results Of 10 topics identified, we present 5 fundamental issues in this article. Although some topics resulted in clear guidance (presenting the chance an event will occur, addressing numerical skills), other topics (context/evaluative labels, conveying uncertainty, risk over time) continue to have evolving knowledge bases. We recommend presenting numbers over a set time period with a clear denominator, using consistent formats between outcomes and interventions to enable unbiased comparisons, and interpreting the numbers for the reader to meet the needs of varying numeracy. Discussion Understanding how different numerical formats can bias risk perception will help decision aid developers communicate risks in a balanced, comprehensible manner and avoid accidental “nudging” toward a particular option. Decisions between probability formats need to consider the available evidence and user skills. The review may be useful for other areas of science communication in which unbiased presentation of probabilities is important.

Publisher

SAGE Publications

Subject

Health Policy

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