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Cited by 122Patient-Provider Communication in HealthcareDecision-Making and Behavioral EconomicsRisk Perception and Management

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Doctors and Patients’ Susceptibility to Framing Bias: A Randomized Trial

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Perneger, Thomas V., Agoritsas, Thomas·2011·Journal of General Internal Medicine
DOI 10.1007/s11606-011-1810-xPMC PMC3235613
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Abstract

Background Framing of risk influences the perceptions of treatment benefit. Objective To determine which risk framing format corresponds best to comprehensive multi-faceted information, and to compare framing bias in doctors and in patients. Design Randomized mail surveys. Participants One thousand four hundred and thirty-one doctors (56% response rate) and 1121 recently hospitalized patients (65% response rate). Intervention Respondents were asked to interpret the results of a hypothetical clinical trial comparing an old and a new drug. They were randomly assigned to the following framing formats: absolute survival (new drug: 96% versus old drug: 94%), absolute mortality (4% versus 6%), relative mortality reduction (reduction by a third) or all three (fully informed condition). The new drug was reported to cause more side-effects. Main measure Rating of the new drug as more effective than the old drug. Results The proportions of doctors who rated the new drug as more effective varied by risk presentation format (abolute survival 51.8%, absolute mortality 68.3%, relative mortality reduction 93.8%, and fully informed condition 69.8%, p < 0.001). In patients these proportions were similar (abolute survival 51.7%, absolute mortality 66.8%, relative mortality reduction 89.3%, and fully informed condition 71.2%, p < 0.001). In both doctors (p = 0.72) and patients (p = 0.23) the fully informed condition was similar to the absolute risk format, but it differed significantly from the other conditions (all p < 0.01). None of the differences between doctors and patients were significant (all p > 0.1). In comparison to the fully informed condition, the odds ratio of greater perceived effectiveness was 0.45 for absolute survival (p < 0.001), 0.89 for absolute mortality (p = 0.29), and 4.40 for relative mortality reduction (p < 0.001). Conclusions Framing bias affects doctors and patients similarly. Describing clinical trial results as absolute risks is the least biased format, for both doctors and patients. Presenting several risk formats (on both absolute and relative scales) should be encouraged.

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Crossref · 10.1007/s11606-011-1810-x

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Citations

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Research works printed but not linked: 26

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Metadata

Authors
Perneger, T. V., & Agoritsas, T.
Affiliations
University of Geneva (CH)
Corresponding author
Perneger, Thomas V.
ORCID
Venue
Journal of General Internal Medicine
Publisher
Springer Science and Business Media LLC
Published
2011-07-27
Volume
26
Issue
12
Pages
1411-1417
ISSN
  • 0884-8734 (ISSN-L)
  • 1525-1497
DOI
10.1007/s11606-011-1810-x
PMC
PMC3235613
OpenAlex
W2039726724
Cited by
122
References
1
Citations by year
2026: 9 · 2025: 6 · 2024: 6 · 2023: 8 · 2022: 26 · 2021: 7 · 2020: 13 · 2019: 13 · 2018: 7 · 2017: 7 · 2016: 5 · 2015: 4 · 2014: 7 · 2013: 2 · 2012: 1
FWCI
6.54
Type
journal article
Language
en
Open access
Licence
www.springer.com/tdm (tdm)
Locations
  • Journal of General Internal Medicine (publishedVersion)
  • Europe PMC (PubMed Central) (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • Archive ouverte UNIGE (University of Geneva) (publishedVersion, other-oa)
  • reroDoc Digital Library (submittedVersion)
  • Archive ouverte UNIGE (University of Geneva) (submittedVersion, cc-by)
Topics
  • Health Sciences › Health Professions › General Health Professions › Patient-Provider Communication in Healthcare
  • Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
  • Social Sciences › Sociology and Political Science › Risk Perception and Management
Keywords
framing bias, risk communication, absolute risk, relative risk reduction, perceived treatment effectiveness, clinical trial results
MeSH terms
Adult, Data Collection, Female, Humans, Male, Middle Aged, Patient Participation, Perception, Physician's Role, Bias, Treatment Outcome, Patient Preference

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