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Eduardo Benigno Arribalzaga 1 Article
Training in statistical analysis reduces the framing effect among medical students and residents in Argentina  
Raúl Alfredo Borracci, Eduardo Benigno Arribalzaga, Jorge Thierer
J Educ Eval Health Prof. 2020;17:25.   Published online September 1, 2020
DOI: https://doi.org/10.3352/jeehp.2020.17.25
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AbstractAbstract PDFSupplementary Material
Purpose
The framing effect refers to a phenomenon wherein, when the same problem is presented using different representations of information, people make significant changes in their decisions. This study aimed to explore whether the framing effect could be reduced in medical students and residents by teaching them the statistical concepts of effect size, probability, and sampling for use in the medical decision-making process.
Methods
Ninety-five second-year medical students and 100 second-year medical residents of Austral University and Buenos Aires University, Argentina were invited to participate in the study between March and June 2017. A questionnaire was developed to assess the different types of framing effects in medical situations. After an initial administration of the survey, students and residents were taught statistical concepts including effect size, probability, and sampling during 2 individual independent official biostatistics courses. After these interventions, the same questionnaire was randomly administered again, and pre- and post-intervention outcomes were compared among students and residents.
Results
Almost every type of framing effect was reproduced either in the students or in the residents. After teaching medical students and residents the analytical process behind statistical concepts, a significant reduction in sample-size, risky-choice, pseudo-certainty, number-size, attribute, goal, and probabilistic formulation framing effects was observed.
Conclusion
The decision-making of medical students and residents in simulated medical situations may be affected by different frame descriptions, and these framing effects can be partially reduced by training individuals in probability analysis and statistical sampling methods.

Citations

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  • Numeracy Education for Health Care Providers: A Scoping Review
    Casey Goldstein, Nicole Woods, Rebecca MacKinnon, Rouhi Fazelzad, Bhajan Gill, Meredith Elana Giuliani, Tina Papadakos, Qinge Wei, Janet Papadakos
    Journal of Continuing Education in the Health Professions.2023;[Epub]     CrossRef

JEEHP : Journal of Educational Evaluation for Health Professions