Related Experiment Video
Updated: Jul 6, 2026

Errors as a Means of Reducing Impulsive Food Choice
Published on: June 5, 2016
Do decision biases predict bad decisions? Omission bias, naturalness bias, and influenza vaccination
Marco daCosta Dibonaventura1, Gretchen B Chapman
1Memorial Sloan-Kettering Cancer Center, New York, NY 10022, USA. dibonavm@mskcc.org
Purpose:
Numerous studies using hypothetical vignettes have demonstrated decision biases or deviations from utility theory. Do people who commit biases in questionnaire studies make worse real-world decisions than do less biased people?
Methods:
Two hundred seventy university faculty and staff participated in a questionnaire study in which they reported whether they accepted a free influenza vaccine offered at their work place. Influenza vaccine acceptance was the measure of real-world decision making. Participants responded to 3 hypothetical scenarios. Two scenarios measured the omission bias and described a vaccine (scenario 1) and a medication (scenario 2) that prevented a negative health outcome but that itself could cause the negative health outcome. The omission bias is a preference for not vaccinating or medicating even when the vaccine/medication lowers the total risk of the negative outcome. A 3rd scenario measured the naturalness bias by presenting a choice between 2 chemically identical medications, one extracted from a natural herb and the other synthesized in a laboratory. Preference for the natural medication indicated the naturalness bias.
Results:
The results indicated that a substantial proportion of participants exhibited these biases and that participants who exhibited these biases were less likely to accept the flu vaccine.
Conclusions:
To the extent that declining a free flu vaccine is a worse real-world decision, people who demonstrate the naturalness and omission biases in hypothetical scenarios make worse real-world decisions.
Related Concept Videos
Bias in Epidemiological Studies
The Availability Heuristic
Bias
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
Hindsight Biases
Confirmation Biases
Motivational Bias

