Abstract
People frequently encounter numeric information in medical and health contexts. In this paper, we investigated the math factors that are associated with decision-making accuracy in health and non-health contexts. This is an important endeavor given that there is relatively little cross-talk between math cognition researchers and those studying health decision making. Ninety adults (M = 37 years; 86% White; 51% male) answered hypothetical health decision-making problems, and 93 adults (M = 36 years; 75% White; 42% males) answered a non-health decision-making problem. All participants were recruited from an online panel. Each participant completed a battery of tasks involving objective math skills (e.g., whole number and fraction estimation, comparison, arithmetic fluency, objective numeracy, etc.) and subjective ratings of their math attitudes, anxiety, and subjective numeracy. In separate regression models, we identified which objective and subjective math measures were associated with health and non-health decision-making accuracy. Magnitude comparison accuracy, multi-step arithmetic accuracy, and math anxiety accounted for significant variance in health decision-making accuracy, whereas attention to math, as illustrated in open-ended strategy reports, was the only significant predictor of non-health decision-making accuracy. Importantly, reliable and valid measures from the math cognition literature were more strongly related to health decision-making accuracy than were commonly used subjective and objective measures of numeracy. These results have a practical implication: Understanding the math factors that are associated with health decision-making performance could inform future interventions to enhance comprehension of numeric health information.
Document Type
Article
Publication Date
7-23-2021
Digital Object Identifier (DOI)
https://doi.org/10.5964/jnc.6545
Funding Information
The writing of this report was supported in part by U.S. Department of Education, Institute of Education Sciences Grant # R305A160295 and R305U200004.
Related Content
The R code, data file, and supplemental analyses that support the findings of this study are available on OSF: https://osf.io/tvc9f/
The above materials are also available for download as the additional file listed at the end of this record.
Repository Citation
Thompson, Clarissa A.; Taber, Jennifer M.; Fitzsimmons, Charles J.; and Sidney, Pooja G., "Math Predictors of Numeric Health and Non-Health Decision-Making Problems" (2021). Psychology Faculty Publications. 208.
https://uknowledge.uky.edu/psychology_facpub/208
Supplementary file
Notes/Citation Information
Published in Journal of Numerical Cognition, v. 7, issue 2.
This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License, CC BY 4.0, which permits unrestricted use, distribution, and reproduction, provided the original work is properly cited.