title: How numeracy influences risk comprehension and medical decision making.
abstract: We review the growing literature on health numeracy, the ability to understand and use numerical information, and its relation to cognition, health behaviors, and medical outcomes. Despite the surfeit of health information from commercial and noncommercial sources, national and international surveys show that many people lack basic numerical skills that are essential to maintain their health and make informed medical decisions. Low numeracy distorts perceptions of risks and benefits of screening, reduces medication compliance, impedes access to treatments, impairs risk communication (limiting prevention efforts among the most vulnerable), and, based on the scant research conducted on outcomes, appears to adversely affect medical outcomes. Low numeracy is also associated with greater susceptibility to extraneous factors (i.e., factors that do not change the objective numerical information). That is, low numeracy increases susceptibility to effects of mood or how information is presented (e.g., as frequencies vs. percentages) and to biases in judgment and decision making (e.g., framing and ratio bias effects). Much of this research is not grounded in empirically supported theories of numeracy or mathematical cognition, which are crucial for designing evidence-based policies and interventions that are effective in reducing risk and improving medical decision making. To address this gap, we outline four theoretical approaches (psychophysical, computational, standard dual-process, and fuzzy trace theory), review their implications for numeracy, and point to avenues for future research.
authors.affiliation: Department of Human Development, Cornell University, B44 Martha Van Rensselaer Hall, Ithaca, NY 14853, USA. vr53@cornell.edu
authors.forename: Valerie F
authors.initials: VF
authors.lastname: Reyna
authors.forename: Wendy L
authors.initials: WL
authors.lastname: Nelson
authors.forename: Paul K
authors.initials: PK
authors.lastname: Han
authors.forename: Nathan F
authors.initials: NF
authors.lastname: Dieckmann
mesh_terms: D032882:Comprehension; D003657:Decision Making; D017143:Fuzzy Logic; D015438:Health Behavior; D006801:Humans; D007206:Individuality; D007600:Judgment; D008962:Models, Theoretical; D011337:Probability Learning; D011340:Problem Solving; D012309:Risk-Taking; D035862:Vulnerable Populations