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. Keywords risk perception; risk communication; mathematical cognition; intuition; dual processesIn a series of television and print advertisements, Robert Jarvik, inventor of the artificial heart, described the benefits of Lipitor for cardiovascular health. In one 2007 advertisement, Jarvik stands in front of an image of a heart. Next to him, in large print, the copy reads: "In patients with multiple risk factors for heart disease, Lipitor reduces risk of heart attack by 36%.*" If you failed to pay attention to the asterisk, you would have missed the following explanation for the impressive 36%: "*That means in a Correspondence concerning this article should be addressed to Valerie F. Reyna, Department of Human Development, Cornell University, B44 Martha Van Rensselaer Hall, Ithaca, NY 14853. vr53@cornell.edu. NIH Public Access Author ManuscriptPsychol Bull. Author manuscript; available in PMC 2010 November 1. Published in final edited form as:Psychol Bull. 2009 November ; 135(6): 943-973. doi:10.1037/a0017327. NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author Manuscript large clinical study, 3% of patients taking a sugar pill or placebo had a heart attack compared to 2% of patients taking Lipitor."People have unprecedented access to information-available online, in print, and through other media-that they can use to improve their mental and physical health. Much of that information is expressed numerically. For exa...

Uncertainty is a pervasive and important problem that has attracted increasing attention in health care, given the growing emphasis on evidence-based medicine, shared decision making, and patient-centered care. However, our understanding of this problem is limited, due in part to the absence of a unified, coherent concept of uncertainty. There are multiple meanings and varieties of uncertainty in health care, which are not often distinguished or acknowledged although each may have unique effects or warrant different courses of action. The literature on uncertainty in health care is thus fragmented, and existing insights have been incompletely translated to clinical practice. In this paper we attempt to address this problem by synthesizing diverse theoretical and empirical literature from the fields of communication, decision science, engineering, health services research, and psychology, and developing a new integrative conceptual taxonomy of uncertainty. We propose a three-dimensional taxonomy that characterizes uncertainty in health care according to its fundamental sources, issues, and locus. We show how this new taxonomy facilitates an organized approach to the problem of uncertainty in health care by clarifying its nature and prognosis, and suggesting appropriate strategies for its analysis and management.

Objectives To revise an existing three-talk model for learning how to achieve shared decision making, and to consult with relevant stakeholders to update and obtain wider engagement. Design Multistage consultation process. Setting Key informant group, communities of interest, and survey of clinical specialties. Participants 19 key informants, 153 member responses from multiple communities of interest, and 316 responses to an online survey from medically qualified clinicians from six specialties. Results After extended consultation over three iterations, we revised the three-talk model by making changes to one talk category, adding the need to elicit patient goals, providing a clear set of tasks for each talk category, and adding suggested scripts to illustrate each step. A new three-talk model of shared decision making is proposed, based on “team talk,” “option talk,” and “decision talk,” to depict a process of collaboration and deliberation. Team talk places emphasis on the need to provide support to patients when they are made aware of choices, and to elicit their goals as a means of guiding decision making processes. Option talk refers to the task of comparing alternatives, using risk communication principles. Decision talk refers to the task of arriving at decisions that reflect the informed preferences of patients, guided by the experience and expertise of health professionals. Conclusions The revised three-talk model of shared decision making depicts conversational steps, initiated by providing support when introducing options, followed by strategies to compare and discuss trade-offs, before deliberation based on informed preferences.

BackgroundMaking evidence-based decisions often requires comparison of two or more options. Research-based evidence may exist which quantifies how likely the outcomes are for each option. Understanding these numeric estimates improves patients’ risk perception and leads to better informed decision making. This paper summarises current “best practices” in communication of evidence-based numeric outcomes for developers of patient decision aids (PtDAs) and other health communication tools.MethodAn expert consensus group of fourteen researchers from North America, Europe, and Australasia identified eleven main issues in risk communication. Two experts for each issue wrote a “state of the art” summary of best evidence, drawing on the PtDA, health, psychological, and broader scientific literature. In addition, commonly used terms were defined and a set of guiding principles and key messages derived from the results.ResultsThe eleven key components of risk communication were: 1) Presenting the chance an event will occur; 2) Presenting changes in numeric outcomes; 3) Outcome estimates for test and screening decisions; 4) Numeric estimates in context and with evaluative labels; 5) Conveying uncertainty; 6) Visual formats; 7) Tailoring estimates; 8) Formats for understanding outcomes over time; 9) Narrative methods for conveying the chance of an event; 10) Important skills for understanding numerical estimates; and 11) Interactive web-based formats. Guiding principles from the evidence summaries advise that risk communication formats should reflect the task required of the user, should always define a relevant reference class (i.e., denominator) over time, should aim to use a consistent format throughout documents, should avoid “1 in x” formats and variable denominators, consider the magnitude of numbers used and the possibility of format bias, and should take into account the numeracy and graph literacy of the audience.ConclusionA substantial and rapidly expanding evidence base exists for risk communication. Developers of tools to facilitate evidence-based decision making should apply these principles to improve the quality of risk communication in practice.

Uncertainty tolerance is an important and complex phenomenon requiring more precise and consistent definition. An integrative definition and conceptual model, intended as a tentative and flexible point of departure for future research, adds needed breadth, specificity, and precision to efforts to conceptualize and measure UT.

There are significant differences in PCPs' and oncologists' knowledge, attitudes, and practices with respect to care of cancer survivors. Improving cancer survivors' care may require more effective communication between these two groups to increase PCPs' confidence in their knowledge, and must also address oncologists' attitudes regarding PCPs' ability to care for cancer survivors.

Background. There is growing interest in shared medical decision making among patients, physicians, and policy makers. This requires patients to interpret increasing amounts of medical information, much of which is uncertain. Little is known about the optimal approaches to or outcomes of communicating uncertainty about the risks and benefits of treatments. Methods. The authors reviewed the literature on various issues related to uncertainty in decision making: conceptualizing uncertainty, identifying its potential sources, assessing uncertainty, potential methods of communicating uncertainty, potential outcomes of communicating uncertainty, and current practices and recommendations by expert groups on communicating uncertainty. Results. There are multiple sources of uncertainty in most medical decisions. There are conceptual differences in how researchers define uncertainty and its sources, as well as in its measurement. The few studies that have assessed alternate means of communicating uncertainty dealt mostly with presenting uncertainty about probabilities. Both patients' and physicians' interpretation of and responses to uncertainty may depend on their personal characteristics and values and may be affected by the manner in which uncertainty is communicated. Conclusions. Research has not yet identified best practices for communicating uncertainty to patients about harms and benefits of treatment. More conceptual, qualitative, and quantitative studies are needed to explore fundamental questions about how people process, interpret, and respond to various types of uncertainty inherent in clinical decisions.

Uncertainty is a pervasive and important problem that has attracted increasing attention in health care, given the growing emphasis on evidence-based medicine, shared decision making, and patient-centered care. However, our understanding of this problem is limited, due in part to the absence of a unified, coherent concept of uncertainty. There are multiple meanings and varieties of uncertainty in health care, which are not often distinguished or acknowledged although each may have unique effects or warrant different courses of action. The literature on uncertainty in health care is thus fragmented, and existing insights have been incompletely translated to clinical practice. In this paper we attempt to address this problem by synthesizing diverse theoretical and empirical literature from the fields of communication, decision science, engineering, health services research, and psychology, and developing a new integrative conceptual taxonomy of uncertainty. We propose a three-dimensional taxonomy that characterizes uncertainty in health care according to its fundamental sources, issues, and locus. We show how this new taxonomy facilitates an organized approach to the problem of uncertainty in health care by clarifying its nature and prognosis, and suggesting appropriate strategies for its analysis and management.