We began this article with a description of the dilemma of low health numeracy. Despite the abundance of health information from commercial and noncommercial sources, including information about major new research discoveries that can be used to prevent and treat disease, most people cannot take advantage of this abundance. Few problems can be said to affect up to 93 million people, based on reliable assessments of nationally representative samples. Low numeracy is such a problem. The ideal of informed patient choice, in which patients share decision making with health care providers, is an elusive goal without the ability to understand numerical information about survival rates, risks of treatments, and conditional probabilities that govern such domains as genetic risk (e.g., the probability of disease given a genetic mutation). Those who are disadvantaged by poverty, lack of education, or linguistic barriers are also unlikely to have numerical skills that would empower them to access health care and to make informed decisions.
Definitions of health numeracy—encompassing computational, analytical, and statistical skills, among other abilities—are impressively broad, and yet, on assessments of all varieties, people cannot accomplish much less ambitious tasks, such as judging whether a .001 risk of death is bigger or smaller than 1 in 100. Moreover, scores on numeracy assessments have been linked to key cognitions that predict morbidity and mortality, to health behaviors, and, in a few cases, to medical outcomes, the latter sometimes only indirectly through measures of literacy that include, and are correlated with, numeracy. Evidence of effects of numeracy exists along a causal chain from initial perceptions of risks and benefits to health-related judgments and decisions, which have been found to be biased and inaccurate for people with low numeracy. Low numeracy has been shown to impair understanding of risks and benefits of cancer screening, to reduce medication compliance in anticoagulation therapy, to limit access to preventive treatments for asthma, and to affect known predictors of death and disability, such as patients’ self-rated functional status.
However, there are many gaps and shortcomings in current research on health numeracy. The health domains that have been studied (e.g., breast cancer risk perception and screening) have been limited. For example, despite its importance, we could find no research on the effects of numeracy in mental health (e.g., on medication compliance in treatment for depression). Research has documented strong effects of numeracy on perceptions of risks and benefits, on elicitation of values or utilities, and on formatting effects such as framing and frequency effects, but only a handful of studies connect such perceptions, values, and effects to health behaviors or outcomes. Finally, and most important, much of the work is merely descriptive, rather than explanatory or, as scientific theory ought to be, predictive based on knowledge of causal mechanisms.
Although evocative and practical, none of the definitions of numeracy is based on empirically informed, theoretically sound conceptions of numeracy. Assessments are similarly pragmatic rather than explanatory, despite evidence of their “validity” and reliability. On the basis of studies that have controlled for education, intelligence, literacy, and other factors, we can be reasonably sure that numeracy is a separate faculty. What that faculty consists of is the province of theory. Several theorists have characterized it as the ability to draw meaning from numbers, although they disagree about whether that meaning is affective, frequentistic, precisely quantitative, or fuzzy gist. The idea that people vary in the quality of the meaning that they extract from numbers is central to characterizing them as low or high in numeracy. Clearly, more sophisticated and coherent conceptual definitions and measures of numeracy are needed to account for the diverse, sometimes inconsistent ways in which numeracy has been found to relate to decision making and other outcomes.
The pervasive theme that those low in numeracy score lower on just about every other dimension studied makes sense, and it is consistent with dual-process theories that contrast intuitive and analytical reasoning and attribute biases and fallacies mainly to the former. However, these theories do not explain surprising and robust exceptions to this rule, including nonnumerical framing effects, inconsistent relations between intuitive versus analytical thinking and biases, and greater preference for numerically inferior options (e.g., saving fewer rather than more lives or a loss bet over a no-loss bet) among those higher in numeracy. Furthermore, standard dual-process theories emphasize affect, which fails to account for some effects, such as frequency, but is implicated in others, such as mood. The surprising findings generated by dual-process theories are informative precisely because they challenge conventional assumptions about numeracy, precision, and accurate reasoning. These anomalies should be a focus of future research in order to better understand the mechanisms of numerical processing.
Each of the theories we reviewed has been applied to pitfalls in numerical processing or to heuristics and biases. Psychophysical approaches fall short in this respect. They explain the ratio dependence of number perception, which can influence decision making involving numbers, but they do not explain ratio bias. This is a serious shortcoming because ratio concepts—fractions, decimals, percentages, and probabilities—are especially difficult to process, as observed in national and international surveys, as well as in many kinds of numeracy assessments. This difficulty is expected, according to fuzzy trace theory, because class-inclusion judgments of all kinds (e.g., in logical reasoning and in judgments of nested probabilities, such as 5-year vs. lifetime risks of cancer) are subject to denominator neglect, explaining ratio bias, frequency effects, and confusion of conditional probabilities, among other findings. The theory also identifies specific interventions to reduce denominator neglect, which have been evaluated with populations ranging from children to physicians and been found effective. Contemporary theory seems to be coalescing around the conclusion that computational simplicity—that is, clarifying relations among classes—is important for understanding. However, little work on individual differences in numeracy has been done from a computational perspective.
Although many of the most important questions for future research on numeracy have implications for theory, some questions do not hinge on any particular theoretical perspective, such as how to better distinguish numeracy from automatic computation or general reasoning ability. However, the most informative research would test specific hypotheses about how people who are low versus high in numeracy process information differently. Are specific results produced by affect or gist, by frequencies or denominator neglect, and what kinds of meaning do highly numerate people extract from important health information? Most imperative, how can such meaning be communicated more broadly to those who need it to make life-and-death decisions?
Without a deeper theoretical understanding of numeracy, especially of deficiencies in numeracy, it is difficult to know which policy recommendations to make. However, one important question raised by the association between numeracy and outcomes is whether clinical screening for low numeracy should be implemented in health care settings. The data that we have reviewed suggest the potential utility of numeracy screening as a means of helping clinicians to identify low-numerate patients at risk for poor understanding of health information and to avert more distal adverse health outcomes through interventions targeted to these patients.
For a number of reasons, however, the prospect of clinical screening for low numeracy is not straightforward. As we have noted, the evidence linking low numeracy and poor health outcomes is newly emerging and much less developed than the evidence on health literacy. There is currently no evidence that either numeracy screening or targeted interventions to improve numeracy or otherwise assist low-numerate patients will improve health outcomes. Although it stands to reason that this should be the case, one can argue that more evidence is needed before such a practice is implemented, particularly given the substantial resources that numeracy screening would likely entail in the clinical setting. Some researchers have advanced the same argument regarding clinical health literacy screening, which also lacks direct empirical support in spite of the larger evidence base linking health literacy and outcomes (Paasche-Orlow & Wolf, 2008
Other important considerations in assessing the prospect of clinical screening for low numeracy include the performance characteristics of the screening tests, and the potential harms of numeracy screening. Currently, there are several tools that could be used to screen for low health numeracy, although none has been widely accepted or validated for clinical purposes. Screening for low numeracy also has unknown acceptability and psychological effects on patients’ experiences with health care, and these factors require further exploration before screening programs are implemented. Although similar concerns have been expressed about health literacy screening, limited evidence suggests that patients have favorable attitudes toward screening (Ryan et al., 2007
); more work needs to be done to determine whether these findings generalize to health numeracy.
A larger question relates to the optimal approach of the health care system to the problem of low numeracy. Clinical screening for low health numeracy represents an individual-based approach, aimed at detecting the risk factor of low numeracy and, in theory, targeting interventions toward high-risk individuals. An alternative population-based approach, however, would be to design communication and care interventions that would benefit all patients, regardless of their individual numeracy levels. For example, clinical interventions to improve the understandability of numerical information and to evaluate and ensure comprehension of this information might benefit all patients, even those with high numeracy. Supporting this possibility, research on health literacy suggests that educational interventions designed to target low-literacy individuals also benefit those with high literacy (DeWalt et al., 2006
). If this is also true for numeracy, then one can ask whether the more worthwhile strategy would be to implement more broadly applicable interventions to improve numerical understanding. These approaches, however, are not mutually exclusive, and the optimal strategy is an empirical question. Once sufficient evidence is gathered, it may be feasible to add effectiveness in overcoming innumeracy as a quality indicator in the evaluation of procedures used in hospitals (e.g., for surgical consent) and in clinical practice.