Low numeracy was common among this epilepsy patient population, with epilepsy patients obtaining a mean of 57% correct on numeracy testing compared with 65% in a representative national sample of over a thousand people in the U.S (p=0.02) (13
) and was not due to lower education level among epilepsy patients. In fact, epilepsy patients in this study were significantly more likely to have college or higher education compared with a representative national sample, suggesting that epilepsy patients’ relative difficulty with numeracy was not compensated by their self-reported attained education level.
Low numeracy in patients has important implications. Sir William Osler once said “Medicine is a science of uncertainty and an art of probability.” For epilepsy patients to make an informed choice, they should have knowledge about the options, the outcomes, and their likelihood, and then integrate their preferences or values for those outcomes. Often medical choices require weighing trade-offs between desirable and adverse outcomes, thus, comprehension of quantitative numerical or at least qualitative estimates becomes essential for optimal patient-centered care. For example, epilepsy patients often make complex decisions such as whether to undergo resective brain surgery, to have an implantable device, or to enroll in an experimental protocol of a new treatment with unknown benefits or risks. Our findings suggest that many epilepsy patients may not understand risk information as typically presented by physicians. For example, 23% of patients in this study did not know which of the following fractions represents the greatest risk (1 in 100, 1 in 1000, and 1 in 10), and 33% could not convert a 10% risk of disease to the number of people that would be affected out of 100 ().
Our findings confirm that education level correlates with numeracy skill but also suggest that a high education level is not sufficient to obtain a high level of numeracy. Studies have shown that even highly educated individuals such as physicians and medical students sometimes have difficulty understanding numerical risk estimates and are susceptible to misinterpreting numerical risk estimates (24
In addition to numeracy, we also examined the relation between patients’ level of numeracy and their susceptibility to framing bias. It is well documented that different presentations of identical risk information can affect patient risk perception and decisions (5
). However, a limited number of studies have examined the role of numeracy in framing bias and only among healthy controls. In one such study, primarily college students were presented with exam scores as either the percent correct or incorrect and then asked to rate the quality of hypothetical students. The study found that although both low- and high-numerate college students were susceptible to framing bias, the less numerate students were more susceptible to framing bias (31
). Our results confirmed this same directionality among our epilepsy patient group and highlight the importance of presenting numerical information to patients in ways that should minimize framing bias.
Physicians should also be cognizant of other factors that can influence patient decisions. For example, describing anecdotal information about treatments as resulting in clearly positive or negative outcomes (as opposed to ambiguous outcomes), was weighted more heavily than statistical information by normal controls (32
Little is known about the neuropsychological basis of framing bias. Two recent studies have reported that prefrontal cortex activity as assessed on functional MRI predicted a reduced susceptibility to the framing bias (6
). We therefore explored whether performance on measures known to assess frontal lobe functioning would correlate with susceptibility to framing bias. We indeed found significant correlations between the degree of framing bias and WCST performance measures, but not with other measures of frontal lobe functioning such as Trails B or Stroop. These findings support divergent validity. WCST assesses problem solving and abstract thinking ability, similar to the task involved in determining whether two numbers framed differently are indeed equal. On the other hand, Trails B measures rapid set switching and Stroop measures response inhibition. Similarly, we found no significant relation between the degree of framing bias and measure of memory performance (i.e., CVLT), which, taken together, suggests that susceptibility to framing bias does not simply reflect general ability level across cognitive domains.
With respect to limitations, our clinical sample included only patients with epilepsy referred to a tertiary care subspecialty practice, limiting the generalizability of our data to other patient populations. Second, only a subgroup of our patient population had a clinical neuropsychological testing, which in turn, might have limited the power to detect small to moderate associations between framing bias and other cognitive variables. Third, although the level of education was higher in our epilepsy population than that of normal controls, the academic quality of education attained in either group is unknown. It is possible that academic quality in the epilepsy patients in this study was poorer than that of the controls, which might have contributed to lower numeracy in epilepsy patients. Lastly, we did not examine other cognitive biases that might impact decisions. Biases such as anchoring bias (tendency to rely too heavily on one piece of information) (33
) and familiarity bias (judging events as more important because they are more familiar in memory) (34
) can be explored in future studies.
In conclusion, our findings suggest that poor numeracy and framing bias are common among epilepsy patients. Facilitating epilepsy patients’ understanding of medical information should be individualized to the numeracy level of the patient. In general, using visual displays during verbal explanation of treatment risks and benefits has been shown to augment patient understanding (35
). To minimize framing bias, presentation of risk information should include both positive (gain) and negative (loss) frames, with clear examples that demonstrate equivalence between identical risks presented in both gain and loss frames. Nonetheless, although these methods have been found to be helpful in other populations (36
), they remain untested in epilepsy patients. Systems-minded, evidence-based, patient-centered care [as recommended by the Institute of Medicine’s Crossing the Quality Chasm (37
)] remains a goal for epilepsy patients.