Which cognitive individual differences predict good Bayesian reasoning? Concurrent comparisons of underlying abilities

Improving patient understanding of prenatal screening tests: Using naturally sampled frequencies, pictures, and accounting for individual differences

Objective

Health professionals must communicate prenatal screening test results effectively to patients, but these tests involve very low prevalence and high false positive risks; a situation known to be difficult for people to understand.

Methods

The present experiments evaluated the effectiveness of presenting prenatal screening test results for Trisomy 21, Trisomy 13, or DiGeorge Syndrome, using either naturally sampled frequencies or standard percentages. Participants were given a task of interpreting the posterior probability of an embryo having the condition.

Results

People were significantly better with naturally sampled frequencies. Numerical literacy and visuospatial ability significantly accounted for individual differences in performance within conditions. Participants nevertheless did not differ in ratings of how useful the different presentation formats were, suggesting a lack of awareness of how format influenced understanding. These results held regardless of whether the respondents were undergraduates (Experiment 1) or members of the general population recruited online (Experiment 2).

Conclusion

Using naturally sampled frequencies improves patient understanding of prenatal screening tests results, with low cost of implementation.

Innovation

Using realistic prenatal screening test results, these results show how to improve patient counseling via the use of naturally sampled frequencies.

Sensitivity to Evidential Dependencies in Judgments Under Uncertainty

According to Bayesian models of judgment, testimony from independent informants has more evidential value than dependent testimony. Three experiments investigated learners' sensitivity to this distinction. Each experiment used a social version of the balls‐and‐urns task, in which participants judged which of two urns was the most likely source of evidence presented by multiple informants. Informants either provided independent testimony based solely on their own observations or dependent‐sequential testimony that considered the testimonies of previous informants. Although participants updated their beliefs with additional evidence, this updating was generally insensitive to evidential dependency (Experiments 1 and 2). A notable exception was when individuals were separated according to their beliefs about the relative value of independent and sequential evidence. Those who viewed independent evidence as having greater value subsequently gave more weight to independent testimony in the balls‐and‐urns task (Experiment 3), in line with the predictions of a Bayesian model. Our findings suggest that only a minority of individuals conform to Bayesian predictions in the relative weighting of independent and dependent evidence in judgments under uncertainty.

What facilitates Bayesian reasoning? A crucial test of ecological rationality versus nested sets hypotheses

Different theoretical views about Bayesian reasoning (ecological rationality and nested sets views) both claim support from results showing that natural sampling, whole numbers, and pictorial representations help with reasoning performance, although they differ in explaining how those results occur. Three studies (total N = 653) use minimally different numerical presentation formats-varying the singular or plural tense of the context story topic-and presence or absence of an additional icon array picture, to better understand the mechanisms driving these reasoning performance results. Plural wording, indicating a conceptual aggregation (i.e., frequencies) rather than just numerical whole numbers, consistently boosted performance. Icon arrays, in contrast, were helpful only when alongside single-tense information. These results fit more consistently with an ecological rationality view which has long argued that the mind is adapted to work best with frequentist information.