Contextual preference reversals occur when a preference for one option over another is reversed by the addition of further options. It has been argued that the occurrence of preference reversals in human behavior shows that people violate the axioms of rational choice and that people are not, therefore, expected value maximizers. In contrast, we demonstrate that if a person is only able to make noisy calculations of expected value and noisy observations of the ordinal relations among option features, then the expected value maximizing choice is influenced by the addition of new options and does give rise to apparent preference reversals. We explore the implications of expected value maximizing choice, conditioned on noisy observations, for a range of contextual preference reversal types—including attraction, compromise, similarity, and phantom effects. These preference reversal types have played a key role in the development of models of human choice. We conclude that experiments demonstrating contextual preference reversals are not evidence for irrationality. They are, however, a consequence of expected value maximization given noisy observations.

People with autism spectrum conditions (ASC) show reduced sensitivity to contextual stimuli in many perceptual and cognitive tasks. We investigated whether this also applies to decision making by examining adult participants’ choices between pairs of consumer products that were presented with a third, less desirable “decoy” option. Participants’ preferences between the items in a given pair frequently switched when the third item in the set was changed, but this tendency was reduced among individuals with ASC, which indicated that their choices were more consistent and conventionally rational than those of control participants. A comparison of people who were drawn from the general population and who varied in their levels of autistic traits revealed a weaker version of the same effect. The reduced context sensitivity was not due to differences in noisy responding, and although the ASC group took longer to make their decisions, this did not account for the enhanced consistency of their choices. The results extend the characterization of autistic cognition as relatively context insensitive to a new domain, and have practical implications for socioeconomic behavior.

Patients and non-specialist healthcare professionals are increasingly expected to understand and interpret the results of genetic or genomic testing. These results are currently reported using a variety of templates, containing different amounts, levels, and layouts of information. We set out to establish a set of recommendations for communicating genetic test results to non-expert readers. We employed a qualitative-descriptive study design with user-centred design principles, including a mixture of in-person semi-structured interviews and online questionnaires with patients, healthcare professionals and the general public. The resulting recommendations and example template include providing at-a-glance comprehension of what the test results mean for the patient; suggested next steps; and details of further information and support. Separation and inclusion of technical methodological details enhances non-specialists' understanding, while retaining important information for specialists and the patients' records. The recommendations address the high-level needs of patients and their nonspecialist clinicians when receiving genetic test results. These recommendations provide a solid foundation for the major content and structure of reports, and we recommend further engagement with patients and clinicians to tailor reports to specific types of test and results.

Human randomness perception is commonly described as biased. This is because when generating random sequences humans tend to systematically under- and overrepresent certain subsequences relative to the number expected from an unbiased random process. In a purely theoretical analysis we have previously suggested that common misperceptions of randomness may actually reflect genuine aspects of the statistical environment, once cognitive constraints are taken into account which impact on how that environment is actually experienced (Hahn & Warren, Psychological Review, 2009). In the present study we undertake an empirical test of this account, comparing human-generated against unbiased process-generated binary sequences in two experiments. We suggest that comparing human and theoretically unbiased sequences using metrics reflecting the constraints imposed on human experience provides a more meaningful picture of lay people’s ability to perceive randomness. Finally, we propose a simple generative model of human random sequence generation inspired by the Hahn and Warren account. Taken together our results question the notion of bias in human randomness perception.