The gender conformity conundrum: The effects of irrelevant gender norms on public conformity.

The purpose of this experiment was to examine influences of gender norms on gender-role conformity. This series of two studies tests whether females or males are more likely to conform to public norms. To test this, we attached men's and women's bathroom-type signs to exit doors from a café at a private academic institution in upstate New York. We then unobtrusively observed whether individuals chose to exit through the door matching their gender. We found that, in both studies, males conformed more to their gender-role sign than did females. This suggests that conformity to certain gender and social norms has greater influence on males, and that these norms have a substantial power over decisions in social settings. In addition, it may be that some males conform to these norms to avoid being represented or perceived as female and/or a lower-power member of society.

Reducing Muslim/Arab stereotypes through evaluative conditioning.

This study replicated and extended Olson and Fazio (2006) by testing whether evaluative conditioning is a means to reduce negative stereotypes about Muslim and other Arab persons. Specifically, evaluative conditioning was hypothesized to lower implicit biases against Muslim and Arab persons. The FreeIAT was used to measure implicit biases. Participants in the evaluative conditioning group showed a significant lowering in implicit biases. Explicit measures of bias were not affected by the conditioning procedure.

Do physicians know when their diagnoses are correct? Implications for decision support and error reduction.

OBJECTIVE: This study explores the alignment between physicians' confidence in their diagnoses and the "correctness" of these diagnoses, as a function of clinical experience, and whether subjects were prone to over-or underconfidence. DESIGN: Prospective, counterbalanced experimental design. SETTING: Laboratory study conducted under controlled conditions at three academic medical centers. PARTICIPANTS: Seventy-two senior medical students, 72 senior medical residents, and 72 faculty internists. INTERVENTION: We created highly detailed, 2-to 4-page synopses of 36 diagnostically challenging medical cases, each with a definitive correct diagnosis. Subjects generated a differential diagnosis for each of 9 assigned cases, and indicated their level of confidence in each diagnosis. MEASUREMENTS AND MAIN RESULTS: A differential was considered "correct" if the clinically true diagnosis was listed in that subject's hypothesis list. To assess confidence, subjects rated the likelihood that they would, at the time they generated the differential, seek assistance in reaching a diagnosis. Subjects' confidence and correctness were "mildly" aligned (kappa=.314 for all subjects, .285 for faculty, .227 for residents, and .349 for students). Residents were overconfident in 41% of cases where their confidence and correctness were not aligned, whereas faculty were overconfident in 36% of such cases and students in 25%. CONCLUSIONS: Even experienced clinicians may be unaware of the correctness of their diagnoses at the time they make them. Medical decision support systems, and other interventions designed to reduce medical errors, cannot rely exclusively on clinicians' perceptions of their needs for such support.

Exploring the boundaries of plausibility: empirical study of a key problem in the design of computer-based clinical simulations.

All clinical simulation designers face the problem of identifying the plausible diagnostic and management options to include in their simulation models. This study explores the number of plausible diagnoses that exist for a given case, and how many subjects must work up a case before all plausible diagnoses are identified. Data derive from 144 residents and faculty physicians from 3 medical centers, each of whom worked 9 diagnostically challenging cases selected from a set of 36. Each subject generated up to 6 diagnostic hypotheses for each case, and each hypothesis was rated for plausibility by a clinician panel. Of the 2091 diagnoses generated, 399 (19.1%), an average of 11 per case, were considered plausible by study criteria. The distribution of plausibility ratings was found to be statistically case dependent. Averaged across cases, the final plausible diagnosis was generated by the 28th clinician (sd = 8) who worked the case. The results illustrate the richness and diversity of human cognition and the challenges these pose for creation of realistic simulations in biomedical domains.