ObjectivesTo assess minimal medical statistical literacy in medical students and senior educators using the 10-item Quick Risk Test; to assess whether deficits in statistical literacy are stable or can be reduced by training.DesignProspective observational study on the students, observational study on the university lecturers.SettingCharité University Medicine medical curriculum for students and a continuing medical education (CME) course at a German University for senior educators.Participants169 students taking part in compulsory final-year curricular training in medical statistical literacy (63% female, median age 25 years). Sixteen professors of medicine and other senior educators attending a CME course on medical statistical literacy (44% female, age range=30–65 years).InterventionsStudents completed a 90 min training session in medical statistical literacy. No intervention for the senior educators.Outcome measuresPrimary outcome measure was the number of correct answers out of four multiple-choice alternatives per item on the Quick Risk Test.ResultsFinal-year students answered on average half (median=50%) of the questions correctly while senior educators answered three-quarters correctly (median=75%). For comparison, chance performance is 25%. A 90 min training session for students increased the median percentage correct from 50% to 90%. 82% of participants improved their performance.ConclusionsMedical students and educators do not master all basic concepts in medical statistics. This can be quickly assessed with the Quick Risk Test. The fact that a 90 min training session on medical statistical literacy improves students’ understanding from 50% to 90% indicates that the problem is not a hard-wired inability to understand statistical concepts. This gap in physicians’ education has long-lasting effects; even senior medical educators could answer only 75% of the questions correctly on average. Hence, medical students and professionals should receive enhanced training in how to interpret risk-related medical statistics.

Please cite this article as: Niklas Keller , Konstantinos V. Katsikopoulos , On the role of psychological heuristics in operational research; and a demonstration in military stability operations, 1 HighlightsWe discuss psychological heuristics and their relationship to soft and hard OR.We discuss the evidence and theory for the performance of psychological heuristics.We propose a psychological heuristic for reducing civilian casualties in checkpoints. AbstractPsychological heuristics are formal models for making decisions that (i) rely on core psychological capacities (e.g., recognizing patterns or recalling information from memory), (ii) do not necessarily use all available information, and process the information they use by simple computations (e.g., ordinal comparisons or un-weighted sums), and (iii) are easy to understand, apply and explain. The contribution of this article is fourfold: First, the conceptual foundation of the psychological heuristics research program is provided, along with a discussion of its relationship to soft and hard OR. Second, empirical evidence and theoretical analyses are presented on the conditions under which psychological heuristics perform on par with or even better than more complex standard models in decision problems such as multi-attribute choice, classification, and forecasting, and in domains as varied as health, economics and management. Third, we demonstrate the application of the psychological heuristics approach to the problem of reducing civilian casualties in military stability operations. Finally, we discuss the role that psychological heuristics can play in OR theory and practice.