Janis A. Cannon-Bowers

This paper examines a skill that is critical to performance in complex team environments—team situational awareness. Specifically, it describes how the concept of shared mental models can be used to explain team situational awareness. A model is presented which explains how shared mental models are transformed into team situational awareness to enable effective team performance in dynamic task situations. Potential training strategies for enhancing team situational awareness are derived from this model and are discussed.

According to the threshold model, when faced with a decision under diagnostic uncertainty, physicians should administer treatment if the probability of disease is above a specified threshold and withhold treatment otherwise. The objectives of the present study are to a) evaluate if physicians act according to a threshold model, b) examine which of the existing threshold models [expected utility theory model (EUT), regret-based threshold model, or dual-processing theory] explains the physicians’ decision-making best.

Background. Patient outcomes critically depend on accuracy of physicians’ judgment, yet little is known about individual differences in cognitive styles that underlie physicians’ judgments. The objective of this study was to assess physicians’ individual differences in cognitive styles relative to age, experience, and degree and type of training. Methods. Physicians at different levels of training and career completed a web-based survey of 6 scales measuring individual differences in cognitive styles (maximizing v. satisficing, analytical v. intuitive reasoning, need for cognition, intolerance toward ambiguity, objectivism, and cognitive reflection). We measured psychometric properties (Cronbach’s α) of scales; relationship of age, experience, degree, and type of training; responses to scales; and accuracy on conditional inference task. Results. The study included 165 trainees and 56 attending physicians (median age 31 years; range 25–69 years). All 6 constructs showed acceptable psychometric properties. Surprisingly, we found significant negative correlation between age and satisficing (r = −0.239; P = 0.017). Maximizing (willingness to engage in alternative search strategy) also decreased with age (r = −0.220; P = 0.047). Number of incorrect inferences negatively correlated with satisficing (r = −0.246; P = 0.014). Disposition to suppress intuitive responses was associated with correct responses on 3 of 4 inferential tasks. Trainees showed a tendency to engage in analytical thinking (r = 0.265; P = 0.025), while attendings displayed inclination toward intuitive-experiential thinking (r = 0.427; P = 0.046). However, trainees performed worse on conditional inference task. Conclusion. Physicians capable of suppressing an immediate intuitive response to questions and those scoring higher on rational thinking made fewer inferential mistakes. We found a negative correlation between age and maximizing: Physicians who were more advanced in their careers were less willing to spend time and effort in an exhaustive search for solutions. However, they appeared to have maintained their “mindware” for effective problem solving.

Pressures to increase the efficacy and effectiveness of medical training are causing the Department of Defense to investigate the use of simulation technologies. This article describes a comprehensive cognitive task analysis technique that can be used to simultaneously generate training requirements, performance metrics, scenario requirements, and simulator/simulation requirements for medical tasks. On the basis of a variety of existing techniques, we developed a scenario-based approach that asks experts to perform the targeted task multiple times, with each pass probing a different dimension of the training development process. In contrast to many cognitive task analysis approaches, we argue that our technique can be highly cost effective because it is designed to accomplish multiple goals. The technique was pilot tested with expert instructors from a large military medical training command. These instructors were employed to generate requirements for two selected combat casualty care tasks-cricothyroidotomy and hemorrhage control. Results indicated that the technique is feasible to use and generates usable data to inform simulation-based training system design.