Cognitive and learning sciences in biomedical and health instructional design: A review with lessons for biomedical informatics education.

Theoretical and methodological advances in the cognitive and learning sciences can greatly inform curriculum and instruction in biomedicine and also educational programs in biomedical informatics. It does so by addressing issues such as the processes related to comprehension of medical information, clinical problem-solving and decision-making, and the role of technology. This paper reviews these theories and methods from the cognitive and learning sciences and their role in addressing current and future needs in designing curricula, largely using illustrative examples drawn from medical education. The lessons of this past work are also applicable, however, to biomedical and health professional curricula in general, and to biomedical informatics training, in particular. We summarize empirical studies conducted over two decades on the role of memory, knowledge organization and reasoning as well as studies of problem-solving and decision-making in medical areas that inform curricular design. The results of this research contribute to the design of more informed curricula based on empirical findings about how people learn and think, and more specifically, how expertise is developed. Similarly, the study of practice can also help to shape theories of human performance, technology-based learning, and scientific and professional collaboration that extend beyond the domain of medicine. Just as biomedical science has revolutionized health care practice, research in the cognitive and learning sciences provides a scientific foundation for education in biomedicine, the health professions, and biomedical informatics.

Towards effective evaluation and reform in medical education: a cognitive and learning sciences perspective.

Health professions education is dealing with major transformations in light of the changing nature of the health care delivery system, including the use of technology for "just in time" delivery of care, evidence-based practice, personalized medical care and learning, as health professionals strive to integrate biomedical advances and clinical practice. This has forced the medical education community to reassess the current teaching and learning practices and more importantly, the evaluation of the medical education process. There have been recent advances in cognitive and learning sciences theories, some of which can inform medical educators about best teaching and learning practices and their impact on the evaluation process. An understanding of these theories provides a sound rationale for choosing specific instructional strategies and choosing evaluation measures that assess the curricular objectives. The review begins with an overview of evaluation and assessment in education, followed by an overview of major theories from the cognitive and learning sciences. Next, the role of cognitive and learning sciences theories in informing the process of medical education evaluation is discussed, including its impact on student learning, performance and professional competence, as well as recommendations for reform of medical curricula based on such theories. The paper continues with the elaboration of current trends in health sciences education, particularly medical education, and available evidence for the impact on student learning and performance as well as areas where more research is needed.

Lay public's knowledge and decisions in response to symptoms of acute myocardial infarction.

Despite public health initiatives targeting rapid action in response to symptoms of myocardial infarction (MI), people continue to delay in going to a hospital when experiencing these symptoms due to lack of recognition as cardiac-related. The objective of this research was to characterize lay individuals' knowledge of symptoms of acute myocardial infarction (AMI) and associated decision processes for timely action. Thirty participants were interviewed about their knowledge of AMI, then presented with unrelated, unfamiliar and familiar scenarios of AMI symptoms and instructed to "think aloud" as they made decisions in response to the scenarios in order to capture the decision process directly. Data were analyzed using qualitative and quantitative methods to identify the semantic relationships between knowledge and decisions. Results showed that most participants (80%) identified three symptoms or less (e.g., chest pain: 93%; dyspnea: 53%). All participants identified urgent actions (calling 911, going to ED) as the appropriate response to AMI symptoms. Urgent action decisions increased with familiarity of symptoms (57% for unrelated symptoms to 83% for most familiar symptoms), and was highest for the cardiac group. Lay knowledge of AMI is necessary, but not sufficient for people to develop required heuristics for timely action. This ineffective decision increases as a function of ambiguous and unfamiliar situations. Health education interventions should focus on teaching clusters of problems with varying levels of familiarity and complexity to increase flexibility in making decisions.

Translational cognition for decision support in critical care environments: a review.

The dynamic and distributed work environment in critical care requires a high level of collaboration among clinical team members and a sophisticated task coordination system to deliver safe, timely and effective care. A complex cognitive system underlies the decision-making process in such cooperative workplaces. This methodological review paper addresses the issues of translating cognitive research to clinical practice with a specific focus on decision-making in critical care, and the role of information and communication technology to aid in such decisions. Examples are drawn from studies of critical care in our own research laboratories. Critical care, in this paper, includes both intensive (inpatient) and emergency (outpatient) care. We define translational cognition as the research on basic and applied cognitive issues that contribute to our understanding of how information is stored, retrieved and used for problem-solving and decision-making. The methods and findings are discussed in the context of constraints on decision-making in real-world complex environments and implications for supporting the design and evaluation of decision support tools for critical care health providers.

The role of emotion in decision-making: a cognitive neuroeconomic approach towards understanding sexual risk behavior.

Models of decision-making usually focus on cognitive, situational, and socio-cultural variables in accounting for human performance. However, the emotional component is rarely addressed within these models. This paper reviews evidence for the emotional aspect of decision-making and its role within a new framework of investigation, called neuroeconomics. The new approach aims to build a comprehensive theory of decision-making, through the unification of theories and methods from economics, psychology, and neuroscience. In this paper, we review these integrative research methods and their applications to issues of public health, with illustrative examples from our research on young adults' safe sex practices. This approach promises to be valuable as a comprehensively descriptive and possibly, better predictive model for construction and customization of decision support tools for health professionals and consumers.

Discerning patterns of human immunodeficiency virus risk in healthy young adults.

Previous research has questioned the effectiveness of existing methods to identify individuals at high risk for contracting and transmitting human immunodeficiency virus and other sexually transmitted diseases. Thus, new approaches are needed to provide these individuals with risk-reduction strategies. We review our research on young adults' sexual decision making by using theories and methods from social and cognitive sciences. Four patterns of condom use and associated levels of risks and beliefs were identified. These patterns suggest value in targeting intervention strategies to individuals at different levels of risk. The findings also imply that the monogamous population may be at higher risk for infection than they realize. Primary-care physicians are the first line of contact for many individuals in the health care system and may be in the best position to screen for at-risk individuals. Given the time demands and other barriers, easy-to-use, evidence-based guidelines for such screening are needed. We propose such guidelines for primary-care physicians to use in identifying an individual's risk, from which custom-tailored intervention strategies can be developed.

Risky decisions despite counter evidence: modeling a culture of safer sexual practices.

To create a culture of safe practices, we need to understand how and under what conditions the public makes risky decisions about their health. Because risky sexual behaviors are known to be common in young adults, we investigated their decision making regarding sexual activities that could incur a high risk of HIV infection. Sixty young urban adults maintained journals for two weeks and were interviewed regarding condom use and sexual history. We characterized four patterns of condom use behavior: consistent (35.0%), inconsistent (16.7%), consistent to inconsistent (35.0%), and inconsistent to consistent (13.3%). Directionality of reasoning was analyzed in the explanations provided for condom use decisions. The consistent and inconsistent patterns were associated with data-driven heuristic reasoning, where behavior becomes automated and is associated with a high level of confidence in one's judgment. In the other two patterns, the shift in behavior was due to a significant event that influenced a change in directionality to explanation-based reasoning. We discuss these results within the framework of identifying potentially high-risk groups for whom customized intervention strategies (such as computer-based educational programs) can be used to reduce risk, thereby creating a culture of safer sexual practices.

Cognitive neuroeconomics: new solutions to old problems.

The current models of decision-making are limited in their ability to provide a comprehensive understanding of the field. We propose the cognitive neuroeconomics model, which, we have used to better understand the process of decision-making in the domain of mental health, namely, young adults' risky sexual behavior. This model can have far reaching implications in developing adequate decision support tools.