The biological and behavioral bases of decision-making in medical professionals

描述（由申请人提供）：人们对医疗决策的基本机制知之甚少，事实上，在类似的高维环境中，任何决策都是如此。我们认为，这些环境与围绕专业知识的社会条件相结合，会导致显著的决策偏差，特别是确认偏差和锚定，这可能在一定程度上导致CER采用缓慢。我们认为，在受控的实验条件下研究医生的决策过程，并结合神经数据的收集，将使我们能够了解助长这些偏见的基本机制，并导致更好的训练和行为干预来纠正它们。

DESCRIPTION (provided by applicant): Little is known about the basic mechanisms of medical decision-making, or in fact any decision making in similar sorts of high-dimensional environment. We propose that these environments, paired with the social conditions around expertise lend themselves to significant decision biases, particularly confirmation-bias and anchoring, which may in part contribute to slow CER adoption. We feel that studying decision-making processes in doctors under controlled experimental conditions, paired with the collection of neural data will allow us to understand the fundamental mechanisms fueling these biases and lead to better training and behavioral interventions to correct them. We will be using both behavioral and fMRI analysis to examine the computational and mechanistic underpinnings of valuation in medical professionals. In addition we will be using quantitative models to explore the computational mechanisms involved in decision making in this population. Further, we will be applying new techniques using real-time fMRI feedback for behavioral modification. Confirmation-bias, success chasing, and anchoring are among the potential causes for faulty updating in physicians. Our preliminary data show that our low-performing subject physicians had a tendency to come to a conclusion quickly and then ignore treatment failures that might invalidate their beliefs. This confirmation-bias led to our subjects forming suboptimal treatment algorithms. In this aim, we will: 1) estimate models of physician learning in a controlled experimental setting in both medical and non-medical contexts, and 2) estimate models of belief formation and information search in physicians given extra external prior information, such as a previous diagnosis; identify the behavioral and neural markers of physicians who are particularly adept at this process; and assess the efficacy of a simple behavioral intervention on outcomes. Our preliminary work showed that high-performers in our clinical decision-making task showed distinctly different neural activations. We believe that by giving physicians feedback on their neural responses as well as their treatment outcomes we will be able to improve their ability to correctly learn the optimal treatment algorithm. PUBLIC HEALTH RELEVANCE: Little is known about the basic mechanisms of medical decision-making. We propose that such multidimensional environments, paired with the social conditions around expertise, lend themselves to significant decision biases, which in part may explain slow CER adoption. We will study decision-making processes in physicians under controlled experimental conditions, paired with the neuroimaging data, to allow for better understanding of the fundamental mechanisms fueling these biases.