On Medical Uncertainty and Coping Strategies during Resident Education
Abstract
Medical residents experience distinct levels of uncertainty in clinical practice, whereby they develop diverse coping strategies with the goal of dealing effectively with ordinary and extraordinary situations. Taken from a previous mixed method study, 36 hypothetical uncertainty situations were presented to residents in a survey and the data was examined to analyze the interaction between 8 types of uncertainty, 11 possible strategies to solve the situation. We explore some of the contextual variables that influence the residents to use one strategy or another depending on the type of uncertainty. Latent class (LC) regression models were used for each type of uncertainty to classify 2,414 students into groups according to the strategy used to handle the uncertainty, as well as independent variables that could have affected belonging to a specific group. Statistically significant contextual elements for resident decision-making: years into the residency, hospital level, and area of specialty. In the LC analysis, up to four classes were identified; two of them were consistent for all types of uncertainty, the other two classes varied depending on the type of uncertainty. Recognition of contextual elements on the uncertainty situations that affect resident decision-making may help plan actions to improve medical practice.
Full Text: PDF DOI: 10.15640/jehd.v7n1a12
Abstract
Medical residents experience distinct levels of uncertainty in clinical practice, whereby they develop diverse coping strategies with the goal of dealing effectively with ordinary and extraordinary situations. Taken from a previous mixed method study, 36 hypothetical uncertainty situations were presented to residents in a survey and the data was examined to analyze the interaction between 8 types of uncertainty, 11 possible strategies to solve the situation. We explore some of the contextual variables that influence the residents to use one strategy or another depending on the type of uncertainty. Latent class (LC) regression models were used for each type of uncertainty to classify 2,414 students into groups according to the strategy used to handle the uncertainty, as well as independent variables that could have affected belonging to a specific group. Statistically significant contextual elements for resident decision-making: years into the residency, hospital level, and area of specialty. In the LC analysis, up to four classes were identified; two of them were consistent for all types of uncertainty, the other two classes varied depending on the type of uncertainty. Recognition of contextual elements on the uncertainty situations that affect resident decision-making may help plan actions to improve medical practice.
Full Text: PDF DOI: 10.15640/jehd.v7n1a12
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