Rationale, aims, and objectives
Uncertainty is a complex and constant phenomenon in clinical practice. How medical students recognize and respond to uncertainty impacts on their well‐being, career choices, and attitudes towards patients. It has been suggested that curricula should do more to prepare medical students for an uncertain world. In order to teach medical students about uncertainty, we need to understand how uncertainty has been conceptualized in the literature to date. The aim of this article is to explore existing models of uncertainty and to develop a framework of clinical uncertainty to aid medical education.
Method
A scoping literature review was performed to identify conceptual models of uncertainty in healthcare. Content and inductive analyses were performed to explore three dimensions of clinical uncertainty: sources of uncertainty, subjective influencers and responses to uncertainty.
Results
Nine hundred one references were identified using our search strategy, of which, 24 met our inclusion criteria. It was possible to classify these conceptual models using one or more of three dimensions of uncertainty; sources, subjective influencers, and responses. Exploration and further classification of these dimensions led to the development of a framework of uncertainty for medical education.
Conclusion
The developed framework of clinical uncertainty highlights sources, subjective influencers, responses to uncertainty, and the dynamic relationship among these elements. Our framework illustrates the different aspects of knowledge as a source of uncertainty and how to distinguish between those aspects. Our framework highlights the complexity of sources of uncertainty, especially when including uncertainty arising from relationships and systems. These sources can occur in combination. Our framework is also novel in how it describes the impact of influencers such as personal characteristics, experience, and affect on perceptions of and responses to uncertainty. This framework can be used by educators and curricula developers to help understand and teach about clinical uncertainty.