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Review
. 2023 Aug 30;8(1):58.
doi: 10.1186/s41235-023-00511-z.

Cognitive perspectives on maintaining physicians' medical expertise: III. Strengths and weaknesses of self-assessment

Affiliations
Review

Cognitive perspectives on maintaining physicians' medical expertise: III. Strengths and weaknesses of self-assessment

Scott H Fraundorf et al. Cogn Res Princ Implic. .

Abstract

Is self-assessment enough to keep physicians' cognitive skills-such as diagnosis, treatment, basic biological knowledge, and communicative skills-current? We review the cognitive strengths and weaknesses of self-assessment in the context of maintaining medical expertise. Cognitive science supports the importance of accurately self-assessing one's own skills and abilities, and we review several ways such accuracy can be quantified. However, our review also indicates a broad challenge in self-assessment is that individuals do not have direct access to the strength or quality of their knowledge and instead must infer this from heuristic strategies. These heuristics are reasonably accurate in many circumstances, but they also suffer from systematic biases. For example, information that feels easy to process in the moment can lead individuals to overconfidence in their ability to remember it in the future. Another notable phenomenon is the Dunning-Kruger effect: the poorest performers in a domain are also the least accurate in self-assessment. Further, explicit instruction is not always sufficient to remove these biases. We discuss what these findings imply about when physicians' self-assessment can be useful and when it may be valuable to supplement with outside sources.

Keywords: Medical expertise; Metacognition; Self-assessment.

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Conflict of interest statement

The authors were not involved with the peer-review process of this work.

Figures

Fig. 1
Fig. 1
Schematic design of the typical judgment-of-learning (JOL) study procedure with immediate JOLs (top row) and delayed JOLs (bottom row)
Fig. 2
Fig. 2
Prototypical Dunning–Kruger effect (not representing data from any specific study)

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