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Updated: Mar 30, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Age-related decline and diagnostic performance of more and less prevalent clinical cases
Christina St-Onge1, Marjolaine Landry2, Marianne Xhignesse2
1Faculté de Médecine et des Sciences de la Santé, Université de Sherbrooke, 12e Avenue Nord, Sherbrooke, QC, J1H 5N4, Canada. Christina.St-Onge@USherbrooke.ca.
Abstract:
Since cognitive abilities have been shown to decrease with age, it is expected that older physicians would not perform as well as their younger counterparts on clinical cases unless their expertise can counteract the cognitive effects of aging. However, studies on the topic have shown contradictory results. This study aimed to further investigate the effect of aging on physicians' diagnostic accuracy when diagnosing prevalent and less prevalent cases based on clinical vignettes. A mixed design was used to assess the influence of case prevalence (high vs. low) as a within-subjects factor, and age group as a between subjects factor (<30; n = 23, 30-39; n = 19, 40-49; n = 27, >50 years old; n = 19) on the diagnostic accuracy of 65 family physicians and 25 residents. Repeated Measure ANOVA revealed a significant effect of case prevalence (p < .001) and age group (p < .001). Post-hoc analyses revealed that younger physicians showed the best performance. This study did not demonstrate the positive effect of experience in older physicians. In line with previous studies on expertise development, findings of the present study suggest that skills should be actively maintained to assure a high performance level throughout one's lifespan. If not, performance level could gradually decline with age.
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