Data-driven approaches to executive function performance and structure in aging: Integrating person-centered analyses and machine learning risk prediction.

Conclusions: Data-driven modeling approaches tested the possibility of an EF aging class that displayed both preserved EF performance levels and sustained multidimensional structure. The two observed classes differed in both performance level (lower, higher) and structure (unidimensional, multidimensional). Machine learning prediction analyses showed that the higher performing and multidimensional class was associated with multiple brain health-related protective factors. (PsycInfo Database Record (c) 2021 APA, all rights reserved)
Source: Neuropsychology - Category: Neurology Source Type: research