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Updated: Jul 5, 2026
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Decisional capacity for research participation in individuals with mild cognitive impairment
Angela L Jefferson1, Susan Lambe, David J Moser
1Department of Neurology, Alzheimer's Disease Center, School of Medicine, University of Massachusetts at Boston, Boston, Massachusetts 02118, USA. angelaj@bu.edu
Objectives:
To assess decisional capacity performance and the neuropsychological correlates of such performance to better understand higher-level instrumental activities of daily living in individuals with mild cognitive impairment (MCI).
Design:
Cross-sectional.
Setting:
Research center, medical center, or patient's home.
Participants:
Forty participants with MCI and 40 cognitively normal older controls (NCs) aged 60 to 90 (mean age+/-standard deviation 73.3+/-6.6; 54% female).
Measurements:
Capacity to provide informed consent for a hypothetical, but ecologically valid, clinical trial was assessed using the MacArthur Competence Assessment Tool for Clinical Research. Neuropsychological functioning was assessed using a comprehensive protocol.
Results:
Adjusted between-group comparisons yielded significant differences for most decisional capacity indices examined, including Understanding (P=.001; NC>MCI) and Reasoning (P=.002; NC>MCI). Post hoc analyses revealed that participants with MCI who were categorized as capable of providing informed consent according to expert raters had higher levels of education than those who were categorized as incapable.
Conclusion:
The findings suggest that many individuals with MCI perform differently on a measure of decisional capacity than their NC peers and that participants with MCI who are incapable of providing informed consent on a hypothetical and complex clinical trial are less educated. These findings are consistent with prior studies documenting functional and financial skill difficulties in individuals with MCI.
