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Updated: May 7, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Attribution of mild cognitive impairment etiology in patients and their care partners
Juleen Rodakowski1, Richard Schulz, Amanda Gentry
1Department of Occupational Therapy, University of Pittsburgh, Pittsburgh, USA.
Objective:
This study examined the attribution of mild cognitive impairment (MCI) etiology assigned by individuals with MCI and their care partners, and the extent to which the dyads agreed on the attribution of MCI etiology.
Methods:
We conducted secondary analyses of cross-sectional data from a cohort of individuals with MCI (n = 60) and their care partners (n = 60). The mean age of the individuals with MCI was 71.0 ± 9.4 years and of care partners 64.2 ± 11.0 years. The primary outcome was attribution assigned to memory deficits on the Illness Perception Questionnaire. We categorized the attribution of MCI etiology as either potentially controllable or uncontrollable factors. We described the distribution of MCI etiology with descriptive and contingency tables. We determined the odds of a patient or care partner choosing one type of MCI etiology over another.
Results:
Although individuals with MCI and their care partners most frequently attributed MCI to uncontrollable factors (81.7% and 61.0%, respectively), care partners were 28.41 (95% CI, 1.26 to 645.48) times more likely to attribute MCI etiology to potentially controllable factors than individuals with MCI. No significant associations between demographic factors and attribution of MCI etiology were found for the individuals with MCI or the care partners.
Conclusion:
Findings demonstrated that members of the dyad attributed MCI etiology to different causes. Attributions of MCI etiology should be explored by professionals to clarify misconceptions and potentially improve subsequent voluntary actions intended to assist oneself or others.
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