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Updated: Aug 11, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Depression in mild cognitive impairment in a community sample of individuals 60-64 years old
Rajeev Kumar1, Anthony F Jorm, Ruth A Parslow
1Department of Psychological Medicine, Australian National University Medical School, Canberra, Australia. Rajeev.Kumar@act.gov.au
Objective:
This cross-sectional study examined the prevalence and characteristics of depression in subjects with mild cognitive impairment (MCI). The data presented here are from the first wave of the longitudinal Personality and Total Health Through Life 60+ (PATH 60+) Project.
Method:
A total of 2551 community-dwelling individuals in the age range 60-64 years were recruited randomly through the electoral roll. They were screened using a short cognitive battery and those who screened positive underwent detailed medical and neuropsychological assessments. There were 29 subjects who fulfilled the Mayo Clinic criteria for MCI and these were compared to 520 controls. Subjects were evaluated for depression symptoms and DSM-IV major and minor depression syndromes.
Results:
Subjects with MCI had more minor depression and higher scores on a symptom scale. However, a multivariate examination of specific symptoms showed that the differences were confined to only two motivation-related symptoms ("felt slowed up" and "little interest or pleasure").
Conclusion:
Motivation-related depressive symptoms are more relevant in subjects with MCI than mood-related symptoms.
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