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Updated: Aug 21, 2026
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Effects of education and culture on the validity of the Geriatric Mental State and its AGECAT algorithm
Martin Prince1, Daisy Acosta, Helen Chiu
1Institute of Psychiatry, King's College, London, UK. m.prince@iop.kcl.ac.uk.
Background:
The Geriatric Mental State (GMS) is the most widely used psychiatric research assessment for older persons. Evidence for validity comes from the developed world.
Aims:
To assess the validity of GMS/AGECAT organicity and depression diagnoses in 26 centres in India, China, Latin America and Africa.
Method:
We studied 2941 persons aged 60 years and over: 742 people with dementia and three groups free of dementia (697 with depression, 719 with high and 783 with low levels of education). Local clinicians diagnosed dementia (DSM-IV) and depression (Montgomery-Asberg Depression Rating Scale score >/=18).
Results:
For dementia diagnosis GMS/AGECAT performed well in many centres but educational bias was evident. Specificity was poor in India and sensitivity sub-optimal in Latin America. A predictive algorithm excluding certain orientation items but including interviewer judgements improved upon the AGECAT algorithm. For depression, sensitivity was high. The EURO-D depression scale, derived from GMS items using European data, has a similar factor structure in Latin America, India and, to a lesser extent, China.
Conclusions:
Valid, comprehensive mental status assessment across cultures seems achievable in principle.
