Factor structure of the Community Screening Interview for Dementia (CSI-D) among Zambian adults
Related Experiment Video
Updated: Oct 31, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Lisa Kalungwana1,2, Nicholas Heaton3, Emily Briceno4
1Ciheb Zambia, Lusaka, Zambia.
Abstract:
The Community Screening Interview for Dementia (CSI-D) has been widely used for dementia research among aging adults in low- and middle-income countries, where few specialists are available to diagnose and manage dementia. Yet, little is known about the psychometric validity of the participant interview, particularly among low-literacy individuals. We used factor analysis methods to assess and refine theoretically driven single- and multiple-factor structural models for the CSI-D participant interview using the population-based Zambian Cohort of Healthy Aging and Dementia (Z-CHAD) in Lusaka. Trained community healthcare workers administered the CSI-D participant interview to 734 adults (68% female, mean age 66.9 years, mean education 7 years). For the four domains of cognitive functioning identified (memory, orientation, language, and visuospatial), single-factor models had satisfactory fit after the removal of five items with low factor loadings. The second-order factor model had adequate fit (confirmatory fit index = 0.96, root mean square error of approximation= 0.03, standardized root mean square residual = 0.08). This factor structure of the CSI-D participant interview reasonably summarizes cognitive domain performance in this sample, yet there is a noticeable ceiling effect in items for orientation and language. Further, domains sensitive to dementia-related impairments, namely executive function, are not assessed.
