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Updated: Oct 2, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
The detection of mental disorders in the community using a 20-item interview version of the General Health
J F Samuels1, G Nestadt, J C Anthony
1Department of Psychiatry and Behavioral Sciences, School of Medicine, Johns Hopkins University, Baltimore, Maryland.
Abstract:
A 20-item interview version of the General Health Questionnaire (GHQ) was used to presumptively identify cases with mental disorders in a sample of 810 community residents. Subjects also were examined by psychiatrists using the Present State Examination (PSE). The screening instrument performed well in detecting PSE-CATEGO syndromes related to anxiety and depression, but less well in detecting psychotic syndromes and cognitive impairment. The overall sensitivity of the instrument for any PSE-CATEGO syndrome was 48%. The study elucidates the specific nature of the psychopathology that this version of the GHQ is likely to detect in the community.
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