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Updated: Feb 15, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Data quality, floor and ceiling effects, and test-retest reliability of the Mild Cognitive Impairment Questionnaire
Katherine Dean1, Zuzana Walker2, Crispin Jenkinson1
1Health Services Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford.
Background:
The Mild Cognitive Impairment Questionnaire (MCQ) is a 13-item measure that assesses health-related quality of life (HRQoL) in people with mild cognitive impairment (PWMCI); it has two domains assessing the emotional and practical effects.
Objective:
The aim of this study was to assess the psychometric properties of the MCQ.
Design:
This is a longitudinal questionnaire-based study.
Setting:
The participants were recruited from the memory clinics and research databases in the South of England.
Subjects:
A total of 299 people aged 50 years and older with a diagnosis of mild cognitive impairment confirmed within the preceding 12 months.
Methods:
MCQs were distributed to patients in memory clinics and those listed on research databases. Participants who returned completed questionnaires were sent a second copy of the MCQ to return 2 weeks after receiving the first questionnaire.
Results:
Five hundred and seven questionnaires were distributed; response rates were 68.2% initially and 89.2% for the second questionnaire. From the returned questionnaires, response rates for each item were high (>98%) and a full range of responses for each item was received with no evidence of significant floor or ceiling effects. Internal consistency reliability for both scale scores at both time points was good, with Cronbach's a≥0.84 in all cases. Test-retest reliability was excellent for both domains with the intraclass correlation coefficients of 0.90 and 0.92 for the practical and emotional domains, respectively. Paired sample t-tests also confirmed the stability of scale score distributions over time.
Conclusion:
The MCQ has robust psychometric properties, which make it suitable for assessing HRQoL in PWMCI, including comparison of group level data in intervention studies.
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