Adaptive cognitive testing in dementia

Hans Wouters*, Aeilko H Zwinderman, Willem A van Gool, Ben Schmand, Robert Lindeboom

*Corresponding author for this work

    Research output: Contribution to journalArticleAcademicpeer-review

    23 Citations (Scopus)

    Abstract

    The objective of this study was to investigate whether the Cambridge Cognitive Examination (CAMCOG), a widely used screening test for dementia, can be tailored to the individual patient with Computerized Adaptive Testing (CAT). CAT accomplishes this by only using items that are appropriate for the level of ability of the patient under investigation. Potential advantages of CAT for clinical practice and research are efficient cognitive testing and a reduction of the test burden in elderly patients and consequently less measurement error during testing. In a two step method with previously collected CAMCOG data (n = 797) (1) patient abilities and CAMCOG item difficulties were estimated with the One Parameter Logistic Model (OPLM), a Rasch type of model. CAT was then used (2) to re-estimate the patient abilities. Despite an average test reduction of 60%, CAT estimates were in excellent agreement (intra-class correlation > 0.98) with the results based on the entire CAMCOG and they also had similar accuracy for the diagnosis of dementia (area under the curve 0.91) as the original CAMCOG. These results were replicated in an independent sample (n = 170). We conclude that tailored testing with CAT enables much more efficient screening for dementia than testing with an extensive instrument.

    Original languageEnglish
    Pages (from-to)118-127
    Number of pages10
    JournalInternational Journal of Methods in Psychiatric Research
    Volume18
    Issue number2
    DOIs
    Publication statusPublished - Jun-2009

    Keywords

    • Adaptation, Psychological
    • Aged
    • Aged, 80 and over
    • Cognition Disorders
    • Dementia
    • Female
    • Humans
    • Logistic Models
    • Male
    • Mental Status Schedule
    • Neuropsychological Tests
    • Predictive Value of Tests

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