title: [Mokken scaling of the Cognitive Screening Test].
abstract: The Cognitive Screening Test (CST) is a twenty-item orientation questionnaire in Dutch, that is commonly used to evaluate cognitive impairment. This study applied Mokken Scale Analysis, a non-parametric set of techniques derived from item response theory (IRT), to CST-data of 466 consecutive participants in psychogeriatric day care. The full item set and the standard short version of fourteen items both met the assumptions of the monotone homogeneity model, with scalability coefficient H = 0.39, which is considered weak. In order to select items that would fulfil the assumption of invariant item ordering or the double monotonicity model, the subjects were randomly partitioned into a training set (50% of the sample) and a test set (the remaining half). By means of an automated item selection eleven items were found to measure one latent trait, with H = 0.67 and item H coefficients larger than 0.51. Cross-validation of the item analysis in the remaining half of the subjects gave comparable values (H = 0.66; item H coefficients larger than 0.56). The selected items involve year, place of residence, birth date, the monarch's and prime minister's names, and their predecessors. Applying optimal discriminant analysis (ODA) it was found that the full set of twenty CST items performed best in distinguishing two predefined groups of patients of lower or higher cognitive ability, as established by an independent criterion derived from the Amsterdam Dementia Screening Test. The chance corrected predictive value or prognostic utility was 47.5% for the full item set, 45.2% for the fourteen items of the standard short version of the CST, and 46.1% for the homogeneous, unidimensional set of selected eleven items. The results of the item analysis support the application of the CST in cognitive assessment, and revealed a more reliable 'short' version of the CST than the standard short version (CST14).
authors.affiliation: PgD, De Stichtse Hof Vivium zorggroep, Laren NH. h.diesfeldt@vivium.nt
authors.forename: H F A
authors.initials: HF
authors.lastname: Diesfeldt
mesh_terms: D000368:Aged; D003072:Cognition Disorders / Q000145:classification / Q000175:diagnosis*; D016002:Discriminant Analysis; D005260:Female; D006801:Humans; D008297:Male; D009426:Netherlands; D011594:Psychometrics / Q000592:standards*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D018709:Statistics, Nonparametric