Greater than the Sum of Its Parts: δ can be Constructed from Item Level Data

This is the authors' abstract. We don't add key points for this paper.

"δ", a latent variable constructed from cognitive performance and functional status measures, can accurately diagnose dementia. The minimal assessment needed is unknown. We have constructed a δ homolog, "dTEXAS", from Telephone Executive Assessment Scale (TEXAS) items, and validated it in a convenience sample of Japanese persons (n = 176). dTEXAS scores correlated strongly with both Instrumental Activities of Daily Living (IADL) (r = -0.86, p < 0.001) and Clinical Dementia Rating Scale (CDR) (r = 0.71, p < 0.001). Constructed independently of their diagnoses, dTEXAS scores accurately distinguished dementia versus controls (area under the receiver operating curve [(AUC; ROC) = 0.92], dementia versus mild cognitive impairment (MCI) (AUC = 0.80) and controls versus MCI (AUC = 0.74). These AUCs are higher than those of multiple observed executive measures, as reported recently by Matsuoka et al., 2014. A dTEXAS score of -0.58 best discriminated between dementia versus controls with 90.1% sensitivity and 80.0% specificity.