Dementia diagnoses from clinical and neuropsychological data compared: The Cache County study

J. T. Tschanz, K. A. Welsh-Bohmer, I. Skoog, N. West, M. C. Norton, B. W. Wyse, R. Nickles, J. C.S. Breitner

Research output: Contribution to journalArticlepeer-review

57 Scopus citations


Objective: To validate a neuropsychological algorithm for dementia diagnosis. Methods: We developed a neuropsychological algorithm in a sample of 1,023 elderly residents of Cache County, UT. We compared algorithmic and clinical dementia diagnoses both based on DSM-III-R criteria. The algorithm diagnosed dementia when there was impairment in memory and at least one other cognitive domain. We also tested a variant of the algorithm that incorporated functional measures that were based on structured informant reports. Results: Of 1,023 participants, 87% could be classified by the basic algorithm, 94% when functional measures were considered. There was good concordance between basic psychometric and clinical diagnoses (79% agreement, kappa = 0.57). This improved after incorporating functional measures (90% agreement, kappa = 0.76). Conclusions: Neuropsychological algorithms may reasonably classify individuals on dementia status across a range of severity levels and ages and may provide a useful adjunct to clinical diagnoses in population studies.

Original languageEnglish (US)
Pages (from-to)1290-1296
Number of pages7
Issue number6
StatePublished - Mar 28 2000
Externally publishedYes


  • Dementia Neuropsychology
  • Psychometric classification

ASJC Scopus subject areas

  • Clinical Neurology


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