title: Clinical validation of the General Ability Index--Estimate (GAI-E): estimating premorbid GAI.
abstract: The clinical utility of the General Ability Index--Estimate (GAI-E; Lange, Schoenberg, Chelune, Scott, & Adams, 2005) for estimating premorbid GAI scores was investigated using the WAIS-III standardization clinical trials sample (The Psychological Corporation, 1997). The GAI-E algorithms combine Vocabulary, Information, Matrix Reasoning, and Picture Completion subtest raw scores with demographic variables to predict GAI. Ten GAI-E algorithms were developed combining demographic variables with single subtest scaled scores and with two subtests. Estimated GAI are presented for participants diagnosed with dementia (n = 50), traumatic brain injury (n = 20), Huntington's disease (n = 15), Korsakoff's disease (n = 12), chronic alcohol abuse (n = 32), temporal lobectomy (n = 17), and schizophrenia (n = 44). In addition, a small sample of participants without dementia and diagnosed with depression (n = 32) was used as a clinical comparison group. The GAI-E algorithms provided estimates of GAI that closely approximated scores expected for a healthy adult population. The greatest differences between estimated GAI and obtained GAI were observed for the single subtest GAI-E algorithms using the Vocabulary, Information, and Matrix Reasoning subtests. Based on these data, recommendations for the use of the GAI-E algorithms are presented.
authors.affiliation: Department of Neurology, University Hospitals of Cleveland and Case Western Reserve University School of Medicine, Cleveland, OH 44106-5000, USA. Michael.Schoenberg@uhhs.com
authors.forename: Mike R
authors.initials: MR
authors.lastname: Schoenberg
authors.forename: Rael T
authors.initials: RT
authors.lastname: Lange
authors.forename: Grant L
authors.initials: GL
authors.lastname: Iverson
authors.forename: Gordon J
authors.initials: GJ
authors.lastname: Chelune
authors.forename: James G
authors.initials: JG
authors.lastname: Scott
authors.forename: Russell L
authors.initials: RL
authors.lastname: Adams
mesh_terms: D000465:Algorithms; D000704:Analysis of Variance; D001927:Brain Diseases / Q000175:diagnosis / Q000503:physiopathology*; D003071:Cognition / Q000502:physiology*; D003710:Demography; D003863:Depression / Q000175:diagnosis / Q000503:physiopathology; D005260:Female; D006801:Humans; D007360:Intelligence / Q000502:physiology*; D007361:Intelligence Tests; D008297:Male; D009483:Neuropsychological Tests; D011237:Predictive Value of Tests; D012015:Reference Standards; D015203:Reproducibility of Results