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Development of the Greek Verbal Learning Test: Reliability, Construct Validity, and Normative Standards
Author(s) -
Christina H. Vlahou,
Mary H. Kosmidis,
Aikaterini Dardagani,
Stella Tsotsi,
Μαρία Γιαννάκου,
Aikaterini Giazkoulidou,
Emmanuel Zervoudakis,
Nikolaos Pontikakis
Publication year - 2012
Publication title -
archives of clinical neuropsychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.909
H-Index - 98
eISSN - 1873-5843
pISSN - 0887-6177
DOI - 10.1093/arclin/acs099
Subject(s) - psychology , construct validity , test (biology) , normative , california verbal learning test , population , reliability (semiconductor) , construct (python library) , test validity , verbal learning , sample (material) , developmental psychology , regression analysis , psychometrics , clinical psychology , cognition , statistics , psychiatry , medicine , mathematics , computer science , chromatography , biology , physics , epistemology , paleontology , quantum mechanics , programming language , philosophy , power (physics) , chemistry , environmental health
We developed a multiple-form list learning test appropriate for use with the Greek population and generated norms for clinical and research use. This task, the Greek Verbal Learning Test (GVLT), was based on the California Verbal Learning Test. We administered the standard version (Form A) to a sample of 354 healthy individuals, as well as two alternative forms (B and C) to a subgroup of the initial sample. Performance on the three forms was equivalent, and each test presented excellent internal consistency. We found good sensitivity and specificity in the testãs (Form A) utility in differentiating individuals with schizophrenia (n = 50) and individuals with traumatic brain injury (n = 53) from healthy adults. A multiple regression analysis indicated that age, education and sex predicted performance. Regression-based norms are also provided. Taken together, these data provide preliminary support for the reliability and construct validity of the GVLT.

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