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Measurement precision across cognitive domains in the Alzheimer's Disease Neuroimaging Initiative (ADNI) data set.
Crane, Paul K; Choi, Seo-Eun; Lee, Michael; Scollard, Phoebe; Sanders, R Elizabeth; Klinedinst, Brandon; Nakano, Connie; Trittschuh, Emily H; Mez, Jesse; Saykin, Andrew J; Gibbons, Laura E; Wang, Chun; Mungas, Dan; Zhu, Ruoyi; Foldi, Nancy S; Lamar, Melissa; Jutten, Roos; Sikkes, Sietske A M; Grandoit, Evan; Rabin, Laura A; Jones, Richard N; Tommet, Doug; Mukherjee, Shubhabrata.
Afiliación
  • Crane PK; Department of Medicine, University of Washington.
  • Choi SE; Department of Medicine, University of Washington.
  • Lee M; Department of Medicine, University of Washington.
  • Scollard P; Department of Medicine, University of Washington.
  • Sanders RE; Department of Medicine, University of Washington.
  • Klinedinst B; Department of Medicine, University of Washington.
  • Nakano C; Department of Medicine, University of Washington.
  • Trittschuh EH; Department of Psychiatry and Behavioral Sciences, University of Washington.
  • Mez J; Department of Neurology, Boston University.
  • Saykin AJ; Department of Radiology and Imaging Sciences, Indiana University.
  • Gibbons LE; Department of Medicine, University of Washington.
  • Wang C; College of Education, University of Washington.
  • Mungas D; Department of Neurology, University of California, Davis.
  • Zhu R; College of Education, University of Washington.
  • Foldi NS; Department of Psychology, Queens College.
  • Lamar M; Department of Psychiatry and Behavioral Sciences, Rush University Medical Center.
  • Jutten R; Department of Neurology, Massachusetts General Hospital, Harvard Medical School.
  • Sikkes SAM; Alzheimer Center Amsterdam, Neurology, Amsterdam University Medical Center, Vrije Universiteit Medical Center.
  • Grandoit E; Department of Psychology, Northwestern University.
  • Rabin LA; Department of Psychology, Brooklyn College, City University of New York.
  • Jones RN; Department of Psychiatry, Brown University.
  • Tommet D; Department of Psychiatry, Brown University.
  • Mukherjee S; Department of Medicine, University of Washington.
Neuropsychology ; 37(4): 373-382, 2023 May.
Article en En | MEDLINE | ID: mdl-37276134
OBJECTIVE: To demonstrate measurement precision of cognitive domains in the Alzheimer's Disease Neuroimaging Initiative (ADNI) data set. METHOD: Participants with normal cognition (NC), mild cognitive impairment (MCI), and Alzheimer's disease (AD) were included from all ADNI waves. We used data from each person's last study visit to calibrate scores for memory, executive function, language, and visuospatial functioning. We extracted item information functions for each domain and used these to calculate standard errors of measurement. We derived scores for each domain for each diagnostic group and plotted standard errors of measurement for the observed range of scores. RESULTS: Across all waves, there were 961 people with NC, 825 people with MCI, and 694 people with AD at their most recent study visit (data pulled February 25, 2019). Across ADNI's battery there were 34 memory items, 18 executive function items, 20 language items, and seven visuospatial items. Scores for each domain were highest on average for people with NC, intermediate for people with MCI, and lowest for people with AD, with most scores across all groups in the range of -1 to +1. Standard error of measurement in the range from -1 to +1 was highest for memory, intermediate for language and executive functioning, and lowest for visuospatial. CONCLUSION: Modern psychometric approaches provide tools to help understand measurement precision of the scales used in studies. In ADNI, there are important differences in measurement precision across cognitive domains. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Enfermedad de Alzheimer / Disfunción Cognitiva Aspecto: Patient_preference Límite: Humans Idioma: En Revista: Neuropsychology Asunto de la revista: NEUROLOGIA / PSICOLOGIA Año: 2023 Tipo del documento: Article Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Enfermedad de Alzheimer / Disfunción Cognitiva Aspecto: Patient_preference Límite: Humans Idioma: En Revista: Neuropsychology Asunto de la revista: NEUROLOGIA / PSICOLOGIA Año: 2023 Tipo del documento: Article Pais de publicación: Estados Unidos