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Published on: September 20, 2018
Clinical Manifestations
Isabella Jaramillo1, Kathleen Hall1, Lourdes Anllo-Vento2
1Neurobehavioral Systems, Inc, Berkeley, CA, USA.
CCAB-Español offers accurate and reliable cognitive testing for Spanish speakers, mirroring the English version's performance. This computerized, in-home test ensures cultural and linguistic relevance for diverse U.S. Hispanic populations.
Area of Science:
- Neuroscience
- Psychometrics
- Health Informatics
Background:
- Hispanics are the largest U.S. minority group, with a significant portion speaking Spanish.
- Limited access to cognitive tests exists for U.S. Hispanics due to examiner shortages and a lack of culturally relevant tools.
- Standardized Spanish-language cognitive tests optimized for the U.S. Hispanic population are needed.
Purpose of the Study:
- To introduce and validate CCAB-Español, a computerized cognitive test adapted for the U.S. Hispanic population.
- To ensure the test maintains linguistic and cultural relevance while preserving psychometric properties.
- To address the need for accessible and reliable cognitive assessment tools for Spanish speakers.
Main Methods:
- CCAB-Español was developed as a computerized, in-home cognitive test mirroring the English CCAB.
- Stimuli were adapted by native Spanish speakers to ensure cultural and linguistic accuracy and psychometric equivalence.
- Automatic Speech Recognition (ASR) and scoring methods were refined to accommodate Spanish linguistic and dialectal variations.
Main Results:
- The normative sample included 108 diverse Spanish-speaking adults with varied backgrounds.
- CCAB-Español demonstrated strong test-retest reliability, comparable to the English version (e.g., story recall r = .83).
- The test showed high accuracy and reliability across 27 cognitive tasks.
Conclusions:
- CCAB-Español provides an accurate and reliable cognitive assessment for Spanish speakers.
- The test's psychometric properties are similar to the English CCAB, making it a valuable tool.
- Adaptations in stimuli, ASR, and scoring ensure fairness and accuracy for diverse Spanish-speaking populations.
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