JOURNAL ARTICLE
Developing a Culturally Competent Neuropsychological Battery for Diagnosis of Dementia in Arabic-Speaking Patients in the United States.
Published In: Archives of Clinical Neuropsychology, 2023, v. 38, n. 3. P. 433 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Stinson, Jennifer M; Armendariz, Victoria; Hegazy, Mohamed Ibrahim Raslan; Strutt, Adriana M; McCauley, Stephen R; York, Michele K 3 of 3
Abstract
This article focuses on the development and review of a culturally and linguistically appropriate neuropsychological test battery for Arabic-speaking older adults in the United States, aimed at improving dementia diagnosis and cognitive assessment. It highlights the linguistic diversity of Arabic dialects, sociodemographic variations across Arab countries, and the importance of culturally informed practices given the growing Arab American population and limited availability of Arabic-speaking neuropsychologists. The battery assembled by the Baylor College of Medicine ECCOS Clinic (Embracing Cultural Competence in Outpatient Settings) includes core and supplemental measures with normative data tailored to specific Arabic dialects and cultural contexts, alongside recommendations for working with medical interpreters. The article emphasizes the need for clinicians to consider acculturation, education, and dialectal differences when selecting tests and interpreting results, and calls for further research to expand normative data across underrepresented Arabic-speaking populations.
Additional Information
- Source:Archives of Clinical Neuropsychology. 2023/05, Vol. 38, Issue 3, p433
- Document Type:Article
- Subject Area:Sociology
- Publication Date:2023
- ISSN:0887-6177
- DOI:10.1093/arclin/acad017
- Accession Number:163336233
- Copyright Statement:Copyright of Archives of Clinical Neuropsychology is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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