JOURNAL ARTICLE

Developing a Culturally Competent Neuropsychological Assessment Battery for Farsi-speaking Patients with Suspected Dementia.

  • Published In: Archives of Clinical Neuropsychology, 2023, v. 38, n. 3. P. 472 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Henry, Samantha K; Talavari, Donna; York, Michele K; Stinson, Jennifer M; Strutt, Adriana M; McCauley, Stephen R 3 of 3

Abstract

This article focuses on the development of a comprehensive neuropsychological battery tailored for differential diagnosis of dementia in Farsi-speaking Iranian adults residing in the United States. Due to the scarcity of neuropsychological tests developed or normed specifically for Farsi speakers, the proposed battery combines core measures validated with Farsi-speaking populations and supplemental tests translated from English, acknowledging limitations in normative data and cultural applicability. The article also presents a case study illustrating the clinical application of this battery with the aid of a certified Farsi interpreter, highlighting challenges such as language barriers, cultural considerations, and the need for culturally competent assessment practices. The authors emphasize the urgent need for more validated neuropsychological tools and normative data for Farsi-speaking and bilingual Iranian Americans to improve diagnostic accuracy and care for this growing, underserved population.

Additional Information

  • Source:Archives of Clinical Neuropsychology. 2023/05, Vol. 38, Issue 3, p472
  • Document Type:Article
  • Subject Area:Language and Linguistics
  • Publication Date:2023
  • ISSN:0887-6177
  • DOI:10.1093/arclin/acac099
  • Accession Number:163336227
  • 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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