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失读症的神经心理学诊断与评估:一项混合方法研究。

Neuropsychological Diagnosis and Assessment of Alexia: A Mixed-Methods Study.

作者信息

Alduais Ahmed, Alarifi Hessah Saad, Alfadda Hind

机构信息

Department of Human Sciences (Psychology), University of Verona, 37129 Verona, Italy.

Department of Educational Administration, College of Education, King Saud University, Riyadh 11362, Saudi Arabia.

出版信息

Brain Sci. 2024 Jun 25;14(7):636. doi: 10.3390/brainsci14070636.

Abstract

The neuropsychological diagnosis and assessment of alexia remain formidable due to its multifaceted presentations and the intricate neural underpinnings involved. The current study employed a mixed-method design, incorporating cluster and thematic analyses, to illuminate the complexities of alexia assessment. We used the Web of Science and Scopus to retrieve articles spanning from 1985 to February 2024. Our selection was based on identified keywords in relation to the assessment and diagnosis of alexia. The analysis of 449 articles using CiteSpace (Version 6.3.R1) and VOSviewer (Version 1.6.19) software identified ten key clusters such as 'pure alexia' and 'posterior cortical atrophy', highlighting the breadth of research within this field. The thematic analysis of the most cited and recent studies led to eight essential categories. These categories were synthesized into a conceptual model that illustrates the interaction between neural, cognitive, and diagnostic aspects, in accordance with the International Classification of Functioning, Disability, and Health (ICFDH) framework. This model emphasizes the need for comprehensive diagnostic approaches extending beyond traditional reading assessments to include specific tasks like character identification, broader visual processing, and numerical tasks. Future diagnostic models should incorporate a diverse array of alexia types and support the creation of advanced assessment tools, ultimately improving clinical practice and research.

摘要

由于失读症的多方面表现以及所涉及的复杂神经基础,对其进行神经心理学诊断和评估仍然具有挑战性。本研究采用了混合方法设计,包括聚类分析和主题分析,以阐明失读症评估的复杂性。我们使用科学网和Scopus检索了1985年至2024年2月期间的文章。我们的选择基于与失读症评估和诊断相关的已确定关键词。使用CiteSpace(6.3.R1版)和VOSviewer(1.6.19版)软件对449篇文章进行的分析确定了十个关键聚类,如“纯失读症”和“后部皮质萎缩”,突出了该领域研究的广度。对被引用最多和最新研究的主题分析得出了八个基本类别。这些类别被综合成一个概念模型,该模型根据国际功能、残疾和健康分类(ICFDH)框架说明了神经、认知和诊断方面之间的相互作用。该模型强调需要采用全面的诊断方法,超越传统的阅读评估,纳入字符识别、更广泛的视觉处理和数字任务等特定任务。未来的诊断模型应纳入各种失读症类型,并支持创建先进的评估工具,最终改善临床实践和研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/825f/11274783/27502f80e3d5/brainsci-14-00636-g001.jpg

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