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言语流畅性测试在不同语言中的常模数据的系统评价。

A Systematic Review of Normative Data for Verbal Fluency Test in Different Languages.

机构信息

Department of Experimental Psychology, School of Psychology, Complutense University of Madrid, Madrid, Spain.

Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, Madrid, Spain.

出版信息

Neuropsychol Rev. 2023 Dec;33(4):733-764. doi: 10.1007/s11065-022-09549-0. Epub 2022 Sep 13.

DOI:10.1007/s11065-022-09549-0
PMID:36098929
Abstract

Verbal fluency tests are easy and quick to use in neuropsychological assessments, so they have been counted among the most classical tools in this context. To date, several normative data for verbal fluency tests have been provided in different languages and countries. A systematic review was carried out with studies that provide normative data for verbal fluency tests. Studies were collected from Scopus, PubMed and Web of Science. 183 studies were retrieved from the database search, of which 73 finally met the inclusion criteria. An analysis of the risk of bias regarding samples selection/characterization and procedure/results reports is conducted for each article. Finally, a full description of the normative data characteristics, considering country and language, verbal fluency task characteristics (type of task) and sample characteristics (number of subjects, gender, age, education) is included. The current systematic review provides an overview and analysis of internationally published normative data that might help clinicians in their search for valid and useful norms on verbal fluency tasks, as well as updated information about qualitative aspects of the different options currently available.

摘要

在神经心理学评估中,言语流畅性测试易于使用且快速,因此它们被认为是该领域最经典的工具之一。迄今为止,已经在不同的语言和国家提供了几种言语流畅性测试的常模数据。本文进行了一项系统综述,其中包括提供言语流畅性测试常模数据的研究。研究从 Scopus、PubMed 和 Web of Science 中收集。从数据库搜索中检索到 183 项研究,其中最终有 73 项符合纳入标准。对每篇文章的样本选择/特征和程序/结果报告的偏倚风险进行分析。最后,包括了对常模数据特征(考虑国家和语言)、言语流畅性任务特征(任务类型)和样本特征(受试者数量、性别、年龄、教育)的全面描述。目前的系统综述提供了对国际发表的常模数据的概述和分析,这可能有助于临床医生寻找言语流畅性任务的有效和有用的常模,以及关于当前可用的不同选项的定性方面的最新信息。

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