■语义言语流畅性(SVF)是额叶执行功能和获得语义记忆的广泛使用的量度。SVF评分指标包括生成的唯一单词数,坚持,入侵,语义簇大小和簇之间的切换,分数根据考试所用的语言而有所不同。在本文中,我们回顾了土耳其现有的规范数据,用于对土耳其语SVF数据进行评分的主要指标,和最常用的类别。
■我们使用Medline对同行评审论文进行了系统综述,EMBASE,PsycInfo,WebofScience,还有两个土耳其语数据库,TR-Dizin和Yok-Tez.包括的论文包含有关健康的以土耳其语为母语的成年人的SVF表现的数据,并报告了使用的类别。要求参与者选择其他类别的SVF版本被排除。我们提取人口统计数据并制成表格,组的描述,使用的度量,使用的类别,和规范数据的来源。评估研究报告结果的详细程度。
■检索了1400项研究。重复数据删除后,abstract,全文筛选,并将论文与其出版的版本合并,共纳入121项研究。114项研究使用了语义类别“动物”,其次是名字(N=14,12%)。所有研究都报告了字数。更复杂的措施很少见(坚持:N=12,10%,聚类和切换:N=5,4%)。七项规范研究中有四项只报告了字数,两个也测量了毅力,和一个报告类别违反和坚持。两项规范性研究以英文发表。
■缺乏具有更复杂指标的规范土耳其SVF数据,例如集群和切换,缺乏用英语出版的规范数据。鉴于土耳其侨民的规模,规范的SVF数据应包括单语和双语使用者。限制包括对关键英语和土耳其语数据库的限制。
UNASSIGNED: Semantic verbal fluency (SVF) is a widely used measure of frontal executive function and access to semantic memory. SVF scoring metrics include the number of unique words generated, perseverations, intrusions, semantic cluster size and switching between clusters, and scores vary depending on the language the test is administered in. In this paper, we review the existing normative data for Turkish, the main metrics used for scoring SVF data in Turkish, and the most frequently used categories.
UNASSIGNED: We conducted a systematic review of peer-reviewed papers using Medline, EMBASE, PsycInfo, Web of Science, and two Turkish databases, TR-Dizin and Yok-Tez. Included papers contained data on the SVF performance of healthy adult native speakers of Turkish, and reported the categories used. Versions of the SVF that required participants to alternate categories were excluded. We extracted and tabulated demographics, descriptions of groups, metrics used, categories used, and sources of normative data. Studies were assessed for level of detail in reporting findings.
UNASSIGNED: 1400 studies were retrieved. After deduplication, abstract, full text screening, and merging of theses with their published versions, 121 studies were included. 114 studies used the semantic category \"animal\", followed by first names (N = 14, 12%). All studies reported word count. More complex measures were rare (perseverations: N = 12, 10%, clustering and switching: N = 5, 4%). Four of seven normative studies reported only word count, two also measured perseverations, and one reported category violations and perseverations. Two normative studies were published in English.
UNASSIGNED: There is a lack of normative Turkish SVF data with more complex metrics, such as clustering and switching, and a lack of normative data published in English. Given the size of the Turkish diaspora, normative SVF data should include monolingual and bilingual speakers. Limitations include a restriction to key English and Turkish databases.