认知功能预测后得性脑损伤患者就业的系统回顾和meta分析

Moritoshi Kitakami, J. Yaeda
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引用次数: 1

摘要

背景:日本目前只有20%的医院为获得性脑损伤(ABI)患者提供工作支持服务。从2018年4月开始,日本的新雇佣配额制规定,私营企业必须聘用精神障碍患者,因此预计ABI患者的数量将会增加。这种社会背景会鼓励医务人员更多地依靠神经心理评估测试分数来了解那些需要职业支持的患者从医院过渡到工作的认知能力。目的:阐明韦氏成人智力量表中预测ABI个体工作能力的子类别。方法:通过系统回顾和荟萃分析来确定与工作能力相关的特定认知功能。我们分析了MEDLINE、CINAHL、ERIC、CiNii和ICHUSHI数据库中符合研究纳入标准的四篇原创文章。结果:语言测试中有“词汇”、“数字跨度”、“算术”和“相似度”四个任务,而表现测试中有“块设计”和“编码”两个任务是工作能力的预测变量。结论:评估ABI个体的“工作记忆”、“持续注意力”、“抽象思维”、“词汇和表达”、“时间序列处理”等认知功能能更有效地预测工作能力。
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A Systematic Review and Meta-Analysis of Cognitive Functions Predicting Employment of Individuals with Acquired Brain Injury
: Background: Only 20% of the hospitals in Japan currently provide work support services for patients with acquired brain injury (ABI). Since the new employment quota system in Japan requires private companies to hire individuals with psychiatric disabilities as of April 2018, the number of employees with ABI is expected to increase. This social background would encourage medical staff to rely more on neuropsychological assessment test scores to under-stand the cognitive abilities of those patients who need vocational support to transition from hospital to work. Purpose: The of the study was to clarify the subcategories of the Wechsler Adult Intelligence Scale that would predict the work ability of individuals with ABI. Methodology: A systematic review and meta-analysis were conducted to identify specific cognitive functions related to work ability. Four original articles from MEDLINE, CINAHL, ERIC, CiNii, and the ICHUSHI database that met study inclusion criteria were analyzed. Results: Results showed that there were four tasks under the verbal test—“vocabulary,” “digit span,” “arithmetic,” and “similarities”—and two tasks under the performance test—“block design” and “coding”—that were predictive variables of work ability. Conclusion: Assessing cognitive functions of individuals with ABI, such as “working memory,” “continuous atten-tion,” “abstract thinking,” “vocabulary and expression,” and “time series processing,” could more effectively predict work ability.
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