Text analysis of problems perceived by employment support workers of Japan during vocational assessment


Author: Kazuaki Maebara
Page Range: 43-53
Published in: International Journal on Disability and Human Development, Volume 23 Issue 1
ISSN: 2191-1231

Table of Contents


Vocational assessments are an important tool for providing the appropriate support for individuals with disabilities. However, conducting these assessments is not easy, because individual clients with disabilities are not the same, and supporters need to have extensive specialized knowledge and skills. Considering the current situation in Japan, it is necessary to clarify the reasons that prevent vocational assessment systems from being implemented, and linking this to subsequent research on the development of support tools and strategies is crucial. This study aimed to identify the challenges perceived by work assessment system supporters and perspectives to improve the execution of vocational assessments in Japan. Survey forms were mailed to all 336 Employment and Livelihood Support Centers for Persons with Disabilities in Japan. They were asked to provide an open-ended response regarding their perceptions of the problems in conducting assessments as it relates to them, their organization, and their community. Free-text descriptions were analyzed by text mining. Findings revealed that the participants faced the following problems: issues in performing assessments, lack of knowledge and skills, and need for collaboration (concerning themselves); inadequate organizational structure, lack of human resources, need for human resource development, and lack of time (concerning their organization); and lack of collaboration, clarification of role division, and formation of common understanding (concerning the community). Providing workplace supervision may enable information sharing with multiple people and help improve the skills and reduce the workload of the employment support workers.

Keywords: Assessment, Vocational Rehabilitation, Work Support, Qualitative Analysis, Text Mining, Persons with Disabilities

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