| Project/Area Number |
17K18300
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Special needs education
Clinical psychology
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| Research Institution | Fukuoka Institute of Technology |
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Principal Investigator |
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| Project Period (FY) |
2017-04-01 – 2020-03-31
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| Project Status |
Completed (Fiscal Year 2019)
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| Budget Amount *help |
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2019: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2018: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2017: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
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| Keywords | 学生支援 / スクリーニング / UPI / 臨床心理学 / 特別支援 / テキストマイニング |
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| Outline of Final Research Achievements |
The purpose of this study was to develop a screening system for the early detection of students in need of support and to build an information sharing structure for practitioners to promote students’ adaption to university life.
In this study, the scores on 60 items of the University Personality Inventory (UPI), a measure of students’ mental health, were used to build a neural network (NN) that focused on accurately predicting maladaptive students from UPI data, and we were able to create a maladaptive risk prediction model. Furthermore, an information sharing structure using this predictive model was examined among clinical psychologists in consideration of the methods of information sharing and their risks.
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| Academic Significance and Societal Importance of the Research Achievements |
本研究の結果から，高等教育機関に常勤する公認心理師や臨床心理士といった専門家でなくても，学生情報の共有から学生の潜在的なニーズを早期に発見しやすくなるとが期待できる。本研究の意義は，①学生は，不適応状態になる前に必要な支援を得やすくなること，②実務者間で学生情報が共有しやすくなるため，現場に勤める臨床心理士の負担が軽減できること，③データから入学時の健康度と大学適応との関係が明確になることが挙げられる。
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