| Project/Area Number |
25861616
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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 |
Ophthalmology
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| Research Institution | The University of Tokyo |
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Principal Investigator |
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| Research Collaborator |
ASAOKA Ryo
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| Project Period (FY) |
2013-04-01 – 2015-03-31
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| Project Status |
Completed (Fiscal Year 2014)
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| Budget Amount *help |
¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000)
Fiscal Year 2014: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2013: ¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000)
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| Keywords | Quality of life / 緑内障 / Quality of Visual Life / Random Forest / Rasch model / Item bank / CAT |
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| Outline of Final Research Achievements |
The the comprehensive investigation about the Quality of Visual Life (QoVL) of glaucoma patients was performed in the current study.
First, we developed a novel system to predict QoVL from the visual field (VF) sensitivity and visual acuity (VA) simultaneously, using a machine learning method of the ‘Random Forest’. As a result, it was suggested that the accurate prediction can be achieved using novel system. In addition, we have validated the ‘Sumi Questionnaire’in estimating the QoVL, using the item response theory; more specifically the Rasch analysis. Consequently, we found that the‘Sumi Questionnaire’ has sufficiently constructive psychometric properties. Moreover, it was confirmed that it is useful to use the Rasch analysis than the classical test theory when interpreting the results of the ‘Sumi Questionnaire’, because the Rasch derived score showed intimate correlation with VF.
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