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1.
Digit Health ; 8: 20552076221089095, 2022.
Article in English | MEDLINE | ID: mdl-35371530

ABSTRACT

Objective: The increased use of smartphones has led to several problems, including excessive smartphone use and the decreased self-ability to control smartphone use. To prevent these problems, the MindsCare app was developed as a method of self-management and intervention based on an evaluation of smartphone usage. We designed the MindsCare app to manage smartphone usage and prevent problematic smartphone use by providing personalized interventions. Methods: We recruited 342 Korean participants over the age of 20 and asked them to use MindsCare for 13 weeks. Subsequently, we evaluated the changes in average smartphone usage time and the usability of the app. We designed a usability evaluation questionnaire based on the Technology Acceptance Model and conducted factor and reliability analyses on the participants' responses. In the eighth week of the study, participants responded to a survey on the usability of the app. We ultimately collected data from 190 participants. Results: The average score for the usability of the system was 3.61 on a five-point Likert scale, and approximately 58% of the participants responded positively to the evaluation items. In addition, our analysis of MindsCare data revealed a significant reduction in average smartphone use time in the eighth week compared to the baseline (t = 3.47, p = 0.001). Structural equation model analysis revealed that effort expectancy and performance expectancy had a positive relation with behavior intention for the app. Conclusions: Through this study, we confirmed the MindsCare app's smartphone usage time reduction effect and proved its good usability. As a result, MindsCare may contribute to achieving users' goals of reducing problematic smartphone use.

2.
Stud Health Technol Inform ; 264: 1506-1507, 2019 Aug 21.
Article in English | MEDLINE | ID: mdl-31438204

ABSTRACT

In this study, we built a multi-center integrated database platform of localized prostate cancer and developed biochemical recurrence (BCR) prediction system with Gradient Boosted Regression model using Korean Prostate Cancer Registry (KPCR) database. This platform will facilitate clinical management of patients with prostate cancer, and it will also help develop appropriate treatment of prostate cancer.


Subject(s)
Prostatic Neoplasms , Databases, Factual , Humans , Male , Neoplasm Recurrence, Local , Prostate-Specific Antigen , Prostatectomy
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