Investigation of Influential Factors of Predicting Individuals' Use and Non-use of Fitness and Diet Apps on Smartphones: Application of the Machine Learning Algorithm (XGBoost)
Keywords: FITNESS AND DIET APPS; MACHINE LEARNING ALGORITHM; SOCIAL INFLUENCE; XGBOOST; mHEALTH
Document Type: Research Article
Affiliations: 1: Jaehee Cho, Associate Professor, School of Media, Arts & Science, Sogang University, Seoul, South Korea;, Email: [email protected] 2: Sehwan Kim, Associate Professor, Department of Biomedical Engineering, Dankook University, Cheonan, South Korea 3: Gwangjin Jeong, MA student, Department of Biomedical Engineering, Dankook University, Cheonan, South Korea 4: Chonghye Kim, Doctoral student, School of Mass Communication, Sogang University, Seoul, South Korea 5: Ja-Kyoung Seo, MA student, School of Mass Communication, Sogang University, Seoul, South Korea
Publication date: 01 January 2021
The American Journal of Health Behavior seeks to improve the quality of life through multidisciplinary health efforts in fostering a better understanding of the multidimensional nature of both individuals and social systems as they relate to health behaviors.
The Journal aims to provide a comprehensive understanding of the impact of personal attributes, personality characteristics, behavior patterns, social structure, and processes on health maintenance, health restoration, and health improvement; to disseminate knowledge of holistic, multidisciplinary approaches to designing and implementing effective health programs; and to showcase health behavior analysis skills that have been proven to affect health improvement and recovery.
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