Galuh Octavia Chrisdianti, P. W. Handayani, F. Azzahro, S. Yudhoatmojo
{"title":"Users’ Intention to Use Mobile Health Applications for Personal Health Tracking","authors":"Galuh Octavia Chrisdianti, P. W. Handayani, F. Azzahro, S. Yudhoatmojo","doi":"10.21609/jsi.v19i1.1196","DOIUrl":null,"url":null,"abstract":"This study aimed to analyze factors influencing the intention to use mobile health applications for personal health tracking (PHT). The respondents were 516 individuals who had used a PHT application, such as Samsung Health, iOS Health, or MiFit. Data processing was done via using partial least squares–structural equation modeling (PLS-SEM). This study uncovered factors that can affect intention to use PHT applications, including perceived usefulness, social influence, facilitating conditions, hedonic motivation, habits, performance risk, and self-health awareness. It was found that perceived ease of use and self-reported health condition do not affect the intention to use PHT applications. This study can provide guidance on PHT application service providers for ensuring data accuracy, increasing user satisfaction when using the applications, and preventing privacy violation.","PeriodicalId":32357,"journal":{"name":"Jurnal Sistem Informasi","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jurnal Sistem Informasi","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21609/jsi.v19i1.1196","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This study aimed to analyze factors influencing the intention to use mobile health applications for personal health tracking (PHT). The respondents were 516 individuals who had used a PHT application, such as Samsung Health, iOS Health, or MiFit. Data processing was done via using partial least squares–structural equation modeling (PLS-SEM). This study uncovered factors that can affect intention to use PHT applications, including perceived usefulness, social influence, facilitating conditions, hedonic motivation, habits, performance risk, and self-health awareness. It was found that perceived ease of use and self-reported health condition do not affect the intention to use PHT applications. This study can provide guidance on PHT application service providers for ensuring data accuracy, increasing user satisfaction when using the applications, and preventing privacy violation.