Mobile apps use for wellness and fitness and university students' subjective wellbeing

被引:11
作者
Aboelmaged, M. [1 ]
Ali, Imran [2 ]
Hashem, G. [3 ]
机构
[1] Univ Sharjah, Coll Business Adm, Sharjah, U Arab Emirates
[2] Cent Queensland Univ, Sch Business & Law, Operat & Innovat Management, Melbourne Campus, Rockhampton, Qld, Australia
[3] Helwan Univ, Management, Fac Commerce, Helwan, Egypt
关键词
mobile applications; subjective wellbeing; TRAM model; technology readiness; wellness and fitness; TECHNOLOGY READINESS; BEHAVIORAL INTENTIONS; ACCEPTANCE; HEALTH; ATTITUDES; ADOPTION;
D O I
10.1177/02666669211020498
中图分类号
G25 [图书馆学、图书馆事业]; G35 [情报学、情报工作];
学科分类号
1205 ; 120501 ;
摘要
Subjective wellbeing among mobile application users attracted researchers' interest in recent years due to its prevalent role in enhancing everyday life, particularly during the recent coronavirus pandemic (COVID-19). While previous work has primarily focused on users' intention to adopt mobile apps for wellness and fitness (MAWF) purposes, scarce attention has been paid to the post-adoption impact of these apps on users' subjective wellbeing. This study empirically integrates 'technology readiness' and 'technology acceptance' models (TRAM) to predict subjective wellbeing among MAWF users. It also critically assesses the strength of the mediating effects on the link between technology readiness and subjective wellbeing. Data analysis of 694 actual users of MAWF by means of SEM-PLS approach proves the robust power of the TRAM model in predicting subjective wellbeing. In addition to their mediating effects, technology acceptance constructs tend to be more influenced by positive dimensions (i.e., optimism and innovativeness) than that of negative dimensions (i.e., insecurity and discomfort) of technology readiness. This study is one of the first attempts to predict subjective wellbeing among actual users of MAWF. The study also delineates a broad spectrum of implications that enrich existing research and better inform decision makers in mobile health field.
引用
收藏
页码:672 / 687
页数:16
相关论文
共 85 条
[1]   Predicting e-readiness at firm-level: An analysis of technological, organizational and environmental (TOE) effects on e-maintenance readiness in manufacturing firms [J].
Aboelmaged, Mohamed Gamal .
INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT, 2014, 34 (05) :639-651
[2]  
Aguilar I., 2014, TEN551 EU EC SOC COM
[3]  
Akroush Mamoun N., 2020, International Journal of Web Based Communities, V16, P150
[4]   Understanding the determinants of mHealth apps adoption in Bangladesh: A SEM-Neural network approach [J].
Alam, Mohammad Zahedul ;
Hu, Wang ;
Kaium, Md Abdul ;
Hoque, Md Rakibul ;
Alam, Mirza Mohammad Didarul .
TECHNOLOGY IN SOCIETY, 2020, 61
[5]  
[Anonymous], P 4 INT C MOB TECHN
[6]   Determinant Factors of Public Acceptance of Stress Management Apps: Survey Study [J].
Apolinario-Hagen, Jennifer ;
Hennemann, Severin ;
Fritsche, Lara ;
Druege, Marie ;
Breil, Bernhard .
JMIR MENTAL HEALTH, 2019, 6 (11)
[7]  
Azjen I., 1980, Understanding Attitude and Predicting Social Behaviour
[8]   Crush the Crave: Development and Formative Evaluation of a Smartphone App for Smoking Cessation [J].
Baskerville, Neill B. ;
Struik, Laura L. ;
Dash, Darly .
JMIR MHEALTH AND UHEALTH, 2018, 6 (03)
[9]   Problematic Internet and mobile phone use and clinical symptoms in college students: The role of emotional intelligence [J].
Beranuy, Marta ;
Oberst, Ursula ;
Carbonell, Xavier ;
Chamarro, Ander .
COMPUTERS IN HUMAN BEHAVIOR, 2009, 25 (05) :1182-1187
[10]   Privacy and security issues in mobile health: Current research and future directions [J].
Bhuyan, Soumitra S. ;
Kim, Hyunmin ;
Isehunwa, Oluwaseyi O. ;
Kumar, Naveen ;
Bhatt, Jay ;
Wyant, David K. ;
Kedia, Satish ;
Chang, Cyril F. ;
Dasgupta, Dipankar .
HEALTH POLICY AND TECHNOLOGY, 2017, 6 (02) :188-191