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Social Media-Based Health Management Systems and Sustained Health Engagement: TPB Perspective

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  • Dongxiao Gu

    (The School of Management, Hefei University of Technology, Hefei 230009, China
    The School of Informatics, Computing and Engineering, Bloomington, IN 47405-3907, USA)

  • Jingjing Guo

    (The School of Management, Hefei University of Technology, Hefei 230009, China)

  • Changyong Liang

    (The School of Management, Hefei University of Technology, Hefei 230009, China)

  • Wenxing Lu

    (The School of Management, Hefei University of Technology, Hefei 230009, China)

  • Shuping Zhao

    (The School of Management, Hefei University of Technology, Hefei 230009, China)

  • Bing Liu

    (China Academy of Social Management & School of Sociology, Beijing Normal University, Beijing 100000, China)

  • Tianyue Long

    (The School of Management, Hefei University of Technology, Hefei 230009, China)

Abstract

Background: With the popularity of mobile Internet and social networks, an increasing number of social media-based health management systems (SocialHMS) have emerged in recent years. These social media-based systems have been widely used in registration, payment, decision-making, chronic diseases management, health information and medical expenses inquiry, etc., and they greatly facilitate the convenience for people to obtain health services. Objective: This study aimed to investigate the factors influencing sustained health engagement of SocialHMS by combining the theory of planned behavior (TPB) with the big-five theory and the trust theory. Method: We completed an empirical analysis based on the 494 pieces of data collected from Anhui Medical University first affiliated hospital (AMU) in East China through structural equation modeling and SmartPLS (statistical analysis software). Results: Openness to new experience has a significantly positive influence on attitude (path coefficient = 0.671, t = 24.0571, R 2 = 0.451), perceived behavioral control (path coefficient = 0.752, t = 32.2893, R 2 = 0.565), and perceived risk (path coefficient = 0.651, t = 18.5940, R 2 = 0.424), respectively. Attitude, perceived behavioral control, subjective norms, and trust have a significantly positive influence on sustained health engagement (path coefficients = 0.206, 0.305, 0.197, 0.183 respectively, t = 3.6684, 4.9158, 4.3414, and 3.3715, respectively). The explained variance of the above factors to the sustained health engagement of SocialHMS is 60.7% ( R 2 = 0.607). Perceived risk has a significantly negative influence on trust (path coefficient = 0.825, t = 46.9598, R 2 = 0.681). Conclusions: Attitude, perceived behavioral control, subjective norm, and trust are the determinants that affect sustained health engagement. The users’ personality trait of openness to new experience and perceived risk were also found to be important factors for sustained health engagement. For hospital managers, there is the possibility to take appropriate measures based on users’ personality to further enhance the implementation and utilization of SocialHMS. As for system suppliers, they can provide the optimal design for SocialHMS so as to meet users’ needs.

Suggested Citation

  • Dongxiao Gu & Jingjing Guo & Changyong Liang & Wenxing Lu & Shuping Zhao & Bing Liu & Tianyue Long, 2019. "Social Media-Based Health Management Systems and Sustained Health Engagement: TPB Perspective," IJERPH, MDPI, vol. 16(9), pages 1-15, April.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:9:p:1495-:d:226438
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    References listed on IDEAS

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    1. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    2. Chechen Liao & Hong-Nan Lin & Yu-Ping Liu, 2010. "Predicting the Use of Pirated Software: A Contingency Model Integrating Perceived Risk with the Theory of Planned Behavior," Journal of Business Ethics, Springer, vol. 91(2), pages 237-252, January.
    3. Aoife De Brún & Eilish McAuliffe, 2018. "Social Network Analysis as a Methodological Approach to Explore Health Systems: A Case Study Exploring Support among Senior Managers/Executives in a Hospital Network," IJERPH, MDPI, vol. 15(3), pages 1-11, March.
    4. Datis Khajeheian & Amir Mohammad Colabi & Nordiana Binti Ahmad Kharman Shah & Che Wan Jasimah Bt Wan Mohamed Radzi & Hashem Salarzadeh Jenatabadi, 2018. "Effect of Social Media on Child Obesity: Application of Structural Equation Modeling with the Taguchi Method," IJERPH, MDPI, vol. 15(7), pages 1-22, June.
    5. Archana Tyagi & Ragini Tyagi, 2012. "Social Media: Opportunities and Challenges for Human Resource Management," International Journal of Knowledge-Based Organizations (IJKBO), IGI Global, vol. 2(2), pages 54-67, April.
    6. Fraedrich, John Paul & Ferrell, O. C., 1992. "The impact of perceived risk and moral philosophy type on ethical decision making in business organizations," Journal of Business Research, Elsevier, vol. 24(4), pages 283-295, June.
    7. Pilar Marqués-Sánchez & María F. Muñoz-Doyague & Yolanda V. Martínez & Martin Everett & Nestor Serrano-Fuentes & Peter Van Bogaert & Ivaylo Vassilev & David Reeves, 2018. "The Importance of External Contacts in Job Performance: A Study in Healthcare Organizations Using Social Network Analysis," IJERPH, MDPI, vol. 15(7), pages 1-17, June.
    8. Bent Egberg Mikkelsen & Paul Bloch & Helene Christine Reinbach & Tine Buch-Andersen & Lise Lawaetz Winkler & Ulla Toft & Charlotte Glümer & Bjarne Bruun Jensen & Jens Aagaard-Hansen, 2018. "Project SoL—A Community-Based, Multi-Component Health Promotion Intervention to Improve Healthy Eating and Physical Activity Practices among Danish Families with Young Children Part 2: Evaluation," IJERPH, MDPI, vol. 15(7), pages 1-15, July.
    9. Viswanath Venkatesh & Fred D. Davis, 2000. "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies," Management Science, INFORMS, vol. 46(2), pages 186-204, February.
    10. Haiyan Wu & Shan Wu & Haibo Wu & Qiming Xia & Ningxiu Li, 2017. "Living Arrangements and Health-Related Quality of Life in Chinese Adolescents Who Migrate from Rural to Urban Schools: Mediating Effect of Social Support," IJERPH, MDPI, vol. 14(10), pages 1-10, October.
    11. Davis, Donald D. & Bjornberg, Nathan H., 2015. "Flourishing in the Workplace Through Meditation and Mindfulness," Industrial and Organizational Psychology, Cambridge University Press, vol. 8(4), pages 667-674, December.
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