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Factors Influencing Use of Smartphone Applications for Healthcare Self-Management: An Extended Technology Acceptance Model

  • Jo, Heui-Sug (Department of Health management & Policy School of Medicine Kangwon National University) ;
  • Jung, Su-Mi (Department of Health management & Policy School of Medicine Kangwon National University)
  • 투고 : 2014.07.30
  • 심사 : 2014.09.15
  • 발행 : 2014.10.01

초록

Objectives: The self-management of chronic diseases is currently receiving much attention. This study applied an extended technology acceptance model (ETAM) to analyze the factors influencing acceptance of a healthcare smartphone application. Methods: Three hundred people living in Seoul and Gyeonggi who used smartphones were quota sampled. A telephone survey was conducted using a structured questionnaire based on ETAM. A path analysis was carried out using the AMOS 17.0 program, and the model was verified. Results: The analysis revealed significant factors of perceived usefulness (.374, p < .001), enjoyment (.210, p < .001), subjective norms (.168, p < .001), perceived costs (.146, p < .001), and innovativeness (.138, p < .001). Cost directly influenced intention to use health applications; self-efficacy and perceived ease of use indirectly affected intention through innovation and perceived usefulness. Conclusions: This study helped to identify the main factors that influence usage intention of smartphone applications. These findings could contribute to promoting the self-management of chronic disease through future health applications using smartphones.

키워드

참고문헌

  1. Ahtola, O. T. (1984). Price as a 'give' component in an exchange theoretic multicomponent model. Advances in Consumer Research, 11, 623-636.
  2. Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs, NJ: Prentice-Hall.
  3. Bae, E. S., Cheon, S. M., Kim, J. W., & Kang, C. W. (2013). A prediction model for depression in patients with parkinson's disease. Korean Journal of Health Education and Promotion, 30(5), 139-151. https://doi.org/10.14367/kjhep.2013.30.5.139
  4. Compeau, D., Higgins, C. A., & Huff, S. (1999). Social cognitive theory and individual reactions to computing technology: a longitudinal study. Management Information Systems Quarterly, 23(2), 145-158. https://doi.org/10.2307/249749
  5. Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems: theory and results. (Doctoral), Massachusetts Institute of Technology, USA.
  6. Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace1. Journal of Applied Social Psychology, 22(14), 1111-1132. https://doi.org/10.1111/j.1559-1816.1992.tb00945.x
  7. Heo, C. Y., & Yu, B. Y. (2013). Domestic and international trends telemedicine using smartphone applications. Journal of Telecommunications Technology Association, 145(1), 38-43.
  8. Kim, G. J. (2009). A study on acceptance factor of digital multimedia broadcasting. Korean Journal of Journalism & Communication Studies, 53(3), 296-323.
  9. Kim, M. H., & Lee, D. H. (2011). Factors related to healthpromoting Behaviors and chronic diseases in the elderly. Korean Journal of Health Education and Promotion, 28(2), 99-107.
  10. Lee, H. J., Lee, J. J., Hwang, T. Y., & Kam, S. (2012). Development and evaluation of a community staged education program for the cardiocerebrovascular disease high-risk patients. Journal of Agricultural Medicine and Community Health, 37(3), 167-180. https://doi.org/10.5393/JAMCH.2012.37.3.167
  11. Lee, J. O., Whang, J., Kang, S., & Lee, S. (2006). Extended TAM for accepting mobile devices including functional attributes: the case of cellular phone. Journal of Information Technology Applications and Management, 13(1), 39-66.
  12. Lee. J., Yim, J., Im, J. S., Oh, D. K., & Han, J. O. (2013). Effects of chronic disease education for hypertension, diabetes patients's knowledge. Korean Journal of Health Education and Promotion, 30(5), 79-90. https://doi.org/10.14367/kjhep.2013.30.5.079
  13. Lee. Y. H., Kim, J. H., Kim, J. K., Min, K. P., Jung, E. Y., & Park, D. K. (2010). Smart phone based personalized menu management system for diabetes patient. The Korea Contents Association, 10(12), 1-9. https://doi.org/10.5392/JKCA.2010.10.12.001
  14. Midgley, D. F., & Dowling, G. R. (1978). Innovativeness: the concept and its measurement. Journal of Consumer Research, 4(4), 229-242. https://doi.org/10.1086/208701
  15. Na, E. Y. (2002). Gender differences in new media use and values mobile phones and internet. Korean Journal of Broadcasting, 16(1), 77-115.
  16. Segars, A. H., & Grover, V. (1993). Re-examining perceived ease of use and usefulness. Management Information Systems Quarterly, 17(4), 517-525. https://doi.org/10.2307/249590
  17. Song, T. (2005). The analysis of influential factors for the acceptability of the health information website. Health & Social Welfare Review, 25, 143-82.
  18. Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: four longitudinal field studies. Management Science, 46(2), 186-204. https://doi.org/10.1287/mnsc.46.2.186.11926
  19. Wang, B. R., Park, J. Y., & Choi, I. Y. (2011). Influencing factors for the adoption of smartphone healthcare application. The Journal of the Korea Contents Association, 11(10), 396-404. https://doi.org/10.5392/JKCA.2011.11.10.396
  20. World Health Organization. (2012). World health statistics 2012. Switzerland: WHO Press.
  21. Zeithaml, V. A. (1988). Consumer perceptions of price, quality, and value: a means-end model and synthesis of evidence. The Journal of Marketing, 52(1), 2-22. https://doi.org/10.2307/1251446

피인용 문헌

  1. The Relationship Between Acceptance Intention Toward a Smartphone Healthcare Application and Health-Promoting Behaviors Among Nursing Students pp.1538-2931, 2018, https://doi.org/10.1097/CIN.0000000000000433
  2. Nursing Students’ Acceptance Intention of a Smart Device, Information Literacy, and Problem-Solving Confidence vol.9, pp.9, 2021, https://doi.org/10.3390/healthcare9091157