Factors affecting acceptance of smartphone application for management of obesity

Healthcare Informatics Research

Volumn 21, Issue 2, 2015, Pages 74-82

  Jeon, Eunjoo ^a   Park, Hyeoun Ae ^a  

^a Seoul National University   (South Korea)

Author keywords

Mobile health units; Obesity; Statistical factor analysis; Telemedicine; Weight loss

Indexed keywords

EID: 84928966874     PISSN: 20933681     EISSN: 2093369X     Source Type: Journal    
DOI: 10.4258/hir.2015.21.2.74     Document Type: Article

References (30)

1. Patrick K, Griswold WG, Raab F, Intille SS. Health and the mobile phone. Am J Prev Med 2008;35(2):177-81.
2. Haux R. Health information systems-past, present, future. Int J Med Inform 2006;75(3-4):268-81.
3. Berg M. Patient care information systems and health care work: a sociotechnical approach. Int J Med Inform 1999;55(2):87-101.
4. Short D, Frischer M, Bashford J. Barriers to the adoption of computerised decision support systems in general practice consultations: a qualitative study of GPs' perspectives. Int J Med Inform 2004;73(4):357-62.
5. Johnson JD, Meyer M, Woodworth M, Ethington C, Stengle W. Information technologies within the cancer information service: factors related to innovation adoption. Prev Med 1998;27(5 Pt 2):S71-83.
6. Wu JH, Wang SC, Lin LM. Mobile computing acceptance factors in the healthcare industry: a structural equation model. Int J Med Inform 2007;76(1):66-77.
7. Zhang H, Cocosila M, Archer N. Factors of adoption of mobile information technology by homecare nurses: a technology acceptance model 2 approach. Comput Inform Nurs 2010;28(1):49-56.
8. Lee J, Rho MJ. Perception of influencing factors on acceptance of mobile health monitoring service: a comparison between users and non-users. Healthc Inform Res 2013;19(3):167-76.
9. Korea Ministry of Health and Welfare. Korea National Health and Nutrition Examination. Seoul: Korea Ministry of Health and Welfare; 2011.
10. Goessens BM, Visseren FL, de Nooijer J, van den Borne HW, Algra A, Wierdsma J, et al. A pilot-study to identify the feasibility of an Internet-based coaching programme for changing the vascular risk profile of high-risk patients. Patient Educ Couns 2008;73(1):67-72.
11. Jeon HO, Kim O. The effects of an internet based coaching program for obesity management in hypertensive patients. Korean J Adult Nurs 2011;23(2):146-59.
12. Breton ER, Fuemmeler BF, Abroms LC. Weight loss-there is an app for that! But does it adhere to evidenceinformed practices? Transl Behav Med 2011;1(4):523-9.
13. Jeon E, Park HA, Min YH, Kim HY. Analysis of the information quality of Korean obesity-management smartphone applications. Healthc Inform Res 2014;20(1):23-9.
14. Research2guidance. Mobile health market report 2011-2016. Berlin: Research2guidance; 2012.
15. Jeon E, Park HA. Development of a smartphone application for clinical-guideline-based obesity management. Healthc Inform Res 2015;21(1):10-20.
16. Venkatesh V, Davis FD. A theoretical extension of the technology acceptance model: four longitudinal field studies. Manag Sci 2000;46(2):186-204.
17. Rogers EM. Diffusion of innovations. 5th ed. New York (NY): Simon & Schuster Inc.; 2003.
18. Compeau DR, Higgins CA. Computer self-efficacy: development of a measure and initial test. MIS Q 1995; 19(2):189-211.
19. Igbaria M, Zinatelli N, Cragg P, Cavaye AL. Personal computing acceptance factors in small firms: a structural equation model. MIS Q 1997;21(3):279-305.
20. Davis FD. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q 1989;13(3):319-40.
21. Van Slyke C, Lou H, Day J. The impact of perceived innovation characteristics on intention to use groupware. Inf Resour Manag J 2002;15(1):1-12.
22. Jelekainen P. GSM-PKI solution enabling secure mobile communications. Int J Med Inform 2004;73(3):317-20.
23. Kim K. AMOS 18.0 structural equation modeling analysis (Korean edition). Seoul, Korea: Hannarae Publishing; 2010.
24. Chau PY, Hu PJ. Investigating healthcare professionals’ decisions to accept telemedicine technology: an empirical test of competing theories. Inf Manag 2002;39(4):297-311.
25. Venkatesh V, Morris MG, Davis GB, Davis FD. User acceptance of information technology: toward a unified view. MIS Q 2003;27(3):425-78.
26. Chapman DW, Carter JF. Translation procedures for the cross cultural use of measurement instruments. Educ Eval Policy Anal 1979;1(3):71-6.
27. Hair Jr JF, Anderson RE, Tatham RL. Multivariate data analysis with readings. 2nd ed. New York (NY): Macmillan Publishing; 1986.
28. Ruder Finn Inc. mHealth report. New York (NY): Ruder Finn Inc.; 2012.
29. Hasan B. Delineating the effects of general and systemspecific computer self-efficacy beliefs on IS acceptance. Inf Manag 2006;43(5):565-71.
30. Kim J, Park HA. Development of a health information technology acceptance model using consumers' health behavior intention. J Med Internet Res 2012;14(5):e133.