1 |
Sin HS. The evolution of health and utilization inequalities over time. Health and Welfare Policy Forum 2009;149:26-35.
|
2 |
Choi GS, Kim YK. Analysis of prehospital care report for improving emergency service at prehospital phase. Korean J Emerg Med Ser 2007;11(3):163-74.
|
3 |
Park SS, Park JS. A study on the use realities and satisfaction with transport services in 119 emergency medical service system and private transport agent in some areas. Korean J Emerg Med Ser 2008;12(1):5-15.
|
4 |
Kang KH. Predictors of emergency medical transports use based on 2009 Korea health panel. J Korean Inst Fire Sci Eng 2014; 28(3):80-6.
|
5 |
Baek HS. Determinants of the demand for public ambulance calls in a metropolitan area. Korean J Emerg Med Ser 2008;12(3): 129-35.
|
6 |
Davis FD, Bagozzi RP, Warshaw PR. User use intention of computer technology: A comparison of two theoretical models. Manag Sci 1989;35:982-1003.
DOI
|
7 |
Venkatesh V, Davis FD. A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science 2000;46(2):186-205. http://dx.doi.org/10.1287/mnsc.46.2.186.11926
DOI
|
8 |
Karsh B, Holden RJ. The technology use intention model: Its past and its future in health care. J Biomed Inform 2000;43(1): 159-72.
DOI
|
9 |
Hu PJH, Chau PTK, Sheng ORL. Adoption of telemedicine technology by health care organizations: An exploratory study. Journal of Organizational Computing and Electronic Commerce 2002;12(3):197-22. http://dx.doi.org/10.1207/S15327744JOCE1203_01
DOI
|
10 |
Taylor S, Todd PA. Understanding information technology usage: A test of competing models. Inf Syst Res 1995;6(2):144-76. http://dx.doi.org/10.1287/isre.6.2.144
DOI
|
11 |
Wood W. Attitude change: Persuasion and social influence. Annu Rev Psychol 2000;51: 539-70. http://dx.doi.org/10.1146/annurev.psych.51.1.539
DOI
|
12 |
Lee WK, An Longitudinal analysis of changing beliefs on the use in IT educatee by elaboration likelihood model. Asia Pacific Journal of Information Systems 2008;18(3):147-65.
|
13 |
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. http://dx.doi.org/10.1016/j.ijmedinf.2006.06.006
DOI
|
14 |
Bhattacherjee A, Sanford C. Influence processes for information technology use intention: An elaboration likelihood model. Manag Inform Syst Q 2006;30:805-25. http://dx.doi.org/10.1016/j.ijmedinf.2006.06.006
DOI
|
15 |
Kim EH. Continuance intention of power- twitter from elaboration likelihood model perspectives. Unpublished master's thesis, Kyunghee University 2012, Seoul, Korea.
|
16 |
Sussman SW, Siegal WS. Informational in fluence in organizations: An integrated approach to knowledge adoption. Inf Syst Res 2003;14(1):47-65. http://dx.doi.org/10.1287/isre.14.1.47.14767
DOI
|
17 |
Kim KY, Kim YK, Lee KH, Yong SJ. Factors affecting the use of a realtime telemetry system in emergency medical services. J Telemed Telecare 2011;17(8):444-5. http://dx.doi.org/0.1258/jtt.2011.110305
|
18 |
Hwang JY, Kim KY, Lee KH. Factors that influence the acceptance of telemetry by emergency medical technicians in ambulances: An application of the extended technology acceptance model. Telemed J E Health 2014; 20(12):1127-34. http://dx.doi.org/10.1089/tmj.2013.0345
DOI
|
19 |
Lee WK, An Longitudinal Analysis of changing beliefs on the use in IT educatee by elaboration likelihood model. Asia Pacific Journal of Information Systems 2008;18(3):147-65.
|
20 |
Petty RE. Haughtvedt CP, Smith SM. Elaboration as a determinant of attitude strength: Creating attitudes that are persistent, resistant, and predictive of behavior, in attitude strength: Antecedents and consequences. Lawrence Erlbaum Associates, 1995. 93-130.
|
21 |
Taylor S, Todd PA. Understanding information technology usage: A test of competing models. Inf Syst Res 1995;6(2): 144-76.
DOI
|
22 |
Bagozzi RP, Phillips LW. Representing and testing organizational theories: A holistic construal. Administrative Science Quarterly 1982;27(3):459-89. http://dx.doi.org/10.2307/2392322
DOI
|
23 |
Fornell C, Larcker DF. Evaluating structural equation models with unobservable variables and measurement error. J Mark Res 1981; 18:39-50. http://dx.doi.org/10.2307/3151312
DOI
|
24 |
Dunnebeil S, Sunyaev A, Blohm I, Leimeister JM, Krcmar H. Determinants of physicians' technology acceptance for e-health in ambulatory care. Int J Med Inform 2012;81(11): 746-60. http://dx.doi.org/10.1016/j.ijmed inf.2012.02.002
DOI
|
25 |
Petty RE, Wegener DT. The elaboration likelihood model: Current status and controversies, in dual-process theories in social psychology. Guilford Press, 1999. 112-25.
|
26 |
Chin WW, Todd PA. On the use, usefulness, and ease of use of structural equation modeling in MIS research: A note of caution. Manag Inform Syst Q 1995;19:237-46. http://dx.doi.org/10.2307/249690
DOI
|
27 |
Gagnon MP, Orruno E, Asua J, Abdeljelil AB, Emparanza J. Using a modified technology acceptance model to evaluate healthcare professionals' adoption of a new telemonitoring system. Telemed J E Health 2012;18(1):54-9. http://dx.doi.org/10.1089/tmj.2011.0066
DOI
|
28 |
Orruno E, Gagnon MP, Asua J, Ben AA. Evaluation of teledermatology adoption by health-care professionals using a modified Technology Acceptance Model. J Telemed Telecare 2011;17(6):303-7. http://dx.doi.org/10.1258/jtt.2011.101101
DOI
|
29 |
Schaper L, Pervan G. ICT and OTs: A model of information and communication technology acceptance and utilisation by occupational therapists. Int J Med Inform 2007; 76S(1):S212-21. http://dx.doi.org/10.1016/j.ijmedinf.2006.05.028
DOI
|