Acknowledgement
The present research was supported by the research fund of Dankook University in 2021
References
- Yasudomi, K., Hamamura, T., Honjo, M., Yoneyama, A., & Uchida, M. Usage Prediction and Effectiveness Verification of App Restriction Function for Smartphone Addiction. 2020 IEEE International Conference on E-health Networking, Application & Services (HEALTHCOM).2021:1-8.
- S.J. Lee et al.. Design, development and implementation of a smartphone overdependence management system for the self-control of smart devices. Applied Sciences 2016; 6(12):440. https://doi.org/10.3390/app6120440
- Y.-H. Lin et al. Incorporation of Mobile Application (App) Measures Into the Diagnosis of Smartphone Addiction. The Journal of clinical psychiatry 2017;78(7): 866-872. https://doi.org/10.4088/JCP.15m10310
- M. J. Rho, I. young Choi, and J. Lee. Predictive factors of telemedicine service acceptance and behavioral intention of physicians. International journal of medical informatics 2014;83(8):559-571. https://doi.org/10.1016/j.ijmedinf.2014.05.005
- Byun, Harim, and Jongwoo Park. A Study on the Intention to Use Korean Telemedicine Services: Focusing on the UTAUT2 Model. Data Science and Digital Transformation in the Fourth Industrial Revolution. Springer. Cham 2021; 1-12.
- Idoga, P. E., Toycan, M., Nadiri, H., & Celebi, E. Assessing factors militating against the acceptance and successful implementation of a cloud based health center from the healthcare professionals' perspective: a survey of hospitals in Benue state, northcentral Nigeria. BMC medical informatics and decision making 2019; 19(1):1-18. https://doi.org/10.1186/s12911-018-0723-6
- M. I. Cajita, N. A. Hodgson, C. Budhathoki, and H.-R. Han. Intention to use mHealth in older adults With heart failure. Journal of Cardiovascular Nursing 2017;32(6):E1-E7. https://doi.org/10.1097/jcn.0000000000000401
- Ammenwerth, Elske. Technology acceptance models in health informatics: TAM and UTAUT. Stud Health Technol Inform 2019; 263: 64-71.
- P. Duarte and J. C. J. J. o. B. R. Pinho. A mixed methods UTAUT2-based approach to assess mobile health adoption. Journal of Business Research 2019;102:140-150. https://doi.org/10.1016/j.jbusres.2019.05.022
- D. Ozdemir-Gungor, M. Goken, N. Basoglu, A. Shaygan, M. Dabic, and T. U. Daim. An Acceptance Model for the Adoption of Smart Glasses Technology by Healthcare Professionals. International Business and Emerging Economy Firms: Springer 2020;163-194.
- E. J. T. Park. User acceptance of smart wearable devices: An expectation-confirmation model approach. Telematics and Informatics 2020;47:101318. https://doi.org/10.1016/j.tele.2019.101318
- T. Shemesh, S. J. T. Barnoy, and e-Health. Assessment of the Intention to Use Mobile Health Applications Using a Technology Acceptance Model in an Israeli Adult Population. Telemedicine and e-Health 2020;26(9).
- M. J. Rho et al. Comparison of the Acceptance of Telemonitoring for Glucose Management Between South Korea and China. Telemedicine and e-Health 2017; 23(11): 881-890. https://doi.org/10.1089/tmj.2016.0217
- Francis, Rita P. Examining Healthcare Providers' Acceptance of Data From Patient Self-Monitoring Devices Using Structural Equation Modeling With the UTAUT2 Model. International Journal of Healthcare Information Systems and Informatics (IJHISI) 2019; 14(1): 44-60. https://doi.org/10.4018/ijhisi.2019010104
- V. Venkatesh, J. Y. Thong, and X. J. M. q. Xu. Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. 2012:157-178.
- F. D. Davis. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly 1989: 319-340.
- M. B. Alazzam et al. Pilot study of EHRs acceptance in Jordan hospitals by UTAUT2. Journal of Theoretical and Applied Information Technology 2016; 85(3);378.
- J. Tavares, A. Goulao, T. J. I. f. H. Oliveira, and S. Care. Electronic health record portals adoption: empirical model based on UTAUT2. Informatics for Health and Social Care 2018;43(2): 109-125. https://doi.org/10.1080/17538157.2017.1363759
- M. Rasmi, M. B. Alazzam, M. K. Alsmadi, I. A. Almarashdeh, R. A. Alkhasawneh, and S. J. I. J. o. H. M. Alsmadi. Healthcare professionals' acceptance Electronic Health Records system: Critical literature review. Jordan case study 2018: 1-13.
- Tubaishat, Ahmad. Perceived usefulness and perceived ease of use of electronic health records among nurses: application of technology acceptance model. Informatics for Health and Social Care 2018; 43(4): 379-389. https://doi.org/10.1080/17538157.2017.1363761
- Tao, D., Shao, F., Wang, H., Yan, M., & Qu, X. Integrating usability and social cognitive theories with the technology acceptance model to understand young users' acceptance of a health information portal. Health informatics journal 2020; 26(2): 1347-1362. https://doi.org/10.1177/1460458219879337
- M. Yan and C. Or. Factors in the 4-week Acceptance of a Computer-Based, Chronic Disease Self-Monitoring System in Patients with Type 2 Diabetes Mellitus and/or Hypertension. Telemedicine and e-Health 2018; 24(2): 121-129. https://doi.org/10.1089/tmj.2017.0064
- K. Dou et al. Patients' Acceptance of Smartphone Health Technology for Chronic Disease Management: A Theoretical Model and Empirical Test. JMIR mHealth and uHealth 2017;5(12).
- Lazard, A. J., Watkins, I., Mackert, M. S., Xie, B., Stephens, K. K., & Shalev, H. Design simplicity influences patient portal use: the role of aesthetic evaluations for technology acceptance. Journal of the American Medical Informatics Association 2016; 23(e1): e157-e161. https://doi.org/10.1093/jamia/ocv174
- X. Zhang et al. User acceptance of mobile health services from users' perspectives: The role of self-efficacy and response-efficacy in technology acceptance. Informatics for Health and Social Care 2017;42(2): 194-206. https://doi.org/10.1080/17538157.2016.1200053
- V. Venkatesh and F. D. Davis. A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science 2000; 46(2): 186-204. https://doi.org/10.1287/mnsc.46.2.186.11926
- V. Venkatesh and H. Bala. Technology acceptance model 3 and a research agenda on interventions. Decision sciences 2008;39(2):273-315. https://doi.org/10.1111/j.1540-5915.2008.00192.x
- X. Lishan, Y. C. Chiuan, M. Choolani, and C. H. Chuan. The perception and intention to adopt female-focused healthcare applications (FHA): A comparison between healthcare workers and non-healthcare workers. International journal of medical informatics 2009; 78(4): 248-258. https://doi.org/10.1016/j.ijmedinf.2008.07.014
- A. C. van Bon, M. J. Kohinor, J. B. Hoekstra, G. von Basum, and J. H. DeVries. Patients' perception and future acceptance of an artificial pancreas. Journal of diabetes science and technology 2010;4(3): 596-602. https://doi.org/10.1177/193229681000400313
- Y.-H. Chang, M.-J. Rho, and J.-B. Lee. Predictive Factors of Telemonitoring Acceptance among Chronically-Ill Patients in Public Healthcare. Journal of International Trade & Commerce 2016; 12(4): 177-193.
- Kamal, S. A., Shafiq, M., & Kakria, P. Investigating acceptance of telemedicine services through an extended technology acceptance model (TAM). Technology in Society 2020; 60:101212. https://doi.org/10.1016/j.techsoc.2019.101212
- H. E. Buysse et al. Introducing telemonitoring for diabetic patients: development of a telemonitoring 'Health Effect and Readiness' questionnaire. international journal of medical informatics 2010; 79(8): 576-584. https://doi.org/10.1016/j.ijmedinf.2010.05.005
- Lee, S. W., Sung, H. J., & Jeon, H. M. Determinants of continuous intention on food delivery apps: extending UTAUT2 with information quality. Sustainability, 2019; 11(11): 3141. https://doi.org/10.3390/su11113141
- C.-L. Hsu and J. C.-C. Lin. Effect of perceived value and social influences on mobile app stickiness and in-app purchase intention. Technological Forecasting and Social Change 2016;108: 42-53. https://doi.org/10.1016/j.techfore.2016.04.012
- Y. Rosseel et al. Package 'lavaan'. Retrieved 2017 June; vol.17.
- J. C. Nunnally, I. H. Bernstein, and J. M. t. Berge. Psychometric theory. McGraw-hill New York, 1967.
- W. W. Chin. Commentary: Issues and opinion on structural equation modeling. ed: JSTOR. 1998.
- W. W. Chin. The partial least squares approach to structural equation modeling. Modern methods for business research 1998;295(2): 295-336.
- C. Fornell and D. F. Larcker. Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research 1981;39-50.
- S. Kim and G. Garrison. Investigating mobile wireless technology adoption: An extension of the technology acceptance model. Information Systems Frontiers 2009;11(3): 323-333. https://doi.org/10.1007/s10796-008-9073-8
- Hubert, M., Blut, M., Brock, C., Zhang, R. W., Koch, V., & Riedl, R. The influence of acceptance and adoption drivers on smart home usage. European Journal of Marketing 2019
- Jaklic, J., Grubljesic, T., & Popovic, A. The role of compatibility in predicting business intelligence and analytics use intentions. International Journal of Information Management 2-18; 43: 305-318. https://doi.org/10.1016/j.ijinfomgt.2018.08.017
- Kamal, S. A., Shafiq, M., & Kakria, P. Investigating acceptance of telemedicine services through an extended technology acceptance model (TAM). Technology in Society 2020; 60: 101212. https://doi.org/10.1016/j.techsoc.2019.101212
- Wu, Long, and Jian-Liang Chen. An extension of trust and TAM model with TPB in the initial adoption of on-line tax: an empirical study. International Journal of Human-Computer Studies 2005;62(6):784-808. https://doi.org/10.1016/j.ijhcs.2005.03.003
- J. Sandberg et al. A qualitative study of the experiences and satisfaction of direct telemedicine providers in diabetes case management. Telemedicine and e-Health 2009;15(8): 742-750. https://doi.org/10.1089/tmj.2009.0027
- A. Martinez, E. Everss, J. L. Rojo-Alvarez, D. P. Figal, and A. Garcia-Alberola. A systematic review of the literature on home monitoring for patients with heart failure. Journal of telemedicine and telecare 2006;12(5): 234-241. https://doi.org/10.1258/135763306777889109
- E. J. Lanseng and T. W. Andreassen. Electronic healthcare: a study of people's readiness and attitude toward performing self-diagnosis. International Journal of Service Industry Management 2007;18(4):394-417. https://doi.org/10.1108/09564230710778155
- Y.-Y. Shih. The effect of computer self-efficacy on enterprise resource planning usage. Behaviour & Information Technology 2006;25(5):407-411. https://doi.org/10.1080/01449290500168103
- Q. Ma, A. H. Chan, and K. Chen. Personal and other factors affecting acceptance of smartphone technology by older Chinese adults. Applied ergonomics 2016;54: 62-71. https://doi.org/10.1016/j.apergo.2015.11.015
- Y. Y. Mun, J. D. Jackson, J. S. Park, and J. C. Probst. Understanding information technology acceptance by individual professionals: Toward an integrative view. Information & Management 2006; 43(3): 350-363. https://doi.org/10.1016/j.im.2005.08.006
- Chao, C. M. Factors determining the behavioral intention to use mobile learning: An application and extension of the UTAUT model. Frontiers in psychology 2019; 10: 1652. https://doi.org/10.3389/fpsyg.2019.01652
- A. Sunyaev, T. Dehling, P. L. Taylor, and K. D. Mandl. Availability and quality of mobile health app privacy policies. Journal of the American Medical Informatics Association 2014;22(e1):e28-e33. https://doi.org/10.1136/amiajnl-2013-002605
- Kim, B. G., Lee, C. H., Jeon, M. J., & Lee, M. H. Development of a residential treatment program for smart-phone addicted adolescent. The Korea Journal of Youth Counseling 2016; 24(2): 37-57. https://doi.org/10.35151/kyci.2016.24.2.003
- Kyoung, S. K., & Kim, J. W. A study on smart-phone addiction in teenager: Focused on comparison smart-phone overdependence, game addiction, SNS addiction. Studies on Life and Culture 2019; 52(1).
- Rho, M. J., Park, J., Na, E., Jeong, J. E., Kim, J. K., Kim, D. J., & Choi, I. Y. Types of problematic smartphone use based on psychiatric symptoms. Psychiatry research 2019; 275: 46-52. https://doi.org/10.1016/j.psychres.2019.02.071
- Park, J., Jeong, J. E., yeon Park, S., & Rho, M. J. Development of the smartphone addiction risk rating score for a smartphone addiction management application. Frontiers in public health 2020; 8.
- Hwang, J., Lee, J. S., & Kim, H. Perceived innovativeness of drone food delivery services and its impacts on attitude and behavioral intentions: The moderating role of gender and age. International Journal of Hospitality Management 2019;81:94-103. https://doi.org/10.1016/j.ijhm.2019.03.002