Pengaruh facilitating conditions, social influences, perceived ease of use, dan perceived usefulness terhadap niat pengguna layanan telemedicine

(1)  

(2) Universitas Pelita Harapan 


DOI : https://doi.org/10.29210/020232850
Full Text:

Abstract
Keywords
References
Abdool, S., Abdallah, S., Akhlaq, S., & Abdul Razzak, H. (2021). User acceptance level of and attitudes towards telemedicine in the United Arab Emirates. Sultan Qaboos University Medical Journal [SQUMJ], 21(2). https://doi.org/10.18295/squmj.2021.21.02.008
Alexandra, S., Handayani, P. W., & Azzahro, F. (2021). Indonesian hospital telemedicine acceptance model: The influence of user behavior and technological dimensions. Heliyon, 7(12). https://doi.org/10.1016/j.heliyon.2021.e08599
Amin, R., Hossain, Md. A., Uddin, Md. M., Jony, M. T., & Kim, M. (2022). Stimuli influencing engagement, satisfaction, and intention to use telemedicine services: An integrative model. Healthcare, 10(7), 1327. https://doi.org/10.3390/healthcare10071327
Andriani, A., & Berlianto, M. P. (2022). Acceptance of Halodoc’s online teleconsultation during Covid-19. Enrichment: Journal of Management, 12 (2), 1566-1574.
Annur, C. M. (2022, September 8). Kepemilikan ponsel di Indonesia melonjak 68% dalam 1 dekade terakhir: Databoks. Pusat Data Ekonomi dan Bisnis Indonesia. https://databoks.katadata.co.id/datapublish/2022/09/08/kepemilikan-ponsel-di- indonesia-melonjak-68-dalam-1-dekade-terakhir
Ardiansyah, A., & Rusfian, E. Z. (2020). Eksplorasi aspek – aspek penghambat penerimaan user telemedicine pada daerah tertinggal di Indonesia. Journal of Education, Humaniora and Social Sciences, 3(2), 671–681.
Badan Pusat Statistik, 2022. Angka Kesakitan Penduduk DKI Jakarta Menurut Jenis Kelamin dan Kabupaten/Kota 2021-2022. Retrieved 3 November, 2023, from https://jakarta.bps.go.id/indicator/30/967/1/angka-kesakitan-penduduk-dki-jakarta-menurut-jenis-kelamin-dan-kabupaten-kota.html
Badan Pusat Statistik. (2022). (rep.). Survei Perilaku Masyarakat Pada Masa Pandemi COVID-19. Retrieved August 19, 2022, from https://covid-19.bps.go.id/home/infografis.
Bettiga, D., Lamberti, L., & Lettieri, E. (2019). Individuals’ adoption of smart technologies for preventive health care: A structural equation modeling approach. Health Care Management Science, 23(2), 203–214. https://doi.org/10.1007/s10729-019-09468-2
Blok, M., van Ingen, E., Jr., de Boer, A. H., & Slootman, M. (2020). The use of information and communication technologies by older people with cognitive impairments: from barriers to benefits. Computers in Human Behavior, 104, 106173.
Chan, Z. Y., Lim, C. F., Leow, J. L., Chium, F. Y., Lim, S. W., Tong, C. H., Zhou, J. J., Tsi, M. M., Tan, R. Y., & Chew, L. S. (2022). Using the technology acceptance model to examine acceptance of telemedicine by cancer patients in an ambulatory care setting. Proceedings of Singapore Healthcare, 31, 201010582211045. https://doi.org/10.1177/20101058221104578
Crico, C., Renzi, C., Graf, N., Buyx, A., Kondylakis, H., Koumakis, L., & Pravettoni, G. (2018). MHealth and telemedicine apps: In search of a common regulation. Ecancermedicalscience, 12. https://doi.org/10.3332/ecancer.2018.853
Dutot, V., Bergeron, F., Rozhkova, K., & Moreau, N. (2019). Factors affecting the adoption of connected objects in e-health: A mixed methods approach. Systèmes d’information & Management, Volume 23(4), 31–66. https://doi.org/10.3917/sim.184.0031
Hair, J. F., M., H. G. T., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least squares structural equations modeling (PLS-SEM). SAGE.
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/ebr-11-2018-0203
Henseler, J., Ringle, C. M., & Sarstedt, M. (2014). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
Hartono, N., Laurence, & Tedja, T. O. (2019). International Conference on Informatics, Technology, and Engineering 2019. Bali; Ubaya. Retrieved August 18, 2023, from https://www.researchgate.net/publication/338117846_Development_initial_model_of_intention_to_use_Halodoc_application_using_PLS-SEM.
Hoque, R., & Sorwar, G. (2017). Understanding factors influencing the adoption of mHealth by the elderly: An extension of the UTAUT model. International Journal of Medical Informatics, 101, 75–84. https://doi.org/10.1016/j.ijmedinf.2017.02.002
Indriyanti, E.R., & Wibowo, S., (2020). Bisnis kesehatan berbasis digital: intensi pengguna aplikasi digital Halodoc. Jurnal Pengabdian dan Kewirausahaan, 4(2), 112–121.
Jewer, J. (2018). Patients’ intention to use online postings of ED wait times: A modified UTAUT model. International Journal of Medical Informatics, 112, 34–39. https://doi.org/10.1016/j.ijmedinf.2018.01.008
Kamal, S. A., Shafiq, M., & Kakria, P. (2020). Investigating acceptance of telemedicine services through an extended technology acceptance model (TAM). Technology in Society, 60, 101212. https://doi.org/10.1016/j.techsoc.2019.101212
Katadata. (2018, April 30). Banyak lansia tinggal dengan anak, mantu, dan cucu: Databoks. Pusat Data Ekonomi dan Bisnis Indonesia. https://databoks.katadata.co.id/datapublish/2018/04/30/banyak-lansia-tinggal-dengan-anak-mantu-dan-cucu
Katadata. (2022). (rep.). Penggunaan layanan kesehatan & telemedik di Indonesia: laporan survey [PDF file]. Retrieved August 24, 2022, from https://cdn1.katadata.co.id/template/frontend_template_v3/images/miniweb/dua-tahun- pandemi/file/KIC_Survei%202022_Penggunaan_Layanan_Telemedik.pdf.
Kemenkes RI. (2017). List rumah sakit yang telah bekerja sama. Telemedicine Indonesia. https://temenin.kemkes.go.id/list_rs/
Kementerian Kesehatan Republik Indonesia, Profil Kesehatan Indonesia Tahun 2021 (2022). Jakarta; Kementerian Kesehatan Republik Indonesia. Retrieved April 8, 2022, from https://www.kemkes.go.id/downloads/resources/download/pusdatin/profil-kesehatan-indonesia/Profil-Kesehatan-2021.pdf.
Kementerian Kesehatan Republik Indonesia, Surat Edaran nomor HK.02.01/MENKES/303/2020 tentang Penyelenggaraan Pelayanan Kesehatan Melalui Pemanfaatan Teknologi Informasi dan Komunikasi Dalam Rangka Pencegahan Penyebaran Covid-19 (2020). Jakarta.
Kissi, J., Dai, B., Dogbe, C. S., Banahene, J., & Ernest, O. (2019). Predictive factors of physicians’ satisfaction with telemedicine services acceptance. Health Informatics Journal, 26(3), 1866–1880. https://doi.org/10.1177/1460458219892162
Kock, N., & Hadaya, P. (2018). Minimum sample size estimation in PLS‐SEM: The inverse square root and gamma‐exponential methods. Information Systems Journal, 28(1), 227– 261.
Lai, P. C. (2017). The literature review of technology adoption models and theories for the novelty technology. Journal of Information Systems and Technology Management, 14(1), 21-38. doi: 10.4301/S1807-17752017000100002.
Macedo, I. M. (2017). Predicting the acceptance and use of information and communication technology by older adults: An empirical examination of the revised UTAUT2. Computers in Human Behavior, 75, 935-948.
Manda, E. F. & Salim, R. (2021). Analysis of the influence of perceived usefulness, perceived ease of use and attitude toward using technology on actual to use Halodoc application using the technology acceptance model (TAM) method approach. International Research Journal of Advanced Engineering and Science, 6(1), 135-140.
Mechanic, O. J., Persaud, Y., & Kimball, A. B. (2022). Telehealth Systems. In StatPearls. StatPearls Publishing.
Rahi, S., Khan, M. M. & Alghizzawi, M. (2021). Factors influencing the adoption of telemedicine health services during COVID-19 pandemic crisis: an integrative research model. Enterprise Information Systems, 15(6), 769-793. https://doi.org/10.1080/17517575.2020.1850872
Schmitz, A., Díaz-Martín, A., & Guillén, M. J. Y. (2022). Modifying UTAUT2 for a cross- country comparison of telemedicine adoption. Computers in Human Behavior, 130, 1- 11. https://doi.org/10.1016/j.chb.2022.107183
Setyowati, D. (2022, April 7). Jumlah pengguna baru layanan telemedicine capai 44% dalam 6 bulan. Katadata. https://katadata.co.id/desysetyowati/digital/624e9b8b96669/jumlah- pengguna-baru-layanan-telemedicine-capai-44-dalam-6-bulan
Shmueli, G., Sarstedt, M., Hair, J. F., Cheah, J.H., Ting, H., Vaithilingam, S., & Ringle, C. M. (2019). Predictive model assessment in PLS-SEM: Guidelines for using PLSpredict. European Journal of Marketing, 53(11), 2322–2347. https://doi.org/10.1108/ejm-02- 2019-0189
Singh, V. & Dev, V. (2021). Telemedicine adoption in India: Identifying factors affecting intention to use. International Journal of Healthcare Information Systems and Informatics, 16(4). https://doi.org/10.3403/30083225u
Tavares, J., Goul ̃ao, A., & Oliveira, T. (2018). Electronic health record portals adoption: Empirical model based on UTAUT2. Informatics for Health and Social Care, 43(2), 109–125. https://doi.org/10.1080/17538157.2017.1363759
World Bank. (2022). Rural population (% of total population) | Data - World Bank Data. World Bank Open Data. https://data.worldbank.org/indicator/SP.RUR.TOTL.ZS
Wang, H., Liang, L., Du, C., & Wu, Y. (2021). Implementation of online hospitals and factors influencing the adoption of mobile medical services in China: cross-sectional survey study. JMIR mHealth and uHealth, 9(2), e25960.
World Health Organization (WHO). (2010). Telemedicine: Opportunities and developments in member states: Report on the second global survey on eHealth 2009. https://www.who.int/goe/publications/goe_telemedicine_2010.pdf
Wu, D., Gu, H., Gu, S., & You, H. (2021). Individual motivation and social influence: a study of telemedicine adoption in China based on social cognitive theory. Health Policy and Technology, 10(3). https://doi.org/10.1016/j.hlpt.2021.100525
Yuswohady, Rachmaniar , A., Fatahillah, F., Brillian, G., & Hanifah, I. (2020, December 14). Indonesia Industry Outlook 2021. Yuswohady.com. https://www.yuswohady.com/tag/indonesia-industry-outlook-2021/
Zhang, X. & Zaman, B. (2020). Adoption mechanism of telemedicine in underdeveloped country. Health Informatics Journal, 26(2), 1088-1103. doi: 10.1177/1460458219868353.
Zobair, K. M., Sanzogni, L., Houghton, L., Sandhu, K., & Islam, M. J. (2021). Health seekers’ acceptance & adoption determinants. Australasian Journal of Information Systems, 25, 1-30. https://doi.org/10.3127/ajis.v25i0.3071
Zobair, K. M., Sanzogni, L., & Sandhu, K. (2020). Telemedicine healthcare service adoption barriers in rural Bangladesh. Australasian Journal of Information Systems, 24, 1-24. https://doi.org/10.3127/ajis.v24i0.2165
Article Metrics


Refbacks
- There are currently no refbacks.