Tam Approach: The Role Of Perceived Usefulness On Attitude In The Use Of Hospital Applications In Indonesia
DOI:
https://doi.org/10.62027/praba.v3i2.343Keywords:
Perceived Ease of Use, Perceived Usefulness, Attitude, Behavioral IntentionAbstract
The development of information technology has changed the way patients interact with hospitals. The Minimum Service Standard Indicator for Hospitals in Indonesia shows that the number of registrations via mobile applications has still not reached the target and the results of the review show that there are still complexities and difficulties in using the application. Understanding the factors that influence patient intention to use the hospital mobile application is essential to optimize its adoption and use. This study aims to test the Technology Acceptance Model in understanding patient intention to use the Hospital mobile application. This quantitative study with the causality method used a sample of 100 users of the application who met the criteria. Data were collected through questionnaires and analyzed using path analysis. The results showed that perceived ease of use and perceived usefulness had an indirect effect on behavioral intention to use through attitude. Research findings show that Perceived Usefulness is the most dominant factor in influencing users attitudes towards applications. The implications are improvements in simplifying features, design, increasing the function of hospital mobile applications, as well as considering patient expectations of the application in order to increase user intention to adopt the application. These findings provide insight for hospital management to design mobile applications that are easier to use and provide benefits to patients, to increase adoption and use of the application.References
A. Almasri, “The Users' Behavioral Intention to use Mobile Health-Tech Application to Prevent the Spread of Coronavirus,” South East Eur. J. Econ. Bus., vol. 17, no. 2, p. 18–33, 2022.
B. Chen, Y. Chang, B. Wang, J. Zou, and S. Tu, “Technology acceptance model perspective on the intention to participate in medical talents training in China,” Heliyon, vol. 10, no. 4, p. e26206, 2024.
C.S. Wood et al., “Taking connected mobile-health diagnostics of infectious diseases into the field,” Nature, vol. 566, no. 7745, p. 467–474, 2019.
D. Akritidi, P. Gallos, V. Koufi, and F. Malamateniou, “Using an Extended Technology Acceptance Model to Evaluate Digital Health Services,” Stud. Health Technol. Inform., vol. 295, p. 530–533, 2022.
FD Davis, “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology,” MIS Q., vol. 13, no. 3, p. 319–340, 1989.
FD Davis, RP Bagozzi, and PR Warshaw, “User Acceptance of Computer Technology: A Comparison of Two Theoretical Models,” Manage. Sci., vol. 35, no. 8, p. 982–1003, 1989.
H. Wang, J. Zhang, Y. Luximon, M. Qin, P. Geng, and D. Tao, “The Determinants of User Acceptance of Mobile Medical Platforms: An Investigation Integrating the TPB, TAM, and Patient-Centered Factors, ” Int. J Environ. Res. Public Health, vol. 19, no. 17, 2022.
HH Muljo et al., “TAM as a model to understand the intention of using a mobile-based cancer early detection learning application,” Int. J. online Biomed. Eng., vol. 16, no. 2, p. 80–93, 2020.
I. Marin, N. Goga, and R.-C. Stanciu, “Web application for self-diagnosis and drug recommendation based on user symptoms,” J. Adv. Technol. Eng. Res., vol. 5, no. 2, p. 62–71, 2019.
IK Mensah, “Understanding the Drivers of Ghanaian Citizens' Adoption Intentions of Mobile Health Services,” Front. Public Heal., vol. 10, no. June, 2022.
J. Mccool, R. Dobson, R. Whittaker, and C. Paton, “Mobile Health (mHealth) in Low- and Middle-Income Countries,” Annu. Rev. of Public Heal., p. 525–539, 2022.
KSLT Zin, S. Kim, HS Kim, andIF Feyissa, "A Study on Technology Acceptance of Digital Healthcare among Older Korean Adults Using Extended Tam (Extended Technology Acceptance Model)," Adm. Sci., vol. 13, no. 2, p. 1–18, 2023.
M. Sinha, L. Fukey, K. Balasubramanian, P. Kunasekaran, NA Ragavan, and MH Hanafiah, “Acceptance of consumer-oriented health information technologies (chits): Integrating technology acceptance model with perceived risk,” Inform, vol. 45, no. 6, p. 45–52, 2021.
M. Yang, A. Al Mamun, J. Gao, MK Rahman, AA Salameh, and SS Alam, “Predicting m-health acceptance from the perspective of unified theory of acceptance and use of technology,” Sci. Rep., vol. 14, no. 1, p. 1–18, 2024.
MH An, SC You, RW Park, and S. Lee, “Using an extended technology acceptance model to understand the factors influencing telehealth utilization after flattening the COVID-19 curve in South Korea: Cross-sectional survey study,” JMIR Med. Informatics, vol. 9, no. 1, 2021.
MH Kalayou, BF Endehabtu, and B. Tilahun, "The applicability of the modified technology acceptance model (Tam) on the sustainable adoption of ehealth systems in resource-limited settings," J. Multidiscip. Health c., vol. 13, p. 1827–1837, 2020.
P. Ramírez-Correa, C. Ramírez-Rivas, J. Alfaro-Pérez, and A. Melo-Mariano, “Telemedicine acceptance during the COVID-19 pandemic: An empirical example of robust consistent partial least squares path modeling,” Symmetry (Basel), vol. 12, no. 10, 2020.
SG Salinding and RK Hasyim, "Acceptance Model of Hospital Information Management System: Case of Study in Indonesia," Eur. J. Bus. Manag. Res., vol. 5, no. 5, p. 1–8, 2020.
Sugiyono, Quantitative, Qualitative and R&D Research Methods. Bandung: Alfabeta, 2017.
V. Venkatesh and FD Davis, “Theoretical extension of the Technology Acceptance Model: Four longitudinal field studies,” Manage. Sci., vol. 46, no. 2, p. 186–204, 2000.
W. Chiu and H. Cho, “The role of technology readiness in individuals' intention to use health and fitness applications: a comparison between users and non-users,” Asia Pacific J. Mark. Logist., vol. 33, no. 3, p. 807–825, 2021.
WT Atinafu, KN Tilahun, TM Yilma, ZA Mekonnen, AD Walle, and JB Adem, “Intention to use a mobile phone to receive mental health support and its predicting factors among women attending antenatal care at public health facilities in Ambo town, West Shoa zone, Ethiopia 2022,” BMC Health Serv. Res., vol. 23, no. 1, p. 1–16, 2023.
Z. Ren and G. Zhou, “Analysis of Driving Factors in the Intention to Use the Virtual Nursing Home for theElderly: A Modified UTAUT Model in the Chinese Context,” Healthc., vol. 11, no. 16, 2023.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Jurnal Praba : Jurnal Rumpun Kesehatan Umum

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.