The readiness and acceptance of patients with tuberculosis to use telecare
DOI:
https://doi.org/10.46542/pe.2024.243.251255Keywords:
Digital health, e-health, Healthcare, TuberculosisAbstract
Background: Tuberculosis (TB) has been a global health burden and a leading infectious killer. The evolving healthcare technology allows telecare services to improve treatment support for TB patients. However, patient readiness and acceptance to use the service still need to be discovered.
Objective: To evaluate the readiness and acceptance of TB patients in using telecare services.
Methods: A cross-sectional survey involving patients at a respiratory hospital in Surabaya, Indonesia, was conducted using an accidental sampling technique from April to June 2023. A validated questionnaire was developed from the technology readiness index (TRI) and technology acceptance model (TAM) framework. Data were analysed using partial least squares-structural equation modelling (PLS-SEM).
Results: A total of 188 respondents participated. Respondents had low to medium-range attitudes towards a readiness to use the telecare service. Nevertheless, the majority of the respondents accepted the idea of telecare service. Optimism and innovativeness were two significant factors influencing patient readiness to use telecare services. Respondents had a positive perception of the perceived ease of use and perceived usefulness of the service.
Conclusion: Not all patients were ready to use telecare despite their high acceptance towards the service. However, the positive perception towards the benefits of the service can be the leveraging factor for gradually adopting the service.
References
AshaRani, P. V, Hua, L. J., Roystonn, K., Kumar, F. D. S., Peizhi, W., Jie, S. Y., Shafie, S., Chang, S., Jeyagurunathan, A., Yiang, C. B., Abdin, E., Vaingankar, J. A., Sum, C. F., Lee, E. S., Chong, S. A., & Subramaniam, M. (2021). Readiness and acceptance of Ehealth services for diabetes care in the general population: Cross-sectional study. Journal of Medical Internet Research, 23(9), e26881.
Buyle, R., Van Compernolle, M., Vlassenroot, E., Vanlishout, Z., Mechant, P., & Mannens, E. (2018). Technology readiness and acceptance model’ as a predictor for the use intention of data standards in smart cities. Media and Communication 6(4Theoretical Reflections and Case Studies), 127–39.
Chang, J. E., Lai, A. Y., Gupta, A., Nguyen, A. M., Berry, C. A., & Shelley, D. A. (2021). Rapid transition to telehealth and the digital divide: Implications for primary care access and equity in a post-COVID era. The Milbank Quarterly, 99(2), 340–68.
Chen, M-F., & Lin, N-P. (2018). Incorporation of health consciousness into the technology readiness and acceptance model to predict App download and usage Intentions. Internet Research, 28(2), 351–73.
Chung, N., Han, H., & Joun, Y. (2015). Tourists’ intention to visit a destination: The role of Augmented Reality (AR) application for a heritage site. Computers in Human Behavior, 50, 588–599.
Gurupur, V., Shettian, K., Xu, P., Hines, S., Desselles, M., Dhawan, M., Wan, T. Th H., Raffenaud, A., & Anderson, L. (2017). Identifying the readiness of patients in implementing telemedicine in Northern Louisiana for an oncology practice. Health Informatics Journal, 23(3), 181–96.
Hermansyah, A., Sukorini, A. I., Asmani, F., Suwito, K. A., & Rahayu, T. P. (2020). The contemporary role and potential of pharmacist contribution for community health using social media. Journal of Basic and Clinical Physiology and Pharmacology, 30(6), 1–8.
Kampa, R. K. (2023). Combining technology readiness and acceptance model for investigating the acceptance of M-learning in higher education in India. Asian Association of Open Universities Journal.
Mucheleng’anga, L, A., Himwaze, C. M., Telendiy, V., Simumba, S., Soko, J., Kayonde, N., Mulenga, B., Hamukale, A., Shibemba, A. L., Lungu, P. S., Tembo, J., Bates, M., Chanda-Kapata, P., Mwaba, P., Kapata, N., Ntoumi, F., & Zumla, A. (2022). Incidental tuberculosis in sudden, unexpected, and violent deaths in the community Lusaka, Zambia - A descriptive forensic post-mortem examination study. International Journal of Infectious Diseases.
Nielsen, A. S., Hanna, L., Larsen, B. F., Appel, C. W., Osborne, R. H., & Kayser, L. (2022). Readiness, acceptance and use of digital patient reported outcome in an outpatient clinic. Health Informatics Journal, 28(2), 14604582221106000.
Peixoto, M. R., & Ferreira, J. B. (2022). Drivers for teleconsultation acceptance in Brazil: Patients ’ perspective during the COVID-19 pandemic. Journal of Contemporary Administration, 26(2), 22.
Sugiarto, M., Soeprapto, A., & Dewanti, I. S. (2015). Technology readiness and acceptance model technology. The2nd University Research Coloquium, 78–86.
Tsang, Y. F., Kumar, V., Samadar, P., Yang, Y., Lee, J., Ok, Y. S., Song, H., Kim, K-H., Kwon, E., E., & Jeon, Y. J. (2019). Production of bioplastic through food waste valorization. Environment International, 127, 625–644.
WHO Global TB Report. (2022). Global tuberculosis report 2022. World Health Organization 2022, 4(1), 168.
Wijkman, M., Carlsson,M., Darwiche, G., & Nystrom, F. H. (2020). A pilot study of hypertension management using a telemedicine treatment approach. Blood Pressure Monitoring, 18–21.
