User Satisfaction and Its Impact on the Intention to Utilize Telemedicine Services in the Dusit Model Prototype Area User Satisfaction and Intention to Utilize Telemedicine Services

Main Article Content

Nontawat Benjakul
Utoomporn Wongsin
Sukhontha Siri
Chardsumon Prutipinyo

Abstract

OBJECTIVE: Gaining insight into user satisfaction and its impact on the intention to use telemedicine is essential for the continued success of such services.
METHODS: A cross-sectional study was carried out through an online survey targeting users of the Vajira@Home telemedicine platform. Data were collected via online survey questions, which was collected and analyzed through descriptive statistics, chi-squared tests, and multivariate binary logistic regression to explore the correlation between satisfaction and the intention to use telemedicine.
RESULTS: A total of 389 respondents completed the questionnaire. Most respondents (81.2%) reported being satisfied with telemedicine services, and 72.5% indicated a strong intention to continue using them. Satisfaction emerged as the most influential factor in predicting the intention to use telemedicine (adjusted odds ratios (OR) = 13.28; 95% CI, 6.47–27.26; p < 0.001). Participants with a monthly income between 15,000 and 30,000 Thai Baht also showed a significantly higher intention to use the service (adjusted OR = 3.40; p = 0.048). Other demographic variables were not significant after adjustment.
CONCLUSION: Satisfaction is the primary factor influencing the intention to use telemedicine under the Dusit Model. These results highlight the need to prioritize patient-centered care and improve user experiences to support the long-term integration of telemedicine into urban healthcare systems.

Downloads

Download data is not yet available.

Article Details

How to Cite
Benjakul, N. ., Wongsin, U. ., Siri, S. ., & Prutipinyo, C. (2025). User Satisfaction and Its Impact on the Intention to Utilize Telemedicine Services in the Dusit Model Prototype Area : User Satisfaction and Intention to Utilize Telemedicine Services. Vajira Medical Journal : Journal of Urban Medicine, 69(3), e274619. https://doi.org/10.62691/vmj.2025.274619
Section
Original Articles

References

Angood PB, Satava R, Doarn C, Merrell R. Telemedicine at the top of the world: the 1998 and 1999 Everest extreme expeditions. Telemed J E Health 2000;6(3):315-25.

Dutta S, Mallick NR, Gayatri P. Telemedicine-digital revolution in healthcare through virtual interconnection: A review. Arch Dent Res 2024;14(2):76-84.

Freed J, Lowe C, Flodgren G, Binks R, Doughty K, Kolsi J. Telemedicine: is it really worth it? A perspective from evidence and experience. J Innov Health Inform 2018;25(1):14-8.

Kale M, Patil VC, Nashte A, Patil A, More R. Telemedicine revolution: bridging gaps in access to healthcare. Int J Recent Innov Trends Comput Comm 2023;11(7):394-9.

Anawade PA, Sharma D, Gahane S. A comprehensive review on exploring the impact of telemedicine on healthcare accessibility. Cureus 2024;16(3):e55996.

Ryu S. Telemedicine: opportunities and developments in member states: report on the second global survey on eHealth 2009 (global observatory for eHealth series, volume 2). Healthc Inform Res 2012;18(2):153.

Ministry of Public Health T. eHealth strategy, ministry of public health (2017-2026). Bangkok: Ministry of Public Health; 2017.

Faculty of Medicine Vajira Hospital. The number of outpatient visits categorized by department and emergency medicine patients (the fiscal year 2023). Bangkok; 2024.

Faculty of Medicine Vajira Hospital. Dusit model health service system development project. 3rd ed. Bangkok: Navamindradhiraj University; 2024.

Health Department. The number of outpatients of the public health service center, Bangkok (the fiscal year 2023). Bangkok; 2024.

Faculty of Medicine Vajira Hospital. Outpatient statistics; annual report 2023. Bangkok; 2023.

Tsai CH. Integrating social capital theory, social cognitive theory, and the technology acceptance model to explore a behavioralmodel of telehealth systems. Int J Environ Res Public Health 2014;11(5):4905-25.

Lin Y, Xu X, Liu Y, Alias H, Hu Z, Wong LP. Perception and acceptance of telemedicine use in health care among the general public in China: web-based cross-sectional survey. J Med Internet Res 2024;26:e53497.

Nguyen M, Waller M, Pandya A, Portnoy J. A review of patient and provider satisfaction with telemedicine. Curr Allergy Asthma Rep 2020;20(11):72.

Vinadé Chagas ME, Cristina Jacovas V, de Campos Moreira T, Rodrigues Moleda Constant HM, Fernanda Rohden S, Stiehl Alves S, et al. Are we adequately measuring patient satisfaction with telemedicine? A systematic review with a meta-analysis. Telemed J E Health 2024;30(6):1522-38.

Noceda AVG, Acierto LMM, Bertiz MCC, Dionisio DEH, Laurito CBL, Sanchez GAT, et al. Patient satisfaction with telemedicine in the Philippines during the COVID-19 pandemic: a mixed methods study. BMC Health Serv Res 2023;23(1):277.

Ghali Z, Garrouch K, Aljasser A. Drivers of patients’ behavioral intention toward public and private clinics’ services. Healthcare (Basel) 2023;11(16):2336.

Bendall‐Lyon D, Powers TL. The impact of structure and process attributes on satisfaction and behavioral intentions. J Serv Mark 2004;18(2):114-21.

Bashshur RL, Howell JD, Krupinski EA, Harms KM, Bashshur N, Doarn CR. The empirical foundations of telemedicine interventions in primary care. Telemed J E Health 2016;22(5):342-75.

Cimperman M, Makovec Brenčič M, Trkman P. Analyzing older users’ home telehealth services acceptance behavior-applying an extended UTAUT model. Int J Med Inform 2016;90:22-31.

Kamal SA, Shafiq M, Kakria P. Investigating acceptance of telemedicine services through an extended technology acceptance model (TAM). Technol Soc 2020;60:101212.

Peruzzo E, Seghieri C, Vainieri M, De Rosis S. Improving the healthcare user experience: an optimization model grounded in patient-centredness. BMC Health Serv Res 2025;25(1):132.

Love M, Hunter AK, Lam G, Muir LV, Lin HC. Patient satisfaction and perceived quality of care with telemedicine in a pediatric gastroenterology clinic. Pediatr Rep 2022;14(2):181-9.

Chen K, Lodaria K, Jackson HB. Patient satisfaction with telehealth versus in-person visits during COVID-19 at a large, public healthcare system. J Eval Clin Pract 2022;28(6):986-90.

Reed ME, Huang J, Parikh R, Millman A, Ballard DW, Barr I, et al. Patient-provider video telemedicine integrated with clinical care: patient experiences. Ann Intern Med 2019;171(3):222-4.

Hussey I, Alsalti T, Bosco F, Elson M, Arslan R. An aberrant abundance of Cronbach’s alpha values at .70. Adv Methods Pract Psychol Sci 2025;8(1).

Saw ZK, Yuen JJX, Ashari A, Ibrahim Bahemia F, Low YX, Nik Mustapha NM, et al. Forward-backward translation, content validity, face validity, construct validity, criterion validity, test-retest reliability, and internal consistency of a questionnaire on patient acceptance of orthodontic retainer. PLoS One 2025;20(1):e0314853.

Dewanta IPKS, Supriyadinata Gorda AANE, Darma GS, Mahyuni LP. Influence attitude and behavioral intention of the millenial generation to adoption of telemedicine platforms in Bali in the new normal era. Int J Soc Sci Bus 2023;7(2):369-80.

Indrayathi A, Julyari DAV, Pradnyani PE, Ulandari LPS, Hilal S. Intention to use telemedicine based on the unified theory of acceptance and use of technology model. Pub Health Prev Med Arch 2023;11(1):14-24.

Garavand A, Aslani N, Nadri H, Abedini S, Dehghan S. Acceptance of telemedicine technology among physicians: a systematic review. Inform Med Unlocked 2022;30:100943.

Dwivedi RK, Saxena AK, Parygin D, Ather D, Yadav V, editor. Applications of perceived usefulness and perceived ease of use: a review. 2019 8th International Conference System Modeling and Advancement in Research Trends (SMART); 2019 Nov 22-23; Moradabad. IEEE; 2019.

Venkatesh V, Bala H. Technology acceptance model 3 and a research agenda on interventions. Decis Sci 2008;39(2):273-315.

Venkatesh V, Thong JYL, Xu X. Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Q 2012;36(1):157.

Tangcharoensathien V, Patcharanarumol W, Kulthanmanusorn A, Saengruang N, Kosiyaporn H. The political economy of UHC reform in Thailand: lessons for low- and middle-income countries. Health Syst Reform 2019;5(3):195-208.

Gaewkhiew P, Kittiratchakool N, Suwanpanich C, Saeraneesopon T, Athibodee T, Kumluang S, et al. Telemedicine utilization in tertiary, specialized, and secondary hospitals in Thailand. Telemed Rep 2024;5(1):237-46.