Factors Affecting Adoption of Telemedicine for Virtual Healthcare Services in Indonesia
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Background: The utilization of virtual healthcare services, particularly telemedicine, has been accelerated by the COVID-19 pandemic. Although the pandemic is no longer the primary concern, telemedicine still holds potential for long-term adoption. However, implementing telemedicine in Indonesia as an online platform for remote healthcare delivery still faces issues, despite its potential. Further investigation is required to identify the factors that affect its adoption and develop strategies to surmount implementation challenges.
Objective: This study aims to examine and enrich knowledge about the adoption of telemedicine in Indonesia.
Methods: A cross-sectional survey was conducted through an online questionnaire to collect data. Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) was employed by integrating with several factors, such as eHealth Literacy, Privacy Concerns, and Trust. Gender and age were considered as moderating variables. Data samples were analyzed using Partial Least Square – Structural Equation Modeling (PLS–SEM).
Results: The findings suggest that performance expectancy, effort expectancy, social influence, eHealth literacy, and trust have a significant impact on adults' behavioral intention to use telemedicine. However, facilitating condition, price value, and privacy concern do not show any significant effects on adults' Behavioral Intention to Use Telemedicine.
Conclusion: This study highlights the importance of understanding adoption factors to develop effective strategies. Results show performance expectancy, effort expectancy, social influence, eHealth literacy, and trust are significant factors, while facilitating condition, price value, and privacy concern are not. The UTAUT2 model is a good predictive tool for healthcare adoption. To increase usage intention, several aspects must be considered in the implementation of telemedicine.
Keywords: Adoption, Behavioral Intention to Use, Telemedicine, UTAUT2, Virtual Healthcare.
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