Main Article Content
Abstract
Telemedicine has emerged as a transformative approach in healthcare delivery, particularly in addressing accessibility and efficiency challenges in traditional systems. While prior research has emphasized its technological and operational benefits, studies investigating the intrinsic drivers of patient engagement, especially from a value cocreation perspective remain scant. Grounded in self-determination theory (SDT) and service-dominant logic (SDL), this study investigates how intrinsic motivation, external regulation, and identified regulation influence value cocreation behavior and, subsequently, patient-perceived value and well-being. Data were collected through an electronic survey targeting telemedicine users in Greater Jakarta who had used digital health services within the past six months. Partial least squares structural equation modeling (PLS-SEM) was employed to analyze the data and assess both the measurement and structural models. Results confirm that all hypothesized relationships are significant. Identified regulation demonstrates the strongest influence on value cocreation behavior, followed by intrinsic motivation and external regulation. Furthermore, value cocreation behavior significantly enhances both perceived value and well-being, with perceived value also positively affecting well-being. The model exhibits strong explanatory power and predictive relevance. This study contributes by highlighting the importance of motivational quality in shaping patient engagement and outcomes thus provides actionable insights for healthcare providers aiming to design telemedicine platforms that foster meaningful interaction, improve patient satisfaction, and enhance overall health-related well-being.
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References
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Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021a). Evaluation of Reflective Measurement Models (pp. 75–90). https://doi.org/10.1007/978-3-030-80519-7_4
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Hau, L. N., & Thuy, P. N. (2022). Enabling customer co-creation behavior at a distance: the case of patients using self-monitoring handheld devices in healthcare. Service Business, 16(1), 99–123. https://doi.org/10.1007/s11628-021-00451-y
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). 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
Hickmann, E., Richter, P., & Schlieter, H. (2022). All together now – patient engagement, patient empowerment, and associated terms in personal healthcare. BMC Health Services Research, 22(1). https://doi.org/10.1186/s12913-022-08501-5
Keelson, S. A., Addo, J. O., & Amoah, J. (2024). The impact of patient engagement on service quality and customer well-being: an introspective analysis from the healthcare providers’ perspective. Cogent Public Health, 11(1). https://doi.org/10.1080/27707571.2024.2340157
Khomkham, P., & Kaewmanee, P. (2024). Patient motivation: A concept analysis. Belitung Nursing Journal, 10(5), 490–497. https://doi.org/10.33546/bnj.3529
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