Numerous telemonitoring projects in many countries have been carried out in the public healthcare sector. This research aimed to identify factors predicting practical telemonitoring acceptance and validate a telemonitoring acceptance model for chronically-ill patients in public healthcare. This study developed an Integrated Telemonitoring Acceptance (ITA) model, based on the unified theory of acceptance and use of technology, innovation diffusion theory, and perceived risk theory, to identify predictive factors of telemonitoring acceptance. Data were collected using a survey administered to 116 chronically-ill patients who have experienced telemonitoring. We used Partial Least Squares (PLS) regression to test the hypothetical model. We identified six predictive factors of telemonitoring acceptance and found that social influence conditions strongly affect telemonitoring acceptance. Amidst the global phenomenon of an aging population, the study proves valuable in providing insight into the potential implication of telemonitoring self-care service for chronically-ill patients thus playing a major role in the future of public healthcare.
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