Telemedicine and AI-Powered Chatbots: Potential and Challenges for Home Care Provided by Family Caregivers

Background/Objectives: The digitization of care opens up new opportunities to support family caregivers, who play a key role in home care. While telemedicine applications have already shown initial relief effects, AI-supported chatbots are increasingly coming into focus as an innovative form of digital support. The aim of this study was to build on an earlier study on the integration of telemedicine into home care and to conduct a complementary study on AI-based chatbots to analyze their acceptance, perceived benefits, and potential barriers from the perspective of family caregivers. Methods: The study comprises two consecutive online surveys with a total of n = 62 family caregivers. The first study assessed the use and acceptance of telemedicine systems; the second complementary survey examined attitudes toward AI-supported chatbots. Both questionnaires were developed based on a systematic literature review and in accordance with the Technology Acceptance Model (TAM). The dimensions of user-friendliness, data protection, communication support, emotional relief, and training needs were among those recorded. The data were evaluated using descriptive statistics, including comparative analyses between the two studies. Results: The results show that family caregivers generally have a positive attitude toward digital health solutions, but at the same time identify specific barriers. While technical barriers and privacy concerns dominated the telemedicine study, the AI results place greater emphasis on psychosocial factors. It also became clear that participants assumed that chatbots would be more acceptable if they were designed to be empathetic and dialogue-oriented. A comparison of the two data sets shows that the perceived benefits of digital systems are shifting from functional support to interactive, emotional support. Conclusions: The results suggest that AI-powered chatbots could offer significant added value to family caregivers by combining information sharing, emotional support, and self-reflection. In doing so, they expand the focus of traditional telemedicine to include a communicative and psychosocial dimension. Future research should examine the actual user experience and effectiveness of such systems in longitudinal and qualitative designs. Despite limitations in terms of sample representativeness and hypothetical usage estimates, the study makes an important contribution to the further development of digital care concepts and the ethically responsible integration of AI into home care.