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This study is guided by the intervention mapping theory, combined with Fogg's behavior model and digital health technologies, focusing on the key rehabilitation obstacles and behavioral characteristics of young and middle-aged MI patients. It constructs a "smart + collaborative" out-of-hospital rehabilitation management model. This model, through systematic needs assessment and problem logical modeling [11], develops individualized rehabilitation paths covering multiple dimensions of intervention such as exercise, diet, medication, and psychological regulation. It relies on digital means such as mobile terminals, online education, behavior check-ins, real-time feedback, and remote follow-ups to achieve intelligent rehabilitation management. At the same time, it emphasizes the multi-disciplinary collaboration mechanism, integrating team members from cardiology, nursing, nutrition, rehabilitation, and psychology, forming a collaborative work system with information sharing, task complementarity, and consistent goals. Together, they promote the activation of patient motivation, improvement of behavioral ability, and improvement of rehabilitation compliance. The study will also verify its feasibility and initial effects in a real clinical environment, and evaluate its practical value in improving rehabilitation behaviors, promoting functional recovery, and enhancing quality of life. This study not only innovatively integrates intervention mapping and behavioral science models into the rehabilitation management of young and middle-aged MI patients in theory, filling the gap in existing rehabilitation models for this group, but also explores the path of digital rehabilitation intervention that can be promoted and replicated in grassroots clinical practice. The research results can provide practical basis for the construction of the smart rehabilitation service system under the background of "Healthy China 2030", and have important practical significance and social value.
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232 participants in 2 patient groups
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Jingjing Cao
Data sourced from clinicaltrials.gov
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