Construction and Application of an Intelligent Collaborative Cardiac Rehabilitation App for Middle-aged and Young Patients With Myocardial Infarction

NCT ID: NCT07289815

Last Updated: 2025-12-17

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

NOT_YET_RECRUITING

Clinical Phase

NA

Total Enrollment

232 participants

Study Classification

INTERVENTIONAL

Study Start Date

2026-01-01

Study Completion Date

2028-12-31

Brief Summary

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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.

Detailed Description

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Conditions

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Myocardial Infarction Cardiac Rehabilitation APP

Study Design

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Allocation Method

NON_RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

TREATMENT

Blinding Strategy

NONE

Study Groups

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experimental group, On the basis of conventional rehabilitation guidance, the "Cardiac Rehabilitatio

Group Type EXPERIMENTAL

Cardiac Rehabilitation Management App

Intervention Type BEHAVIORAL

Develop a targeted and actionable health management APP focusing on five major health issues (diet, medication, exercise, psychology, and smoking cessation). The experimental group will use it for check-in, while the APP will be equipped with a management mechanism, and the intervention will last for 6 months.

normal group, conventional rehabilitation guidance

Group Type ACTIVE_COMPARATOR

Conventional Rehabilitation Guidance

Intervention Type BEHAVIORAL

① Before discharge, cardiologists will provide face-to-face health education to patients, covering the rehabilitation goals of myocardial infarction (MI), risk factor control, dietary recommendations, exercise precautions, medication adherence, and prevention of common complications.② Patients will be given a uniformly compiled printed Cardiac Rehabilitation Guidance Manual for self-directed reading and learning.③ After discharge, the responsible nurse will conduct health follow-ups via phone call or WeChat at the 1st week, 1st month, 3rd month, and 6th month to monitor rehabilitation progress and medication compliance, and provide targeted guidance.

Interventions

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Cardiac Rehabilitation Management App

Develop a targeted and actionable health management APP focusing on five major health issues (diet, medication, exercise, psychology, and smoking cessation). The experimental group will use it for check-in, while the APP will be equipped with a management mechanism, and the intervention will last for 6 months.

Intervention Type BEHAVIORAL

Conventional Rehabilitation Guidance

① Before discharge, cardiologists will provide face-to-face health education to patients, covering the rehabilitation goals of myocardial infarction (MI), risk factor control, dietary recommendations, exercise precautions, medication adherence, and prevention of common complications.② Patients will be given a uniformly compiled printed Cardiac Rehabilitation Guidance Manual for self-directed reading and learning.③ After discharge, the responsible nurse will conduct health follow-ups via phone call or WeChat at the 1st week, 1st month, 3rd month, and 6th month to monitor rehabilitation progress and medication compliance, and provide targeted guidance.

Intervention Type BEHAVIORAL

Eligibility Criteria

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Exclusion Criteria

* ① Complicated with severe hepatic or renal insufficiency, malignant tumors, cognitive impairment, or mental illnesses; ② Patients with NYHA class Ⅳ or definite exercise contraindications (e.g., those assessed as high-risk in exercise risk evaluation) who are unable to participate in exercise prescription intervention; ③ Patients who have difficulty completing follow-up or withdraw midway.
Minimum Eligible Age

18 Years

Maximum Eligible Age

60 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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The Fourth Affiliated Hospital of Zhejiang University School of Medicine

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Central Contacts

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Jingjing Cao

Role: CONTACT

Phone: 86-13858061081

Email: [email protected]

Other Identifiers

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KY-2025-302

Identifier Type: -

Identifier Source: org_study_id