Abstract
Background: The high mortality and recurrence rates associated with coronary heart disease (CHD) impose substantial health care costs and economic burdens globally. Identifying effective interventions to improve patient outcomes is paramount. Digital health technologies (DHTs) offer novel solutions to overcome the challenge of low participation rates in traditional cardiac rehabilitation (CR).
Objective: This review aims to systematically map the scope of application, intervention objectives, and evaluation metrics of DHTs in CR for patients with CHD, thereby providing a structured evidence base for future research and practice.
Methods: This scoping review adheres to the Joanna Briggs Institute’s methodology and is reported according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. A systematic search was conducted across 5 major databases, PubMed, Web of Science, Embase, Cochrane Library, and EBSCO, covering the period from inception to February 2026. Inclusion criteria were developed based on the participants, concept, and context framework. Studies focused on the application of various DHTs within CR settings for patients with CHD. Eligible literature comprised randomized controlled trials, quasi-randomized controlled trials, and longitudinal before-and-after studies published in peer-reviewed journals. Two researchers (XZ and ZL) independently conducted literature screening and data extraction. Findings were presented through a comprehensive narrative synthesis and evidence gap maps.
Results: A total of 43 studies were included, predominantly randomized controlled trials (n=40). Findings revealed (1) diverse technological formats, categorized into 3 main types: digital health tools, real-time remote support, and asynchronous communication. Multitechnology combined interventions have become the mainstream model (36/43, 83.7%). (2) Intervention objectives were multifaceted, consolidating into 4 dimensions: motivation and guidance, knowledge and skills, monitoring and security, and social and group dynamics. (3) Evaluation metrics were multidimensional, encompassing clinical physiological indicators, health behaviors, patient-reported outcomes, service use rates, and technological feasibility. DHTs demonstrated positive effects in improving short-term physiological function and health behaviors; however, evidence remains insufficient regarding their impact on long-term clinical outcomes such as reducing adverse events.
Conclusions: The innovation of this scoping review lies in integrating highly heterogeneous evidence to reveal the field’s evolution from isolated tools toward systematic, integrated solutions. Research confirms that DHTs effectively overcome temporal and spatial constraints, enhancing rehabilitation accessibility and engagement. They serve as crucial strategic tools for bridging geographical disparities in health care resources and advancing equity in cardiovascular health services. However, the evidence base remains limited, including insufficient long-term efficacy data and inadequate exploration of vulnerable populations such as older people and those with low digital literacy. Future research urgently requires large-scale, long-term follow-up clinical trials, alongside enhanced studies on adaptability for specific populations and considerations of health equity. This will propel digital CR toward greater scientific rigor, universal applicability, and precision.
doi:10.2196/85917
Keywords
Introduction
Background
The World Health Organization’s (WHO) report on the world’s top 10 causes of death indicates that cardiovascular disease (CVD) claims the highest number of lives, with coronary heart disease (CHD) accounting for 13% of global mortality []. Beyond the health burden, CVD, particularly CHD, imposes a significant economic strain. Globally, CHD accounts for 42% of total CVD expenditure, with annual per capita expenditure on CHD reaching 4.9% to 137.8% of per capita gross domestic product []. This underscores how CHD has become a “heavy burden” weighing upon individuals, families, society, and health care systems. More notably, despite substantial investment, the overall prognosis for patients with CHD has yet to improve effectively.
In response to this challenge, cardiac rehabilitation (CR) has demonstrated significant value as a comprehensive intervention. Research indicates that CR can reduce cardiovascular adverse events by 28%, 1-year readmission rates by 31%, and mortality by 24% while effectively reducing health care expenditure [-]. It is recommended as a class Ia evidence-based intervention in clinical guidelines [,]. However, participation rates in CR programs remain universally low among patients with CHD globally [-]. Rates range from 9.7% to 22.5% in Germany, 20% to 30% in the United States, and a mere 41.5% in the United Kingdom [-]. Asian nations present similarly unfavorable figures: Singapore at 12.3% and Japan and South Korea between 14% and 50% [,-]. As the most populous developing nation, China has CR centers constituting merely 0.06% of all medical institutions, with underdeveloped regions accounting for a mere 8.8% []. Beyond awareness factors, limitations inherent to traditional CR, such as transport difficulties, time conflicts, and uneven resource distribution, constitute primary barriers to participation [].
At this intersection of practical need and technological innovation, digital health technologies (DHTs) have transcended the constraints of conventional CR, forging novel pathways for its implementation []. In 2019, the WHO formally introduced the concept of DHTs, defining them as the field of developing and using digital technologies to disseminate health knowledge and facilitate related practices []. This encompasses applications of technologies such as the Internet of Things and artificial intelligence within health management []. Digital devices such as pedometers, accelerometers, and smartphones enable daily activity tracking, exercise intensity assessment, and personalized exercise guidance for patients with CHD [,]. Smart pillboxes and “digital pills” facilitate real-time monitoring of medication adherence [,]. Thus, DHTs overcome temporal and spatial constraints to deliver more accessible rehabilitation support. They effectively alleviate resource scarcity issues and hold promise for extending benefits to a broader population with CHD [,].
In summary, DHTs offer novel solutions to low CR participation rates. However, their highly heterogeneous delivery formats result in fragmented evidence. Compared to traditional review methodologies, scoping reviews can integrate heterogeneous evidence and define research boundaries [-]. Therefore, in this study, we use a scoping review approach to systematically collate evidence in this field, providing a holistic perspective for subsequent research and policy formulation. This aims to bridge gaps in cardiovascular health accessibility and advance the scientific, universal, and sustainable development of digital CR.
Objectives and Research Questions
In this study, we aim to systematically review the scope of DHT applications in CR for patients with CHD through a scoping literature review methodology. It seeks to provide evidence-based guidance for the diversified development and effective implementation of future CR.
Our research will clarify (1) the application strategies and scenarios of existing digital technologies in CR for patients with CHD; (2) the key performance indicators determining the effectiveness of current DHT applications, alongside identifying their primary challenges; and (3) how DHTs can be more effectively applied to CR for patients with CHD and future research directions.
Methods
Overview
In this study, we strictly followed the Joanna Briggs Institute’s scoping review methodology framework to ensure methodological rigor and transparency in the research process [,]. This scoping review adhered strictly to a structured research process, using standardized methodologies to ensure the reliability of findings and their practical applicability. The research involved comprehensive systematic literature searches, data extraction, and evidence synthesis analysis, culminating in a narrative synthesis of studies concerning the application of DHTs in CR for patients with CHD. As a scoping review, our primary objective is to systematically map the current application, intervention formats, and outcome measures of DHTs in CR for patients with CHD. It does not evaluate intervention effectiveness or evidence quality grades; consequently, no rigorous methodological quality assessment of included studies was conducted []. Our review was reported according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines []. The PRISMA-ScR checklist is provided in .
Eligibility Criteria
The inclusion criteria for this scoping review were based on the Joanna Briggs Institute Scope Review Methodology Guide and structured using the participants, concept, context framework []. The inclusion and exclusion criteria are presented in .
Inclusion criteria
- All patients diagnosed with coronary heart disease, irrespective of nationality, gender, or ethnic background. Coronary heart disease encompasses, but is not limited to, the following clinical presentations: stable angina pectoris, acute coronary syndromes (including unstable angina pectoris, non–ST-segment elevation myocardial infarction, and ST-segment elevation myocardial infarction), and patients who have undergone percutaneous coronary intervention or coronary artery bypass grafting.
- Focus on the various digital health technologies used in cardiac rehabilitation (CR), including but not limited to mobile health apps, wearable devices, telemedicine or remote monitoring platforms, educational modules delivered via web-based or online platforms, virtual reality, and text messaging.
- The context of interest pertains to the application of digital health technologies within CR, where such technologies serve as complementary, alternative, augmenting, or extended means to traditional CR. Their purpose is to support, optimize, or enhance the delivery of CR services. This context is not restricted to specific countries or health care systems, permitting the inclusion of studies from diverse cultural, geographical, or medical settings.
- The types of literature included are empirical studies, which must be published in peer-reviewed journals. The study designs encompass randomized controlled trials, quasi-randomized controlled trials, and longitudinal before-and-after studies.
Exclusion criteria
- Research participants who have undergone cardiac or cardiopulmonary transplantation or patients with chronic heart failure.
- Studies involving participants younger than 18 years of age.
- Non-English language literature, duplicated publications, gray literature, studies where the full text is unavailable, conference abstracts, review papers, or qualitative research.
Information Sources
We conducted systematic searches of the following 5 electronic databases: PubMed, Web of Science (Clarivate), Embase (Elsevier), Cochrane Library (Wiley), and EBSCO (EBSCOhost). Searches were performed independently within each database interface, without using cross-database simultaneous search functionality.
Search Strategy
The literature search process for this study was reported in accordance with the PRISMA-S (extension to the PRISMA Statement for Reporting Literature Searches in Systematic Reviews) guidelines []. The search strategy was independently developed by the research team based on the databases’ subject term lists, without direct adaptation or use of other published scoping review strategies. The complete search strategies for each database are detailed in . The researchers first conducted a preliminary search in the PubMed database to expand the keywords and use MeSH to determine standardized subject terms. Following this, a search strategy was developed, and an initial search was conducted in PubMed, with a brief analysis of the results. Two researchers collaboratively developed the final search strategy, which was reviewed by a third researcher. The PubMed search strategy is detailed in . To maintain sensitivity, no restrictions were applied regarding study design, language, or publication type. The search time frame spanned from the inception of each database to February 2026. Furthermore, as this scoping review aimed to map published evidence to delineate the existing evidence base, clinical trial registries were excluded from the search.
((((((((((((((((“Coronary Disease”[Mesh]) OR (“Myocardial Infarction”[Mesh])) OR (“Coronary Artery Disease”[Mesh])) OR (“Coronary Heart Disease*“[Title/Abstract])) OR (“Heart Attack*“[Title/Abstract])) OR (“Myocardial Infarct*“[Title/Abstract])) OR (“Cardiovascular Stroke*“[Title/Abstract])) OR (“acute coronary syndrome”[Title/Abstract])) OR (“angina pectoris”[Title/Abstract])) OR (“STEMI”[Title/Abstract])) OR (“NSTEMI”[Title/Abstract])) OR (“PCI”[Title/Abstract])) OR (“percutaneous coronary intervention”[Title/Abstract])) OR (“CABG”[Title/Abstract])) OR (“coronary artery bypass grafting”[Title/Abstract]))
AND
((((((((((((((((((((((((((((((((“Telemedicine”[Mesh]) OR (“Wearable Electronic Devices”[Mesh])) OR (“Digital Health”[Mesh])) OR (“Remote Patient Monitoring”[Mesh])) OR (“Text Messaging”[Mesh])) OR (“Virtual Medicine”[Title/Abstract])) OR (“Tele-Referral*“[Title/Abstract])) OR (“Mobile Health”[Title/Abstract])) OR (“mHealth”[Title/Abstract])) OR (“Telehealth”[Title/Abstract])) OR (“eHealth”[Title/Abstract])) OR (“Tele Intensive Care”[Title/Abstract])) OR (“Tele Care”[Title/Abstract])) OR (“Wearable Device*“[Title/Abstract])) OR (“Wearable Technolog*“[Title/Abstract])) OR (“Wearable Computer”[Title/Abstract])) OR (“Digital Health Technolog*“[Title/Abstract])) OR (“Health Technolog*“[Title/Abstract])) OR (“Short Message Service”[Title/Abstract])) OR (“digital therapeutics”[Title/Abstract])) OR (“smartwatch”[Title/Abstract])) OR (“fitness tracker”[Title/Abstract])) OR (“activity tracker”[Title/Abstract])) OR (“tele-rehabilitation”[Title/Abstract])) OR (“virtual care”[Title/Abstract])) OR (“mobile phone”[Title/Abstract])) OR (“cell phone”[Title/Abstract])) OR (“application”[Title/Abstract])) OR (“internet-based”[Title/Abstract])) OR (“web-based”[Title/Abstract])) OR (“online program”[Title/Abstract])))
AND
((((((((((((((((((“Cardiac Rehabilitation”[Mesh]) OR (“Secondary Prevention”[Mesh])) OR (“Cardiac Rehabilitation*“[Title/Abstract])) OR (“Cardiovascular Rehabilitation*“[Title/Abstract])) OR (“Secondary Prevention*“[Title/Abstract])) OR (“Disease Prevention*“[Title/Abstract])) OR (“Secondary Disease Prevention*“[Title/Abstract])) OR (“Early Therap*“[Title/Abstract])) OR (“Relapse Prevention*“[Title/Abstract])) OR (“exercise training”[Title/Abstract])) OR (“physical activity”[Title/Abstract])) OR (“lifestyle modification”[Title/Abstract])) OR (“behavior change”[Title/Abstract])) OR (“self-management”[Title/Abstract])) OR (“Exercise Therapy”[Title/Abstract])) OR (“Patient Education”[Title/Abstract])) OR (“Risk Factor Management”[Title/Abstract])) OR (“Medication Adherence”[Title/Abstract]))
Selection of Sources
The literature retrieval and screening process were independently conducted by 2 researchers trained in evidence-based medicine and possessing cardiovascular research experience, with the entire procedure subject to third-party oversight. The specific workflow was as follows: (1) Search results from all databases were imported into EndNote (Clarivate) reference management software, which automatically identified and excluded duplicate records; (2) 2 researchers independently conducted an initial screening of the remaining literature based on predefined inclusion and exclusion criteria, reviewing titles and abstracts; (3) screening results were cross-checked; discrepancies were resolved through third-party discussion until consensus was reached; and (4) full-text evaluation of initially selected papers determined final inclusion in the study.
Data Charting Process and Items
Data extraction was conducted using predesigned standardized forms by 2 researchers independently using Microsoft Excel to extract content covering the following core elements: (1) basic information: author, year of publication, and country; (2) study design: study type, sample size, follow-up duration, and control group configuration; (3) population characteristics: disease type; (4) intervention details: type of DHT, intervention duration, frequency of use, combination use, and combination method; (5) intervention objective; (6) outcome measures: primary outcomes and secondary outcomes; and (7) key findings: intervention effectiveness. In the event of disagreement during data extraction, a third researcher shall arbitrate the resolution.
Results
Selection of Sources of Evidence
As illustrated in , this study strictly adhered to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) process for literature screening []. The initial search yielded 8156 publications. After removing 2320 duplicates using EndNote, 2 researchers (XZ and ZL) independently screened titles and abstracts. Based on predefined inclusion criteria, 5836 publications were excluded. The remaining 407 publications underwent full-text assessment, resulting in the exclusion of 364 publications that did not meet the requirements. Ultimately, 43 studies were included in the analysis.

Characteristics of Sources of Evidence
presents an overview of the 43 included studies by year and geographical distribution. The publication span of the included studies ranges from 2014 to 2026, with a marked increase in relevant research since 2021, with 60.5% of studies published from 2021 to 2026. The geographical coverage spans 18 countries, with China accounting for the highest proportion of studies at 34.9% (15/43) [,-].
Of the 43 studies included in total, the vast majority used randomized controlled designs, comprising 33 randomized controlled trials [,,,,,-] and 7 randomized controlled pilot studies [,,,,-]. Among the remaining studies, 2 were quasi-randomized controlled trials [,], and 1 was a controlled before-and-after study []. Detailed characteristics of the studies included in this scoping review are presented in .

| Author (year) | Country | Design | Population (sample size) | Type and duration of intervention | Outcome measures | Statistically significant | Forms of intervention | Objectives of the intervention |
| Krzowski et al (2023) [] | Poland | RCT | Patients after acute myocardial infarction (n=100) |
|
| Partially valid |
|
|
| Hong et al (2021) [] | China | RCT | Patients with coronary artery disease (n=60) |
|
| Valid |
|
|
| Chan et al (2022) [] | China | RCT pilot | Patients with stable coronary artery disease (n=139) |
|
| Valid |
|
|
| Varnfield et al (2014) [] | Australia | RCT | Patients after myocardial infarction (n=120) |
|
| Valid |
|
|
| Duan et al (2018) [] | China | RCT pilot | Patients with coronary artery disease (n=136) |
|
| Valid |
|
|
| Xu et al (2024) [] | China | RCT | Patients with CHD after PCI (n=147) |
|
| Valid |
|
|
| Avila et al (2018) [] | Belgium | RCT | Patients with coronary artery disease (n=90) |
|
| Valid |
|
|
| Nishio et al (2025) [] | Japan | RCT pilot | Patients with coronary artery disease (n=50) |
|
| Partially valid |
|
|
| Li et al (2022) [] | China | RCT pilot | Patients with coronary artery disease (n=300) |
|
| Valid |
|
|
| Cruz-Cobo et al (2024) [] | Spain | RCT | Patients with acute coronary syndrome after PCI (n=300) |
|
| Valid |
|
|
| Bernal-Jiménez et al (2024) [] | Spain | RCT | Patients with CHD after PCI (n=128) |
|
| Valid |
|
|
| Bae et al (2021) [] | Korea | RCT | Patients after the first PCI (n=879) |
|
| Invalid |
|
|
| Su and Yu (2021) [] | China | RCT | Patients with coronary artery disease (n=146) |
|
| Valid |
|
|
| Dodson et al (2025) [] | United States | RCT | Patients aged 65 years or older with ischemic heart disease (n=400) |
|
| Partially valid |
|
|
| Dorje et al (2019) [] | China | RCT | Patients with CHD after PCI (n=312) |
|
| Valid |
|
|
| Hisam et al (2022) [] | Pakistan | RCT | After an acute coronary syndrome (n=160) |
|
| Valid |
|
|
| Zheng et al (2024) [] | China | RCT | Patients with CHD after PCI (n=106) |
|
| Valid |
|
|
| Ma et al (2021) [] | China | Q-RCT | Patients with CHD after PCI (n=335) |
|
| Valid |
|
|
| Xu et al (2024) [] | China | RCT | Patients with coronary artery disease (n=108) |
|
| Valid |
|
|
| Widmer et al (2017) [] | United States | RCT | Patients with acute coronary syndrome after PCI (n=80) |
|
| Partially valid |
|
|
| Yudi et al (2021) [] | Australia | RCT | Patients with acute coronary syndromes (n=206) |
|
| Valid |
|
|
| Gallagher et al (2023) [] | Australia | RCT | Patients with coronary artery disease (n=390) |
|
| Invalid |
|
|
| Wohlfahrt et al (2024) [] | Czech Republic | RCT pilot | Patients after myocardial infarction (n=64) |
|
| Valid |
|
|
| Ramachandran et al (2025) [] | Singapore | RCT pilot | Patients after acute myocardial infarction (n=50) |
|
| Valid |
|
|
| Jo et al (2024) [] | Korea | RCT | Patients after acute myocardial infarction (n=48) |
|
| Invalid |
|
|
| Fallah et al (2025) [] | Iran | RCT | Patients with myocardial infarction (n=144) |
|
| Valid |
|
|
| Li et al (2023) [] | China | RCT pilot | Patients with acute myocardial infarction after PCI (n=60) |
|
| Valid |
|
|
| Waranski et al (2024) [] | Germany | Q-RCT | Patients with coronary artery disease (n=169) |
|
| Valid |
|
|
| Ni et al (2022) [] | China | RCT | Patients with coronary artery disease (n=230) |
|
| Valid |
|
|
| Liu et al (2026) [] | China | RCT | Patients after PCI (n=180) |
|
| Valid |
|
|
| Bruggmann et al (2021) [] | Switzerland | RCT | Patients with acute coronary syndromes (n=60) |
|
| Partially valid |
|
|
| Zhang et al (2025) [] | China | RCT | Patients with coronary artery disease (n=62) |
|
| Valid |
|
|
| Patterson et al (2023) [] | Australia | RCT | Patients with coronary artery disease (n=120) |
|
| Invalid |
|
|
| Batalik et al (2020) [] | Czech Republic | RCT | Patients with coronary artery disease (n=56) |
|
| Invalid |
|
|
| Dalli Peydró et al (2022) [] | Spain | RCT | Patients with acute coronary syndromes (n=67) |
|
| Valid |
|
|
| Bravo-Escobar et al (2017) [] | Spain | RCT | Patients with stable, intermediate-risk coronary artery disease (n=28) |
|
| Partially valid |
|
|
| Widmer et al (2015) [] | United States | CBA | Patients after myocardial infarction (n=42) |
|
| Valid |
|
|
| Johnston et al (2016) [] | Sweden | RCT | Patients after myocardial infarction (n=174) |
|
| Valid |
|
|
| Kumar et al (2024) [] | India | RCT | Patients after CABG (n=40) |
|
| Valid |
|
|
| Bretschneider et al (2024) [] | Germany | RCT | Patients with coronary artery disease (n=354) |
|
| Valid |
|
|
| Herring et al (2021) [] | Britain | RCT | Patients with coronary artery disease (n=291) |
|
| Invalid |
|
|
| Li et al (2025) [] | China | RCT | Patients with coronary artery disease (n=294) |
|
| Valid |
|
|
| Khikmatova Madina et al [] (2025) | Uzbekistan | RCT | Patients after myocardial infarction (n=300) |
|
| Valid |
|
|
aInformation regarding authors, publication year, participants, study design, study outcomes, and methodology for 43 studies. Digital health technology intervention name: zero-time exercise (ZTEx), care assessment platform of cardiac rehabilitation (CAP-CR), nurse-led eHealth cardiac rehabilitation (NeCR), mobile health cardiac rehabilitation (mHealth-CR), smartphone and social media–based cardiac rehabilitation and secondary prevention (SMART-CR/SP), mobile health augmented cardiac rehabilitation (MCard), home-based cardiac telerehabilitation (HCT), home-based cardiac rehabilitation (HBCR), digital health intervention (DHI), smartphone-based cardiac rehabilitation program (S-CRP), fifth generation mobile communication technology Internet of Things platform (5G IoT platform), persuasive systems design (PSD), coronary artery bypass grafting (CABG), internet-based cardiac rehabilitation enhancement (i-CARE).
bRCT: randomized controlled trial.
cNT-proBNP: N-terminal pro-brain natriuretic peptide.
dIPAQ: International Physical Activity Questionnaire.
eCR: cardiac rehabilitation.
fCHD: coronary heart disease.
gPCI: percutaneous coronary intervention.
hSCeiP: Self-Monitoring, Coaching, e-Health, Interactive Feedback, and Personalization.
i6MWD: 6-minute walk distance.
jSF-12: Short Form 12 Health Survey.
kFBIS: Framingham Burden of Illness Scale.
lLVEF: left ventricular ejection fraction.
mQ-RCT: quasi-randomized controlled trial.
nMET: metabolic equivalents of task.
oARMS: Adherence to Refills and Medications Scale.
pHETAQ: Home-Based Cardiac Rehabilitation Adherence Questionnaire.
qSF-36: Short Form 36 Health Survey.
rCBA: controlled before-after study.
sWHOQOL-BREF: World Health Organization Quality of Life-BREF.
tGPAQ: Global Physical Activity Questionnaire.
uHeartQoL: Heart Disease-Specific Quality of Life Questionnaire.
vSC-CHDI: Self-Care Behaviour in Coronary Heart Disease Inventory.
Results of Individual Sources of Evidence
In this study, we analyzed data from 43 research papers and generated an evidence gap map () illustrating the application forms and objectives of DHT interventions.
| Author (year) | Forms of intervention | Objectives of the intervention | ||||||||||||||||||||||||
| Wearable devices | Application | Website | Digital video | Social media platform | Telephone | Group meeting | Remote counseling sessions | SMS text messaging | Goal setting | Feedback | Reward mechanism | Gamification | Alerts and reminders | Personalization | Health education | Training courses | Data monitor | Real-time monitoring | Ensuring safety | Remotely adjust prescription | Peer effect | Social support | Emotional support | Counseling | ||
| Krzowski et al (2023) [] | ✓ | ✓ | ✓ | ✓ | ||||||||||||||||||||||
| Hong et al (2021) [] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | |||||||||||||||||||
| Chan et al (2022) [] | ✓ | ✓ | ✓ | ✓ | ✓ | |||||||||||||||||||||
| Varnfield et al (2014) [] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | |||||||||||||||||||
| Duan et al (2018) [] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ||||||||||||||||||||
| Xu et al (2024) [] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ||||||||||||||||
| Avila et al (2018) [] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | |||||||||||||||||
| Nishio et al (2025) [] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ||||||||||||||||||||
| Li et al (2022) [] | ✓ | ✓ | ✓ | ✓ | ✓ | |||||||||||||||||||||
| Cruz-Cobo et al (2024) [] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ||||||||||||||
| Bernal-Jiménez et al (2024) [] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | |||||||||||||||
| Bae et al (2021) [] | ✓ | ✓ | ✓ | ✓ | ||||||||||||||||||||||
| Su and Yu (2021) [] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | |||||||||||||||
| Dodson et al (2025) [] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ||||||||||||||||||
| Dorje et al (2019) [] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ||||||||||||||||||
| Hisam et al (2022) [] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ||||||||||||||||||
| Zheng et al (2024) [] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ||||||||||||||||||
| Ma et al (2021) [] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ||||||||||||||||||
| Xu et al (2024) [] | ✓ | ✓ | ✓ | |||||||||||||||||||||||
| Widmer et al (2017) [] | ✓ | ✓ | ✓ | ✓ | ||||||||||||||||||||||
| Yudi et al (2021) [] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | |||||||||||||||||||
| Gallagher et al (2023) [] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ||||||||||||||||||
| Wohlfahrt et al (2024) [] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ||||||||||||||||||||
| Ramachandran et al (2025) [] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | |||||||||||||||
| Jo et al (2024) [] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | |||||||||||||||||
| Fallah et al (2025) [] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ||||||||||||||||||||
| Li et al (2023) [] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | |||||||||||||||||
| Waranski et al (2024) [] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | |||||||||||||||||||
| Ni et al (2022) [] | ✓ | ✓ | ✓ | ✓ | ||||||||||||||||||||||
| Liu et al (2026) [] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ||||||||||||||||||||
| Bruggmann et al (2021) [] | ✓ | ✓ | ✓ | ✓ | ||||||||||||||||||||||
| Zhang et al (2025) [] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | |||||||||||||||||||
| Patterson et al (2023) [] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ||||||||||||||||||||
| Batalik et al (2020) [] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | |||||||||||||||||||
| Dalli Peydró et al (2022) [] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ||||||||||||||||||||
| Bravo-Escobar et al (2017) [] | ✓ | ✓ | ✓ | ✓ | ✓ | |||||||||||||||||||||
| Widmer et al (2015) [] | ✓ | ✓ | ✓ | ✓ | ✓ | |||||||||||||||||||||
| Johnston et al (2016) [] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | |||||||||||||||||||
| Kumar et al (2024) [] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ||||||||||||||||||||
| Bretschneider et al (2024) [] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ||||||||||||||||||
| Herring et al (2021) [] | ✓ | ✓ | ✓ | ✓ | ||||||||||||||||||||||
| Li et al (2025) [] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ||||||||||||||||||
| Khikmatova et al (2025) [] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | |||||||||||||||||||
The Form of DHT in CR for Patients With CHD
The 43 studies included in this research demonstrate that DHTs exhibit significant diversity in their application within CR for patients with CHD. These technologies can be categorized into 3 core groups (): digital health tools, real-time remote support, and asynchronous communication. Among these, digital health tools represent the most prevalent intervention form, enabling patients with CHD to undertake self-management and monitoring primarily through devices or software. This includes apps (28/43, 65.1%) [,,-,-,,,,,-,-,,,], wearable devices (22/43, 51.1%) [,,,,,,,,,-,,-,-], websites (9/43, 20.9%) [,,,,,,,,], and social media platforms (6/43, 13.9%) [,,,,,]. Wearable devices encompass smartwatches, heart rate monitors, fitness trackers, and pedometers, primarily used for real-time monitoring of physiological indicators and exercise data. Real-time remote support involves direct interpersonal interaction via voice or video, covering telephone (15/43, 34.8%) [,,,,,,,,,,,,,,], remote counseling sessions, and group meetings. Asynchronous communication delivers reminders, education, and support through non–real-time information exchange, chiefly via SMS text messaging (10/43, 23.2%) [,-,,,,,] and email. As shown in , multitechnology combined interventions have become the predominant model. A substantial 83.7% (36/43) of studies used combinations of 2 or more digital technologies, such as “app+wearable device” [,,,,,,,,-,,] and “social media platform+wearable device+telephone” [,]. Some studies further integrated digital technologies with traditional rehabilitation methods like face-to-face guidance and offline education, forming blended online-offline rehabilitation models. This landscape not only reflects varying levels of technological support, from standalone tools to interpersonal interactions, but also signals the trend toward systematized and diversified digital CR.
| Type | Core functionality | Content |
| Digital health tools | Provide patients with tools for independent health management through a technology platform, emphasizing self-monitoring and personalized interaction. |
|
| Real-time remote support | Provides real-time, person-to-person professional support or peer interaction through synchronous communication technology, with high interactivity. |
|
| Asynchronous communication | Reminders, education, and support are provided through non–real-time information transmission methods, which are flexible and not restricted by time or space. |
|
The Objectives of DHT in CR for Patients With CHD
From the perspective of intervention objectives, the application of DHTs in CHD rehabilitation exhibits distinct functional stratification. Health education (36/43, 83.7%) [,-,-,-,-], data monitor (34/43, 79.1%) [,-,-,-,-,-], and reminders and alerts (18/43, 41.9%) [,,,,,-,,-,,,-] form the core functional layer, each accounting for over 80% of applications in the included studies. Feedback, goal setting, and personalized interventions constitute the secondary core functional layer, with application rates ranging between 50% and 70%. Additionally, some studies integrated distinctive features such as gamification, reward mechanisms, social support, emotional support or counseling, and remotely adjust prescription to address patients’ diverse rehabilitation needs. Building upon this, this study systematically categorized the intervention objectives across 43 publications, identifying 15 specific types grouped into 4 major categories: first, motivation and guidance, encompassing goal setting, feedback, reward mechanisms, gamification, and reminders and alerts, aimed at incentivizing patients with CHD to complete rehabilitation behaviors and enhance adherence; second, foundation of knowledge and skills, centered on health education and training courses to help patients with CHD build the knowledge base and self-management capabilities required for disease management; third, monitoring and security, including data monitoring, real-time monitoring, and ensuring safety for physiological indicator tracking, risk assessment, and safety protection during rehabilitation; and fourth, social and group dynamics, leveraging peer effects and social support mechanisms to use social relationships and group interactions to promote patient adherence to rehabilitation behaviors. The specific composition is detailed in . As shown in , health education emerged most frequently, underscoring the central role of knowledge transfer in contemporary digital rehabilitation practice. Notably, the vast majority of studies adopted multipurpose integrated intervention strategies, organically combining educational, motivational, monitoring, and social support functions rather than relying on single technological approaches. It is precisely this composite application model that has transformed DHTs from fragmented tools into systematic rehabilitation support systems, significantly enhancing the holistic nature and continuity of rehabilitation interventions.
| Type | Core objective | Content |
| Motivation and guidance | Motivate patients and guide them to complete specific behaviors. |
|
| Foundation of knowledge and skills | Provide necessary information and cultivate patients’ self-management skills. |
|
| Monitoring and security | Track data, assess risks, and provide a safety net. |
|
| Social and group dynamics | Using social relationships and group dynamics to promote patient adherence and change. |
|
Evaluation Criteria of DHT in CR for Patients With CHD
The outcome measures included in the study encompass 5 major categories: clinical physiological indicators, rehabilitation behavioral indicators, patient-reported outcomes, rehabilitation service use rates, and technical feasibility. Clinical physiological indicators include peak oxygen uptake, 6-minute walk distance, and blood pressure. Rehabilitation behavioral indicators include exercise adherence, medication adherence, physical activity levels, dietary adherence, and sedentary time. Patient-reported outcomes encompassed quality of life, self-efficacy, anxiety and depression levels, disease knowledge, and rehabilitation satisfaction. Rehabilitation service use metrics included rehabilitation acceptance rate, adherence rate, completion rate, readmission rate, and emergency department visit rate. Technical feasibility referred to patient satisfaction with the DHT used.
Clinical Efficacy and Physiological Indicators
Clinical efficacy and physiological indicators constitute the core dimensions for evaluating the effectiveness of DHTs, with over 60% of studies incorporating them as primary outcomes. These encompass 3 specific levels: cardiopulmonary function, physical capacity and strength, and clinical end-point events. Cardiopulmonary function stands as the most critical indicator, with peak oxygen uptake [,,,,,,,] and 6-minute walk distance [,,,,,,] being the most widely applied measures. Combining remote monitoring, wearable devices, and online guidance can effectively improve patients’ cardiopulmonary function, as measured by peak oxygen uptake and 6-minute walk distance [,]. Physical function and strength serve as supplementary dimensions, encompassing muscle endurance and overall physical capacity. Dalli Peydró et al [] confirmed that remote rehabilitation improves patients’ physical activity capabilities. Regarding clinical end points, over 20 studies evaluated blood pressure, lipid profiles, N-terminal pro-brain natriuretic peptide, and left ventricular ejection fraction. Li et al [] found that app-based interventions increased lipid control rates; however, no consistent conclusions have emerged regarding long-term outcomes such as readmission rates and major adverse cardiovascular events. For instance, Krzowski et al [] did not demonstrate a significant advantage of digital interventions in reducing readmission rates, suggesting that further research is needed to substantiate long-term efficacy.
Health Behavior and Lifestyle
Health behaviors and lifestyle constitute core factors in improving the long-term prognosis of patients with CHD, with over half of the studies incorporating them into evaluations. These are categorized into 2 dimensions: exercise behavior and daily lifestyle. Regarding exercise behavior, key indicators include physical activity levels, exercise adherence, number of exercise days, and duration. Xu et al [] demonstrated in a telerehabilitation study based on the Self-Monitoring, Coaching, e-Health, Interactive Feedback, and Personalization model that the intervention group exhibited significantly superior exercise adherence and duration compared to the control group. Varnfield et al [] confirmed that smartphone-based home rehabilitation effectively enhances physical activity levels in patients with postmyocardial infarction. Optimization of daily lifestyle habits has also garnered significant attention, encompassing indicators such as medication adherence, dietary compliance, fruit and vegetable intake, sedentary time, and smoking cessation behavior. Interventions incorporating digital tools have shown positive effects on dietary adherence, sedentary time, and smoking cessation [,]. DHTs effectively enhance patient motivation for behavioral change through personalized reminders, real-time feedback, and adaptive goal-setting, thereby promoting the sustained maintenance of healthy behaviors.
Patient-Reported Outcomes and Cognitive Function
Patient-reported outcomes and cognitive-related indicators constitute crucial dimensions for evaluating the humanistic value of DHTs. A total of 34 such indicators were incorporated into the studies as assessment criteria, encompassing domains such as quality of life, social cognition and support, disease knowledge, and psychological state [-,-,-,,,,-,,,]. Quality of life emerged as the most frequently assessed outcome, with multiple studies using scales such as the Short Form 36 Health Survey, EQ-5D, and Heart Disease-Specific Quality of Life Questionnaire. Dodson et al [] demonstrated positive trends in mobile health interventions improving health status among older patients, while Hisam et al [] found that mobile health interventions significantly enhanced quality of life in patients with postacute coronary syndrome. Regarding knowledge and self-management capabilities, health education emerged as the most prevalent intervention objective. Its efficacy was evaluated through indicators such as cardiovascular risk factor knowledge and self-management competence. Chan et al [] confirmed that 0-time exercise interventions can enhance patients’ exercise self-efficacy. In the domain of social cognition and support, Duan et al [] incorporated social cognitive outcomes into its evaluation. DHTs effectively enhance patient cognition through personalized education and interactive feedback, providing crucial support for the long-term maintenance of rehabilitation outcomes.
Program Participation and Adherence
Participation rates and adherence in CR are core indicators for assessing the real-world feasibility of DHTs. These encompass rehabilitation program participation rates, adherence rates, completion rates, alongside patient satisfaction and perceived acceptability. Varnfield et al [] found that smartphone-based home rehabilitation significantly improved rehabilitation uptake, adherence, and completion rates among patients with postmyocardial infarction compared to conventional rehabilitation, providing robust evidence for digital technologies enhancing rehabilitation engagement. Ramachandran et al [] further validated the advantages of home-based remote rehabilitation in improving rehabilitation use rates. Patient satisfaction, acceptability, and perceived ease of use of the technology are also crucial evaluation components. Studies by Bernal-Jiménez et al [] and Cruz-Cobo et al [] both incorporated application satisfaction into their evaluation frameworks. Multiple studies indicate that DHTs, through their accessibility, convenience, and interactive features, significantly reduce participation barriers such as geographical constraints and time conflicts, laying a solid foundation for improving rehabilitation participation rates and adherence.
Technical Feasibility, Safety, and Use
Against the backdrop of rapid advancements in DHTs, evaluating their feasibility, safety, and impact on health care service use is particularly crucial. Assessments of technical feasibility encompass device operational stability, data collection integrity, and user-friendliness. Wohlfahrt et al [] demonstrated in their study that smart device step tracking exhibits good feasibility and compliance among patients with postmyocardial infarction. Safety assessments involve adverse event monitoring, data privacy protection, and risk alert mechanisms. Ma et al [] demonstrated in a long-term follow-up study that digital interventions did not increase the risk of major adverse cardiovascular events. Health care use metrics include readmission rates and emergency department visit rates. Widmer et al [] observed a downward trend in readmissions and emergency visits within the digital intervention group, though this did not reach statistical significance. Several studies have mentioned the need for cost-effectiveness analysis of digital rehabilitation, and preliminary explorations suggest that it may have potential economic advantages, but more empirical evidence is needed, though further evidence accumulation remains necessary.
Discussion
Principal Findings
In this study, we used a scoping review methodology to systematically evaluate the current application of DHTs in CR for patients with CHD. The research revealed its core characteristics, including diverse forms of technological application, multidimensional intervention objectives, and multilevel assessment indicators. It integrated 3 categories of technological application forms, 4 categories of intervention objectives, and 5 types of outcome assessment indicators. Findings indicate that DHTs have evolved from supplementary aids to systematic solutions, effectively overcoming the temporal and spatial constraints of traditional rehabilitation. This advance has significantly improved patient engagement in CR and treatment adherence in patients with CHD.
Diversity and Integration of DHTs
Through this scoping review, we found that DHTs show obvious diversity and integration in the form of technology app, which can be divided into 3 main types: digital health tools, real-time remote support, and asynchronous communication. These encompass 10 specific formats including wearable devices, app, website, digital video, social media platform, telephone, group meeting, remote counseling sessions, email, and SMS text messaging. In this scoping review, we found that apps are the main intervention tool for digital CR, and wearable devices are key for real-time data monitoring; their combined application represents the most prevalent model.
From a technical support perspective, digital health tools are primarily oriented toward patient self-management and health monitoring. This aligns with the findings of van Olmen et al [], who concluded that digital health tools can effectively empower individuals to engage in self-management and advance the achievement of relevant health goals. Real-time remote support emphasizes direct interpersonal interaction between clinicians and patients, preserving the inherent humanistic care inherent in traditional health care []. For instance, studies by Ryan et al [] integrated empathy and care into remote interactions, revealing no significant difference in perceived humanistic care compared to in-person consultations. Asynchronous communication, leveraging flexible information delivery, provides patients with continuous health reminders and educational support [].
These 3 complementary levels synergistically construct a multitiered, multidimensional, and comprehensive rehabilitation support system spanning patient self-management to real-time clinician-patient interaction. This provides a viable pathway for developing personalized, multimodal CR models. Notably, some studies further integrate offline face-to-face guidance, forming a blended rehabilitation model combining online and offline approaches [,,,]. This aligns with findings from Thomas et al [], confirming that a comprehensive digital technology app significantly enhances the individualized adaptability of CR. Compared to traditional rehabilitation methods, this blended model partially addresses limitations such as relatively monotonous formats and insufficient consideration of individual differences [].
The Multifaceted Application Objectives of DHTs
In this scoping review, we found that DHTs exhibit multifaceted features in terms of intervention goals, which can be divided into 4 main dimensions: motivation and guidance, foundation of knowledge and skills, monitoring and security, and social and group dynamics. A total of 15 specific objectives have been identified. Health education, data monitoring, and reminders and alerts form the core layer; feedback, goal setting, and personalized interventions constitute the secondary layer; while some studies incorporate distinctive features such as gamification, rewards, and social support.
All interventions integrate multidimensional objectives, with health education appearing most frequently, highlighting the central role of knowledge transfer []. Features like gamification and social support effectively address patient issues such as lack of motivation and difficulty sustaining behavior [,,]. This aligns with the WHO Global Digital Health Strategy’s advocacy for “patient-centered approaches to achieve sustainable behavioral change” []. This multidimensional goal integration enables DHTs to systematically tackle key barriers to participation in traditional CR []. Knowledge gaps can be addressed through health education, motivation deficits remedied by gamified incentives, and sustained support ensured via social interaction []. It is precisely this composite application model that has evolved DHTs from fragmented tools into systematic rehabilitation support systems. This significantly enhances the comprehensiveness and continuity of rehabilitation interventions, providing a crucial pathway for advancing patients with CHD understanding of CR and enabling precision-targeted interventions [].
Effect Evaluation
Analysis of multidimensional assessment indicators across 43 included studies demonstrates that DHTs exhibit clear short-term intervention value for CR of patients with CHD. However, evidence for long-term clinical outcomes remains scarce, strongly aligning with the findings of positive short- to medium-term effects and insufficient long-term evidence.
Regarding clinical physiological indicators, DHTs significantly improve patients’ cardiopulmonary function and physical fitness levels, with statistically significant improvements in core metrics like peak oxygen uptake and 6-minute walk distance observed in intervention groups. They also positively influence blood pressure and lipid control, validating the effectiveness of real-time monitoring and personalized guidance in short-term physiological optimization [,,,,,,,]. At the health behavior level, digital technologies significantly enhance rehabilitation adherence in areas like exercise, medication, and diet through mechanisms such as scheduled reminders and real-time feedback. They also correct unhealthy lifestyle habits like prolonged sitting, aligning with findings where health behaviors serve as core assessment dimensions [,,]. Regarding patient-reported outcomes and rehabilitation service use, digital interventions effectively improve patients’ quality of life, disease awareness, and self-efficacy. They also significantly overcome temporal and spatial constraints, increasing rehabilitation participation and completion rates while alleviating barriers to traditional rehabilitation, consistent with outcome-related findings [,,,].
However, existing studies have not reached a unified conclusion regarding the assessment of long-term clinical outcomes. While some studies observed a downward trend in readmission rates, they failed to demonstrate statistical significance in reducing major adverse cardiovascular events or long-term mortality [,,]. This is closely related to the limited sample sizes and short follow-up periods in most studies, as well as the significant heterogeneity in intervention designs and the lack of systematic long-term rehabilitation management systems. Research on the long-term cost-effectiveness and sustainability of these interventions is also scarce, necessitating further exploration [].
Advantages and Challenges of DHT
The most significant advantage of DHTs lies in their ability to effectively overcome geographical constraints and economic barriers, substantially enhancing the accessibility of CR and patient participation rates []. In this study, we found that by providing easily accessible, user-friendly, and highly interactive digital technologies, it is possible to significantly reduce structural barriers commonly encountered in traditional rehabilitation models, such as transport difficulties, time conflicts, and uneven resource distribution []. Research by Varnfield et al [] confirmed that smartphone-based home rehabilitation significantly outperformed traditional rehabilitation in terms of uptake, adherence, and completion rates among patients with postmyocardial infarction. Ramachandran et al [] further validated the superiority of home-based remote rehabilitation in enhancing rehabilitation use rates. This finding provides a pathway to high-quality rehabilitation services for remote areas with scarce medical resources and for patients with CHD with limited mobility, positioning DHTs as a crucial strategic tool for bridging geographical disparities in health care resources and advancing equity in cardiovascular health services. However, the widespread adoption of digital technologies also presents a new challenge: the “digital divide” []. Older adults, low-income groups, and patients with lower educational attainment may encounter significant difficulties in operating digital devices, using apps, or accessing information [,,].
Therefore, advancing DHT must prioritize equity and inclusivity as core principles []. Simplified interfaces and voice-assisted features tailored for older people and low-skilled users should be developed, alongside personalized, face-to-face training in digital technology use []. Exploring device subsidies or digital equipment loan schemes for vulnerable groups is essential to overcome digital barriers and encourage active participation in digital CR []. Furthermore, key challenges for scaling DHTs include technical feasibility, data security and privacy protection, sustainable cost-effectiveness, and seamless integration of digital interventions into existing clinical workflows []. Currently, while some studies have begun examining implementation-level indicators for DHTs, such as the feasibility of smart device monitoring and remote rehabilitation, overall evidence remains limited. Greater practical research and systematic evaluation are urgently needed to advance the standardized application and long-term development of digital CR models [,].
Limitations
Although we systematically reviewed the current application of DHTs in CR for patients with CHD through a scoping review methodology, several limitations remain. First, regarding literature sources, we only included peer-reviewed empirical research published in English. While this approach helps ensure the quality of included studies, it may overlook important literature published in other languages and relevant gray literature, thereby affecting the comprehensiveness of the study conclusions. Second, significant methodological heterogeneity among the included studies limited the integration and comparability of results. We varied significantly in intervention design, technology combinations, intervention duration, use frequency, participant characteristics, selected outcome measures, and follow-up periods. Furthermore, most studies featured small sample sizes and short follow-up durations, lacking comprehensive assessments of long-term clinical outcomes, cost-effectiveness, intervention sustainability, and impacts on health equity. This limits a thorough evaluation of the long-term value of DHTs.
Conclusions
In this study, we used a scoping review methodology to systematically examine the current application and practical value of DHTs in CR for patients with CHD. Findings confirm that DHTs effectively improve patients’ short-term physiological function and optimize health behaviors. Simultaneously, they overcome limitations in traditional CR regarding spatial-temporal constraints and health care resource allocation, significantly enhancing patient engagement and adherence to rehabilitation programs. In clinical practice, health care providers can integrate multiple DHTs to develop personalized rehabilitation plans tailored to individual characteristics such as patient age, digital literacy, and disease severity, thereby enhancing the precision and adaptability of CR. Future research should prioritize large-scale, multicenter, long-term follow-up randomized controlled trials to thoroughly investigate the impact of DHTs on long-term clinical outcomes for patients with CHD and explore potential mechanisms of action, such as long-term mortality and major adverse cardiovascular events. This will provide more robust evidence-based support for validating their long-term efficacy and advancing standardized clinical implementation.
Acknowledgments
The authors wish to express their gratitude to the librarians who assisted in formulating the retrieval strategy, as well as to all scholars in relevant fields for their accumulated prior research. The authors did not use any artificial intelligence generation tool in the study.
Funding
This work was supported by grants from 2025 Basic Scientific Research Projects of Colleges and Universities in Humanities and Social Sciences Category of Liaoning Provincial Department of Education (LJ112510162012); 2025 Nursing Discipline Research Projects of the Chinese Medical Association Publishing House (CMAPH-NRC2025011). The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Authors' Contributions
Conceptualization: XZ (lead), LL (supporting)
Data curation: XZ (lead), ZL (supporting), LL (supporting), JW (supporting)
Formal analysis: XZ (lead), JW (supporting), ZL (supporting)
Funding acquisition: LL (lead), JW (equal)
Investigation: XZ (lead), ZL (supporting), LL (supporting), JW (supporting)
Methodology: XZ (lead), LL (supporting)
Project administration: MZ (lead), YW (supporting), HL (supporting)
Resources: MZ (lead), YW (equal), HL (equal)
Supervision: LL (lead), HL (supporting), YW (supporting), MZ (supporting)
Writing—original draft: XZ (lead), JW (supporting), YT (supporting)
Writing—review and editing: XZ (lead), JW (supporting), YW (supporting), YT (supporting), LL (supporting), MZ (supporting), HL (supporting)
Conflicts of Interest
None declared.
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Abbreviations
| CHD: coronary heart disease |
| CR: cardiac rehabilitation |
| CVD: cardiovascular disease |
| DHT: digital health technology |
| PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-Analyses |
| PRISMA-S: extension to the PRISMA Statement for Reporting Literature Searches in Systematic Reviews |
| PRISMA-ScR: Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews |
| WHO: World Health Organization |
Edited by Stefano Brini; submitted 15.Oct.2025; peer-reviewed by Kazufumi Kitagaki, Zhen Yang; final revised version received 12.Mar.2026; accepted 12.Mar.2026; published 29.Apr.2026.
Copyright© Xinyu Zhu, Lei Liu, Yingjie Wang, Hongyuan Li, Min Zang, Jiayu Wang, Yu Tian, Zihan Li. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 29.Apr.2026.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research (ISSN 1438-8871), is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.

