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Barriers and Enablers to Routine Clinical Implementation of Cardiac Implantable Electronic Device Remote Monitoring in Australia Among Cardiologists, Cardiac Physiologists, Nurses, and Patients: Interview Study

Barriers and Enablers to Routine Clinical Implementation of Cardiac Implantable Electronic Device Remote Monitoring in Australia Among Cardiologists, Cardiac Physiologists, Nurses, and Patients: Interview Study

CIED: cardiac implantable electronic device; CVD: cardiovascular disease; TDF: theoretical domains framework. The main benefits noted by stakeholders included the improved patient treatment outcomes facilitated by RM (Quotes 1-3 in Table S1 in Multimedia Appendix 2).

Brodie Sheahen, Edel T O'Hagan, Kenneth Cho, Tim Shaw, Astin Lee, Sean Lal, Aaron L Sverdlov, Clara Chow

JMIR Cardio 2025;9:e67758

Effectiveness of a WeChat Mini Program–Based Intervention on Promoting Multiple Health Behavior Changes Among Chinese Patients With Cardiovascular Diseases in Home-Based Rehabilitation: Randomized Controlled Trial

Effectiveness of a WeChat Mini Program–Based Intervention on Promoting Multiple Health Behavior Changes Among Chinese Patients With Cardiovascular Diseases in Home-Based Rehabilitation: Randomized Controlled Trial

Cardiac rehabilitation, a critical component of comprehensive CVD management, has been demonstrated to be effective in preventing disease progression and recurrence [4]. It provides patients with CVD with guidance on adopting a healthy lifestyle, emphasizing the importance of engaging in adequate physical activity (PA; eg, ≥150 min of moderate-to-vigorous PA [MVPA] per week) and maintaining a nutritious diet (eg, ≥5 servings of fruit and vegetables per day) [5].

Yanping Duan, Wei Liang, Lan Guo, Huimin Zhan, Chunli Xia, Huan Ma, Borui Shang, Yanping Wang, Min Yang, Shishi Cheng

J Med Internet Res 2025;27:e66249

The Influence of eHealth Stress Management Interventions on Psychological Health Parameters in Patients With Cardiovascular Disease: Systematic Review and Meta-Analysis

The Influence of eHealth Stress Management Interventions on Psychological Health Parameters in Patients With Cardiovascular Disease: Systematic Review and Meta-Analysis

The link between stress and mental health disorders, as well as between stress and CVD, is well-documented [18-20]. Reducing stress is crucial for cardiovascular risk. Since mental health disorders often create barriers to seeking professional help, e Health interventions can provide more accessible options for stress management.

Ouahiba El-Malahi, Darya Mohajeri, Alexander Bäuerle, Raluca Ileana Mincu, Christos Rammos, Christoph Jansen, Martin Teufel, Tienush Rassaf, Julia Lortz

J Med Internet Res 2025;27:e67118

Telemedicine Booths for Screening Cardiovascular Risk Factors: Prospective Multicenter Study

Telemedicine Booths for Screening Cardiovascular Risk Factors: Prospective Multicenter Study

Cardiovascular disease (CVD) is the leading cause of death worldwide [1]. In France, the disease affects around 7.9% of the population and causes around 140,000 deaths each year, which is only exceeded by deaths caused by cancer [2,3]. The health care costs are substantial, representing around 10% of the country’s health care reimbursements [4]. The burden of CVD is likely to increase over the coming years due to an aging population and is thus a major cause for concern [4].

Mélanie Decambron, Christine Tchikladze Merand

JMIR Hum Factors 2025;12:e57032

Psychological eHealth Interventions for Patients With Cardiovascular Diseases: Systematic Review and Meta-Analysis

Psychological eHealth Interventions for Patients With Cardiovascular Diseases: Systematic Review and Meta-Analysis

Inclusion criteria Population: studies that included individuals with a medical diagnosis of cardiovascular disease (CVD), including arrhythmia, heart failure, valve disease, and cardiomyopathy, as well as studies that included a mixture of patients with CVD and at high CVD risk.

Jing Jing Su, Rose Lin, Ladislav Batalik, Arkers Kwan Ching Wong, Sherry L Grace

J Med Internet Res 2025;27:e57368

The Construction and Application of a Clinical Decision Support System for Cardiovascular Diseases: Multimodal Data-Driven Development and Validation Study

The Construction and Application of a Clinical Decision Support System for Cardiovascular Diseases: Multimodal Data-Driven Development and Validation Study

The high incidence of cardiovascular disease (CVD) is an important public health problem worldwide. CVD remains the leading cause of mortality worldwide and a major contributor to disability. CVD was responsible for 18.6 million deaths according to the 2019 Global Burden of Disease study. China is one of the countries most burdened by CVD [1]. In 2021, approximately 5.1 million individuals lost their lives to CVD in China [2].

Shumei Miao, Pei Ji, Yongqian Zhu, Haoyu Meng, Mang Jing, Rongrong Sheng, Xiaoliang Zhang, Hailong Ding, Jianjun Guo, Wen Gao, Guanyu Yang, Yun Liu

JMIR Med Inform 2025;13:e63186

Estimating Trends in Cardiovascular Disease Risk for the EXPOSE (Explaining Population Trends in Cardiovascular Risk: A Comparative Analysis of Health Transitions in South Africa and England) Study: Repeated Cross-Sectional Study

Estimating Trends in Cardiovascular Disease Risk for the EXPOSE (Explaining Population Trends in Cardiovascular Risk: A Comparative Analysis of Health Transitions in South Africa and England) Study: Repeated Cross-Sectional Study

Sixth, the 1-year risk of CVD is calculated as the product of the joint HR and the group-specific annual CVD event rate. Seventh, the 1-year survival is calculated as the exponential of the negative value of the 1-year risk of CVD (eg, a 1-year CVD risk of 0.06 translates to a 1-year survival of exp(–0.06)=0.942). In the eighth stage, the cumulative survival is calculated as the product of the 1-year survival in year T and the survival in year T–1.

Shaun Scholes, Jennifer S Mindell, Mari Toomse-Smith, Annibale Cois, Kafui Adjaye-Gbewonyo

JMIR Cardio 2025;9:e64893

Targeting Key Risk Factors for Cardiovascular Disease in At-Risk Individuals: Developing a Digital, Personalized, and Real-Time Intervention to Facilitate Smoking Cessation and Physical Activity

Targeting Key Risk Factors for Cardiovascular Disease in At-Risk Individuals: Developing a Digital, Personalized, and Real-Time Intervention to Facilitate Smoking Cessation and Physical Activity

The leading cause of disease burden across the globe is cardiovascular disease (CVD) [1]. Over the years, CVD prevalence and the number of CVD deaths have increased; in 2019, there were 523 million cases of CVD and 18.6 million deaths due to CVD [1]. CVD mortality is decreasing in most European countries, yet there are still 3.9 million deaths yearly [2,3]. Important behavioral CVD risk factors include smoking, low physical activity, unhealthy diet, and alcohol use [2,4].

Anke Versluis, Kristell M Penfornis, Sven A van der Burg, Bouke L Scheltinga, Milon H M van Vliet, Nele Albers, Eline Meijer

JMIR Cardio 2024;8:e47730