JMIR mHealth and uHealth

Accurate limb circumference measurement is essential for the diagnosis and management of lymphedema, facilitating the objective evaluation of treatment outcomes and early detection of disease progression. Although manual tape measurements are inexpensive and widely used, they are limited by interobserver variability and low reproducibility. Advanced modalities such as computed tomography and magnetic resonance imaging provide high precision but are costly and impractical for routine or home-based use. To overcome these limitations, we developed and validated a novel 3D measurement system that integrates a marker-based bodysuit (ZOZOSUIT2) with a smartphone app, enabling fast, accurate, and reproducible limb circumference assessment.

Asthma remains one of the most serious chronic diseases of childhood. Individuals with severe asthma experience sudden episodes of breathlessness due to acute airflow obstruction, leading to recurrent pediatric intensive care unit (PICU) admissions that often result in mechanical ventilation and even death. Existing clinical assessments lack temporal resolution to effectively track the rapidly changing physiology.

Artificial intelligence (AI)–driven pose estimation (PE) offers a scalable and cost-effective solution to track exercises in mobile health apps. However, occlusion, influenced by camera angle and distance, can reduce detection accuracy and repetition counting precision. The influence of smartphone positioning on these performance metrics remains underexplored in controlled studies.

The Chinese National Guidelines on Diagnosis and Treatment of Gonorrhea (2020) recommend ceftriaxone 1 g intramuscularly as a single dose for the treatment of uncomplicated gonococcal infections. However, nonadherence to the guidelines remains common among physicians in China, partly due to their poor awareness of the recommendations.

Despite the high prevalence of type 2 diabetes mellitus in China, few patients are achieving adequate management targets. While digital behavior change interventions (DBCIs) are promising solutions, sustained long-term user engagement with these new technologies remains challenging.

Mobile health (mHealth) apps are widely available, and some have proven safe and effective for management of specific chronic conditions. Despite a high degree of interest, the potential of these technologies has yet to be realized. Patient and clinician attitudes are key factors that influence the adoption of mHealth apps but remain poorly understood, particularly in the United States.

Effective self-management of type 1 diabetes mellitus (T1DM) by children and adolescents remains challenging despite advances in insulin delivery and glucose monitoring technologies. Mobile health (mHealth) interventions have emerged as promising tools to support pediatric diabetes care. However, their clinical impact and the behavioral mechanisms through which they operate—particularly those grounded in social cognitive theory (SCT)—are not well established.

Chronic spontaneous urticaria (CSU) is characterized by recurrent wheals or angioedema lasting for more than 6 weeks and substantially affecting the quality of life. Given its fluctuating course, accurate symptom monitoring is essential. Mobile health apps (MHAs) offer promising tools for real-time symptom tracking, patient education, and communication. Systematic evaluation of existing MHAs for CSU is critical to inform the development of effective, patient-centered digital solutions.

Digital health interventions incorporating self-management strategies are increasingly used to support individuals in managing depression. These interventions often leverage self-monitoring and passive sensor-based data collection to provide personalized feedback, guiding behavioral change. With the proliferation of smartphones and wearable devices, there is growing potential to continuously collect behavioral and physiological data. However, a major limitation in the field is the lack of consolidated evidence on which specific parameters are most useful for monitoring and predicting depression-related outcomes.

Nutritional and exercise interventions have shown beneficial effects after gastrectomy for gastric cancer. While digital health tools show promise in cancer care, their long-term effectiveness in patients with gastric cancer remains unclear. In addition, large-scale studies of personalized interventions initiated in the immediate postoperative period are lacking.

The growth of mobile health has underscored the critical importance of equitable internet access in promoting healthy aging. Among older adults, particularly those in digitally underserved populations, access to mobile data is often limited due to affordability and technological barriers, leading to a phenomenon known as “data deprivation.” This form of digital inequality limits the older adults’ ability to participate in social, recreational, and community-based activities, which are protective against isolation and decline in later life. In South Korea, where unlimited smartphone data plans have become increasingly accessible, a unique opportunity exists to examine the real-world association of improved data accessibility on older adults’ social lives and digital engagement.

China’s diabetes epidemic faces critical gaps in glycemic control, with only 50.1% of treated patients achieving hemoglobin A (HbA) targets in 2021. Conventional interventions struggle with scalability in primary care, particularly for vulnerable populations.