JMIR mHealth and uHealth

Physical activity is central to maintaining the quality of life for patients with complex chronic conditions and is thus at the core of neurorehabilitation. However, maintaining activity improvements in daily life is challenging. The novel Stay With It program aims to promote physical activity after neurorehabilitation by cultivating self-monitoring skills and habits.

There is growing interest in enhancing stroke self-management support using mobile health (mHealth) technology (eg, smartphones and apps). Despite this growing interest, “self-management support” is inconsistently defined and applied in the poststroke mHealth intervention literature, which limits efforts to synthesize and compare evidence. To address this gap in conceptual clarity, a scoping review was conducted.

Reproductive health conditions such as endometriosis, uterine fibroids, and polycystic ovary syndrome (PCOS) affect a large proportion of women and people who menstruate worldwide. Prevalence estimates for these conditions range from 5% to 40% of women of reproductive age. Long diagnostic delays, up to 12 years, are common and contribute to health complications and increased health care costs. Symptom checker apps provide users with information and tools to better understand their symptoms and thus have the potential to reduce the time to diagnosis for reproductive health conditions.

Digital health technologies are widely used for disease management, with their computing platforms, software, and sensors for healthcare. These technologies were developed to manage chronic diseases and infectious bacterial diseases, including tuberculosis (TB).

Physical activity plays a crucial role in maintaining a healthy lifestyle, and wrist-worn wearables, such as smartwatches and smart bands, have become popular tools for measuring activity levels in daily life. However, studies on physical activity using wearable devices have limitations that these studies often rely on a single device model or use improper clustering methods for analyzing the wearable data which are extracted from wearable devices.

In contemporary society, age tech (age technology) represents a significant advancement in health care aimed at enhancing patient engagement, ensuring sustained independence, and promoting quality of life for older people. One innovative form of age tech is the intelligent toilet seat, which is designed to collect, analyze, and provide insights based on toileting logs and excreta data. Understanding how older people perceive and interact with such technology can offer invaluable insights to researchers, technology developers, and vendors.

Pelvic floor dysfunction is a public health issue, with 1 in 3 women experiencing symptoms at some point in their lifetime. The gold standard of treatment for pelvic floor dysfunction is supervised pelvic floor muscle training (PFMT); however, adherence to PFMT in women is poor. Mobile apps are increasingly being used in the National Health Service to enable equity in the distribution of health care and increase accessibility to services. However, it is unclear how PFMT mobile apps influence PFMT adherence in women.

Mobile ecological momentary assessment (EMA) is a powerful tool for collecting real-time and contextual data from individuals. As our reliance on online technologies to increase convenience accelerates, the way we access food is changing. Online food delivery (OFD) services may further encourage unhealthy food consumption habits, given the high availability of energy-dense, nutrient-poor foods. We used EMA to understand the real-time effects of OFD on individuals’ food choices and consumption behaviors.

Smartphone-based emergency response apps are increasingly being used to identify and dispatch volunteer first responders (VFRs) to medical emergencies to provide faster first aid, which is associated with better prognoses. Volunteers’ availability and willingness to respond are uncertain, leading in recent studies to response rates of 17% to 47%. Dispatch algorithms that select volunteers based on their estimated time of arrival (ETA) without considering the likelihood of response may be suboptimal due to a large percentage of alerts wasted on VFRs with shorter ETA but a low likelihood of response, resulting in delays until a volunteer who will actually respond can be dispatched.

Many smartphone apps designed to assist individuals in managing their weight are accessible, but the assessment of app quality and features has predominantly taken place in Western countries. Nevertheless, there is a scarcity of research evaluating weight management apps in China, which highlights the need for further investigation in this area.

There are more than 350,000 digital health interventions (DHIs) in the app stores. To ensure that they are effective and safe to use, they should be assessed for compliance with best practice standards.

Physical inactivity is a global health issue, and mobile health (mHealth) applications (apps) are expected to play an important role in promoting physical activity. Empirical studies have demonstrated the efficacy and efficiency of app-based interventions, and an increasing number of apps with more functions and richer content have been released in markets. Regardless of the success of mHealth apps, there are important evidence gaps in the literature; that is, it is largely unknown who uses what app functions and which functions are associated with physical activity