JMIR mHealth and uHealth

Artificial intelligence–assisted interactive health promotion systems are useful tools for the management of musculoskeletal conditions.

Delays in the diagnosis of neurodevelopmental disorders (NDDs) in toddlers and postnatal depression (PND) in mothers are major public health issues. In both cases, early intervention is crucial.

The prevalence of obesity in India is increasing at an alarming rate. Obesity-related mHealth apps have proffered an exciting opportunity to remotely deliver obesity-related information. This opportunity raises the question of whether such apps are truly effective.

Children and adolescents increasingly do not meet physical activity (PA) recommendations. Hence, insufficient PA (IPA) and sedentary behavior (SB) among children and adolescents are relevant behavior change domains for using individualized mobile health (mHealth) interventions.

Mobile health (mHealth) interventions may help adolescents adopt healthy lifestyles. However, attrition in these interventions is high. Overall, there is a lack of research on nonusage attrition in adolescents, particularly regarding the role of socioeconomic status (SES).

As the global burden of chronic conditions increases, their effective management is a concern. Although the need for chronic disease management using mobile self-management health care apps is increasing, there are still many barriers to their practical application in the primary care field.

Women’s mobile health (mHealth) is a growing phenomenon in the mobile app global market. An increasing number of women worldwide use apps geared to female audiences (female technology). Given the often private and sensitive nature of the data collected by such apps, an ethical assessment from the perspective of data privacy, sharing, and security policies is warranted.

Mobile health (mHealth) tools have emerged as a promising health care technology that may contribute to cost savings, better access to care, and enhanced clinical outcomes; however, it is important to ensure their acceptance and adoption to harness this potential. Patient adoption has been recognized as a key challenge that requires further exploration.

Patients suffering from inflammatory bowel disease (IBD) frequently need long-term medical treatment. Mobile apps promise to complement and improve IBD management, but so far there has been no scientific analysis of their quality.

In the era of digital health information technology, there has been a proliferation of devices that collect patient-generated health data (PGHD), including consumer blood pressure (BP) monitors. Despite their widespread use, it remains unclear whether such devices can improve health outcomes.

Over the past decade, the wide availability and small size of different types of sensors, together with the decrease in pricing, have allowed the acquisition of a substantial amount of data about a person’s life in real time. These sensors can be incorporated into personal electronic devices available at a reasonable cost, such as smartphones and small wearable devices. They allow the acquisition of images, audio, location, physical activity, and physiological signals among other data. With these data, usually denoted as lifelog data, we can then analyze and understand personal experiences and behaviors. This process is called lifelogging.

Over the past decade, the wide availability and small size of different types of sensors, together with the decrease in pricing, have allowed the acquisition of a substantial amount of data about a person’s life in real time. These sensors can be incorporated into personal electronic devices available at a reasonable cost, such as smartphones and small wearable devices. They allow the acquisition of images, audio, location, physical activity, and physiological signals among other data. With these data, usually denoted as lifelog data, we can then analyze and understand personal experiences and behaviors. This process is called lifelogging.