JMIR Research Protocols

There is growing evidence that noncommunicable diseases (NCDs) can be attributable to unhealthy lifestyle habits. However, there has been little application of this knowledge in primary health care (PHC).

People with COVID-19 are instructed to self-isolate at home. During self-isolation, they may experience anxiety and insufficient care. Patient portals can allow patients to self-monitor and remotely share their health status with health care professionals, but little data are available on their feasibility.

Youth with cerebral palsy do not have enjoyable, accessible, and scalable exercise options that can empower them to independently maintain their cardiometabolic health.

Type 2 Diabetes (T2D) is common, with a prevalence of approximately 7% of the population in the United Kingdom. The quality of T2D care is inconsistent across the United Kingdom, and Greater Manchester (GM) does not currently achieve the National Institute for Health and Care Excellence treatment targets. Barriers to delivery of care include low attendance and poor engagement with local T2D interventions, which tend to consist of programs of education delivered in traditional, face-to-face clinical settings. Thus, a flexible approach to T2D management that is accessible to people from different backgrounds and communities is needed. Diabetes My Way (DMW) is a digital platform that offers a comprehensive self-management and educational program that should be accessible to a wide range of people through mobile apps and websites. Building on evidence generated by a Scotland-wide pilot study, DMW is being rolled out and tested across GM.

Predictive theoretical models suggest that health knowledge works in conjunction with motivation and behavioral skills to influence adolescents’ obesogenic behavior. However, most of the existing adolescent interventions target these variables in isolation. Furthermore, health literacy (HL), a precursor to health knowledge, is necessary for translating health knowledge into behavior and is negatively related to adolescents’ obesity status. However, HL has not been included in obesity interventions targeting adolescents.

e-Waste is a rapidly growing waste stream worldwide, and Bangladesh is a hub of e-waste handling. Informal e-waste recycling operations involve crude methods for dismantling, repairing, sorting, and recycling electronic goods with bare hands and without personal health protections. Direct inhalation or dermal exposure to toxicants during informal recycling is common. Evidence suggests that e-waste–derived toxicants pollute the terrestrial ecosystem and have been linked with adverse health effects. However, e-waste recycling–related occupational health hazards have not been adequately explored in the context of Bangladesh.

Despite showing strong evidence of positive outcomes, a common problem in the field of digital health is poor engagement and adherence. Non–health care, for-profit digital ventures, such as Facebook, LinkedIn, and Twitter, conduct behavioral experiments to increase user engagement. To our knowledge, digital health organizations have not published similar types of experiments in ad libitum environments, and there are limited published data indicating whether nudges and prompts can be leveraged to increase engagement with digital health interventions.

Early childhood development is highly dependent on the sensitive care provided by caregivers, and interventions focused on supporting parents to improve their sensitivity have shown to be effective. The COVID-19 pandemic has had a significant impact on mental health, with pregnant women and mothers of infants being an especially vulnerable group and maternal sensitivity particularly affected. However, access to face-to-face interventions is restricted; thus, it is important to have remote interventions to support this group of mothers.

Policies that promote aging in place are common in Sweden and many other countries. However, the current housing stock cannot sufficiently accommodate a population aging in place considering how functional capacity and housing needs change as people age. To be suitable for all regardless of their functional ability, housing should be designed or adapted to facilitate the performance of activities of daily living. Long-term planning and plausible projections of development 20 to 30 years into the future are needed.

Overweight and obesity are serious public health concerns. As the prevalence of excess weight among individuals continues to increase, there is a parallel need for inexpensive, highly accessible, and evidence-based weight loss programs.

Adherence to care plans is a major issue in health care systems. Improved adherence has several potential benefits such as ensuring treatment effectiveness and control of chronic diseases. There is currently a lack of tools to maximize treatment adherence in an integrated manner, that is, covering multiple aspects of patients’ health continuously throughout their medical care. To ensure better adherence, such tools must meet the needs of patients with chronic conditions as well as those of health care professionals. Acknowledging the health issues associated with nonadherence to treatment, an industry-research-clinical partnership aims to adapt a digital platform—facilitating patient-health care professional interactions—to improve therapeutic adherence in patients with chronic illnesses. The platform allows for exchanges between patients and health care professionals to facilitate the timing of medication use or chronic disease management and maximize patient adherence.

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic, complex, heterogeneous disease that affects millions and lacks both diagnostics and treatments. Big data, or the collection of vast quantities of data that can be mined for information, have transformed the understanding of many complex illnesses, such as cancer and multiple sclerosis, by dissecting heterogeneity, identifying subtypes, and enabling the development of personalized treatments. It is possible that big data can reveal the same for ME/CFS.