Digital health technologies, apps, and informatics for patient education, medicine and nursing, preventative interventions, and clinical care / home care for elderly populations
Editor-in-Chief: Jing Wang, PhD, MPH, RN, FAAN, Dean and Professor, Florida State University College of Nursing, Tallahassee, FL, USA
Jing Wang, PhD, MPH, RN, FAAN, Dean and Professor, Florida State University College of Nursing, Tallahassee, FL, USA
JMIR Aging (JA, Founding Editor-in-chief: Jing Wang, PhD, MPH, RN, FAAN, Dean and Professor, Florida State University College of Nursing, Tallahassee, FL, USA) is an open access journal, focusing on technologies, medical devices, apps, engineering, informatics applications and patient education for medicine and nursing, education, preventative interventions and clinical care / home care for elderly populations. In addition, aging-focused big data analytics using data from electronic health record systems, health insurance databases, federal reimbursement databases (e.g. U.S. Medicare and Medicaid), and other large databases are also welcome.
This journal is read by clinicians, nurses/allied health professionals, informal caregivers and patients alike and have (as all JMIR journals) a focus on readable and applied science reporting the design and evaluation of health innovations and emerging technologies. We publish original research, viewpoints, and reviews (both literature reviews and medical device/technology/app reviews).
JMIR Aging is indexed in PubMed Central (PMC), PubMed, and Scopus. Upon acceptance, an article processing fee will apply.
Mobile health (mHealth) apps using novel visual mapping assistive technology can allow users to develop personalized maps that aid people living with cognitive impairment in the recall of steps needed to independently complete activities of daily living (ADLs), such as bathing, toileting, and dressing.
The worldwide increase in community-dwelling people with dementia underscores the need for innovative eHealth technologies that aim to provide support to both patients and their informal caregivers in the home setting. However, sustainable implementation of eHealth technologies within this target group can be difficult.
The continuous growth of the older adult population will have implications for the organization of health and social care. Potentially, in-home monitoring unobtrusive sensing systems (USSs) can be used to support formal or informal caregivers of older adults, as they can monitor deviant physical and physiological behavior changes. Most existing USSs are not specific to older adult care. Hence, to facilitate the implementation of existing USSs in older adult care, it is important to know which USSs would be more suitable for older adults.
During the COVID-19 pandemic, the depression level among US adults has significantly increased. Age disparity in depression during the pandemic has been reported in recent studies. Delay or avoidance of medical care is one of the collateral damages associated with the COVID-19 pandemic, and it can lead to increased morbidity and mortality.
Numerous living labs have established a new approach for studying the health, independent living, and well-being of older adults with dementia. Living labs interact with a broad set of stakeholders, including students, academic institutions, private companies, health care organizations, and patient representative bodies and even with other living labs. Hence, it is crucial to identify the types of cocreations that should be attempted and how they can be facilitated through living labs.
As life expectancy grows, so do the challenges of caring for an aging population. Older adults, including people with dementia, want to live independently and feel in control of their lives for as long as possible. Assistive technologies powered by artificial intelligence and internet of things devices are being proposed to provide living environments that support the users’ safety, psychological, and medical needs through remote monitoring and interventions.
Barriers to assessing depression in advanced dementia include the presence of informant and patient recall biases. Ecological momentary assessment provides an improved approach for mood assessment by collecting observations in intervals throughout the day, decreasing recall bias, and increasing ecological validity.
Smartwatches enable physicians to monitor symptoms in patients with knee osteoarthritis, their behavior, and their environment. Older adults experience fluctuations in their pain and related symptoms (mood, fatigue, and sleep quality) that smartwatches are ideally suited to capture remotely in a convenient manner.
A disproportionate number of COVID-19 cases affect older, minority populations. Obese older adults are at higher risk of developing severe COVID-19 complications and lower survival rates, and minority older adults often experience higher rates of obesity. A plant-based diet intervention may improve COVID-19-related modifiable risk factors for obesity. Encouraging the consumption of plant-based diets comprising vegetables, fruits, whole grains, legumes, seeds, and nuts by utilizing community outreach strategies and digital technology can contribute to improving COVID-19 risk factors among this population.
Falling is one of the most common and serious age-related issues, and falls can significantly impair the quality of life of older adults. Approximately one-third of people over 65 experience a fall annually. Previous research has shown that physical exercise could help reduce falls among older adults and improve their health. However, older adults often find it challenging to follow and adhere to physical exercise programs. Interventions using mixed reality (MR) technology could help address these issues. MR combines artificial augmented computer-generated elements with the real world. It has frequently been used for training and rehabilitation purposes.