JMIR Aging

Demoralization negatively affects the quality of life, especially in people with mental disorders.

The use of emergency medical services in Germany has significantly increased, particularly for nonemergency cases. This issue becomes especially relevant for nursing homes, where staff is confronted with resource shortages and organizational challenges, making emergency medical services involvement a common course of action. This leads to potentially avoidable hospitalizations for nursing home residents and exposes them to severe health risks, such as nosocomial infections. To address this, we developed the Optimal@NRW project, implementing an innovative intersectoral telemedicine intervention that includes an early warning system and mobile nonphysician medical assistants in order to enable outpatient treatment in acute medical cases for nursing home residents. We hypothesize that hospitalizations could be significantly reduced, as patients could be treated on-site in the absence of a life-threatening emergency.

Older adults often express positive attitudes toward digital health technologies in surveys, yet adoption remains low. Self-report measures may not capture automatic affective reactions such as anxiety or distrust. Implicit paradigms such as the affect misattribution procedure (AMP) can reveal these automatic attitudes, but parameters optimized for younger adults may not be suitable for older adults because of age-related slowing and changes in visual processing.

The “aged” filter has gone viral on TikTok. This filter leverages AI to superimpose signs of aging, such as wrinkles, crow’s feet, and sagging skin, onto a user’s face. Notably, several dermatologists have attested to the accuracy of this filter in simulating the effects of aging. Reactions among the TikTok community have been mixed, with some utterly dismayed but others wholeheartedly embracing the sight of their aged visages.

Leprosy is endemic in many low-income countries, affecting mainly the poorest communities. The disease can lead to sensorimotor functional losses that can predispose patients to reduced independence. In older adults, these losses associated with leprosy are added to those already resulting from natural aging and associated comorbidities, which can contribute to the clinical picture of frailty syndrome in these older adults. Early detection of frailty can reduce several serious consequences for these individuals, preventing loss of quality of life and financial costs to patients and the health care system. Sensors built into smartphones have been proposed as low-cost, and highly sensitive tools for detecting motor loss and could help monitor the risk of some frailty features in older people affected by leprosy.

China’s rapidly aging population and high burden of frailty make proactive preparation for future care increasingly urgent, yet few older adults engage in such preparation. Existing interventions often overlook the heterogeneity between prefrail and frail populations and lack precision-oriented digital strategies.

Intergenerational communication has been recognized as a key factor in enhancing social connections among older adults by improving the quality of interactions, which is a crucial component of healthy aging. However, effective interventions to foster intergenerational communication and engagement remain scarce at this stage.

Exergames, which combine physical exercise with interactive gameplay, are increasingly being incorporated into fall prevention programs for older adults. Gamified elements, such as real-time feedback and progress tracking, may enhance motivation, engagement, and adherence. Although several systematic reviews have examined the effects of exergaming on balance and physical function, fewer have focused specifically on clinically meaningful outcomes, such as falls and injurious falls, or on indicators that may influence real-world adoption of exergames.

Rapid population aging and a worsening shortage of care workers necessitate the identification of older adults who require proactive interventions. Although machine learning (ML) has been increasingly applied in gerontology, existing studies have predominantly focused on social isolation, loneliness, depression, falls, and frailty in isolation rather than on the integrated construct of care needs.

The swift pace of digital transformation has heightened individuals’ dependence on digital technologies. This makes it imperative to explore how individual factors such as digital self-efficacy and social capital affect satisfaction with the daily life changes stemming from digital transformation. This investigation is particularly essential among middle-aged and older adults because they encounter numerous challenges and opportunities from digital transformation.

Physical and cognitive function, both of which decline with aging, are significantly interrelated. Although numerous studies have investigated the effect of physical exercise on cognitive function, relatively few have examined the impact of pure cognitive training on physical performance.

Artificial intelligence (AI) has the potential to improve health among older adults, yet how different stakeholders decide to develop, finance, and adopt AI innovations is not well understood.