JMIR Aging

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.

By 2050, 22% of the global population will be aged 60 years or older, with Europe experiencing rapid aging. This increase in chronic diseases and functional decline demands a shift from fragmented, hospital-centric care to continuous care models. The World Health Organization’s healthy aging framework prioritizes intrinsic capacity (IC)—defined as physical and mental abilities across the locomotion, vitality, sensory, cognition, and psychology domains. Digital health solutions enable remote monitoring but face barriers, such as low digital literacy and usability challenges among older adults.

Age-related cognitive and sensorimotor declines co-occur and reinforce one another, increasing vulnerability to functional dependence and falls. Exergaming offers integrated cognitive-motor training, but most systems lack features that support personalized care for socially vulnerable, community-dwelling older adults. Low-income older adults receiving Public Community Care services bear a disproportionate burden of cognitive and sensorimotor decline, yet remain underrepresented in digital health research. As part of a broader program to develop a digital health monitoring-to-intervention framework, we evaluated a pressure sensor–based exergame designed to deliver targeted cognitive-motor training within the existing Public Community Care infrastructure.

Multidomain dementia-prevention interventions delivered via apps have the potential to reach large populations. However, existing trials have tended to recruit more socioeconomically advantaged participants, raising concerns that the resulting interventions may be less usable for older adults from minority ethnic, lower educational, or lower socioeconomic backgrounds, who are at higher risk of dementia. The Tailored Intervention for Brain Health and Cognitive Enrichment (ENHANCE) app was designed to address this by prioritizing accessibility and engagement across diverse user groups.

The population of adults aged 65 and older is rapidly increasing, while the availability of caregivers is declining. Smart homes that provide unobtrusive, continuous monitoring and alerting on clinically relevant changes in daily activity patterns offer a potentially innovative solution for aging in place.

Many clinically relevant aspects of health are expressed through behavior, affect, and interaction, and therefore rely on observation rather than instrumental measurement; yet such information is often documented infrequently in routine care. Dementia, and particularly behavioral and psychological symptoms of dementia (BPSD), is a relevant case because symptoms fluctuate across time and context. Little is known about how structured daily symptom assessment can be integrated into routine dementia care practice.

Gamified digital training may support long-term engagement in aging populations, yet randomized evidence linking behavioral effects to convergent neuroimaging outcomes remains limited.