JMIR Aging
Using technological innovations and data science to inform and improve health care services and health outcomes for older adults.
Editor-in-Chief:
Yun Jiang, PhD, MS, RN, FAMIA, University of Michigan School of Nursing, USA; and Jinjiao Wang, PhD, RN, MPhil, University of Texas Health Science Center, USA
Impact Factor 4.6 More information about Impact Factor CiteScore 6.4 More information about CiteScore
Recent Articles


Nutritional status is an influential factor for functional status and rehabilitation outcomes in patients undergoing geriatric rehabilitation. Although there is evidence for the potential of eHealth interventions in patients undergoing geriatric rehabilitation in general, the evidence for eHealth interventions with a focus on nutrition is scarce. In other target groups with older people, eHealth applications to support nutrition, such as computer-based food records, have been used successfully.

Older adults in affordable housing face heightened risks of social isolation and loneliness due to limited social networks, transportation barriers, chronic conditions, and inadequate technology access. Smart speakers offer potential for enhancing social connectedness in this underserved population, yet technology interventions are rarely designed with meaningful input from older adults themselves. User-centered design (UCD) approaches can address this gap by engaging end users throughout the development process to ensure technology solutions align with their needs and living contexts.

Age-related cognitive decline can threaten independence in older adults, creating an urgent need for effective and practical preventive strategies. Nonpharmacological approaches such as physical activity, cognitive stimulation, and combined programs show promise, but their comparative effectiveness and the specific cognitive domains they influence are not yet clearly established.

Wearables such as smartwatches can support point-of-care health management for older adults while reducing pressure on health care systems as aging populations grow. Although many studies emphasize technical accuracy, user-centered research on smartwatch adoption among older adults remains limited, particularly in low- and middle-income countries, such as Bangladesh.


Sedentary behavior (SB) is a critical, modifiable risk factor for adverse health outcomes. Evidence suggests that SB is higher among individuals with cognitive impairment relative to their cognitively healthy peers. However, the nature and extent of SB across cognitive impairments remains unclear, largely due to the reliance on self-report data and the lack of synthesized evidence from more accurate methodology, such as wearable devices. Wearable device–based methodologies offer a reliable means of capturing SB in real-world settings, circumventing the recall bias inherent to self-report methods. Continuous remote monitoring of SB, via wearable devices, may provide nuanced insights important for understanding SB’s contribution to cognitive impairment and health consequences.


Continuous advancements in voice artificial intelligence technologies aim to assist older adults and caregivers, potentially improving quality of life and reducing caregiving burdens. Although research has explored the potential of voice-enabled artificial intelligence (VAI) assistants, such as Alexa (Amazon.com, Inc) and Google Home, to support older adults’ health in informal care settings, there remains a significant gap in understanding the ethical dimensions and values that may influence their future adoption by caregivers and care recipients.


Postoperative frailty is highly prevalent among older adults undergoing hip surgery and is closely linked to poor clinical outcomes. Despite growing interest in understanding its progression, the temporal patterns of frailty remain underexplored. Moreover, there is a lack of validated models that can predict frailty trajectories and stratify patients by risk in the early postoperative period.
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