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 4.8 CiteScore 6.6
Recent Articles

Personal support workers (PSWs) are often expected to provide ongoing support for complex conditions and have identified an increased need for training in several areas, including dementia and mental health. Web-based interventions may be helpful complements to traditional in-person continuing education and training, but their effectiveness must be explored further.

Dementia is a neurodegenerative condition that combines several diseases and impacts millions around the world and those around them. Agitation and aggression (AA) in people living with dementia (PwD) contribute to distress and increased healthcare demands. Current assessment methods rely on caregiver intervention and manual reporting of incidents, which introduces subjectivity and bias. Artificial Intelligence (AI) and predictive algorithms offer a potential solution for detecting AA episodes in PwD.

In order to address fall underestimation by the International Classification of Diseases (ICD) in clinical settings, incorporating information from clinical notes via Natural Language Processing (NLP) has emerged as a solution. However, its application to inpatient notes has not been fully investigated.



The rising prevalence of mental health conditions such as depression and anxiety among the ageing population underscores the need for accessible and effective psychosocial support, particularly for community-dwelling older adults who face barriers like social stigma and limited mental health literacy. Peer volunteers have emerged as a promising resource to support these individuals, yet often lack the requisite training for effective intervention.

Sedentary behavior is highly prevalent among older adults, with adherence to exercise being a major challenge. Exercise offers significant physical, psychological, and social benefits, but enjoyment is a key factor influencing adherence. Technology-based interventions, have shown promise in enhancing motivation and participation, demonstrating higher adherence rates compared to conventional treatments, though challenges like motivation loss and technological barriers persist. This review evaluates active videogames interventions' effectiveness in enjoyment and satisfaction.

Over half of people over 60 experience cognitive impairment, with limited treatment options, making it crucial to identify risk factors. Studies have examined the association between sarcopenia and cognitive impairment; however, the evidence is inconclusive and cannot be used to make causal inferences.

Walking is frequently recommended as a beneficial physical activity for older adults, as it can enhance both their physical and mental well-being and help prevent cognitive decline and dementia. While it is known that mobile health technology can help improve physical activity among older adults, there is limited research on its effectiveness for older individuals with cognitive impairment.

Game-based cognitive assessments (GBCAs) have the potential to transform the field of cognitive testing by enabling more effective screening of age-related cognitive decline. However, we lack a strong understanding of the usability and overall user experience of these games. This is a risk because the primary target users for GBCAs, older people, are seldom involved in game design research and development.
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