The effectiveness of e-interventions on fall, neuromuscular functions and quality of life in community-dwelling older adults: A systematic review and meta-analysis

06/11/2020

Source: International Journal of Nursing Studies

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Date of publication: January 2021, Vol. 113.

 Publication type: Journal article

In a nutshell: Falls in older adults result in serious, life-limiting consequences. An increasing number of fall prevention interventions have used technology to reduce the number of falls in community-dwelling adults. Various types of e-interventions are being tested in clinical trials and in the community. These include telehealth, exergames, cognitive games, socialized training, smart home systems and non-conventional balance training. Currently, no systematic review and meta-analysis has assessed the overall effectiveness of e-interventions and compared the effectiveness of the different types.

The aim of this review was to synthesize best available evidence concerning the effectiveness of e-interventions on fall, neuromuscular functions and quality of life in community-dwelling older adults.

Length of publication: 12 pages

Some important notes: Please contact your local NHS Library for the full text of the article. Follow this link to find your local NHS Library.


Recruitment and retention of older adults in assisted living facilities to a clinical trial using technology for falls prevention: a qualitative case study of barriers and facilitators

05/10/2020

Source: Health and Social Care in the Community

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Date of publication: 11 September 2020

Publication type: Journal article

In a nutshell: Older adults often have health complexities and higher levels of attrition. Even though they are the main users of healthcare, they are often not included in health research because the health research may not be well designed to accommodate their evolving health needs. One research area in which participation of older adults is essential focuses on improving physical function. In this field, there are many innovations and new technologies developed. Barriers and facilitators to recruit older adults to research that improves physical function by using technology are not well explored yet. This study aims to explore barriers and facilitators regarding recruitment and retention of older adults living in Assisted Living Facilities to a randomised controlled trial study that aimed to improve physical function by using technology.

Some important notes: Please contact your local NHS Library for the full text of the article. Follow this link to find your local NHS Library.


Promoting fall prevention among community dwelling older adults through activLife: a physical and social activation

30/03/2020

Source: Journal of Population Ageing

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Date of publication: 12 February 2020

Publication type: Journal article

In a nutshell: Falls have been recognized as the second leading cause of injury or death for older adults. The related economic burden caused by fall related injuries is not negligible. Earlier research has demonstrated that regular participation in appropriate prescribed physical activity by improving upper and lower limb strength, balance, coordination, transfer skills, and reaction to environmental hazards can lower the risk for falls and fall-related fractures and other injuries. Conversely, physical inactivity can significantly double the risk of developing a disability, which will affect mobility as well as the ability to perform even the most basic activities of daily life, therefore, ultimately increases the older adults’ risk for falls.

This paper first presents a technological solution ActivLife that aims at preventing older adults from falling through practicing physical training in a safe and playful manner, followed by a randomized controlled study with 43 older adults with an average age of 77 for a period of 16 weeks in a social activation center het Ontmoet en Groethuys in Eindhoven, the Netherlands to demonstrate to what extent ActivLife could help to prevent falling among older adults.

Some important notes: Please contact your local NHS Library for the full text of the article. Follow this link to find your local NHS Library.


Strengthening family caregiving through innovative technology solutions

03/12/2019

Source: Innovations in Aging

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Date of publication: 3 November 2019

 Publication type: Journal article

In a nutshell: Technology has the potential to enhance the repertoire of tools for family caregiving to address the complexities of caring for older adults. There are examples of technology-enabled interventions helping older adults remain independent and safe in their home; easing the financial, physical, and psychological challenges of family caregiving; assisting in the management of chronic illness; improving socialization and support; offering information and resources on a “just in time” basis; and improving the quality of care and quality of life for both older adults and their family caregivers. This session will review eight evidence-based, technology-enabled solutions for family caregivers, including technology solutions that address medication adherence, falls prevention, personal emergency response, remote monitoring, telehealth, dementia tracking, social engagement, and care training. Key drivers for successful application of these interventions (e.g., technology, analytics, user experience design) as well as barriers to scaling (e.g., accessibility, affordability, regulation) will be reviewed.

Some important notes: Please contact your local NHS Library for the full text of the article. Follow this link to find your local NHS Library.


When will my patient fall? Sensor-based in-home walking speed identifies future falls in older adults

25/06/2019

Source: The Journal of Gerontology series A

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Date of publication: 16 May 2019

 Publication type: Journal article

In a nutshell: Although there are known clinical measures that may be associated with risk of future falls in older adults, we are still unable to predict when the fall will happen. Our objective was to determine whether unobtrusive in-home assessment of walking speed can detect a future fall.

Some important notes: Please contact your local NHS Library for the full text of the article. Follow this link to find your local NHS Library.

 


Fall classification by machine learning using mobile phones

06/12/2012

Source: PLoS ONE, 2012, 7 (5/e36556) p. 1-6

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Date of publication: May 2012

Publication type: Journal article

In a nutshell: With falls being a common source of injury in elderly people and the ability to automatically detect falls allowing rapid responses to potential emergencies, techniques have been developed to reliably detect a fall as well as to automatically classify the type. This study demonstrated technology that enables machines to identify a fall and collect information to quickly classify the type to enable a more rapid response.

Length of publication: 6 pages