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Open access · US-GOV via ClinicalTrials.gov Clinical trial

Home-based and Residence-based Virtual Reality Training to Increase Rehabilitative Exercise in Seniors

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Bruyère Health Research Institute. · 2019

Abstract

Seniors are at risk for reduced independence and lowered quality of life after injury or illness. Gains in strength, stamina, balance, cardiovascular fitness and confidence resulting from regular exercise can help seniors to maintain (or improve) their functional ability, independence, and quality of life. However, seniors experience many barriers to exercise. The objective is to assess the use of virtual reality (VR) as a motivating way to encourage seniors to do regular rehabilitative exercise. Seniors who could benefit from rehabilitative exercise and who live in two situations, a) long-term care and b) independently in their homes, will be recruited. Participants will be randomized to usual activity (control) or usual activity plus VR exercise. Long-term care residents will do VR with the assistance of care staff or study partners under the direction of the research team. Independent-living participants will do VR in their homes with the supervision of study partners, under the direction of the research team. All participants will be asked to do VR 3-5 times a week for 8 weeks. Mobility (balance, gait, physical function), and health outcomes (falls, hospital admissions) will be assessed and compared over time.

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ClinicalTrials.gov
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2026-10-07 MST

Cite this

APA
Anonymous. (2019). Home-based and Residence-based Virtual Reality Training to Increase Rehabilitative Exercise in Seniors. <em>Bruyère Health Research Institute.</em>. https://clinicaltrials.gov/study/NCT04083885
Vancouver
Anonymous. Home-based and Residence-based Virtual Reality Training to Increase Rehabilitative Exercise in Seniors. Bruyère Health Research Institute.. 2019.
BibTeX
@misc{anon2019Homeba, title = {Home-based and Residence-based Virtual Reality Training to Increase Rehabilitative Exercise in Seniors}, author = {Anonymous}, journal = {Bruyère Health Research Institute.}, year = {2019}, }

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