Accepted for/Published in: JMIR Research Protocols
Date Submitted: Nov 15, 2020
Date Accepted: Jun 8, 2021
Date Submitted to PubMed: Aug 13, 2021
Technological-based platform for risk assessment, detection, and prevention of falls among home-dwelling elderly: a study protocol
ABSTRACT
Background:
According to the United Nations, it is estimated that by 2050, the number of people aged 80 and over will be three times the current number. An increased longevity is often accompanied by structural and functional changes that occur throughout an individual’s lifespan. These changes are often aggravated by chronic comorbidities, adopted behaviours or lifestyles and environmental exposures, among other reasons. Some of the related outcomes are loss of muscle strength, balance control and mobility impairments, which are strongly associated with the occurrence of falls in the elderly. Despite the importance of knowledge on fall prevention among the elderly population remaining undervalued by primary care health professionals, several evidence-based (single or multifaceted) fall prevention programmes such as the Otago Exercise Programme (OEP), have demonstrated a significant reduction in the risk of falls and fall-related injuries in the elderly within community settings. Recent studies have strived to integrate technology into physical exercise programmes, which is effective for adherence and overcoming barriers to exercise, as well as causing improvements in physical functioning
Objective:
To assess the impact of the OEP on the functionality of home-dwelling elderly using a common technological platform. Particularly, the impact on muscle strength, balance, mobility, risk of falling, the perception of fear of falling and the perception of the elderly regarding the ease of use of technology has been examined in this study.
Methods:
A quasi-experimental study (before and after a single group) will be conducted comprising male and female participants aged 65 years or over living at home in the district of Porto. Participants will be recruited through the network COLABORAR, with a minimum of 30 participants following the study inclusion and exclusion criteria. All participants will sign informed consent forms. The data collection instrument consists of socio-demographic/clinical variables (self-reported), functional evaluation variables, and environmental risk variables. The data collection tool integrates primary and secondary outcomes variables. The primary outcome is gait (TUGT) (normal step). The secondary outcome variables are lower limb strength and muscle resistance (30 Seconds CST), the balance (4 SBT balance test), the assessment of the frequency of falls, the functional capacity evaluation (Lawton and Brody - Portuguese version), the fear of falling (FES-I - Portuguese version), the usability of the technology (SUS - Portuguese version) and environmental risk variables (HFPC) for Older Adults. Technological solutions will be used, such as the FallSensing Home application and Kallisto wearable device, which will allow the detection and prevention of falls. The intervention is characterized by the OEP conducted over eight weeks through a common technological platform three times a week. Throughout these weeks, the participants will be followed-up in person or by telephonic contact by the rehabilitation nurse. Considering the COVID-19 outbreak, all guidelines by the National Health Service (NHS) will be followed. The project was funded by InnoStars, in collaboration with the Local EIT Health RIS Hub of the University of Porto.
Results:
This study was approved on 10/09/2020 by the Ethics Committee of ESEP. The recruitment process was meant to start in October, but due to the COVID-19 pandemic it was suspended. We expect to restart the study by the beginning of the third quarter of 2021
Conclusions:
The findings of this study protocol will contribute to the design and development of future robust studies for technological tests in a clinical context. Clinical Trial: ISRCTN15895163 , https://doi.org/10.1186/ISRCTN15895163
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.