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A Technological-Based Platform for Risk Assessment, Detection, and Prevention of Falls Among Home-Dwelling Older Adults: Protocol for a Quasi-Experimental Study

2021Journal article Open access
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dc.contributor.authorAraújo, F.
dc.contributor.authorNilza Caldevilla, Maria
dc.contributor.authorSilva, Joana
dc.contributor.authorRego, Sílvia
dc.date.accessioned2022-11-08T16:34:28Z
dc.date.available2022-11-08T16:34:28Z
dc.date.issued2021
dc.description.abstractBackground: According to the United Nations, it is estimated that by 2050, the number of people aged 80 years and older will have increased by 3 times. 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 behaviors or lifestyles, and environmental exposure, among other factors. Some of the related outcomes are loss of muscle strength, decreased balance control, and mobility impairments, which are strongly associated with the occurrence of falls in the elderly. Despite the continued undervaluation of the importance of knowledge on fall prevention among the elderly population by primary care health professionals, several evidence-based (single or multifaceted) fall prevention programs such as the Otago Exercise Program (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 programs, which is effective for adherence and overcoming barriers to exercise, as well as improving physical functioning. Objective: This study aims 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 are being examined in this study. Methods: A quasi-experimental study (before and after; single group) will be conducted with male and female participants aged 65 years or older living at home in the district of Porto. Participants will be recruited through the network COLABORAR, with a minimum of 30 participants meeting the study inclusion and exclusion criteria. All participants will sign informed consent forms. The data collection instrument consists of sociodemographic and clinical variables (self-reported), functional evaluation variables, and environmental risk variables. The data collection tool integrates primary and secondary outcome variables. The primary outcome is gait (timed-up and go test; normal step). The secondary outcome variables are lower limb strength and muscle resistance (30-second chair stand test), balance (4-stage balance test), frequency of falls, functional capacity (Lawton and Brody - Portuguese version), fear of falling (Falls Efficacy Scale International - Portuguese version), usability of the technology (System Usability Scale - Portuguese version), and environmental risk variables (home fall prevention checklist for older adults). Technological solutions, such as the FallSensing Home application and Kallisto wearable device, will be used, which will allow the detection and prevention of falls. The intervention is characterized by conducting the OEP through a common technological platform 3 times a week for 8 weeks. Throughout these weeks, the participants will be followed up in person or by telephone contact by the rehabilitation nurse. Considering the COVID-19 outbreak, all guidelines from the National Health Service will be followed. The project was funded by InnoStars, in collaboration with the Local EIT Health Regional Innovation Scheme Hub of the University of Porto. Results: This study was approved on October 9, 2020 by the Ethics Committee of Escola Superior de Enfermagem do Porto (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.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationAraújo F, Nogueira MN, Silva J, Rego S A Technological-Based Platform for Risk Assessment, Detection, and Prevention of Falls Among Home-Dwelling Older Adults: Protocol for a Quasi-Experimental Study JMIR Res Protoc 2021;10(8):e25781pt_PT
dc.identifier.doi10.2196/25781pt_PT
dc.identifier.eissn1929-0748
dc.identifier.urihttp://hdl.handle.net/10400.26/42264
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherJMIR Publicationspt_PT
dc.relation.publisherversionhttps://www.researchprotocols.org/2021/8/e25781pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectFall preventionpt_PT
dc.subjectTechnological platformpt_PT
dc.subjectElderlypt_PT
dc.subjectOtago Exercise Programpt_PT
dc.titleA Technological-Based Platform for Risk Assessment, Detection, and Prevention of Falls Among Home-Dwelling Older Adults: Protocol for a Quasi-Experimental Studypt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.issue8pt_PT
oaire.citation.startPagee25781pt_PT
oaire.citation.titleJMIR Research Protocolspt_PT
oaire.citation.volume10pt_PT
person.familyNameElias
person.familyNameCaldevilla
person.givenNameMaria
person.givenNameMª Nilza
person.identifier.ciencia-id0B10-71D6-F317
person.identifier.ciencia-id8D1A-59CB-B63B
person.identifier.orcid0000-0001-5254-530X
person.identifier.orcid0000-0002-9903-9233
person.identifier.ridK-5848-2013
person.identifier.ridK-5117-2013
person.identifier.scopus-author-id55759868000
person.identifier.scopus-author-id55981295300
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication39c2fd40-c7b7-4e9d-9a50-8fef96f53020
relation.isAuthorOfPublication60c7ef3c-4734-41cb-ad7c-1c772b0bc9ac
relation.isAuthorOfPublication.latestForDiscovery60c7ef3c-4734-41cb-ad7c-1c772b0bc9ac

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