Validity of the Original and Short Versions of the Dynamic Gait Index in Predicting Falls in Stroke Survivors

An, Seung Heon; Jee, Young Ju; Shin, Hyeon Hui; Lee, GyuChang

doi:10.1002/rnj.280

Cited by 12 publications

(7 citation statements)

References 28 publications

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“…To assess fall risk, performance-oriented balance tests are commonly used. All the tests below were described to be able to identify individuals who are prone to falls or to predict the probability of falls in various populations ( Shumway-Cook et al, 2000 ; Hall et al, 2004 ; An et al, 2017 ; Cleary and Skornyakov, 2017 ; Raîche et al, 2000 ; Jeon and Kim, 2017 ; Lauretani et al, 2019 ; Rose et al, 2002 ). Nine studies ( Grigorova-Petrova et al, 2015 ; Yesilyaprak et al, 2016 ; Sun et al, 2018 ; Wu et al, 2019 ; Cicek et al, 2020 ; Fakhro et al, 2020 ; Babadi and Daneshmandi, 2021 ; Ramnath et al, 2021 ; Zahedian-Nasab et al, 2021 ) assessed fall risk using the Timed Up and Go Test (TUG, Mathias et al, 1986 ), two ( Monteiro-Junior et al, 2017 ; Rica et al, 2020 ) a slightly modified version of the TUG, the 8-Foot Up and Go test (8UG, Rikli and Jones, 1999 ), and one ( Delbroek et al, 2017 ) the instrumented TUG (iTUG, Salarian et al, 2010 ), which uses portable inertial sensors for a more detailed analysis.…”

Section: Resultsmentioning

confidence: 99%

Effectiveness and Acceptability of e- and m-Health Interventions to Promote Physical Activity and Prevent Falls in Nursing Homes—A Systematic Review

et al. 2022

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Age-related decreases in physical activity (PA) and a decline in physical functioning lead to increased fall risk. As falls are a major cause of accidental deaths and hospitalization in older adults, PA promotion and fall prevention are important measures, especially in nursing homes (NH). With advances in information and communication technology, e- and m-health solutions have been developed to positively influence various health-related factors. To date, only little research exists on the implementation of these technologies to promote health in NH. Therefore, the objective of this systematic review was to provide an overview of the effectiveness, acceptability, and feasibility of e- and m-health interventions aimed at promoting PA and preventing falls in NH. Additionally, the effectiveness of such interventions regarding the secondary outcomes physical function, cognitive function, neuropsychiatric symptoms, and psychosocial status was examined. A systematic literature search was performed in five databases and studies published until 15 November 2021, were considered for inclusion. All studies that examined the effectiveness and/or the acceptability and feasibility of e- or m-health interventions in promoting PA and preventing falls in NH, without restriction on language or date of publication, were included in the final synthesis. Of the 1,358 records retrieved, 28 studies were included in this systematic review. Twenty-four studies contained digital exergaming as an intervention or as a part of the intervention, the four additional studies on e-health interventions only examined a small number of outcomes. No m-health intervention study was identified. Data synthesis indicates that exergaming may be effective in reducing the number of falls and fall risk in NH residents. Several significant improvements were also reported regarding secondary outcomes albeit not consistent across studies. No conclusion can be drawn about the effects of exergaming and other e-health interventions on PA, as data is scarce. E-health interventions were mostly reported as feasible and well accepted by NH residents. However, these findings may not be applicable to NH residents with advanced physical and/or cognitive impairments, since they were excluded in many studies. Therefore, more research examining other digital solutions besides exergaming to promote PA in this specific population is critical.Systematic Review Registration:https://www.crd.york.ac.uk/prospero/, identifier CRD42021289488

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Section: Resultsmentioning

confidence: 99%

Effectiveness and Acceptability of e- and m-Health Interventions to Promote Physical Activity and Prevent Falls in Nursing Homes—A Systematic Review

et al. 2022

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“…Similar to 5T-STS is the Dynamic Gait Index (DGI), that verifies the participant’s ability to maintain the equilibrium of walking by responding to different requests. Some studies demonstrated the high reliability of the assessment in elderly people, subjects suffering from vestibular dysfunction, multiple sclerosis and post-stroke [ 15 ]. It can be performed in both hospital and home settings, as it does not require any special equipment.…”

Section: Discussionmentioning

confidence: 99%

“…It can be performed in both hospital and home settings, as it does not require any special equipment. It evaluates all aspects of gait, but takes a long time to administer (15 min) [ 15 ].…”

Section: Discussionmentioning

confidence: 99%

Fall Risk Assessment Scales: A Systematic Literature Review

Strini

Schiavolin

Prendin³

2021

Nursing Reports

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Background: Falls are recognized globally as a major public health problem. Although the elderly are the most affected population, it should be noted that the pediatric population is also very susceptible to the risk of falling. The fall risk approach is the assessment tool. There are different types of tools used in both clinical and territorial settings. Material and methods: In the month of January 2021, a literature search was undertaken of MEDLINE, CINHAL and The Cochrane Database, adopting as limits: last 10 years, abstract available, and English and Italian language. The search terms used were “Accidental Falls” AND “Risk Assessment” and “Fall Risk Assessment Tool” or “Fall Risk Assessment Tools”. Results: From the 115 selected articles, 38 different fall risk assessment tools were identified, divided into two groups: the first with the main tools present in the literature, and the second represented by tools of some specific areas, of lesser use and with less supporting literature. Most of these articles are prospective cohort or cross-sectional studies. All articles focus on presenting, creating or validating fall risk assessment tools. Conclusion: Due to the multidimensional nature of falling risk, there is no “ideal” tool that can be used in any context or that performs a perfect risk assessment. For this reason, a simultaneous application of multiple tools is recommended, and a direct and in-depth analysis by the healthcare professional is essential.

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“…We also used the Mini-Mental Scare Examination as a screening tool for participants’ cognitive function (>24) [ 50 ]. We also used the Berg-Balance Scale (BBS) [ 51 ] and Dynamic Gait Index [ 52 ] to measure participants’ balance function. We used the Activities-specific Balance Confidence (ABC) scale [ 53 ] to evaluate participants perceived balance function during activities of daily living, and the Geriatric Depression Scale (GDS) [ 54 ] and Stroke Impact Scale (SIS) [ 55 ] to assess participant’s mental function and perceived impact of poststroke disability on their quality of life, respectively.…”

Section: Methodsmentioning

confidence: 99%

A Challenge-Based Approach to Body Weight–Supported Treadmill Training Poststroke: Protocol for a Randomized Controlled Trial

2018

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BackgroundBody weight support treadmill training protocols in conjunction with other modalities are commonly used to improve poststroke balance and walking function. However, typical body weight support paradigms tend to use consistently stable balance conditions, often with handrail support and or manual assistance.ObjectiveIn this paper, we describe our study protocol, which involved 2 unique body weight support treadmill training paradigms of similar training intensity that integrated dynamic balance challenges to help improve ambulatory function post stroke. The first paradigm emphasized walking without any handrails or manual assistance, that is, hands-free walking, and served as the control group, whereas the second paradigm incorporated practicing 9 essential challenging mobility skills, akin to environmental barriers encountered during community ambulation along with hands-free walking (ie hands-free + challenge walking).MethodsWe recruited individuals with chronic poststroke hemiparesis and randomized them to either group. Participants trained for 6 weeks on a self-driven, robotic treadmill interface that provided body weight support and a safe gait-training environment. We assessed participants at pre-, mid- and post 6 weeks of intervention-training, with a 6-month follow-up. We hypothesized greater walking improvements in the hands-free + challenge walking group following training because of increased practice opportunity of essential mobility skills along with hands-free walking.ResultsWe assessed 77 individuals with chronic hemiparesis, and enrolled and randomized 30 individuals poststroke for our study (hands-free group=19 and hands-free + challenge walking group=20) from June 2012 to January 2015. Data collection along with 6-month follow-up continued until January 2016. Our primary outcome measure is change in comfortable walking speed from pre to post intervention for each group. We will also assess feasibility, adherence, postintervention efficacy, and changes in various exploratory secondary outcome measures. Additionally, we will also assess participant responses to a study survey, conducted at the end of training week, to gauge each group's training experiences.ConclusionsOur treadmill training paradigms, and study protocol represent advances in standardized approaches to selecting body weight support levels without the necessity for using handrails or manual assistance, while progressively providing dynamic challenges for improving poststroke ambulatory function during rehabilitation.Trial RegistrationClinicalTrials.gov NCT02787759; https://clinicaltrials.gov/ct2/show/NCT02787759 (Archived by Webcite at http://www.webcitation.org/6yJZCrIea)

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Validity of the Original and Short Versions of the Dynamic Gait Index in Predicting Falls in Stroke Survivors

Abstract: DGI-8 and DGI-4 can be useful for predicting falls of stroke patients, allowing better quality of care.

Cited by 12 publications

References 28 publications

Effectiveness and Acceptability of e- and m-Health Interventions to Promote Physical Activity and Prevent Falls in Nursing Homes—A Systematic Review

Effectiveness and Acceptability of e- and m-Health Interventions to Promote Physical Activity and Prevent Falls in Nursing Homes—A Systematic Review

Fall Risk Assessment Scales: A Systematic Literature Review

A Challenge-Based Approach to Body Weight–Supported Treadmill Training Poststroke: Protocol for a Randomized Controlled Trial

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