BACKGROUND: Falls and fall-related injuries among older adults are a serious threat to the quality of life and result in high healthcare and societal costs. Despite evidence that falls can be prevented by fall prevention programmes, practical barriers may challenge the implementation of these programmes. In this study, we will investigate the effectiveness and cost-effectiveness of In Balance, a fourteen-week, low-cost group fall prevention intervention, that is widely implemented in community-dwelling older adults with an increased fall risk in the Netherlands. Moreover, we will be the first to include cost-effectiveness for this intervention. Based on previous evidence of the In Balance intervention in pre-frail older adults, we expect this intervention to be (cost-)effective after implementation-related adjustments on the target population and duration of the intervention.METHODS: This study is a single-blinded, multicenter randomized controlled trial. The target sample will consist of 256 community-dwelling non-frail and pre-frail adults of 65 years or older with an increased risk of falls. The intervention group receives the In Balance intervention as it is currently widely implemented in Dutch healthcare, which includes an educational component and physical exercises. The physical exercises are based on Tai Chi principles and focus on balance and strength. The control group receives general written physical activity recommendations. Primary outcomes are the number of falls and fall-related injuries over 12 months follow-up. Secondary outcomes consist of physical performance measures, physical activity, confidence, health status, quality of life, process evaluation and societal costs. Mixed model analyses will be conducted for both primary and secondary outcomes and will be stratified for non-frail and pre-frail adults.DISCUSSION: This trial will provide insight into the clinical and societal impact of an implemented Dutch fall prevention intervention and will have major benefits for older adults, society and health insurance companies. In addition, results of this study will inform healthcare professionals and policy makers about timely and (cost-)effective prevention of falls in older adults.TRIAL REGISTRATION: Netherlands Trial Register: NL9248 (registered February 13, 2021).
Background: Falls in people 65 years and older evaluated in the emergency department are increasing. Of all unintentional injury-related deaths among older people, 55% are due to falls. The impact of falls, especially concerning Dutch older people with the highest proportion of living independently worldwide, is unclear. Objective: To identify the influence of age, gender, health conditions, and type of fall on the severity of injury, hospital length of stay, mortality, and discharge destination. Methods: A total number of 6,084 patients from a comprehensive regional trauma care system, 65 years and older and hospitalized after a fall, were included. Groups were compared for patient-related factors and multivariable logistic regression analysis to explore the consequences. Results: Mean age was 82 years (SD = 8.3), and 70% were female. Most falls (66.4%) were due to "slipping and tripping" or "falls on the same level," 57.4% had Injury Severity Scores between 9 and 12, and 43.3% were discharged home. Higher age and type of fall increased the likelihood of severe injuries. Men experienced shorter hospital stays than women and were less frequently discharged home. Mortality was higher in males (10.8%) than in females (6.7%) and increased with the American Society of Anesthesiologists scores for preexisting health conditions. Conclusion: Advanced age, gender, type of fall, and prior health status play a significant role in the severity of injuries, length of hospital stay, 30-day mortality, and higher discharge destination to care homes in older people hospitalized after a fall.
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Background: There are indications that older adults who suffer from poor balance have an increased risk for adverse health outcomes, such as falls and disability. Monitoring the development of balance over time enables early detection of balance decline, which can identify older adults who could benefit from interventions aimed at prevention of these adverse outcomes. An innovative and easy-to-use device that can be used by older adults for home-based monitoring of balance is a modified bathroom scale. Objective: The objective of this paper is to study the relationship between balance scores obtained with a modified bathroom scale and falls and disability in a sample of older adults. Methods: For this 6-month follow-up study, participants were recruited via physiotherapists working in a nursing home, geriatricians, exercise classes, and at an event about health for older adults. Inclusion criteria were being aged 65 years or older, being able to stand on a bathroom scale independently, and able to provide informed consent. A total of 41 nursing home patients and 139 community-dwelling older adults stepped onto the modified bathroom scale three consecutive times at baseline to measure their balance. Their mean balance scores on a scale from 0 to 16 were calculated—higher scores indicated better balance. Questionnaires were used to study falls and disability at baseline and after 6 months of follow-up. The cross-sectional relationship between balance and falls and disability at baseline was studied using t tests and Spearman rank correlations. Univariate and multivariate logistic regression analyses were conducted to study the relationship between balance measured at baseline and falls and disability development after 6 months of follow-up.
Horse riding falls under the “Sport for Life” disciplines, where a long-term equestrian development can provide a clear pathway of developmental stages to help individuals, inclusive of those with a disability, to pursue their goals in sport and physical activity, providing long-term health benefits. However, the biomechanical interaction between horse and (disabled) rider is not wholly understood, leaving challenges and opportunities for the horse riding sport. Therefore, the purpose of this KIEM project is to start an interdisciplinary collaboration between parties interested in integrating existing knowledge on horse and (disabled) rider interaction with any novel insights to be gained from analysing recently collected sensor data using the EquiMoves™ system. EquiMoves is based on the state-of-the-art inertial- and orientational-sensor system ProMove-mini from Inertia Technology B.V., a partner in this proposal. On the basis of analysing previously collected data, machine learning algorithms will be selected for implementation in existing or modified EquiMoves sensor hardware and software solutions. Target applications and follow-ups include: - Improving horse and (disabled) rider interaction for riders of all skill levels; - Objective evidence-based classification system for competitive grading of disabled riders in Para Dressage events; - Identifying biomechanical irregularities for detecting and/or preventing injuries of horses. Topic-wise, the project is connected to “Smart Technologies and Materials”, “High Tech Systems & Materials” and “Digital key technologies”. The core consortium of Saxion University of Applied Sciences, Rosmark Consultancy and Inertia Technology will receive feedback to project progress and outcomes from a panel of international experts (Utrecht University, Sport Horse Health Plan, University of Central Lancashire, Swedish University of Agricultural Sciences), combining a strong mix of expertise on horse and rider biomechanics, veterinary medicine, sensor hardware, data analysis and AI/machine learning algorithm development and implementation, all together presenting a solid collaborative base for derived RAAK-mkb, -publiek and/or -PRO follow-up projects.
Bicycle manufacturing currently falls behind the fast technological developments in automotive industries. We propose to design, develop and test a smart cycling eco-system where bicycles communicate in realtime with each other, and with the urban transport infrastructure (e.g. traffic lights) to optimize the use and improve traffic safety, economical value, and efficiency. This require technologies and mechanisms to allow monitoring the bike, understanding the cyclist and the context, as well as data sharing between cyclists, industry, service providers, government, and urban planners. The new eco-system can drive decision-making, behaviour incentivisation, and ultimately investment, across government, and beyond. A key ingredient is an AI-enabled IoT ecosystem in which data is securely collected, shared, processed in combination with other data sources, and made available to establish new services. This allows to reliably identify relevant events (like dangerous situations), detect trends (like decreasing performance of components, allowing maintenance to be performed in time), and give new insights to the user (such as health and performance).
