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Background/Objectives: Measuring the physical functioning of older hip fracture patients using wearables is desirable, with physical activity monitoring offering a promising approach. However, it is first important to assess physical activity in healthy older adults. This study quantifies physical functioning with physical activity parameters and assesses those parameters in community-dwelling older adults. The results are compared with the results from one case participant 2 months post-hip fracture surgery. Methods: Twenty-four community-dwelling older adults (aged ≥ 80) participated. The acts of moving around the house, toileting, getting in/out of bed, and preparing meals was quantified by total time, time spent sitting, standing, and walking, number of transfers, and intensity of physical activity. MOX and APDM sensors measured the intensity of physical activity, with the tasks performed in a living lab while video-recorded. The case participant's total time and intensity of physical activity were measured for walking to a door and getting in/out of bed. Results: Preparing meals showed the longest total time and time spent standing/walking, while moving around the house and getting in/out of bed had the highest intensity of physical activity. Only getting in/out of bed required sitting. The physical activity parameters varied among participants, with very active participants completing tasks faster. The case participant had longer total times and lower intensities of physical activity two months post-surgery compared to before the fracture. Conclusions: This study provides initial insights into the physical activity levels of community-dwelling older adults. It represents the beginning of more efficient and continuous monitoring of physical functioning. [ABSTRACT FROM AUTHOR]

Background: To support early recognition of clinical deterioration on a general ward continuous vital signs monitoring (CMVS) systems using wearable devices are increasingly being investigated. Although nurses play a crucial role in successful implementation, reported nurse adoption and acceptance scores vary significantly. In-depth insight into the perspectives of nurses regarding CMVS is lacking. To this end, we applied a theoretical approach for behaviour change derived from the Behaviour Change Wheel (BCW). Aim: To provide insight in the capability, opportunity and motivation of nurses working with CMVS, in order to inform future implementation efforts. Methods: A qualitative study was conducted, including twelve nurses of a surgical ward in a tertiary teaching hospital with previous experience of working with CMVS. Semi-structured interviews were audiotaped, transcribed verbatim, and analysed using thematic analysis. The results were mapped onto the Capability, Opportunity, Motivation – Behaviour (COM-B) model of the BCW. Results: Five key themes emerged. The theme 'Learning and coaching on the job' linked to Capability. Nurses favoured learning about CVSM by dealing with it in daily practice. Receiving bedside guidance and coaching was perceived as important. The theme 'interpretation of vital sign trends' also linked to Capability. Nurses mentioned the novelty of monitoring vital sign trends of patients on wards. The theme 'Management of alarms' linked to Opportunity. Nurses perceived the (false) alarms generated by the system as excessive resulting in feelings of irritation and uncertainty. The theme 'Integration and compatibility with clinical workflow' linked to Opportunity. CVSM was experienced as helpful and easy to use, although integration in mobile devices and the EMR was highly favoured and the management of clinical workflows would need improvement. The theme 'Added value for nursing care' linked to Motivation. All nurses recognized the potential added value of CVSM for postoperative care. Conclusion: Our findings suggest all parts of the COM-B model should be considered when implementing CVSM on general wards. When the themes in Capability and Opportunity are not properly addressed by selecting interventions and policy categories, this may negatively influence the Motivation and may compromise successful implementation. [ABSTRACT FROM AUTHOR]

OBJECTIVE: To describe the cumulative injury proportion after 1000 and 2000 km of running among runners from 87 countries worldwide using wearable devices. Secondly, examine if the cumulative injury proportion differed between runners from different countries. DESIGN: Cohort study with an 18-month follow-up. METHODS: Runners aged ≥18 years who were familiar with the English language, and who were using a Garmin sports watch that supported tracking of running were eligible for inclusion. The exposure was residential country; self-reported running-related injury was the primary outcome. A generalized linear model was used to estimate the cumulative injury proportion for each country and the cumulative risk difference between the countries (country with the lowest risk used as reference). Data were analyzed at 1000 and 2000 km. RESULTS: The proportions of injured runners among the 7605 included runners from 87 different countries were 57.6% [95% CI: 56.9%, 59.0%] at 1000 km and 69.8% [95% CI: 68.3%, 71.4%] at 2000 km. Runners from the Czech Republic (40.3% [95% CI: 28.7%, 51.9%]), Austria (41.1% [95% CI: 25.9%, 52.2%]), and Germany (41.9% [95% CI: 36.0%, 47.9%]) had the lowest cumulative injury proportions at 1000 km, whereas Ireland (75.4% [95% CI: 60.4%, 90.4%]), Great Britain and Northern Ireland (73.2% [95% CI: 69.3%, 77.1%]), and Finland (67.5% [95% CI: 47.2%, 87.7%]) had the highest proportions. At 2000 km, Poland (47.7% [95% CI: 36.0%, 59.4%]), Slovenia (52.2% [95% CI: 28.5%, 75.8%]), and Croatia (54.2% [95% CI: 35.6%, 72.7%]) had the lowest proportions of injured runners. The highest cumulative injury proportions were reported in Great Britain and Northern Ireland (83.6% [95% CI: 79.6%, 87.6%]) and the Netherlands (78.3% [95% CI: 70.6%, 85.9%]). CONCLUSION: More than half of the population of adult runners from 87 countries using wearable devices sustained a running-related injury during follow-up. There were considerable between-country differences in injury proportions. J Orthop Sports Phys Ther 2024;54(2):1-9. Epub 16 November 2023. doi:10.2519/jospt.2023.11959 .

Background: In the absence of a vaccine or effective treatment for COVID-19, countries have adopted nonpharmaceutical interventions (NPIs) such as social distancing and full lockdown. An objective and quantitative means of passively monitoring the impact and response of these interventions at a local level is needed.Objective: We aim to explore the utility of the recently developed open-source mobile health platform Remote Assessment of Disease and Relapse (RADAR)-base as a toolbox to rapidly test the effect and response to NPIs intended to limit the spread of COVID-19.Methods: We analyzed data extracted from smartphone and wearable devices, and managed by the RADAR-base from 1062 participants recruited in Italy, Spain, Denmark, the United Kingdom, and the Netherlands. We derived nine features on a daily basis including time spent at home, maximum distance travelled from home, the maximum number of Bluetooth-enabled nearby devices (as a proxy for physical distancing), step count, average heart rate, sleep duration, bedtime, phone unlock duration, and social app use duration. We performed Kruskal-Wallis tests followed by post hoc Dunn tests to assess differences in these features among baseline, prelockdown, and during lockdown periods. We also studied behavioral differences by age, gender, BMI, and educational background.Results: We were able to quantify expected changes in time spent at home, distance travelled, and the number of nearby Bluetooth-enabled devices between prelockdown and during lockdown periods (P<.001 for all five countries). We saw reduced sociality as measured through mobility features and increased virtual sociality through phone use. People were more active on their phones (P<.001 for Italy, Spain, and the United Kingdom), spending more time using social media apps (P<.001 for Italy, Spain, the United Kingdom, and the Netherlands), particularly around major news events. Furthermore, participants had a lower heart rate (P<.001 for Italy and Spain; P=.02 for Denmark), went to bed later (P<.001 for Italy, Spain, the United Kingdom, and the Netherlands), and slept more (P<.001 for Italy, Spain, and the United Kingdom). We also found that young people had longer homestay than older people during the lockdown and fewer daily steps. Although there was no significant difference between the high and low BMI groups in time spent at home, the low BMI group walked more.Conclusions: RADAR-base, a freely deployable data collection platform leveraging data from wearables and mobile technologies, can be used to rapidly quantify and provide a holistic view of behavioral changes in response to public health interventions as a result of infectious outbreaks such as COVID-19. RADAR-base may be a viable approach to implementing an early warning system for passively assessing the local compliance to interventions in epidemics and pandemics, and could help countries ease out of lockdown. [ABSTRACT FROM AUTHOR]