The case for wearable proximity devices to inform physical distancing among healthcare workers.
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ABSTRACT: Objective
Despite the importance of physical distancing in reducing SARS-CoV-2 transmission, this practice is challenging in healthcare. We piloted use of wearable proximity beacons among healthcare workers (HCWs) in an inpatient unit to highlight considerations for future use of trackable technologies in healthcare settings.Materials and methods
We performed a feasibility pilot study in a non-COVID adult medical unit from September 28 to October 28, 2020. HCWs wore wearable proximity beacons, and interactions defined as <6 feet for ≥5 s were recorded. Validation was performed using direct observations.Results
A total of 6172 close proximity interactions were recorded, and with the removal of 2033 false-positive interactions, 4139 remained. The highest proportion of interactions occurred between 7:00 Am-9:00 Am. Direct observations of HCWs substantiated these findings.Discussion
This pilot study showed that wearable beacons can be used to monitor and quantify HCW interactions in inpatient settings.Conclusion
Technology can be used to track HCW physical distancing.
SUBMITTER: Keller SC
PROVIDER: S-EPMC8672930 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundHealthcare workers (HCWs) not adhering to physical distancing recommendations is a risk factor for acquisition of severe acute respiratory coronavirus virus 2 (SARS-CoV-2). The study objective was to assess the impact of interventions to improve HCW physical distancing on actual distance between HCWs in a real-life setting.MethodsHCWs voluntarily wore proximity beacons to measure the number and intensity of physical distancing interactions between each other in a pediatric intensive care unit. We compared interactions before and after implementing a bundle of interventions including changes to the layout of workstations, cognitive aids, and individual feedback from wearable proximity beacons.ResultsOverall, we recorded 10,788 interactions within 6 feet (∼2 m) and lasting >5 seconds. The number of HCWs wearing beacons fluctuated daily and increased over the study period. On average, 13 beacons were worn daily (32% of possible staff; range, 2-32 per day). We recorded 3,218 interactions before the interventions and 7,570 interactions after the interventions began. Using regression analysis accounting for the maximum number of potential interactions if all staff had worn beacons on a given day, there was a 1% decline in the number of interactions per possible interactions in the postintervention period (incident rate ratio, 0.99; 95% confidence interval, 0.98-1.00; P = .02) with fewer interactions occurring at nursing stations, in workrooms and during morning rounds.ConclusionsUsing quantitative data from wearable proximity beacons, we found an overall small decline in interactions within 6 feet between HCWs in a busy intensive care unit after a multifaceted bundle of interventions was implemented to improve physical distancing.
| S-EPMC8692852 | biostudies-literature
Project description:BackgroundPhysical distancing among healthcare workers (HCWs) is an essential strategy in preventing HCW-to-HCWs transmission of severe acute respiratory coronavirus virus 2 (SARS-CoV-2).ObjectiveTo understand barriers to physical distancing among HCWs on an inpatient unit and identify strategies for improvement.DesignQualitative study including observations and semistructured interviews conducted over 3 months.SettingA non-COVID-19 adult general medical unit in an academic tertiary-care hospital.ParticipantsHCWs based on the unit.MethodsWe performed a qualitative study in which we (1) observed HCW activities and proximity to each other on the unit during weekday shifts July-October 2020 and (2) conducted semi-structured interviews of HCWs to understand their experiences with and perspectives of physical distancing in the hospital. Qualitative data were coded based on a human-factors engineering model.ResultsWe completed 25 hours of observations and 20 HCW interviews. High-risk interactions often occurred during handoffs of care at shift changes and patient rounds, when HCWs gathered regularly in close proximity for at least 15 minutes. Identified barriers included spacing and availability of computers, the need to communicate confidential patient information, and the desire to maintain relationships at work.ConclusionsPhysical distancing can be improved in hospitals by restructuring computer workstations, work rooms, and break rooms; applying visible cognitive aids; adapting shift times; and supporting rounds and meetings with virtual conferencing. Additional strategies to promote staff adherence to physical distancing include rewarding positive behaviors, having peer leaders model physical distancing, and encouraging additional safe avenues for social connection at a safe distance.
| S-EPMC8111196 | biostudies-literature
Project description:IntroductionThe aims of this study were to examine the mediation effect of viral anxiety of healthcare workers on the influence of their intolerance of uncertainty on the adherence to physical distancing during the COVID-19 pandemic.MethodsAn online survey was conducted among 329 healthcare workers (female: 81.4%, nursing professionals: 59.0%, and shift workers: 22.3%) on November 29, 2021. Participants responded to questionnaires on adherence to physical distancing, health beliefs, and perceived social norms, and rating scales of the Stress and Anxiety to Viral Epidemics-6 items (SAVE-6), Patient Health Questionnaire-9 items (PHQ-9), and the Intolerance of Uncertainty-12 items (IUS-12) scale.ResultsAdherence to physical distancing of healthcare workers was predicted by perceived benefits of physical distancing (β = 0.13, p = 0.01), personal injunctive norms (β = 0.32, p < 0.001), SAVE-6 score (β = 0.13, p = 0.02), and IUS-12 score (β = 0.10, p = 0.045) (adjusted R2 = 0.21, F = 22.3, p < 0.001). Viral anxiety mediated the association between intolerance of uncertainty and adherence to physical distancing but not the influence of perceived benefits and personal injunctive norms on adherence to physical distancing.ConclusionWe observed that viral anxiety of healthcare workers mediated the association between intolerance of uncertainty and adherence to physical distancing. During this pandemic, exploring adherence to physical distancing and its predicting factors will be helpful for the safety of healthcare workers and the patients for whom they care.
| S-EPMC9207240 | biostudies-literature
Project description:BackgroundThe recent COVID-19 pandemic has contributed to the emergence of several technologies for infectious disease management. Although much focus has been placed on contact-tracing apps, another promising new tactic is proximity tracing, which focuses on health-related behavior and can be used for primary prevention. Underpinned by theories on behavioral design, a proximity-detection system can be devised that provides a user with immediate nudges to maintain physical distance from others. However, the practical feasibility of proximity detection during an infectious disease outbreak has not been sufficiently investigated.ObjectiveWe aimed to evaluate the feasibility of using a wearable device to nudge for distance and to gather important insights about how functionality and interaction are experienced by users. The results of this study can guide future research and design efforts in this emerging technology.MethodsIn this retrospective case study, a wearable proximity-detection technology was used in a workplace for 6 weeks during the production of a music competition. The purpose of the technology was to nudge users to maintain their physical distance using auditory feedback. We used a mixed methods sequential approach, including interviews (n=8) and a survey (n=30), to compile the experiences of using wearable technology in a real-life setting.ResultsWe generated themes from qualitative analysis based on data from interviews and open-text survey responses. The quantitative data were subsequently integrated into these themes: feasibility (implementation and acceptance-establishing a shared problem; distance tags in context-strategy, environment, and activities; understanding and learning; and accomplishing the purpose) and design aspects (a purposefully annoying device; timing, tone, and proximity; and additional functions).ConclusionsThis empirical study reports on the feasibility of using wearable technology based on proximity detection to nudge individuals to maintain physical distance in the workplace. The technology supports attention to distance, but the usability of this approach is dependent on the context and situation. In certain situations, the audio signal is frustrating, but most users agree that it needs to be annoying to ensure sufficient behavioral adaption. We proposed a dual nudge that involves vibration followed by sound. There are indications that the technology also facilitates learning how to maintain a greater distance from others, and that this behavior can persist beyond the context of technology use. This study demonstrates that the key value of this technology is that it places the user in control and enables immediate action when the distance to others is not maintained. This study provides insights into the emerging field of personal and wearable technologies used for primary prevention during infectious disease outbreaks. Future research is needed to evaluate the preventive effect on transmission and investigate behavioral changes in detail and in relation to different forms of feedback.
| S-EPMC9746677 | biostudies-literature
Project description:ObjectiveTo determine the feasibility and validity of using wearable activity trackers to test associations between gout flares with physical activity and sleep.MethodsParticipants with physician-diagnosed gout, hyperuricemia (≥ 6.8 mg/dl), current smartphone use, and ≥ 2 self-reported flares in the previous 6 months were enrolled. Physical activity, heart rate, and sleep data were obtained from wearable activity trackers (Fitbit Charge HR2). Daily compliance was defined by the availability of sufficiently complete activity data at least 80% of the day. Associations of weekly gout flares with sleep and activity were measured by comparing flare-related values to average sleep and steps per day. We used mixed linear models to account for repeated observations.ResultsForty-four participants enrolled; 33 met the criteria for minimal wear time and flare reporting, with activity tracker data available for 60.5% of all total study days. Mean ± SD age was 48.8 ± 14.9 years; 85% were men; 15% were black; 88% were on allopurinol or febuxostat, and 30% reported ≥ 6 flares in the prior 6 months. Activity trackers captured 204 (38%) person-weeks with flares and 340 (62%) person-weeks without flares. Mean ± SD daily step count was significantly lower (p < 0.0001) during weeks with gout flares (5900 ± 4071) than during non-flare periods (6972 ± 5214); sleep however did not differ.ConclusionThe pattern of wear in this study illustrates reasonable feasibility of using such devices in future arthritis research. The use of these devices to passively measure changes in physical activity patterns may provide an estimate of gout flare occurrence and duration.Trial registrationNCT, NCT02855437 . Registered 4 August 2016.
| S-EPMC7398057 | biostudies-literature
Project description:A wearable C-shaped antenna based on a fabric material operating at 2.4 GHz frequency is proposed for use in flexible/wearable IoT medical systems. The wearable IoT device plays a key role in medical applications, and the antenna is a key part of it. Loading the presented antenna on the body models showed a frequency detuned with the gain and efficiency reduced from 1. 28 to −9 dB and 90% to 10%. In addition, the SAR did not meet the safety health requirement defined by the FCC or ICNIRP standards. Therefore, an “Artificial Magnetic Conductor” structure (AMC) is added to the C-shaped antenna to overcome these problems. The AMC acts as shielding material between the human skin and the presented antenna because of its 0° reflection phase, which mimics the action of the Perfect Magnetic Conductor (PMC). The overall size of the proposed design was 54 × 54 × 3.9 mm3. Numerical and experimental findings indicated that integrating the AMC structures with a C-shaped antenna was robust for body deformation and load. The C-shaped antenna worked equally well with the AMC, whether positioned in free space or on the chest or the arm of the human body. The integrated antenna with AMC structures has excellent performances. The gain and efficiency without loading on the chest were 6.49 dB and 84%, respectively. While for loaded on the chest were 6.21 dB and 81%, respectively. It also decreased the back radiation and raised the Front to Back Ration (FBR) by 13.8 dB. SAR levels have been reduced by more than 90% between the FCC and ICNIRP standards compared to the C-shaped antenna alone, which does not comply with the standards. As a result, the C-shaped integration with AMC structures is highly suitable for assembly in any wearable system. Supplementary Information The online version contains supplementary material available at 10.1007/s11276-021-02770-4.
| S-EPMC8435302 | biostudies-literature
Project description:Wearable biometric monitoring devices (BMDs) and artificial intelligence (AI) enable the remote measurement and analysis of patient data in real time. These technologies have generated a lot of "hype," but their real-world effectiveness will depend on patients' uptake. Our objective was to describe patients' perceptions of the use of BMDs and AI in healthcare. We recruited adult patients with chronic conditions in France from the "Community of Patients for Research" (ComPaRe). Participants (1) answered quantitative and open-ended questions about the potential benefits and dangers of using of these new technologies and (2) participated in a case-vignette experiment to assess their readiness for using BMDs and AI in healthcare. Vignettes covered the use of AI to screen for skin cancer, remote monitoring of chronic conditions to predict exacerbations, smart clothes to guide physical therapy, and AI chatbots to answer emergency calls. A total of 1183 patients (51% response rate) were enrolled between May and June 2018. Overall, 20% considered that the benefits of technology (e.g., improving the reactivity in care and reducing the burden of treatment) greatly outweighed the dangers. Only 3% of participants felt that negative aspects (inadequate replacement of human intelligence, risks of hacking and misuse of private patient data) greatly outweighed potential benefits. We found that 35% of patients would refuse to integrate at least one existing or soon-to-be available intervention using BMDs and AI-based tools in their care. Accounting for patients' perspectives will help make the most of technology without impairing the human aspects of care, generating a burden or intruding on patients' lives.
| S-EPMC6572821 | biostudies-literature
Project description:Impact of Technical Sources of Variation on the Hand Microbiome Dynamics of Healthcare Workers
| PRJEB5147 | ENA
Project description:BackgroundThe rapid advancements in science and technology of wrist-wearable activity devices offer considerable potential for clinical applications. Self-monitoring of physical activity (PA) with activity devices is helpful to improve the PA levels of adolescents. However, knowing the accuracy of activity devices in adolescents is necessary to identify current levels of PA and assess the effectiveness of intervention programs designed to increase PA.ObjectiveThe study aimed to determine the validity of the 11 commercially available wrist-wearable activity devices for monitoring total steps and total 24-hour total energy expenditure (TEE) in healthy adolescents under simulated free-living conditions.MethodsNineteen (10 male and 9 female) participants aged 14 to 18 years performed a 24-hour activity cycle in a metabolic chamber. Each participant simultaneously wore 11 commercial wrist-wearable activity devices (Mi Band 2 [XiaoMi], B2 [Huawei], Bong 2s [Meizu], Amazfit [Huamei], Flex [Fitbit], UP3 [Jawbone], Shine 2 [Misfit], GOLiFE Care-X [GoYourLife], Pulse O2 [Withings], Vivofit [Garmin], and Loop [Polar Electro]) and one research-based triaxial accelerometer (GT3X+ [ActiGraph]). Criterion measures were total EE from the metabolic chamber (mcTEE) and total steps from the GT3X+ (AGsteps).ResultsPearson correlation coefficients r for 24-hour TEE ranged from .78 (Shine 2, Amazfit) to .96 (Loop) and for steps ranged from 0.20 (GOLiFE) to 0.57 (Vivofit). Mean absolute percent error (MAPE) for TEE ranged from 5.7% (Mi Band 2) to 26.4% (Amazfit) and for steps ranged from 14.2% (Bong 2s) to 27.6% (Loop). TEE estimates from the Mi Band 2, UP3, Vivofit, and Bong 2s were equivalent to mcTEE. Total steps from the Bong 2s were equivalent to AGsteps.ConclusionsOverall, the Bong 2s had the best accuracy for estimating TEE and total steps under simulated free-living conditions. Further research is needed to examine the validity of these devices in different types of physical activities under real-world conditions.
| S-EPMC7819784 | biostudies-literature
Project description:UnlabelledGetting enough sleep, exercising, and limiting sedentary activities can greatly contribute to disease prevention and overall health and longevity. Measuring the full 24-h activity cycle-sleep, sedentary behavior (SED), light-intensity physical activity (LPA), and moderate-to-vigorous physical activity (MVPA)-may now be feasible using small wearable devices.PurposeThis study compared nine devices for accuracy in a 24-h activity measurement.MethodsAdults (n = 40, 47% male) wore nine devices for 24 h: ActiGraph GT3X+, activPAL, Fitbit One, GENEactiv, Jawbone Up, LUMOback, Nike Fuelband, Omron pedometer, and Z-Machine. Comparisons (with standards) were made for total sleep time (Z-machine), time spent in SED (activPAL), LPA (GT3X+), MVPA (GT3X+), and steps (Omron). Analysis included mean absolute percent error, equivalence testing, and Bland-Altman plots.ResultsError rates ranged from 8.1% to 16.9% for sleep, 9.5% to 65.8% for SED, 19.7% to 28.0% for LPA, 51.8% to 92% for MVPA, and 14.1% to 29.9% for steps. Equivalence testing indicated that only two comparisons were significantly equivalent to standards: the LUMOback for SED and the GT3X+ for sleep. Bland-Altman plots indicated GT3X+ had the closest measurement for sleep, LUMOback for SED, GENEactiv for LPA, Fitbit for MVPA, and GT3X+ for steps.ConclusionsCurrently, no device accurately captures activity data across the entire 24-h day, but the future of activity measurement should aim for accurate 24-h measurement as a goal. Researchers should continue to select measurement devices on the basis of their primary outcomes of interest.
| S-EPMC4760880 | biostudies-literature