Association between behavioral phenotypes and sustained use of smartphones and wearable devices to remotely monitor physical activity
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ABSTRACT:
SUBMITTER: Fendrich S
PROVIDER: S-EPMC8563736 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BACKGROUND:There is growing interest in using wearable devices to remotely monitor patient behaviors. However, there has been little evaluation of how often these technologies are used to monitor sleep patterns over longer term periods, particularly among more high-risk patients. OBJECTIVE:The goal of the research was to evaluate the proportion of time that patients with ischemic heart disease used wearable devices to monitor their sleep and identify differences in characteristics of patients with higher versus lower use. METHODS:We evaluated wearable device data from a previously conducted clinical trial testing the use of wearable devices with personalized goal-setting and financial incentives. Patients with ischemic heart disease established a sleep baseline and were then followed for 24 weeks. The proportion of days that sleep data was collected was compared over the 24 weeks and by study arm. Characteristics of patients were compared to groups with high, low, or no sleep data. RESULTS:The sample comprised 99 patients with ischemic heart disease, among which 79% (78/99) used the wearable device to track their sleep. During the 6-month trial, sleep data were collected on 60% (10,024/16,632) of patient-days. These rates declined over time from 77% (4292/5544) in months 1 and 2 to 58% (3188/5544) in months 3 and 4 to 46% (2544/5544) in months 5 and 6. Sleep data were collected at higher rates among the intervention group compared with control (67% vs 55%, P<.001). In the main intervention period (months 3 and 4), patients with higher rates of sleep data were on average older (P=.03), had a history of smoking (P=.007), and had higher rates of commercial health insurance (P=.03). CONCLUSIONS:Among patients with ischemic heart disease in a physical activity trial, a high proportion used wearable devices to track their sleep; however, rates declined over time. Future research should consider larger evaluations coupled with behavioral interventions. TRIAL REGISTRATION:ClinicalTrials.gov NCT02531022; https://clinicaltrials.gov/ct2/show/NCT02531022.
| S-EPMC7175186 | biostudies-literature
Project description:Wearable physical activity (PA) monitors are widely promoted as a means to motivate people to be more active, but the motivational profile of users has never been assessed. This study's purpose was to classify adult users by their motivational regulation scores and examine how these profiles were associated with moderate to vigorous PA (MVPA). Current users (N = 320) recruited across the United States completed a Web-based survey. Motivational regulations were measured using the Behavioral Regulation in Exercise Questionnaire, and associations with MVPA were explored using bivariate correlations. MVPA was more highly correlated with autonomous rather than controlling regulations. A cluster analysis was conducted using the respondents' motivational regulation scores. Five motivational profiles emerged from this analysis, and they differed significantly across motivation and MVPA scores. PA monitor users characterized by more autonomous motives presented with higher MVPA. As technology use increases, assessing the multidimensionality of PA monitor users' motivation may add value when researching PA behaviors.
| S-EPMC7483559 | biostudies-literature
Project description:OBJECTIVE:To determine the feasibility and validity of using wearable activity trackers to test associations between gout flares with physical activity and sleep. METHODS:Participants 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. RESULTS:Forty-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. CONCLUSION:The 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 REGISTRATION:NCT, NCT02855437 . Registered 4 August 2016.
| S-EPMC7398057 | biostudies-literature
Project description:Mobile health monitoring via non-invasive wearable sensors is poised to advance telehealth for older adults and other vulnerable populations. Extreme heat and other environmental conditions raise serious health challenges that warrant monitoring of real-time physiological data as people go about their normal activities. Mobile systems could be beneficial for many communities, including elite athletes, military special forces, and at-home geriatric monitoring. While some commercial monitors exist, they are bulky, require reconfiguration, and do not fit seamlessly as a simple wearable device. We designed, prototyped and tested an integrated sensor platform that records heart rate, oxygen saturation, physical activity levels, skin temperature, and galvanic skin response. The device uses a small microcontroller to integrate the measurements and store data directly on the device for up to 48+ h. continuously. The device was compared to clinical standards for calibration and performance benchmarking. We found that our system compared favorably with clinical measures, such as fingertip pulse oximetry and infrared thermometry, with high accuracy and correlation. Our novel platform would facilitate an individualized approach to care, particularly those whose access to healthcare facilities is limited. The platform also can be used as a research tool to study physiological responses to a variety of environmental conditions, such as extreme heat, and can be customized to incorporate new sensors to explore other lines of inquiry.
| S-EPMC7039288 | biostudies-literature
Project description:ObjectiveDespite 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 methodsWe 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.ResultsA 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.DiscussionThis pilot study showed that wearable beacons can be used to monitor and quantify HCW interactions in inpatient settings.ConclusionTechnology can be used to track HCW physical distancing.
| S-EPMC8672930 | biostudies-literature
Project description:ObjectivesThe research investigated the extent to which students, residents, and faculty members in Canadian medical faculties use mobile devices, such as smartphones (e.g., iPhone, Android, Blackberry) and tablet computers (e.g., iPad), to answer clinical questions and find medical information. The results of this study will inform how health libraries can effectively support mobile technology and collections.MethodsAn electronic survey was distributed by medical librarians at four Canadian universities to medical students, residents, and faculty members via departmental email discussion lists, personal contacts, and relevant websites. It investigated the types of information sought, facilitators to mobile device use in medical information seeking, barriers to access, support needs, familiarity with institutionally licensed resources, and most frequently used resources.ResultsThe survey of 1,210 respondents indicated widespread use of smartphones and tablets in clinical settings in 4 Canadian universities. Third- and fourth-year undergraduate students (i.e., those in their clinical clerkships) and medical residents, compared to other graduate students and faculty, used their mobile devices more often, used them for a broader range of activities, and purchased more resources for their devices.ConclusionsTechnological and intellectual barriers do not seem to prevent medical trainees and faculty from regularly using mobile devices for their medical information searches; however, barriers to access and lack of awareness might keep them from using reliable, library-licensed resources.ImplicationsLibraries should focus on providing access to a smaller number of highly used mobile resources instead of a huge collection until library-licensed mobile resources have streamlined authentication processes.
| S-EPMC3878932 | biostudies-literature
Project description:Low-cost, robust, and reusable continuous glucose monitoring systems that can provide quantitative measurements at point-of-care settings is an unmet medical need. Optical glucose sensors require complex and time-consuming fabrication processes, and their readouts are not practical for quantitative analyses. Here, a wearable contact lens optical sensor was created for the continuous quantification of glucose at physiological conditions, simplifying the fabrication process and facilitating smartphone readouts. A photonic microstructure having a periodicity of 1.6 ?m was printed on a glucose-selective hydrogel film functionalized with phenylboronic acid. Upon binding with glucose, the microstructure volume swelled, which modulated the periodicity constant. The resulting change in the Bragg diffraction modulated the space between zero- and first-order spots. A correlation was established between the periodicity constant and glucose concentration within 0-50 mM. The sensitivity of the sensor was 12 nm mM-1, and the saturation response time was less than 30 min. The sensor was integrated with commercial contact lenses and utilized for continuous glucose monitoring using smartphone camera readouts. The reflected power of the first-order diffraction was measured via a smartphone application and correlated to the glucose concentrations. A short response time of 3 s and a saturation time of 4 min was achieved in the continuous monitoring mode. Glucose-sensitive photonic microstructures may have applications in point-of-care continuous monitoring devices and diagnostics at home settings.
| S-EPMC6107296 | biostudies-literature
Project description:Getting 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.This study compared nine devices for accuracy in a 24-h activity measurement.Adults (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.Error 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.Currently, 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
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:Study objectivesThe use of telemedicine with a mobile application (MA) and a wearable device (WD) for the management of sleep disorders has recently received considerable attention. We designed an MA synchronizable with a WD for insomnia treatment. Our pilot study determined the efficacy of simplified group cognitive behavioral therapy for insomnia (CBT-I) delivered using our MA and assessed participant adherence to and satisfaction with the device.MethodsThe efficacy of the CBT-I using MA (CBT-I-MA) was assessed by comparing sleep variables (sleep efficiency [SE], Insomnia Severity Index [ISI], and Pittsburgh Sleep Quality Inventory [PSQI] scores) before and after a 4-week treatment protocol in 19 patients with insomnia disorder patients. SE was assessed using a sleep diary, actigraphy, and the PSQI.ResultsThe intervention significantly improved all three measures of SE (P < .05), and the response rate to treatment was high (94.7%). Total ISI and PSQI scores and sleep latency, as measured by the sleep diary, improved significantly. Participants showed relatively good adherence to our MA, and sleep diary entries were made on 24.3 ± 3.8 of 28 days. Moreover, 94.7% of the participants reported that our MA was effective for treating insomnia.ConclusionsOur pilot study suggested the clinical usefulness of a CBT-I-MA. We expect that our findings will lead to further development and replication studies of CBT-I-MA.
| S-EPMC5359343 | biostudies-literature