Search

Direct-to-consumer (D2C) wearables are becoming increasingly popular in cardiovascular health management because of their affordability and capability to capture diverse health data. Wearables may enable continuous health care provider-patient partnerships and reduce the volume of episodic clinic-based care (thereby reducing health care costs). However, challenges arise from the unregulated use of these devices, including questionable data reliability, potential misinterpretation of information, unintended psychological impacts, and an influx of clinically nonactionable data that may overburden the health care system. Further, these technologies could exacerbate, rather than mitigate, health disparities. Experience with wearables in atrial fibrillation underscores these challenges. The prevalent use of D2C wearables necessitates a collaborative approach among stakeholders to ensure effective integration into cardiovascular care. Wearables are heralding innovative disease screening, diagnosis, and management paradigms, expanding therapeutic avenues, and anchoring personalized medicine. [Display omitted] • D2C wearables offer affordable and accessible health care data that may facilitate management of cardiovascular disorders. • There are concerns about accuracy, value, unintended psychological responses, and data overload from wearable-derived data. • Wearables promise novel paradigms for disease screening, diagnosis, and management, thereby setting a foundation for personalized medicine. [ABSTRACT FROM AUTHOR]

BackgroundSelf-reported physical activity is often inaccurate. Wearable devices utilizing multiple sensors are now widespread. The aim of this study was to determine acceptability of Fitbit Charge HR for children and their families, and to determine best practices for processing its objective data.MethodsData were collected via Fitbit Charge HR continuously over the course of 3 weeks. Questionnaires were given to each child and their parent/guardian to determine the perceived usability of the device. Patterns of data were evaluated and best practice inclusion criteria recommended.ResultsBest practices were established to extract, filter, and process data to evaluate device wear, r and establish minimum wear time to evaluate behavioral patterns. This resulted in usable data available from 137 (89%) of the sample.ConclusionsActivity trackers are highly acceptable in the target population and can provide objective data over longer periods of wear. Best practice inclusion protocols that reflect physical activity in youth are provided.

Background: Wearables have begun to play a transformative role in health management and disease prevention. Objective: This study examined the use of wearable devices in African American communities in Mississippi, USA, through the lens of church leaders. Methods: We conducted focus groups with church leaders to record their perceptions about the use of wearables of their community members. We conducted six focus groups with a total of 89 church leaders from across the state of Mississippi. The focus groups were designed to contextualize and explain the socio-cognitive processes that provided an understanding of wearable device adoption practices among community members. Participants were male and female church leaders who were recruited from the three Mississippi Districts. The church leaders' perceptions of barriers and challenges to the adoption of consumer wearables in their communities were thoroughly analyzed using thematic analysis. Results: There was great apprehension on the part of community members about the security of the information they entered into the wearable devices and about how that information could be used by other parties. Many community members who understood the value of proactive health behaviors could not afford the high cost of purchasing wearable devices, while others displayed a low level of comfort with technology, believing that wearable use was for younger people. Conclusion: More expansive adoption of wearable devices in Mississippi will depend on the ability of the public health professionals, policy-makers and manufacturers to address the barriers that were identified by this study, thereby enabling the community to have full access to the potential benefits of these technologies.

Background Consumer wearable devices with health and wellness features are increasingly common and may enhance disease detection and management. Yet studies informing relationships between wearable device use, attitudes toward device data, and comprehensive clinical profiles are lacking. Methods and Results WATCH‐IT (Wearable Activity Tracking for Comprehensive Healthcare‐Integrated Technology) studied adults receiving longitudinal primary or ambulatory cardiovascular care in the Mass General Brigham health care system from January 2010 to July 2021. Participants completed a 20‐question electronic survey about perceptions and use of consumer wearable devices, with responses linked to electronic health records. Multivariable logistic regression was used to identify factors associated with device use. Among 214 992 individuals receiving longitudinal primary or cardiovascular care with an active electronic portal, 11 121 responded (5.2%). Most respondents (55.8%) currently used a wearable device, and most nonusers (95.3%) would use a wearable if provided at no cost. Although most users (70.2%) had not shared device data with their doctor previously, most believed it would be very (20.4%) or moderately (34.4%) important to share device‐related health information with providers. In multivariable models, older age (odds ratio [OR], 0.80 per 10‐year increase [95% CI, 0.77–0.82]), male sex (OR, 0.87 [95% CI, 0.80–0.95]), and heart failure (OR, 0.75 [95% CI, 0.63–0.89]) were associated with lower odds of wearable device use, whereas higher median income (OR, 1.08 per 1‐quartile increase [95% CI, 1.04–1.12]) and care in a cardiovascular medicine clinic (OR, 1.17 [95% CI, 1.05–1.30]) were associated with greater odds of device use. Conclusions Among patients in primary and cardiovascular medicine clinics, consumer wearable device use is common, and most users perceive value in wearable health data.

Background: Wearables have begun to play a transformative role in health management and disease prevention. Objective: This study examined the use of wearable devices in African American communities in Mississippi, USA, through the lens of church leaders. Methods: We conducted focus groups with church leaders to record their perceptions about the use of wearables of their community members. We conducted six focus groups with a total of 89 church leaders from across the state of Mississippi. The focus groups were designed to contextualize and explain the socio-cognitive processes that provided an understanding of wearable device adoption practices among community members. Participants were male and female church leaders who were recruited from the three Mississippi Districts. The church leaders’ perceptions of barriers and challenges to the adoption of consumer wearables in their communities were thoroughly analyzed using thematic analysis. Results: There was great apprehension on the part of community members about the security of the information they entered into the wearable devices and about how that information could be used by other parties. Many community members who understood the value of proactive health behaviors could not afford the high cost of purchasing wearable devices, while others displayed a low level of comfort with technology, believing that wearable use wasfor younger people. Conclusion: More expansive adoption of wearable devices in Mississippi will depend on the ability of the public health professionals, policymakers and manufacturers to address the barriers that were identified by this study, thereby enabling the community to have full access to the potential benefits of these technologies. [ABSTRACT FROM AUTHOR]

The capability of measuring specific neurophysiological and autonomic parameters plays a crucial role in the objective evaluation of a human's mental and emotional states. These human aspects are commonly known in the scientific literature to be involved in a wide range of processes, such as stress and arousal. These aspects represent a relevant factor especially in real and operational environments. Neurophysiological autonomic parameters, such as Electrodermal Activity (EDA) and Photoplethysmographic data (PPG), have been usually investigated through research-graded devices, therefore resulting in a high degree of invasiveness, which could negatively interfere with the monitored user's activity. For such a reason, in the last decade, recent consumer-grade wearable devices, usually designed for fitness-tracking purposes, are receiving increasing attention from the scientific community, and are characterized by a higher comfort, ease of use and, therefore, by a higher compatibility with daily-life environments. The present preliminary study was aimed at assessing the reliability of a consumer wearable device, i.e., the Fitbit Sense, with respect to a research-graded wearable, i.e., the Empatica E4 wristband, and a laboratory device, i.e., the Shimmer GSR3+. EDA and PPG data were collected among 12 participants while they performed multiple resting conditions. The results demonstrated that the EDA- and PPG-derived features computed through the wearable and research devices were positively and significantly correlated, while the reliability of the consumer device was significantly lower. [ABSTRACT FROM AUTHOR]

As wearable devices, which allow individuals to track and self-manage their health, become more ubiquitous, the opportunities are growing for researchers to use these sensors within interventions and for data collection. They offer access to data that are captured continuously, passively, and pragmatically with minimal user burden, providing huge advantages for health research. However, the growth in their use must be coupled with consideration of their potential limitations, in particular, digital inclusion, data availability, privacy, ethics of third-party involvement, data quality, and potential for adverse consequences. In this paper, we discuss these issues and strategies used to prevent or mitigate them and recommendations for researchers using wearables as part of interventions or for data collection. [ABSTRACT FROM AUTHOR]

The capability of measuring specific neurophysiological and autonomic parameters plays a crucial role in the objective evaluation of a human’s mental and emotional states. These human aspects are commonly known in the scientific literature to be involved in a wide range of processes, such as stress and arousal. These aspects represent a relevant factor especially in real and operational environments. Neurophysiological autonomic parameters, such as Electrodermal Activity (EDA) and Photoplethysmographic data (PPG), have been usually investigated through research-graded devices, therefore resulting in a high degree of invasiveness, which could negatively interfere with the monitored user’s activity. For such a reason, in the last decade, recent consumer-grade wearable devices, usually designed for fitness-tracking purposes, are receiving increasing attention from the scientific community, and are characterized by a higher comfort, ease of use and, therefore, by a higher compatibility with daily-life environments. The present preliminary study was aimed at assessing the reliability of a consumer wearable device, i.e., the Fitbit Sense, with respect to a research-graded wearable, i.e., the Empatica E4 wristband, and a laboratory device, i.e., the Shimmer GSR3+. EDA and PPG data were collected among 12 participants while they performed multiple resting conditions. The results demonstrated that the EDA- and PPG-derived features computed through the wearable and research devices were positively and significantly correlated, while the reliability of the consumer device was significantly lower.

Background: Although positive airway pressure (PAP) therapy is considered first-line treatment for obstructive sleep apnea (OSA), nonadherence is common. Numerous factors influence PAP use, including a belief that the therapy is important and effective. In theory, providing information to patients about their blood oxygen levels during sleep (which may be low when PAP is not used), juxtaposed to information about their PAP use, may influence a patient's beliefs about therapy and increase PAP use. With the advent of consumer wearable smartwatches' blood oxygen saturation monitoring capability (and the existing routine availability of PAP use data transmitted via modem to clinical dashboards), there is an opportunity to provide this combination of information to patients., Objective: This study aims to test the feasibility, acceptability, and preliminary efficacy of the Chronic Care Management With Wearable Devices in Patients Prescribed Positive Airway Pressure Therapy (mPAP), a program that augments current PAP therapy data with consumer-grade wearable device to promote self-management of PAP therapy for OSA in a pilot randomized waitlist-controlled clinical trial., Methods: This is a single-blinded randomized controlled trial. We will randomize 50 individuals with a history of OSA, who receive care from a Department of Veterans Affairs medical center in the Los Angeles area and are nonadherent to prescribed PAP therapy, into either an immediate intervention group or a waitlist control group. During a 28-day intervention, the participants will wear a study-provided consumer wearable device and complete a weekly survey about their OSA symptoms. A report that summarizes consumer wearable-provided oxygen saturation values, PAP use derived from modem data, and patient-reported OSA symptoms will be prepared weekly and shared with the patient. The immediate intervention group will begin intervention immediately after randomization (T1). Assessments will occur at week 5 (T3; 1 week after treatment for the immediate intervention group and repeat baseline for the waitlist control group) and week 11 (T5; follow-up for the immediate intervention group and 1 week after treatment for the waitlist control group). The primary outcome will be the change in 7-day PAP adherence (average minutes per night) from T1 to T3. The primary analysis will be a comparison of the primary outcome between the immediate intervention and the waitlist control groups (intention-to-treat design), using a 2-sample, 2-sided t test on change scores (unadjusted)., Results: Recruitment began in October 2023. Data analysis is expected to begin in October 2024 when all follow-ups are complete, and a manuscript summarizing trial results will be submitted following completion of data analysis., Conclusions: Findings from the study may provide additional insights on how patients with OSA might use patient-generated health data collected by consumer wearables to inform self-management of OSA and possibly increase their use of PAP therapy., Trial Registration: ClinicalTrials.gov NCT06039865; https://clinicaltrials.gov/study/NCT06039865., International Registered Report Identifier (irrid): DERR1-10.2196/60769., (©Selene Mak, Garrett Ash, Li-Jung Liang, Erin Der-McLeod, Sara Ghadimi, Anjali Kewalramani, Saadia Naeem, Michelle Zeidler, Constance Fung. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 19.09.2024.)

Background: Self-reported physical activity is often inaccurate. Wearable devices utilizing multiple sensors are now widespread. The aim of this study was to determine acceptability of Fitbit Charge HR for children and their families, and to determine best practices for processing its objective data. Methods: Data were collected via Fitbit Charge HR continuously over the course of 3 weeks. Questionnaires were given to each child and their parent/guardian to determine the perceived usability of the device. Patterns of data were evaluated and best practice inclusion criteria recommended. Results: Best practices were established to extract, filter, and process data to evaluate device wear, r and establish minimum wear time to evaluate behavioral patterns. This resulted in usable data available from 137 (89%) of the sample. Conclusions: Activity trackers are highly acceptable in the target population and can provide objective data over longer periods of wear. Best practice inclusion protocols that reflect physical activity in youth are provided.

Consumer digital technology is rapidly evolving, allowing users to manage their health in a simple, non-invasive manner. However, there are few studies revealing if using digital technology as part of an intervention really has an impact in consumer health compared with traditional strategies. The objective of the current study is to compare two groups (MTB; n = 18, 46.1 ± 10.4 years and MTBAPP; n = 19, 45.3 ± 6.40 years) of overweight, prehypertensive individuals in losing weight and lowering their blood pressure. Both were provided with nutritionist-guided recommendations, a wearable tracking device and a dietary supplement that has previously been proven to help lose body weight and lower blood pressure. In addition, one of the groups (MTBAPP) used a mobile app specifically designed for the intervention. Blood pressure, body composition, triglyceride level, peak expiratory flow, forced expiratory volume in the first second and maximum oxygen volume were measured at different time points. In addition, participants were monitored with an activity bracelet throughout the intervention. As a result, both groups significantly lost body weight, while the group using the app additionally improved blood pressure levels and lowered fat mass. Furthermore, the app users significantly increased the number of daily steps and decreased sedentary time. In conclusion, the addition of a mobile app with daily reminders to follow healthy lifestyle recommendations increased physical activity and overall improved blood pressure and fat mass levels when compared with a group performing the same intervention but in absence of the mobile application.

Sleep disturbances and sleep disorders are prevalent in children/adolescents and have a bidirectional relationship with pediatric medical and mental health disorders. Screening tools and mechanisms for the evaluation and treatment of sleep disturbances and sleep disorders in the pediatric mental health clinic are less well-known; hence, sleep disturbances and disorders are under-recognized in the pediatric clinics. We present specific, validated screening and evaluation tools to identify sleep disturbances and sleep disorders in children/adolescents. We offer guidance related to the use of consumer wearables for sleep assessments and use of sleep telemedicine in pediatric mental health and primary care clinics., Competing Interests: Disclosure The authors have nothing to disclose., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Background: Consumer wearable devices with health and wellness features are increasingly common and may enhance disease detection and management. Yet studies informing relationships between wearable device use, attitudes toward device data, and comprehensive clinical profiles are lacking., Methods and Results: WATCH-IT (Wearable Activity Tracking for Comprehensive Healthcare-Integrated Technology) studied adults receiving longitudinal primary or ambulatory cardiovascular care in the Mass General Brigham health care system from January 2010 to July 2021. Participants completed a 20-question electronic survey about perceptions and use of consumer wearable devices, with responses linked to electronic health records. Multivariable logistic regression was used to identify factors associated with device use. Among 214 992 individuals receiving longitudinal primary or cardiovascular care with an active electronic portal, 11 121 responded (5.2%). Most respondents (55.8%) currently used a wearable device, and most nonusers (95.3%) would use a wearable if provided at no cost. Although most users (70.2%) had not shared device data with their doctor previously, most believed it would be very (20.4%) or moderately (34.4%) important to share device-related health information with providers. In multivariable models, older age (odds ratio [OR], 0.80 per 10-year increase [95% CI, 0.77-0.82]), male sex (OR, 0.87 [95% CI, 0.80-0.95]), and heart failure (OR, 0.75 [95% CI, 0.63-0.89]) were associated with lower odds of wearable device use, whereas higher median income (OR, 1.08 per 1-quartile increase [95% CI, 1.04-1.12]) and care in a cardiovascular medicine clinic (OR, 1.17 [95% CI, 1.05-1.30]) were associated with greater odds of device use., Conclusions: Among patients in primary and cardiovascular medicine clinics, consumer wearable device use is common, and most users perceive value in wearable health data.

Purpose: This study was initiated to examine factors that motivate African American students who use wearable devices at an HBCU in Mississippi., Method: We conducted a correlational research study on undergraduate and graduate students from a southern USA university. The stratified random sample comprised a total of 239 students. The responses of the students were analyzed using the Fisher exact test to determine whether or not there was a significant association between the categorical demographic variables (age, gender, ethnicity, and student classification) and the students' motivation for using a wearable device., Results: Students used wearables for one main reason, to help them increase their awareness of their health status because they understand the importance of tracking their health metrics to boost their health status and reduce risk factors for developing chronic diseases. Students also demonstrated that they understand the value of tracking health information, such as heart rate and blood pressure, as a way to reduce the prevalence and impact of risk factors that can lead to chronic diseases., Conclusions: Wearables enable individuals to regularly observe, measure, and record their physical status and physiological measures, and facilitate medication adherence by enabling individuals to maintain their prescribed medication regimen adequately. The data collected and stored through these wearables can provide data that will be useful for medical personnel in their treatment of patients and in developing strategies for prevention and intervention for the larger community., Competing Interests: The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2023.)

Introduction: The use of wearable activity monitors has seen rapid growth; however, the mode and intensity of exercise could affect the validity of heart rate (HR) and caloric (energy) expenditure (EE) readings. There is a lack of data regarding the validity of wearable activity monitors during graded cycling regimen and a standard resistance exercise. The present study determined the validity of eight monitors for HR compared with an ECG and seven monitors for EE compared with a metabolic analyzer during graded cycling and resistance exercise. Methods: Fifty subjects (28 women, 22 men) completed separate trials of graded cycling and three sets of four resistance exercises at a 10-repetition-maximum load. Monitors included the following: Apple Watch Series 2, Fitbit Blaze, Fitbit Charge 2, Polar H7, Polar A360, Garmin Vivosmart HR, TomTom Touch, and Bose SoundSport Pulse (BSP) headphones. HR was recorded after each cycling intensity and after each resistance exercise set. EE was recorded after both protocols. Validity was established as having a mean absolute percent error (MAPE) value of ≤10%. Results: The Polar H7 and BSP were valid during both exercise modes (cycling: MAPE = 6.87%, R = 0.79; resistance exercise: MAPE = 6.31%, R = 0.83). During cycling, the Apple Watch Series 2 revealed the greatest HR validity (MAPE = 4.14%, R = 0.80). The BSP revealed the greatest HR accuracy during resistance exercise (MAPE = 6.24%, R = 0.86). Across all devices, as exercise intensity increased, there was greater underestimation of HR. No device was valid for EE during cycling or resistance exercise. Conclusions: HR from wearable devices differed at different exercise intensities; EE estimates from wearable devices were inaccurate. Wearable devices are not medical devices, and users should be cautious when using these devices for monitoring physiological responses to exercise. [ABSTRACT FROM AUTHOR]

The market for smartphones, smartwatches, and wearable devices is booming. In recent years, individuals and researchers have used these devices as additional tools to monitor and track sleep, physical activity, and behavior. Their use in sleep research and clinical applications could address the difficulties in scaling up studies that rely on polysomnography, the gold-standard. However, the use of commercial devices for large-scale sleep studies is not without challenges. With this in mind, this paper presents an extensive review of sleep monitoring systems and the techniques used in their development. We also discuss their performance in terms of reliability and validity, and consider the needs and expectations of users, whether they are experts, patients, or the general public. Through this review, we highlight a number of challenges with current studies: a lack of standard evaluation methods for consumer-grade devices (e.g., reliability and validity assessment); limitations in the populations studied; consumer expectations of monitoring devices; constraints on the resources of consumer-grade devices (e.g., power consumption). [ABSTRACT FROM AUTHOR]

Sleep disturbances and sleep disorders are prevalent in children/adolescents and have a bidirectional relationship with pediatric medical and mental health disorders. Screening tools and mechanisms for the evaluation and treatment of sleep disturbances and sleep disorders in the pediatric mental health clinic are less well-known; hence, sleep disturbances and disorders are under-recognized in the pediatric clinics. We present specific, validated screening and evaluation tools to identify sleep disturbances and sleep disorders in children/adolescents. We offer guidance related to the use of consumer wearables for sleep assessments and use of sleep telemedicine in pediatric mental health and primary care clinics., Competing Interests: Disclosure The authors have nothing to disclose., (Copyright © 2020 Elsevier Inc. All rights reserved.)