Wearable Fitness Trackers Research Articles

A Randomized Controlled Trial of Gamification to Increase Physical Activity Among Black and Hispanic Breast and Prostate Cancer Survivors: Rationale and Design of the ALLSTAR Clinical Trial

Survivors of breast and prostate cancer, especially those that are Black and/or Hispanic, are at high risk for cardiovascular events. Physical activity can reduce the risk of cardiovascular events in cancer survivors, but Black and Hispanic people are less likely to engage in routine physical activity. Concepts from behavioral economics have been used to design scalable, low-touch, gamification interventions that increase physical activity in individuals at high risk for cardiovascular events, but the effectiveness of these strategies in Black and Hispanic survivors of breast and prostate cancer is uncertain. ALLSTAR (NCT05176756) is a pragmatic, virtual, randomized controlled trial designed to evaluate the effectiveness of a gamification intervention informed by behavioral economic concepts to increase daily physical activity in Black and Hispanic breast and prostate cancer survivors who received cardiotoxic therapies and have additional risk factors for cardiovascular disease. Patients were either referred by their cancer care team or identified by electronic health record searches; contacted by letter, email, text message and/or phone; and complete enrollment and informed consent on the Penn Way to Health online platform. Patients are then provided with a wearable fitness tracker, establish a baseline daily step count, set a goal to increase daily step count by 1500-3000 steps from baseline, and are randomized 1:1 to control or gamification. Interventions continue for 6 months, with follow-up for an additional 3 months to evaluate the durability of behavior change. The trial has met its enrollment goal of 150 participants, with a primary endpoint of change from baseline in daily steps over the 6-month intervention period. Key secondary endpoints include change from baseline in daily steps over the 3-month post-intervention follow-up period, change in moderate to vigorous physical activity over the intervention and follow-up periods, and change in patient-reported measures of physical function, fatigue, and overall quality of life. ALLSTAR is a virtual, pragmatic randomized clinical trial powered to demonstrate whether gamification is superior to control in increasing physical activity in Black and Hispanic breast and prostate cancer survivors. Its results will have important implications for strategies to promote physical activity in survivors of breast and prostate cancer, specifically among minority populations. clinicaltrials.gov; https://clinicaltrials.gov/study/NCT05176756.

Assessment of heart rate measurements by commercial wearable fitness trackers for early identification of metabolic syndrome risk

Metabolic syndrome increases the risks of cardiovascular diseases, type 2 diabetes, and certain cancers. The early detection of metabolic syndrome is clinically relevant, as it enables timely and targeted interventions. In the current study, we aimed to investigate the association between metabolic syndrome and heart rate measured using wearable devices in a real-world setting and compare this association with that for clinical resting heart rate. Data from 564 middle-aged adults who wore wearable devices for at least 7 days with a minimum daily wear time of 20 h were analyzed. The results showed significantly elevated all-day, sleeping, minimum, and inactive heart rates in men with pre-metabolic or metabolic syndrome compared with those in normal individuals, whereas sleeping heart rate and heart rate dips were significantly increased and decreased, respectively, in women with metabolic syndrome. After adjusting for confounders, every 10-beats-per-minute increment in all-day, sleeping, minimum, and inactive heart rates in men corresponded to odds ratios of 2.80 (95% confidence interval 1.53–5.44), 3.06 (1.57–6.40), 4.21 (1.87–10.47), and 3.09 (1.64–6.29), respectively, for the presence of pre-metabolic or metabolic syndrome. In women, the association was significant only for heart rate dips (odds ratio = 0.49 [95% confidence interval 0.25–0.96] for every 10% increment). Models incorporating inactive or minimum heart rate in men and heart rate dip in women demonstrated better fits, as indicated by lower Akaike information criterion values (170.3 in men and 364.9 in women), compared with models that included clinical resting heart rate (173.4 in men and 369.1 in women). These findings suggest that the heart rate indices obtained from wearable devices may facilitate early identification of metabolic syndrome.

Influence of Technology Integration in Physical Education on Student Engagement and Fitness Outcomes in American Schools

Purpose: The aim of the study was to analyze the influence of technology integration in physical education on student engagement and fitness outcomes in American schools. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: The use of wearable fitness trackers, interactive apps, and virtual sports tools has enhanced student participation, making PE classes more interactive and personalized. Students are more motivated to engage in physical activities when they can track their progress and receive instant feedback. Additionally, technology has helped teachers tailor fitness programs to meet individual student needs, leading to improved fitness outcomes such as increased cardiovascular endurance and overall physical activity levels. Unique Contribution to Theory, Practice and Policy: Self-determination theory (SDT), the technology acceptance model (tam) & constructivist learning theory may be used to anchor future studies on the influence of technology integration in physical education on student engagement and fitness outcomes in American schools. Schools should strategically integrate various technologies, such as wearable fitness trackers, interactive apps, and VR, into physical education curricula. Educational policymakers should allocate funding and resources to support the integration of technology in physical education.

Comparing sleep measures in cancer survivors: self-reported sleep diary versus objective wearable sleep tracker.

Cancer survivors are increasingly using wearable fitness trackers, but it is unclear if they match traditional self-reported sleep diaries. We aimed to compare sleep data from Fitbit and the Consensus Sleep Diary (CSD) in this group. We analyzed data from two randomized clinical trials, using both CSD and Fitbit to collect sleep outcomes: total sleep time (TST), wake time after sleep onset (WASO), number of awakenings (NWAK), time in bed (TIB), and sleep efficiency (SE). Insomnia severity was measured by Insomnia Severity Index (ISI). We used the Wilcoxon signed rank test, Spearman's rank correlation coefficients, and the Mann-Whitney test to compare sleep outcomes and assess their ability to distinguish insomnia severity levels between CSD and Fitbit data. Among 62 participants, compared to CSD, Fitbit recorded longer TST by an average of 14.6 (SD = 84.9) minutes, longer WASO by an average of 28.7 (SD = 40.5) minutes, more NWAK by an average of 16.7 (SD = 6.6) times per night, and higher SE by an average of 7.1% (SD = 14.4); but shorter TIB by an average of 24.4 (SD = 71.5) minutes. All the differences were statistically significant (all p < 0.05), except for TST (p = 0.38). Moderate correlations were found for TST (r = 0.41, p = 0.001) and TIB (r = 0.44, p < 0.001). Compared to no/mild insomnia group, participants with clinical insomnia reported more NWAK (p = 0.009) and lower SE (p = 0.029) as measured by CSD, but there were no differences measured byFitbit. TST was the only similar outcome between Fitbit and CSD. Our study highlights the advantages, disadvantages, and clinical utilization of sleep trackers in oncology.

Physical Fitness Test Data Analysis and Training Program Recommendation Based on Machine Learning

Physical fitness is the state of being physically healthy and capable of performing daily tasks with vigor and resilience. Physical fitness and machine learning intersect in various ways, primarily through the use of wearable devices, fitness apps, and data analysis. Wearable fitness trackers equipped with sensors, such as heart rate monitors, accelerometers, and GPS trackers, collect vast amounts of data on individuals' physical activity, sleep patterns, and vital signs. The paper presents an innovative approach to physical fitness assessment and training program recommendation using the Gradient Probabilistic Automated Recommender System with Machine Learning (GPA-RS-ML). This system utilizes machine learning techniques to assess fitness data from individuals and then suggests training programs that are customized to their specific goals and needs. By incorporating gradient values and probabilistic predictions, the GPA-RS-ML algorithm offers a comprehensive and individualized approach to fitness training, enhancing the efficiency and effectiveness of training interventions. The study demonstrates the efficacy of the GPA-RS-ML system in accurately predicting suitable training programs for participants, considering their unique fitness profiles and preferences. This research contributes to the advancement of automated fitness assessment and recommendation systems, providing a valuable tool for fitness professionals and enthusiasts to optimize fitness outcomes and improve adherence to training regimens.

Body composition, physical activity, and menopause symptoms: how do they relate?

This study characterized the impact of physical activity (light, moderate, and vigorous [VIG] active minutes per day) and body composition (percent body fat [%BF] and fat-free mass index) on total menopausal symptoms (TMSs) in 72 premenopausal, perimenopausal (PERI), or postmenopausal women. Activity minutes were collected from wearable fitness trackers. Body composition was evaluated using a whole-body dual-energy x-ray absorptiometry scan. TMSs were quantified using The North American Menopause Society Questionnaire. Significant associations were observed between TMSs and %BF ( r = 0.464, P < 0.001) and VIG ( r = -0.245, P = 0.038). %BF and VIG were significant predictors for TMSs across groups ( R2 = 0.146 and R2 = 0.092, respectively), but only %BF maintained for PERI ( R2 = 0.421, P < 0.001). %BF predicted nearly half of the variance in PERI TMSs, whereas VIG predicted 9% of the sample variance, demonstrating an important influence of body fat accumulation and intense physical activity in the menopause transition. High-intensity exercise interventions to alleviate body composition changes may also reduce menopausal-related symptoms for PERI women.

Life Satisfaction Factors, Stress, and Depressive Symptoms among Young Women Living in Urban Kampala: Findings from the TOPOWA Project Pilot Studies.

Young women living in Kampala, Uganda, often face adversities related to Social Determinants of Mental Health (SDoMH) including poverty, food scarcity, environmental stressors such as high levels of community violence, and lack of adequate healthcare access. Two consecutive pilot studies were conducted to assess the feasibility and acceptability of survey questions, wearable fitness trackers, and daily diaries before launching a larger prospective cohort study. Preliminary associations between SDoMH factors with depressive symptoms, stress levels, and life satisfaction were examined among the total sample of 60 women across two pilot studies. A total of 32.2% of respondents (out of n = 59) reported being depressed most or all of the time in the past 30 days. Frequent depressive symptoms correlated with food insecurity (χ2 = 5.38, df = 1, p = 0.02). Higher stress levels were significantly associated with lower overall life satisfaction scores (t = 2.74, df = 6.20, p = 0.03). Additionally, frequent depressive symptoms were associated with lower satisfaction scores in the living conditions and lifestyle domain (t = 2.22, df = 36.18, p = 0.03). However, overall life satisfaction scores and other domains (social relationships and personal independence) were not statistically associated with frequent depressive symptoms. Identifying the most impactful SDoMH factors among young women in Kampala can inform targeted approaches to improve mental health outcomes.

Developing a novel mobile application for cognitive behavioral therapy for insomnia for people with schizophrenia: integration of wearable and environmental sleep sensors

BackgroundPeople with serious mental illnesses (SMIs) have three-fold higher rates of comorbid insomnia than the general population, which has downstream effects on cognitive, mental, and physical health. Cognitive Behavioral Therapy for Insomnia (CBT-i) is a safe and effective first-line treatment for insomnia, though the therapy’s effectiveness relies on completing nightly sleep diaries which can be challenging for some people with SMI and comorbid cognitive deficits. Supportive technologies such as mobile applications and sleep sensors may aid with completing sleep diaries. However, commercially available CBT-i apps are not designed for individuals with cognitive deficits. To aid with this challenge, we have developed an integrated mobile application, named “Sleep Catcher,” that will automatically incorporate data from a wearable fitness tracker and a bed sensor to track nightly sleep duration, overnight awakenings, bed-times, and wake-times to generate nightly sleep diaries for CBT-i.MethodsThe application development process will be described—writing algorithms to generating useful data, creating a clinician web portal to oversee patients and the mobile application, and integrating sleep data from device platforms and user input.ResultsThe mobile and web applications were developed using Flutter, IBM Code Engine, and IBM Cloudant database. The mobile application was developed with a user-centered approach and incremental changes informed by a series of beta tests. Special user-interface features were considered to address the challenges of developing a simple and effective mobile application targeting people with SMI.ConclusionThere is strong potential for synergy between engineering and mental health expertise to develop technologies for specific clinical populations. Digital health technologies allow for the development of multi-disciplinary solutions to existing health disparities in vulnerable populations, particularly in people with SMI.

Security and Privacy Issues in Internet of Things (IoT) Devices Using COPRAS Method

This paper explores various security and privacy issues inherent in IoT devices, ranging from vulnerabilities in device firmware and software to data breaches and unauthorized access. We delve into the challenges of securing IoT devices due to their resource constraints, diverse communication protocols, and often lax security practices during development. Additionally, we discuss privacy implications stemming from the collection and sharing of sensitive personal data by IoT devices, as well as the potential for surveillance and data misuse. Furthermore, we examine the implications of IoT devices in critical infrastructure and industrial systems, where security breaches can have severe consequences. Finally, we propose potential solutions and best practices to address these challenges, including robust encryption methods, regular security updates, and improved authentication mechanisms, to ensure the security and privacy of IoT devices in an increasingly connected world. The exponential growth of IoT devices across various sectors such as smart homes, healthcare, transportation, and industrial automation underscores the importance of ensuring their security and privacy. As these devices become more integrated into daily life and critical infrastructure, any vulnerability can have widespread and severe consequences. The evaluation of alternative performances through Complex Proportionality Assessment (COPRAS) requires an understanding of key criteria, exploration of options, and comparison of relevant facts. Meeting the decision-makers' desire for comparing grades involves choosing among multiple options based on predetermined competing requirements. COPRAS offer a method for such assessments in real-world scenarios, where criteria are nuanced and values cannot be quantified numerically. From the result smart thermostat got the first rank whereas wearable fitness tracker is having the lowest rank.

Perioperative Nutritional Support by a Multidisciplinary Team for Patients with Esophageal Cancer

Esophageal cancer surgery is a highly invasive procedure, and a multidisciplinary team approach is crucial for safe perioperative management of patients without complications. The Hamamatsu Perioperative Care Team (HOPE) has been established, which is a multidisciplinary team that promotes safer and more reliable perioperative care. HOPE has proven effective in preventing post-esophagectomy pneumonia and weight loss. Currently, HOPE is being developed through comprehensive staff training and the implementation of innovative features, including treatment diaries and wearable fitness trackers. This article explores the benefits of collaborative medical practices and the future objectives of HOPE, whilst also examining the progress of perioperative team medicine in Japan.

Developing a Smartwatch-Based Healthcare Application: Notes to Consider.

Wearable devices and fitness trackers have gained popularity in healthcare and telemedicine as tools to reduce hospitalization costs, improve personalized health management, and monitor patients in remote areas. Smartwatches, particularly, offer continuous monitoring capabilities through step counting, heart rate tracking, and activity monitoring. However, despite being recognized as an emerging technology, the adoption of smartwatches in patient monitoring systems is still at an early stage, with limited studies delving beyond their feasibility. Developing healthcare applications for smartwatches faces challenges such as short battery life, wearable comfort, patient compliance, termination of non-native applications, user interaction difficulties, small touch screens, personalized sensor configuration, and connectivity with other devices. This paper presents a case study on designing an Android smartwatch application for remote monitoring of geriatric patients. It highlights obstacles encountered during app development and offers insights into design decisions and implementation details. The aim is to assist programmers in developing more efficient healthcare applications for wearable systems.

Maximizing Endurance: Exercise Physiology's Role in Elevating Athletic Performance

This article provides a comprehensive overview of the role of exercise physiology in enhancing athletic performance, with a specific focus on endurance sports. It begins by introducing the concept of exercise physiology and its significance in sports science, emphasizing the importance of endurance in athletic pursuits. The article then delves into the science of exercise physiology, defining key terms and explaining how the discipline studies the body's responses and adaptations to physical activity. It highlights crucial physiological factors influencing endurance, such as VO2 max and lactate threshold. The principles of endurance training are explored, detailing training methodologies like overload, specificity, and recovery, and their application in endurance training programs. The article also discusses the critical roles of nutrition, hydration, and psychological aspects, including mental toughness and coping strategies for fatigue. The impact of technological advancements, such as wearable fitness trackers and training software, is examined, demonstrating how these tools aid in monitoring and enhancing endurance training. Real-world case studies are presented to illustrate the practical application of exercise physiology principles, showcasing how athletes across various sports have benefited from tailored training programs. The article concludes with a summary of the key points and a reflective note on the future of endurance training, highlighting potential areas of research that could further advance our understanding and application of exercise physiology in sports.

Digital technology for delivering and monitoring exercise programs for people with cystic fibrosis.

Digital technology for delivering and monitoring exercise programs for people with cystic fibrosis.

The brain health champion study: A health coaching intervention with mobile technology in older adults with mild cognitive impairment or risk factors for dementia – An update

AbstractBackgroundExtensive evidence suggests that adherence to brain‐healthy behaviors can slow the rate of cognitive decline and decrease risk of dementia. We previously demonstrated that a health coaching intervention, including weekly phone calls, facilitated adherence to recommendations for brain‐healthy behaviors in older adults with mild cognitive impairment (MCI) or mild dementia. The current study extends this research to include cognitively normal, older adults at risk for dementia and adds a mobile health platform, two‐way texting, and wearable fitness trackers, to the health coaching intervention. Although subjects are still enrolling, the number of participants has increased substantially from our earlier report and data show promising trends.MethodParticipants, age 60‐79, with MCI or dementia risk factors are being randomized to the Brain Health Champion (BHC) intervention or a counseling and education (CE) control. In BHC, with guidance from a health coach, participants set personalized goals, reinforced by weekly video calls, mobile messaging, one dietitian consult, and 30‐minute in‐person or virtual visits every six weeks. In CE, educational materials sent every six weeks supplement usual care. Changes in physical activity, diet, social/cognitive engagement, neuropsychological test scores, and metrics of behavioral health are being measured over six months using questionnaires, wearable fitness trackers, and photographed food logs. Maintenance of behavior changes is also being assessed six months post‐intervention.ResultThirty‐four participants have enrolled in the study, with 27 (15 BHC, 12 CE) completers to date. All participants successfully operated the mobile technology by themselves or with caregivers’ assistance. Current trends show BHC participants increased participation in cognitive activities and adherence to a Mediterranean diet based on photographed food logs compared to CE. Participants in both arms show significantly increased scores on the composite neuropsychological assessment (pre‐ and post‐study), quality of life measures, and an increase in active minutes from pre‐ to post‐assessments.ConclusionTrends in the data indicate that the BHC program may be effective for promoting brain‐healthy behaviors, particularly increasing cognitive activities and Mediterranean diet adherence. Additionally, participating in a brain health study, regardless of intervention, may promote meaningful changes in quality of life and improved cognition.

Fitness Application with Music Player &amp; Heart Rate Measurement

Abstract: After the usage of loads of health apps on a day after day foundation we started to become pissed off with all the litter and inappropriate capabilities protected with them. Some of those apps are too complicated and might do away with from the apps most important purpose. Simplicity ought to move a protracted manner in a health/health application. This is one in every of the motives we believed constructing a less complicated health app might be an excellent concept. We are very lively person who takes element in sports activities in addition to attending the fitness center regularly. There have been matters we observed myself doing on a day after day foundation which we felt ought to be protected in an app. There are such a lot of complicated and indulgent apps out there for nearly each thing of health/health and to be sincere there truly isn’t much that hasn’t already been carried out on this market. But we had the concept that we desired to create an app that might put into effect every of those factors simply, with a purpose to be hassle loose and now no longer do away with from the intention which the person set out withinside the first place. There is the hike in the technology where people are attracted to the health equipment such as smart watches, fitness applications and many other techs. Fitness trackers software, which works in conjunction with a wearable Fitness trackers watch that records your steps and displays your pulmonary heart rate on a video display. But, despite being in the kingdom of the art, all of those apps have one flaw in common: they're crammed with unnecessary features that detract from the initial concept and distract the user. we for one while running out need a hassle-unfastened interplay with an application, we need to get in there and get it done

Moderate intensity exercise in pregnant patients with cardiovascular disease: A pilot study

Exercise in pregnancy has proven health benefits, yet the safety of exercise in patients with pre-existing cardiovascular disease (CVD) has not been established. Our aim was to determine the feasibility and safety profile of moderate intensity exercise during pregnancy in patients with CVD, compared with those without CVD. This is a prospective single center pilot study of a moderate intensity exercise regimen, with data collection through wearable fitness trackers and personal exercise logs in pregnant patients with and without pre-existing CVD. The primary outcome was Doppler umbilical artery systolic to diastolic (S/D) ratio measured between 32 and 34 weeks' gestation. The secondary outcomes were adverse maternal and fetal events, trends in wearable fitness tracker data, C-reactive protein levels, and weight changes. At baseline, the CVD group (62% congenital heart disease) took part in more prepregnancy walking, less weightlifting, and had a higher body mass index compared to the control group, and on average walked 539 fewer steps per day during pregnancy than the control group. Resting heart rate (HR) was found to increase in both groups up to 30 weeks' gestation. The cardiovascular disease group displayed an overall lower exercise intensity, as measured by the ability to increase HR with exercise over resting heart rate 1 hour prior to exercise at study baseline (45% vs 59% P < .001). Umbilical artery S/D ratio was normal in both groups. No differences were seen in adverse events between groups. This pilot study of moderate intensity exercise in pregnant individuals with pre-existing CVD demonstrated that patients with CVD were not able to increase their HR during exercise throughout pregnancy compared to those in the control group. Although a small study group, this data supports the hypothesis that exercise interventions during pregnancy for patients with CVD are feasible without evidence abnormal fetal Doppler profiles. Further studies using wearable fitness trackers may provide the opportunity to understand how to safely tailor exercise programs to pregnant individuals with CVD.

A randomized controlled trial of gamification, financial incentives, or both to increase physical activity among patients with elevated risk for cardiovascular disease: rationale and design of the be active study

Higher levels of physical activity are associated with improvements in cardiovascular health, and consensus guidelines recommend that individuals with or at risk for atherosclerotic cardiovascular disease (ASCVD) participate in regular physical activity. However, most adults do not achieve recommended levels of physical activity. Concepts from behavioral economics have been used to design scalable interventions that increase physical activity over short time periods, but the longer-term efficacy of these strategies is uncertain. BE ACTIVE (NCT03911141) is a pragmatic, virtual, randomized controlled trial designed to evaluate the effectiveness of 3 strategies informed by behavioral economic concepts to increase daily physical activity in patients with established ASCVD or 10-year ASCVD risk > 7.5% who are seen in primary care and cardiology clinics affiliated with the University of Pennsylvania Health System. Patients are contacted by email or text message, and complete enrollment and informed consent on the Penn Way to Health online platform. Patients are then provided with a wearable fitness tracker, establish a baseline daily step count, set a goal to increase daily step count by 33% to 50%, and are randomized 1:2:2:2 to control, gamification, financial incentives, or both gamification and financial incentives. Interventions continue for 12 months, with follow-up for an additional 6 months to evaluate the durability of behavior change. The trial has met its enrollment goal of 1050 participants, with a primary endpoint of change from baseline in daily steps over the 12-month intervention period. Key secondary endpoints include change from baseline in daily steps over the 6-month post-intervention follow-up period and change in moderate to vigorous physical activity over the intervention and follow-up periods. If the interventions prove effective, their effects on life expectancy will be compared with their costs in cost-effectiveness analysis. BE ACTIVE is a virtual, pragmatic randomized clinical trial powered to demonstrate whether gamification, financial incentives, or both are superior to attention control in increasing physical activity. Its results will have important implications for strategies to promote physical activity in patients with or at risk for ASCVD, as well as for the design and implementation of pragmatic virtual clinical trials within health systems.

Effects of Wearable Fitness Trackers and Activity Adequacy Mindsets on Affect, Behavior, and Health: Longitudinal Randomized Controlled Trial.

There is some initial evidence suggesting that mindsets about the adequacy and health consequences of one's physical activity (activity adequacy mindsets [AAMs]) can shape physical activity behavior, health, and well-being. However, it is unknown how to leverage these mindsets using wearable technology and other interventions. This research examined how wearable fitness trackers and meta-mindset interventions influence AAMs, affect, behavior, and health. A total of 162 community-dwelling adults were recruited via flyers and web-based platforms (ie, Craigslist and Nextdoor; final sample size after attrition or exclusion of 45 participants). Participants received an Apple Watch (Apple Inc) to wear for 5 weeks, which was equipped with an app that recorded step count and could display a (potentially manipulated) step count on the watch face. After a baseline week of receiving no feedback about step count, participants were randomly assigned to 1 of 4 experimental groups: they received either accurate step count (reference group; 41/162, 25.3%), 40% deflated step count (40/162, 24.7%), 40% inflated step count (40/162, 24.7%), or accurate step count+a web-based meta-mindset intervention teaching participants the value of adopting more positive AAMs (41/162, 25.3%). Participants were blinded to the condition. Outcome measures were taken in the laboratory by an experimenter at the beginning and end of participation and via web-based surveys in between. Longitudinal analysis examined changes within the accurate step count condition from baseline to treatment and compared them with changes in the deflated step count, inflated step count, and meta-mindset conditions. Participants receiving accurate step counts perceived their activity as more adequate and healthier, adopted a healthier diet, and experienced improved mental health (Patient-Reported Outcomes Measurement Information System [PROMIS]-29) and aerobic capacity but also reduced functional health (PROMIS-29; compared with their no-step-count baseline). Participants exposed to deflated step counts perceived their activity as more inadequate; ate more unhealthily; and experienced more negative affect, reduced self-esteem and mental health, and increased blood pressure and heart rate (compared with participants receiving accurate step counts). Inflated step counts did not change AAM or most other outcomes (compared with accurate step counts). Participants receiving the meta-mindset intervention experienced improved AAM, affect, functional health, and self-reported physical activity (compared with participants receiving accurate step counts only). Actual step count did not change in either condition. AAMs--induced by trackers or adopted deliberately--can influence affect, behavior, and health independently of actual physical activity. ClinicalTrials.gov NCT03939572; https://www.clinicaltrials.gov/ct2/show/NCT03939572.

Information fusion of stationary, mobile, and wearable consumer-grade sensors to confidently estimate bedroom ventilation rates

This study adds to the body of research investigating ventilation rates measured in residential dwellings. Using open-source Consumer-Grade Sensors (CGS), we measure Carbon Dioxide (CO2) to estimate ventilation rates under one of three conditions: CO2build-up when bedrooms were initially occupied, steady-state CO2 during the latter half of participants’ sleep episodes, and CO2decay after participants wake and vacate their bedroom. We do not ask participants to record their bedroom occupancy, but use information fusion to identify nightly occupied periods by cross-referencing home addresses to GPS measurements provided by their smartphones during sleep episodes identified by Fitbit wearable fitness trackers. We estimate 106 ventilation rates during build-up conditions which ranged from 0.04–1.36 h−1, 242 ventilation rates under steady-state conditions spanning 0.17–2.49 h−1, and 39 ventilation rates from decay conditions over a range of 0.06–1.05 h−1. In addition, we used occupied periods alongside times when GPS confirmed participants were away from home to label Indoor Air Quality (IAQ) data, and to train a Multi-Layer Perceptron (MLP) to classify occupancy based on CO2 and Total Volatile Organic Compound (TVOC) measurements. Using periods classified as occupied with at least 90% confidence, we estimated 116 additional steady-state ventilation rates spanning 0.25–2.49 h−1. Our results are consistent with more traditional and costly sensing approaches, and we conclude that information fusion of CGS is effective in measuring IAQ, detecting occupancy, and estimating ventilation rates.

Sex inequality driven by dispersal

Inequality between the sexes is pervasive both outside and inside the home. One contributing factor could be the dispersal of one sex at marriage that sets up sex-specific differences in relatedness to the group. Here we exploit the ecological diversity and different social structures found in southwest China to investigate the role of sex-biased dispersal on inequality in the sexual division of labor. We use a wearable fitness tracker and validated readings by confirming that participants' daily "steps" were positively correlated with time spent in high-energy activities, such as agriculture and animal husbandry work, and negatively correlated with low-energy activities, such as leisure and relaxation. We applied multilevel comparative approaches to examine the relative workload pattern between the sexes under different dispersal states. Our results reveal two characteristics that lead to an unfavorable division of workload: being female and dispersing at marriage. This is consistent with the hypothesis that males have increased bargaining power when remaining in their natal home, leading to inequality in workload.