Fitbit Charge HR Research Articles

Exploring Health-Related Quality of Life in Children With Hypertrophic Cardiomyopathy and Relationship to Physical Activity.

Hypertrophic cardiomyopathy is a burdensome condition that inflicts both physical and psychological impairment on those with the disease, negatively impacting health-related quality of life (HRQoL). Given the abundance of evidence suggesting a role of physical activity (PA) in modulating HRQoL in healthy populations of children, we sought to determine the relationship between HRQoL and PA in children diagnosed with hypertrophic cardiomyopathy. A multicenter prospective observational cohort study was conducted, with patients with hypertrophic cardiomyopathy aged 10 to 19 years being provided a wrist-worn activity tracker (Fitbit Charge HR) to wear for 14 days. Patients self-reported on Pediatric Quality of Life 4.0 quality of life inventory items, which were associated with PA metrics following covariate adjustment using linear regression. A total of 56 participants were recruited to the study. The median age at enrollment was 15.5 years (interquartile range, 13.8-16.8), and 16 out of 56 (29%) of the cohort were girls. The cohort reported decreased metrics of physical, psychosocial, and total summary scores compared with health reference populations, with scores comparable with that of published populations with chronic disease. Increased physical HRQoL scores were significantly associated with increased daily steps taken, distance traveled, and flights of stairs climbed. These results show that impaired PA correlates with reduced HRQoL in children with hypertrophic cardiomyopathy, suggesting PA may partially mediate HRQoL in this population.

Using explainable machine learning and fitbit data to investigate predictors of adolescent obesity

Sociodemographic and lifestyle factors (sleep, physical activity, and sedentary behavior) may predict obesity risk in early adolescence; a critical period during the life course. Analyzing data from 2971 participants (M = 11.94, SD = 0.64 years) wearing Fitbit Charge HR 2 devices in the Adolescent Brain Cognitive Development (ABCD) Study, glass box machine learning models identified obesity predictors from Fitbit-derived measures of sleep, cardiovascular fitness, and sociodemographic status. Key predictors of obesity include identifying as Non-White race, low household income, later bedtime, short sleep duration, variable sleep timing, low daily step counts, and high heart rates (AUCMean = 0.726). Findings highlight the importance of inadequate sleep, physical inactivity, and socioeconomic disparities, for obesity risk. Results also show the clinical applicability of wearables for continuous monitoring of sleep and cardiovascular fitness in adolescents. Identifying the tipping points in the predictors of obesity risk can inform interventions and treatment strategies to reduce obesity rates in adolescents.

Benefits of physical activity self-monitoring in patients with haemophilia: a prospective study with one-year follow-up.

Activity wristbands have been shown to be effective in relation to self-monitoring activity levels and increasing exercise adherence. However, previous reports have been based on short-term follow-ups in people with haemophilia (PWH). (1) To evaluate compliance with physical activity (PA) recommendations in PWH during a 1-year follow-up period using activity wristbands to record daily steps and intensity; (2) To determine the effect of PA self-monitoring on clinical outcomes. A prospective observational study was conducted in 27 adults with severe haemophilia undergoing prophylactic treatment. The Fitbit Charge HR was used to track daily PA for an entire year. The participants were encouraged to try to reach a goal of 10,000 steps/day and to track their progress. The pre- and post-evaluation included quality of life (A36 Hemophilia-QoL Questionnaire), joint health (Haemophilia Joint Health Score), functionality (Timed Up and Go test), and muscle strength. A total of 323.63 (95%CI: 194-364) valid days (i.e.,>2000 steps) were recorded. The annual average number of steps per day taken by participants was 10,379. Sixteen (59%) PWH reached 10,000 steps/day at baseline and 17 (63%) at 1 year follow-up, with no significant differences (x2=.33; p=.56). A statistically significant improvement was observed in daily moderate activity time (p=.012) and in the 'physical health' quality of life subscale (mean difference: 2.15 points; 95%CI:.64-3.65; p=.007). Our results suggest that patients with severe haemophilia who self-managed their PA can improve their long-term quality of life in the domain of physical health and also the daily time spent in moderate-intensity PA.

Associations between patient reported fatigue and remotely monitored activity in patients with prostate cancer receiving androgen deprivation therapy.

593 Background: Androgen deprivation therapy (ADT) is commonly used for the management of prostate cancer (PCa). Despite its benefits, ADT can lead to a range of side effects that have prominent determents on patient quality of life, specifically fatigue. Fatigue is a multidimensional symptom that influences a patient’s psychological and physical well-being, including the inability to perform daily activities due to lack of energy. This analysis evaluates associations between patient-reported fatigue and remotely monitored objective activity in PCa patients. Methods: This is a secondary analysis ofa multi-site observational cohort study (DigiPRO) among men diagnosed with advanced PCa, initiating ADT within 6 months, conducted between 12/2020 and 4/2023. Eligible patients wore an activity monitor (Fitbit Charge HR 4) continuously for the 12-week study and completed NIH PROMIS fatigue surveys via REDCap, which included Likert-scale questions (8 items, range 1-5 (worse)) about fatigue severity and interference, at baseline, 4, 8, and 12 weeks. PROMIS scores were converted to standardized T-scores (mean 50: SD: 10). Pearson correlation coefficients were calculated, and multivariable logistic regression models were fit to evaluate associations between activity and fatigue T-scores. Results: 40 patients were included in the analysis (median age: 70 yrs, range 51-85; 37% Black or African American/63% White, 10% Hispanic/90% non-Hispanic White). 11 patients reported high levels of fatigue (T-Score>60) at least once over the course of the study and 20% of patients experienced an increase > 5 T-score points from baseline, indicating clinically meaningful deterioration. Higher fatigue T-scores were negatively correlated with higher daily step counts (r=-0.6, p=0.003) and calories expended (r=-0.5, p=0.002) and positively correlated with increased sedentary time (r=0.5, p=0.002) at baseline. Lower baseline step counts were significantly associated with any occurrence of worsening patient fatigue over the study period (OR: 2.08, 95% CI 1.12-3.8, per 1000 step decrease, p=0.02) after adjusting for age and race. Patients who reported worsening fatigue had a mean step count of 3,426 compared to 5,664 steps/day among those who reported stable or improving fatigue (p=0.02). Conclusions: Findings from this analysis suggest that objective measures of daily activityare correlated with patient-reported fatigue and predict worsening fatigue over time. Routine collection and monitoring of patient-reported fatigue and daily activity during ADT may help identify patients at increased risk for worsening fatigue. More research is needed to determine the role of wearable activity monitors as potential interventions and for real time monitoring to help manage fatigue and other symptoms during ADT. Clinical trial information: NCT04575402 .

Feasibility and Utility of a Fitbit Tracker Among Ambulatory Children and Youth With Disabilities.

To examine the feasibility and utility of the Fitbit Charge HR to estimate physical activity among ambulatory children and youth with disabilities. Participants (4-17y old) with disabilities were recruited and asked to wear a Fitbit for 28days. Feasibility was assessed as the number of participants who adhered to the 28-day protocol. Heat maps were generated to visually examine variability in step count by age, gender, and disability group. Between-group differences for wear time and step counts by age, gender, and disability type were assessed by independent sample t tests for gender and disability group, and a 1-way analysis of variance for age group. Participants (N = 157; median age = 10y; 71% boys; 71% nonphysical disabilities) averaged 21 valid days of wear time. Wear time was higher in girls than boys (mean difference = 18.0; 95% confidence interval [CI], 6.8 to 29.1), and in preadolescents (mean difference = 27.6; 95% CI, 15.5 to 39.7) and adolescents (mean difference = -21.2; 95% CI, -33.6 to -8.7) than children. More daily steps were taken by boys than girls (mean difference = -1040; 95% CI, -1465 to -615) and individuals with a nonphysical disability than a physical disability (mean difference = -1120; 95% CI, -1474 to -765). The heat maps showed peaks in physical activity on weekdays before school, at recess, lunchtime, and after school. The Fitbit is a feasible tool for monitoring physical activity among ambulatory children and youth with disabilities and may be useful for population-level surveillance and intervention.

Postponing sleep after a stressful day: Patterns of stress, bedtime procrastination, and sleep outcomes in a daily diary approach.

Sleep problems and stress are common among students and are associated with negative effects on academic performance as well as mental and physical health risks, but studies exploring mediating factors between stress and sleep on a daily basis are scarce. This study aimed to investigate the relationship of daily stress, Bedtime procrastination (BP) (i.e., postponing bedtime without external reasons), and sleep outcomes controlling for trait factors such as self-control. N=96 students at a German university (M=22.2years, SD=4.0) wore a sleep-tracking wearable (Fitbit Charge HR) for two weeks to assess sleep duration and to calculate the gap between the intended time to go to sleep and the objectively measured time of falling asleep. Stress, intended time to go to sleep, and sleep quality were assessed via daily diaries. Established questionnaires were used to measure trait self-control, trait BP, and smartphone addiction. Multilevel analyses indicated that more stress experienced during the day was associated with more BP (b=2.32, p=0.008), shorter sleep duration (b=-3.46, p=0.003), and lower sleep quality (b=1.03, p=0.005) after controlling for several trait factors. The association of daily stress with sleep outcomes (quality and duration) was partly mediated by BP. Our findings indicate that BP might be one factor that contributes to stress-linked decreases in sleep duration and quality. Potential reasons for stress-related later time to fall asleep-like higher physiological arousal or stress-related worries-should be investigated in future studies.

Efficacy of a Commercial Physical Activity Monitor in Longitudinal Tracking of Patients With Pulmonary Hypertension: A Pilot Study.

Patients with pulmonary arterial hypertension have quality-of-life limitations, decreased exercise capacity, and poor prognosis if the condition is left untreated. Standard exercise testing is routinely performed to evaluate patients with pulmonary arterial hypertension but may be limited in its ability to monitor activity levels in daily living. To evaluate the validity of the commercial Fitbit Charge HR as a tool to assess real-time exercise capacity as compared with standard exercise testing. Ambulatory pediatric and adult patients were enrolled and given a Fitbit with instructions to continuously wear the device during waking hours. Patients underwent a 6-minute walk test, cardiopulmonary exercise test, and a 36-Item Short Form Health Survey on the day of enrollment and follow-up. Twenty-seven ambulatory patients with pulmonary arterial hypertension were enrolled, and 21 had sufficient data for analyses (median age, 25 years [range, 13-59 years]; 14 female participants). Daily steps measured by the Fitbit had a positive correlation with 6-minute walk distance (r = 0.72, P = .03) and an inverse trend with World Health Organization functional class. On the 36-Item Short Form Health Survey, 77% of patients reported improvement in vitality (P = .055). At follow-up, there was a strong correlation between number of steps recorded by Fitbit and role limitations because of physical problems (r = 0.88, P = .02) and weaker correlations with other quality-of-life markers. The findings of this pilot study suggest activity monitors may have potential as a simple and novel method of assessing longitudinal exercise capacity and activity levels in patients with pulmonary hypertension. Further study in larger cohorts of patients is warranted to determine which accelerometer measures correlate best with outcomes.

Are Wrist-based Heart Rate Monitors a Valid Tool for Fitness Professionals to Measure Training Intensity During Exercise Classes?

This article aims to inform personal trainers and group fitness coaches about the validity and utility of wrist-located heart rate (HR) monitors compared to chest-located HR monitors for training purposes. HR from four wrist-based optical sensor HR products (Fitbit Charge HR, Garmin Vivosmart HR, Apple Watch series 1, Mio Fuse) were compared against a Polar H7 chest strap & RS800cx receiver during nine activities. Two researchers visually observed HR during a protocol incorporating resting, standing, a grocery bag carry, and a 6-stage cycle ergometer protocol that reached maximal HR. Pearson’s r and interclass correlations (ICC) in the sample (n=45, mean age=20.22 [SD 2.32]) resulted in the following: Mio Fuse r=.93, ICC=.97; Apple Watch 1 r=.91, ICC=.95; Fitbit Charge HR r=.83, ICC=.91; and Garmin Vivosmart HR r=.74, ICC=.85 (all p’s <.001). Bland-Altman plots showed the lowest bias for the Mio (-3.30 bpm), followed by the Apple Watch (-2.82 (SD:14.6) bpm), Garmin (-2.99 (SD:23.9) bpm) with Fitbit having the highest bias (-8.13 (SD:20.6) bpm). No drift in bias was found for any device in successive HR categories (all p’s >.09). Wrist-based HR monitors were deemed acceptable for fitness classes, though caution should be taken when interpreting any singular visually observed measurement point. KEYWORDS: Smartwatch; Heart Rate Monitoring; Fitness; Fitness Watch; Validity; Exercise; Cycle Ergometer; Training; Intensity

SAT291 Remote Monitoring Of Biometric, Proteomic, And Patient-reported Outcomes In Adrenal Insufficiency

Abstract Disclosure: A. Ben-Shlomo: None. B. Chazarin: None. G. Gresham: None. M. Choudhary: None. K. Barnhill: None. K. Haptonstall: None. J. Van Eyk: None. Background: Damaged hypothalamic-pituitary adrenal axis may result in adrenal insufficiency (AI) and require hydrocortisone replacement. Currently, there are no biometric or circulating biomarkers to assess hydrocortisone replacement adequacy. Dosing is based on symptomatology, often resulting in over- or undertreatment. Methods: We used remote monitoring precision health solutions to identify AI molecular and biometric biomarkers over 2 weeks. Using remote sampling devices (Mitra Neoteryx), 10-µL dried blood samples were collected weekly for protein analysis by AI subjects before and 5 hours after daily hydrocortisone doses and age- and sex matched adrenal sufficient (AS) subjects at approximately the same times. Continuous physical activity were measured with a wearable biosensor (Fitbit Charge HR) along with remote systolic (SBP) and diastolic (DBP) blood pressure and heart rate (HR) (Omron Evolv). Self-reported AddiQoL questionnaires were completed twice daily. For biometric endpoints and questionnaires, data are summarized as mean ± SD using two-sided t-tests, where a p value <0.05 is considered statistically significant. For proteomic analysis, median value was calculated, and statistical testing identified differentially expressed proteins (DEPs; FDR<5%). Results: Fifteen AI (6 primary AI [PAI] and 9 secondary AI [SAI] and 15 AS subjects completed the study. AI group mean age was 46.3±15.7 and AS was 41.7±13.2. In both groups, 80% were female. Adherence to home monitoring was 100% in AI subjects and >90% in AS (13/15 assessable for biometrics (activity and BP) and 14/15 for AddiQoL). SBP was lower in PAI (106.2±7.9/68.3±7.6 [n=5]) vs SAI (119.1±15.3/71.1±8.9 [n=8]; p=0.04). Nighttime BP (22:00-05:00) for both PAI (102.3±7.8/68.5±7.9) and SAI (101.2±8.2/63.8±9) were significantly lower than AS (115.5±15.6; p=0.04 and p=0.02, respectively). AI heart rate was lower vs AS at night (61.4±11.6 [n=13] vs 72.5±11.1 [n=11]; p=0.01), especially in PAI (57.7±5 [n=5]; p=0.001). Average daily activity was higher in AS than AI as measured by steps (9010 vs 7787; p=0.02), miles (3.94 vs 3.36; p=0.03) and stair flights (14.19 vs 9.85; p=0.01). On AddiQoL, AI subjects scored lower than AS subjects (126.8±18.1 vs 143.3±14.9, respectively; p<0.0001). Across all dried blood samples, 444 proteins were quantified. Comparing AI vs AS, 78 were identified before morning hydrocortisone dose vs 88 before afternoon dose. Forty-nine DEPs were commonly identified and showed the same regulation trends. Nine DEPs before and 18 DEPs after morning and afternoon dosing, respectively, were identified in AI. None of these DEPs were common, indicating potential blood proteome signature changes in the morning and in the afternoon. Conclusion: Remote monitoring of biometrics and blood proteome in AI is feasible and informative and may identify biomarkers to optimize hydrocortisone replacement therapy. Presentation: Saturday, June 17, 2023

Knee Extension Exercise Effects on Physiological and Psychophysical Performance: Normal Weight Versus Obese Office Workers.

Knee extension exercise is useful and practical for obese and overweight people as this form of exercise is effective in minimizing body weight loading on joints and improving the body's physiological function. This study aimed to compare the physiological and psychophysical parameters of office workers while computer-based working in an active workstation equipped with an active footrest (AFR) prototype with a mechanism for performing knee extension exercises in a sitting position, and also to compare the physiological and psychophysical parameters among normal-weight and obese office workers. In this quasi-experimental study, the physiological parameters of heart rate (HR) and energy expenditure (EE) (measured with the Fitbit Charge HR smartwatch) were measured in two cross-over random sessions for 32 office workers (16 normal-weight and 16 obese) aged 28 to 50 years (M = 42.72, standard deviation [SD] = 4.37) while performing office tasks in sitting and active workstations (equipped with AFR). Perceived physical exertion, comfort, fatigue, and liking were also measured by rating the participants. Short-term activity of the participants with AFR performing computer tasks significantly improved physiological and psychophysical parameters compared with the participants in sitting workstations. However, there was no significant difference in the effect of AFR on physiological and psychophysical parameters between normal-weight and obese participants. Given the significant increase in EE and HR resulting from exercise with AFR compared with the conventional workstation, the use of AFR can help office workers achieve the minimum standard of physical activity at their workplace.

How was remote technology accepted among cardiac rehabilitees in outpatient self-rehabilitation context?

The purpose of the article The purpose of this study was to investigate cardiac rehabilitees’ experiences with wrist-worn activity monitor (Fitbit Charge HR) and internet-based coaching software (Movendos m-coach) in outpatient rehabilitation to promote physical activity and a healthy lifestyle. Materials and methods A 12-month cardiac rehabilitation intervention consisted of three 5-day inpatient periods in a rehabilitation centre, between which participants (n = 32; age mean 62.3 years old (SD 6.3), men n = 24 (75%)) used an activity monitor and internet-based coaching software at home. Experiences with the use of technologies were measured at the end of the 12-month intervention with a questionnaire that was designed using the framework of the Technology Acceptance Model (Likert scale 1–7; 1 = strongly agree and 7 = strongly disagree). Data analysis was based on indicators describing the average experiences and Spearman’s correlation coefficient. Results Both technologies had positive acceptance (internet application mean: 3.2, 95% CI: 2.6–3.7; activity monitor mean 2.1, 95% CI: 1.7–2.5). Sociodemographic factors, physical activity, and familiarity with using technology in daily life were not correlated with technology acceptance of either technology. Conclusions Cardiac rehabilitees had positive acceptance on wrist worn activity monitor and internet-based coaching software, which suggests the use of these tools in outpatient cardiac rehabilitation. Trial Registration ISRCTN Registry, url: https://doi.org/10.1186/ISRCTN61225589, reg. number: ISRCTN61225589

MP29-15 REMOTELY-MONITORED SLEEP MEASURES IN PROSTATE CANCER PATIENTS UNDERGOING ANDROGEN DEPRIVATION THERAPY (ADT)

You have accessJournal of UrologyCME1 Apr 2023MP29-15 REMOTELY-MONITORED SLEEP MEASURES IN PROSTATE CANCER PATIENTS UNDERGOING ANDROGEN DEPRIVATION THERAPY (ADT) Brandon Noorvash, Aubrey Jarman, Carolina Raines, Edwin M. Posadas, Howard M. Sandler, Stephen J. Freedland, and Gillian Gresham Brandon NoorvashBrandon Noorvash More articles by this author , Aubrey JarmanAubrey Jarman More articles by this author , Carolina RainesCarolina Raines More articles by this author , Edwin M. PosadasEdwin M. Posadas More articles by this author , Howard M. SandlerHoward M. Sandler More articles by this author , Stephen J. FreedlandStephen J. Freedland More articles by this author , and Gillian GreshamGillian Gresham More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003257.15AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Sleep disturbance is a common symptom experienced among men with prostate cancer (PC) undergoing ADT that can lead to increased fatigue, diminished quality of life, and poor clinical outcomes. Wearable activity monitors (e.g. Fitbits) allow for objective measures of sleep outside the clinical setting. Despite its importance, there is a current lack of information supporting the use of commercially available wearables for sleep monitoring among PC patients. Thus, we evaluated remotely-monitored longitudinal sleep measures in PC patients receiving ADT. METHODS: PC patients initiating ADT and recruited from Cedars-Sinai and the Durham VA wore a Fitbit Charge HR continuously for 8 weeks to capture daily activity and sleep and monthly electronic patient-reported sleep disturbance (NIH PROMIS survey) and insomnia (PRO-CTCAE). Objective and patient-reported sleep data were summarized, and changes were calculated at 4 and 8 weeks from baseline. RESULTS: A total of 25 patients were included in the analysis (median age 69, range 51-85, 64% Non-Hispanic White, 16% Black, 20% other race/ethnicity). Adherence to wearing the device was 100% at baseline, 88% at 4 weeks, and 76% at week 8. Sleep measures are summarized in /Table 1/. Objective sleep duration decreased over time (-1.5 hours at 8 weeks, p=0.02) and the number of sleep disturbances increased, although not statistically significant. Severity and interference of patient-reported insomnia (PRO-CTCAE) also worsened over time (Table 1). CONCLUSIONS: Our findings suggest that the use of wearables to remotely monitor sleep is feasible in PC patients. Sleep duration and quality were poor and worsened over time, with many awakenings and segmented sleep, which may be associated with treatment effects and other symptoms (e.g., hot flashes, nocturia). More research is needed to inform the development of tailored interventions to improve sleep in this population. Source of Funding: Department of Defense © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e387 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Brandon Noorvash More articles by this author Aubrey Jarman More articles by this author Carolina Raines More articles by this author Edwin M. Posadas More articles by this author Howard M. Sandler More articles by this author Stephen J. Freedland More articles by this author Gillian Gresham More articles by this author Expand All Advertisement PDF downloadLoading ...

Wearable sensor-based performance status assessment in cancer: A pilot multicenter study from the Alliance for Clinical Trials in Oncology (A19_Pilot2).

Clinical performance status is designed to be a measure of overall health, reflecting a patient's physiological reserve and ability to tolerate various forms of therapy. Currently, it is measured by a combination of subjective clinician assessment and patient-reported exercise tolerance in the context of daily living activities. In this study, we assess the feasibility of combining objective data sources and patient-generated health data (PGHD) to improve the accuracy of performance status assessment during routine cancer care. Patients undergoing routine chemotherapy for solid tumors, routine chemotherapy for hematologic malignancies, or hematopoietic stem cell transplant (HCT) at one of four sites in a cancer clinical trials cooperative group were consented to a six-week prospective observational clinical trial (NCT02786628). Baseline data acquisition included cardiopulmonary exercise testing (CPET) and a six-minute walk test (6MWT). Weekly PGHD included patient-reported physical function and symptom burden. Continuous data capture included use of a Fitbit Charge HR (sensor). Baseline CPET and 6MWT could only be obtained in 68% of study patients, suggesting low feasibility during routine cancer treatment. In contrast, 84% of patients had usable fitness tracker data, 93% completed baseline patient-reported surveys, and overall, 73% of patients had overlapping sensor and survey data that could be used for modeling. A linear model with repeated measures was constructed to predict the patient-reported physical function. Sensor-derived daily activity, sensor-derived median heart rate, and patient-reported symptom burden emerged as strong predictors of physical function (marginal R2 0.429-0.433, conditional R2 0.816-0.822). Trial Registration: Clinicaltrials.gov Id NCT02786628.

Self-care Practices of Patients With Heart Failure Using Wearable Electronic Devices: A Systematic Review.

Heart failure (HF) is the fastest growing cardiovascular condition globally; associated management costs and hospitalizations place an immense burden on healthcare systems. Wearable electronic devices (WEDs) may be useful tools to enhance HF management and mitigate negative health outcomes. We aimed to perform a systematic review to examine the potential of WEDs to support HF self-care in ambulatory patients at home. Five databases were searched for studies published between 2007 and May 2022, including OVID MEDLINE, EMBASE (OVID), APA PsycINFO (OVID), Cochrane Central Register of Controlled Trials (OVID), and CINAHL Plus with Full Text (Ebsco). After 6210 duplicates were removed, 4045 records were screened and 6 were included for review (2 conference abstracts and 4 full-text citations). All studies used WEDs as 1 component of a larger intervention. Outcome measures included quality of life, physical activity, self-efficacy, self-care, functional status, time to readmission, social isolation, and mood. Studies were of moderate to high quality and mixed findings were reported. Enhanced exercise habits and motivational behavior to exercise, as well as decreased adverse symptoms of fatigue and dyspnea, were identified in 2 studies. However, improvements in exercise capacity and increased motivational behavior did not lead to exercise adherence in another 2 studies. The findings from this review suggest that WEDs may be a viable health behavior improvement strategy for patients with HF. However, studies of higher quality, with the primary intervention being a WED, and consistent outcome measures are needed to replicate the positive findings of studies identified in this review.

FEELING YOUNG TODAY, FEELING GOOD TOMORROW? MICROLONGITUDINAL DYNAMICS IN SUBJECTIVE AGE

Abstract Insights into the short-term dynamics and micro-longitudinal consequences of subjective age can drive our understanding of its long-term mechanisms across adulthood. Using data from 80 newly retired individuals (aged 59 to 76 years; 59% women) collected on 21 days, we made use of a recent methodological advance—multilevel dynamic structural equation modeling. As possible same-day correlates and micro-longitudinal consequences of subjective age, we investigated physical activity, step number, sleep quality, affect, and stress, which were either assessed via wearables (FitBit Charge HR) or daily diaries. Analyses suggest a weak autoregression of subjective age, indicating that how old one feels is determined via daily rather than lasting experiences. Indeed, there were significant same-day relations to all suggested correlates. The one effect lasting across several days was from an older subjective age on subsequent negative affect—a potential short-term mechanism contributing to the detrimental long-term influence of an older subjective age.

Recommendations for Identifying Valid Wear for Consumer-Level Wrist-Worn Activity Trackers and Acceptability of Extended Device Deployment in Children

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. 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. 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. 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.

Evaluation of physical health status beyond daily step count using a wearable activity sensor

Physical health status defines an individual’s ability to perform normal activities of daily living and is usually assessed in clinical settings by questionnaires and/or by validated tests, e.g. timed walk tests. These measurements have relatively low information content and are usually limited in frequency. Wearable sensors, such as activity monitors, enable remote measurement of parameters associated with physical activity but have not been widely explored beyond measurement of daily step count. Here we report on results from a cohort of 22 individuals with Pulmonary Arterial Hypertension (PAH) who were provided with a Fitbit activity monitor (Fitbit Charge HR®) between two clinic visits (18.4 ± 12.2 weeks). At each clinical visit, a maximum of 26 measurements were recorded (19 categorical and 7 continuous). From analysis of the minute-to-minute step rate and heart rate we derive several metrics associated with physical activity and cardiovascular function. These metrics are used to identify subgroups within the cohort and to compare to clinical parameters. Several Fitbit metrics are strongly correlated to continuous clinical parameters. Using a thresholding approach, we show that many Fitbit metrics result in statistically significant differences in clinical parameters between subgroups, including those associated with physical status, cardiovascular function, pulmonary function, as well as biomarkers from blood tests. These results highlight the fact that daily step count is only one of many metrics that can be derived from activity monitors.

Using wearables to promote physical activity in old age : Feasibility, benefits, and user friendliness.

BackgroundWearables provide new opportunities to promote physical activity also among older adults but data on effectiveness and user friendliness are rare.ObjectiveThe effects of a comprehensive self-regulative intervention on moderate to vigorous physical activity (MVPA) and number of steps were examined using commercially available activity trackers. Acceptance regarding the devices was analysed in various domains.MethodsIn this study 80 older adults (mean = 67.03 years, standard deviation = 3.97 years; 59% women) wore a Fitbit Charge HR for 21 days including a baseline, a postintervention and a follow-up week. The intervention comprised feedback, goal setting and planning and 50% of the participants were additionally randomized to a role model component. Social cognitive predictors based on the health action process approach (HAPA) and user experience were assessed via questionnaires.ResultsThe MVPA increased by an average of 19 min per week and steps by 1317 per day. An additional benefit of the role model component could be observed for MVPA. In the follow-up, the intervention effect was still significant for the number of steps, while MVPA dropped back to baseline. Multilevel models including HAPA variables explained small but significant amounts of variance in MVPA (8% within-person, 26% between-person) and steps (11% within-person, 12% between-person). User experience was rated as very high.ConclusionProviding an intervention based on established behavior change techniques and self-monitoring via wearables seems to be effective for increasing physical activity among older adults. The HAPA variables seem to play a limited role to explain activity levels. Acceptance of wearables can be expected to be high.Supplementary InformationThe online version of this article (10.1007/s00391-022-02083-x) contains supplementary material, which is available to authorized users.

A randomized trial to promote physical activity in adult pre-hypertensive and hypertensive patients

ABSTRACT The purpose of the pilot study was to determine the effectiveness of wearable activity trackers alone or in combination with behaviour change strategies for promoting physical activity (PA) among individuals with pre-hypertension or hypertension. A sample of 44 adults (68% female and mean age 55) were randomized to receive either a Fitbit Charge HR 3 alone (FB) or the Fitbit in combination with behaviour change strategies (i.e., goal setting, behaviour goal review, adaptive feedback) delivered by a trained health coach (FB+) for 12 weeks. Moderate and vigorous PA (MVPA), steps, and sedentary time (ST) were assessed using ActiGraph wGT3X-BT. The FB+ group significantly increased PA [+1854 (2518) steps/day, p < .01] and MVPA [+26 (34) mins/day, p < .05], and decreased their ST [−63 (73) mins/day, p < .01]. The FB group significantly increased MVPA [+11 (16) mins/day, p < .05], and decreased their ST [−87 (117) mins/day, p < .01]. Participants in FB+ had a significantly greater increase in MVPA/day compared to FB only with a between-group effect size of 0.6 (p < .05). Using Fitbit for self-monitoring is effective in increasing PA and reducing ST among pre-hypertensive and hypertensive participants. Additional behaviour change support amplified the intervention effectiveness for promoting MVPA.

Comparing three wearable accelerometers to measure early activity after cardiac surgery

ObjectiveWearable activity monitors can provide detailed data on activity after cardiac surgery and discriminate a patient's risk for hospital-based outcomes. However, comparative data for different monitoring approaches, as well as predictive ability over clinical characteristics, are lacking. In addition, data on specific thresholds of activity are needed. The objective of this study was to compare 3 wearable activity monitors and 1 observational mobility scale in discriminating risk for 3 hospital-based outcomes, and to establish clinically relevant step thresholds. MethodsCardiac surgery patients were enrolled between June 2016 and August 2017 in a cohort study. Postoperative activity was measured by 3 accelerometry monitors (StepWatch Ambulation Monitor, Fitbit Charge HR, and ActiGraph GT9X) and 1 nurse-based observation scale. Monitors represent a spectrum of characteristics, including wear location (ankle/wrist), output (activity counts/steps), consumer accessibility, and cost. Primary outcomes were duration of hospitalization >7 days, discharge to a nonhome location, and 30-day readmission. ResultsData were available from 193 patients (median age 67 years [interquartile range, 58-72]). All postoperative day 2 activity metrics (ie, from StepWatch, Fitbit, ActiGraph, and the observation scale) were independently associated with prolonged hospitalization and discharge to a nonhome location. Only steps as measured by StepWatch was independently associated with 30-day readmission. Overall, StepWatch provided the greatest discrimination (C-statistics 0.71-0.76 for all outcomes). Step thresholds between 250 and 500 steps/day identified between 74% and 96% of patients with any primary outcome. ConclusionsData from wearable accelerometers provide additive value in early postoperative risk-stratification for hospital-based outcomes. These results both support and provide guidance for activity-monitoring programs after cardiac surgery.