Establishing a Consensus-Based Framework for the Use of Wearable Activity Trackers in Health Care: Delphi Study.

BACKGROUND: Physical activity (PA) plays a crucial role in health care, providing benefits in the prevention and management of many noncommunicable diseases. Wearable activity trackers (WATs) provide an opportunity to monitor and promote PA in various health care settings. OBJECTIVE: This study aimed to develop a consensus-based framework for the optimal use of WATs in health care. METHODS: A 4-round Delphi survey was conducted, involving a panel (n=58) of health care professionals, health service managers, and researchers. Round 1 used open-response questions to identify overarching themes. Rounds 2 and 3 used 9-point Likert scales to refine participants' opinions and establish consensus on key factors related to WAT use in health care, including metrics, device characteristics, clinical populations and settings, and software considerations. Round 3 also explored barriers and mitigating strategies to WAT use in clinical settings. Insights from Rounds 1-3 informed a draft checklist designed to guide a systematic approach to WAT adoption in health care. In Round 4, participants evaluated the draft checklist's clarity, utility, and appropriateness. RESULTS: Participation rates for rounds 1 to 4 were 76% (n=44), 74% (n=43), 74% (n=43), and 66% (n=38), respectively. The study found a strong interest in using WATs across diverse clinical populations and settings. Key metrics (step count, minutes of PA, and sedentary time), device characteristics (eg, easy to charge, comfortable, waterproof, simple data access, and easy to navigate and interpret data), and software characteristics (eg, remote and wireless data access, access to multiple patients' data) were identified. Various barriers to WAT adoption were highlighted, including device-related, patient-related, clinician-related, and system-level issues. The findings culminated in a 12-item draft checklist for using WATs in health care, with all 12 items endorsed for their utility, clarity, and appropriateness in Round 4. CONCLUSIONS: This study underscores the potential of WATs in enhancing patient care across a broad spectrum of health care settings. While the benefits of WATs are evident, successful integration requires addressing several challenges, from technological developments to patient education and clinician training. Collaboration between WAT manufacturers, researchers, and health care professionals will be pivotal for implementing WATs in the health care sector.

Deconstructing Fitbit to Specify the Effective Features in Promoting Physical Activity Among Inactive Adults: Pilot Randomized Controlled Trial.

BACKGROUND: Wearable activity trackers have become key players in mobile health practice as they offer various behavior change techniques (BCTs) to help improve physical activity (PA). Typically, multiple BCTs are implemented simultaneously in a device, making it difficult to identify which BCTs specifically improve PA. OBJECTIVE: We investigated the effects of BCTs implemented on a smartwatch, the Fitbit, to determine how each technique promoted PA. METHODS: This study was a single-blind, pilot randomized controlled trial, in which 70 adults (n=44, 63% women; mean age 40.5, SD 12.56 years; closed user group) were allocated to 1 of 3 BCT conditions: self-monitoring (feedback on participants' own steps), goal setting (providing daily step goals), and social comparison (displaying daily steps achieved by peers). Each intervention lasted for 4 weeks (fully automated), during which participants wore a Fitbit and responded to day-to-day questionnaires regarding motivation. At pre- and postintervention time points (in-person sessions), levels and readiness for PA as well as different aspects of motivation were assessed. RESULTS: Participants showed excellent adherence (mean valid-wear time of Fitbit=26.43/28 days, 94%), and no dropout was recorded. No significant changes were found in self-reported total PA (dz<0.28, P=.40 for the self-monitoring group, P=.58 for the goal setting group, and P=.19 for the social comparison group). Fitbit-assessed step count during the intervention period was slightly higher in the goal setting and social comparison groups than in the self-monitoring group, although the effects did not reach statistical significance (P=.052 and P=.06). However, more than half (27/46, 59%) of the participants in the precontemplation stage reported progress to a higher stage across the 3 conditions. Additionally, significant increases were detected for several aspects of motivation (ie, integrated and external regulation), and significant group differences were identified for the day-to-day changes in external regulation; that is, the self-monitoring group showed a significantly larger increase in the sense of pressure and tension (as part of external regulation) than the goal setting group (P=.04). CONCLUSIONS: Fitbit-implemented BCTs promote readiness and motivation for PA, although their effects on PA levels are marginal. The BCT-specific effects were unclear, but preliminary evidence showed that self-monitoring alone may be perceived demanding. Combining self-monitoring with another BCT (or goal setting, at least) may be important for enhancing continuous engagement in PA. TRIAL REGISTRATION: Open Science Framework; https://osf.io/87qnb/?view_only=f7b72d48bb5044eca4b8ce729f6b403b.

Machine Learning-Based Prediction of Changes in the Clinical Condition of Patients With Complex Chronic Diseases: 2-Phase Pilot Prospective Single-Center Observational Study.

BACKGROUND: Functional impairment is one of the most decisive prognostic factors in patients with complex chronic diseases. A more significant functional impairment indicates that the disease is progressing, which requires implementing diagnostic and therapeutic actions that stop the exacerbation of the disease. OBJECTIVE: This study aimed to predict alterations in the clinical condition of patients with complex chronic diseases by predicting the Barthel Index (BI), to assess their clinical and functional status using an artificial intelligence model and data collected through an internet of things mobility device. METHODS: A 2-phase pilot prospective single-center observational study was designed. During both phases, patients were recruited, and a wearable activity tracker was allocated to gather physical activity data. Patients were categorized into class A (BI≤20; total dependence), class B (2060; moderate or mild dependence, or independent). Data preprocessing and machine learning techniques were used to analyze mobility data. A decision tree was used to achieve a robust and interpretable model. To assess the quality of the predictions, several metrics including the mean absolute error, median absolute error, and root mean squared error were considered. Statistical analysis was performed using SPSS and Python for the machine learning modeling. RESULTS: Overall, 90 patients with complex chronic diseases were included: 50 during phase 1 (class A: n=10; class B: n=20; and class C: n=20) and 40 during phase 2 (class B: n=20 and class C: n=20). Most patients (n=85, 94%) had a caregiver. The mean value of the BI was 58.31 (SD 24.5). Concerning mobility aids, 60% (n=52) of patients required no aids, whereas the others required walkers (n=18, 20%), wheelchairs (n=15, 17%), canes (n=4, 7%), and crutches (n=1, 1%). Regarding clinical complexity, 85% (n=76) met patient with polypathology criteria with a mean of 2.7 (SD 1.25) categories, 69% (n=61) met the frailty criteria, and 21% (n=19) met the patients with complex chronic diseases criteria. The most characteristic symptoms were dyspnea (n=73, 82%), chronic pain (n=63, 70%), asthenia (n=62, 68%), and anxiety (n=41, 46%). Polypharmacy was presented in 87% (n=78) of patients. The most important variables for predicting the BI were identified as the maximum step count during evening and morning periods and the absence of a mobility device. The model exhibited consistency in the median prediction error with a median absolute error close to 5 in the training, validation, and production-like test sets. The model accuracy for identifying the BI class was 91%, 88%, and 90% in the training, validation, and test sets, respectively. CONCLUSIONS: Using commercially available mobility recording devices makes it possible to identify different mobility patterns and relate them to functional capacity in patients with polypathology according to the BI without using clinical parameters.

The Wearable Activity Tracker Checklist for Healthcare (WATCH): a 12-point guide for the implementation of wearable activity trackers in healthcare.

Increasing physical activity in patients offers dual benefits, fostering improved patient health and recovery, while also bolstering healthcare system efficiency by minimizing costs related to extended hospital stays, complications, and readmissions. Wearable activity trackers offer valuable opportunities to enhance physical activity across various healthcare settings and among different patient groups. However, their integration into healthcare faces multiple implementation challenges related to the devices themselves, patients, clinicians, and systemic factors. This article presents the Wearable Activity Tracker Checklist for Healthcare (WATCH), which was recently developed through an international Delphi study. The WATCH provides a comprehensive framework for implementation and evaluation of wearable activity trackers in healthcare. It covers the purpose and setting for usage; patient, provider, and support personnel roles; selection of relevant metrics; device specifications; procedural steps for issuance and maintenance; data management; timelines; necessary adaptations for specific scenarios; and essential resources (such as education and training) for effective implementation. The WATCH is designed to support the implementation of wearable activity trackers across a wide range of healthcare populations and settings, and in those with varied levels of experience. The overarching goal is to support broader, sustained, and systematic use of wearable activity trackers in healthcare, therefore fostering enhanced physical activity promotion and improved patient outcomes.

Attitudes, Barriers, and Motivators Toward Daily Walking and a Mobile App to Increase Walking Among Women: Web-Based Anonymous Survey.

BACKGROUND: There are disparities in the prevalence of physical activity (PA) with women engaging in less PA than men, a gap which widens during midlife. Walking is a generally accepted form of PA among women and should be encouraged. Motivations, barriers, and attitudes to engaging in walking change with age, but the influencing factors are not well understood nor are the features of mobile apps that facilitate daily walking. OBJECTIVE: This study explores the relationship between age and women's self-reported motivations, barriers, attitudes, and beliefs toward daily walking. It further assesses attitudes toward features of a mobile app designed to sync with a wearable step tracker to increase and maintain levels of daily walking among women. METHODS: A web-based anonymous survey was completed by 400 women, aged 21-75 years. The 31-item survey captured women's perceived barriers and motivators toward daily walking and attitudes toward mobile apps to support and maintain daily walking. For analysis, responses to the survey were grouped into 2 categories of women: ages 21-49 years and ages 50-75 years. Bivariate analyses were conducted through SPSS (IBM Corp) for each of the survey questions using chi-square for dichotomous variables and 1-tailed t tests for scales and continuous variables to identify significant differences between the groups. One-tailed t tests were run for scaled variables to identify significant differences between the 10-year age increments. RESULTS: Significant barriers to daily walking were observed in the 21-49-year group for personal and work responsibilities, motivational and psychosocial factors, and physical and environmental factors. Motivators to walk daily in the 21- 49-year group were significantly higher to reduce stress and anxiety, and motivators to walk daily in the 50-75-year group were significantly higher to help manage or lose weight and to reduce the risk of chronic illness. Women's walking preferences, beliefs around their walking behaviors, and their perceived importance of the features of a future mobile app for walking designed specifically for women showed significant variation according to age. When asked about the importance of features for a mobile app, women aged 21-49 years indicated a significantly higher number of positive responses for the following features: digital community support, rewards or point system, and seeing a daily or weekly or monthly progress chart. CONCLUSIONS: Our findings indicate that barriers, motivators, and beliefs around daily walking and the importance of preferred features of a mobile app vary according to women's ages. Messaging and app features should be tailored to different age groups of women. These study results can be viewed as a foundation for future research and development of mobile health interventions to effectively increase daily walking among women of all ages.

Feasibility and Preliminary Effectiveness of the INSPIRE Pilot Study for Adolescent Girls.

INTRODUCTION: This pilot study evaluated the feasibility and preliminary effectiveness of the Intervention to Support Physical Activity Independence and Routine Everyday program. METHOD: This quasi-experimental single-group pretest/posttest study included adolescent girls (n = 15) who received a Fitbit Inspire 2 wearable activity tracker and participated in the seven-week Intervention to Support Physical Activity Independence and Routine Everyday program on a college campus in the Midwest. Feasibility outcomes included intervention participation, fidelity, and satisfaction. Preliminary effectiveness outcomes included moderate-to-vigorous physical activity, cardiorespiratory fitness, and resting heart rate. RESULTS: For intervention sessions, the mean attendance rate was 83.42%, the mean minutes of moderate-to-vigorous physical activity was 62.03, and the mean satisfaction score was 28.90. Moderate-to-vigorous physical activity and resting heart rate improved significantly from baseline to postintervention, but cardiorespiratory fitness did not. DISCUSSION: Results suggest the need for a pilot randomized controlled trial to improve cardiorespiratory fitness and incorporating an objective measure of moderate-to-vigorous physical activity.

Effect of a Wearable Device-Based Physical Activity Intervention in North Korean Refugees: Pilot Randomized Controlled Trial.

BACKGROUND: Effective health interventions for North Korean refugees vulnerable to metabolic disorders are currently unelucidated. OBJECTIVE: This study aimed to evaluate the effects of digital health interventions in North Korean refugees using a wearable activity tracker (Fitbit device). METHODS: We conducted a prospective, randomized, open-label study on North Korean refugees aged 19-59 years between June 2020 and October 2021 with a 12-week follow-up period. The participants were randomly assigned to either an intervention group or a control group in a 1:1 ratio. The intervention group received individualized health counseling based on Fitbit data every 4 weeks, whereas the control group wore the Fitbit device but did not receive individualized counseling. The primary and secondary outcomes were the change in the mean daily step count and changes in the metabolic parameters, respectively. RESULTS: The trial was completed by 52 North Korean refugees, of whom 27 and 25 were in the intervention and control groups, respectively. The mean age was 43 (SD 10) years, and 41 (78.8%) participants were women. Most participants (44/52, 95.7%) had a low socioeconomic status. After the intervention, the daily step count in the intervention group increased, whereas that in the control group decreased. However, there were no significant differences between the 2 groups (+83 and -521 steps in the intervention and control groups, respectively; P=.500). The effects of the intervention were more prominent in the participants with a lower-than-average daily step count at baseline (<11,667 steps/day). After the 12-week study period, 85.7% (12/14) and 46.7% (7/15) of the participants in the intervention and control groups, respectively, had an increased daily step count (P=.05). The intervention prevented the worsening of the metabolic parameters, including BMI, waist circumference, fasting blood glucose level, and glycated hemoglobin level, during the study period. CONCLUSIONS: The wearable device-based physical activity intervention did not significantly increase the average daily step count in the North Korean refugees in this study. However, the intervention was effective among the North Korean refugees with a lower-than-average daily step count; therefore, a large-scale, long-term study of this intervention type in an underserved population is warranted. TRIAL REGISTRATION: Clinical Research Information Service KCT0007999; https://cris.nih.go.kr/cris/search/detailSearch.do/23622.

Validity of the Xiaomi Mi Band 2, 3, 4 and 5 Wristbands for Assessing Physical Activity in 12-to-18-Year-Old Adolescents under Unstructured Free-Living Conditions. Fit-Person Study.

The purpose was to assess the validity of four generations of Xiaomi Mi Band wristbands for the assessment of step count and physical activity (PA) levels among adolescents aged 12-18 years under free-living conditions. One hundred adolescents were invited to participate in the present study. The final sample consisted of 62 high-school students (34 females), aged 12-18 years old (Mage = 14.1 ± 1.6 years), who wore an ActiGraph accelerometer on their hip (PA and step count reference measures) and four activity wristbands (Xiaomi Mi Band 2, 3, 4, and 5) on their non-dominant wrist during the waking time of one day. Results showed that the agreement between daily PA levels (i.e., slow, brisk, and slow-brisk pace walking, total PA and moderate-to-vigorous PA) measured by Xiaomi Mi Band wristbands and the accelerometer were poor (ICC, 95% CI = 0.06-0.78, 0.00-0.92; MAPE = 50.1-150.6%). However, agreement between daily step count measured by the accelerometer and the Xiaomi Mi Band wristbands were between acceptable (MAPE = 12.2-13.6%) to excellent (ICC, 95% CI = 0.94-0.95, 0.90-0.97). Furthermore, the Xiaomi Mi Band wristbands have a good to excellent validity for correctly classifying adolescents as meeting or not meeting the recommended 10,000 steps per day (P = 0.89-0.95, k = 0.71-0.87) and the recommended 60 minutes of moderate-to-vigorous PA per day (P = 0.89-0.94, k = 0.69-0.83). Furthermore, comparability between the four Xiaomi Mi Band generations were poor to excellent (ICC, 95% CI = 0.22-0.99, 0.00-1.00) for the daily PA levels outputs, although it was excellent (ICC, 95% CI = 0.99-1.00, 0.96-1.00; MAPE = 0.0-0.1%) for daily step count. Different models of Xiaomi Mi Band wristbands were comparable and presented good validity for measuring adolescents' step count, and they accurately classified adolescents as meeting or not meeting the PA recommendations under free-living conditions.

Reporting quality of interventions using a wearable activity tracker to improve physical activity in patients with inflammatory arthritis or osteoarthritis: a systematic review.

To assess the reporting quality of interventions aiming at promoting physical activity (PA) using a wearable activity tracker (WAT) in patients with inflammatory arthritis (IA) or hip/knee osteoarthritis (OA). A systematic search was performed in eight databases (including PubMed, Embase and Cochrane Library) for studies published between 2000 and 2022. Two reviewers independently selected studies and extracted data on study characteristics and the reporting of the PA intervention using a WAT using the Consensus on Exercise Reporting Template (CERT) (12 items) and Consolidated Standards of Reporting Trials (CONSORT) E-Health checklist (16 items). The reporting quality of each study was expressed as a percentage of reported items of the total CERT and CONSORT E-Health (50% or less = poor; 51-79% = moderate; and 80-100% = good reporting quality). Sixteen studies were included; three involved patients with IA and 13 with OA. Reporting quality was poor in 6/16 studies and moderate in 10/16 studies, according to the CERT and poor in 8/16 and moderate in 8/16 studies following the CONSORT E-Health checklist. Poorly reported checklist items included: the description of decision rule(s) for determining progression and the starting level, the number of adverse events and how adherence or fidelity was assessed. In clinical trials on PA interventions using a WAT in patients with IA or OA, the reporting quality of delivery process is moderate to poor. The poor reporting quality of the progression and tailoring of the PA programs makes replication difficult. Improvements in reporting quality are necessary.

Using Consumer-Wearable Activity Trackers for Risk Prediction of Life-Threatening Heart Arrhythmia in Patients with an Implantable Cardioverter-Defibrillator: An Exploratory Observational Study.

Ventricular arrhythmia (VA) is a leading cause of sudden death and health deterioration. Recent advances in predictive analytics and wearable technology for behavior assessment show promise but require further investigation. Yet, previous studies have only assessed other health outcomes and monitored patients for short durations (7−14 days). This study explores how behaviors reported by a consumer wearable can assist VA risk prediction. An exploratory observational study was conducted with participants who had an implantable cardioverter-defibrillator (ICD) and wore a Fitbit Alta HR consumer wearable. Fitbit reported behavioral markers for physical activity (light, fair, vigorous), sleep, and heart rate. A case-crossover analysis using conditional logistic regression assessed the effects of time-adjusted behaviors over 1−8 weeks on VA incidence. Twenty-seven patients (25 males, median age 59 years) were included. Among the participants, ICDs recorded 262 VA events during 8093 days monitored by Fitbit (median follow-up period 960 days). Longer light to fair activity durations and a higher heart rate increased the odds of a VA event (p < 0.001). In contrast, lengthier fair to vigorous activity and sleep durations decreased the odds of a VA event (p < 0.001). Future studies using consumer wearables in a larger population should prioritize these outcomes to further assess VA risk.

The impact of ActiGraph's low-frequency extension filter on measurement of children's physical activity.

This study examines differences in accelerometer-based measurements of children's movement with and without applying ActiGraph's low-frequency extension (LFE) filter. Thirty children wore ActiGraph GT9X devices during structured physical activity (PA) periods. Raw accelerometry data for each activity period were processed with and without the LFE filter applied. For each activity period, paired t-tests were used to compare vector magnitude counts and minutes spent in moderate-to-vigorous physical activity (MVPA) with and without the LFE filter applied. Repeated measures MANOVA models were used for compositional data analysis of the percentage of time spent in sedentary behaviour and light, moderate, and vigorous PA with and without the LFE filter applied. Applying the LFE filter significantly increased vector magnitude counts and estimated minutes spent in MVPA for all activity periods when compared to the normal filter. For brisk walking, the LFE filter had a significant impact on the composition of time spent in sedentary behaviour and PA intensities. Children's activity data processed with the LFE filter may not be compatible with cut-points for activity levels developed with the normal filter, and caution should be taken when comparing children's activity levels or movement data between studies that do and do not use the LFE filter.

Effect of Walking Steps Measured by a Wearable Activity Tracker on Improving Components of Metabolic Syndrome: A Prospective Study.

We compared the improvement in components of metabolic syndrome (MS) before and after lifestyle modification, as determined by daily step counts (on a wrist-worn Fitbit®) in participants with and without MS recruited from volunteers attending medical health checkup programs. A linear mixed model was used to analyze the change in MS components between participants with and without MS by group × time interaction. Multiple logistic regression analysis after adjustment for confounders was used to obtain odds ratios (ORs) and 95% confidence intervals (CIs) for improvements in MS components per 1000-steps/day increments. Waist circumference, triglycerides, fasting plasma glucose, and diastolic blood pressure were significantly different between participants with and without MS (group × time: p = 0.010, p < 0.001, p = 0.025, and p = 0.010, respectively). Multivariable-adjusted ORs (95% CI) of improvement in MS components per 1000-steps/day increments were 1.24 (1.01−1.53) in participants with and 1.14 (0.93−1.40) in participants without MS. Walking improved MS components more in individuals with than without MS. From a public health perspective, walking should be encouraged for high-risk MS individuals.

Health Habits and Wearable Activity Tracker Devices: Analytical Cross-Sectional Study.

Wearable activity trackers are electronic devices that facilitate self-monitoring of information related to health. The purpose of this study was to examine the use of tracker devices to record daily activity (calories) and its associations with gender, generation, BMI, and physical activity behavior of United States of America resident adults; a cross-sectional study in 892 subjects recruited to participate in an anonymous online survey was performed. Being female increased the odds of using a tracker device by 2.3 times. Having low cardiovascular disease mortality risk related to time spent sitting increased the odds for using a tracker device by 2.7 times, and having medium risk 1.9 times, with respect to having high risk. For every 1-point increase in BMI, the odds for using a tracker device increased by 5.2%. Conclusions: Subjects who had ever used any tracker device had a higher BMI. The use of tracker devices was related to lower cardiovascular disease mortality risk related to sitting time. The amount of physical activity and the time spent walking were not associated with the usage of tracker devices. It is possible that the user of tracker devices should be supported by professionals to implement deep change in health habits.

Promoting work ability with a wearable activity tracker in working age individuals with hip and/or knee osteoarthritis: a randomized controlled trial.

BACKGROUND: Physical activity (PA) may improve work ability and health in individuals with hip and/or knee osteoarthritis (OA). The use of wearable activity trackers (WATs) has been shown to increase PA and improve other health outcomes but little is known concerning their effect on work ability. The objectives of this study were to examine the effect of self-monitoring PA with a WAT on work ability, PA and work productivity among individuals of working age with hip and/or knee OA. METHODS: Individuals (n = 160) were included and cluster-randomized to a Supported Osteoarthritis Self-management Program (SOASP) with the addition of self-monitoring PA using a commercial WAT for 12 weeks (n = 86), or only the SOASP (n = 74). Primary outcome was self-reported work ability measured with the Work Ability Index (WAI) and secondary outcomes were self-reported PA measured with the International Physical Activity Questionnaire - Short Form (IPAQ-SF) and work productivity, measured with the Work Productivity and Activity Impairment scale: Osteoarthritis (WPAI:OA) at baseline and after 3, 6 and 12 months. Data was primarily analysed with linear mixed models. RESULTS: Participants with data from baseline and at least one follow-up were included in the analyses (n = 124). Linear mixed models showed no statistically significant difference between groups regarding pattern of change in work ability or PA, from baseline to follow-ups. Also, neither group had a statistically significant difference in work ability between baseline and each follow-up. CONCLUSION: The SOASP together with self-monitoring PA with a WAT did not have any effect on the primary outcome variable work ability. Participants already at baseline had good work ability and were physically active, which could have reduced the possibility for improvements. Future interventions should target a population with lower work ability and PA-level. TRIAL REGISTRATION: ClinicalTrials.gov, NCT03354091 . Registered 15/11/2017.

Survivors' health competence mediates the association between wearable activity tracker use and self-rated health: HINTS analysis.

PURPOSE: Physical activity (PA) plays an important role in achieving positive self-rated health (SRH) among cancer survivors. Wearable activity trackers (WATs) can be effective for self-monitoring and tracking PA. Studies have shown that survivors who use WATs are more likely to engage in more PA. However, few studies have examined the direct and indirect associations between WAT use, PA, and SRH mediated by constructs derived from self-determination theory, perceived health competence, and perceived social relatedness for health. METHODS: Data on survivors were analyzed from National Cancer Institute's Health Information National Trend Survey (HINTS) Cycle 1-3 (n = 1,421). Path analysis was used to test the total, direct, and indirect associations. RESULTS: Previous WAT use was directly associated with PA level (standardized beta (SB): 0.07, p = 0.005) and indirectly associated with SRH (SB: 0.04, p = 0.005), mediated by perceived health competence and PA. Perceived health competence was directly associated with SRH (SB: 0.51, p < .0001) and PA (SB: 0.20, p < .0001), and perceived social relatedness for health was not significantly associated with PA (SB: 0.005, p = 0.8) or SRH (SB: 0.02, p = 0.31). CONCLUSIONS: Overall, these results indicate that perceived health competence significantly mediated the associations between WAT use and SRH; however, WAT use was only directly associated with PA and was not mediated. IMPLICATIONS FOR CANCER SURVIVORS: These findings support the notion that WATs may play a role in addressing SRH among cancer survivors through fostering perceived health competence by providing real-time feedback, goal setting, and opportunities for self-monitoring.

Effects of Consumer-Wearable Activity Tracker-Based Programs on Objectively Measured Daily Physical Activity and Sedentary Behavior Among School-Aged Children: A Systematic Review and Meta-analysis.

BACKGROUND: The popularity of consumer-wearable activity trackers has led the scientific community to conduct an increasing number of intervention studies integrating them to promote physical activity (PA) and to reduce sedentary behavior (SB) levels among school-aged children. Therefore, the aim of the present study was to estimate the effects of consumer-wearable activity tracker-based programs on daily objectively measured PA and SB among apparently healthy school-aged children, as well as to compare the influence of participants' and programs' characteristics. METHODS: Eligibility criteria were: (1) participants: apparently healthy school-aged children (< 18 years old); (2) intervention: aimed to promote PA and/or to reduce SB incorporating consumer-wearable activity trackers; (3) comparator: baseline measurements and/or a control/traditional group; (4) outcomes: objectively measured daily PA and/or SB levels; (5) study design: pre-experimental, quasi-experimental, and true-experimental trials. Relevant studies were searched from eight databases up to December 2020, as well as from four alternative modes of searching. Based on the Cochrane Risk-of-bias tool 2, the risk of bias was assessed following four domains: (1) randomization process; (2) missing outcome data; (3) measurement of the outcomes; and (4) selection of the reported results. Based on a comprehensive systematic review, meta-analyses of the Cohen's standardized mean difference (d) and 95% confidence interval (CI) with a random-effects model were conducted to estimate the overall effects, as well as the within- and between-study subgroups analyses effects, of the programs on daily total steps, moderate-to-vigorous PA (MVPA), total PA and SB. RESULTS: Forty-four publications (i.e., 45 studies) were included in the systematic review (5,620 unique participants; mean age = 12.85 ± 2.84 years) and 40 publications (i.e., 41 studies) in the meta-analysis. Programs had a mean length of 11.78 ± 13.17 weeks and most used a waist-worn consumer-wearable activity tracker (77.78% waist-worn; 22.22% wrist-worn). Programs characteristics were: goal-setting strategies (64.06%); participants' logbooks (56.25%); counseling sessions (62.50%); reminders (28.13%); motivational strategies (42.19%); and exercise routine (17.19%). Results showed a statistically significant moderate favorable effect on daily total steps (d = 0.612, 95% CI 0.477-0.746), small favorable effect on daily MVPA (d = 0.220, 95% CI 0.134-0.307), trivial favorable effect on daily total PA (d = 0.151, 95% CI 0.038-0.264) and trivial unfavorable effect on daily SB (d = 0.172, 95% CI 0.039-0.305). Subgroups analyses showed a higher effect for daily total steps and daily MVPA levels in females and the physically inactive for daily total steps (p = 0.003-0.044). Programs with educational counseling and/or goal-setting strategies, as well as a greater number of strategies, were more effective for improving children's daily total steps, and wrist-worn activity trackers were more effective than waist-worn trackers for improving their daily MVPA levels (p = 0.001-0.021). CONCLUSIONS: Consumer-wearable activity tracker-based programs seem to be effective in promoting school-aged children's daily total steps and MVPA levels, especially for females and those that are physically inactive. These programs should include specific goal-setting, educational counseling, and wrist-worn trackers as especially effective strategies. However, due to the certainty of evidence being from "low" to "moderate", future well-designed primary research studies about the topic are needed. PROSPERO: CRD42020222363.

Sleep affects the motor memory of basketball shooting skills in young amateurs.

Sleep has long been shown as important for memory processing and retention, and has recently been implicated in motor memory consolidation. However, it is not known whether sports skills, including basketball shooting skills, are also affected by sleep in young, healthy individuals. Therefore, we investigated whether sleep before and after basketball shooting skill training affected the acquisition and retention of shooting skills. This study included 19 healthy male subjects who participated in a basketball shooting skill training session (100 shots) and a retention test performed 2 days later (30 shots). The learning and retention indices were calculated using performance scores that evaluated each subject's shooting skills. A wearable activity tracker was used to measure sleep parameters for 4 consecutive days, 2 days before and 2 days after training. We discovered the relationship between sleep duration before and after training and retention of shooting skills (sleep duration before training; p = 0.044, r = 0.467, sleep duration after training; p = 0.006, r = 0.606). The retention index for the subgroup with long sleep duration before and after training was significantly higher than that for the subgroup with short sleep duration before and after training, respectively (p = 0.021 for both). There was no significant relationship between learning index and each sleep parameter. Our results demonstrated that sleep duration before and after training was related to retention of shooting skills following basketball shooting skills training.

Enhancing the Physical Activity Levels of Frail Older Adults with a Wearable Activity Tracker-Based Exercise Intervention: A Pilot Cluster Randomized Controlled Trial.

A wearable activity tracker (WAT) incorporated with behavioral change techniques (BCTs) increases physical activity in younger adults; however, its effectiveness with frail older adults is unknown. The feasibility and preliminary effects of a WAT-based exercise intervention to increase physical activity levels in frail older adults was investigated in this pilot study involving 40 community-dwelling frail older adults. The experimental group received a 14-week WAT-based group exercise intervention and a 3-month follow-up, while the control group only received similar physical training and all BCTs. The recruitment rate was 93%, and the average attendance rate was 85.2% and 82.2% in the WAT and control groups, respectively, establishing feasibility. Adherence to wearing the WAT was 94.2% and 92% during the intervention and follow-up periods, respectively. A significant interaction effect between time and group was found in all physical assessments, possibly lasting for 3 months post-intervention. However, no significant difference between groups was observed in any daily activity level by the ActiGraph measurement. The majority of the WAT group's ActiGraph measurements reverted to baseline levels at the 1-month follow-up. Thus, the WAT-based exercise program has potential for employment among community-dwelling frail older adults, but sustaining the effects after the intervention remains a major challenge.

Introducing an Integrated Model of Adults' Wearable Activity Tracker Use and Obesity Information-Seeking Behaviors From a National Quota Sample Survey.

BACKGROUND: Research from multiple perspectives to investigate adults' use of wearable activity-tracking devices is limited. We offer a multiperspective model and provide empirical evidence of what leads to frequent usage of wearable health technologies from a large, nationally representative survey sample. OBJECTIVE: This study aims to explore factors affecting the use of wearable activity-tracking devices among health consumers from the perspectives of individual health beliefs (perceived severity, perceived susceptibility, perceived benefits, and self-efficacy) and information-seeking behaviors. METHODS: Our Integrated Model of Wearable Activity Tracker (IMWAT) use and proposed hypotheses were validated and tested with data collected from a telephone survey with a national quota sample. The data were analyzed using a variety of statistical techniques, including structural equation analysis. RESULTS: The sample comprised 2006 participants. Our results showed that the perceived benefits of physical activity, perceived susceptibility, and self-efficacy toward obesity were significant predictors of information-seeking behaviors, which, in turn, mediated their effects on the use of wearable activity trackers. Perceptions of obesity severity directly promoted wearable device usage. CONCLUSIONS: This study provided a new and powerful theoretical model that combined the health beliefs and information-seeking behaviors behind the use of wearable activity trackers in the adult population. The findings provide meaningful implications for developers and designers of wearable health technology products and will assist health informatics practitioners and obesity prevention communicators.

Comparing the Effectiveness of a Wearable Activity Tracker in Addition to Counseling and Counseling Only to Reinforce Leisure-Time Physical Activity among Breast Cancer Patients: A Randomized Controlled Trial.

This randomized controlled trial aimed to compare the effectiveness of a wearable activity tracker (WAT) in addition to counseling (WAT+counseling) and counseling only for reinforcing leisure-time physical activity (LTPA) among breast cancer patients during radiotherapy (RT). A total of 152 breast cancer patients who were planning to undergo radiation therapy (RT) after surgery participated in the study. The WAT+counseling group (n = 76) underwent physical activity (PA) self-monitoring using a WAT and participated in counseling. The counseling-only group (n = 76) received telephone counseling once a week during RT and did not receive WAT. The WAT+counseling group had increased relative change in self-reported LTPA (102.8) compared with the counseling-only group (57.8) immediately after RT compared to baseline. Although the relative changes of self-reported LTPA of the WAT+counseling group were higher at three and six months after the end of RT compared to in the counseling-only group, the results were not significant. The mean average daily step count of the WAT+counseling group was 9351.7, which increased to 11,592.2 during RT and 12,240.1 after RT. In the subgroup analysis, patients who did not perform regular PA before cancer diagnosis had significantly increased step counts. This study shows the feasibility of WAT with counseling to reinforce PA among breast cancer patients.