Comprehensive comparison of Apple Watch and Fitbit monitors in a free-living setting

Defining Activity Thresholds Triggering a "Stand Hour" for Apple Watch Users: Cross-Sectional Study

BACKGROUND

Sedentary behavior (SB) is one of the largest contributing factors increasing the risk of developing noncommunicable diseases, including cardiovascular disease and type 2 diabetes. Guidelines from the World Health Organization for physical activity suggest the substitution of SB with light physical activity. The Apple Watch contains a health metric known as the stand hour (SH). The SH is intended to record standing with movement for at least 1 minute per hour; however, the activity measured during the determination of the SH is unclear.

OBJECTIVE

In this cross-sectional study, we analyzed the algorithm used to determine time spent standing per hour. To do this, we investigated activity measurements also recorded on Apple Watches that influence the recording of an SH. We also aimed to estimate the values of any significant SH predictors in the recording of a SH.

METHODS

The cross-sectional study used anonymized data obtained in August 2022 from 20 healthy individuals gathered via convenience sampling. Apple Watch data were extracted from the Apple Health app through the use of a third-party app. Appropriate statistical models were fitted to analyze SH predictors.

RESULTS

Our findings show that active energy (AE) and step count (SC) measurements influence the recording of an SH. Comparing when an SH is recorded with when an SH is not recorded, we found a significant difference in the mean and median AE and SC. Above a threshold of 97.5 steps or 100 kJ of energy, it became much more likely that an SH would be recorded when each predictor was analyzed as a separate entity.

CONCLUSIONS

The findings of this study reveal the pivotal role of AE and SC measurements in the algorithm underlying the SH recording; however, our findings also suggest that a recording of an SH is influenced by more than one factor. Irrespective of the internal validity of the SH metric, it is representative of light physical activity and might, therefore, have use in encouraging individuals through various means, for example, notifications, to reduce their levels of SB.

Examining and Comparing the Energy Expenditure of Two Modes of a Virtual Reality Fitness Game (Supernatural): Indirect Calorimetry Study

BACKGROUND

The effectiveness of virtual reality (VR) fitness games as a form of moderate to vigorous physical activity has yet to be thoroughly quantified through gold standard energy expenditure measures.

OBJECTIVE

The purpose of this study was to examine the energy expenditure of 2 medium-intensity modes ("Flow and "Boxing") of a VR fitness game, Supernatural, using indirect calorimetry.

METHODS

Indirect calorimetry was used to examine relative and objective maximal oxygen consumption (VO2 max), metabolic equivalents of task (METs), and calories burned during medium-intensity bouts of both Flow and Boxing gameplay modes in young (mean age 25.42, SD 3.25 years), active individuals (n=12 female and n=11 male). METs and calories were also compared using a triaxial waist-worn accelerometer, an Apple smartwatch, and a VR headset. Mood states were assessed pre- and postbout using the shortened Profile of Mood States Questionnaire. Paired 2-tailed t tests were used to examine differences in game modes, between sexes, and pre-post exercise sessions.

RESULTS

Objective and relative VO2 max averaged 1.93 (SD 0.44) L/min and 27.61 (SD 5.60) mL/kg/min, respectively, between modes. Flow (mean 8.2, SD 1.54 METs) and Boxing (mean 7.6, SD 1.66 METs) are both classified as high energy expenditure, vigorous activities. Calorie expenditure data of the accelerometer and VR headset differed significantly from the metabolic cart. Mood changes pre- to post exercise were consistent with expected values for moderate- to vigorous-intensity physical activity, with participants reporting that they felt more "active," "full of pep," "vigorous," and "lively" (P<.05) following bouts. Male individuals reported higher objective oxygen consumption (VO2) for both Flow and Boxing modes; no other sex-specific differences were observed.

CONCLUSIONS

Both Flow and Boxing gameplay modes of Supernatural classify as vigorous physical activity and demonstrate the potential to promote mental and physical health benefits. Supernatural may be an effective exercise modality in a VO2 training program.

A Comprehensive Review of Behavior Change Techniques in Wearables and IoT: Implications for Health and Well-Being

This research paper delves into the effectiveness and impact of behavior change techniques fostered by information technologies, particularly wearables and Internet of Things (IoT) devices, within the realms of engineering and computer science. By conducting a comprehensive review of the relevant literature sourced from the Scopus database, this study aims to elucidate the mechanisms and strategies employed by these technologies to facilitate behavior change and their potential benefits to individuals and society. Through statistical measurements and related works, our work explores the trends over a span of two decades, from 2000 to 2023, to understand the evolving landscape of behavior change techniques in wearable and IoT technologies. A specific focus is placed on a case study examining the application of behavior change techniques (BCTs) for monitoring vital signs using wearables, underscoring the relevance and urgency of further investigation in this critical intersection of technology and human behavior. The findings shed light on the promising role of wearables and IoT devices for promoting positive behavior modifications and improving individuals' overall well-being and highlighting the need for continued research and development in this area to harness the full potential of technology for societal benefit.

Democratizing Health Care in the Metaverse: How Video Games can Monitor Eye Conditions Using the Vision Performance Index: A Pilot Study

Objective

In a world where digital media is deeply engrained into our everyday lives, there lies an opportunity to leverage interactions with technology for health and wellness. The Vision Performance Index (VPI) leverages natural human-technology interaction to evaluate visual function using visual, cognitive, and motor psychometric data over 5 domains: field of view, accuracy, multitracking, endurance, and detection. The purpose of this study was to describe a novel method of evaluating holistic visual function through video game-derived VPI score data in patients with specific ocular pathology.

Design

Prospective comparative analysis.

Participants

Patients with dry eye, glaucoma, cataract, diabetic retinopathy (DR), age-related macular degeneration, and healthy individuals.

Methods

The Vizzario Inc software development kit was integrated into 2 video game applications, Balloon Pop and Picture Perfect, which allowed for generation of VPI scores. Study participants were instructed to play rounds of each video game, from which a VPI score was compiled.

Main Outcome Measures

The primary outcome was VPI overall score in each comparison group. Vision Performance Index component, subcomponent scores, and psychophysical inputs were also compared.

Results

Vision Performance Index scores were generated from 93 patients with macular degeneration (n = 10), cataract (n = 10), DR (n = 15), dry eye (n = 15), glaucoma (n = 16), and no ocular disease (n = 27). The VPI overall score was not significantly different across comparison groups. The VPI subcomponent "reaction accuracy" score was significantly greater in DR patients (106 ± 13.2) versus controls (96.9 ± 11.5), P = 0.0220. The VPI subcomponent "color detection" score was significantly lower in patients with DR (96.8 ± 2.5; p=0.0217) and glaucoma (98.5 ± 6.3; P = 0.0093) compared with controls (101 ± 11). Psychophysical measures were statistically significantly different from controls: proportion correct (lower in DR, age-related macular degeneration), contrast errors (higher in cataract, DR), and saturation errors (higher in dry eye).

Conclusions

Vision Performance Index scores can be generated from interactions of an ocular disease population with video games. The VPI may offer utility in monitoring select ocular diseases through evaluation of subcomponent and psychophysical input scores; however, future larger-scale studies must evaluate the validity of this tool.

Financial Disclosures

Proprietary or commercial disclosure may be found after the references.

The Role of Daily Steps in the Treatment of Major Depressive Disorder: Secondary Analysis of a Randomized Controlled Trial of a 6-Month Internet-Based, Mindfulness-Based Cognitive Behavioral Therapy Intervention for Youth

BACKGROUND

Current evidence supports physical activity (PA) as an adjunctive treatment for major depressive disorder (MDD). Few studies, however, have examined the relationship between objectively measured PA and MDD treatment outcomes using prospective data.

OBJECTIVE

This study is a secondary analysis of data from a 24-week internet-based, mindfulness-based cognitive behavioral therapy program for MDD. The purpose of this analysis was twofold: (1) to examine average daily step counts in relation to MDD symptom improvement, and whether pain moderated this relationship; and (2) to examine whether changes in step activity (ie, step trajectories) during treatment were associated with baseline symptoms and symptom improvement.

METHODS

Patients from the Centre for Addiction and Mental Health were part of a randomized controlled trial evaluating the effects of internet-based, mindfulness-based cognitive behavioral therapy for young adults (aged 18-30 years old) with MDD. Data from 20 participants who had completed the intervention were analyzed. PA, in the form of objectively measured steps, was measured using the Fitbit-HR Charge 2 (Fitbit Inc), and self-reported depression severity was measured with the Beck Depression Inventory-II (BDI-II). Linear regression analysis was used to test PA's relationship with depression improvement and the moderating effect of pain severity and pain interference. Growth curve and multivariable regression models were used to test longitudinal associations.

RESULTS

Participants walked an average of 8269 steps per day, and each additional +1000-step difference between participants was significantly associated with a 2.66-point greater improvement (reduction) in BDI-II, controlling for anxiety, pain interference, and adherence to Fitbit monitoring (P=.02). Pain severity appeared to moderate (reduce) the positive effect of average daily steps on BDI-II improvement (P=.03). Higher baseline depression and anxiety symptoms predicted less positive step trajectories throughout treatment (Ps≤.001), and more positive step trajectories early in the trial predicted greater MDD improvement at the end of the trial (Ps<.04). However, step trajectories across the full duration of the trial did not significantly predict MDD improvement (Ps=.40).

CONCLUSIONS

This study used objective measurements to demonstrate positive associations between PA and depression improvement in the context of cognitive behavioral treatment. Pain appeared to moderate this relationship, and baseline symptoms of anxiety and depression predicted PA trajectories. The findings inform future interventions for major depression. Future research with larger samples should consider additional moderators of PA-related treatment success and the extent to which outcomes are related to PA change in multimodal interventions.

TRIAL REGISTRATION

Clinical Trials.gov NCT03406052; https://www.clinicaltrials.gov/ct2/show/NCT03406052.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/11591.

The use of commercial wrist-worn technology to track physiological outcomes in behavioral interventions

PURPOSE OF REVIEW

The aim of this review is to provide an overview of the use of commercial wrist-worn mobile health devices to track and monitor physiological outcomes in behavioral interventions as well as discuss considerations for selecting the optimal device.

RECENT FINDINGS

Wearable technology can enhance intervention design and implementation. The use of wrist-worn wearables provides the opportunity for tracking physiological outcomes, thus providing a unique approach for assessment and delivery of remote interventions. Recent findings support the utility, acceptability, and benefits of commercial wrist-worn wearables in interventions, and they can be used to continuously monitor outcomes, remotely administer assessments, track adherence, and personalize interventions. Wrist-worn devices show acceptable accuracy when measuring heart rate, blood pressure, step counts, and physical activity; however, accuracy is dependent on activity type, intensity, and device brand. These factors should be considered when designing behavioral interventions that utilize wearable technology.

SUMMARY

With the continuous advancement in technology and frequent product upgrades, the capabilities of commercial wrist-worn devices will continue to expand, thus increasing their potential use in intervention research. Continued research is needed to examine and validate the most recent devices on the market to better inform intervention design and implementation.

Accuracy and Reliability of a Suite of Digital Measures of Walking Generated Using a Wrist-Worn Sensor in Healthy Individuals: Performance Characterization Study

BACKGROUND

Mobility is a meaningful aspect of an individual's health whose quantification can provide clinical insights. Wearable sensor technology can quantify walking behaviors (a key aspect of mobility) through continuous passive monitoring.

OBJECTIVE

Our objective was to characterize the analytical performance (accuracy and reliability) of a suite of digital measures of walking behaviors as critical aspects in the practical implementation of digital measures into clinical studies.

METHODS

We collected data from a wrist-worn device (the Verily Study Watch) worn for multiple days by a cohort of volunteer participants without a history of gait or walking impairment in a real-world setting. On the basis of step measurements computed in 10-second epochs from sensor data, we generated individual daily aggregates (participant-days) to derive a suite of measures of walking: step count, walking bout duration, number of total walking bouts, number of long walking bouts, number of short walking bouts, peak 30-minute walking cadence, and peak 30-minute walking pace. To characterize the accuracy of the measures, we examined agreement with truth labels generated by a concurrent, ankle-worn, reference device (Modus StepWatch 4) with known low error, calculating the following metrics: intraclass correlation coefficient (ICC), Pearson r coefficient, mean error, and mean absolute error. To characterize the reliability, we developed a novel approach to identify the time to reach a reliable readout (time to reliability) for each measure. This was accomplished by computing mean values over aggregation scopes ranging from 1 to 30 days and analyzing test-retest reliability based on ICCs between adjacent (nonoverlapping) time windows for each measure.

RESULTS

In the accuracy characterization, we collected data for a total of 162 participant-days from a testing cohort (n=35 participants; median observation time 5 days). Agreement with the reference device-based readouts in the testing subcohort (n=35) for the 8 measurements under evaluation, as reflected by ICCs, ranged between 0.7 and 0.9; Pearson r values were all greater than 0.75, and all reached statistical significance (P<.001). For the time-to-reliability characterization, we collected data for a total of 15,120 participant-days (overall cohort N=234; median observation time 119 days). All digital measures achieved an ICC between adjacent readouts of >0.75 by 16 days of wear time.

CONCLUSIONS

We characterized the accuracy and reliability of a suite of digital measures that provides comprehensive information about walking behaviors in real-world settings. These results, which report the level of agreement with high-accuracy reference labels and the time duration required to establish reliable measure readouts, can guide the practical implementation of these measures into clinical studies. Well-characterized tools to quantify walking behaviors in research contexts can provide valuable clinical information about general population cohorts and patients with specific conditions.

Prophylactic relationship between mental health disorder symptoms and physical activity of Royal Canadian Mounted Police Cadets during the cadet training program

Objective

Royal Canadian Mounted Police report experiencing extremely frequent potentially psychologically traumatic events (PPTE). In a recent study, approximately half of participating RCMP screened positive for one or more mental disorders, which is approximately five times the diagnostic proportion for the general Canadian population. Increased reporting of mental health symptoms been linked to PPTE exposures. Programs promoting physical activity may be useful interventions to supplement or pair with mental health interventions, providing anxiolytic, antidepressant, and stress-buffering effects. The current study was designed to assess the relationship between physical activity behaviors and reported mental health disorder symptoms of cadets during the Royal Mounted Canadian Police (RCMP) Cadet Training Program (CTP). The current study also examined the relationship between exercise and mental health disorder symptoms of cadets during the CTP.

Methods

The study included data from 394 cadets (76.1% male). An analysis of variance (ANOVA) and a series of t-tests were used to assess several differences across sociodemographic groups. Bivariate Spearman's Rank correlations were performed between the average number of active calories burned per day, as recorded by Apple Watches, and changes in self-reported mental health disorder symptoms (i.e., Generalized Anxiety Disorder [GAD], Major Depressive Disorder [MDD], Posttraumatic Stress Disorder [PTSD], Social Anxiety Disorder [SAD]. Alcohol Use Disorders [AUD], Panic Disorder [PD]) from pre-training (starting the CTP) to pre-deployment (completing the CTP) 26 weeks later.

Results

There were statistically significant correlations between physical activity and self-reported mental health disorder symptom scores during CTP. Cadets who performed more physical activity from pre-training to pre-deployment had statistically significantly greater decreases in symptoms of GAD (ρ = -0.472, p < 0.001), MDD (ρ = -0.307, p < 0.001), PTSD (ρ = -0.343, p < 0.001), and AUD (ρ = -0.085, p < 0.05). There was no statistically significant relationship between physical activity and changes in PD symptoms (ρ = -0.037, p > 0.05). There were also no statistically significant relationships between pre-CTP mental health disorder symptom scores and the volume of physical activity performed during CTP.

Conclusion

There was evidence of a significant relationship between reductions in mental health disorder symptom scores and physical activity during the 26-week CTP. The results highlight the role that exercise can play as an important tool for reducing mental health disorder symptoms, considering there was no relationship between pre-CTP baseline mental health scores and physical activity performed during CTP. Further research is needed to understand differences in physical activity behaviours among cadets and serving RCMP.

Study protocol for two pilot randomised controlled trials aimed at increasing physical activity using electrically assisted bicycles to enhance prostate or breast cancer survival

BACKGROUND

In 2020, 1.4 and 2.3 million new cases of prostate cancer and breast cancer respectively were diagnosed globally. In the UK, prostate cancer is the most common male cancer, while breast cancer is the most common female cancer. Engaging in physical activity (PA) is a key component of treatment. However, rates of PA are low in these clinical populations. This paper describes the protocol of CRANK-P and CRANK-B, two pilot randomised controlled trials, involving an e-cycling intervention aimed at increasing PA in individuals with prostate cancer or breast cancer respectively.

METHODS

These two trials are single-centre, stratified, parallel-group, two-arm randomised waitlist-controlled pilot trials in which forty individuals with prostate cancer (CRANK-P) and forty individuals with breast cancer (CRANK-B) will be randomly assigned, in a 1:1 allocation ratio, to an e-cycling intervention or waitlist control. The intervention consists of e-bike training with a certified cycle instructor, followed by the provision of an e-bike for 12 weeks. Following the intervention period, participants in the e-bike condition will be directed to community-based initiatives through which they can access an e-bike. Data will be collected at baseline (T0), immediately post intervention (T1) and at 3-month follow-up (T2). In addition, in the intervention group, data will be collected during the intervention and follow-up periods. Quantitative and qualitative methods will be used. The primary objectives are to determine effective recruitment strategies, establish recruitment and consent rates, adherence and retention in the study, and determine the feasibility and acceptability of the study procedures and intervention. The potential impact of the intervention on clinical, physiological and behavioural outcomes will be assessed to examine intervention promise. Data analyses will be descriptive.

DISCUSSION

The findings from these trials will provide information on trial feasibility and highlight the potential of e-cycling as a strategy to positively impact the health and behaviour of individuals with prostate cancer and breast cancer. If appropriate, this information can be used to design and deliver a fully powered definitive trial.

TRIAL REGISTRATION

CRANK-B: [ISRCTN39112034]. CRANK-P [ISRCTN42852156]. Registered [08/04/2022] https://www.isrctn.com .

An Algorithm to Classify Real-World Ambulatory Status From a Wearable Device Using Multimodal and Demographically Diverse Data: Validation Study

BACKGROUND

Measuring the amount of physical activity and its patterns using wearable sensor technology in real-world settings can provide critical insights into health status.

OBJECTIVE

This study's aim was to develop and evaluate the analytical validity and transdemographic generalizability of an algorithm that classifies binary ambulatory status (yes or no) on the accelerometer signal from wrist-worn biometric monitoring technology.

METHODS

Biometric monitoring technology algorithm validation traditionally relies on large numbers of self-reported labels or on periods of high-resolution monitoring with reference devices. We used both methods on data collected from 2 distinct studies for algorithm training and testing, one with precise ground-truth labels from a reference device (n=75) and the second with participant-reported ground-truth labels from a more diverse, larger sample (n=1691); in total, we collected data from 16.7 million 10-second epochs. We trained a neural network on a combined data set and measured performance in multiple held-out testing data sets, overall and in demographically stratified subgroups.

RESULTS

The algorithm was accurate at classifying ambulatory status in 10-second epochs (area under the curve 0.938; 95% CI 0.921-0.958) and on daily aggregate metrics (daily mean absolute percentage error 18%; 95% CI 15%-20%) without significant performance differences across subgroups.

CONCLUSIONS

Our algorithm can accurately classify ambulatory status with a wrist-worn device in real-world settings with generalizability across demographic subgroups. The validated algorithm can effectively quantify users' walking activity and help researchers gain insights on users' health status.

Physical activity and pregnancy outcomes: an expert review

This expert review aimed to assess current literature on the effect and tracking of physical activity during pregnancy and associated outcomes. Self-reported physical activity may be inaccurate given the subjective nature of the questionnaires. The accelerometer ActiGraph is considered the "gold standard" to objectively measure physical activity. However, other more user-friendly wearable devices are now widely available and may accurately track physical activity. Conclusive data from both validated activity questionnaires and accelerometers indicate that physical activity is safe during pregnancy. In addition, studies of physical activity during pregnancy that evaluate pregnancy outcomes have found reduced risks of preterm birth, preeclampsia, and gestational diabetes mellitus and improved mental health among individuals who regularly engage in physical activity. In the United States, approximately 48% of pregnant individuals gain more than the recommended amount of weight during pregnancy; excessive gestational weight gain is associated with an increased risk of maternal and fetal complications, including preterm birth, preeclampsia, and gestational diabetes mellitus, and corresponding higher adverse short- and long-term maternal and offspring health outcomes. Although physical activity is safe during pregnancy and may reduce excessive gestational weight gain and resultant pregnancy complications, further research is needed to determine the frequency and duration of specific types of physical activity during pregnancy. Providers should encourage physical activity before and during pregnancy and educate patients regarding the benefits and safety of physical activity.

Effect of Physical Activity and Exercise on the Level of COVID-19 Antibodies and Lifestyle-Related Factors among Vaccinated Health Science Center (HSC) Students: A Pilot Randomized Trial

A vaccine is a type of medicine that increases immunity and the number of antibodies (IgM and IgG) when injected into the body, preparing it in case of an actual viral infection. It has been shown in several studies that there is a significant relationship between physical activity and vaccination. Furthermore, it has been documented that physical activity can play a major role in reducing stress. Evidence also shows the existence of a relationship between immunity, vaccine response, and sleep duration. To investigate the effects of physical activity on the level of COVID-19 antibodies and lifestyle-related factors, Health Science Center (HSC) students who had taken the third dose of the vaccine and had no prior infection of the COVID-19 virus were investigated. To serve the purpose of this study, an anti-SARS-CoV-2 test was applied by taking a blood sample from the students. The Perceived Stress Scale (PSS) and Pittsburgh Sleep Quality Index (PSQI) questionnaires and the Borg’s 15-point scale were given to the participants to fill out. The study utilized a two-arm randomized control research design in which 40 participants were randomly assigned into one of two groups, either the control group (n = 20) or the treatment group (n = 20). All tests and assessments were performed before and after intervention for both groups. The control group walked less than 5000 steps every day for one month with a 20 min rest during the exercise session, while the treatment group walked more than 12,000 steps every day for the same time and exercise task session. The students’ steps were monitored using an Apple watch. There was a significant decrease in the IgG antibody level in the treatment group compared to the control group (p < 0.001). The IgM antibody level of all groups did not show any significant difference before starting the intervention. However, there was a significant (p < 0.05) decrease in the IgM level of the treatment group after treatment compared to before treatment. Moreover, there was a significant decrease in the treatment group’s stress level and sleep disruption, indicating better sleep quality, compared to the control group (p < 0.035). The levels of IgG and IgM did not improve for the treatment group. However, the treatment group improved their stress level and sleep disruption. Therefore, further rigorous research is needed to investigate vaccine efficacy among more physically active people.

Are Wrist-Worn Activity Trackers and Mobile Applications Valid for Assessing Physical Activity in High School Students? Wearfit Study

The purpose was to examine the validity of three wrist-worn commercial activity trackers (Samsung Galaxy Watch Active 2, Apple Watch Series 5, and Xiaomi Mi Band 5) and six mobile apps (Pedometer and Pacer for android and iPhone mobiles, Google Fit for android, and Apple Health for iPhone mobiles) for estimating high school students' steps and physical activity (PA) under free-living conditions. A sample of 56 (27 females; mean age = 14.7 years) and 51 (25 females; mean age = 14.0 years) high school students participated in Study 1 and 2, respectively. Study 1: Students performed a 200-meter course in four different conditions while wearing the wearables. Step counting through a video record was used as the golden standard. Study 2: Students wore the three wrist-worn commercial activity trackers during the waking time of one day, considering ActiGraph model wGT3X-BT accelerometers as a standard of reference. Afterward, the agreement between the PA scores measured by the commercial activity trackers and the video (study 1) or accelerometers (study 2) were calculated as follows: Equivalence test, Limits of Agreement (LOA); Mean Absolute Error (MAE); Mean Absolute Percentage Error (MAPE); and Intraclass Correlation Coefficient (ICC). Results showed that all the wearables presented excellent validity for assessing steps in structured free-living conditions (study 1; MAPE &lt; 5%), although their validity was between poor-excellent based on ICC (95% confidence interval) values (ICC = 0.56-1.00). Regarding Study 2, the Xiaomi wristband and the Samsung Watch presented acceptable-excellent (MAPE = 9.4-11.4%; ICC = 0.91-0.97) validity for assessing steps under unstructured free-living conditions (study 2). However, the Apple Watch presented questionable-excellent validity (MAPE = 18.0%; ICC = 0.69-0.95). Regarding moderate-to-vigorous PA (MVPA) and total PA, only the Apple Watch showed low-acceptable validity for MAPE value and questionable-excellent validity for the ICC values for MVPA assessment (MAPE = 22.6; ICC = 0.67-0.93). All wearables checked in this study have shown adequate validity results in order to assess steps in both structured and unstructured free-living conditions for both continuous and dichotomous variables. Moreover, for assessing MVPA, only the Apple Watch reported valid results for compliance or non-compliance with the daily PA recommendations. However, the results showed low validity for total PA and MVPA as continuous variables. In conclusion, depending on the user's/researcher's aim and context, one or another wearable activity tracker could be more adequate, mainly because of its valid measurements and its costs.

Accuracy and Precision of Consumer-Grade Wearable Activity Monitors for Assessing Time Spent in Sedentary Behavior in Children and Adolescents: Systematic Review

Background

A large number of wearable activity monitor models are released and used each year by consumers and researchers. As more studies are being carried out on children and adolescents in terms of sedentary behavior (SB) assessment, knowledge about accurate and precise monitoring devices becomes increasingly important.

Objective

The main aim of this systematic review was to investigate and communicate findings on the accuracy and precision of consumer-grade physical activity monitors in assessing the time spent in SB in children and adolescents.

Methods

Searches of PubMed (MEDLINE), Scopus, SPORTDiscus (full text), ProQuest, Open Access Theses and Dissertations, DART Europe E-theses Portal, and Networked Digital Library of Theses and Dissertations electronic databases were performed. All relevant studies that compared different types of consumer-grade monitors using a comparison method in the assessment of SB, published in European languages from 2015 onward were considered for inclusion. The risk of bias was estimated using Consensus-Based Standards for the Selection of Health Status Measurement Instruments. For enabling comparisons of accuracy measures within the studied outcome domain, measurement accuracy interpretation was based on group mean or percentage error values and 90% CI. Acceptable limits were predefined as –10% to +10% error in controlled and free-living settings. For determining the number of studies with group error percentages that fall within or outside one of the sides from previously defined acceptable limits, two 1-sided tests of equivalence were carried out, and the direction of measurement error was examined.

Results

A total of 8 studies complied with the predefined inclusion criteria, and 3 studies provided acceptable data for quantitative analyses. In terms of the presented accuracy comparisons, 14 were subsequently identified, with 6 of these comparisons being acceptable in terms of quantitative analysis. The results of the Cochran Q test indicated that the included studies did not share a common effect size (Q₅=82.86; P<.001). I², which represents the percentage of total variation across studies due to heterogeneity, amounted to 94%. The summary effect size based on the random effects model was not statistically significant (effect size=14.36, SE 12.04, 90% CI −5.45 to 34.17; P=.23). According to the equivalence test results, consumer-grade physical activity monitors did not generate equivalent estimates of SB in relation to the comparison methods. Majority of the studies (3/7, 43%) that reported the mean absolute percentage errors have reported values of <30%.

Conclusions

This is the first study that has attempted to synthesize available evidence on the accuracy and precision of consumer-grade physical activity monitors in measuring SB in children and adolescents. We found very few studies on the accuracy and almost no evidence on the precision of wearable activity monitors. The presented results highlight the large heterogeneity in this area of research.

Trial Registration

PROSPERO CRD42021251922; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=251922

A Standardised Core Outcome Set for Measurement and Reporting Sedentary Behaviour Interventional Research: The CROSBI Consensus Study

Heterogeneity of descriptors and outcomes measured and reported in sedentary behaviour (SB) research hinder the meta-analysis of data and accumulation of evidence. The objective of the Core Research Outcomes for Sedentary Behaviour Interventions (CROSBI) consensus study was to identify and validate, a core outcome set (COS) to report (what, how, when to measure) in interventional sedentary behaviour studies. Outcomes, extracted from a systematic literature review, were categorized into domains and data items (COS v0.0). International experts (n = 5) provided feedback and identified additional items, which were incorporated into COS v0.1. A two round online Delphi survey was conducted to seek consensus from a wider stakeholder group and outcomes that achieved consensus in the second round COS (v0.2), were ratified by the expert panel. The final COS (v1.0) contains 53 data items across 12 domains, relating to demographics, device details, wear-time criteria, wear-time measures, posture-related measures, sedentary breaks, sedentary bouts and physical activity. Notably, results indicate that sedentary behaviour outcomes should be measured by devices that include an inclinometry or postural function. The proposed standardised COS is available openly to enhance the accumulation of pooled evidence in future sedentary behaviour intervention research and practice.

Quality Evaluation of Free-living Validation Studies for the Assessment of 24-Hour Physical Behavior in Adults via Wearables: Systematic Review

Background

Wearable technology is a leading fitness trend in the growing commercial industry and an established method for collecting 24-hour physical behavior data in research studies. High-quality free-living validation studies are required to enable both researchers and consumers to make guided decisions on which study to rely on and which device to use. However, reviews focusing on the quality of free-living validation studies in adults are lacking.

Objective

This study aimed to raise researchers’ and consumers’ attention to the quality of published validation protocols while aiming to identify and compare specific consistencies or inconsistencies between protocols. We aimed to provide a comprehensive and historical overview of which wearable devices have been validated for which purpose and whether they show promise for use in further studies.

Methods

Peer-reviewed validation studies from electronic databases, as well as backward and forward citation searches (1970 to July 2021), with the following, required indicators were included: protocol must include real-life conditions, outcome must belong to one dimension of the 24-hour physical behavior construct (intensity, posture or activity type, and biological state), the protocol must include a criterion measure, and study results must be published in English-language journals. The risk of bias was evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2 tool with 9 questions separated into 4 domains (patient selection or study design, index measure, criterion measure, and flow and time).

Results

Of the 13,285 unique search results, 222 (1.67%) articles were included. Most studies (153/237, 64.6%) validated an intensity measure outcome such as energy expenditure. However, only 19.8% (47/237) validated biological state and 15.6% (37/237) validated posture or activity-type outcomes. Across all studies, 163 different wearables were identified. Of these, 58.9% (96/163) were validated only once. ActiGraph GT3X/GT3X+ (36/163, 22.1%), Fitbit Flex (20/163, 12.3%), and ActivPAL (12/163, 7.4%) were used most often in the included studies. The percentage of participants meeting the quality criteria ranged from 38.8% (92/237) to 92.4% (219/237). On the basis of our classification tree to evaluate the overall study quality, 4.6% (11/237) of studies were classified as low risk. Furthermore, 16% (38/237) of studies were classified as having some concerns, and 72.9% (173/237) of studies were classified as high risk.

Conclusions

Overall, free-living validation studies of wearables are characterized by low methodological quality, large variability in design, and focus on intensity. Future research should strongly aim at biological state and posture or activity outcomes and strive for standardized protocols embedded in a validation framework. Standardized protocols for free-living validation embedded in a framework are urgently needed to inform and guide stakeholders (eg, manufacturers, scientists, and consumers) in selecting wearables for self-tracking purposes, applying wearables in health studies, and fostering innovation to achieve improved validity.

Accuracy and Precision of Energy Expenditure, Heart Rate, and Steps Measured by Combined-Sensing Fitbits Against Reference Measures: Systematic Review and Meta-analysis

BACKGROUND

Although it is widely recognized that physical activity is an important determinant of health, assessing this complex behavior is a considerable challenge.

OBJECTIVE

The purpose of this systematic review and meta-analysis is to examine, quantify, and report the current state of evidence for the validity of energy expenditure, heart rate, and steps measured by recent combined-sensing Fitbits.

METHODS

We conducted a systematic review and Bland-Altman meta-analysis of validation studies of combined-sensing Fitbits against reference measures of energy expenditure, heart rate, and steps.

RESULTS

A total of 52 studies were included in the systematic review. Among the 52 studies, 41 (79%) were included in the meta-analysis, representing 203 individual comparisons between Fitbit devices and a criterion measure (ie, n=117, 57.6% for heart rate; n=49, 24.1% for energy expenditure; and n=37, 18.2% for steps). Overall, most authors of the included studies concluded that recent Fitbit models underestimate heart rate, energy expenditure, and steps compared with criterion measures. These independent conclusions aligned with the results of the pooled meta-analyses showing an average underestimation of -2.99 beats per minute (k comparison=74), -2.77 kcal per minute (k comparison=29), and -3.11 steps per minute (k comparison=19), respectively, of the Fitbit compared with the criterion measure (results obtained after removing the high risk of bias studies; population limit of agreements for heart rate, energy expenditure, and steps: -23.99 to 18.01, -12.75 to 7.41, and -13.07 to 6.86, respectively).

CONCLUSIONS

Fitbit devices are likely to underestimate heart rate, energy expenditure, and steps. The estimation of these measurements varied by the quality of the study, age of the participants, type of activities, and the model of Fitbit. The qualitative conclusions of most studies aligned with the results of the meta-analysis. Although the expected level of accuracy might vary from one context to another, this underestimation can be acceptable, on average, for steps and heart rate. However, the measurement of energy expenditure may be inaccurate for some research purposes.

Associations Between Device-Measured Physical Activity and Glycemic Control and Variability Indices Under Free-Living Conditions

Background: Disturbances of glycemic control and large glycemic variability have been associated with increased risk of type 2 diabetes in the general population as well as complications in people with diabetes. Long-term health benefits of physical activity are well documented but less is known about the timing of potential short-term effects on glycemic control and variability in free-living conditions. Materials and Methods: We analyzed data from 85 participants without diabetes from the Food & You digital cohort. During a 2-week follow-up, device-based daily step count was studied in relationship to glycemic control and variability indices using generalized estimating equations. Glycemic indices, evaluated using flash glucose monitoring devices (FreeStyle Libre), included minimum, maximum, mean, standard deviation, and coefficient of variation of daily glucose values, the glucose management indicator, and the approximate area under the sensor glucose curve. Results: We observed that every 1000 steps/day increase in daily step count was associated with a 0.3588 mg/dL (95% confidence interval [CI]: -0.6931 to -0.0245), a 0.0917 mg/dL (95% CI: -0.1793 to -0.0042), and a 0.0022% (95% CI: -0.0043 to -0.0001) decrease in the maximum glucose values, mean glucose, and in the glucose management indicator of the following day, respectively. We did not find any association between daily step count and glycemic indices from the same day. Conclusions: Increasing physical activity level was linked to blunted glycemic excursions during the next day. Because health-related benefits of physical activity can be long to observe, such short-term physiological benefits could serve as personalized feedback to motivate individuals to engage in healthy behaviors.

Usability of a two-way personalized mobile trainer system in a community-based exercise program for adults with chronic traumatic brain injury

OBJECTIVE

To examine the usability of an Apple Watch-based, two-way Personalized Mobile Trainer (PMT) in community-based exercise programs for individuals with chronic traumatic brain injury (cTBI).

METHODS

This is a prospective pilot study. Twenty participants with cTBI aged 46-73 were enrolled in a 3-month individualized exercise program. After one in-person training session on PMT and exercise program, participants were prescribed either aerobic exercise training (AET) or stretching and toning (SAT) performed at home. The PMT was used to remotely deliver updated exercise prescription, track exercise progress, and communicate with the participants. The primary outcome was compliance with the exercise programs.

RESULTS

All the participants completed the assigned exercise program with an average compliance of 76%. Nineteen (95%) participants were able to use the PMT properly during exercise sessions. After 3 months of training, the AET trended toward maintaining exercise endurance when compared with the SAT group (0.3% vs -4%, p = 0.14) with a medium effect size of 0.43.

CONCLUSION

Using the PMT system to support and track exercise in community-based exercise programs is feasible. The PMT may promote compliance with the training program but testing its effectiveness with larger trials is warranted.

Validity of the Fitbit Ace and Moki Devices for Assessing Steps During Different Walking Conditions in Young Adolescents

PURPOSE

Using wearable monitoring devices is increasingly ubiquitous, including among young people. However, there is limited evidence of the validity of devices which are aimed at children and adolescents. The purpose of this study was to evaluate the validity of Fitbit Ace and Moki monitors in healthy young adolescents.

METHODS

This cross-sectional study included 17 young adolescents (ages 11-13 y) ambulating between 3 different walking conditions (incidental [∼6 min], controlled, and treadmill [each 3 min], while wearing wrist-worn devices [Fitbit Ace, Moki] on each wrist [left and right, respectively]). Data from the devices were compared with observer counts (criterion). Bland-Altman plots and mean absolute percentage errors were computed.

RESULTS

Analyses identified that the Fitbit Ace showed higher levels of bias across conditions compared with the Moki device: (mean difference [SD]; Fitbit Ace: 30.0 [38.0], 3.0 [13.0], and 13.0 [23.0] steps and Moki: 1.0 [19.0], 4.0 [16.0], and 6.0 [14.0] steps, incidental, controlled, and treadmill, respectively). Mean absolute percentage errors ranged from 3.1% to 9.5% for the Fitbit Ace and 3.0% to 4.0% for the Moki device.

CONCLUSION

The Fitbit Ace and Moki devices might not provide acceptable validity under all walking conditions, but the Moki provides more accurate estimates of incidental walking and might therefore be a good choice for free-living research or school-based interventions.

Reference Values for Wristband Accelerometry Data in Children Aged 6-11 Years of Age

OBJECTIVES

Wristband activity trackers (accelerometers) could serve as a convenient monitoring tool to continuously quantify physical activity throughout the day. We aim to provide reference values for the use of these devices in healthy children.

METHODS

Children were recruited at a local school and provided with activity trackers (Fitbit Charge 2). Pupils were instructed to wear devices during all normal daytime activities over a period of 11-15 days. Demographic data, total number of daily steps and heart rate were recorded. In addition, all children/parents were asked to complete a questionnaire providing information about daily physical routine (mode of transport to school, sporting activities as well as sport club memberships).

RESULTS

Three hundred two children (54.6% boys; median age 8.7 years) participated in this prospective study. Median wearing time of the device was 12.1 h/day. Overall, the median daily total step count was 12,095. Median step counts/day were significantly higher in boys compared to girls (13,015 vs. 11,305 steps/day; p < 0.0001). In addition, step counts were significantly higher during the week, compared to weekend days. The effect of age on daily step count was found to be non-linear: the total daily step count increased from 6 to 8.5 years of age, while older children (aged >8.5 years) had lower step counts compared to the younger children. Significant predictors of the daily step count were male gender (+1,324.9 steps, p = 0.0008), mode of transportation to school (walking, bicycle, scooter: +865.5 steps p = 0.049), active membership in a sports club (+1,324.9 steps/day, p = 0.0008), and number of structured units of physical exercise performed (+336.5/per 45 min, p < 0.0001). Severe obesity was associated with a significant reduction in total daily step count (-3037.7 steps/day, p = 0.015).

CONCLUSION

Our prospective cohort study of healthy school children provides reference values for wristband accelerometers in normal individuals. In addition, it clarifies the effect of age, body weight and lifestyle on normal daily step counts in school children. This data should be helpful to judge the degree of physical limitation of patients compared to healthy peers.

Quantitative Analysis of Performance Recovery in Semi-Professional Football Players after the COVID-19 Forced Rest Period

This study proposes the instrumental analysis of the physiological and biomechanical adaptation of football players to a fatigue protocol during the month immediately after the COVID-19 lockdown, to get insights into fitness recovery. Eight male semi-professional football players took part in the study and filled a questionnaire about their activity during the lockdown. At the resumption of activities, the mean heart rate and covered distances during fatiguing exercises, the normalized variations of mean and maximum exerted power in the Wingate test and the Bosco test outcomes (i.e., maximum height, mean exerted power, relative strength index, leg stiffness, contact time, and flight time) were measured for one month. Questionnaires confirmed a light-intensity self-administered physical activity. A significant effect of fatigue (Wilcoxon signed-rank test p < 0.05) on measured variables was confirmed for the four weeks. The analysis of the normalized variations of the aforementioned parameters allowed the distinguishing of two behaviors: downfall in the first two weeks, and recovery in the last two weeks. Instrumental results suggest a physiological and ballistic (i.e., Bosco test outcomes) recovery after four weeks. As concerns the explosive skills, the observational data are insufficient to show complete recovery.

STEPS to Enhance Physical Activity After Hematopoietic Cell Transplantation for Multiple Myeloma

BACKGROUND

Finding effective ways to increase physical activity immediately following high-dose chemotherapy and autologous hematopoietic cell transplantation (HCT) for treatment of multiple myeloma (MM) is challenging.

OBJECTIVE

This pilot randomized clinical trial tested the acceptability, feasibility, and preliminary effects of a free-living physical activity intervention (STEPS) compared with usual care (UC) on physical activity, fatigue, muscle strength, functional ability, sleep, and quality of life following treatment for MM with HCT.

METHODS

Using a 2-group pretest/posttest design (N = 32), this study compared the 6-week STEPS intervention to UC. Data were collected using self-report questionnaires, functional performance tests, and wrist actigraphy before HCT and 7 weeks following hospital discharge.

RESULTS

The STEPS group achieved their physical activity goals on 53% of intervention days. The STEPS group experienced greater appetite loss, more diarrhea, and slept more than UC regardless of time point. Both groups reported improvements in mental fatigue, emotional functioning, pain, sleep disturbance, anger, anxiety, and depression but climbed stairs slower and had weaker hand grips after intervention. Both groups subjectively reported fewer sleep disturbances but objectively experienced more wakefulness after sleep onset and an increased number of awakenings postintervention.

CONCLUSIONS

The STEPS intervention is acceptable and feasible for people with MM treated with HCT. Both groups reported some improved symptoms but experienced some declines in physical performance postintervention.

IMPLICATIONS FOR PRACTICE

Nurses strive to optimize health and promote well-being. Helping people increase their physical activity after treatment for MM with HCT may improve symptoms, but additional studies are needed.