scholarly journals Wearable Activity Trackers for Monitoring Adherence to Home Confinement During the COVID-19 Pandemic Worldwide: Data Aggregation and Analysis

10.2196/19787 ◽  
2020 ◽  
Vol 22 (6) ◽  
pp. e19787 ◽  
Author(s):  
Jean Louis Pépin ◽  
Rosa Maria Bruno ◽  
Rui-Yi Yang ◽  
Vincent Vercamer ◽  
Paul Jouhaud ◽  
...  
Keyword(s):  
Physical Activity ◽  
Activity Patterns ◽  
Control Measures ◽  
Time Data ◽  
School Closures ◽  
Absolute Level ◽  
Natural Activity ◽  
Activity Trackers ◽  
Steps Per Day ◽  
Wearable Activity Trackers

Background In the context of home confinement during the coronavirus disease (COVID-19) pandemic, objective, real-time data are needed to assess populations’ adherence to home confinement to adapt policies and control measures accordingly. Objective The aim of this study was to determine whether wearable activity trackers could provide information regarding users' adherence to home confinement policies because of their capacity for seamless and continuous monitoring of individuals’ natural activity patterns regardless of their location. Methods We analyzed big data from individuals using activity trackers (Withings) that count the wearer’s average daily number of steps in a number of representative nations that adopted different modalities of restriction of citizens’ activities. Results Data on the number of steps per day from over 740,000 individuals around the world were analyzed. We demonstrate the physical activity patterns in several representative countries with total, partial, or no home confinement. The decrease in steps per day in regions with strict total home confinement ranged from 25% to 54%. Partial lockdown (characterized by social distancing measures such as school closures, bar and restaurant closures, and cancellation of public meetings but without strict home confinement) does not appear to have a significant impact on people’s activity compared to the pre-pandemic period. The absolute level of physical activity under total home confinement in European countries is around twofold that in China. In some countries, such as France and Spain, physical activity started to gradually decrease even before official commitment to lockdown as a result of initial less stringent restriction orders or self-quarantine. However, physical activity began to increase again in the last 2 weeks, suggesting a decrease in compliance with confinement orders. Conclusions Aggregate analysis of activity tracker data with the potential for daily updates can provide information regarding adherence to home confinement policies.

scholarly journals Wearable Activity Trackers for Monitoring Adherence to Home Confinement During the COVID-19 Pandemic Worldwide: Data Aggregation and Analysis (Preprint)

2020 ◽  
Author(s):  
Jean Louis Pépin ◽  
Rosa Maria Bruno ◽  
Rui-Yi Yang ◽  
Vincent Vercamer ◽  
Paul Jouhaud ◽  
...  
Keyword(s):  
Physical Activity ◽  
Activity Patterns ◽  
Control Measures ◽  
Time Data ◽  
School Closures ◽  
Absolute Level ◽  
Natural Activity ◽  
Activity Trackers ◽  
Steps Per Day ◽  
Wearable Activity Trackers

BACKGROUND In the context of home confinement during the coronavirus disease (COVID-19) pandemic, objective, real-time data are needed to assess populations’ adherence to home confinement to adapt policies and control measures accordingly. OBJECTIVE The aim of this study was to determine whether wearable activity trackers could provide information regarding users' adherence to home confinement policies because of their capacity for seamless and continuous monitoring of individuals’ natural activity patterns regardless of their location. METHODS We analyzed big data from individuals using activity trackers (Withings) that count the wearer’s average daily number of steps in a number of representative nations that adopted different modalities of restriction of citizens’ activities. RESULTS Data on the number of steps per day from over 740,000 individuals around the world were analyzed. We demonstrate the physical activity patterns in several representative countries with total, partial, or no home confinement. The decrease in steps per day in regions with strict total home confinement ranged from 25% to 54%. Partial lockdown (characterized by social distancing measures such as school closures, bar and restaurant closures, and cancellation of public meetings but without strict home confinement) does not appear to have a significant impact on people’s activity compared to the pre-pandemic period. The absolute level of physical activity under total home confinement in European countries is around twofold that in China. In some countries, such as France and Spain, physical activity started to gradually decrease even before official commitment to lockdown as a result of initial less stringent restriction orders or self-quarantine. However, physical activity began to increase again in the last 2 weeks, suggesting a decrease in compliance with confinement orders. CONCLUSIONS Aggregate analysis of activity tracker data with the potential for daily updates can provide information regarding adherence to home confinement policies.

scholarly journals B.01 Impact of work-hours and sleep on well-being and burnout for physicians-in-training: the prospective RATE Study

2017 ◽  
Vol 44 (S2) ◽  
pp. S10-S10
Author(s):  
D Mendelsohn ◽  
I Despot ◽  
PA Gooderham ◽  
A Singhal ◽  
GJ Redekop ◽  
...  
Keyword(s):  
Physical Activity ◽  
Job Satisfaction ◽  
Well Being ◽  
Work Hours ◽  
Surgical Residents ◽  
Activity Trackers ◽  
Steps Per Day ◽  
Wearable Activity Trackers ◽  
Rate Study ◽  
The Impact

Background: Wearable activity trackers are an innovative tool for measuring sleep and physical activity. The Resident Activity Tracker Evaluation (RATE) is a prospective observational study evaluating the impact of work-hours, sleep, and physical activity on resident well-being, burnout, and job satisfaction. Methods: Residents were recruited from: 1. general surgery and orthopedics (SURG), 2. internal medicine and neurology (MED) and 3. anesthesia and radiology (RCD). Groups 1 and 2 do not enforce on-call duration restrictions and group 3 had 12-hour restricted-call durations (RCD). Participants wore FitBit activity trackers for 14 days and completed four validated surveys assessing self-reported health, sleepiness, burnout, and job satisfaction. Results: Fifty-nine residents completed the study. 778 days of activity and 244 on-call periods were tracked. Surgical residents worked 24 more hours per week than non-surgical residents (84.3 vs 60.7). Surgical residents had 7 less hours of sleep per week and reported significantly higher Epworth Sleepiness scores. Nearly two-thirds of participants (61%) scored high burnout on the Maslach depersonalization subscore. Total steps per day and self-reported well-being, burnout, and job satisfaction were comparable between the groups. Conclusions: Despite a positive correlation between work-hours and sleepiness, burnout and well-being were similar among residents. Physical activity did not prevent burnout. These findings are relevant to work-hours policies.

scholarly journals Wearable Activity Trackers in the Management of Rheumatic Diseases: Where Are We in 2020?

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4797
Author(s):  
Thomas Davergne ◽  
Antsa Rakotozafiarison ◽  
Hervé Servy ◽  
Laure Gossec
Keyword(s):  
Physical Activity ◽  
Time Management ◽  
Automatic Monitoring ◽  
Great Accuracy ◽  
Self Monitoring ◽  
Activity Tracker ◽  
External Monitoring ◽  
Activity Trackers ◽  
Steps Per Day ◽  
Wearable Activity Trackers

In healthcare, physical activity can be monitored in two ways: self-monitoring by the patient himself or external monitoring by health professionals. Regarding self-monitoring, wearable activity trackers allow automated passive data collection that educate and motivate patients. Wearing an activity tracker can improve walking time by around 1500 steps per day. However, there are concerns about measurement accuracy (e.g., lack of a common validation protocol or measurement discrepancies between different devices). For external monitoring, many innovative electronic tools are currently used in rheumatology to help support physician time management, to reduce the burden on clinic time, and to prioritize patients who may need further attention. In inflammatory arthritis, such as rheumatoid arthritis, regular monitoring of patients to detect disease flares improves outcomes. In a pilot study applying machine learning to activity tracker steps, we showed that physical activity was strongly linked to disease flares and that patterns of physical activity could be used to predict flares with great accuracy, with a sensitivity and specificity above 95%. Thus, automatic monitoring of steps may lead to improved disease control through potential early identification of disease flares. However, activity trackers have some limitations when applied to rheumatic patients, such as tracker adherence, lack of clarity on long-term effectiveness, or the potential multiplicity of trackers.

scholarly journals The Acceptability, Feasibility and Effectiveness of Wearable Activity Trackers for Increasing Physical Activity in Children and Adolescents: A Systematic Review

2021 ◽  
Vol 18 (12) ◽  
pp. 6211
Author(s):  
Amy V. Creaser ◽  
Stacy A. Clemes ◽  
Silvia Costa ◽  
Jennifer Hall ◽  
Nicola D. Ridgers ◽  
...  
Keyword(s):  
Physical Activity ◽  
Systematic Review ◽  
Children And Adolescents ◽  
Behaviour Change Techniques ◽  
Physically Active ◽  
Self Monitoring ◽  
Start Date ◽  
Activity Trackers ◽  
Wearable Activity Trackers

Wearable activity trackers (wearables) embed numerous behaviour change techniques (BCTs) that have previously been shown to increase adult physical activity (PA). With few children and adolescents achieving PA guidelines, it is crucial to explore ways to increase their PA. This systematic review examined the acceptability, feasibility, and effectiveness of wearables and their potential mechanisms of action for increasing PA in 5 to 19-year-olds. A systematic search of six databases was conducted, including data from the start date of each database to December 2019 (PROSPERO registration: CRD42020164506). Thirty-three studies were included. Most studies (70%) included only adolescents (10 to 19 years). There was some—but largely mixed—evidence that wearables increase steps and moderate-to-vigorous-intensity PA and reduce sedentary behaviour. There were no apparent differences in effectiveness based on the number of BCTs used and between studies using a wearable alone or as part of a multi-component intervention. Qualitative findings suggested wearables increased motivation to be physically active via self-monitoring, goal setting, feedback, and competition. However, children and adolescents reported technical difficulties and a novelty effect when using wearables, which may impact wearables’ long-term use. More rigorous and long-term studies investigating the acceptability, feasibility, and effectiveness of wearables in 5 to 19-year-olds are warranted.

An Examination of the Activity Patterns of Elementary School Children

2002 ◽  
Vol 14 (4) ◽  
pp. 432-441 ◽  
Author(s):  
Susan D. Vincent ◽  
Robert P. Pangrazi
Keyword(s):  
Physical Activity ◽  
Activity Patterns ◽  
Individual Variability ◽  
Activity Levels ◽  
Same Sex ◽  
Factorial Anova ◽  
Step Counts ◽  
Meaningful Activity ◽  
Significant Difference ◽  
Steps Per Day

Research has suggested a trend of decreasing activity with age necessitating a renewed emphasis on promoting physical activity for children. The purpose of this study was to assess current physical activity levels of children and to establish initial standards for comparison in determining appropriate activity levels of children based on pedometer counts. Children, 6–12 years old (N = 711), wore sealed pedometers for 4 consecutive days. Mean step counts ranged from 10,479–11,274 and 12300–13989 for girls and boys respectively. Factorial ANOVA found a significant difference between sex (F = 90.16, p < .01) but not among age (F = 0.78, p = .587). Great individual variability existed among children of the same sex. Further analysis found significant differences among children of the same sex above the 80th percentile and below the 20th percentile. A reasonable activity standard might be approximately 11,000 and 13,000 steps per day for girls and boys respectively, although further discussion of this is warranted. The descriptive nature of this study provides insights into the activity patterns of children and the mean step counts for boys and girls at each age can serve as a preliminary guide for determining meaningful activity levels for children based on pedometer counts.

Who Uses Wearable Activity Trackers and Why? A Comparison of Former and Current Users in the United States

2020 ◽  
Vol 34 (7) ◽  
pp. 762-769
Author(s):  
Ciarán P. Friel ◽  
Carol Ewing Garber
Keyword(s):  
Physical Activity ◽  
Average Length ◽  
Physical Activity Behavior ◽  
The United States ◽  
Web Based ◽  
Shared Data ◽  
Activity Trackers ◽  
Wearable Activity Trackers ◽  
Average Current ◽  
Activity Behavior

Background: There has been an explosion in the use of wearable activity trackers (WATs), but we do not fully understand who wears them and why. This study’s purpose was to describe the characteristics of WAT users and to compare current and former users. Materials and Methods: A variety of internet-based resources (eg, Craigslist, Facebook) were used to recruit current and former WAT users. Respondents completed a web-based survey, where they provided information on sociodemographic characteristics, health, physical activity behavior, and about their WAT use. Results: Of the 2826 respondents who gave informed consent, 70.8% (n = 2002) met inclusion criteria for this analysis. Respondents ranged from 18 to 81 years old (mean 32.9 ± 12.2 standard deviation) with 73.8% women. Most were current WAT users (68.7%), and the average length of WAT use overall was 9.3 ± 9.7 months. On average, current users wore the device for 3.7 months longer than former users. Compared to current users, former users had a lower body mass index (1.2 kg/m2 less), reported fewer medical conditions, shared data from their device less often, and received the device as a gift more frequently. Conclusions: Current and former users varied in their reasons for using a WAT and how they used their device. Differences identified between these groups support further exploration of associations between WAT users’ profiles and their physical activity behavior.

Wearable sensors and Mobile Health (mHealth) technologies to assess and promote physical activity in stroke: a narrative review

2016 ◽  
Vol 17 (1) ◽  
pp. 34-42 ◽  
Author(s):  
Shamala Thilarajah ◽  
Ross A Clark ◽  
Gavin Williams
Keyword(s):  
Physical Activity ◽  
Behaviour Change ◽  
Mobile Health ◽  
Wearable Sensors ◽  
Chronic Illnesses ◽  
Behaviour Change Techniques ◽  
Health Issues ◽  
Activity Trackers ◽  
Wearable Activity Trackers ◽  
Smartphone Technology

Stroke is a leading cause of disability worldwide, with approximately one third of people left with permanent deficits impacting on their function. This may contribute to a physically inactive lifestyle and further associated health issues. Current research suggests that people after stroke are not meeting the recommended levels of physical activity, and are less active than people with other chronic illnesses. Thus, it is important to understand how to support people after stroke to uptake and maintain physical activity. Wearable sensors and mobile health (mHealth) technologies are a potential platform to measure and promote physical activity. Some of these technologies may incorporate behaviour change techniques such as real-time feedback. Although wearable activity trackers and smartphone technology are widely available, the feasibility and applicability of these technologies for people after stroke is unclear. This article reviews the devices available for assessment of physical activity in stroke and discusses the potential for advances in technology to promote physical activity in this population.

scholarly journals Comparison of the Physical Activity Measured by a Consumer Wearable Activity Tracker and That Measured by Self-Report: Cross-Sectional Analysis of the Health eHeart Study (Preprint)

2020 ◽  
Author(s):  
Alexander J Beagle ◽  
Geoffrey H Tison ◽  
Kirstin Aschbacher ◽  
Jeffrey E Olgin ◽  
Gregory M Marcus ◽  
...  
Keyword(s):  
Physical Activity ◽  
Self Report ◽  
Moderate Activity ◽  
Vigorous Activity ◽  
Cross Sectional ◽  
Active Time ◽  
Step Counts ◽  
Steps Per Day ◽  
Wearable Activity Trackers ◽  
Sectional Analysis

BACKGROUND Commercially acquired wearable activity trackers such as the Fitbit provide objective, accurate measurements of physically active time and step counts, but it is unclear whether these measurements are more clinically meaningful than self-reported physical activity. OBJECTIVE The aim of this study was to compare self-reported physical activity to Fitbit-measured step counts and then determine which is a stronger predictor of BMI by using data collected over the same period reflecting comparable physical activities. METHODS We performed a cross-sectional analysis of data collected by the Health eHeart Study, a large mobile health study of cardiovascular health and disease. Adults who linked commercially acquired Fitbits used in free-living conditions with the Health eHeart Study and completed an International Physical Activity Questionnaire (IPAQ) between 2013 and 2019 were enrolled (N=1498). Fitbit step counts were used to quantify time by activity intensity in a manner comparable to the IPAQ classifications of total active time and time spent being sedentary, walking, or doing moderate activities or vigorous activities. Fitbit steps per day were computed as a measure of the overall activity for exploratory comparisons with IPAQ-measured overall activity (metabolic equivalent of task [MET]-h/wk). Measurements of physical activity were directly compared by Spearman rank correlation. Strengths of associations with BMI for Fitbit versus IPAQ measurements were compared using multivariable robust regression in the subset of participants with BMI and covariates measured. RESULTS Correlations between synchronous paired measurements from Fitbits and the IPAQ ranged in strength from weak to moderate (0.09-0.48). In the subset with BMI and covariates measured (n=586), Fitbit-derived predictors were generally stronger predictors of BMI than self-reported predictors. For example, an additional hour of Fitbit-measured vigorous activity per week was associated with nearly a full point reduction in BMI (–0.84 kg/m<sup>2</sup>, 95% CI –1.35 to –0.32) in adjusted analyses, whereas the association between self-reported vigorous activity measured by IPAQ and BMI was substantially smaller in magnitude (–0.17 kg/m<sup>2</sup>, 95% CI –0.34 to –0.00; <i>P</i>&lt;.001 versus Fitbit) and was dominated by the Fitbit-derived predictor when compared head-to-head in a single adjusted multivariable model. Similar patterns of associations with BMI, with Fitbit dominating self-report, were seen for moderate activity and total active time and in comparisons between overall Fitbit steps per day and IPAQ MET-h/wk on standardized scales. CONCLUSIONS Fitbit-measured physical activity was more strongly associated with BMI than self-reported physical activity, particularly for moderate activity, vigorous activity, and summary measures of total activity. Consumer-marketed wearable activity trackers such as the Fitbit may be useful for measuring health-relevant physical activity in clinical practice and research.

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