Dataset Information

Effect of wrist-worn activity monitor feedback on physical activity behavior: A randomized controlled trial in Finnish young men.

ABSTRACT: UNLABELLED:The purpose of this study is to evaluate whether the use of an activity monitor providing feedback has an effect on physical activity (PA) in young men. A population-based sample of 276 conscription-aged (mean = 17.9, SD = 0.7 years) men participated in a 3-month randomized controlled trial in Oulu in 2012. Participants were randomized to an intervention group (INT, N = 137) and a control group (CON, N = 139). INT received a wrist-worn monitor (Polar Active) showing daily activity, and CON received identical monitors without feedback. Main outcome was the change from baseline in objectively measured weekly time spent in moderate-to-vigorous PA (MVPA) and sedentary activity (SED), as assessed by generalized estimation equations (GEE). Other lifestyle factors were assessed by a questionnaire at baseline and at 3 months. Weekly physical activity data (? 4 days with ? 8 h each) were obtained from 72 (53%) and 90 (65%) men in the INT and CON, respectively. Based on GEE, time spent in MVPA increased (p = 0.012) and SED decreased (p = 0.032) in the INT compared with the CON. During the first 7 weeks, the INT spent on average 1 h less sedentary than the CON (t-test, p < 0.05). During the first week, the INT showed 12 minutes more MVPA compared to the CON (t-test, p = 0.034). Based on questionnaire data, the proportion of the most sedentary men decreased in the INT (Wilcoxon test, 28% vs. 10%, p = 0.029), with no change in the CON (20% vs. 19%, p = 0.546). To conclude, a wrist-worn activity monitor providing feedback had a short-term positive effect on PA and SED in young men. TRIAL REGISTRATION:This is a pilot study for a larger randomized controlled trial registered to the clinical trials register NCT01376986.

SUBMITTER: Jauho AM

PROVIDER: S-EPMC4721342 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Effect of wrist-worn activity monitor feedback on physical activity behavior: A randomized controlled trial in Finnish young men.

Jauho Anna-Maiju AM Pyky Riitta R Ahola Riikka R Kangas Maarit M Virtanen Paula P Korpelainen Raija R Jämsä Timo T

Preventive medicine reports 20150722

<h4>Unlabelled</h4>The purpose of this study is to evaluate whether the use of an activity monitor providing feedback has an effect on physical activity (PA) in young men. A population-based sample of 276 conscription-aged (mean = 17.9, SD = 0.7 years) men participated in a 3-month randomized controlled trial in Oulu in 2012. Participants were randomized to an intervention group (INT, N = 137) and a control group (CON, N = 139). INT received a wrist-worn monitor (Polar Active) showing daily acti ...[more]

PMID: 26844128

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Project description:BACKGROUND:Physical activity (PA) level is associated with multiple health benefits during early childhood. However, inconsistency in the methods for quantification of PA levels among preschoolers remains a problem. OBJECTIVE:This study aimed to develop PA intensity cut points for wrist-worn accelerometers by using machine learning (ML) approaches to assess PA in preschoolers. METHODS:Wrist- and hip-derived acceleration data were collected simultaneously from 34 preschoolers on 3 consecutive preschool days. Two supervised ML models, receiver operating characteristic curve (ROC) and ordinal logistic regression (OLR), and one unsupervised ML model, k-means cluster analysis, were applied to establish wrist-worn accelerometer vector magnitude (VM) cut points to classify accelerometer counts into sedentary behavior, light PA (LPA), moderate PA (MPA), and vigorous PA (VPA). Physical activity intensity levels identified by hip-worn accelerometer VM cut points were used as reference to train the supervised ML models. Vector magnitude counts were classified by intensity based on three newly established wrist methods and the hip reference to examine classification accuracy. Daily estimates of PA were compared to the hip-reference criterion. RESULTS:In total, 3600 epochs with matched hip- and wrist-worn accelerometer VM counts were analyzed. All ML approaches performed differently on developing PA intensity cut points for wrist-worn accelerometers. Among the three ML models, k-means cluster analysis derived the following cut points: ?2556 counts per minute (cpm) for sedentary behavior, 2557-7064 cpm for LPA, 7065-14532 cpm for MPA, and ?14533 cpm for VPA; in addition, k-means cluster analysis had the highest classification accuracy, with more than 70% of the total epochs being classified into the correct PA categories, as examined by the hip reference. Additionally, k-means cut points exhibited the most accurate estimates on sedentary behavior, LPA, and VPA as the hip reference. None of the three wrist methods were able to accurately assess MPA. CONCLUSIONS:This study demonstrates the potential of ML approaches in establishing cut points for wrist-worn accelerometers to assess PA in preschoolers. However, the findings from this study warrant additional validation studies.

Project description:BackgroundPhysical activity has not been objectively measured in prospective cohorts with sufficiently large numbers to reliably detect associations with multiple health outcomes. Technological advances now make this possible. We describe the methods used to collect and analyse accelerometer measured physical activity in over 100,000 participants of the UK Biobank study, and report variation by age, sex, day, time of day, and season.MethodsParticipants were approached by email to wear a wrist-worn accelerometer for seven days that was posted to them. Physical activity information was extracted from 100Hz raw triaxial acceleration data after calibration, removal of gravity and sensor noise, and identification of wear / non-wear episodes. We report age- and sex-specific wear-time compliance and accelerometer measured physical activity, overall and by hour-of-day, week-weekend day and season.Results103,712 datasets were received (44.8% response), with a median wear-time of 6.9 days (IQR:6.5-7.0). 96,600 participants (93.3%) provided valid data for physical activity analyses. Vector magnitude, a proxy for overall physical activity, was 7.5% (2.35mg) lower per decade of age (Cohen's d = 0.9). Women had a higher vector magnitude than men, apart from those aged 45-54yrs. There were major differences in vector magnitude by time of day (d = 0.66). Vector magnitude differences between week and weekend days (d = 0.12 for men, d = 0.09 for women) and between seasons (d = 0.27 for men, d = 0.15 for women) were small.ConclusionsIt is feasible to collect and analyse objective physical activity data in large studies. The summary measure of overall physical activity is lower in older participants and age-related differences in activity are most prominent in the afternoon and evening. This work lays the foundation for studies of physical activity and its health consequences. Our summary variables are part of the UK Biobank dataset and can be used by researchers as exposures, confounding factors or outcome variables in future analyses.

Project description:BackgroundNew fitness trackers and smartwatches are released to the consumer market every year. These devices are equipped with different sensors, algorithms, and accompanying mobile apps. With recent advances in mobile sensor technology, privately collected physical activity data can be used as an addition to existing methods for health data collection in research. Furthermore, data collected from these devices have possible applications in patient diagnostics and treatment. With an increasing number of diverse brands, there is a need for an overview of device sensor support, as well as device applicability in research projects.ObjectiveThe objective of this study was to examine the availability of wrist-worn fitness wearables and analyze availability of relevant fitness sensors from 2011 to 2017. Furthermore, the study was designed to assess brand usage in research projects, compare common brands in terms of developer access to collected health data, and features to consider when deciding which brand to use in future research.MethodsWe searched for devices and brand names in six wearable device databases. For each brand, we identified additional devices on official brand websites. The search was limited to wrist-worn fitness wearables with accelerometers, for which we mapped brand, release year, and supported sensors relevant for fitness tracking. In addition, we conducted a Medical Literature Analysis and Retrieval System Online (MEDLINE) and ClinicalTrials search to determine brand usage in research projects. Finally, we investigated developer accessibility to the health data collected by identified brands.ResultsWe identified 423 unique devices from 132 different brands. Forty-seven percent of brands released only one device. Introduction of new brands peaked in 2014, and the highest number of new devices was introduced in 2015. Sensor support increased every year, and in addition to the accelerometer, a photoplethysmograph, for estimating heart rate, was the most common sensor. Out of the brands currently available, the five most often used in research projects are Fitbit, Garmin, Misfit, Apple, and Polar. Fitbit is used in twice as many validation studies as any other brands and is registered in ClinicalTrials studies 10 times as often as other brands.ConclusionsThe wearable landscape is in constant change. New devices and brands are released every year, promising improved measurements and user experience. At the same time, other brands disappear from the consumer market for various reasons. Advances in device quality offer new opportunities for research. However, only a few well-established brands are frequently used in research projects, and even less are thoroughly validated.

Dataset Information

Effect of wrist-worn activity monitor feedback on physical activity behavior: A randomized controlled trial in Finnish young men.

Publications

Effect of wrist-worn activity monitor feedback on physical activity behavior: A randomized controlled trial in Finnish young men.

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