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      Users’ experiences of wearable activity trackers: a cross-sectional study

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          Abstract

          Background

          Wearable activity trackers offer considerable promise for helping users to adopt healthier lifestyles. This study aimed to explore users’ experience of activity trackers, including usage patterns, sharing of data to social media, perceived behaviour change (physical activity, diet and sleep), and technical issues/barriers to use.

          Methods

          A cross-sectional online survey was developed and administered to Australian adults who were current or former activity tracker users. Results were analysed descriptively, with differences between current and former users and wearable brands explored using independent samples t-tests, Mann-Whitney, and chi square tests.

          Results

          Participants included 200 current and 37 former activity tracker users (total N = 237) with a mean age of 33.1 years (SD 12.4, range 18–74 years). Fitbit (67.5%) and Garmin devices (16.5%) were most commonly reported. Participants typically used their trackers for sustained periods (5–7 months) and most intended to continue usage. Participants reported they had improved their physical activity (51–81%) more commonly than they had their diet (14–40%) or sleep (11–24%), and slightly more participants reported to value the real time feedback (89%) compared to the long-term monitoring (78%). Most users (70%) reported they had experienced functionality issues with their devices, most commonly related to battery life and technical difficulties.

          Conclusions

          Results suggest users find activity trackers appealing and useful tools for increasing perceived physical activity levels over a sustained period.

          Electronic supplementary material

          The online version of this article (10.1186/s12889-017-4888-1) contains supplementary material, which is available to authorized users.

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          Most cited references17

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          Effect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy.

          Strong evidence shows that physical inactivity increases the risk of many adverse health conditions, including major non-communicable diseases such as coronary heart disease, type 2 diabetes, and breast and colon cancers, and shortens life expectancy. Because much of the world's population is inactive, this link presents a major public health issue. We aimed to quantify the eff ect of physical inactivity on these major non-communicable diseases by estimating how much disease could be averted if inactive people were to become active and to estimate gain in life expectancy at the population level. For our analysis of burden of disease, we calculated population attributable fractions (PAFs) associated with physical inactivity using conservative assumptions for each of the major non-communicable diseases, by country, to estimate how much disease could be averted if physical inactivity were eliminated. We used life-table analysis to estimate gains in life expectancy of the population. Worldwide, we estimate that physical inactivity causes 6% (ranging from 3·2% in southeast Asia to 7·8% in the eastern Mediterranean region) of the burden of disease from coronary heart disease, 7% (3·9-9·6) of type 2 diabetes, 10% (5·6-14·1) of breast cancer, and 10% (5·7-13·8) of colon cancer. Inactivity causes 9% (range 5·1-12·5) of premature mortality, or more than 5·3 million of the 57 million deaths that occurred worldwide in 2008. If inactivity were not eliminated, but decreased instead by 10% or 25%, more than 533 000 and more than 1·3 million deaths, respectively, could be averted every year. We estimated that elimination of physical inactivity would increase the life expectancy of the world's population by 0·68 (range 0·41-0·95) years. Physical inactivity has a major health eff ect worldwide. Decrease in or removal of this unhealthy behaviour could improve health substantially. None.
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            Restricted and disrupted sleep: effects on autonomic function, neuroendocrine stress systems and stress responsivity.

            Frequently disrupted and restricted sleep is a common problem for many people in our modern around-the-clock society. In this context, it is an important question how sleep loss affects the stress systems in our bodies since these systems enable us to deal with everyday challenges. Altered activity and reactivity of these systems following insufficient sleep might have serious repercussions for health and well-being. Studies on both humans and rodents have shown that sleep deprivation and sleep restriction are conditions often associated with mild, temporary increases in the activity of the major neuroendocrine stress systems, i.e., the autonomic sympatho-adrenal system and the hypothalamic-pituitary-adrenal axis. Sleep deprivation may not only have a direct activating effect by itself but, in the long run, it may also affect the reactivity of these systems to other stressors and challenges. Although the first signs of alterations in the way people deal with challenges under conditions of restricted sleep appear to be on the level of emotional perception, chronic sleep restriction may ultimately change the fundamental properties of neuroendocrine stress systems as well. Understandably, few controlled studies in humans have been devoted to this topic. Yet, experimental studies in rodents show that chronic sleep restriction may gradually alter neuroendocrine stress responses as well as the central mechanisms involved in the regulation of these responses. Importantly, the available data from studies in laboratory animals suggest that sleep restriction may gradually change certain brain systems and neuroendocrine systems in a manner that is similar to what is seen in stress-related disorders such as depression (e.g., reduced serotonin receptor sensitivity and altered regulation of the hypothalamic-pituitary-adrenal axis). Such data support the view that insufficient sleep, by acting on stress systems, may sensitize individuals to stress-related disorders. Indeed, epidemiological studies suggest that sleep complaints and sleep restriction may be important risk factors for a variety of diseases that are often linked to stress, including cardiovascular diseases and mood disorders.
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              Systematic review of the validity and reliability of consumer-wearable activity trackers

              Background Consumer-wearable activity trackers are electronic devices used for monitoring fitness- and other health-related metrics. The purpose of this systematic review was to summarize the evidence for validity and reliability of popular consumer-wearable activity trackers (Fitbit and Jawbone) and their ability to estimate steps, distance, physical activity, energy expenditure, and sleep. Methods Searches included only full-length English language studies published in PubMed, Embase, SPORTDiscus, and Google Scholar through July 31, 2015. Two people reviewed and abstracted each included study. Results In total, 22 studies were included in the review (20 on adults, 2 on youth). For laboratory-based studies using step counting or accelerometer steps, the correlation with tracker-assessed steps was high for both Fitbit and Jawbone (Pearson or intraclass correlation coefficients (CC) > =0.80). Only one study assessed distance for the Fitbit, finding an over-estimate at slower speeds and under-estimate at faster speeds. Two field-based studies compared accelerometry-assessed physical activity to the trackers, with one study finding higher correlation (Spearman CC 0.86, Fitbit) while another study found a wide range in correlation (intraclass CC 0.36–0.70, Fitbit and Jawbone). Using several different comparison measures (indirect and direct calorimetry, accelerometry, self-report), energy expenditure was more often under-estimated by either tracker. Total sleep time and sleep efficiency were over-estimated and wake after sleep onset was under-estimated comparing metrics from polysomnography to either tracker using a normal mode setting. No studies of intradevice reliability were found. Interdevice reliability was reported on seven studies using the Fitbit, but none for the Jawbone. Walking- and running-based Fitbit trials indicated consistently high interdevice reliability for steps (Pearson and intraclass CC 0.76–1.00), distance (intraclass CC 0.90–0.99), and energy expenditure (Pearson and intraclass CC 0.71–0.97). When wearing two Fitbits while sleeping, consistency between the devices was high. Conclusion This systematic review indicated higher validity of steps, few studies on distance and physical activity, and lower validity for energy expenditure and sleep. The evidence reviewed indicated high interdevice reliability for steps, distance, energy expenditure, and sleep for certain Fitbit models. As new activity trackers and features are introduced to the market, documentation of the measurement properties can guide their use in research settings. Electronic supplementary material The online version of this article (doi:10.1186/s12966-015-0314-1) contains supplementary material, which is available to authorized users.
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                Author and article information

                Contributors
                carol.maher@unisa.edu.au
                jillian.ryan@unisa.edu.au
                christina.ambrosi@mymail.unisa.edu.au
                sarah.edney@unisa.edu.au
                Journal
                BMC Public Health
                BMC Public Health
                BMC Public Health
                BioMed Central (London )
                1471-2458
                15 November 2017
                15 November 2017
                2017
                : 17
                : 880
                Affiliations
                ISNI 0000 0000 8994 5086, GRID grid.1026.5, Alliance for Research in Exercise, Nutrition and Activity (ARENA), School of Health Sciences & Sansom Institute for Health Research, , University of South Australia, ; GPO Box 2471, Adelaide, South Australia 5001 Australia
                Article
                4888
                10.1186/s12889-017-4888-1
                5688726
                29141607
                e90b832b-738d-4bdb-a808-03e0703af765
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 5 March 2017
                : 6 November 2017
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2017

                Public health
                fitness,health behaviour,measurement,motion sensors,pedometry,physical activity assessment

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