Technologies that assess the location of physical activity and sedentary behavior: a systematic review

Background: The location in which physical activity and sedentary behavior are performed can provide valuable behavioral information, both in isolation and synergistically with other areas of physical activity and sedentary behavior research. Global positioning systems (GPS) have been used in physical activity research to identify outdoor location; however, while GPS can receive signals in certain indoor environments, it is not able to provide room- or subroom-level location. On average, adults spend a high proportion of their time indoors. A measure of indoor location would, therefore, provide valuable behavioral information. Objective: This systematic review sought to identify and critique technology which has been or could be used to assess the location of physical activity and sedentary behavior. Methods: To identify published research papers, four electronic databases were searched using key terms built around behavior, technology, and location. To be eligible for inclusion, papers were required to be published in English and describe a wearable or portable technology or device capable of measuring location. Searches were performed up to February 4, 2015. This was supplemented by backward and forward reference searching. In an attempt to include novel devices which may not yet have made their way into the published research, searches were also performed using three Internet search engines. Specialized software was used to download search results and thus mitigate the potential pitfalls of changing search algorithms. Results: A total of 188 research papers met the inclusion criteria. Global positioning systems were the most widely used location technology in the published research, followed by wearable cameras, and radio-frequency identification. Internet search engines identified 81 global positioning systems, 35 real-time locating systems, and 21 wearable cameras. Real-time locating systems determine the indoor location of a wearable tag via the known location of reference nodes. Although the type of reference node and location determination method varies between manufacturers, Wi-Fi appears to be the most popular method. Conclusions: The addition of location information to existing measures of physical activity and sedentary behavior will provide important behavioral information

Novel technology to help understand the context of physical activity and sedentary behaviour.

When used in large, national surveillance programmes, objective measurement tools provide prevalence estimates of low physical activity guideline compliance and high amounts of sedentary time. There are undoubtedly a plethora of reasons for this but one possible contributing factor is the current lack of behavioural context offered by accelerometers and posture sensors. Context includes information such as where the behaviour occurs, the type of activity being performed and is vital in allowing greater refinement of intervention strategies. Novel technologies are emerging with the potential to provide this information. Example data from three ongoing studies is used to illustrate the utility of these technologies. Study one assesses the concurrent validity of electrical energy monitoring and wearable cameras as measures of television viewing. This study found that on average the television is switched on for 202 min d(-1) but is visible in just 90 min of wearable camera images with a further 52 min where the participant is in their living room but the television is not visible in the image. Study two utilises indoor location monitoring to assess where older adult care home residents accumulate their sedentary time. This study found that residents were highly sedentary (sitting for an average of 720 min d(-1)) and spent the majority of their time in their own rooms with more time spent in communal areas in the morning than in the afternoon. Lastly, study three discusses the use of proximity sensors to quantify exposure to a height adjustable desk. These studies are example applications of this technology, with many other technologies available and applications possible. The adoption of these technologies will provide researchers with a more complete understanding of the behaviour than has previously been available

Using digital health technologies to understand the association between movement behaviors and interstitial glucose: Exploratory analysis

© Andrew P Kingsnorth, Maxine E Whelan, James P Sanders, Lauren B Sherar, Dale W Esliger. Background: Acute reductions in postprandial glucose excursions because of movement behaviors have been demonstrated in experimental studies but less so in free-living settings. Objective: The objective of this study was to explore the nature of the acute stimulus-response model between accelerometer-assessed physical activity, sedentary time, and glucose variability over 13 days in nondiabetic adults. Methods: This study measured physical activity, sedentary time, and interstitial glucose continuously over 13 days in 29 participants (mean age in years: 44.9 [SD 9.1]; female: 59%, 17/29; white: 90%, 26/29; mean body mass index: 25.3 [SD 4.1] ) as part of the Sensing Interstitial Glucose to Nudge Active Lifestyles (SIGNAL) research program. Daily minutes spent sedentary, in light activity, and moderate to vigorous physical activity were associated with daily mean glucose, SD of glucose, and mean amplitude of glycemic excursions (MAGE) using generalized estimating equations. Results: After adjustment for covariates, sedentary time in minutes was positively associated with a higher daily mean glucose (mmol/L; beta=0.0007; 95% CI 0.00030-0.00103; P < .001), SD of glucose (mmol/L; beta=0.0006; 95% CI 0.00037-0.00081; P < .001), and MAGE (mmol/L; beta=0.002; 95% CI 0.00131-0.00273; P < .001) for those of a lower fitness. Additionally, light activity was inversely associated with mean glucose (mmol/L; beta=−0.0004; 95% CI −0.00078 to −0.00006; P=.02), SD of glucose (mmol/L; beta=−0.0006; 95% CI −0.00085 to −0.00039; P < .001), and MAGE (mmol/L; beta=−0.002; 95% CI −0.00285 to −0.00146; P < .001) for those of a lower fitness. Moderate to vigorous physical activity was only inversely associated with mean glucose (mmol/L; beta=−0.002; 95% CI −0.00250 to −0.00058; P=.002). Conclusions: Evidence of an acute stimulus-response model was observed between sedentary time, physical activity, and glucose variability in low fitness individuals, with sedentary time and light activity conferring the most consistent changes in glucose variability. Further work is required to investigate the coupling of movement behaviors and glucose responses in larger samples and whether providing these rich data sources as feedback could induce lifestyle behavior change

Devices for self-monitoring sedentary time or physical activity: a scoping review.

It is well documented that meeting the guideline levels (150 minutes per week) of moderate-to-vigorous physical activity (PA) is protective against chronic disease. Conversely, emerging evidence indicates the deleterious effects of prolonged sitting. Therefore, there is a need to change both behaviors. Self-monitoring of behavior is one of the most robust behavior-change techniques available. The growing number of technologies in the consumer electronics sector provides a unique opportunity for individuals to self-monitor their behavior.The aim of this study is to review the characteristics and measurement properties of currently available self-monitoring devices for sedentary time and/or PA.To identify technologies, four scientific databases were systematically searched using key terms related to behavior, measurement, and population. Articles published through October 2015 were identified. To identify technologies from the consumer electronic sector, systematic searches of three Internet search engines were also performed through to October 1, 2015.The initial database searches identified 46 devices and the Internet search engines identified 100 devices yielding a total of 146 technologies. Of these, 64 were further removed because they were currently unavailable for purchase or there was no evidence that they were designed for, had been used in, or could readily be modified for self-monitoring purposes. The remaining 82 technologies were included in this review (73 devices self-monitored PA, 9 devices self-monitored sedentary time). Of the 82 devices included, this review identified no published articles in which these devices were used for the purpose of self-monitoring PA and/or sedentary behavior; however, a number of technologies were found via Internet searches that matched the criteria for self-monitoring and provided immediate feedback on PA (ActiGraph Link, Microsoft Band, and Garmin Vivofit) and sedentary time (activPAL VT, the Lumo Back, and Darma).There are a large number of devices that self-monitor PA; however, there is a greater need for the development of tools to self-monitor sedentary time. The novelty of these devices means they have yet to be used in behavior change interventions, although the growing field of wearable technology may facilitate this to change

Effectiveness of interventions to increase device-measured physical activity in pregnant women: systematic review and meta-analysis of randomised controlled trials

Background:  Interventions that provide pregnant women with opportunities to access and participate in physical activity have been shown to be beneficial to their health. Much of this evidence however has been based on self-reported physical activity data, which may be prone to inflated effects due to recall bias and social desirability bias. No previous synthesis of randomised controlled trials has assessed the effectiveness of these interventions using only device measured data, to assess their health benefits more accurately in pregnant women. This systematic review and meta-analysis aimed to address this evidence gap.  Data sources:  Cochrane Central Register of Controlled Trials, Medline, SportDiscus, APA PsycINFO, Embase and Web of Science databases were queried from inception up to December 2, 2021. An updated search of PubMed was conducted on May 16, 2022.  Study eligibility criteria:  Randomised controlled trials that recruited pregnant women, participating in any physical activity intervention (excluding interventions aimed entirely at body conditioning), compared with standard antenatal care (comparators), using device-measured total physical activity as an outcome were eligible for inclusion.  Methods:  3144 titles and abstracts were screened for eligibility, and 18 met the inclusion criteria. Data were analysed using random effect models, (standardised mean difference and mean difference), using data from baseline to last available follow-up (primary end point), and until between 24 to 30 weeks gestation. Gestational weight gain was also assessed at these timepoints in the included trials.  Results:  No significant differences between the groups were found for total physical activity at last available follow-up or 24 to 30 weeks gestation (95% CI 0.03 to 0.27, p = 0.10: 95% CI -0.05 to 0.33, p = 0.15) respectively. On average, pregnant women randomised to a physical activity intervention completed 435 and 449 more steps per day than comparators at last available follow-up and at 24 to 30 weeks gestation (95% CI -0.5-870.6, p = 0.05: 95% CI 5.5-892.7, p = 0.05) respectively. Intervention participants also gained 0.69 kg less (95% CI -1.30 to -0.08, p = 0.03) weight than comparators.  Conclusion:  Based on device-measured data, interventions to promote physical activity during pregnancy have small but important effects on increasing physical activity and managing excessive gestational weight gain.</p

‘Snacktivity™’ to increase physical activity: Time to try something different?

Evidence demonstrates that participation in regular physical activity (PA) reduces the risk of morbidity and mortality. However, current PA guidelines are focused on weekly accumulation of 150 min of moderate intensity PA as a threshold. Although recent developments of this guidance have discussed the merits of short bouts of physical activity, guidance that sets large behavioural goals for PA has not been successful in supporting the public to become sufficiently physically active and a ‘one-size fits all’ approach to PA guidelines may not be optimal. A complementary ‘whole day’ approach to PA promotion (i.e. incorporating PA throughout the day) that could motivate the population to be more physically active, is a concept we have called ‘Snacktivity™’. The Snacktivity™ approach promotes small or ‘bite’ size bouts (e.g. 2–5 min) of PA accumulated throughout the whole day. Snacktivity™ is consistent with the small change approach which suggest that behaviour change and habit formation are best achieved through gradual building of task self-efficacy, celebrating small successes. Snacktivity™ also offers opportunities to “piggyback” on to existing behaviours/habits, using them as prompts for Snacktivity™. Moreover, small behaviour changes are easier to initiate and maintain than larger ones. A plethora of evidence supports the hypothesis that Snacktivity may be a more acceptable and effective way to help the public reach, or exceed current PA guidelines. This paper outlines the evidence to support the Snacktivity™ approach and the mechanisms by which it may increase population levels of physical activity. Future research directions for Snacktivity™ are also outlined

Views of the public about Snacktivity™: a small changes approach to promoting physical activity and reducing sedentary behaviour

BackgroundMany people do not meet the recommended health guidance of participation in a minimum of 150–300 min of moderate intensity physical activity per week, often promoted as at least 30 min of physical activity on 5 days of the week. This is concerning and highlights the importance of finding innovative ways to help people to be physically active each day. Snacktivity™ is a novel approach that aims to encourage people to do small, 2–5 min bouts of physical activity ‘snacks’ throughout the whole day, such that they achieve at least 150 min of moderate intensity activity per week. However, before it can be recommended, there is a need to explore whether the concept is acceptable to the public.MethodsA survey to assess the views of the public about Snacktivity™ was distributed to adult patients registered at six general practices in the West Midlands, UK and to health care employees in the same region.ResultsA total of 5989 surveys were sent to patients, of which 558 were returned (9.3%). A further 166 surveys were completed by health care employees. A total of 85% of respondents liked the Snacktivity™ concept. The flexibility of the approach was highly rated. A high proportion of participants (61%) reported that the ability to self-monitor their behaviour would help them to do Snacktivity™ throughout their day. Physically inactive participants perceived that Snacktivity™ would help to increase their physical activity, more than those who were physically active (OR = 0.41, 95% CI: 0.25–0.67). Approximately 90% of respondents perceived that Snacktivity™ was easy to do on a non-working day compared to 60% on a working day. Aerobic activity ‘snacks’ were preferred to those which were strength based.ConclusionsThe Snacktivity™ approach to promoting physical activity was viewed positively by the public and interventions to test the merits of such an approach now need to be developed and tested in a variety of everyday contexts.</div