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Presented as a six-course meal, this article addresses the ethics of innovations, interruptions, and intrusions in physical education (PE). The central ingredient in this meal is Michel Serres' character-concept of the parasite. We begin by interpreting debates about PE's purposes, futures, beneficiaries, and so on, as offering researchers and practitioners food-for-thought about the status quo in PE and its transformation. We then introduce the tastes and textures of the parasite and explore these flavours further using PE research on outsourcing and the use of healthy lifestyle technologies. In the main course, we propose a situated and symbiotic parasitic ethics grounded in hesitation and discuss what this set of sensitivities offers debates in PE about outsourcing and healthy lifestyle technology-use. Recognising there will never be a PE without parasites, we advocate an attunement to what it is to parasite well in PE and to the role of the parasite in the composition of any PE collective. [ABSTRACT FROM AUTHOR]

Abstract Background Physical inactivity is considered one of the main modifiable risk factors for noncommunicable diseases. It has been proven that an active lifestyle is an efficient means of preventing and managing noncommunicable diseases. Multiple barriers have been identified that hinder engagement in conventional physical activity programs and the achievement of physical activity recommendations. Digital interventions may expand opportunities to resolve these barriers and empower people with noncommunicable diseases to be physically active. This overview of systematic reviews aims to evaluate the efficacy of digital interventions on physical activity promotion among individuals with major noncommunicable diseases. Method A protocol was registered in the PROSPERO database (CRD42022364350). A qualitative synthesis method was applied to summarize the efficacy data. The assessment of methodological quality using AMSTAR-2 for each systematic review was performed by two independent reviewers. Results Searches in nine databases resulted in seven systematic reviews for inclusion. Most of the primary studies included in these seven reviews were conducted in high-income countries. The reviews addressed five populations: participants with cancers, cardiovascular diseases, chronic obstructive pulmonary disease, type 2 diabetes, and osteoarthritis. Digital interventions were classified into two categories: interventions based on digital activity trackers and remote interventions via digital facilities. Additional components were identified in both categories of interventions such as motivational content, counseling, goal setting, tailored feedback/reminders, and other behavioral change techniques. The overall quality of the reviews ranged from critically low to low. The findings provided some evidence that both categories of interventions were effective in promoting physical activity. Conclusion The findings of this overview suggest that some types of digital interventions, such as self-monitoring with digital activity trackers and remote interventions via digital facilities, may be effective means of promoting physical activity across major noncommunicable diseases. The findings should be interpreted cautiously since the methodological quality of the included reviews ranged from critically low to low, and there was no consistent assessment of the certainty of evidence. Further systematic reviews are required on efficacy of digital interventions with more rigorous conducting and reporting of systematic review methodologies.

Wearable health technologies are designed to improve a user's self-awareness of their state of health and increase motivation and physical activity, but there is limited understanding of the psychological and behavioral impact these devices have. The present research attempts to further clarify the influence of individual characteristics on the cognitive, affective, and behavioral outcomes of activity tracker usage, including the development of dependency. A cross-sectional study of 212 college students who used activity trackers was conducted to evaluate the psychological and behavioral impact of activity tracker usage and users' affective response to their device. Participants expressed more positive affect while wearing their device as opposed to when they were unable to wear it. Female participants exhibited more positive affect than male participants while wearing their device but less when unable to wear it. Only 9% of the sample reported a dependency effect. The dependency effect was negatively associated with intrinsic motivation to be physically active, motivation by the idea of success, and the personality traits of agreeableness and conscientiousness. The dependency effect was positively associated with extrinsic motivation for physical activity and tracker usage, as well as need for cognitive closure. This research elucidates the unintended outcomes of activity tracker usage along with the individual characteristics that present as predictors of these outcomes. [ABSTRACT FROM AUTHOR]

Background: Physical inactivity is considered one of the main modifiable risk factors for noncommunicable diseases. It has been proven that an active lifestyle is an efficient means of preventing and managing noncommunicable diseases. Multiple barriers have been identified that hinder engagement in conventional physical activity programs and the achievement of physical activity recommendations. Digital interventions may expand opportunities to resolve these barriers and empower people with noncommunicable diseases to be physically active. This overview of systematic reviews aims to evaluate the efficacy of digital interventions on physical activity promotion among individuals with major noncommunicable diseases. Method: A protocol was registered in the PROSPERO database (CRD42022364350). A qualitative synthesis method was applied to summarize the efficacy data. The assessment of methodological quality using AMSTAR-2 for each systematic review was performed by two independent reviewers. Results: Searches in nine databases resulted in seven systematic reviews for inclusion. Most of the primary studies included in these seven reviews were conducted in high-income countries. The reviews addressed five populations: participants with cancers, cardiovascular diseases, chronic obstructive pulmonary disease, type 2 diabetes, and osteoarthritis. Digital interventions were classified into two categories: interventions based on digital activity trackers and remote interventions via digital facilities. Additional components were identified in both categories of interventions such as motivational content, counseling, goal setting, tailored feedback/reminders, and other behavioral change techniques. The overall quality of the reviews ranged from critically low to low. The findings provided some evidence that both categories of interventions were effective in promoting physical activity. Conclusion: The findings of this overview suggest that some types of digital interventions, such as self-monitoring with digital activity trackers and remote interventions via digital facilities, may be effective means of promoting physical activity across major noncommunicable diseases. The findings should be interpreted cautiously since the methodological quality of the included reviews ranged from critically low to low, and there was no consistent assessment of the certainty of evidence. Further systematic reviews are required on efficacy of digital interventions with more rigorous conducting and reporting of systematic review methodologies. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to assess patients' interest in education content delivered through electronic modalities and identify trends in internet access and use among emergency department patients of various socioeconomic statuses. Methods: A prospective, cross-sectional survey with 50 questions was completed by 241 English and Spanish-speaking patients in 2014 and repeated with 253 participants in 2019 at the University of California, Irvine Medical Center's Emergency Department (UCIMCED). Results: Internet access increased from 83.8 % in 2014 to 88.1 % in 2019. Most internet-using patients owned smartphones (80.1 % in 2014, 89.7 % in 2019). Patients used electronic devices, such as fit bits and activity trackers, to obtain health information. Email was the preferred method for receiving discharge instructions. Conclusions: As of 2019, 88.1 % of UCIMCED patients have access to the internet or email, making electronic media a reasonable venue for patient education. Given that we have a predominantly low-income patient population—61 % and 32 % of respondents in 2014 and 2019, respectively, reporting an income of less than $25,000—these results are provide new avenues to reach patients of all socioeconomic statuses. Innovation: The implications of this study can be used to develop electronic resources tailored to educate emergency department patients about their healthcare beyond the confines of a hospital.

Background: The field of smart devices and physical activity is evolving rapidly, with a wide range of devices measuring a wide range of parameters. Scientific articles look at very different populations in terms of the impact of smart devices but do not take into account which characteristics of the devices are important for the group and which may influence the effectiveness of the device. In our study, we aimed to analyse articles about the impact of smart devices on physical activity and identify the characteristics of different target groups. Methods: Queries were run on two major databases (PubMed and Web of Science) between 2017 and 2024. Duplicates were filtered out, and according to a few main criteria, inappropriate studies were excluded so that 37 relevant articles were included in a more detailed analysis. Results: Four main target groups were identified: healthy individuals, people with chronic diseases, elderly people, and competitive athletes. We identified the essential attributes of smart devices by target groups. For the elderly, an easy-to-use application is needed. In the case of women, children, and elderly people, gamification can be used well, but for athletes, specific measurement tools and accuracy may have paramount importance. For most groups, regular text messages or notifications are important. Conclusions: The use of smart devices can have a positive impact on physical activity, but the context and target group must be taken into account to achieve effectiveness. [ABSTRACT FROM AUTHOR]

Background: Data loss in wearable sensors is an inevitable problem that leads to misrepresentation during diabetes health monitoring. We systematically investigated missing wearable sensors data to get causal insight into the mechanisms leading to missing data. Methods: Two-week-long data from a continuous glucose monitor and a Fitbit activity tracker recording heart rate (HR) and step count in free-living patients with type 2 diabetes mellitus were used. The gap size distribution was fitted with a Planck distribution to test for missing not at random (MNAR) and a difference between distributions was tested with a Chi-squared test. Significant missing data dispersion over time was tested with the Kruskal–Wallis test and Dunn post hoc analysis. Results: Data from 77 subjects resulted in 73 cleaned glucose, 70 HR and 68 step count recordings. The glucose gap sizes followed a Planck distribution. HR and step count gap frequency differed significantly (p < 0.001), and the missing data were therefore MNAR. In glucose, more missing data were found in the night (23:00–01:00), and in step count, more at measurement days 6 and 7 (p < 0.001). In both cases, missing data were caused by insufficient frequency of data synchronization. Conclusions: Our novel approach of investigating missing data statistics revealed the mechanisms for missing data in Fitbit and CGM data. [ABSTRACT FROM AUTHOR]

Abstract Background Thyroid cancer (TC) patients are understudied but appear to be at risk for poor physical and psychosocial outcomes. Knowledge of the course and determinants of these deteriorated outcomes is lacking. Furthermore, little is known about mediating biological mechanisms. Objectives The WaTCh-study aims to; 1. Examine the course of physical and psychosocial outcomes. 2. Examine the association of demographic, environmental, clinical, physiological, and personality characteristics to those outcomes. In other words, who is at risk? 3. Reveal the association of mediating biological mechanisms (inflammation, kynurenine pathway) with poor physical and psychological outcomes. In other words, why is a person at risk? Design and methods Newly diagnosed TC patients from 13 Dutch hospitals will be invited. Data collection will take place before treatment, and at 6, 12 and 24 months after diagnosis. Sociodemographic and clinical information is available from the Netherlands Cancer Registry. Patients fill-out validated questionnaires at each time-point to assess quality of life, TC-specific symptoms, physical activity, anxiety, depression, health care use, and employment. Patients are asked to donate blood three times to assess inflammation and kynurenine pathway. Optionally, at each occasion, patients can use a weighing scale with bioelectrical impedance analysis (BIA) system to assess body composition; can register food intake using an online food diary; and can wear an activity tracker to assess physical activity and sleep duration/quality. Representative Dutch normative data on the studied physical and psychosocial outcomes is already available. Impact WaTCh will reveal the course of physical and psychosocial outcomes among TC patients over time and answers the question who is at risk for poor outcomes, and why. This knowledge can be used to provide personalized information, to improve screening, to develop and provide tailored treatment strategies and supportive care, to optimize outcomes, and ultimately increase the number of TC survivors that live in good health.

Background: The field of smart devices and physical activity is evolving rapidly, with a wide range of devices measuring a wide range of parameters. Scientific articles look at very different populations in terms of the impact of smart devices but do not take into account which characteristics of the devices are important for the group and which may influence the effectiveness of the device. In our study, we aimed to analyse articles about the impact of smart devices on physical activity and identify the characteristics of different target groups. Methods: Queries were run on two major databases (PubMed and Web of Science) between 2017 and 2024. Duplicates were filtered out, and according to a few main criteria, inappropriate studies were excluded so that 37 relevant articles were included in a more detailed analysis. Results: Four main target groups were identified: healthy individuals, people with chronic diseases, elderly people, and competitive athletes. We identified the essential attributes of smart devices by target groups. For the elderly, an easy-to-use application is needed. In the case of women, children, and elderly people, gamification can be used well, but for athletes, specific measurement tools and accuracy may have paramount importance. For most groups, regular text messages or notifications are important. Conclusions: The use of smart devices can have a positive impact on physical activity, but the context and target group must be taken into account to achieve effectiveness.

Background: Thyroid cancer (TC) patients are understudied but appear to be at risk for poor physical and psychosocial outcomes. Knowledge of the course and determinants of these deteriorated outcomes is lacking. Furthermore, little is known about mediating biological mechanisms. Objectives: The WaTCh-study aims to; Examine the course of physical and psychosocial outcomes. Examine the association of demographic, environmental, clinical, physiological, and personality characteristics to those outcomes. In other words, who is at risk? Reveal the association of mediating biological mechanisms (inflammation, kynurenine pathway) with poor physical and psychological outcomes. In other words, why is a person at risk? Design and methods: Newly diagnosed TC patients from 13 Dutch hospitals will be invited. Data collection will take place before treatment, and at 6, 12 and 24 months after diagnosis. Sociodemographic and clinical information is available from the Netherlands Cancer Registry. Patients fill-out validated questionnaires at each time-point to assess quality of life, TC-specific symptoms, physical activity, anxiety, depression, health care use, and employment. Patients are asked to donate blood three times to assess inflammation and kynurenine pathway. Optionally, at each occasion, patients can use a weighing scale with bioelectrical impedance analysis (BIA) system to assess body composition; can register food intake using an online food diary; and can wear an activity tracker to assess physical activity and sleep duration/quality. Representative Dutch normative data on the studied physical and psychosocial outcomes is already available. Impact: WaTCh will reveal the course of physical and psychosocial outcomes among TC patients over time and answers the question who is at risk for poor outcomes, and why. This knowledge can be used to provide personalized information, to improve screening, to develop and provide tailored treatment strategies and supportive care, to optimize outcomes, and ultimately increase the number of TC survivors that live in good health. [ABSTRACT FROM AUTHOR]

Abstract Background Preliminary evidence suggests that web-based physical activity interventions with tailored advice and Fitbit integration are effective and may be well suited to older adults. Therefore, this study aimed to examine the engagement, acceptability, usability, and satisfaction with ‘Active for Life,’ a web-based physical activity intervention providing computer-tailored physical activity advice to older adults. Methods Inactive older adults (n = 243) were randomly assigned into 3 groups: 1) tailoring + Fitbit, 2) tailoring only, or 3) a wait-list control. The tailoring + Fitbit group and the tailoring-only group received 6 modules of computer-tailored physical activity advice over 12 weeks. The advice was informed by objective Fitbit data in the tailoring + Fitbit group and self-reported physical activity in the tailoring-only group. This study examined the engagement, acceptability, usability, and satisfaction of Active for Life in intervention participants (tailoring + Fitbit n = 78, tailoring only n = 96). Wait-list participants were not included. Engagement (Module completion, time on site) were objectively recorded through the intervention website. Acceptability (7-point Likert scale), usability (System Usability Scale), and satisfaction (open-ended questions) were assessed using an online survey at post intervention. ANOVA and Chi square analyses were conducted to compare outcomes between intervention groups and content analysis was used to analyse program satisfaction. Results At post-intervention (week 12), study attrition was 28% (22/78) in the Fitbit + tailoring group and 39% (37/96) in the tailoring-only group. Engagement and acceptability were good in both groups, however there were no group differences (module completions: tailoring + Fitbit: 4.72 ± 2.04, Tailoring-only: 4.23 ± 2.25 out of 6 modules, p = .14, time on site: tailoring + Fitbit: 103.46 ± 70.63, Tailoring-only: 96.90 ± 76.37 min in total, p = .56, and acceptability of the advice: tailoring + Fitbit: 5.62 ± 0.89, Tailoring-only: 5.75 ± 0.75 out of 7, p = .41). Intervention usability was modest but significantly higher in the tailoring + Fitbit group (tailoring + Fitbit: 64.55 ± 13.59, Tailoring-only: 57.04 ± 2.58 out of 100, p = .003). Participants reported that Active for Life helped motivate them, held them accountable, improved their awareness of how active they were and helped them to become more active. Conversely, many participants felt as though they would prefer personal contact, more detailed tailoring and more survey response options. Conclusions This study supports web-based physical activity interventions with computer-tailored advice and Fitbit integration as engaging and acceptable in older adults. Trial registration Australian and New Zealand Clinical Trials Registry: ACTRN12618000646246. Registered April 23 2018, https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=374901

Non-exercise physical activity (NEPA), also called unstructured or informal physical activity, refers to those daily activities that require movement of the human body without planning or strict control of the physical effort made. Due to new technologies and motorized transportation devices, the general population has significantly decreased its NEPA. This increase in sedentary lifestyles, physical inactivity, and excessive energy intake is considered a risk factor for obesity, non-communicable diseases (NCDs), and all-cause mortality. Searching in PubMed/MEDLINE and Web of Science databases, a narrative review of NEPA was carried out to address its conceptualization, promotion strategies for the general population, and monitoring through wearable devices. It is strongly recommended that governmental entities, health practitioners, and the construction industry adhere to "The Global Action Plan on Physical Activity 2018–2030: More Active People for a Healthier World" and implement different salutogenic urban strategies. These strategies aim to generate environments that motivate increases in NEPA, such as cycling and walking transportation (between 5000–12,500 steps per day), and the progression to physical exercise. There is a wide variety of electronic devices for personal use, such as accelerometers, smartphone apps, or "smart clothes", that allow for the monitoring of NEPA, some with a wide range of analysis variables contributing to the estimation of total daily energy expenditure and the promotion of healthy habits. In general, the further promotion and monitoring of NEPA is required as part of a strategy to promote healthy habits sustainable over time for the prevention and control of obesity and NCDs. [ABSTRACT FROM AUTHOR]

Means of steps/day and time spent in MVPA/day for ActiGraph and Garmin devices and ActiGraph and Fitbit devices are presented in Table 1. Keywords: accelerometers; activity trackers; physical activity; wearables; young people with haemophilia EN accelerometers activity trackers physical activity wearables young people with haemophilia 942 945 4 05/19/23 20230501 NES 230501 Dear Editor The health benefits of physical activity (PA) are well documented including contributing to the prevention of certain non-communicable diseases. 1 TABLE Mean and standard deviation for steps and MVPA minutes for Garmin and ActiGraph devices and Fitbit and ActiGraph devices. [Extracted from the article]

Many existing sedentary behavior and physical activity studies focus on primary outcomes that assess change by comparing participants' activity from baseline to post-intervention. With the widespread availability of consumer-grade devices that track activity daily, researchers do not need to rely on those endpoint measurements alone. Using activity trackers, researchers can collect remote data about the process of behavior change and future maintenance of the change by measuring participants’ intra-individual physical activity variability. Measuring intra-individual physical activity variability can enable researchers to create tailored and dynamic interventions that account for different physical activity behavior change trajectories, and by that, improve participants' program adherence, enhance intervention design and management, and advance interventions measurements' reliability. We propose an application of intra-individual physical activity variability as a measurement and provide three use cases within interventions. Intra-individual physical activity variability can be used: prior to the intervention period, where relationships between participants' intra-individual physical activity variability and individual characteristics can be used to predict adherence and subsequently tailor interventions; during the intervention period, to assess progress and subsequently boost interventions; and after the intervention, to obtain a reliable representation of the change in primary outcome.

BackgroundMany individuals with intellectual disability (ID) have a sedentary lifestyle. Few interventions aimed at increasing their level of physical activity (PA) have shown lasting effects.AimTo assess the feasibility and acceptability of a pilot intervention study using innovative mobile health (mHealth) support systems to encourage PA in individuals with ID.MethodsNine individuals with ID and a low level of PA, aged 16–36 years, were included in the present convergent triangulation mixed method design. Two mHealth support systems (apps) were developed and tested. PA was measured with a Fitbit smartwatch, accelerometer, the International Physical Activity Questionnaire—Short Form (IPAQ-S), and Goal attainment scaling. Data were collected through online pre-, mid- (4 weeks), and post-intervention (12 weeks) questionnaires and activity trackers. Semi-structured qualitative interviews with participants and/or a family or staff member were held after the 12-week follow-up. Data were analyzed using conventional nonparametric statistics and thematic analyses.ResultsThe response rate and retention to the trial were 16% and 100%, respectively. Data quality was high, except for missing data from Fitbit activity trackers of approximately 30% from the 4- and 12-week follow-up stages. The feasibility challenges with activity trackers include rashes, size, non-acceptance, and loss of motivation. Participants and family members/staff reported interest in the study theme and were pleased with the data collection method. All but one participant achieved their PA goals. Most participants reported being satisfied with the apps as they were enjoyable or provided a reminder for performing physical and other activities. Social support for PA among family members also increased. However, app support from staff and family members was needed, and apps were not used regularly. Two of nine participants (22%) had increased their PA measured as steps per day with Fitbit at the 12-week follow-up.ConclusionsThe acceptability and feasibility of using tailored mobile applications in natural settings to increase PA among adults with ID are promising. This study aligns with previous studies in showing the challenges to increasing PA, which requires the inclusion of family members, staff, and stakeholders. The intervention requires modifications before a randomized controlled trial can be conducted.

Purpose: Activity trackers are useful tools for physical activity promotion in adolescents, but robust validity evaluations have not been done under free-living conditions. This study evaluated the validity of the Garmin Vívofit 1 (G1) and Garmin Vívofit 3 (G3) in different settings and contexts. Methods: The participants (girls: 52%, age: 15.9 [1.9] y) wore the G1 and G3 on their nondominant wrist and the Yamax pedometer on their right hip for a period of 1 week. Validity was examined in 4 discrete segments (before school, in school, after school, and whole day). The criterion method was the Yamax pedometer. Results: Both the G1 and G3 could be considered equivalent to the Yamax pedometer regarding the before school, in school, and whole day segments. The G1 showed wider limits of agreement than G3. Conclusions: The G1 and G3 trackers exhibited acceptable validity for 3 of the 4 segments (before school, in school, and whole day measurements). The results were less accurate during the after-school segment. The evidence that the validity of the monitors varied depending on the setting and context is an important consideration for research on adolescent activity patterns. [ABSTRACT FROM AUTHOR]

The article focuses on the challenges and opportunities associated with integrating wearable activity trackers (WATs) into cardiovascular care, including the need for better understanding of WATs' acceptability and the concept of care ecosystems emphasizing complexity and stewardship.

Wearable technologies are increasing both in number and variety enabling new ways for collecting personal data, as well as novel interaction modalities. Even though the Human-Computer Interaction (HCI) community has widely explored the potential applications of wearables, its theoretical contribution on this research field has been far from impressive. Most scholars and designers seem to rely on a series of dominant assumptions that look at wearables "from the outside" by focusing on their "external properties." When these assumptions are fully embraced at design-time, however, they may cloud opportunities for designing for the "internal aspects" of our everyday experience. In this article, I propose a theory that looks at wearables "from the inside,"giving a theoretical backdrop to all those wearable designs that pay attention to the internal aspects of interaction. By adopting a postphenomenological approach, I conceptualize wearable devices as "extensions" of our intentionality and introduce the "extension relation" to explain how wearables may alter how we relate to the world. In doing so, I propose a series of design considerations that aim to trace future research lines for all those wearables that are currently designed from an "externalistic" perspective. [ABSTRACT FROM AUTHOR]

Background: Preliminary evidence suggests that web-based physical activity interventions with tailored advice and Fitbit integration are effective and may be well suited to older adults. Therefore, this study aimed to examine the engagement, acceptability, usability, and satisfaction with ‘Active for Life,’ a web-based physical activity intervention providing computer-tailored physical activity advice to older adults. Methods: Inactive older adults (n = 243) were randomly assigned into 3 groups: 1) tailoring + Fitbit, 2) tailoring only, or 3) a wait-list control. The tailoring + Fitbit group and the tailoring-only group received 6 modules of computer-tailored physical activity advice over 12 weeks. The advice was informed by objective Fitbit data in the tailoring + Fitbit group and self-reported physical activity in the tailoring-only group. This study examined the engagement, acceptability, usability, and satisfaction of Active for Life in intervention participants (tailoring + Fitbit n = 78, tailoring only n = 96). Wait-list participants were not included. Engagement (Module completion, time on site) were objectively recorded through the intervention website. Acceptability (7-point Likert scale), usability (System Usability Scale), and satisfaction (open-ended questions) were assessed using an online survey at post intervention. ANOVA and Chi square analyses were conducted to compare outcomes between intervention groups and content analysis was used to analyse program satisfaction. Results: At post-intervention (week 12), study attrition was 28% (22/78) in the Fitbit + tailoring group and 39% (37/96) in the tailoring-only group. Engagement and acceptability were good in both groups, however there were no group differences (module completions: tailoring + Fitbit: 4.72 ± 2.04, Tailoring-only: 4.23 ± 2.25 out of 6 modules, p =.14, time on site: tailoring + Fitbit: 103.46 ± 70.63, Tailoring-only: 96.90 ± 76.37 min in total, p =.56, and acceptability of the advice: tailoring + Fitbit: 5.62 ± 0.89, Tailoring-only: 5.75 ± 0.75 out of 7, p =.41). Intervention usability was modest but significantly higher in the tailoring + Fitbit group (tailoring + Fitbit: 64.55 ± 13.59, Tailoring-only: 57.04 ± 2.58 out of 100, p =.003). Participants reported that Active for Life helped motivate them, held them accountable, improved their awareness of how active they were and helped them to become more active. Conversely, many participants felt as though they would prefer personal contact, more detailed tailoring and more survey response options. Conclusions: This study supports web-based physical activity interventions with computer-tailored advice and Fitbit integration as engaging and acceptable in older adults. Trial registration: Australian and New Zealand Clinical Trials Registry: ACTRN12618000646246. Registered April 23 2018, [ABSTRACT FROM AUTHOR]

New digital technologies like activity trackers, nudge concepts, and approaches can inspire and improve personal health. There is increasing interest in employing such devices to monitor people's health and well-being. These devices can continually gather and examine health-related information from people and groups in their familiar surroundings. Context-aware nudges can assist people in self-managing and enhancing their health. In this protocol paper, we describe how we plan to investigate what motivates people to engage in physical activity (PA), what influences them to accept nudges, and how participant motivation for PA may be impacted by technology use. [ABSTRACT FROM AUTHOR]

Background: The 6 min walk test is widely used to measure the severity of COPD, but this test imposes an extensive burden on patients and medical staff. As an alternative to this test, the measurement of activity amount during daily activities that cause COPD patients to feel shortness of breath can be acquired using wearable devices, and the measurements between COPD patients and healthy people can be compared. Accordingly, based on machine learning, we first evaluated the accuracy of the accelerometers in recognizing such activities. Methods: Forty-six healthy participants wore tri-axial accelerometers on the wrist and hip, and performed nine activities: changing clothes, sitting, standing, lying in a supine position, brushing teeth, moving luggage, going up/down the stairs, running, and walking. Features were extracted from 10 s windows of 31 datasets and input into a machine-learning classifier model. Results: The wrist+hip classifier recognized the activities of changing clothes, standing, lying in a supine position, brushing teeth, moving luggage, going up/down the stairs, walking, and running. Sitting and other movements were not appropriately recognized. Conclusions: Sedentary movements such as sitting were difficult to recognize. However, changing clothes, standing, lying in a supine position, brushing teeth, moving luggage, going up/down the stairs, walking, and running were recognizable. These recognized activities tend to cause shortness of breath in COPD patients. Thus, the findings confirm the feasibility of an algorithm that could determine the severity of COPD by comparing activity amount for each of these activities with those of the healthy people of the same age. [ABSTRACT FROM AUTHOR]

Background: Despite rapid growth in the popularity of smartwatches, evidence lacks regarding older adults' acceptance of smartwatches. Since most wearable sensors are not designed specifically for older adults, there is a need to examine wearability and usability challenges of wearable sensing devices faced by older adults to facilitate the use of objective measurements of health and mobility. Objectives: We aimed to examine older adults' perceptions of GPS‐enabled smartwatches and to identify potential barriers and facilitators of smartwatch and sensor data use. Methods: As part of a larger feasibility study, we conducted a mixed‐methods study that included a descriptive content analysis of interviews and a brief usability survey with 30 participants aged 60 years and older after they had used a smartwatch for 3 days. Results: Most participants perceived wearable activity trackers including smartwatches and sensor‐based data as useful for tracking health, finding activity patterns and promoting healthy behaviours. Privacy was of little concern, leading to willingness to share activity and location data with others. Participants identified barriers to usability as clumsy design, lack of aesthetic appeal, and difficulty reading the display and using the GPS tracking function. In contrast, identified facilitators of adoption included a big display, high‐tech look, self‐awareness and possible behaviour change. Conclusions: Smartwatches have the potential of personalised detection of health deterioration and disability prevention, based on analysis of older adults' activities in free‐living environments. The usefulness of this technology for older adults can be significantly increased by addressing usability issues and providing instructions on challenging features. Implications for Practice: To support sustained self‐monitoring behaviours through wearable sensor devices in older adults, it is critical to examine how they perceive those devices and identify factors affecting technology acceptance that can maximise adoption. [ABSTRACT FROM AUTHOR]

Background: In radiotherapy the timely identification of patients needing intervention and supportive care due to side effects is an important task especially in the outpatient setting. Activity trackers as an increasingly used lifestyle device may enable physicians to monitor patient’s physical activity (PA) and to intervene early during the course of radiotherapy. Objective: The primary aim of this trial was to assess patient acceptance of PA monitoring in an outpatient setting and to correlate changes in PA with toxicity and changes in quality of life. Methods: Patients undergoing radio(chemo-)therapy with a curative intent were eligible to participate in this prospective pilot phase II trial. Patients were instructed to wear a commercially available activity tracker during the course of radiotherapy and four weeks afterwards. Quality of life (QoL) and fatigue was scored using the Functional assessment of Chronic Illness Therapy questionnaire. A linear regression was performed to determine baseline activity and changes in step counts during radiotherapy. Results: We included 23 patients in this trial. Two withdrew consent before the start of treatment, two patients were excluded after prophylactic feeding tube placement and prolonged recovery. Compliance in the remaining 19 patients was high, with availability of step-counts on 92% of the days. Baseline step counts were 6274 for breast cancer patients and 3621 for patients with other entities. Decreasing activity during radiotherapy coincided with the development of side effects and declines in quality of life. Conclusions: Activity trackers as tool to monitor PA during and after radiotherapy were accepted by a majority of the patients included in the current trial. Observed changes in PA correlated with patient reported side effects and QoL in some of the patients.

Abstract Background Breast cancer (BC) has particular characteristics in young women, with diagnosis at more advanced stages, a poorer prognosis and highly aggressive tumors. In NeoFit, we will use an activity tracker to identify and describe various digital profiles (heart rate, physical activity, and sleep patterns) in women below the age of 45 years on neoadjuvant chemotherapy for BC. Methods NeoFit is a prospective, national, multicenter, single-arm open-label study. It will include 300 women below the age of 45 years treated with neoadjuvant chemotherapy for BC. Participants will be asked to wear a Withing Steel HR activity tracker round the clock for 12 months. The principal assessments will be performed at baseline, at the end of neoadjuvant chemotherapy and at 12 months. We will evaluate clinical parameters, such as toxicity and the efficacy of chemotherapy, together with quality of life, fatigue, and parameters relating to lifestyle and physical activity. The women will complete REDCap form questionnaires via a secure internet link. Discussion In this study, the use of an activity tracker will enable us to visualize changes in the lifestyle of young women on neoadjuvant chemotherapy for BC, over the course of a one-year period. This exploratory study will provide crucial insight into the digital phenotypes of young BC patients on neoadjuvant chemotherapy and the relationship between these phenotypes and the toxicity and efficacy of treatment. This trial will pave the way for interventional studies involving sleep and physical activity interventions. Trial registration Clinicaltrials.gov identifier: NCT05011721 . Registration date: 18/08/2021.

Background: The 6 min walk test is widely used to measure the severity of COPD, but this test imposes an extensive burden on patients and medical staff. As an alternative to this test, the measurement of activity amount during daily activities that cause COPD patients to feel shortness of breath can be acquired using wearable devices, and the measurements between COPD patients and healthy people can be compared. Accordingly, based on machine learning, we first evaluated the accuracy of the accelerometers in recognizing such activities. Methods: Forty-six healthy participants wore tri-axial accelerometers on the wrist and hip, and performed nine activities: changing clothes, sitting, standing, lying in a supine position, brushing teeth, moving luggage, going up/down the stairs, running, and walking. Features were extracted from 10 s windows of 31 datasets and input into a machine-learning classifier model. Results: The wrist+hip classifier recognized the activities of changing clothes, standing, lying in a supine position, brushing teeth, moving luggage, going up/down the stairs, walking, and running. Sitting and other movements were not appropriately recognized. Conclusions: Sedentary movements such as sitting were difficult to recognize. However, changing clothes, standing, lying in a supine position, brushing teeth, moving luggage, going up/down the stairs, walking, and running were recognizable. These recognized activities tend to cause shortness of breath in COPD patients. Thus, the findings confirm the feasibility of an algorithm that could determine the severity of COPD by comparing activity amount for each of these activities with those of the healthy people of the same age.

Background: Given the popularity of thigh-worn accelerometers, it is important to understand their reliability and validity. Purpose: Our study evaluated laboratory validity and free-living intermonitor reliability of the Fibion monitor and free-living intermonitor reliability of the activPAL monitor. Free-living comparability of the Fibion and activPAL monitors was also assessed. Methods: Nineteen adult participants wore Fibion monitors on both thighs while performing 11 activities in a laboratory setting. Then, participants wore Fibion and activPAL monitors on both thighs for 3 days during waking hours. Accuracy of the Fibion monitor was determined for recognizing lying/sitting, standing, slow walking, fast walking, jogging, and cycling. For the 3-day free-living wear, outputs from the Fibion monitors were compared, with similar analyses conducted for the activPAL monitors. Finally, free-living comparability of the Fibion and activPAL monitors was determined for nonwear, sitting, standing, stepping, and cycling. Results: The Fibion monitor had an overall accuracy of 85%–89%, with high accuracy (94%–100%) for detecting prone and supine lying, sitting, and standing but some misclassification among ambulatory activities and for left-/right-side lying with standing. Intermonitor reliability was similar for the Fibion and activPAL monitors, with best reliability for sitting but poorer reliability for activities performed least often (e.g., cycling). The Fibion and activPAL monitors were not equivalent for most tested metrics. Conclusion: The Fibion monitor appears suitable for assessment of sedentary and nonsedentary waking postures, and the Fibion and activPAL monitors have comparable intermonitor reliability. However, studies using thigh-worn monitors should use the same monitor brand worn on the same leg to optimize reliability. [ABSTRACT FROM AUTHOR]

Apply It!: By reading this article, fitness professionals who work with novice exercisers with type 2 diabetes mellitus (T2DM) will be able to: • individualize recommendations for activity timing, reducing sedentary time, and modes of exercise to maximize blood sugar control for clients with T2DM; • summarize the benefits and limitations of step tracking on blood sugar control for individuals with T2DM. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the impact of a wearable activity tracker used to encourage physical activity, on disease flares in patients with spondyloarthritis (SpA).Methods: This randomized controlled trial involved randomizing 108 patients with SpA into tracker and nontracker groups. The participants were then subjected to assessments of disease activity, performance (6-minute walk test), and quality of life (QOL; 36-item Short Form Health Survey) at the 12th, 24th, and 36th week. The primary outcome was the change in the frequency of flare episodes (categorized as no flare, flare in ≤ 3 days, and flare in > 3 days) between baseline and 12 weeks.Results: The results of the study showed that at the 12th week, the mean change (∆) of the number of flares improved in both groups: -0.32 (95% CI -0.66 to 0.02) and -0.38 (95% CI -0.68 to -0.09) in the tracker and nontracker group, respectively. However, the between-group differences were insignificant (P = 0.87). Performance scores improved in both groups at the 12th, 24th, and 36th week (all P < 0.01). The different dimensions of QOL also improved at the 12th week (P < 0.01). Conversely, moderate flares (P < 0.01) and performance (P < 0.01) improved over time; however, the influence over time of a wearable activity tracker was not significant (P = 0.29 and P = 0.66, respectively).Conclusion: The use of a wearable activity tracker did not affect the number of flares, performance, or QOL of patients with SpA. Nevertheless, this study confirmed the benefits of physical activity on flares, disease activity, QOL, and physical performance in patients with SpA. (Move Your Spondyl "Better Live Its Rheumatism With the Physical Activity"; ClinicalTrials.gov: NCT03458026). [ABSTRACT FROM AUTHOR]

Consumer activity devices use prompts to alter sedentary and physical activity (PA) behaviors. However, it is unclear if PA prompts are effective. Purpose: To evaluate the effectiveness of PA prompts from a consumer wearable device in reducing sitting time and increasing PA in university employees. Methods: Thirty-three university employees without a history of consumer activity device wear were randomly assigned a Fitbit Alta HR that administered PA prompts (Prompt group) or had the prompt feature deactivated (No Prompt group). Participants wore an activPAL for 5–7 days to measure baseline sitting time and PA behaviors. Participants then wore the Fitbit for 12 days during waking hours and an activPAL during the last 5–7 days of the Fitbit wear period. Changes in activPAL sitting time and PA were compared across groups. Mean Fitbit steps taken in the first 50 min and the last 10 min of each hour were calculated and compared across groups during "Inactive" hours (<250 steps in the first 50 min), where a prompt was given (Prompt group) or would have been given (No Prompt group). Results: Mean activPAL sitting time increased in the Prompt group (0.66 ± 1.70 hr/day) and remained stable in the No Prompt group (−0.04 ± 1.29 hr/day), with no statistically significant differences between groups (d = 0.33, p =.36). Moderate to vigorous PA increased modestly in both groups, but no significant differences were observed. Fitbit steps during the last 10 min of inactive hours did not differ across groups. Conclusion: Fitbit PA prompts did not alter sitting time or PA behaviors in university employees. [ABSTRACT FROM AUTHOR]

The purpose of this scoping review was to examine publications using accelerometers in children aged 6 months to <6 years and report on current methodologies used for data collection and analyses. We examined device make and model, device placement, sampling frequency, data collection protocol, definition of nonwear time, inclusion criteria, epoch duration, and cut points. Five online databases and three gray literature databases were searched. Studies were included if they were published in English between January 2009 and March 2021. A total of 627 articles were included for descriptive analyses. Of the reviewed articles, 75% used ActiGraph devices. The most common device placement was hip or waist. More than 80% of articles did not report a sampling frequency, and 7-day protocols during only waking hours were the most frequently reported. Fifteen-second epoch durations and the cut points developed by Pate et al. in 2006 were the most common. A total of 203 articles did not report which definition of nonwear time was used; when reported, "20 minutes of consecutive zeros" was the most frequently used. Finally, the most common inclusion criteria were "greater or equal to 10 hr/day for at least 3 days" for studies conducted in free-living environments and "greater than 50% of the school day" for studies conducted in preschool or childcare environments. Results demonstrated a major lack of reporting of methods used to analyze accelerometer data from young children. A list of recommended reporting practices was developed to encourage increased reporting of key methodological details for research in this area. [ABSTRACT FROM AUTHOR]

Technology and its influence upon society have turned into a controversial topic in today’s fast-developing world, where advances in innovation are continuous, fast, and complex. The relationship between technology and society has become an increasing interest for many researchers, trying to explore and clarify this connection. This article focuses on the psychological impact of technology, expressed through activity tracking devices, upon user’s attitudes towards pursuing an active lifestyle. To conduct the analysis, users’ registered behavioral changes after engaging with technological devices are explored, by examining academic literature reports studies, supplemented by experimental material written by the users themselves on publicly available websites. The study proposes a deductive research design, by constructing its analysis on a relevant theoretical framework, that of Technological Determinism theory, which advocates that technology can influence society, however without being affected by humans. Nevertheless, the results of the research show that the relationship between technology and society is not that linear, as influences coming from the social environment usually interact and impact the way technology is used. This determines the consideration of an additional theoretical concept to the analysis, that of Social Shaping of Technology, and changes the dynamics of exploring the topic. Conclusions demonstrate that the relationship between user and technology can be characterized as a double-way approach, with complex and ambiguous attributes, where both forces interact and can lead to positive and constructive behavioral outcomes but also to critical and hard to control mental conditions.

Non-exercise physical activity (NEPA), also called unstructured or informal physical activity, refers to those daily activities that require movement of the human body without planning or strict control of the physical effort made. Due to new technologies and motorized transportation devices, the general population has significantly decreased its NEPA. This increase in sedentary lifestyles, physical inactivity, and excessive energy intake is considered a risk factor for obesity, non-communicable diseases (NCDs), and all-cause mortality. Searching in PubMed/MEDLINE and Web of Science databases, a narrative review of NEPA was carried out to address its conceptualization, promotion strategies for the general population, and monitoring through wearable devices. It is strongly recommended that governmental entities, health practitioners, and the construction industry adhere to “The Global Action Plan on Physical Activity 2018–2030: More Active People for a Healthier World” and implement different salutogenic urban strategies. These strategies aim to generate environments that motivate increases in NEPA, such as cycling and walking transportation (between 5000–12,500 steps per day), and the progression to physical exercise. There is a wide variety of electronic devices for personal use, such as accelerometers, smartphone apps, or “smart clothes”, that allow for the monitoring of NEPA, some with a wide range of analysis variables contributing to the estimation of total daily energy expenditure and the promotion of healthy habits. In general, the further promotion and monitoring of NEPA is required as part of a strategy to promote healthy habits sustainable over time for the prevention and control of obesity and NCDs.

Nowadays, there is growing interest in establishing daily activity wristband-based physical activity recommendations. Unfortunately, empirical studies examining the activity wristband-measured physical activity thresholds related to the daily physical activity recommendation in adolescents were not found. The main aim of the present study was to establish daily activity wristband-measured steps thresholds related to the recommendation of 60 minutes of moderate-to-vigorous physical activity daily in adolescents. The secondary aims of this study were twofold: (a) to establish daily activity wristband-measured total physical activity and moderate-to-vigorous physical activity thresholds; and (b) to examine the cross-validity of daily activity wristband-measured steps thresholds established in previous studies associated with the recommended 60 minutes per day of moderate-to-vigorous physical activity in adolescents. Following a cross-sectional design, 85 Spanish adolescents (including 56 females; aged 12–18 years old) from a public high school wore an ActiGraph GT3X+ accelerometer and four activity wristbands (Xiaomi Mi Band 2, Fitbit Alta HR, Polar A360 and Garmin Vivofit 4; non-dominant hand; index tests) for a day. A total of 38.8% of the adolescents met the moderate-to-vigorous physical activity recommendation. The results showed that the validity of the daily total step-based thresholds tended to be higher (e.g., AUC = 0.83–0.91, P < 0.001) than those with total physical activity or moderate-to-vigorous physical activity (AUC = 0.66–0.88, P < 0.01). The results of the cross-validity showed that the 10,000 step-per-day threshold had a high agreement (e.g., Xiaomi, P = 0.80; k = 0.58; Garmin, P = 0.82; k = 0.63). Activity wristband-measured total steps thresholds have a high validity for translating the daily moderate-to-vigorous physical activity recommendation, being more preferable than those with total physical activity or moderate-to-vigorous physical activity. A 10,000 step-per-day target seems to be a practical and adequate activity wristband-based threshold among adolescents. This knowledge may help policy makers to provide adequate daily activity wristband-measured step-based recommendations for adolescents. [ABSTRACT FROM AUTHOR]

Purpose: Inertial-based trackers have become a common tool in data capture for ambulatory studies that aim at characterizing physical activity. Many systems that perform remote recording of accelerometer data use commercial trackers and black-box aggregation algorithms, often resulting in data that are locked into proprietary formats and metrics that make later replication or comparison difficult. Methods: The primary purpose of this manuscript is to validate an open-source ambulatory assessment system that consists of hardware devices, algorithms, and software components of our approach. We report on two validation experiments, one lab-based treadmill study on a convenience sample of 16 volunteers and one 'in vivo' study with 28 volunteers suffering from diabetes or cardiovascular disease. Results: A comparison between data from ActiGraph GT9X trackers and our proposed system reveals that the original inertial sensor signals at the wrist strongly correlate (Pearson correlation coefficients for raw inertial sensor signals of 0.97 in the controlled treadmill-walking setting) and that estimated steps from an open-source wrist-based detection approach correlate with the hip-worn ActiGraph output (average Pearson correlation coefficients of 0.81 for minute-wise comparisons of detected steps) in day-long ambulatory data. Conclusion: Recording inertial sensor data in a standardized form and relying on open-source algorithms on these data form a promising methodology that ensures that datasets can be replicated or enriched long after the wearable trackers have been decommissioned. [ABSTRACT FROM AUTHOR]

Background: Breast cancer (BC) has particular characteristics in young women, with diagnosis at more advanced stages, a poorer prognosis and highly aggressive tumors. In NeoFit, we will use an activity tracker to identify and describe various digital profiles (heart rate, physical activity, and sleep patterns) in women below the age of 45 years on neoadjuvant chemotherapy for BC.Methods: NeoFit is a prospective, national, multicenter, single-arm open-label study. It will include 300 women below the age of 45 years treated with neoadjuvant chemotherapy for BC. Participants will be asked to wear a Withing Steel HR activity tracker round the clock for 12 months. The principal assessments will be performed at baseline, at the end of neoadjuvant chemotherapy and at 12 months. We will evaluate clinical parameters, such as toxicity and the efficacy of chemotherapy, together with quality of life, fatigue, and parameters relating to lifestyle and physical activity. The women will complete REDCap form questionnaires via a secure internet link.Discussion: In this study, the use of an activity tracker will enable us to visualize changes in the lifestyle of young women on neoadjuvant chemotherapy for BC, over the course of a one-year period. This exploratory study will provide crucial insight into the digital phenotypes of young BC patients on neoadjuvant chemotherapy and the relationship between these phenotypes and the toxicity and efficacy of treatment. This trial will pave the way for interventional studies involving sleep and physical activity interventions.Trial Registration: Clinicaltrials.gov identifier: NCT05011721 . Registration date: 18/08/2021. [ABSTRACT FROM AUTHOR]

Introduction: Numerous healthcare apps, medical trackers, and wearable sensors are the furthermost significant progression in medical technology for self-care, especially in children, older people, and Alzheimer's patients. Objective: The study aims to discover opportunities by medication apps and wearable selfmonitoring sensors for older adults, children, and Alzheimer's patients. Method: We investigated that how the advancement in modern technology can help in preventing health issues in individuals. Various applications in smartphone and wearable devices utilize these technologies, make them more user-friendly with only one tap and successfully prevent serious health conditions. Results: The deep investigation revealed three primary themes: 'Device Functionality', 'Reasons for Use,' and 'Utilization Strategies.' Conclusion: In summarized manner we can say that critical health and lifestyle aspects of individuals can handle by SW-SHMS or medical tracker devices, especially in older people, children and those individuals who are suffering from chronic diseases and neuro disorders such as Alzheimer's. [ABSTRACT FROM AUTHOR]

As smartphone and wearable device ownership increase, interest in their utility to monitor physical activity has risen concurrently. Numerous examples of the application of wearables in clinical and epidemiological research settings already exist. However, whether these devices are all suitable for physical activity surveillance is open for debate. In this commentary, we respond to a commentary by Mair et al. (2021) and discuss four key issues specifically relevant to surveillance that we believe need to be tackled before consumer wearables can be considered for this measurement purpose: representative sampling, representative wear time, validity and reliability, and compatibility between devices. A recurring theme is how to deal with systematic biases by demographic groups. We suggest some potential solutions to the issues of concern such as providing individuals with standardized devices, considering summary metrics of physical activity less prone to wear time biases, and the development of a framework to harmonize estimates between device types and their inbuilt algorithms. We encourage collaborative efforts from researchers and consumer wearable manufacturers in this area. In the meantime, we caution against the use of consumer wearable device data for inference of population-level activity without the consideration of these issues. [ABSTRACT FROM AUTHOR]

Purpose: This study examined adherence with a physical activity tracker and patterns of activity among different subgroups of African American/Black breast cancer survivors (AABCS). Design: Secondary analysis of weight loss trial that used an activity tracker (FitBit) with or without a commercial eHealth program (SparkPeople) over 12 months. Setting and Subjects: AABCS (N = 44) in New Jersey. Measures and Analysis: Adherence with tracker use, steps per day, and active minutes per week were compared by demographic and clinical characteristics using nonparametric statistics. Results: Median adherence was over 6 days per week throughout the 12-months. Adherence was significantly correlated with steps and active minutes (p < 0.015). Groups with lower adherence included: those with 5 or more conditions (p = 0.039), had higher number of household members (p = 0.008), and younger than 60 years (p = 0.044). Median number of steps per day remained consistently around 7000 throughout 12 months. Factors associated with lower activity included: age > 60; retirement; higher number of household members, comorbidity, or baseline BMI; and those in the SparkPeople + Fitbit group. Self-monitoring, goal setting, and self-efficacy were significantly correlated with activity levels (p < 0.05). Conclusion: Use of a physical activity tracker may help increase activity levels in AABCS. Certain subgroups, e.g. those older than age 60 years, retired, with BMI over 40, higher number of comorbidities or more household members, may require additional interventions. [ABSTRACT FROM AUTHOR]

Abstract Background Lack of physical activity (PA) is a risk factor for death and non-communicable disease. Despite this, more than one fourth of adults worldwide do not follow PA guidelines. As part of a feasibility study to test a complex intervention for increasing PA, we included a consumer-based activity tracker (AT) as a tool to measure PA outcomes and to track heart rate during exercise sessions. The aim of the present study was to identify factors that increase wear time when using a consumer-based AT for monitoring of participants in clinical research. Methods Sixteen participants aged 55–74 years, with obesity, sedentary lifestyle, and elevated cardiovascular risk were recruited to a 12-month feasibility study. Participants wore a Polar M430 AT to collect continuous PA data during a six-month intervention followed by 6 months of follow-up. We performed quantitative wear time analysis, tested the validity of the AT, and completed two rounds of qualitative interviews to investigate how individual wear-time was linked to participant responses. Results From 1 year of tracking, mean number of valid wear days were 292 (SD = 86), i.e. 80%. The Polar M430 provides acceptable measurements for total energy expenditure. Motivations for increased wear time were that participants were asked to wear it and the ability to track PA progress. Perceived usefulness included time keeping, heart rate- and sleep tracking, becoming more conscious about day-to-day activity, and improved understanding of which activity types were more effective for energy expenditure. Sources of AT annoyance were measurement inaccuracies and limited instruction for use. Suggestions for improvement were that the AT was big, unattractive, and complicated to use. Conclusions Adherence to wearing a consumer-based AT was high. Results indicate that it is feasible to use a consumer-based AT to measure PA over a longer period. Potential success factors for increased wear time includes adequate instruction for AT use, allowing participants to choose different AT designs, and using trackers with accurate measurements. To identify accurate trackers, AT validation studies in the target cohort may be needed. Trial registration U.S. National Library of Medicine, Clinical Trial registry: NCT03807323 ; Registered 16 September 2019 – Retrospectively registered.

To evaluate the impact of Health interventions promoting physical activity, researchers typically conduct pre- and post-assessments using accelerometers. While aggregated metrics such as daily counts, daily steps and time spent at various intensity levels are commonly used, very few studies exploit the richness of the data often collected with a very fine granularity. We investigate the benefit of a deeper analysis of wrist accelerometry data to understand physical activity behaviours throughout the day, as well as how these may change overtime. To analyse physical activity behaviour changes, we propose a methodology that extracts bouts of physical activity characterised by their activity levels and duration, and uses these as features to cluster participants' daily and hourly behaviours. We then compare these clusters to assess changes following an intervention promoting physical activity in children. We demonstrate that this approach provides a more insightful analysis of the physical activity behaviours because it highlights the nature and the timing of behaviour changes, when present. We illustrate this methodology using data from research-grade activity trackers (GENEActiv) and explain the insights discovered in the context of an intervention aimed at educating school children about healthy behaviours.

Research suggests optimizing sleep, exercise and work-life balance may improve resident physician burnout. Wearable biosensors may allow residents to detect and correct poor sleep and exercise habits before burnout develops. Our objectives were to evaluate the feasibility of a wearable biosensor to characterize exercise/sleep in neurology residents and examine its relationship to self-reported, validated survey measures. We also assessed the device's impact on well-being and barriers to use. This prospective cohort study evaluated the WHOOP Strap 2.0 in neurology residents. Participants completed regular online surveys, including self-reported hours of sleep/exercise, and validated sleep/exercise scales at 3-month intervals. Autonomic, exercise, and sleep measures were obtained from WHOOP. Changes were evaluated over time via linear regression. Survey and WHOOP metrics were compared using Pearson correlations. Sixteen (72.7%) of 22 eligible participants enrolled. Eleven (68.8%) met the minimum usage requirement (6+ months) and were classified as 'consecutive wearers.' Significant increases were found in sleep duration and exercise intensity. Moderate-to-low correlations were found between survey responses and WHOOP measures. Most (73%) participants reported a positive impact on well-being. Barriers to use included 'Forgetting to wear' (20%) and 'not motivational' (23.3%). Wearable biosensors may be a feasible tool to evaluate sleep/exercise in residents. [ABSTRACT FROM AUTHOR]

Objectives: The aim of this study was to examine the extent to which older adults utilize mobile health tracking tools in everyday life and their willingness to share the collected health-related data with doctors, health insurance companies, or research institutions. Methods: This study used a survey to assess mobile device use (smartphone, tablet, fitness tracker, and smartwatch), health app use (e.g., health insurance apps, fitness apps), and willingness to share health-related data in 1,149 Swiss adults aged ≥ 65 years. Results: 75.0% of the participants used at least one mobile device; 22.9% used health-related apps. Younger individuals and those with a strong interest in new technology had a higher likelihood of using health apps. Participants were more often willing to share their data with doctors than with health insurance companies or researchers; this willingness was also influenced by an affinity for technology. Discussion: These results support the promotion of mHealth adoption among older adults by developers and policymakers.

Inadequate physical activity is currently one of the leading risk factors for mortality worldwide. University students are a high-risk group in terms of rates of obesity and lack of physical activity. In recent years, activity trackers have become increasingly popular for measuring physical activity. The aim of the present study is to examine whether university students in Hungary meet the health recommendations (10,000 steps/day) for physical activity and investigate the impact of different variables (semester-exam period, days-weekdays, days, months, sex) on the level of physical activity in free-living conditions for 3 months period. In free-living conditions, 57 healthy university students (male: 25 female: 32 mean age: 19.50 SD = 1.58) wore MiBand 1S activity tracker for 3 months. Independent sample t-tests were used to explore differences between sexes. A One-way analysis of variance (ANOVA) was used to explore differences in measures among different grouping variables and step count. A Two-way ANOVA was conducted to test for differences in the number of steps by days of the week, months, seasons and for sex differences. Tukey HSD post-hoc tests were used to examine significant differences. Students in the study achieved 10,000 steps per day on 17% of days (minimum: 0%; maximum: 76.5%; median: 11.1%). Unfortunately, 70% of the participants did not comply the 10,000 steps at least 80% of the days studied. No statistical difference were found between sexes. However, significant differences were found between BMI categories (underweight 30 kg/m2, the number of steps in the overweight category was significantly lower (F = 72.073, p < 0.001). The average daily steps were significantly higher in autumn (t = 11.457, p < 0.001) than in winter. During exam period average steps/day were significantly lower than during fall semester (t = 13.696, p < 0.001). On weekdays, steps were significantly higher than on weekends (F = 14.017, p < 0.001), and even within this, the greatest physical activity can be done by the middle of the week. Our data suggest that university students may be priority groups for future physical activity interventions. Commercial activity trackers provide huge amount of data for relatively low cost therefore it has the potential to objectively analyze physical activity and plan interventions.

Purpose: Variability in accelerometry-data processing decisions limited data comparability across studies. We aimed to examine different accelerometry-data processing rules: varying bout lengths and allowance of 0- and 2-min interruptions on the total and bout-accumulated time spent in moderate-to-vigorous physical activity (MVPA) and sedentary behavior estimates, and describe the distribution of activity time based on counts per min (CPM) in granular categories. Method: Using the Singapore Health 2 survey, this study included 746 adults (41.8% women, median age 45.0 years) who provided valid ActiGraph GT3X+ accelerometer-data (≥4 valid days with ≥10-h/day). Quantile regression analysis adjusting for accelerometry daily wear time, age, and gender was performed to calculate the median and interquartile range of accelerometry estimates. Results: Median MVPA time accumulated in bouts of 1-min versus bouts of 10-min was 39.2 min/day and 6.0 min/day, respectively. MVPA time was higher when considering a 2-min interruption (range: 1.8-39.2 min/day) compared to 0-min interruption (range: 0-35.5 min/day) across bout lengths of 1- to 15-min. Participants were sedentary (≤100 CPM) for a daily median of 7.6 h/day. Median activities min/day on the lower-intensity activity spectrum (100-2499 CPM) decreased from 63.4 to 4.6 min/day, while on the higher-intensity activity spectrum (≥2500 CPM) was ≤2.9 min/day. Men generally spent more time in MVPA than women. Conclusions: This study highlights the differences in accelerometry estimates based on data processing decisions, and the importance of quantifying accelerometry-based activity time across the granular intensity spectrum. More studies are warranted to understand the determinants and health impact of these behaviors. [ABSTRACT FROM AUTHOR]

Mentoring can improve physical activity among youth. However, this strategy has yet to be employed between college and elementary school students. This efficacy study investigated the impact of an individualized collegementored physical activity program on physical activity levels among older elementary school students. A diverse population (16.7% white, 66.7% Hispanic, 16.7% African American) of fifth grade elementary school students (n = 12) were paired with individual local undergraduate college mentors. Bi-weekly running sessions occurred on an elementary school campus for six weeks. Multiple assessments from activity trackers were compared on intervention versus non-intervention days using paired samples t-tests. When compared to non-intervention days, there were statistically significant increases in steps (t(11) = 8.056; p ≤ .001), distance (t(11) = 6.883; p ≤ .001), moderate-to-vigorous activity (t(11) = 5.202; p ≤ .001), calories burned (t(11) = 5.206; p ≤ .001), and activity calories (t(11) = 2.731; p = .02) on intervention days, but no difference in sedentary time (t(11) = -1.087; p = .300). Individualized mentoring from college students contributed to increased physical activity in older elementary school students. This novel high-impact and low-cost approach should be considered in future school-based physical activity programs. [ABSTRACT FROM AUTHOR]

Background: Researchers are interested in using digital tools, such as physical activity trackers (PAT), to promote and measure physical activity. PAT is a fast-growing research area that measures movement therefore, reliable questions on the ownership and use of PATs among adolescent populations need to be developed. Objective: The aim of this study was to conduct an intra-rater test-retest reliability study on PAT survey items used for surveillance purposes among young adolescents in ownership and use of smartphone applications (apps) and heart rate monitors (HRM). Methods: Young adolescents (N = 755; 11-, 13-, and 15-year-olds) in the Olomouc region of the Czech Republic were recruited to complete the questionnaire with a three-week gap during autumn 2017. Kappa statistics were used for measuring reliability. Results: When items were dichotomised into owners and non-owners, there was moderate agreement for boys (apps Kappa = .563, HRM Kappa = .575) and girls (apps Kappa = .447, HRM Kappa = .443). Conclusions: Measures in ownership and use of PAT can be assumed reliable among young adolescents.

Background: Ready to Move (RTM), a university worksite wellness program, was implemented to get employees moving more and sitting less by combining student health coaching and activity trackers (AT’s). Aim: This article provides program specifics and survey data outcomes to facilitate ideas for university faculty, staff and student collaboration. The intent of the article is to provide an example of how academic classes can contribute to employee worksite wellness programming within a university. Methods: Twelve cohorts (2015 - 2017) comprised of 295 university employees received Fitbit Flex ATs and health coaching from students enrolled in a physical activity (PA) behavioral interventions class during a 10-week program. The employees met with their student coach eight times to learn how to use their AT and set movement goals. Employee’s completed self-reported surveys on average PA days and PA confidence pre/post program. Results: Findings revealed RTM significantly impacted employees average number of PA days and their confidence in ability to sustain PA. Employee qualitative comments revealed RTM instilled the importance of utilizing ATs combined with student engagement made the experience enjoyable and effective. Conclusion: RTM’s combination improved employee movement outcomes and provided additional programming ideas for the employee wellness program at a large Midwestern university.