Behavior Change Techniques Incorporated in Fitness Trackers: Content Analysis

Acceptability of a remotely delivered sedentary behaviour intervention to improve sarcopenia and maintain independent living in older adults with frailty: a mixed-methods study

BACKGROUND

Sarcopenia is a leading cause of functional decline, loss of independence, premature mortality, and frailty in older adults. Reducing and breaking up sedentary behaviour is associated with positive sarcopenia and frailty outcomes. This study aimed to explore the acceptability, engagement and experiences of a remotely delivered sedentary behaviour intervention to improve sarcopenia and independent living in older adults with frailty.

METHODS

This was a mixed-methods study. In-depth qualitative semi-structed interviews were conducted with a subset (N = 15) of participants with frailty (aged 74 ± 6 years) who had participated in the Frail-LESS (LEss Sitting and Sarcopenia in Frail older adults) intervention aimed at reducing sedentary behaviour. The interviews explored acceptability of the intervention overall and its individual components (a psychoeducation workbook, wrist-worn activity tracker, health coaching, online peer support and tailored feedback on sitting, standing and stepping). Process evaluation questionnaires with closed and scaled questions explored intervention engagement, fidelity and experiences.

RESULTS

Overall acceptability of the intervention was good with most participants perceiving the intervention to have supported them in reducing and/or breaking up their sedentary behaviour. The wrist-worn activity tracker and health coaching appeared to be the most acceptable and useful components, with high levels of engagement. There was attendance at 104 of 150 health coaching sessions offered and 92% of participants reported using the wrist-worn activity tracker. There was a mixed response regarding acceptability of, and engagement with, the psychoeducation workbook, tailored feedback, and online peer support.

CONCLUSIONS

The Frail-LESS intervention had good levels of acceptability and engagement for some components. The findings of the study can inform modifications to the intervention to optimise acceptability and engagement in a future definitive randomised controlled trial.

TRIAL REGISTRATION

The trial was registered with ISRCTN (number ISRCTN17158017).

Considering User Experience and Behavioral Approaches in the Design of mHealth Interventions for Atrial Fibrillation: Systematic Review

BACKGROUND

Atrial fibrillation (AF) is a leading chronic cardiac disease associated with an increased risk of stroke, cardiac complications, and general mortality. Mobile health (mHealth) interventions, including wearable devices and apps, can aid in the detection, screening, and management of AF to improve patient outcomes. The inclusion of approaches that consider user experiences and behavior in the design of health care interventions can increase the usability of mHealth interventions, and hence, hopefully, yield an increase in positive outcomes in the lives of users.

OBJECTIVE

This study aims to show how research has considered user experiences and behavioral approaches in designing mHealth interventions for AF detection, screening, and management; the phases of designing complex interventions from the UK Medical Research Council (MRC) were referenced: namely, identification, development, feasibility, evaluation, and implementation.

METHODS

Studies published until September 7, 2022, that examined user experiences and behavioral approaches associated with mHealth interventions in the context of AF were extracted from multiple databases. The PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) guidelines were used.

RESULTS

A total of 2219 records were extracted, with only 55 records reporting on usability, user experiences, or behavioral approaches more widely for designing mHealth interventions in the context of AF. When mapping the studies onto the phases of the UK MRC's guidance for developing and evaluating complex interventions, the following was found: in the identification phase, there were significant differences between the needs of patients and health care workers. In the development phase, user perspectives guided the iterative development of apps, interfaces, and intervention protocols in 4 studies. Most studies (43/55, 78%) assessed the usability of interventions in the feasibility phase as an outcome, although the data collection tools were not designed together with users and stakeholders. Studies that examined the evaluation and implementation phase entailed reporting on challenges in user participation, acceptance, and workflows that could not be captured by studies in the previous phases. To realize the envisaged human behavior intended through treatment, review results highlight the scant inclusion of behavior change approaches for mHealth interventions across multiple levels of sociotechnical health care systems. While interventions at the level of the individual (micro) and the level of communities (meso) were found in the studies reviewed, no studies were found intervening at societal levels (macro). Studies also failed to consider the temporal variation of user goals and feedback in the design of long-term behavioral interventions.

CONCLUSIONS

In this systematic review, we proposed 2 contributions: first, mapping studies to different phases of the MRC framework for developing and evaluating complex interventions, and second, mapping behavioral approaches to different levels of health care systems. Finally, we discuss the wider implications of our results in guiding future mHealth research.

Utilizing technology for diet and exercise change in complex chronic conditions across diverse environments (U-DECIDE): feasibility randomised controlled trial

BACKGROUND

Diet and exercise are important components of treatment for complex chronic conditions, however access to allied health support is limited. When available, support is often siloed and fragmented. Digital health incorporating patient choice may help to align health care services with preferences and goals. This study evaluated the implementation of a ubiquitously accessible patient-centred digital health diet and exercise service.

METHODS

U-DECIDE was a single-centre, 26-week randomised controlled trial set in kidney and liver disease clinics in a tertiary hospital in Brisbane, Australia. Participants were adults with a complex chronic condition referred for dietetic consultation with at least one feature of the metabolic syndrome. All participants received a dietary consultation, an activity monitor and usual care. Intervention participants were offered one text message per week and access to additional digital health options (increased text message frequency, nutrition app, exercise app, group-based diet and/or exercise video consultations). The primary outcome of feasibility was determined by safety (study-related serious adverse events: SRSAEs), recruitment (≥ 50% eligible patients), retention (≥ 70%), exposure uptake (≥ 75% of intervention group had greater access to health professional contact than comparator) and video consultation adherence (≥ 80% attendance). Secondary outcomes included process evaluation metrics and clinical outcomes.

RESULTS

Of 67 participants (intervention n = 33, comparator n = 34), 37 (55%) were men, median (IQR) age was 51 (41-58) years. The most chosen digital health options were the nutrition app (n = 29, 88%) and exercise video consultations (n = 26, 79%). Only one participant chose no additional digital health options. The intervention group had no SRSAEs. The study exceeded targets for recruitment (52%), retention (81%) and exposure uptake (94%). Video consultation adherence was 42%. Engagement across digital health options was inconsistent.

CONCLUSIONS

Digital health options incorporating patient choice were feasible and can be offered to people with complex chronic disease as a service model option.

TRIAL REGISTRATION

Australia and New Zealand Trials Register: Trial Registration Number: ACTRN12620001282976. Registered 27th November 2020.

A Comprehensive Review of Behavior Change Techniques in Wearables and IoT: Implications for Health and Well-Being

This research paper delves into the effectiveness and impact of behavior change techniques fostered by information technologies, particularly wearables and Internet of Things (IoT) devices, within the realms of engineering and computer science. By conducting a comprehensive review of the relevant literature sourced from the Scopus database, this study aims to elucidate the mechanisms and strategies employed by these technologies to facilitate behavior change and their potential benefits to individuals and society. Through statistical measurements and related works, our work explores the trends over a span of two decades, from 2000 to 2023, to understand the evolving landscape of behavior change techniques in wearable and IoT technologies. A specific focus is placed on a case study examining the application of behavior change techniques (BCTs) for monitoring vital signs using wearables, underscoring the relevance and urgency of further investigation in this critical intersection of technology and human behavior. The findings shed light on the promising role of wearables and IoT devices for promoting positive behavior modifications and improving individuals' overall well-being and highlighting the need for continued research and development in this area to harness the full potential of technology for societal benefit.

Feasibility and Preliminary Effectiveness of the INSPIRE Pilot Study for Adolescent Girls

INTRODUCTION

This pilot study evaluated the feasibility and preliminary effectiveness of the Intervention to Support Physical Activity Independence and Routine Everyday program.

METHOD

This quasi-experimental single-group pretest/posttest study included adolescent girls (n = 15) who received a Fitbit Inspire 2 wearable activity tracker and participated in the seven-week Intervention to Support Physical Activity Independence and Routine Everyday program on a college campus in the Midwest. Feasibility outcomes included intervention participation, fidelity, and satisfaction. Preliminary effectiveness outcomes included moderate-to-vigorous physical activity, cardiorespiratory fitness, and resting heart rate.

RESULTS

For intervention sessions, the mean attendance rate was 83.42%, the mean minutes of moderate-to-vigorous physical activity was 62.03, and the mean satisfaction score was 28.90. Moderate-to-vigorous physical activity and resting heart rate improved significantly from baseline to postintervention, but cardiorespiratory fitness did not.

DISCUSSION

Results suggest the need for a pilot randomized controlled trial to improve cardiorespiratory fitness and incorporating an objective measure of moderate-to-vigorous physical activity.

Universal health coverage in China part 2: addressing challenges and recommendations

This report analyses the underlying causes of China's achievements and gaps in universal health coverage over the past 2 decades and proposes policy recommendations for advancing universal health coverage by 2030. Although strong political commitment and targeted financial investment have produced positive outcomes in reproductive, maternal, newborn, and child health and infectious diseases, a fragmented and hospital-centric delivery system, rising health-care costs, shallow benefit coverage of health insurance schemes, and little integration of health in all policies have restricted China's ability to effectively prevent and control chronic disease and provide adequate financial risk protection, especially for lower-income households. Here, we used a health system conceptual framework and we propose a set of feasible policy recommendations that draw from international experiences and first-hand knowledge of China's unique institutional landscape. Our six recommendations are: instituting a primary care-focused integrated delivery system that restructures provider incentives and accountability mechanisms to prioritise prevention; leveraging digital tools to support health behaviour change; modernising information campaigns; improving financial protection through insurance reforms; promoting a health in all policy; and developing a domestic monitoring framework with refined tracer indicators that reflects China's disease burden.

How Could Sensor-Based Measurement of Physical Activity Be Used in Cardiovascular Healthcare?

Physical activity and cardiovascular disease (CVD) are intimately linked. Low levels of physical activity increase the risk of CVDs, including myocardial infarction and stroke. Conversely, when CVD develops, it often reduces the ability to be physically active. Despite these largely understood relationships, the objective measurement of physical activity is rarely performed in routine healthcare. The ability to use sensor-based approaches to accurately measure aspects of physical activity has the potential to improve many aspects of cardiovascular healthcare across the spectrum of healthcare, from prediction, prevention, diagnosis, and treatment to disease monitoring. This review discusses the potential of sensor-based measurement of physical activity to augment current cardiovascular healthcare. We highlight many factors that should be considered to maximise the benefit and reduce the risks of such an approach. Because the widespread use of such devices in society is already a reality, it is important that scientists, clinicians, and healthcare providers are aware of these considerations.

Understanding Physical Activity Determinants in an HIV Self-Management Intervention: Qualitative Analysis Guided by the Theory of Planned Behavior

BACKGROUND

People living with HIV have long life expectancy and are experiencing more comorbid conditions, being at an increased risk for developing cardiovascular disease (CVD) and diabetes, further exacerbated due to the HIV or inflammatory process. One effective intervention shown to decrease mortality and improve health outcomes related to CVD and diabetes in people living with HIV is increased regular physical activity. However, people living with HIV often fall short of the daily recommended physical activity levels. While studies show that mobile health (mHealth) can potentially help improve people's daily activity levels and reduce mortality rates due to comorbid conditions, these studies do not specifically focus on people living with HIV. As such, it is essential to understand how mHealth interventions, such as wearables, can improve the physical activity of people living with HIV.

OBJECTIVE

This study aimed to understand participants' experiences wearing a fitness tracker and an app to improve their physical activity.

METHODS

In total, 6 focus groups were conducted with participants who completed the control arm of a 6-month randomized controlled trial (ClinicalTrials.gov NCT03205982). The control arm received daily walk step reminders to walk at least 5000 steps per day and focused on the overall wellness of the individual. The analysis of the qualitative focus groups used inductive content analysis using the theory of planned behavior as a framework to guide and organize the analysis.

RESULTS

In total, 41 people living with HIV participated in the focus groups. The majority (n=26, 63%) of participants reported their race as Black or African American, and 32% (n=13) of them identified their ethnicity as Hispanic or Latino. In total, 9 major themes were identified and organized following the theory of planned behavior constructs. Overall, 2 major themes (positive attitude toward tracking steps and tracking steps is motivating) related to attitudes toward the behavior, 2 major themes (social support or motivation from the fitness tracker and app and encouragement from family and friends) related to participant's subjective norms, 1 theme (you can adjust your daily habits with time) related to perceived behavioral control, 2 themes (reach their step goal and have a healthier lifestyle) related to participant's intention, and 2 themes (continuing to walk actively and regularly wearing the fitness tracker) related to participant's changed behavior. Participants highlighted how the mHealth interface with the avatar and daily step tracking motivated them to both begin and continue to engage in physical activity by adjusting their daily routines.

CONCLUSIONS

Findings from this study illustrate how features of mHealth apps may motivate people living with HIV to start and continue sustained engagement in physical activities. This sustained increase in physical activity is crucial for reducing the risk of comorbid conditions such as diabetes or CVD.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03205982; https://classic.clinicaltrials.gov/ct2/show/NCT03205982.

Impact of wearable device-based interventions with feedback for increasing daily walking activity and physical capacities in cardiovascular patients: a systematic review and meta-analysis of randomised controlled trials

OBJECTIVE

To systematically review randomised controlled trials (RCTs) using a wearable physical activity monitoring device as an intervention to increase daily walking activity and improve physical capacities in patients with cardiovascular disease (CVD).

DESIGN

Systematic review and meta-analysis of RCTs.

DATA SOURCES

PubMed, Embase and Web of Science from inception to June 2022.

ELIGIBILITY CRITERIA

Randomised controlled studies including patients with CVD over 18 years of age at the end of a cardiac rehabilitation programme comparing an intervention group using a wearable physical activity monitoring device with feedback with usual care or with a control group receiving no feedback on their physical activity and reporting a change in the daily number of steps and/or a change in the distance covered in the 6-minute walk test (6-MWT) or a change in peak oxygen uptake (V̇O2_peak) as endpoints.

RESULTS

Sixteen RCTs were included. The intervention of wearing a physical activity monitoring device with feedback significantly improved daily number of steps compared with controls (standardised mean difference (SMD) 0.85; 95% CI (0.42; 1.27); p<0.01). The effect was greater when the duration of the intervention was less than 3 months (SMD 1.0; 95% CI (0.18; 1.82); p<0.01) than when the duration of the intervention was 3 months or longer (SMD 0.71; 95% CI (0.27; 1.16); p<0.01), but no significant interaction was found between subgroups (p=0.55). 6-MWT distance and V̇O2_peak showed only small effects (SMD 0.34; 95% CI (-0.11; 0.80); p=0.02 and SMD 0.54; 95% CI (0.03; 1.03); p=0.07, respectively).

CONCLUSION

The use of wearable physical activity monitoring devices appears to help patients with CVD to increase their daily walking activity and thus their physical activity, particularly in the short term.

PROSPERO REGISTRATION NUMBER

CRD42022300423.

Acceptable, useful, and ineffective? Recent retirees’ experiences of a 12-month activity tracker-based physical activity intervention

Objective

Activity trackers appear cost-effective and acceptable intervention tools for promoting physical activity among older adults, particularly in the short-term. However, long-term studies focused on participants’ experiences continue to be scarce. This study evaluated participants’ experiences of a 12-month activity tracker-driven physical activity intervention.

Methods

Participants’ experiences were assessed qualitatively using open-ended questionnaire items ( n = 113) and semi-structured interviews conducted after the 12-month intervention ( n = 27). Quantitative items assessed the perceived ease-of-use and usefulness of the activity tracker during the intervention. Qualitative data was analyzed using thematic analysis and Wilcoxon signed-rank tests were used to examine changes in the perceived ease-of-use and usefulness over time.

Results

The 113 participants completing the 12-month intervention were on average 65.2 ( SD 1.0) years old and 81.4% women with 92.3% providing activity tracker data on at least 2 weeks per each intervention month. In the qualitative analysis, four main themes with 20 subthemes were identified: (a) burdens of participation, (b) affective attitudes of using the activity tracker, (c) perceived effects of using the activity tracker, and (d) no perceived behavioral effects. At 12 months, the participants found activity trackers mainly easy to use (mean 4.6, SD 0.6), reliable (mean 3.6, SD 1.2), motivating (mean 3.9, SD 1.0), and helpful in reducing sitting (mean 3.7, SD 1.0) with no changes observed during the intervention.

Conclusions

The participants’ experiences were highly varied suggesting that tailored intervention designs are likely to be required for effectively using activity trackers to promote long-term changes in daily activity among older adults.

The Use of Wearable Activity Trackers in Schools to Promote Child and Adolescent Physical Activity: A Descriptive Content Analysis of School Staff's Perspectives

BACKGROUND

The school environment is an ideal setting for promoting physical activity (PA). Wearable activity trackers (wearables) have previously been implemented, in research, as intervention tools within the school-environment. However, the large-scale use and acceptance of wearables, in schools, is unknown.

METHODS

This study distributed a cross-sectional survey to school staff to investigate the prevalence of child and adolescent wearable use in schools, including when and how they are used, and school staff's willingness to use them in the future (as implemented by school staff). This survey consisted of between 13 and 22 items, including closed-ended and open-ended questions. Closed-ended responses were displayed descriptively (wearable prevalence and characteristics), and open-ended qualitative responses were categorised using descriptive content analysis (how wearables are used).

RESULTS

1087 school staff provided valid responses. Of those, 896 (82.4%) had never used a wearable as a teaching or support tool for their students, and 120 (11%) currently used- and 71 (6.5%) had previously used- a wearable as a teaching or support tool for their students. When wearables were used, school staff implemented their use regularly and during physical education lessons or throughout the entire school day. Wearables were used to monitor or increase student's PA levels, or for student and staff educational purposes (e.g., academic learning, movement breaks). Most school staff were willing to use a wearable as a teaching or support tool to promote student's PA, and/or learning about PA, in the future.

CONCLUSIONS

This study is the first study to explore the widescale use and acceptance of children and adolescents using wearables in the school-setting. Findings may inform the development of future school-based interventions and public health initiatives for physical activity promotion, using wearables.

Activity tracker-based intervention to increase physical activity in patients with type 2 diabetes and healthy individuals: study protocol for a randomized controlled trial

BACKGROUND

One relevant strategy to prevent the onset and progression of type 2 diabetes mellitus (T2DM) focuses on increasing physical activity. The use of activity trackers by patients could enable objective measurement of their regular physical activity in daily life and promote physical activity through the use of a tracker-based intervention. This trial aims to answer three research questions: (1) Is the use of activity trackers suitable for longitudinal assessment of physical activity in everyday life? (2) Does the use of a tracker-based intervention lead to sustainable improvements in the physical activity of healthy individuals and in people with T2DM? (3) Does the accompanying digital motivational intervention lead to sustainable improvements in physical activity for participants using the tracker-based device?

METHODS

The planned study is a randomized controlled trial focused on 1642 participants with and without T2DM for 9 months with regard to their physical activity behavior. Subjects allocated to an intervention group will wear an activity tracker. Half of the subjects in the intervention group will also receive an additional digital motivational intervention. Subjects allocated to the control group will not receive any intervention. The primary outcome is the amount of moderate and vigorous physical activity in minutes and the number of steps per week measured continuously with the activity tracker and assessed by questionnaires at four time points. Secondary endpoints are medical parameters measured at the same four time points. The collected data will be analyzed using inferential statistics and explorative data-mining techniques.

DISCUSSION

The trial uses an interdisciplinary approach with a team including sports psychologists, sports scientists, health scientists, health care professionals, physicians, and computer scientists. It also involves the processing and analysis of large amounts of data collected with activity trackers. These factors represent particular strengths as well as challenges in the study.

TRIAL REGISTRATION

The trial is registered at the World Health Organization International Clinical Trials Registry Platform via the German Clinical Studies Trial Register (DRKS), DRKS00027064 . Registered on 11 November 2021.

Influence of upper limb activity on the step count and accuracy of sleep time of a wristband-type physical activity tracker

Background

A wristband-type consumer physical activity tracker (PAT) is commonly used in rehabilitation to assess an individual’s physical activity. However, under the free-living setting, the wristband-type PAT tends to overestimate step counts when compared with the research-standard criterion. Also, daily rhythm characteristics, such as sleep time, are difficult to monitor accurately based solely on self-reporting.

Purpose

To identify the conditions measured as step counts by a wristband-type consumer PAT when using the upper limbs in daily living, and the measurement accuracy of the sleeping time estimated from the wristband-type PAT.

Methods

Forty participants (20 females, mean age 32.65 ± 9.52 years) were enrolled in two experiments in this study. In Experiment 1, we measured the influence of upper limbs activity (movement speed and distance) on step counts of wristband-type and waist holder-type PAT in two upper limb tasks. In Experiment 2, we verified the measurement accuracy of two sleep times by wristband-type PAT using a self-reported survey for 3 days.

Results

The results of Experiment 1 revealed that the step counts using wristband-type PAT were influenced by upper limbs activity depending on movement distance (F (1, 19) = 31.705, p < 0.001) but not speed (F (1, 19) = 2.669, p < 0.117). Whereas, there was no relationship between step counts and upper limb activity in waist holder-type PAT. The results of Experiment 2 showed that the sleep times of wristband-type and self-report had a strong correlation (coefficient value = 0.93, p < 0.001).

Conclusions

This PAT is useful for capturing changes in the amount of physical activity and the daily rhythm within the individual. It can be expected to be used for rehabilitation support centered on upper limb activity and daily rhythm.

The effectiveness of physical activity interventions using activity trackers during or after inpatient care: a systematic review and meta-analysis of randomized controlled trials

BACKGROUND

Promoting physical activity (PA) in patients during and/or after an inpatient stay appears important but challenging. Interventions using activity trackers seem promising to increase PA and enhance recovery of physical functioning.

OBJECTIVE

To review the effectiveness of physical activity interventions using activity trackers on improving PA and physical functioning, compared to usual care in patients during and/or after inpatient care. In addition, it was determined whether the following intervention characteristics increase the effectiveness of these interventions: the number of behaviour change techniques (BCTs) used, the use of a theoretical model or the addition of coaching by a health professional.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

PubMed, EMBASE, Cinahl, SportDiscus and Web of Science databases were searched in March 2020 and updated in March 2021.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

Randomized controlled trials (RCTs) including interventions using activity trackers and feedback on PA in adult patients during, or less than 3 months after, hospitalization or inpatient rehabilitation.

METHODS

Following database search and title and abstract screening, articles were screened on full text for eligibility and then assessed for risk of bias by using the Physiotherapy Evidence Database (PEDro) scale. Meta-analyses, including subgroup analysis on intervention characteristics, were conducted for the outcomes PA and physical functioning.

RESULTS

Overall, 21 RCTs totalling 2355 patients were included. The trials covered a variety of clinical areas. There was considerable heterogeneity between studies. For the 13 studies that measured PA as an outcome variable(N = 1435), a significant small positive effect in favour of the intervention was found (standardized mean difference (SMD) = 0.34; 95%CI 0.12-0.56). For the 13 studies that measured physical functioning as an outcome variable (N = 1415) no significant effect was found (SMD = 0.09; 95%CI -0.02 - 0.19). Effectiveness on PA seems to improve by providing the intervention both during and after the inpatient period and by using a theoretical model, multiple BCTs and coaching by a health professional.

CONCLUSION

Interventions using activity trackers during and/or after inpatient care can be effective in increasing the level of PA. However, these improvements did not necessarily translate into improvements in physical functioning. Several intervention characteristics were found to increase the effectiveness of PA interventions.

TRIAL REGISTRATION

Registered in PROSPERO ( CRD42020175977 ) on March 23th, 2020.

Digital Companion Choice to Support Teachers' Stress Self-management: Systematic Approach Through Taxonomy Creation

BACKGROUND

There are thousands of digital companions designed for emotional well-being and stress, including websites, wearables, and smartphone apps. Although public evaluation frameworks and ratings exist, they do not facilitate digital companion choice based on contextual or individual information, such as occupation or personal management strategies.

OBJECTIVE

The aim of this study is to establish a process for creating a taxonomy to support systematic choice of digital companions for teachers' stress self-management.

METHODS

We used a 4-step study design. In step 1, we identified the dimension of stress self-management and strategic classifications. In step 2, we identified the dimension of the digital techniques and conceptual descriptions. In step 3, we created 6 criteria for the inclusion of digital companions. In step 4, we used the taxonomy framework created by steps 1 and 2 and populated it with digital companions for stress self-management, as identified in step 3.

RESULTS

First, in the dimension of stress self-management, we identified four classes of strategies: educational, physiological, cognitive, and social. Second, in the digital techniques dimension, we derived four conceptual descriptions for the digital companions' mechanisms of action: fostering reflection, suggesting treatment, peer-to-peer support, and entertainment. Third, we created six criteria for digital companion inclusion in the taxonomy: suitability, availability, evaluation, security, validity, and cost. Using the taxonomy framework and criteria, we populated it with digital companions for stress management ahead of presentation to teachers in a stress study workshop.

CONCLUSIONS

The elements of our approach can be generalized as principles for the creation of taxonomies for other occupations or conditions. Taxonomies such as this could be a valuable resource for individuals to understand which digital companion could be of help in their personal context.

The Effect of Commercial Activity Tracker Based Physical Activity Intervention on Body Composition and Cardiometabolic Health Among Recent Retirees

The REACT is a commercial activity tracker based intervention, which primarily aimed to increase physical activity. This study examines the secondary outcomes of the physical activity intervention on body composition and cardiometabolic health indicators. Overall 231 recently retired Finnish men and women [65.2 (SD 1.1) years, 83% women] took part to the study. The participants were randomized into intervention (n = 117) and control (n = 114) groups. The intervention group members used a commercial activity tracker (Polar Loop 2, Polar, Kempele, Finland) with a daily activity goal and inactivity alerts every day for 12 months. Controls received no intervention. Secondary health outcomes included body weight, fat mass, fat free mass, waist circumference, blood pressure, indicators of glucose and lipid metabolisms, and high-sensitivity C-reactive protein, and they were measured at baseline and at 12-months end point. Hierarchical linear mixed models were used to examine the differences between the groups over time, and no differences in the mean changes of the body composition and cardiometabolic health indicators between the groups were found (group*time interaction &gt;0.20 for all measures). Fat free mass, waist circumference, blood pressure, and low density lipoprotein levels decreased in both groups over the 12 months. These findings state that 1-year daily use of commercial activity tracker does not induce different cardiometabolic health effects when compared to the non-user controls among general population of recent retirees.

Smart wearable devices in cardiovascular care: where we are and how to move forward

Technological innovations reach deeply into our daily lives and an emerging trend supports the use of commercial smart wearable devices to manage health. In the era of remote, decentralized and increasingly personalized patient care, catalysed by the COVID-19 pandemic, the cardiovascular community must familiarize itself with the wearable technologies on the market and their wide range of clinical applications. In this Review, we highlight the basic engineering principles of common wearable sensors and where they can be error-prone. We also examine the role of these devices in the remote screening and diagnosis of common cardiovascular diseases, such as arrhythmias, and in the management of patients with established cardiovascular conditions, for example, heart failure. To date, challenges such as device accuracy, clinical validity, a lack of standardized regulatory policies and concerns for patient privacy are still hindering the widespread adoption of smart wearable technologies in clinical practice. We present several recommendations to navigate these challenges and propose a simple and practical 'ABCD' guide for clinicians, personalized to their specific practice needs, to accelerate the integration of these devices into the clinical workflow for optimal patient care.

Use of Fitbit Devices in Physical Activity Intervention Studies Across the Life Course: Narrative Review

BACKGROUND

Commercial off-the-shelf activity trackers (eg, Fitbit) allow users to self-monitor their daily physical activity (PA), including the number of steps, type of PA, amount of sleep, and other features. Fitbits have been used as both measurement and intervention tools. However, it is not clear how they are being incorporated into PA intervention studies, and their use in specific age groups across the life course is not well understood.

OBJECTIVE

This narrative review aims to characterize how PA intervention studies across the life course use Fitbit devices by synthesizing and summarizing information on device selection, intended use (intervention vs measurement tool), participant wear instructions, rates of adherence to device wear, strategies used to boost adherence, and the complementary use of other PA measures. This review provides intervention scientists with a synthesis of information that may inform future trials involving Fitbit devices.

METHODS

We conducted a search of the Fitabase Fitbit Research Library, a database of studies published between 2012 and 2018. Of the 682 studies available on the Fitabase research library, 60 interventions met the eligibility criteria and were included in this review. A supplemental search in PubMed resulted in the inclusion of 15 additional articles published between 2019 and 2020. A total of 75 articles were reviewed, which represented interventions conducted in childhood; adolescence; and early, middle, and older adulthood.

RESULTS

There was considerable heterogeneity in the use of Fitbit within and between developmental stages. Interventions for adults typically required longer wear periods, whereas studies on children and adolescents tended to have more limited device wear periods. Most studies used developmentally appropriate behavior change techniques and device wear instructions. Regardless of the developmental stage and intended Fitbit use (ie, measurement vs intervention tool), the most common strategies used to enhance wear time included sending participants reminders through texts or emails and asking participants to log their steps or synchronize their Fitbit data daily. The rates of adherence to the wear time criteria were reported using varying metrics. Most studies supplemented the use of Fitbit with additional objective or self-reported measures for PA.

CONCLUSIONS

Overall, the heterogeneity in Fitbit use across PA intervention studies reflects its relative novelty in the field of research. As the use of monitoring devices continues to expand in PA research, the lack of uniformity in study protocols and metrics of reported measures represents a major issue for comparability purposes. There is a need for increased transparency in the prospective registration of PA intervention studies. Researchers need to provide a clear rationale for the use of several PA measures and specify the source of their main PA outcome and how additional measures will be used in the context of Fitbit-based interventions.

A Home-Based Mobile Health Intervention to Replace Sedentary Time With Light Physical Activity in Older Cancer Survivors: Randomized Controlled Pilot Trial

Background

Older cancer survivors are at risk of the development or worsening of both age- and treatment-related morbidity. Sedentary behavior increases the risk of or exacerbates these chronic conditions. Light-intensity physical activity (LPA) is more common in older adults and is associated with better health and well-being. Thus, replacing sedentary time with LPA may provide a more successful strategy to reduce sedentary time and increase physical activity.

Objective

This study primarily aims to evaluate the feasibility, acceptability, and preliminary efficacy of a home-based mobile health (mHealth) intervention to interrupt and replace sedentary time with LPA (standing and stepping). The secondary objective of this study is to examine changes in objective measures of physical activity, physical performance, and self-reported quality of life.

Methods

Overall, 54 cancer survivors (aged 60-84 years) were randomized in a 1:1:1 allocation to the tech support intervention group, tech support plus health coaching intervention group, or waitlist control group. Intervention participants received a Jawbone UP2 activity monitor for use with their smartphone app for 13 weeks. Tech support and health coaching were provided via 5 telephone calls during the 13-week intervention. Sedentary behavior and physical activity were objectively measured using an activPAL monitor for 7 days before and after the intervention.

Results

Participants included survivors of breast cancer (21/54, 39%), prostate cancer (16/54, 30%), and a variety of other cancer types; a mean of 4.4 years (SD 1.6) had passed since their cancer diagnosis. Participants, on average, were 70 years old (SD 4.8), 55% (30/54) female, 24% (13/54) Hispanic, and 81% (44/54) overweight or obese. Malfunction of the Jawbone trackers occurred in one-third of the intervention group, resulting in enrollment stopping at 54 rather than the initial goal of 60 participants. Despite these technical issues, the retention in the intervention was high (47/54, 87%). Adherence was high for wearing the tracker (29/29, 100%) and checking the app daily (28/29, 96%) but low for specific aspects related to the sedentary features of the tracker and app (21%-25%). The acceptability of the intervention was moderately high (81%). There were no significant between-group differences in total sedentary time, number of breaks, or number of prolonged sedentary bouts. There were no significant between-group differences in physical activity. The only significant within-group change occurred within the health coaching group, which increased by 1675 daily steps (95% CI 444-2906; P=.009). This increase was caused by moderate-intensity stepping rather than light-intensity stepping (+15.2 minutes per day; 95% CI 4.1-26.2; P=.008).

Conclusions

A home-based mHealth program to disrupt and replace sedentary time with stepping was feasible among and acceptable to older cancer survivors. Future studies are needed to evaluate the optimal approach for replacing sedentary behavior with standing and/or physical activity in this population.

Trial Registration

ClinicalTrials.gov NCT03632694; https://clinicaltrials.gov/ct2/show/NCT03632694

The need for exercise sciences and an integrated response to COVID-19: A position statement from the international HL-PIVOT network

COVID-19 is one of the biggest health crises that the world has seen. Whilst measures to abate transmission and infection are ongoing, there continues to be growing numbers of patients requiring chronic support, which is already putting a strain on health care systems around the world and which may do so for years to come. A legacy of COVID-19 will be a long-term requirement to support patients with dedicated rehabilitation and support services. With many clinical settings characterized by a lack of funding and resources, the need to provide these additional services could overwhelm clinical capacity. This position statement from the Healthy Living for Pandemic Event Protection (HL-PIVOT) Network provides a collaborative blueprint focused on leading research and developing clinical guidelines, bringing together professionals with expertise in clinical services and the exercise sciences to develop the evidence base needed to improve outcomes for patients infected by COVID-19.

Deep CHORES: Estimating Hallmark Measures of Physical Activity Using Deep Learning

Wrist accelerometers for assessing hallmark measures of physical activity (PA) are rapidly growing with the advent of smartwatch technology. Given the growing popularity of wrist-worn accelerometers, there needs to be a rigorous evaluation for recognizing (PA) type and estimating energy expenditure (EE) across the lifespan. Participants (66% women, aged 20-89 yrs) performed a battery of 33 daily activities in a standardized laboratory setting while a tri-axial accelerometer collected data from the right wrist. A portable metabolic unit was worn to measure metabolic intensity. We built deep learning networks to extract spatial and temporal representations from the time-series data, and used them to recognize PA type and estimate EE. The deep learning models resulted in high performance; the F1 score was: 0.82, 0.81, and 95 for recognizing sedentary, locomotor, and lifestyle activities, respectively. The root mean square error was 1.1 (+/-0.13) for the estimation of EE.

Analysis of the Behavioral Change and Utility Features of Electronic Activity Monitors

The aim of this study was to perform a content analysis of electronic activity monitors that also evaluates utility features, code behavior change techniques included in the monitoring systems, and align the results with intervention functions of the Behaviour Change Wheel program planning model to facilitate informed device selection. Devices were coded for the implemented behavior change techniques and device features. Three trained coders each wore a monitor for at least 1 week from December 2019-April 2020. Apple Watch Nike, Fitbit Versa 2, Fitbit Charge 3, Fitbit Ionic-Adidas Edition, Garmin Vivomove HR, Garmin Vivosmart 4, Amazfit Bip, Galaxy Watch Active, and Withings Steel HR were reviewed. The monitors all paired with a phone/tablet, tracked exercise sessions, and were wrist-worn. On average, the monitors implemented 27 behavior change techniques each. Fitbit devices implemented the most behavior change techniques, including techniques related to the intervention functions: education, enablement, environmental restructuring, coercion, incentivization, modeling, and persuasion. Garmin devices implemented the second highest number of behavior change techniques, including techniques related to enablement, environmental restructuring, and training. Researchers can use these results to guide selection of electronic activity monitors based on their research needs.

Behavior Change Techniques in Wrist-Worn Wearables to Promote Physical Activity: Content Analysis

Background

Decreasing levels of physical activity (PA) increase the incidences of noncommunicable diseases, obesity, and mortality. To counteract these developments, interventions aiming to increase PA are urgently needed. Mobile health (mHealth) solutions such as wearable sensors (wearables) may assist with an improvement in PA.

Objective

The aim of this study is to examine which behavior change techniques (BCTs) are incorporated in currently available commercial high-end wearables that target users’ PA behavior.

Methods

The BCTs incorporated in 5 different high-end wearables (Apple Watch Series 3, Garmin Vívoactive 3, Fitbit Versa, Xiaomi Amazfit Stratos 2, and Polar M600) were assessed by 2 researchers using the BCT Taxonomy version 1 (BCTTv1). Effectiveness of the incorporated BCTs in promoting PA behavior was assessed by a content analysis of the existing literature.

Results

The most common BCTs were goal setting (behavior), action planning, review behavior goal(s), discrepancy between current behavior and goal, feedback on behavior, self-monitoring of behavior, and biofeedback. Fitbit Versa, Garmin Vívoactive 3, Apple Watch Series 3, Polar M600, and Xiaomi Amazfit Stratos 2 incorporated 17, 16, 12, 11, and 11 BCTs, respectively, which are proven to effectively promote PA.

Conclusions

Wearables employ different numbers and combinations of BCTs, which might impact their effectiveness in improving PA. To promote PA by employing wearables, we encourage researchers to develop a taxonomy specifically designed to assess BCTs incorporated in wearables. We also encourage manufacturers to customize BCTs based on the targeted populations.

Sensor technology for nursing research

BACKGROUND

Electronic sensors measuring biological and behavioral aspects of health and the environment are becoming ubiquitous and, with advances in data science and ehealth technology, provide opportunities for new inquiry and innovative approaches to nursing research.

PURPOSE

To conceptualize the use of sensor technology from the perspective of nursing science.

METHODS

This review reports the keynote presentation from the Expanding Science of Sensor Technology in Nursing Research Conference presented by the Council for Advancement of Nursing Science in 2019 FINDINGS: Electronic sensors enable collection, recording, and transmission of data in real time in real life settings, remote monitoring, self-monitoring, and communication between health care professionals and patients. A deliberative approach to selecting and applying electronic sensors and analyzing and interpreting the data is needed for successful research.

DISCUSSION

Electronic sensors have high potential to advance nursing science.

Sedentary Behavior and the Use of Wearable Technology: An Editorial

Globally, we continue to face a mounting issue of obesity combined with inactivity; sedentary behaviour is independently associated with poor health outcomes including disease and mortality. As such, exploring ways to try to reduce sedentary behaviour and decrease the risk of diseases is an important area of consideration. The role of wearable technology, such as fitness trackers, to encourage and subsequently increase physical activity is relatively well documented. These devices have been successful at encouraging populations to increase daily activity levels. While time being sedentary is often correlated with physical activity participation, this is not always the case. Therefore, it may be just as important to consider the activity an individual is not doing when evaluating health and well-being. This Editorial will summarize the importance of distinguishing between physical activity and sedentary behaviour. It will also discuss how wearable technology, in the form of fitness trackers, may be used to encourage someone to break up sedentary bouts more often. Finally, we will consider important future research directions.

The Length and Number of Sedentary Bouts Predict Fibrinogen Levels in Postmenopausal Women

Menopause is associated with adverse changes in coagulation homeostasis. We aimed to investigate the association between objectively measured sedentary behavior (SB) and SB bouts (i.e., number and length of SB bouts) vs. fibrinogen levels in post-menopausal women. Fifty-three post-menopausal women (age 59.8 ± 6.2 years, BMI 27.3 ± 4.4) wore a multisensory device (Sensewear Mini Armband, BodyMedia, Inc., Pittsburgh, PA) for 5 days, to measure SB and physical activity (PA). Blood samples were collected to measure serum fibrinogen. Fibrinogen was directly correlated with SB (r = −0.48, p < 0.01), lying down during awake time (r = −0.50, p < 0.01), and both medium (11–30 mins) and very long bouts (>1 h) of SB (r = −0.59, p < 0.01; r = −0.51, p < 0.01, respectively), and inversely correlated with moderate to vigorous-intensity physical activity (r = −0.39, p < 0.01). Furthermore, fibrinogen was also directly correlated with BMI (r = −0.28, p < 0.05). In postmenopausal women without prevalent cardiovascular disease, the number of prolonged and uninterrupted sedentary bouts is directly correlated with increased fibrinogen levels, regardless of PA and BMI. This result suggests the importance of delivering new strategies to counteract the increase of sedentariness and inactivity of the postmenopausal population.

Consumer Perceptions of Wearable Technology Devices: Retrospective Review and Analysis

Background

Individuals of all ages are becoming more health conscious, and wearable technology devices (eg, Fitbit and Apple Watch) are becoming increasingly popular in encouraging healthy lifestyles.

Objective

The aim of this paper was to explore how consumers use wearable devices.

Methods

A retrospective review was done on the top-rated verified purchase reviews of the Fitbit One posted on Amazon.com between January 2014 and August 2018. Relevant themes were identified by qualitatively analyzing open-ended reviews.

Results

On retrieval, there were 9369 reviews with 7706 positive reviews and 1663 critical reviews. The top 100 positive and top 100 critical comments were subsequently analyzed. Four major themes were identified: sleep hygiene (“charts when you actually fall asleep, when you wake up during the night, when you're restless--and gives you a cumulative time of “actual sleep” as well as weekly averages.”), motivation (“25 lbs lost after 8 months – best motivator ever!”), accountability (“platform to connect with people you know and set little competitions or group…fun accountability if you set a goal with a friend/family.”), and discretion (“able to be clipped to my bra without being seen.”). Alternatively, negative reviewers felt that the wearable device’s various tracking functions, specifically steps and sleep, were inaccurate.

Conclusions

Wearable technology devices are an affordable, user-friendly application that can support all individuals throughout their everyday lives and potentially be implemented into medical surveillance, noninvasive medical care, and mobile health and wellness monitoring. This study is the first to explore wearable technology device use among consumers, and further studies are needed to examine the limitless possibilities of wearable devices in health care.