Effectiveness of wearable activity trackers to increase physical activity and improve health: a systematic review of systematic reviews and meta-analyses

Age Unplugged: A Brief Narrative Review on the Intersection of Digital Tools, Sedentary and Physical Activity Behaviors in Community-Dwelling Older Adults

This brief narrative review assesses how digital technologies-such as wearables, mobile health apps, and various digital tools such as computers, game consoles, tablets, smartphones, and extended reality systems-can influence sedentary and physical activity behaviors among community-dwelling older adults. Each section highlights the central role of these technologies in promoting active aging through increased motivation, engagement and customized experiences. It underlines the critical importance of functionality, usability and adaptability of devices and confirms the effectiveness of digital interventions in increasing physical activity and reducing sedentary behavior. The sustainable impact of these technologies needs to be further investigated, with a focus on adapting digital health strategies to the specific needs of older people. The research advocates an interdisciplinary approach and points out that such collaborations are essential for the development of accessible, effective and ethical solutions. This perspective emphasizes the potential of digital tools to improve the health and well-being of the aging population and recommends their strategic integration into health promotion and policy making.

Validating the Fitbit Charge 4© wearable activity monitor for use in physical activity interventions

OBJECTIVES

Commercially available wearable activity monitors can promote physical activity behaviour. Clinical trials typically quantify physical activity with research grade activity monitors prior to testing interventions utilising commercially available wearable activity monitors aimed at increasing step count. Therefore, it is important to test the agreement of these two types of activity monitors.

OBJECTIVES

Observational.

METHODS

Thirty adults (20-65 years, n = 19 females) were provided a Fitbit Charge 4©. To determine reliability using an intraclass correlation coefficient, two, one-minute bouts of treadmill walking were performed at a self-selected pace. Subsequently, participants wore both an ActiGraph wGT3X-BT and the Fitbit for seven days. To determine agreement, statistical equivalence and the mean absolute percentage error were calculated and represented graphically with a Bland-Altman plot. Ordinary least products regression was performed to identify fixed or proportional bias.

RESULTS

The Fitbit showed 'good' step count reliability on the treadmill (intraclass correlation coefficient = 0.75, 95 % CI = 0.53-0.87, p < 0.001). In free-living however, it overestimated step count when compared to the ActiGraph wGT3X-BT (mean absolute percentage error = 26.02 % ± 14.63). Measurements did not fall within the ± 10 % equivalence region and proportional bias was apparent (slope 95 % CI = 1.09-1.35).

CONCLUSIONS

The Fitbit Charge 4© is reliable when measuring step count on a treadmill. However, there is an overestimation of daily steps in free-living environments which may falsely indicate compliance with physical activity recommendations.

Exploring the impact of socially assistive robots on health and wellbeing across the lifespan: An umbrella review and meta-analysis

BACKGROUND

Socially assistive robots offer an alternate source of connection for interventions within health and social care amidst a landscape of technological advancement and reduced staff capacity. There is a need to summarise the available systematic reviews on the health and wellbeing impacts to evaluate effectiveness, explore potential moderators and mediators, and identify recommendations for future research and practice.

OBJECTIVE

To explore the effect of socially assistive robots within health and social care on psychosocial, behavioural, and physiological health and wellbeing outcomes across the lifespan (PROSPERO registration number: CRD42023423862).

DESIGN

An umbrella review utilising meta-analysis, narrative synthesis, and vote counting by direction of effect.

METHODS

14 databases were searched (ProQuest Health Research Premium collection, Scopus, PubMed, Web of Science, ASM Digital Library, IEEE Xplore, Cochrane Reviews, and EPISTEMONIKOS) from 2005 to May 4, 2023. Systematic reviews including the effects of socially assistive robots on health outcomes were included and a pooled meta-analysis, vote counting by direction of effect, and narrative synthesis were applied. The second version of A MeaSurement Tool to Assess systematic Reviews (AMSTAR-2) was applied to assess quality of included reviews.

RESULTS

35 reviews were identified, most focusing on older adults with or without dementia (n = 24). Pooled meta-analysis indicated no effect of socially assistive robots on quality of life (standard mean difference (SMD) = 0.43), anxiety (SMD = -0.02), or depression (SMD = 0.21), although vote counting identified significant improvements in social interaction, mood, positive affect, loneliness, stress, and pain across the lifespan, and narrative synthesis identified an improvement in anxiety in children. However, some reviews reported no significant difference between the effects of socially assistive robots and a plush toy, and there was no effect of socially assistive robots on psychiatric outcomes including agitation, neuropsychiatric symptoms, and medication use.

DISCUSSION

Socially assistive robots show promise for improving non-psychiatric outcomes such as loneliness, positive affect, stress, and pain, but exert no effect on psychiatric outcomes such as depression and agitation. The main mechanism of effect within group settings appeared to be the stimulation of social interaction with other humans. Limitations include the low quality and high amount of overlap between included reviews.

CONCLUSION

Socially assistive robots may help to improve loneliness, social interaction, and positive affect in older adults, decrease anxiety and distress in children, and improve mood, stress, and reduce pain across the lifespan. However, before recommendations for socially assistive robots can be made, a cost-effectiveness analysis of socially assistive robots to improve mood across the lifespan, and a quantitative analysis of the effects on pain, anxiety, and distress in children are required.

Patient-perceived factors influencing physical activity sensor use in stroke prevention and rehabilitation: A thematic synthesis protocol

INTRODUCTION

While the putative benefits of "fitness trackers" continue to fuel a booming consumer market, results of device-based clinical interventions remain remarkably mixed. This study will explore factors influencing wearable physical activity (PA) sensor use in the context of stroke prevention and rehabilitation for older adults. The findings of this thematic synthesis will provide insights into factors influencing the use of PA sensors in stroke which may inform more effective device-based interventions.

METHODS AND ANALYSIS

Thematic synthesis as a formal method described by Thomas and Arden can be used within a systematic review to synthesize primary qualitative research. Accordingly, the proposed study will systematically search bibliographic databases for relevant peer-reviewed papers and synthesize coded thematic data within included papers. The quality of papers will be assessed using the JBI Critical Appraisal Checklist for Qualitative Research. Patterns in the text will be coded, preliminary data visualised, and higher-level analytical themes discerned to explain factors influencing the use of PA sensors in older stroke patients.

DISCUSSION

This study does not require ethics approval. Results are expected to be available by June 2024. Data from the thematic synthesis will provide insights into barriers and facilitators influencing the use of wearable PA sensors in stroke and older adults at risk, and implications these factors have for the design of effective device-based interventions.

TRIAL REGISTRATION

Systematic review registration: PROSPERO registration number: CRD42020211472. https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020211472.

Physical activity and sedentary behavior levels among individuals with mental illness: A cross-sectional study from 23 countries

People with mental illness tend to present low levels of physical activity and high levels of sedentary behavior. The study aims to compare these levels in mental illness patients, exploring the role of socioeconomic development and treatment setting. This cross-sectional study used accelerometers and the Simple Physical Activity Questionnaire (SIMPAQ) to assess physical activity and sedentary behavior in mental illness individuals living in 23 countries. Two-way ANOVAs were used to evaluate the interaction between socioeconomic development and the treatment settings on physical activity and sedentary behavior. A total of 884 (men = 55.3%) participants, mean age of 39.3 (SD = 12.8), were evaluated. A significant interaction between socioeconomic development and treatment settings was found in sedentary behavior (F = 5.525; p = 0.019; η2p = 0.009; small effect size). Main effects were observed on socioeconomic development (F = 43.004; p < 0.001; η2p = 0.066; medium effect size) and treatment setting (F = 23.001; p < 0.001; η2p = 0.036; small effect size) for sedentary behavior and physical activity: socioeconomic development (F = 20.888; p < 0.001; η2p = 0.033; small effect size) and treatment setting (F = 30.358; p < 0.001; η2p = 0.047; small effect size), showing that HIC patients were more active, while MIC patients were more sedentary. Moreover, despite of inpatients had presented higher levels of physical activity than outpatients, they also spent more time sitting. Socioeconomic development plays an important role in sedentary behavior in patients with mental disorders, warning the need to develop new strategies to reduce these levels in this population.

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.

Association Between Wearable Device Use and Quality of Life in Patients With Idiopathic Inflammatory Myopathies and Primary Systemic Vasculitis

Background Despite the increasing use of wearable devices worldwide, concise data on these instruments in patients with systemic autoimmune rheumatic diseases, including idiopathic inflammatory myopathies (IIM) and primary systemic vasculitis (PSV), are lacking. Objectives The aim of this study is to investigate the knowledge and use of wearable devices and to assess their impact on the general quality of life of patients with IIM and PSV. Moreover, we compared these characteristics between patients with IIM and PSV users and non-users of wearable devices. Methods This single-center, cross-sectional study was conducted between January 2023 and June 2023. We included adult patients with IIM and PSV and a control group (CTR) and evaluated their use of cell phones and wearables, level of physical activity, and quality of life. Results A total of 132 patients with IIM, 82 with PSV, and 178 in the CTR were evaluated. Overall, 169 patients and 144 in the CTR were aware of wearable devices, of whom 50 (29.6%) and 47 (32.6%), respectively, had already used this technology. In addition, the IPAQ-Mets and EQ-5D scores were lower in the IIM and PSV groups than in the CTR, and the fatigue severity scale (FSS) scores were higher in the IIM and PSV groups than in the CTR. Patients who used the devices showed FSS scores of 29 (18-40) points, with higher levels of IPAQ-Mets among device users, indicating greater physical activity than among nonusers. Conclusion Based on the results, the use of wearable devices is associated with better fatigue and IPAQ scores. Possibly, the use of such devices can have an impact on better lifestyle habits among these patients.

[Wearables in rheumatology]

As a result of digitalization in medicine wearable computing devices (wearables) are becoming increasingly more important. Wearables are small portable electronic devices with which the user can record data relevant to health, such as number of steps, activity profile, electrocardiogram (ECG), heart and breathing frequency or oxygen saturation. Initial studies on the use of wearables in patients with rheumatological diseases show the opening up of new possibilities for prevention, disease monitoring and treatment. This study provides the current data situation and the implementation of wearables in the discipline of rheumatology. Additionally, future potential fields of application as well as challenges and limits of the implementation of wearables are illustrated.

E-Tattoos: Toward Functional but Imperceptible Interfacing with Human Skin

The human body continuously emits physiological and psychological information from head to toe. Wearable electronics capable of noninvasively and accurately digitizing this information without compromising user comfort or mobility have the potential to revolutionize telemedicine, mobile health, and both human-machine or human-metaverse interactions. However, state-of-the-art wearable electronics face limitations regarding wearability and functionality due to the mechanical incompatibility between conventional rigid, planar electronics and soft, curvy human skin surfaces. E-Tattoos, a unique type of wearable electronics, are defined by their ultrathin and skin-soft characteristics, which enable noninvasive and comfortable lamination on human skin surfaces without causing obstruction or even mechanical perception. This review article offers an exhaustive exploration of e-tattoos, accounting for their materials, structures, manufacturing processes, properties, functionalities, applications, and remaining challenges. We begin by summarizing the properties of human skin and their effects on signal transmission across the e-tattoo-skin interface. Following this is a discussion of the materials, structural designs, manufacturing, and skin attachment processes of e-tattoos. We classify e-tattoo functionalities into electrical, mechanical, optical, thermal, and chemical sensing, as well as wound healing and other treatments. After discussing energy harvesting and storage capabilities, we outline strategies for the system integration of wireless e-tattoos. In the end, we offer personal perspectives on the remaining challenges and future opportunities in the field.

Effect of a coaching intervention to enhance physical activity and prevent falls in community-dwelling people aged 60+ years: a cluster randomised controlled trial

OBJECTIVES

To evaluate the effect of a coaching intervention compared with control on physical activity and falls rate at 12 months in community-dwelling people aged 60+ years.

DESIGN

Cluster randomised controlled trial.

SETTING

Community-dwelling older people.

PARTICIPANTS

72 clusters (605 participants): 37 clusters (290 participants) randomised to the intervention and 35 (315 participants) to control.

INTERVENTION

Intervention group received written information, fall risk assessment and prevention advice by a physiotherapist, activity tracker and telephone-based coaching from a physiotherapist focused on safe physical activity. Control group received written information and telephone-based dietary coaching. Both groups received up to 19 sessions of telephone coaching over 12 months.

OUTCOMES

The co-primary outcomes were device-measured physical activity expressed in counts per minute at 12 months and falls rate over 12 months. Secondary outcomes included the proportion of fallers, device-measured daily steps and moderate-to-vigorous physical activity (MVPA), self-reported hours per week of physical activity, body mass index, eating habits, goal attainment, mobility-related confidence, quality of life, fear of falling, risk-taking behaviour, mood, well-being and disability.

RESULTS

The mean age of participants was 74 (SD 8) years, and 70% (n=425) were women. There was no significant effect of the intervention on device-measured physical activity counts per minute (mean difference 5 counts/min/day, 95% CI -21 to 31), or falls at 12 months (0.71 falls/person/year in intervention group and 0.87 falls/person/year in control group; incidence rate ratio 0.86, 95% CI 0.65 to 1.14). The intervention had a positive significant effect on device-measured daily steps and MVPA, and self-reported hours per week of walking, well-being, quality of life, and disability. No significant between-group differences were identified in other secondary outcomes.

CONCLUSION

A physical activity and fall prevention programme including fall risk assessment and prevention advice, plus telephone-based health coaching, did not lead to significant differences in physical activity counts per minute or falls rate at 12 months. However, this programme improved other physical activity measures (ie, daily steps, MVPA, hours per week of walking), overall well-being, quality of life and disability.

TRIAL REGISTRATION NUMBER

ACTRN12615001190594.

Association Between Physical Activity and the Risk of Burnout in Health Care Workers: Systematic Review

BACKGROUND

Burnout is a multidimensional psychological syndrome that arises from chronic workplace stress. Health care workers (HCWs), who operate in physically and emotionally exhausting work contexts, constitute a vulnerable group. This, coupled with its subsequent impact on patients and public economic resources, makes burnout a significant public health concern. Various self-care practices have been suggested to have a positive effect on burnout among HCWs. Of these, physical activity stands out for its ability to combine psychological, physiological, and biochemical mechanisms. In fact, it promotes psychological detachment from work and increases self-efficacy by inhibiting neurotransmitters and neuromodulators, increasing endorphin levels, enhancing mitochondrial function, and attenuating the hypothalamic pituitary-adrenal axis response to stress.

OBJECTIVE

Our objective was to conduct a systematic review of the evidence on the association between physical activity and burnout among HCWs.

METHODS

We considered HCWs, physical activity, and burnout, framing them as population, exposure, and outcome, respectively. We searched APA PsycArticles, MEDLINE, and Scopus until July 2022. We extracted relevant data on study design, methods to measure exposure and outcome, and statistical approaches.

RESULTS

Our analysis encompassed 21 independent studies. Although 10% (2/21) of the studies explicitly focused on physical activity, the remaining investigations were exploratory in nature and examined various predictors, including physical activity. The most commonly used questionnaire was the Maslach Burnout Inventory. Owing to the heterogeneity in definitions and cutoffs used, the reported prevalence of burnout varied widely, ranging from 7% to 83%. Heterogeneity was also observed in the measurement tools used to assess physical activity, with objective measures rarely used. In total, 14% (3/21) of the studies used structured questionnaires to assess different types of exercise, whereas most studies (18/21, 86%) only recorded the attainment of a benchmark or reported the frequency, intensity, or duration of exercise. The reported prevalence of physically active HCWs ranged from 44% to 87%. The analyses, through a variety of inferential approaches, indicated that physical activity is often associated with a reduced risk of burnout, particularly in the domains of emotional exhaustion and depersonalization. Furthermore, we compiled and classified a list of factors associated with burnout.

CONCLUSIONS

Our comprehensive overview of studies investigating the association between physical activity and burnout in HCWs revealed significant heterogeneity in definitions, measurements, and analyses adopted in the literature. To address this issue, it is crucial to adopt a clear definition of physical activity and make thoughtful choices regarding measurement tools and methodologies for data analysis. Our considerations regarding the measurement of burnout and the comprehensive list of associated factors have the potential to improve future studies aimed at informing decision-makers, thus laying the foundation for more effective management measures to address burnout.

The Wearable Activity Tracker Checklist for Healthcare (WATCH): a 12-point guide for the implementation of wearable activity trackers in healthcare

Increasing physical activity in patients offers dual benefits, fostering improved patient health and recovery, while also bolstering healthcare system efficiency by minimizing costs related to extended hospital stays, complications, and readmissions. Wearable activity trackers offer valuable opportunities to enhance physical activity across various healthcare settings and among different patient groups. However, their integration into healthcare faces multiple implementation challenges related to the devices themselves, patients, clinicians, and systemic factors. This article presents the Wearable Activity Tracker Checklist for Healthcare (WATCH), which was recently developed through an international Delphi study. The WATCH provides a comprehensive framework for implementation and evaluation of wearable activity trackers in healthcare. It covers the purpose and setting for usage; patient, provider, and support personnel roles; selection of relevant metrics; device specifications; procedural steps for issuance and maintenance; data management; timelines; necessary adaptations for specific scenarios; and essential resources (such as education and training) for effective implementation. The WATCH is designed to support the implementation of wearable activity trackers across a wide range of healthcare populations and settings, and in those with varied levels of experience. The overarching goal is to support broader, sustained, and systematic use of wearable activity trackers in healthcare, therefore fostering enhanced physical activity promotion and improved patient outcomes.

Development of a multi-wear-site, deep learning-based physical activity intensity classification algorithm using raw acceleration data

BACKGROUND

Accelerometers are widely adopted in research and consumer devices as a tool to measure physical activity. However, existing algorithms used to estimate activity intensity are wear-site-specific. Non-compliance to wear instructions may lead to misspecifications. In this study, we developed deep neural network models to classify device placement and activity intensity based on raw acceleration data. Performances of these models were evaluated by making comparisons to the ground truth and results derived from existing count-based algorithms.

METHODS

54 participants (26 adults 26.9±8.7 years; 28 children, 12.1±2.3 years) completed a series of activity tasks in a laboratory with accelerometers attached to each of their hip, wrist, and chest. Their metabolic rates at rest and during activity periods were measured using the portable COSMED K5; data were then converted to metabolic equivalents, and used as the ground truth for activity intensity. Deep neutral networks using the Long Short-Term Memory approach were trained and evaluated based on raw acceleration data collected from accelerometers. Models to classify wear-site and activity intensity, respectively, were evaluated.

RESULTS

The trained models correctly classified wear-sites and activity intensities over 90% of the time, which outperformed count-based algorithms (wear-site correctly specified: 83% to 85%; wear-site misspecified: 64% to 75%). When additional parameters of age, height and weight of participants were specified, the accuracy of some prediction models surpassed 95%.

CONCLUSIONS

Results of the study suggest that accelerometer placement could be determined prospectively, and non-wear-site-specific algorithms had satisfactory accuracies. The performances, in terms of intensity classification, of these models also exceeded typical count-based algorithms. Without being restricted to one specific wear-site, research protocols for accelerometers wear could allow more autonomy to participants, which may in turn improve their acceptance and compliance to wear protocols, and in turn more accurate results.

Assessing cardiorespiratory fitness in clinical and community settings: Lessons and advancements in the 100th year anniversary of VO2max

Cardiorespiratory fitness (CRF) is a well-established biomarker that has applications to all adults across the health and disease spectrum. Despite overwhelming evidence supporting the prognostic utility of CRF, it remains vastly underutilized. CRF is optimally measured via cardiopulmonary exercise testing which may not be feasible to implement on a large scale. Therefore, it is prudent to develop ways to accurately estimate CRF that can be applied in clinical and community settings. As such, several prediction equations incorporating non-exercise information that is readily available from routine clinical encounters have been developed that provide an adequate reflection of CRF that could be implemented to raise awareness of the importance of CRF. Further, technological advances in smartphone apps and consumer-grade wearables have demonstrated promise to provide reasonable estimates of CRF that are widely available, which could enhance the utilization of CRF in both clinical and community settings.

The current state of physical activity assessment and interventions with public policy solutions

Currently, assessing physical activity (PA) and cardiorespiratory fitness in healthcare settings and supporting patients on their journey toward active living is not a standard of practice in the US, although significant progress is underway. This paper summarizes the foundational as well as supporting public policies necessary to make PA assessment, prescription, and referral a standard of care in the US healthcare system to support active living for all. Measure standardization and healthcare integration will be supported by digital health and public private partnerships, as well as payer strategies and quality and performance incentives. The policy and systems change effort, currently being led by the Physical Activity Alliance's "It's Time to Move" initiative, will improve patient care and the ability to monitor PA levels across the US population, filling in gaps in current national public health surveillance systems. Having patient data available will also allow for additional research that elucidates the relationship between PA and overall health and well-being.

Effects of eHealth Interventions on 24-Hour Movement Behaviors Among Preschoolers: Systematic Review and Meta-Analysis

BACKGROUND

The high prevalence of unhealthy movement behaviors among young children remains a global public health issue. eHealth is considered a cost-effective approach that holds great promise for enhancing health and related behaviors. However, previous research on eHealth interventions aimed at promoting behavior change has primarily focused on adolescents and adults, leaving a limited body of evidence specifically pertaining to preschoolers.

OBJECTIVE

This review aims to examine the effectiveness of eHealth interventions in promoting 24-hour movement behaviors, specifically focusing on improving physical activity (PA) and sleep duration and reducing sedentary behavior among preschoolers. In addition, we assessed the moderating effects of various study characteristics on intervention effectiveness.

METHODS

We searched 6 electronic databases (PubMed, Ovid, SPORTDiscus, Scopus, Web of Science, and Cochrane Central Register of Controlled Trials) for experimental studies with a randomization procedure that examined the effectiveness of eHealth interventions on 24-hour movement behaviors among preschoolers aged 2 to 6 years in February 2023. The study outcomes included PA, sleep duration, and sedentary time. A meta-analysis was conducted to assess the pooled effect using a random-effects model, and subgroup analyses were conducted to explore the potential effects of moderating factors such as intervention duration, intervention type, and risk of bias (ROB). The included studies underwent a rigorous ROB assessment using the Cochrane ROB tool. Moreover, the certainty of evidence was evaluated using the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) assessment.

RESULTS

Of the 7191 identified records, 19 (0.26%) were included in the systematic review. The meta-analysis comprised a sample of 2971 preschoolers, which was derived from 13 included studies. Compared with the control group, eHealth interventions significantly increased moderate to vigorous PA (Hedges g=0.16, 95% CI 0.03-0.30; P=.02) and total PA (Hedges g=0.37, 95% CI 0.02-0.72; P=.04). In addition, eHealth interventions significantly reduced sedentary time (Hedges g=-0.15, 95% CI -0.27 to -0.02; P=.02) and increased sleep duration (Hedges g=0.47, 95% CI 0.18-0.75; P=.002) immediately after the intervention. However, no significant moderating effects were observed for any of the variables assessed (P>.05). The quality of evidence was rated as "moderate" for moderate to vigorous intensity PA and sedentary time outcomes and "low" for sleep outcomes.

CONCLUSIONS

eHealth interventions may be a promising strategy to increase PA, improve sleep, and reduce sedentary time among preschoolers. To effectively promote healthy behaviors in early childhood, it is imperative for future studies to prioritize the development of rigorous comparative trials with larger sample sizes. In addition, researchers should thoroughly examine the effects of potential moderators. There is also a pressing need to comprehensively explore the long-term effects resulting from these interventions.

TRIAL REGISTRATION

PROSPERO CRD42022365003; http://tinyurl.com/3nnfdwh3.

Barriers and facilitators to smartwatch-based prehabilitation participation among frail surgery patients: a qualitative study

BACKGROUND

For older, frail adults, exercise before surgery through prehabilitation (prehab) may hasten return recovery and reduce postoperative complications. We developed a smartwatch-based prehab program (BeFitMe) for older adults that encourages and tracks at-home exercise. The objective of this study was to assess patient perceptions about facilitators and barriers to prehab generally and to using a smartwatch prehab program among older adult thoracic surgery patients to optimize future program implementation.

METHODS

We recruited patients, aged ≥50 years who had or were having surgery and were screened for frailty (Fried's Frailty Phenotype) at a thoracic surgery clinic at a single academic institution. Semi-structured interviews were conducted by telephone after obtaining informed consent. Participants were given a description of the BeFitMe program. The interview questions were informed by The Five "Rights" of Clinical Decision-Making framework (Information, Person, Time, Channel, and Format) and sought to identify the factors perceived to influence smartwatch prehab program participation. Interview transcripts were transcribed and independently coded to identify themes in for each of the Five "Rights" domains.

RESULTS

A total of 29 interviews were conducted. Participants were 52% men (n = 15), 48% Black (n = 14), and 59% pre-frail (n = 11) or frail (n = 6) with a mean age of 68 ± 9 years. Eleven total themes emerged. Facilitator themes included the importance of providers (right person) clearly explaining the significance of prehab (right information) during the preoperative visit (right time); providing written instructions and exercise prescriptions; and providing a preprogrammed and set-up (right format) Apple Watch (right channel). Barrier themes included pre-existing conditions and disinterest in exercise and/or technology. Participants provided suggestions to overcome the technology barrier, which included individualized training and support on usage and responsibilities.

CONCLUSIONS

This study reports the perceived facilitators and barriers to a smartwatch-based prehab program for pre-frail and frail thoracic surgery patients. The future BeFitMe implementation protocol must ensure surgical providers emphasize the beneficial impact of participating in prehab before surgery and provide a written prehab prescription; must include a thorough guide on smartwatch use along with the preprogrammed device to be successful. The findings are relevant to other smartwatch-based interventions for older adults.

Applications of digital health approaches for cardiometabolic diseases prevention and management in the Western Pacific region

Cardiometabolic diseases (CMDs) are the major types of non-communicable diseases, contributing to huge disease burdens in the Western Pacific region (WPR). The use of digital health (dHealth) technologies, such as wearable gadgets, mobile apps, and artificial intelligence (AI), facilitates interventions for CMDs prevention and treatment. Currently, most studies on dHealth and CMDs in WPR were conducted in a few high- and middle-income countries like Australia, China, Japan, the Republic of Korea, and New Zealand. Evidence indicated that dHealth services promoted early prevention by behavior interventions, and AI-based innovation brought automated diagnosis and clinical decision-support. dHealth brought facilitators for the doctor-patient interplay in the effectiveness, experience, and communication skills during healthcare services, with rapidly development during the pandemic of coronavirus disease 2019. In the future, the improvement of dHealth services in WPR needs to gain more policy support, enhance technology innovation and privacy protection, and perform cost-effectiveness research.

Steps per day and health-related quality of life in schoolchildren: the mediator role of cardiorespiratory fitness

To analyse the relationship between steps per day and health-related quality of life (HRQoL) and cardiorespiratory fitness (CRF) and to examine whether the relationship between steps per day and HRQoL is mediated by CRF in schoolchildren. This was a cross-sectional study including 501 schoolchildren (aged 9-12 years, 47% girls), from Cuenca, Spain. Steps per day were measured using the Xiaomi Mi Band 3 Smart Bracelet, HRQoL was estimated by the KIDSCREEN-27 questionnaire, and CRF was assessed using the 20-m shuttle run test. Analysis of covariance and multivariate analysis of covariance models showed that children with a higher mean number of steps per day (> 9000 steps/day) had better HRQoL (global score, and physical and psychological well-being) and higher CRF levels than their peers with a lower number of steps per day (p < 0.05); however, these differences were no longer significant when controlling for sex, age, mother's education level, and CRF (p > 0.05). Linear regression models estimated that each 1000-step increment was associated with better CRF (β = 0.350; 95% CI, 0.192 to 0.508). In addition, the relationship between steps per day and HRQoL was mediated by CRF (p < 0.05).    Conclusion: Steps per day are a good metric to estimate daily physical activity because of its positive relationship with CRF. Moreover, those children taking more than 9000 steps per day are associated with higher levels of physical and psychological well-being. Finally, a substantial part of the improvement in HRQoL achieved through the increase in physical activity (steps per day) is mediated by CRF. What is Known: • Physical activity is known to have a positive impact on health-related quality of life in children. Steps per day are commonly used as a measure of physical activity. • Cardiorespiratory fitness is a recognized indicator of overall health in youth. What is New: • Increments of steps per day were associated with better CRF, with a nonlinear association after approximately 9000 steps/day. • Schoolchildren with > 9000 steps/ day showed better HRQoL.

Physical Activity Intervention Characteristics and Effects on Behavioral and Health-Related Outcomes Among Adolescents and Young Adults Living with and Beyond Cancer: A Systematic Review

Participation in physical activity (PA) during and after cancer treatment is safe and beneficial in the adolescent and young adult (AYA) cancer population. PA can positively impact health-related outcomes; however, participation remains low. This systematic review aims to describe PA intervention characteristics and outcomes in AYA survivors of cancer (AYASCa). This review followed Preferred Reporting Index for Systematic Reviews and Meta Analyses (PRISMA) guidelines and was registered with Prospero (CRD42022365661). PubMed, CINAHL, and Scopus databases were searched for randomized control trials (RCTs) and pre/post-test studies without a control group through December 31, 2022. Data included: participant demographics, PA intervention characteristics, and health-related outcomes. Studies were assessed using the National Institute of Health Critical Appraisal Tools, and findings were synthesized to identify common characteristics of PA interventions and outcomes. Twenty-three studies were included: 15 RCTs and 8 pre/post-test studies. Heterogeneity existed across design, sample demographics, intervention timing, and observed outcomes. The most common characteristics of PA interventions were supervision of PA, wearable device use, tailored/individualized PA prescriptions, and goal setting. PA interventions positively affected health-related outcomes, with 21 studies reporting statistically significant findings. Implementing personalized PA prescriptions, utilizing wearable devices, and incorporating goal setting as characteristics in PA interventions hold potential benefits for AYASCa, leading to improved outcomes. Still, additional research is needed to explore interventions that utilize these PA characteristics and determine which ones are most effective for AYASCa. By further investigating and identifying optimal PA characteristics, interventions can be better tailored to meet this population's specific needs and preferences, ultimately enhancing their overall well-being and recovery.

Wearable Devices to Improve Physical Activity and Reduce Sedentary Behaviour: An Umbrella Review

BACKGROUND

Several systematic reviews (SRs), with and without meta-analyses, have investigated the use of wearable devices to improve physical activity, and there is a need for frequent and updated syntheses on the topic.

OBJECTIVE

We aimed to evaluate whether using wearable devices increased physical activity and reduced sedentary behaviour in adults.

METHODS

We conducted an umbrella review searching PubMed, Cumulative Index to Nursing and Allied Health Literature, the Cochrane Library, MedRxiv, Rxiv and bioRxiv databases up to February 5th, 2023. We included all SRs that evaluated the efficacy of interventions when wearable devices were used to measure physical activity in adults aged over 18 years. The primary outcomes were physical activity and sedentary behaviour measured as the number of steps per day, minutes of moderate to vigorous physical activity (MVPA) per week, and minutes of sedentary behaviour (SB) per day. We assessed the methodological quality of each SR using the Assessment of Multiple Systematic Reviews, version 2 (AMSTAR 2) and the certainty of evidence of each outcome measure using the GRADE (Grading of Recommendations, Assessment, Development, and Evaluations). We interpreted the results using a decision-making framework examining the clinical relevance and the concordances or discordances of the SR effect size.

RESULTS

Fifty-one SRs were included, of which 38 included meta-analyses (302 unique primary studies). Of the included SRs, 72.5% were rated as 'critically low methodological quality'. Overall, with a slight overlap of primary studies (corrected cover area: 3.87% for steps per day, 3.12% for MVPA, 4.06% for SB) and low-to-moderate certainty of the evidence, the use of WDs may increase PA by a median of 1,312.23 (IQR 627-1854) steps per day and 57.8 (IQR 37.7 to 107.3) minutes per week of MVPA. Uncertainty is present for PA in pathologies and older adults subgroups and for SB in mixed and older adults subgroups (large confidence intervals).

CONCLUSIONS

Our findings suggest that the use of WDs may increase physical activity in middle-aged adults. Further studies are needed to investigate the effects of using WDs on specific subgroups (such as pathologies and older adults) in different follow-up lengths, and the role of other intervention components.

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.

Impact of a wearable-based physical activity and sleep intervention in multimorbidity patients: protocol for a randomized controlled trial

BACKGROUND

The benefits of physical activity (PA) and adequate sleep are well documented, and their importance strengthens with the increasing prevalence of chronic diseases and multimorbidity (MM). Interventions to promote physical activity and sleep that use commercial activity trackers may be useful non-pharmacological approaches to managing individual health; however, limited evidence exists on their use to improve physical activity in older adult patients with MM.

METHODS

This study aims to measure the effects of behavioral change techniques (BCTs) delivered by a wearable device on physical activity and quality of sleep (QS) in older adult patients with MM. We designed an open-label randomized controlled trial with participants recruited through primary care and a specialist outpatient clinic. Participants must be more than 65 years old, have MM, and have access to smartphones. All eligible participants will receive PA promotion content and will be randomly assigned to wear a smartwatch. The primary outcome will be the participants' PA measurement at baseline and at six months using the International Physical Activity Questionnaire - Short Form (IPAQ-SF). Secondary outcomes will include changes in the participants' frailty status, biometric measurements, quality of life, and biopsychosocial assessments. A sample size of 40 participants per arm was calculated to detect group differences, with 50 participants planned to recruit and randomize into each arm.

DISCUSSION

This study aims to contribute to a better understanding of PA patterns and the impact of wearable-based PA interventions in patients with MM. In addition, we aim to contribute to more knowledge about the relationship between PA patterns, Patient Reported Outcomes Measures (PROMs), and healthcare resource utilization in patients with MM. To achieve this, the study will leverage a locally developed PROMs registry and assess data from participants' medical records, in order to understand the added impact of wearable data and medical information data on predicting PROMs and unplanned hospital admissions.

TRIAL REGISTRATION

NCT05777291.

Implementation of Remote Activity Sensing to Support a Rehabilitation Aftercare Program: Observational Mixed Methods Study With Patients and Health Care Professionals

BACKGROUND

Physical activity is central to maintaining the quality of life for patients with complex chronic conditions and is thus at the core of neurorehabilitation. However, maintaining activity improvements in daily life is challenging. The novel Stay With It program aims to promote physical activity after neurorehabilitation by cultivating self-monitoring skills and habits.

OBJECTIVE

We examined the implementation of the Stay With It program at the Valens Rehabilitation Centre in Switzerland using the normalization process theory framework, focusing on 3 research aims. We aimed to examine the challenges and facilitators of program implementation from the perspectives of patients and health care professionals. We aimed to evaluate the potential of activity sensors to support program implementation and patient acceptance. Finally, we aimed to evaluate patients' engagement in physical activity after rehabilitation, patients' self-reported achievement of home activity goals, and factors influencing physical activity.

METHODS

Patients were enrolled if they had a disease that was either chronic or at risk for chronicity and participated in the Stay With It program. Patients were assessed at baseline, the end of rehabilitation, and a 3-month follow-up. The health care professionals designated to deliver the program were surveyed before and after program implementation. We used a mixed methods approach combining standardized questionnaires, activity-sensing data (patients only), and free-text questions.

RESULTS

This study included 23 patients and 13 health care professionals. The diverse needs of patients and organizational hurdles were major challenges to program implementation. Patients' intrinsic motivation and health care professionals' commitment to refining the program emerged as key facilitators. Both groups recognized the value of activity sensors in supporting program implementation and sustainability. Although patients appreciated the sensor's ability to monitor, motivate, and quantify activity, health care professionals saw the sensor as a motivational tool but expressed concerns about technical difficulties and potential inaccuracies. Physical activity levels after patients returned home varied considerably, both within and between individuals. The self-reported achievement of activity goals at home also varied, in part because of vague definitions. Common barriers to maintaining activity at home were declining health and fatigue often resulting from heat and pain. At the 3-month follow-up, 35% (8/23) of the patients withdrew from the study, with most citing deteriorating physical health as the reason and that monitoring and discussing their low activity would negatively affect their mental health.

CONCLUSIONS

Integrating aftercare programs like Stay With It into routine care is vital for maintaining physical activity postrehabilitation. Although activity trackers show promise in promoting motivation through monitoring, they may lead to frustration during health declines. Their acceptability may also be influenced by an individual's health status, habits, and technical skills. Our study highlights the importance of considering health care professionals' perspectives when integrating new interventions into routine care.

Effectiveness of holistic mobile health interventions on diet, and physical, and mental health outcomes: a systematic review and meta-analysis

Background

Good physical and mental health are essential for healthy ageing. Holistic mobile health (mHealth) interventions-including at least three components: physical activity, diet, and mental health-could support both physical and mental health and be scaled to the population level. This review aims to describe the characteristics of holistic mHealth interventions and their effects on related behavioural and health outcomes among adults from the general population.

Methods

In this systematic review and meta-analysis, we searched MEDLINE, Embase, Cochrane Central Register of Controlled Trials, PsycINFO, Scopus, China National Knowledge Infrastructure, and Google Scholar (first 200 records). The initial search covered January 1, 2011, to April 13, 2022, and an updated search extended from April 13, 2022 to August 30, 2023. Randomised controlled trials (RCTs) and non-randomised studies of interventions (NRSIs) were included if they (i) were delivered via mHealth technologies, (ii) included content on physical activity, diet, and mental health, and (iii) targeted adults (≥18 years old) from the general population or those at risk of non-communicable diseases (NCDs) or mental disorders. Studies were excluded if they targeted pregnant women (due to distinct physiological responses), individuals with pre-existing NCDs or mental disorders (to emphasise prevention), or primarily utilised web, email, or structured phone support (to focus on mobile technologies without exclusive human support). Data (summary data from published reports) extraction and risk-of-bias assessment were completed by two reviewers using a standard template and Cochrane risk-of-bias tools, respectively. Narrative syntheses were conducted for all studies, and random-effects models were used in the meta-analyses to estimate the pooled effect of interventions for outcomes with comparable data in the RCTs. The study was registered in PROSPERO, CRD42022315166.

Findings

After screening 5488 identified records, 34 studies (25 RCTs and 9 pre-post NRSIs) reported in 43 articles with 5691 participants (mean age 39 years, SD 12.5) were included. Most (91.2%, n = 31/34) were conducted in high-income countries. The median intervention duration was 3 months, and only 23.5% (n = 8/34) of studies reported follow-up data. Mobile applications, short-message services, and mobile device-compatible websites were the most common mHealth delivery modes; 47.1% (n = 16/34) studies used multiple mHealth delivery modes. Of 15 studies reporting on weight change, 9 showed significant reductions (6 targeted on individuals with overweight or obesity), and in 10 studies reporting perceived stress levels, 4 found significant reductions (all targeted on general adults). In the meta-analysis, holistic mHealth interventions were associated with significant weight loss (9 RCTs; mean difference -1.70 kg, 95% CI -2.45 to -0.95; I2 = 89.00%) and a significant reduction in perceived stress levels (6 RCTs; standardised mean difference [SMD] -0.32; 95% CI -0.52 to -0.12; I2 = 14.52%). There were no significant intervention effects on self-reported moderate-to-vigorous physical activity (5 RCTs; SMD 0.21; 95%CI -0.25 to 0.67; I2 = 74.28%) or diet quality scores (5 RCTs; SMD 0.21; 95%CI -0.47 to 0.65; I2 = 62.27%). All NRSIs were labelled as having a serious risk of bias overall; 56% (n = 14/25) of RCTs were classified as having some concerns, and the others as having a high risk of bias.

Interpretation

Findings from identified studies suggest that holistic mHealth interventions may aid reductions in weight and in perceived stress levels, with small to medium effect sizes. The observed effects on diet quality scores and self-reported moderate-to-vigorous physical activity were less clear and require more research. High-quality RCTs with longer follow-up durations are needed to provide more robust evidence. To promote population health, future research should focus on vulnerable populations and those in middle- and low-income countries. Optimal combinations of delivery modes and components to improve efficacy and sustain long-term effects should also be explored.

Funding

National Research Foundation, Prime Minister's Office, Singapore, under its Campus for Research Excellence and Technological Enterprise (CREATE) Programme and Physical Activity and Nutrition Determinants in Asia (PANDA) Research Programme.

Obesity Management in Adults: A Review

Importance

Obesity affects approximately 42% of US adults and is associated with increased rates of type 2 diabetes, hypertension, cardiovascular disease, sleep disorders, osteoarthritis, and premature death.

Observations

A body mass index (BMI) of 25 or greater is commonly used to define overweight, and a BMI of 30 or greater to define obesity, with lower thresholds for Asian populations (BMI ≥25-27.5), although use of BMI alone is not recommended to determine individual risk. Individuals with obesity have higher rates of incident cardiovascular disease. In men with a BMI of 30 to 39, cardiovascular event rates are 20.21 per 1000 person-years compared with 13.72 per 1000 person-years in men with a normal BMI. In women with a BMI of 30 to 39.9, cardiovascular event rates are 9.97 per 1000 person-years compared with 6.37 per 1000 person-years in women with a normal BMI. Among people with obesity, 5% to 10% weight loss improves systolic blood pressure by about 3 mm Hg for those with hypertension, and may decrease hemoglobin A1c by 0.6% to 1% for those with type 2 diabetes. Evidence-based obesity treatment includes interventions addressing 5 major categories: behavioral interventions, nutrition, physical activity, pharmacotherapy, and metabolic/bariatric procedures. Comprehensive obesity care plans combine appropriate interventions for individual patients. Multicomponent behavioral interventions, ideally consisting of at least 14 sessions in 6 months to promote lifestyle changes, including components such as weight self-monitoring, dietary and physical activity counseling, and problem solving, often produce 5% to 10% weight loss, although weight regain occurs in 25% or more of participants at 2-year follow-up. Effective nutritional approaches focus on reducing total caloric intake and dietary strategies based on patient preferences. Physical activity without calorie reduction typically causes less weight loss (2-3 kg) but is important for weight-loss maintenance. Commonly prescribed medications such as antidepressants (eg, mirtazapine, amitriptyline) and antihyperglycemics such as glyburide or insulin cause weight gain, and clinicians should review and consider alternatives. Antiobesity medications are recommended for nonpregnant patients with obesity or overweight and weight-related comorbidities in conjunction with lifestyle modifications. Six medications are currently approved by the US Food and Drug Administration for long-term use: glucagon-like peptide receptor 1 (GLP-1) agonists (semaglutide and liraglutide only), tirzepatide (a glucose-dependent insulinotropic polypeptide/GLP-1 agonist), phentermine-topiramate, naltrexone-bupropion, and orlistat. Of these, tirzepatide has the greatest effect, with mean weight loss of 21% at 72 weeks. Endoscopic procedures (ie, intragastric balloon and endoscopic sleeve gastroplasty) can attain 10% to 13% weight loss at 6 months. Weight loss from metabolic and bariatric surgeries (ie, laparoscopic sleeve gastrectomy and Roux-en-Y gastric bypass) ranges from 25% to 30% at 12 months. Maintaining long-term weight loss is difficult, and clinical guidelines support the use of long-term antiobesity medications when weight maintenance is inadequate with lifestyle interventions alone.

Conclusion and Relevance

Obesity affects approximately 42% of adults in the US. Behavioral interventions can attain approximately 5% to 10% weight loss, GLP-1 agonists and glucose-dependent insulinotropic polypeptide/GLP-1 receptor agonists can attain approximately 8% to 21% weight loss, and bariatric surgery can attain approximately 25% to 30% weight loss. Comprehensive, evidence-based obesity treatment combines behavioral interventions, nutrition, physical activity, pharmacotherapy, and metabolic/bariatric procedures as appropriate for individual patients.

Wearable technology interventions in patients with chronic obstructive pulmonary disease: a systematic review and meta-analysis

Chronic obstructive pulmonary disease (COPD) is the third leading cause of death and is associated with multiple medical and psychological comorbidities. Therefore, future strategies to improve COPD management and outcomes are needed for the betterment of patient care. Wearable technology interventions offer considerable promise in improving outcomes, but prior reviews fall short of assessing their role in the COPD population. In this systematic review and meta-analysis we searched ovid-MEDLINE, ovid-EMBASE, CINAHL, CENTRAL, and IEEE databases from inception to April 2023 to identify studies investigating wearable technology interventions in an adult COPD population with prespecified outcomes of interest including physical activity promotion, increasing exercise capacity, exacerbation detection, and quality-of-life. We identified 7396 studies, of which 37 were included in our review. Meta-analysis showed wearable technology interventions significantly increased: the mean daily step count (mean difference (MD) 850 (494-1205) steps/day) and the six-minute walk distance (MD 5.81 m (1.02-10.61 m). However, the impact was short-lived. Furthermore, wearable technology coupled with another facet (such as health coaching or pulmonary rehabilitation) had a greater impact that wearable technology alone. Wearable technology had little impact on quality-of-life measures and had mixed results for exacerbation avoidance and prediction. It is clear that wearable technology interventions may have the potential to form a core part of future COPD management plans, but further work is required to translate this into meaningful clinical benefit.

Technical Assistance Received by Older Adults to Use Commercially Available Physical Activity Monitors (Ready Steady 3.0 Trial): Ad-Hoc Descriptive Longitudinal Study

Background

Despite evidence that regular physical activity (PA) among older adults confers numerous health and functional benefits, PA participation rates are low. Using commercially available wearable PA monitors (PAMs) is one way to augment PA promotion efforts. However, while expert recommendations exist for the specific information needed at the beginning of PAM ownership and the general ongoing need for structures that support as-needed technical troubleshooting, information is lacking about the type, frequency, and modes of assistance needed during initial and long-term ownership.

Objective

This paper describes problems reported and technical assistance received by older adults who used PAMs during the 18 months they participated in a community-based PA trial: Ready Steady 3.0 (RS3).

Methods

This was an ad-hoc longitudinal analysis of process variables representing technical problems reported and assistance received by 113 RS3 study participants in the 18 months after their orientation to PAMs. Variables included date of contact, problem(s) reported, mode of technical assistance, and whether the equipment was replaced. The descriptive analysis included frequencies and incidence rates of distinct contacts, types of problems, and technical assistance modes.

Results

On average, participants were aged 77 (SD 5.2) years. Most identified as female (n=87, 77%), reported experience using smartphones (n=92, 81.4%), and used the PAM between 2 and 18 months. Eighty-two participants (72.6%) reported between 1 to 9 problems with using PAMs, resulting in a total of 150 technical assistance contacts with a mean of 1.3 (SD 1.3) contacts. The incidence rate of new, distinct contacts for technical assistance was 99 per 100 persons per year from 2018 to 2021. The most common problems were wearing the PAM (n=43, 28.7%), reading its display (n=23, 15.3%), logging into its app (n=20, 13.3%), charging it (n=18, 12%), and synchronizing it to the app (n=16, 10.7%). The modalities of technical assistance were in person (n=53, 35.3%), by telephone (n=51, 34%), by email (n=25, 16.7%), and by postal mail (n=21, 14%).

Conclusions

In general, the results of this study show that after receiving orientation to PAMs, problems such as uncomfortable wristbands, difficulty using the PAM or its related app, and obtaining or interpreting relevant personal data were occasionally reported by participants in RS3. Trained staff helped participants troubleshoot and solve these technical problems primarily in person or by phone. Results also underscore the importance of involving older adults in the design, usability testing, and supportive material development processes to prevent technical problems for the initial and ongoing use of PAMs. Clinicians and researchers should further assess technical assistance needed by older adults, accounting for variations in PAM models and wear time, while investigating additional assistance strategies, such as proactive support, short GIF videos, and video calls.

Use Patterns of Smartphone Apps and Wearable Devices Supporting Physical Activity and Exercise: Large-Scale Cross-Sectional Survey

Background

Physical inactivity is a global health issue, and mobile health (mHealth) apps are expected to play an important role in promoting physical activity. Empirical studies have demonstrated the efficacy and efficiency of app-based interventions, and an increasing number of apps with more functions and richer content have been released. Regardless of the success of mHealth apps, there are important evidence gaps in the literature; that is, it is largely unknown who uses what app functions and which functions are associated with physical activity.

Objective

This study aims to investigate the use patterns of apps and wearables supporting physical activity and exercise in a Japanese-speaking community sample.

Methods

We recruited 20,573 web-based panelists who completed questionnaires concerning demographics, regular physical activity levels, and use of apps and wearables supporting physical activity. Participants who indicated that they were using a physical activity app or wearable were presented with a list of app functions (eg, sensor information, goal setting, journaling, and reward), among which they selected any functions they used.

Results

Approximately one-quarter (n=4465) of the sample was identified as app users and showed similar demographic characteristics to samples documented in the literature; that is, compared with app nonusers, app users were younger (odds ratio [OR] 0.57, 95% CI 0.50-0.65), were more likely to be men (OR 0.83, 95% CI 0.77-0.90), had higher BMI scores (OR 1.02, 95% CI 1.01-1.03), had higher levels of education (university or above; OR 1.528, 95% CI 1.19-1.99), were more likely to have a child (OR 1.16, 95% CI 1.05-1.28) and job (OR 1.28, 95% CI 1.17-1.40), and had a higher household income (OR 1.40, 95% CI 1.21-1.62). Our results revealed unique associations between demographic variables and specific app functions. For example, sensor information, journaling, and GPS were more frequently used by men than women (ORs <0.84). Another important finding is that people used a median of 2 (IQR 1-4) different functions within an app, and the most common pattern was to use sensor information (ie, self-monitoring) and one other function such as goal setting or reminders.

Conclusions

Regardless of the current trend in app development toward multifunctionality, our findings highlight the importance of app simplicity. A set of two functions (more precisely, self-monitoring and one other function) might be the minimum that can be accepted by most users. In addition, the identified individual differences will help developers and stakeholders pave the way for the personalization of app functions.

Rates of compliance and adherence to high-intensity interval training: a systematic review and Meta-analyses

BACKGROUND

To determine rates of compliance (i.e., supervised intervention attendance) and adherence (i.e., unsupervised physical activity completion) to high-intensity interval training (HIIT) among insufficiently active adults and adults with a medical condition, and determine whether compliance and adherence rates were different between HIIT and moderate-intensity continuous training (MICT).

METHODS

Articles on adults in a HIIT intervention and who were either insufficiently active or had a medical condition were included. MEDLINE, EMBASE, PsychINFO, SPORTDiscus, CINAHL, and Web of Science were searched. Article screening and data extraction were completed by two independent reviewers. Risk of bias was assessed using RoB 2.0 or ROBINS-I. Meta-analyses were conducted to discern differences in compliance and adherence between HIIT vs. MICT. Sensitivity analyses, publication bias, sub-group analyses, and quality appraisal were conducted for each meta-analysis.

RESULTS

One hundred eighty-eight unique studies were included (n = 8928 participants). Compliance to HIIT interventions averaged 89.4% (SD:11.8%), while adherence to HIIT averaged 63% (SD: 21.1%). Compliance and adherence to MICT averaged 92.5% (SD:10.6%) and 68.2% (SD:16.2%), respectively. Based on 65 studies included in the meta-analysis, compliance rates were not different between supervised HIIT and MICT interventions [Hedge's g = 0.015 (95%CI: - 0.088-0.118), p = .78]. Results were robust and low risk of publication bias was detected. No differences were detected based on sub-group analyses comparing medical conditions or risk of bias of studies. Quality of the evidence was rated as moderate over concerns in the directness of the evidence. Based on 10 studies, adherence rates were not different between unsupervised HIIT and MICT interventions [Hedge's g = - 0.313 (95%CI: - 0.681-0.056), p = .096]. Sub-group analysis points to differences in adherence rates dependent on the method of outcome measurement. Adherence results should be interpreted with caution due to very low quality of evidence.

CONCLUSIONS

Compliance to HIIT and MICT was high among insufficiently active adults and adults with a medical condition. Adherence to HIIT and MICT was relatively moderate, although there was high heterogeneity and very low quality of evidence. Further research should take into consideration exercise protocols employed, methods of outcome measurement, and measurement timepoints.

REGISTRATION

This review was registered in the PROSPERO database and given the identifier CRD42019103313.

Modeling personalized heart rate response to exercise and environmental factors with wearables data

Heart rate (HR) response to workout intensity reflects fitness and cardiorespiratory health. Physiological models have been developed to describe such heart rate dynamics and characterize cardiorespiratory fitness. However, these models have been limited to small studies in controlled lab environments and are challenging to apply to noisy-but ubiquitous-data from wearables. We propose a hybrid approach that combines a physiological model with flexible neural network components to learn a personalized, multidimensional representation of fitness. The physiological model describes the evolution of heart rate during exercise using ordinary differential equations (ODEs). ODE parameters are dynamically derived via a neural network connecting personalized representations to external environmental factors, from area topography to weather and instantaneous workout intensity. Our approach efficiently fits the hybrid model to a large set of 270,707 workouts collected from wearables of 7465 users from the Apple Heart and Movement Study. The resulting model produces fitness representations that accurately predict full HR response to exercise intensity in future workouts, with a per-workout median error of 6.1 BPM [4.4-8.8 IQR]. We further demonstrate that the learned representations correlate with traditional metrics of cardiorespiratory fitness, such as VO2 max (explained variance 0.81 ± 0.003). Lastly, we illustrate how our model is naturally interpretable and explicitly describes the effects of environmental factors such as temperature and humidity on heart rate, e.g., high temperatures can increase heart rate by 10%. Combining physiological ODEs with flexible neural networks can yield interpretable, robust, and expressive models for health applications.

Harnessing technology and gamification to increase adult physical activity: a cluster randomized controlled trial of the Columbia Moves pilot

BACKGROUND

The use of health technologies and gamification to promote physical activity has increasingly been examined, representing an opportunistic method for harnessing social support inherent within existing social ties. However, these prior studies have yielded mixed findings and lacked long-term follow-up periods. Thus, a pilot cluster randomized controlled trial was conducted to gauge the feasibility and preliminary efficacy of a digital gamification-based physical activity promotion approach among teams of insufficiently active adults with existing social ties.

METHODS

Teams (N = 24; 116 total participants) were randomized to either a 12-week intervention (Fitbit, step goals, app, feedback; TECH) or the same program plus gamification (TECH + Gamification). Mixed effects models were used to compare group differences in treatment adherence, and changes in social support, steps, and moderate-to-vigorous physical activity at 12 weeks and 52 weeks from baseline, adjusted for sociodemographic characteristics and team size.

RESULTS

TECH had a lower mean number of days of Fitbit self-monitoring versus TECH + Gamification during the intervention (adjusted difference: -.30; 95% CI, -.54 to -.07; P = .01). Post-intervention, TECH had 47% lower odds of self-monitoring 7 days per week versus TECH + Gamification (.53; 95% CI, .31 to .89; P = .02). No differences were observed between TECH + Gamification and TECH in increases in social support (0.04; 95% CI, -.21 to .29; P = .76), ActiGraph-measured daily steps (-425; 95% CI, -1065 to 215; P = .19), or moderate-to-vigorous physical activity minutes (-3.36; 95% CI, -8.62 to 1.91; P = .21) from baseline to 12 weeks or in the regression of these improvements by 1 year (Ps > .05). Although not significant in the adjusted models (Ps > .05), clinically meaningful differences in Fitbit-measured daily steps (TECH, 7041 ± 2520; TECH + Gamification, 7988 ± 2707) and active minutes (TECH, 29.90 ± 29.76; TECH + Gamification, 36.38 ± 29.83) were found during the intervention.

CONCLUSIONS

A gamified physical activity intervention targeting teams of adults with existing social ties was feasible and facilitated favorable, clinically meaningful additive physical activity effects while in place but did not drive enhanced, long-term physical activity participation. Future investigations should explore optimal team dynamics and more direct ways of leveraging social support (training teams; gamifying social support).

TRIAL REGISTRATION

Clinicaltrials.gov ( NCT03509129 , April 26, 2018).

Mobile Health and Preventive Medicine

Wearable devices providing health-related data (mobile health [mHealth]) have grown in numbers and types of data available over the past 2 decades. Applications in prevention with some of the longest track records are activity trackers to promote fitness (primary prevention), mobile electrocardiogram devices to detect arrhythmias (secondary prevention), and continuous glucose monitoring to improve glycemic control in type 2 diabetes (tertiary prevention). Continued integration of multiple diverse data streams and improved interfaces with individuals (such as artificial intelligence-driven health coaches), and health care teams (as in the hospital-at-home concept), promise to optimize use of mHealth to improve clinical and public health outcomes.

Views and experiences of healthcare practitioners supporting people with COPD who have used activity monitors: "More than just steps"

INTRODUCTION

Activity monitors (apps and wearables) are increasingly used by the general population, including people with Chronic Obstructive Pulmonary Disease (COPD). There is potential for activity monitors to support increases in physical activity for people with COPD and healthcare practitioners (HCPs) are likely to be key in supporting their use, but little is currently known about HCPs' views or experiences. This qualitative research aimed to explore HCPs' views and experiences of supporting people with COPD who have used activity monitors.

METHODS

Seventeen semi-structured telephone or online interviews were conducted with HCPs between September 2020 and May 2021. HCPs included two nurses, an occupational therapist, a physician, and 13 physiotherapists. Participants were recruited via social media advertisements. They all had experience of supporting people with COPD who had used activity monitors. Interviews were analysed using reflexive thematic analysis.

FINDINGS

Four themes were developed highlighting the challenges and benefits of HCPs supporting patients with using activity monitors and utilising patient-collected activity data; 1) Skills and experience are needed to increase accessibility and engagement, 2) Objectively monitored physical activity can support exercise prescription, 3) Applications of activity monitors vary across different settings, and 4) Support is needed for future use of activity monitors.

DISCUSSION

HCPs recognised the potential for activity monitors to impact patients' ability to self-manage their COPD. However, there is a lack of guidance and information to support integration within practice. Future research is needed to co-develop information and guidelines for people with COPD and HCPs.

The use of commercial wrist-worn technology to track physiological outcomes in behavioral interventions

PURPOSE OF REVIEW

The aim of this review is to provide an overview of the use of commercial wrist-worn mobile health devices to track and monitor physiological outcomes in behavioral interventions as well as discuss considerations for selecting the optimal device.

RECENT FINDINGS

Wearable technology can enhance intervention design and implementation. The use of wrist-worn wearables provides the opportunity for tracking physiological outcomes, thus providing a unique approach for assessment and delivery of remote interventions. Recent findings support the utility, acceptability, and benefits of commercial wrist-worn wearables in interventions, and they can be used to continuously monitor outcomes, remotely administer assessments, track adherence, and personalize interventions. Wrist-worn devices show acceptable accuracy when measuring heart rate, blood pressure, step counts, and physical activity; however, accuracy is dependent on activity type, intensity, and device brand. These factors should be considered when designing behavioral interventions that utilize wearable technology.

SUMMARY

With the continuous advancement in technology and frequent product upgrades, the capabilities of commercial wrist-worn devices will continue to expand, thus increasing their potential use in intervention research. Continued research is needed to examine and validate the most recent devices on the market to better inform intervention design and implementation.

Mapping physical activity patterns in hospitalised patients with moderate to severe acquired brain injury - MAP-ABI: Protocol for an observational study

Introduction

The physical activity level in patients hospitalised for rehabilitation across multiple diagnoses is low. Moderate to severe acquired brain injury further reduces activity levels as impaired physical and cognitive functioning affect mobility independence. Therefore, supervised out-of-bed mobilisation and physical activity training are essential rehabilitation strategies. Few studies have measured the physical activity patterns in the early phases of rehabilitation after moderate to severe brain injury.

Objectives

To map and quantify physical activity patterns in patients admitted to brain injury rehabilitation. Further, to investigate which factors are associated with activity and if the early physical activity level is associated with functional outcome at discharge.

Methods

This observational study includes patients admitted to rehabilitation after moderate to severe acquired brain injury. Mobility and physical activity patterns are measured continuously during rehabilitation at two separate seven-day periods using a wearable activity tracker. Activity will be categorised into four levels and presented descriptively. Linear and logistic regression models will analyse associations between descriptive variables and activity levels.

Discussion

This protocol describes an observational study investigating patients' mobility and physical activity patterns with moderate to severe acquired brain injury during in-hospital rehabilitation. The ability to increase the amount of mobilisation and physical activity in subgroups may have profound consequences on the rehabilitation outcome. Furthermore, data from this study may be used to inform a large variety of trials investigating physical rehabilitation interventions. (NCT05571462).

Ambient fine particulate matter and pregnancy outcomes: An umbrella review

The available evidence on the effects of ambient fine particulate matter (PM2.5) and pregnancy outcomes (birth outcomes and pregnancy complications) has increased substantially. The purpose of this umbrella review is to refine the evidence of the association between birth outcome (birth defects) and PM2.5; and summarize the credibility of existing research on the association between pregnancy complications and PM2.5. We searched PubMed, Web of Science, Embase, and Cochrane databases for relevant systematic reviews and meta-analyses up to March 16, 2022 in accordance with PRISMA guidelines. Two independent investigators conducted data extraction. AMSTAR 2 and GRADE assessment criteria were used to evaluate the methodological and evidence quality. We performed subgroup analyses by trimesters of pregnancy. The review protocol for this study has been registered in PROSPERO (CRD42022325550). This umbrella review identified a total of 41 systematic reviews, including 28 articles evaluating the influence of PM2.5 on birth outcomes and 13 on pregnancy complications. Positive associations between perinatal PM2.5 exposure and adverse birth outcomes were found, including low birth weight, preterm birth, stillbirth, small for gestational age, and birth defects. Pregnant women exposed to PM2.5 had a significantly higher risk of developing hypertensive disorder of pregnancy, gestational diabetes mellitus, gestational hypertension, and preeclampsia. The findings of subgroup analysis demonstrated that the effects of ambient PM2.5 exposure on pregnancy outcomes varied by trimesters. The findings of this extensive umbrella review provide convincing proof that exposure to ambient PM2.5 raises the risks of unfavorable birth outcomes and pregnancy complications. Some associations show considerable disparity between trimesters. These findings have implications for strengthen perinatal health care on air pollution and improving intergenerational equity.

Non-pharmaceutical interventions to optimize cancer immunotherapy

The traditional picture of cancer patients as weak individuals requiring maximum rest and protection is beginning to dissolve. Too much focus on the medical side and one's own vulnerability and mortality might be counterproductive and not doing justice to the complexity of human nature. Unlike cytotoxic and lympho-depleting treatments, immune-engaging therapies strengthen the immune system and are typically less harmful for patients. Thus, cancer patients receiving checkpoint inhibitors are not viewed as being vulnerable per se, at least not in immunological and physical terms. This perspective article advocates a holistic approach to cancer immunotherapy, with an empowered patient in the center, focusing on personal resources and receiving domain-specific support from healthcare professionals. It summarizes recent evidence on non-pharmaceutical interventions to enhance the efficacy of immune checkpoint blockade and improve quality of life. These interventions target behavioral factors such as diet, physical activity, stress management, circadian timing of checkpoint inhibitor infusion, and waiving unnecessary co-medication curtailing immunotherapy efficacy. Non-pharmaceutical interventions are universally accessible, broadly applicable, instantly actionable, scalable, and economically sustainable, creating value for all stakeholders involved. Most importantly, this holistic framework re-emphasizes the patient as a whole and harnesses the full potential of anticancer immunity and checkpoint blockade, potentially leading to survival benefits. Digital therapeutics are proposed to accompany the patients on their mission toward change in lifestyle-related behaviors for creating optimal conditions for treatment efficacy and personal growth.

A large-scale observational study of the causal effects of a behavioral health nudge

Nudges are interventions promoting healthy behavior without forbidding options or substantial incentives; the Apple Watch, for example, encourages users to stand by delivering a notification if they have been sitting for the first 50 minutes of an hour. On the basis of 76 billion minutes of observational standing data from 160,000 subjects in the public Apple Heart and Movement Study, we estimate the causal effect of this notification using a regression discontinuity design for time series data with time-varying treatment. We show that the nudge increases the probability of standing by up to 43.9% and remains effective with time. The nudge's effectiveness increases with age and is independent of gender. Closing Apple Watch Activity Rings, a visualization of participants' daily progress in Move, Exercise, and Stand, further increases the nudge's impact. This work demonstrates the effectiveness of behavioral health interventions and introduces tools for investigating their causal effect from large-scale observations.

A randomized trial of a mobile health intervention to augment cardiac rehabilitation

Mobile health (mHealth) interventions may enhance positive health behaviors, but randomized trials evaluating their efficacy are uncommon. Our goal was to determine if a mHealth intervention augmented and extended benefits of center-based cardiac rehabilitation (CR) for physical activity levels at 6-months. We delivered a randomized clinical trial to low and moderate risk patients with a compatible smartphone enrolled in CR at two health systems. All participants received a compatible smartwatch and usual CR care. Intervention participants received a mHealth intervention that included a just-in-time-adaptive intervention (JITAI) as text messages. The primary outcome was change in remote 6-minute walk distance at 6-months stratified by device type. Here we report the results for 220 participants enrolled in the study (mean [SD]: age 59.6 [10.6] years; 67 [30.5%] women). For our primary outcome at 6 months, there is no significant difference in the change in 6 min walk distance across smartwatch types (Intervention versus control: +31.1 meters Apple Watch, -7.4 meters Fitbit; p = 0.28). Secondary outcomes show no difference in mean step counts between the first and final weeks of the study, but a change in 6 min walk distance at 3 months for Fitbit users. Amongst patients enrolled in center-based CR, a mHealth intervention did not improve 6-month outcomes but suggested differences at 3 months in some users.

Adherence to cognitive and physical exercise engagement: a challenge to successful dementia risk reduction and prevention efforts

With human life expectancy and proportion of older adults increasing, global use of evidence-supported preventative methods to minimize risk of brain-related disabilities such as Alzheimer's disease and other dementias-as well as interventions to slow rate of disease progression-is important. Sustained engagement in cognitive and physical exercise programs may prevent or delay dementia onset as well as maximize health and function of those with dementia. Despite awareness of the importance of cognitive and physical exercise to brain health, exercise program adherence by older adults is extremely challenging. In this Perspective article, we summarize what is known about contributors to exercise program adherence and strategies to promote it. We discuss our viewpoint on knowledge gaps regarding exercise adherence and research that needs to be conducted. We conclude by proposing a multi-dimensional exercise adherence assessment framework that includes portable neurophysiologic technologies to inform initial design and updating of individualized exercise programs that optimize sustained exercise program engagement and, ultimately, maximize brain health in older adults with and without mild cognitive impairment and dementia.

Expensive Ornaments or Essential Technology? A Qualitative Metasynthesis to Identify Lessons From User Experiences of Wearable Devices and Smart Technology in Health Care

This review sought to describe experiences of using wearable devices worn on the body for the purpose of tracking health status and movement and or using in-home health-related smart technologies. In this qualitative metasynthesis, five databases were searched from database inception to May 11, 2022. Included were qualitative studies of the experiences of using wearable or in-home sensors for monitoring health. The primary outcome was any study that reported experiences of using smart health technology using a wearable device or sensors in the home. Eighteen studies covering a range of technologies and health user groups were critically appraised, and data were extracted. Primary study themes were synthesized, and participant quotes across the studies were organized to construct broad themes and subthemes. The three themes included the following: technology as a motivator; reassurance from technology; and animosity toward technology. Technology was welcomed when participants experienced benefits such as reassurance that their health was being tracked and they were aware when problems arose. Participants appreciated the technology could motivate them to challenge themselves on the basis of feedback from the device. Some participants appeared to wish to avoid the technology but experienced resentment when they could not conceal the technology and still receive the other benefits. Data collected should be accessible to the technology user and the clinician together, to enhance transparency and reduce the power differential.

TrialRegistration

PROSPERO Identifier: CRD42022325402.

Availability of Physical Activity Tracking Data from Wearable Devices for Glaucoma Patients

Physical activity has been found to potentially modulate glaucoma risk, but the evidence remains inconclusive. The increasing use of wearable physical activity trackers may provide longitudinal and granular data suitable to address this issue, but little is known regarding the characteristics and availability of these data sources. We performed a scoping review and query of data sources on the availability of wearable physical activity data for glaucoma patients. Literature databases (PubMed and MEDLINE) were reviewed with search terms consisting of those related to physical activity trackers and those related to glaucoma, and we evaluated results at the intersection of these two groups. Biomedical databases were also reviewed, for which we completed database queries. We identified eight data sources containing physical activity tracking data for glaucoma, with two being large national databases (UK BioBank and All of Us) and six from individual journal articles providing participant-level information. The number of glaucoma patients with physical activity tracking data available, types of glaucoma-related data, fitness devices utilized, and diversity of participants varied across all sources. Overall, there were limited analyses of these data, suggesting the need for additional research to further investigate how physical activity may alter glaucoma risk.

Consumer Wearable Health and Fitness Technology in Cardiovascular Medicine: JACC State-of-the-Art Review

The use of consumer wearable devices (CWDs) to track health and fitness has rapidly expanded over recent years because of advances in technology. The general population now has the capability to continuously track vital signs, exercise output, and advanced health metrics. Although understanding of basic health metrics may be intuitive (eg, peak heart rate), more complex metrics are derived from proprietary algorithms, differ among device manufacturers, and may not historically be common in clinical practice (eg, peak V˙O2, exercise recovery scores). With the massive expansion of data collected at an individual patient level, careful interpretation is imperative. In this review, we critically analyze common health metrics provided by CWDs, describe common pitfalls in CWD interpretation, provide recommendations for the interpretation of abnormal results, present the utility of CWDs in exercise prescription, examine health disparities and inequities in CWD use and development, and present future directions for research and development.

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.

Clinicians' Perspectives of Wearable Technology to Detect and Monitor Exacerbations of Chronic Obstructive Pulmonary Disease: Mixed-Method Survey

Objective

To investigate clinicians' perspectives on the current use of wearable technology for detecting COPD exacerbations, and to identify potential facilitators and barriers to its adoption in clinical settings.

Methods

A mixed-method survey was conducted through an online survey platform involving clinicians working with COPD patients. The questionnaires were developed by an expert panel specialising in respiratory medicine at UCL. The questionnaire evaluated clinicians' perspectives on several aspects: the current extent of wearable technology utilisation, the perceived feasibility, and utility of these devices, as well as the potential facilitators and barriers that hinder its wider implementation.

Results

Data from 118 clinicians were included in the analysis. Approximately 80% of clinicians did not currently use information from wearable devices in routine clinical care. A majority of clinicians did not have confidence in the effectiveness of wearables and their consequent impact on health outcomes. However, clinicians highlighted the potential value of wearables in helping deliver personalised care and more rapid assistance. Ease of use, technical support and accessibility of data were considered facilitating factors for wearable utilisation. Costs and lack of technical knowledge were the most frequently reported barriers to wearable utilisation.

Conclusion

Clinicians' perspectives of the use of wearable technology to detect and monitor COPD exacerbations are variable. While accessibility and technical support facilitate wearable implementation, cost, technical issues, and knowledge act as barriers. Our findings highlight the facilitators and barriers to using wearables in patients with COPD and emphasise the need to assess patients' perspectives on wearable acceptability.

Role of the internet of medical things in care for patients with interstitial lung disease

PURPOSE OF REVIEW

Online technologies play an increasing role in facilitating care for patients with interstitial lung disease (ILD). In this review, we will give an overview of different applications of the internet of medical things (IoMT) for patients with ILD.

RECENT FINDINGS

Various applications of the IoMT, including teleconsultations, virtual MDTs, digital information, and online peer support, are now used in daily care of patients with ILD. Several studies showed that other IoMT applications, such as online home monitoring and telerehabilitation, seem feasible and reliable, but widespread implementation in clinical practice is lacking. The use of artificial intelligence algorithms and online data clouds in ILD is still in its infancy, but has the potential to improve remote, outpatient clinic, and in-hospital care processes. Further studies in large real-world cohorts to confirm and clinically validate results from previous studies are needed.

SUMMARY

We believe that in the near future innovative technologies, facilitated by the IoMT, will further enhance individually targeted treatment for patients with ILD by interlinking and combining data from various sources.

Cardiac rehabilitation, physical activity, and the effectiveness of activity monitoring devices on cardiovascular patients: an umbrella review of systematic reviews

AIMS

To consolidate the evidence on the effectiveness of activity-monitoring devices and mobile applications on physical activity and health outcomes of patients with cardiovascular disease who attended cardiac rehabilitation (CR) programmes.

METHODS AND RESULTS

An umbrella review of published randomized controlled trials, systematic reviews, and meta-analyses was conducted. Nine databases were searched from inception to 9 February 2022. Search and data extraction followed the JBI methodology for umbrella reviews and PRISMA guidelines. Nine systematic reviews met the inclusion criteria, comparing outcomes of participants in CR programmes utilizing devices/applications, to patients without access to CR with devices/applications. A wide range of physical, clinical, and behavioural outcomes were reported, with results from 18 712 participants. Meta-analyses reported improvements in physical activity, minutes/week [standardized mean difference (SMD) 0.23, 95% confidence interval (CI) 0.10-0.35] and activity levels (SMD 0.29, 95% CI 0.07-0.51), and a reduction in sedentariness [risk ratio (RR) 0.54, 95% CI 0.39-0.75] in CR participants, compared with usual care. Of clinical outcomes, the risk of re-hospitalization reduced significantly (RR 0.49, 95% CI 0.27-0.89), and there was reduction (non-significant) in mortality (RR 0.27, 95% CI 0.05-1.54). From the behavioural outcomes, reviews reported improvements in smoking behaviour (RR 0.87, 95% CI 0.67-1.13) and total diet quality intake (RR 0.79, 95% CI 0.66-0.94) among CR patients.

CONCLUSIONS

The use of devices/applications was associated with increase in activity, healthy behaviours, and reductions in clinical indicators. Although most effect sizes indicate limited clinical benefits, the broad consistency of the narrative suggests devices/applications are effective at improving CR patients' outcomes.

Physical Activity Over the Lifecourse and Cardiovascular Disease

Despite improvements in cardiovascular care in recent decades, cardiovascular disease (CVD) remains a leading cause of death worldwide. At its core, CVD is a largely preventable disease with diligent risk factor management and early detection. As highlighted in the American Heart Association's Life's Essential 8, physical activity plays a central role in CVD prevention at an individual and population level. Despite pervasive knowledge of the numerous cardiovascular and noncardiovascular health benefits of physical activity, physical activity has steadily decreased over time and unfavorable changes in physical activity occur throughout people's lives. Here, we use a lifecourse framework to examine the evidence reporting on the association of physical activity with CVD. From in utero to older adults, we review and discuss the evidence detailing how physical activity may prevent incident CVD and mitigate CVD-related morbidity and death across all life stages.

Interventions Using Wearable Activity Trackers to Improve Patient Physical Activity and Other Outcomes in Adults Who Are Hospitalized: A Systematic Review and Meta-analysis

Importance

Low levels of physical activity during hospitalization are thought to contribute to a range of poor outcomes for patients. Using wearable activity trackers during hospitalization may help improve patient activity, sedentary behavior, and other outcomes.

Objective

To evaluate the association of interventions that use wearable activity trackers during hospitalization with patient physical activity, sedentary behavior, clinical outcomes, and hospital efficiency outcomes.

Data Sources

OVID MEDLINE, CINAHL, Embase, EmCare, PEDro, SportDiscuss, and Scopus databases were searched from inception to March 2022. The Cochrane Central Register for Controlled trials, ClinicalTrials.gov, and World Health Organization Clinical Trials Registry were also searched for registered protocols. No language restrictions were imposed.

Study Selection

Randomized clinical trials and nonrandomized clinical trials of interventions that used wearable activity trackers to increase physical activity or reduce sedentary behavior in adults (aged 18 years or older) who were hospitalized were included.

Data Extraction and Synthesis

Study selection, data extraction, and critical appraisal were conducted in duplicate. Data were pooled for meta-analysis using random-effects models. The Preferred Reporting Items for Systematic Reviews and Meta-analyses guideline was followed.

Main Outcomes and Measures

The primary outcomes were objectively measured physical activity or sedentary behavior. Secondary outcomes included clinical outcomes (eg, physical function, pain, mental health), and hospital efficiency outcomes (eg, length of stay, readmission).

Results

Fifteen studies with a total of 1911 participants were included, representing various surgical cohorts (4 studies), stroke rehabilitation (3 studies), orthopedic rehabilitation (3 studies), mixed rehabilitation (3 studies), and mixed medical (2 studies). All studies were included in meta-analyses. There was a significant association between wearable activity tracker interventions with higher overall physical activity (standardized mean difference, 0.35; 95% CI, 0.15 to 0.54; I2 = 72%; P < .002) and less sedentary behavior (mean difference, -35.46 min/d; 95% CI, -57.43 to -13.48 min/d; I2 = 0; P = .002), and a significant association between wearable activity tracker interventions with improvements in physical function (standardized mean difference, 0.27; 95% CI, 0.08 to 0.46; I2 = 0; P = .006) compared with usual care. There was no significant association between wearable activity tracker interventions with pain, mental health, length of stay, or readmission risk.

Conclusions and Relevance

In this systematic review and meta-analysis, interventions that used wearable activity trackers with patients who are hospitalized were associated with higher physical activity levels, less sedentary behavior, and better physical functioning compared with usual care.