Utilizing wearable technology to increase physical activity in future physicians: A randomized trial

The impact of the COVID-19 pandemic on physical activity habits at a residential university

OBJECTIVE

To assess changes in physical activity (PA) after a COVID-19 shutdown on a primarily residential university campus.

METHODS

Eighty students, faculty, and staff (FS) of a university (age: 32.2 ± 13.6 yr) who wore a consumer wearable technology (CWT) device completed an anonymous survey by inputting data for 30 days prior to- and 30 days following an academic break in 2020, in which the university transitioned to remote learning.

RESULTS

Steps decreased after spring break in all subjects (p < .001), but steps were impacted to a greater extent in students. 30-day, weekday, and weekend step averages all decreased in students (p < .001). FS were able to maintain their weekend step averages.

CONCLUSIONS

PA decreased in a university community after the COVID-19 shutdown. Students, no longer active transport for campus life, saw a greater impact on their PA. These changes could have an impact on health status.

The combined effect of motivational interviewing and wearable fitness trackers on motivation and physical activity in inactive adults: A randomized controlled trial

Despite overwhelming adoption of wearable fitness trackers (WFT), it is unclear if they affect physical activity (PA) engagement or PA motivation. We hypothesized that combining a WFT with an effective intervention, motivational interviewing (MI), would positively influence both motivation and PA. A 12-week randomized controlled trial was conducted in 40 adults who did not meet PA recommendations. The four conditions were: a PA education (Educational control, n = 10), a WFT (WFT, n = 10), bi-weekly MI sessions (MI, n = 10), or both interventions (WFT+, n = 10). Motivation and PA were measured through an online survey and actigraphy pre- and post-intervention. Both the WFT+ and MI groups improved autonomous forms and decreased controlled forms of motivation. They also had higher basic psychological needs scores when compared to the Education group post-intervention. We detected no changes in PA. High autonomous motivation at baseline predicted higher post-intervention PA in the WFT+ group but predicted lower post-intervention PA in the WFT group. Results suggests that MI alone or with a WFT can improve basic psychological needs and autonomous forms of motivation for PA, but not PA participation. Individual differences in motivation at baseline may moderate the effect of a WFT on PA. This study was registered at clinicaltrials.gov (NCT490014).

Challenges and recommendations for wearable devices in digital health: Data quality, interoperability, health equity, fairness

Wearable devices are increasingly present in the health context, as tools for biomedical research and clinical care. In this context, wearables are considered key tools for a more digital, personalised, preventive medicine. At the same time, wearables have also been associated with issues and risks, such as those connected to privacy and data sharing. Yet, discussions in the literature have mostly focused on either technical or ethical considerations, framing these as largely separate areas of discussion, and the contribution of wearables to the collection, development, application of biomedical knowledge has only partially been discussed. To fill in these gaps, in this article we provide an epistemic (knowledge-related) overview of the main functions of wearable technology for health: monitoring, screening, detection, and prediction. On this basis, we identify 4 areas of concern in the application of wearables for these functions: data quality, balanced estimations, health equity, and fairness. To move the field forward in an effective and beneficial direction, we present recommendations for the 4 areas: local standards of quality, interoperability, access, and representativity.

Effect of a 12-week non-contact exercise intervention on body composition and health-related physical fitness in adults: a pilot test

[Purpose] The purpose of this study was to evaluate the effects of a 12-week non-contact exercise intervention on body composition and health-related physical fitness in adults.[Methods] One hundred adults were initially enrolled; however, ninety-seven participants (men: n = 41, women: n = 56) completed the study. The non-contact exercise was performed for 12 weeks using a smart tracker (Charge 4, Fitbit, USA) and mobile phone applications. The non-contact exercise program included resistance, aerobic, and flexibility exercises.[Results] The results showed that percent body fat (<i>F</i>=4.993, <i>p</i>=.016, η_p²=.049), fat-free mass (<i>F</i>=4.690, <i>p</i>=.024, η_p²=.047), and skeletal muscle mass (<i>F</i>=5.623, <i>p</i>=.004, η_p²=.055) significantly changed during the intervention period. Further, significant increases were seen in hand grip strength (<i>F</i>=12.167, <i>p</i><.001, η_p²=.112), sit-and-reach (<i>F</i>=20.497, <i>p</i><.001, η_p²=.176), sit-ups (<i>F</i>=42.107, <i>p</i><.001, η_p²=.305), and VO_2max (<i>F</i>=4.311, <i>p</i>=.037, η_p²=.043).[Conclusion] Our findings suggest that 12 weeks of non-contact exercise improves body composition and health-related physical fitness. Wearable technologies encourage individuals to modify their lifestyles by increasing physical activity and achieving the goal of maintaining health conditions among adults.

Do physical activity interventions combining self-monitoring with other components provide an additional benefit compared with self-monitoring alone? A systematic review and meta-analysis

Objective

To determine the net effect of different physical activity intervention components on step counts in addition to self-monitoring.

Design

A systematic review with meta-analysis and meta-regression.

Data sources

Five databases (PubMed, Scopus, Web of Science, ProQuest and Discus) were searched from inception to May 2022. The database search was complemented with backward and forward citation searches and search of the references from relevant systematic reviews.

Eligibility criteria

Randomised controlled trials comparing an intervention using self-monitoring (active control arm) with an intervention comprising the same treatment PLUS any additional component (intervention arm).

Data extraction and synthesis

The effect measures were mean differences in daily step count. Meta-analyses were performed using random-effects models, and effect moderators were explored using univariate and multivariate meta-regression models.

Results

Eighty-five studies with 12 057 participants were identified, with 75 studies included in the meta-analysis at postintervention and 24 at follow-up. At postintervention, the mean difference between the intervention and active control arms was 926 steps/day (95% CI 651 to 1201). At a follow-up, the mean difference was 413 steps/day (95% CI 210 to 615). Interventions with a prescribed goal and involving human counselling, particularly via phone/video calls, were associated with a greater mean difference in the daily step count than interventions with added print materials, websites, smartphone apps or incentives.

Conclusion

Physical activity interventions that combine self-monitoring with other components provide an additional modest yet sustained increase in step count compared with self-monitoring alone. Some forms of counselling, particularly remote phone/video counselling, outperformed other intervention components, such as websites and smartphone apps.

PROSPERO registered number

CRD42020199482.

The association between sleep deficits and sedentary behavior in people with mild Parkinson disease

Purpose: Sleep deficits are a common nonmotor symptom of Parkinson disease (PD). People with mild PD also achieve less physical activity (PA) than healthy older adults (HOA), but the relationship between sleep and PA in PD is unclear. This study examined associations between sleep and PA in participants with PD and HOA.Materials and Methods: Secondary analysis of a prospective observational study. Participants wore a commercially available activity monitor for two weeks. Wilcoxon Rank-Sum tests compared nighttime sleep, wakenings after sleep onset, number of wakenings, naps, step count, and PA intensity between PD and HOA groups. Age-adjusted regression models calculated associations between nighttime sleep and PA.Results: Per day, participants with PD slept 75 fewer minutes (p < 0.01), took 5,792 fewer steps (p < 0.001), achieved less PA at all intensities, and had 32% more sedentary time (p < 0.001) compared to HOA. Thirty minutes more sleep was associated with 26 fewer sedentary minutes for HOA (p = 0.01) and 25 fewer sedentary minutes for the PD group (p < 0.001).Conclusions: Sleep and PA are reduced in mild PD compared to HOA. Both groups demonstrated similar associations between reduced sleep and increased sedentary behavior. Results may encourage providers to screen for sleep deficits when promoting PA.IMPLICATIONS FOR REHABILITATIONThe use of a wrist-worn commercial activity and sleep monitor was well tolerated by both healthy older adults and people with mild Parkinson Disease in this study.People with mild Parkinson Disease slept less and were less active than a group of healthy older adults.Less sleep was associated with more sedentary behavior in both groups.The relationship between poor sleep and sedentary behavior in mild Parkinson Disease suggests that rehabilitation interventions may be optimized by targeting both physical activity and sleep deficits.

Effectiveness of Physical-Activity-Based Interventions Targeting Overweight and Obesity among University Students—A Systematic Review

Overweight and obesity, including their prevalence and consequences, reflect a leading public health problem. Studies have already shown that physical activity leads to a reduction in body weight in children and adults. However, the university setting has rarely been investigated. The aim of this review is, therefore, to examine and summarize the effectiveness of physical-activity-based interventions to reduce obesity and overweight in university students. Three databases (PubMed, Scopus, and Web of Science) were searched for relevant studies published in English between January 2010 and February 2022. Quantitative studies conducting a physical-activity-based intervention with overweight or obese university students and reporting changes in BMI were included. Data were described in a narrative synthesis. Out of 16 included studies, 11 reported a significant reduction in BMI. However, all studies except one were able to demonstrate some BMI improvements, whereas all studies reported significant changes in at least one health-related indicator. Aerobic exercises were able to demonstrate the greatest reductions in BMI. This review is the first systematic presentation on the effectiveness of physical-activity-based interventions in overweight and obese university students. Future work should reconsider BMI as the primary outcome if appropriate within the respective study design (i.e., to measure long-term effects). More interventions are needed to improve strategies.

Wearing the Future—Wearables to Empower Users to Take Greater Responsibility for Their Health and Care: Scoping Review

Background

Wearables refer to devices that are worn by individuals. In the health care field, wearables may assist with individual monitoring and diagnosis. In fact, the potential for wearable technology to assist with health care has received recognition from health systems around the world, including a place in the strategic Long Term Plan shared by the National Health Service in England. However, wearables are not limited to specialist medical devices used by patients. Leading technology companies, including Apple, have been exploring the capabilities of wearable health technology for health-conscious consumers. Despite advancements in wearable health technology, research is yet to be conducted on wearables and empowerment.

Objective

This study aimed to identify, summarize, and synthesize knowledge on how wearable health technology can empower individuals to take greater responsibility for their health and care.

Methods

This study was a scoping review with thematic analysis and narrative synthesis. Relevant guidance, such as the Arksey and O’Malley framework, was followed. In addition to searching gray literature, we searched MEDLINE, EMBASE, PsycINFO, HMIC, and Cochrane Library. Studies were included based on the following selection criteria: publication in English, publication in Europe or the United States, focus on wearables, relevance to the research, and the availability of the full text.

Results

After identifying 1585 unique records and excluding papers based on the selection criteria, 20 studies were included in the review. On analysis of these 20 studies, 3 main themes emerged: the potential barriers to using wearables, the role of providers and the benefits to providers from promoting the use of wearables, and how wearables can drive behavior change.

Conclusions

Considerable literature findings suggest that wearables can empower individuals by assisting with diagnosis, behavior change, and self-monitoring. However, greater adoption of wearables and engagement with wearable devices depend on various factors, including promotion and support from providers to encourage uptake; increased short-term investment to upskill staff, especially in the area of data analysis; and overcoming the barriers to use, particularly by improving device accuracy. Acting on these suggestions will require investment and constructive input from key stakeholders, namely users, health care professionals, and designers of the technology. As advancements in technology to make wearables viable health care devices have only come about recently, further studies will be important for measuring the effectiveness of wearables in empowering individuals. The investigation of user outcomes through large-scale studies would also be beneficial. Nevertheless, a significant challenge will be in the publication of research to keep pace with rapid developments related to wearable health technology.

Fitbit Use and Activity Levels From Intervention to 2 Years After: Secondary Analysis of a Randomized Controlled Trial

Background

There has been a rapid increase in the use of commercially available activity trackers, such as Fitbit, in physical activity intervention research. However, little is known about the long-term sustained use of trackers and behavior change after short-term interventions.

Objective

This study aims to use minute-level data collected from a Fitbit tracker for up to 2 years after the end of a randomized controlled trial to examine patterns of Fitbit use and activity over time.

Methods

Participants in this secondary data analysis were 75 female breast cancer survivors who had been enrolled in a 12-week physical activity randomized controlled trial. Participants randomized to the exercise intervention (full intervention arm) received a Fitbit One, which was worn daily throughout the 12-week intervention, and then were followed for 2 years after the intervention. Participants randomized to the waitlist arm, after completing the randomized controlled trial, received a Fitbit One and a minimal version of the exercise intervention (light intervention arm), and then were followed for 2 years after the intervention. Average and daily adherence and MVPA were compared between the 2 groups in the interventional and postinterventional periods using both linear and generalized additive mixed effects models.

Results

Adherence to wearing the Fitbit during the 12-week intervention period was significantly higher in the full intervention arm than in the light intervention arm (85% vs 60%; P<.001). Average adherence was significantly lower for both study arms during the follow-up period than in the intervention period; however, there were statistically different patterns of adherence during the follow-up period, with the light intervention arm having steeper declines than the full intervention arm over time (P<.001). Similar to the adherence results, mean minutes of Fitbit-measured MVPA was higher for the full intervention arm than for the light intervention arm during the 12-week intervention period (mean MVPA 27.89 minutes/day, SD 16.38 minutes/day vs 18.35 minutes/day, SD 12.64 minutes/day; P<.001). During the follow-up period, average MVPA was significantly lower than the 12-week intervention period for both the full intervention arm (21.74 minutes/day, SD 24.65 minutes/day; P=.002) and the light intervention arm (15.03 minutes/day, SD 13.27 minutes/day; P=.004). Although the mean MVPA in each arm was similar across the follow-up period (P=.33), the pattern of daily MVPA was significantly different between the 2 groups (P<.001).

Conclusions

While adherence to wearing activity trackers and maintaining physical activities declined after completion of a 12-week exercise intervention, a more active interventional strategy resulted in greater wear time and activity levels during the intervention and more stable patterns of adherence and activity in the long term. An improved understanding of long-term maintenance patterns may inform improved exercise interventions that result in sustained increases in physical activity.

Trial Registration

ClinicalTrials.gov NCT02332876; https://clinicaltrials.gov/ct2/show/NCT02332876

The Effect of Wearable Tracking Devices on Cardiorespiratory Fitness Among Inactive Adults: Crossover Study

Background

Modern lifestyle is associated with a high prevalence of physical inactivity.

Objective

This study aims to investigate the effect of a wearable tracking device on cardiorespiratory fitness among inactive adults and to explore if personal characteristics and health outcomes can predict adoption of the device.

Methods

In total, 62 inactive adults were recruited for this study. A control period (4 weeks) was followed by an intervention period (8 weeks) where participants were instructed to register and follow their physical activity (PA) behavior on a wrist-worn tracking device. Data collected included estimated cardiorespiratory fitness, body composition, blood pressure, perceived stress levels, and self-reported adoption of using the tracking device.

Results

In total, 50 participants completed the study (mean age 48, SD 13 years, 84% women). Relative to the control period, participants increased cardiorespiratory fitness by 1.52 mL/kg/minute (95% CI 0.82-2.22; P<.001), self-reported PA by 140 minutes per week (95% CI 93.3-187.1; P<.001), daily step count by 982 (95% CI 492-1471; P<.001), and participants’ fat percentage decreased by 0.48% (95% CI –0.84 to –0.13; P=.009). No difference was observed in blood pressure (systolic: 95% CI –2.16 to 3.57, P=.63; diastolic: 95% CI –0.70 to 2.55; P=.27) or perceived stress (95% CI –0.86 to 1.78; P=.49). No associations were found between adoption of the wearable tracking device and age, gender, personality, or education. However, participants with a low perceived stress at baseline were more likely to rate the use of a wearable tracking device highly motivating.

Conclusions

Tracking health behavior using a wearable tracking device increases PA resulting in an improved cardiorespiratory fitness among inactive adults.

The Role of Individualized Exercise Prescription in Obesity Management-Case Study

Introduction: Obesity, or adiposity-based chronic disease (ABCD), is one of the most common health risk factors nowadays. Regular exercise—part of complex lifestyle medicine program—is effective treatment for obesity but is still underestimated. Monitoring andindividualization by an exercise professional is needed to define the accurate dose effect. Materials and Methods: The 30-week lifestyle change program of a 65-year-old male patient (body mass index (BMI) 43.8 kg/m²) was followed by a medical doctor, exercise physiologist, and nutritionist. Over regular controls and blood tests, each training activity was measured with a heart rate monitor watch, and a diet diary was written. Results: Bodyweight decreased by 24.1 kg (18.4%) and BMI to 35.8 kg/m². Decreased resting heart rate (from 72 bpm to 63 bpm), diastolic blood pressure (from 72 mmHg to 67 mmHg), and increased systolic blood pressure (from 126 mmHg to 135 mmHg) were reported, besides the reduction in antihypertensive and antidiabetic medicines. Blood test results and fitness level improved, and daily steps and time spent training increased. Conclusions: Lifestyle medicine with professional support is an effective and long-term treatment for ABCD. Individualized exercise and nutritional therapy are essential, and wearable technology with telemedicine consultation also has an important role.

Effects of Short-Term Unsupervised Exercise, Based on Smart Bracelet Monitoring, on Body Composition in Patients Recovering from Breast Cancer

OBJECTIVE

We aimed to investigate the effects of exercise, monitored and managed using smart bracelets, on body composition, and quality of life in breast cancer survivors.

METHODS

A before-and-after study was conducted in 109 patients who were in the recovery phase of breast cancer and attended the Breast Surgery Department of the Cancer Hospital of Fudan University up to December 2017. Patients were advised to adhere to at least 150 minutes of moderate-intensity exercise per week, and a smart bracelet was issued to each participant to record their daily exercise data for 3 months. Bioelectrical impedance analysis was used to observe the effects of short-term unsupervised exercise intervention on body composition in patients recovering from breast cancer. Patients completed the Functional Assessment of Cancer Therapy-Breast to assess health-related quality of life.

RESULTS

Weight, body mass index (BMI), body fat mass (BFM), fat mass index (FMI), percent body fat (PBF), arm circumference (AC), arm muscle circumference (AMC), and visceral fat area (VFA) were lower than baseline after exercising for 3 months based on data from the wearable devices (P < .05). The only significant improvement was found in the "additional concerns about breast cancer" category among the quality-of-life assessments (P < .05). The average walking time was negatively associated with BFM, PBF, and FMI, while the average calorie consumption due to running was positively associated with fat free mass (FFM).

CONCLUSION

In this study, we demonstrated that short-term exercise may be beneficial for postoperative breast cancer survivors. A wearable device could help patients track physical data easily and promote a healthier and more positive life.

Effect of Mobile-Based Lifestyle Intervention on Weight Loss among the Overweight and Obese Elderly Population in China: A Randomized Controlled Trial

Background and Objective: Overweight or obesity, as an independent risk factor for chronic diseases, has been on the rise globally. Adopting a healthy lifestyle is positive to weight control. Mobile-based lifestyle interventions have shown potential benefits in weight loss, but most studies were carried out among non-elderly population, so it is necessary to perform well-designed randomized controlled trials among the elderly with overweight or obesity. The purpose of this study is to assess the effect of mobile-based lifestyle intervention on weight loss among the overweight and obese elderly population in China. Methods: This is a prospective, open-labeled, three-month, multicenter, randomized controlled trial involving 750 participants from five cities who were randomly assigned to dietary and physical activity interventions group (DPG; mobile phone with the App and bracelet), physical activity interventions group (PG; mobile phone with the App and bracelet) and control group (CG; no interventions and kept their lifestyle as before). The outcomes evaluated were changes in weight, body mass index (BMI), waist circumference (WC), and hip circumference (HC). Results: In total, 642 (85.6%) participants completed the study, 237 (94.8%), 203 (81.2%), and 202 (80.8%) for DPG, PG, and CG respectively. Comparing with PG and CG, the DPG showed a significant decrease in all outcomes after three months, including body weight (−4.1 kg vs. −1.0 kg; −4.1 kg vs. −0.8 kg; p < 0.05), BMI (−1.6 kg/m² vs. −0.4 kg/m²; −1.6 kg/m² vs. −0.3 kg/m²; p < 0.05), WC (−2.8 cm vs. −0.1 cm; −2.8 cm vs. −0.5 cm; p < 0.05), and HC (−3.8 cm vs. −1.3 cm; −3.8 cm vs. −1.3 cm; p < 0.05). Similar effects were seen across sex and BMI subgroups. Conclusions: Mobile-based lifestyle intervention obtained beneficial effect in weight loss among the elderly with overweight or obesity. Nevertheless, further studies are needed to confirm the effectiveness and its sustainability.

General Practitioners' Perceptions of the Use of Wearable Electronic Health Monitoring Devices: Qualitative Analysis of Risks and Benefits

Background

The rapid diffusion of wearable electronic health monitoring devices (wearable devices or wearables) among lay populations shows that self-tracking and self-monitoring are pervasively expanding, while influencing health-related practices. General practitioners are confronted with this phenomenon, since they often are the expert-voice that patients will seek.

Objective

This article aims to explore general practitioners’ perceptions of the role of wearable devices in family medicine and of their benefits, risks, and challenges associated with their use. It also explores their perceptions of the future development of these devices.

Methods

Data were collected during a medical conference among 19 Swiss general practitioners through mind maps. Maps were first sketched at the conference and their content was later compared with notes and reports written during the conference, which allowed for further integration of information. This tool represents an innovative methodology in qualitative research that allows for time-efficient data collection and data analysis.

Results

Data analysis highlighted that wearable devices were described as user-friendly, adaptable devices that could enable performance monitoring and support medical research. Benefits included support for patients’ empowerment and education, behavior change facilitation, better awareness of personal medical history and body functioning, efficient information transmission, and connection with the patient’s medical network; however, general practitioners were concerned by a lack of scientific validation, lack of clarity over data protection, and the risk of stakeholder-associated financial interests. Other perceived risks included the promotion of an overly medicalized health culture and the risk of supporting patients’ self-diagnosis and self-medication. General practitioners also feared increased pressure on their workload and a compromised doctor–patient relationship. Finally, they raised important questions that can guide wearables’ future design and development, highlighting a need for general practitioners and medical professionals to be involved in the process.

Conclusions

Wearables play an increasingly central role in daily health-related practices, and general practitioners expressed a desire to become more involved in the development of such technologies. Described as useful information providers, wearables were generally positively perceived and did not seem to pose a threat to the doctor–patient relationship. However, general practitioners expressed their concern that wearables may fuel a self-monitoring logic, to the detriment of patients’ autonomy and overall well-being. While wearables can contribute to health promotion, it is crucial to clarify the logic underpinning the design of such devices. Through the analysis of group discussions, this study contributes to the existing literature by presenting general practitioners’ perceptions of wearable devices. This paper provides insight on general practitioners’ perception to be considered in the context of product development and marketing.

Effects of Supervised Exercise-Based Telerehabilitation on Walk Test Performance and Quality of Life in Patients in India With Chronic Disease: Combatting Covid-19

Background:

The world is currently undergoing a pandemic, caused by the SARS-CoV-2 virus (COVID-19). According to the World Health Organization, patients with chronic illnesses appear to be at the highest risk for COVID-19 associated sequelae. Inability to participate in outpatient-based rehabilitation programs and being home-bound can increase the risk for and potential worsening of chronic health conditions. This study evaluated the short-term effects of telerehabilitation on patients' walk test performance and health related quality of life (HRQoL).

Methods:

47 patients (23 cardiovascular, 15 pulmonary, 9 oncology) participated in the telerehabilitation program. At baseline and following a 1-month intervention, patients had their 6-minute walk test distance (6MWTD) and HRQoL assessed. Average daily step counts were measured by the PACER App.

Conclusions:

Our results indicate that a short-term, supervised virtual telerehabilitation program had significant positive effects on 6MWTD and HRQoL in cardiac, pulmonary and oncology patients during COVID-19.

Effectiveness of Minimal Contact Interventions: An RCT

INTRODUCTION

Around 23% of adults worldwide are insufficiently active. Wearable devices paired with virtual coaching software could increase physical activity. The effectiveness of 3 minimal contact interventions (paper-based physical activity diaries, activity trackers, and activity trackers coupled with virtual coaching) in increasing physical activity energy expenditure and cardiorespiratory fitness were compared over 12 weeks among inactive adults.

METHODS

This was an open label, parallel-group RCT. Inactive adults (aged ≥18 years, N=488) were randomized to no intervention (Control; n=121), paper-based diary (Diary; n=124), activity tracker (Activity Band; n=122), or activity tracker plus virtual coaching (Activity Band PLUS; n=121) groups. Coprimary outcomes included 12-week changes in physical activity energy expenditure and fitness (May 2012-January 2014). Analyses were conducted in 2019-2020.

RESULTS

There were no differences between groups overall (physical activity energy expenditure: p=0.114, fitness: p=0.417). However, there was a greater increase in physical activity energy expenditure (4.21 kJ/kg/day, 95% CI=0.42, 8.00) in the Activity Band PLUS group than in the Diary group. There were also greater decreases in BMI and body fat percentage in the Activity Band PLUS group than in the Control group (BMI= -0.24 kg/m2, 95% CI= -0.45, -0.03; body fat= -0.48%, 95% CI= -0.88, -0.08) and in theActivity Band PLUS group than in the Diary group (BMI= -0.30 kg/m2, 95% CI= -0.50, -0.09; body fat= -0.57%, 95% CI= -0.97, -0.17).

CONCLUSIONS

Coupling activity trackers with virtual coaching may facilitate increases in physical activity energy expenditure compared with a traditional paper‒based physical activity diary intervention and improve some secondary outcomes compared with a traditional paper‒based physical activity diary intervention or no intervention.

TRIAL REGISTRATION

This study is registered at www.clinicaltrials.gov ISRCTN31844443.

Anesthesia in the modern world of apps and technology: Implications and impact on wellness

Recent decades have seen an unprecedented leap in digital innovation, with far-reaching implications in healthcare. Anesthesiologists have historically championed the adoption of new technologies. However, the rapid evolution of these technologies has outpaced attempts at studying their potential impact on healthcare providers' well-being. This document introduces several categories of workplace technologies commonly encountered by the anesthesiologist. We examine examples of novel technology and the impact of these digital interventions on the anesthesiologist's well-being. We also review popular personalized technology aimed at improving wellness and the impact on well-being examined. Finally, technology acceptance models are introduced to improve technology adoption, which, when appropriately applied, may minimize the negative impacts of technology on anesthesiologists' well-being. Incorporating quantitative, serial assessments of well-being as part of technology implementation are proposed as a future direction for examining the wellness impact of technology on anesthesiologists.

Future Mobile Device Usage, Requirements, and Expectations of Physicians in German University Hospitals: Web-Based Survey

Background

The use of mobile devices in hospital care constantly increases. However, smartphones and tablets have not yet widely become official working equipment in medical care. Meanwhile, the parallel use of private and official devices in hospitals is common. Medical staff use smartphones and tablets in a growing number of ways. This mixture of devices and how they can be used is a challenge to persons in charge of defining strategies and rules for the usage of mobile devices in hospital care.

Objective

Therefore, we aimed to examine the status quo of physicians’ mobile device usage and concrete requirements and their future expectations of how mobile devices can be used.

Methods

We performed a web-based survey among physicians in 8 German university hospitals from June to October 2019. The online survey was forwarded by hospital management personnel to physicians from all departments involved in patient care at the local sites.

Results

A total of 303 physicians from almost all medical fields and work experience levels completed the web-based survey. The majority regarded a tablet (211/303, 69.6%) and a smartphone (177/303, 58.4%) as the ideal devices for their operational area. In practice, physicians are still predominantly using desktop computers during their worktime (mean percentage of worktime spent on a desktop computer: 56.8%; smartphone: 12.8%; tablet: 3.6%). Today, physicians use mobile devices for basic tasks such as oral (171/303, 56.4%) and written (118/303, 38.9%) communication and to look up dosages, diagnoses, and guidelines (194/303, 64.0%). Respondents are also willing to use mobile devices for more advanced applications such as an early warning system (224/303, 73.9%) and mobile electronic health records (211/303, 69.6%). We found a significant association between the technical affinity and the preference of device in medical care (χs2=53.84, P<.001) showing that with increasing self-reported technical affinity, the preference for smartphones and tablets increases compared to desktop computers.

Conclusions

Physicians in German university hospitals have a high technical affinity and positive attitude toward the widespread implementation of mobile devices in clinical care. They are willing to use official mobile devices in clinical practice for basic and advanced mobile health uses. Thus, the reason for the low usage is not a lack of willingness of the potential users. Challenges that hinder the wider adoption of mobile devices might be regulatory, financial and organizational issues, and missing interoperability standards of clinical information systems, but also a shortage of areas of application in which workflows are adapted for (small) mobile devices.

Do smartphone applications and activity trackers increase physical activity in adults? Systematic review, meta-analysis and metaregression

OBJECTIVE

To determine the effectiveness of physical activity interventions involving mobile applications (apps) or trackers with automated and continuous self-monitoring and feedback.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

PubMed and seven additional databases, from 2007 to 2020.

STUDY SELECTION

Randomised controlled trials in adults (18-65 years old) without chronic illness, testing a mobile app or an activity tracker, with any comparison, where the main outcome was a physical activity measure. Independent screening was conducted.

DATA EXTRACTION AND SYNTHESIS

We conducted random effects meta-analysis and all effect sizes were transformed into standardised difference in means (SDM). We conducted exploratory metaregression with continuous and discrete moderators identified as statistically significant in subgroup analyses.

MAIN OUTCOME MEASURES

Physical activity: daily step counts, min/week of moderate-to-vigorous physical activity, weekly days exercised, min/week of total physical activity, metabolic equivalents.

RESULTS

Thirty-five studies met inclusion criteria and 28 were included in the meta-analysis (n=7454 participants, 28% women). The meta-analysis showed a small-to-moderate positive effect on physical activity measures (SDM 0.350, 95% CI 0.236 to 0.465, I²=69%, T ²=0.051) corresponding to 1850 steps per day (95% CI 1247 to 2457). Interventions including text-messaging and personalisation features were significantly more effective in subgroup analyses and metaregression.

CONCLUSION

Interventions using apps or trackers seem to be effective in promoting physical activity. Longer studies are needed to assess the impact of different intervention components on long-term engagement and effectiveness.

Effectiveness of an mHealth Intervention Combining a Smartphone App and Smart Band on Body Composition in an Overweight and Obese Population: Randomized Controlled Trial (EVIDENT 3 Study)

Background

Mobile health (mHealth) is currently among the supporting elements that may contribute to an improvement in health markers by helping people adopt healthier lifestyles. mHealth interventions have been widely reported to achieve greater weight loss than other approaches, but their effect on body composition remains unclear.

Objective

This study aimed to assess the short-term (3 months) effectiveness of a mobile app and a smart band for losing weight and changing body composition in sedentary Spanish adults who are overweight or obese.

Methods

A randomized controlled, multicenter clinical trial was conducted involving the participation of 440 subjects from primary care centers, with 231 subjects in the intervention group (IG; counselling with smartphone app and smart band) and 209 in the control group (CG; counselling only). Both groups were counselled about healthy diet and physical activity. For the 3-month intervention period, the IG was trained to use a smartphone app that involved self-monitoring and tailored feedback, as well as a smart band that recorded daily physical activity (Mi Band 2, Xiaomi). Body composition was measured using the InBody 230 bioimpedance device (InBody Co., Ltd), and physical activity was measured using the International Physical Activity Questionnaire.

Results

The mHealth intervention produced a greater loss of body weight (–1.97 kg, 95% CI –2.39 to –1.54) relative to standard counselling at 3 months (–1.13 kg, 95% CI –1.56 to –0.69). Comparing groups, the IG achieved a weight loss of 0.84 kg more than the CG at 3 months. The IG showed a decrease in body fat mass (BFM; –1.84 kg, 95% CI –2.48 to –1.20), percentage of body fat (PBF; –1.22%, 95% CI –1.82% to 0.62%), and BMI (–0.77 kg/m², 95% CI –0.96 to 0.57). No significant changes were observed in any of these parameters in men; among women, there was a significant decrease in BMI in the IG compared with the CG. When subjects were grouped according to baseline BMI, the overweight group experienced a change in BFM of –1.18 kg (95% CI –2.30 to –0.06) and BMI of –0.47 kg/m² (95% CI –0.80 to –0.13), whereas the obese group only experienced a change in BMI of –0.53 kg/m² (95% CI –0.86 to –0.19). When the data were analyzed according to physical activity, the moderate-vigorous physical activity group showed significant changes in BFM of –1.03 kg (95% CI –1.74 to –0.33), PBF of –0.76% (95% CI –1.32% to –0.20%), and BMI of –0.5 kg/m² (95% CI –0.83 to –0.19).

Conclusions

The results from this multicenter, randomized controlled clinical trial study show that compared with standard counselling alone, adding a self-reported app and a smart band obtained beneficial results in terms of weight loss and a reduction in BFM and PBF in female subjects with a BMI less than 30 kg/m² and a moderate-vigorous physical activity level. Nevertheless, further studies are needed to ensure that this profile benefits more than others from this intervention and to investigate modifications of this intervention to achieve a global effect.

Trial Registration

Clinicaltrials.gov NCT03175614; https://clinicaltrials.gov/ct2/show/NCT03175614.

International Registered Report Identifier (IRRID)

RR2-10.1097/MD.0000000000009633

Fitbit-Based Interventions for Healthy Lifestyle Outcomes: Systematic Review and Meta-Analysis

BACKGROUND

Unhealthy behaviors, such as physical inactivity, sedentary lifestyle, and unhealthful eating, remain highly prevalent, posing formidable challenges in efforts to improve cardiovascular health. While traditional interventions to promote healthy lifestyles are both costly and effective, wearable trackers, especially Fitbit devices, can provide a low-cost alternative that may effectively help large numbers of individuals become more physically fit and thereby maintain a good health status.

OBJECTIVE

The objectives of this meta-analysis are (1) to assess the effectiveness of interventions that incorporate a Fitbit device for healthy lifestyle outcomes (eg, steps, moderate-to-vigorous physical activity, and weight) and (2) to identify which additional intervention components or study characteristics are the most effective at improving healthy lifestyle outcomes.

METHODS

A systematic review was conducted, searching the following databases from 2007 to 2019: MEDLINE, EMBASE, CINAHL, and CENTRAL (Cochrane). Studies were included if (1) they were randomized controlled trials, (2) the intervention involved the use of a Fitbit device, and (3) the reported outcomes were related to healthy lifestyles. The main outcome measures were related to physical activity, sedentary behavior, and weight. All the studies were assessed for risk of bias using Cochrane criteria. A random-effects meta-analysis was conducted to estimate the treatment effect of interventions that included a Fitbit device compared with a control group. We also conducted subgroup analysis and fuzzy-set qualitative comparative analysis (fsQCA) to further disentangle the effects of intervention components.

RESULTS

Our final sample comprised 41 articles reporting the results of 37 studies. For Fitbit-based interventions, we found a statistically significant increase in daily step count (mean difference [MD] 950.54, 95% CI 475.89-1425.18; P<.001) and moderate-to-vigorous physical activity (MD 6.16, 95% CI 2.80-9.51; P<.001), a significant decrease in weight (MD -1.48, 95% CI -2.81 to -0.14; P=.03), and a nonsignificant decrease in objectively assessed and self-reported sedentary behavior (MD -10.62, 95% CI -35.50 to 14.27; P=.40 and standardized MD -0.11, 95% CI -0.48 to 0.26; P=.56, respectively). In general, the included studies were at low risk for bias, except for performance bias. Subgroup analysis and fsQCA demonstrated that, in addition to the effects of the Fitbit devices, setting activity goals was the most important intervention component.

CONCLUSIONS

The use of Fitbit devices in interventions has the potential to promote healthy lifestyles in terms of physical activity and weight. Fitbit devices may be useful to health professionals for patient monitoring and support.

TRIAL REGISTRATION

PROSPERO International Prospective Register of Systematic Reviews CRD42019145450; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42019145450.

Effects of Motivational Interviewing and Wearable Fitness Trackers on Motivation and Physical Activity: A Systematic Review

OBJECTIVE

To systematically review the impacts of Wearable Fitness Trackers (WFTs), Motivational Interviewing (MI), and Self Determination Theory (SDT)-based interventions on physical activity (PA) and motivation for PA.

DATA SOURCE

Manuscripts published between 2008 and 2018 in PubMed, Web of Science, CABAbstracts, and SPORTDiscus database were reviewed.

STUDY INCLUSION AND EXCLUSION CRITERIA

Inclusion criteria were original pilot studies, randomized controlled trials (RCT), cross-sectional studies, qualitative assessments, prospective cohort studies, longitudinal observational studies, and pretest posttest designs published in peer-reviewed journals.

DATA EXTRACTION

Studies were evaluated by 2 independent researchers for inclusion.

DATA SYNTHESIS

Extracted data were synthesized in a tabular format and narrative summary.

RESULTS

Twenty-six studies met final inclusion criteria, 10 addressed WFT use and PA behavior, 4 investigated WFT use and its association with motivation for PA, and 10 examined SDT and/or MI and their effect on motivation for PA and/or PA behavior. Finally, 2 studies addressed SDT-based MI, WFT use, and the combined effect on PA behavior.

CONCLUSIONS

While SDT-based interventions and MI positively impact motivation for PA and PA behavior, WFTs revealed mixed results. Wearable Fitness Trackers prove effective among individuals not currently meeting PA guidelines but have little impact on other populations. Self Determination Theory, MI, and WFTs use provides a promising combination of interventions to increase PA among sedentary individuals, though research is limited.

Examining the Relationship Between Biometric Indicators and Pharmacy Students' Academic Performance

Objective. To use a fitness tracking device to track student wellness habits, specifically number of steps, activity, and sleep duration, in an attempt to identify relationships between these variables and academic performance outcomes such as examination scores and course grades. Methods. A fitness tracker was issued to second professional year Doctor of Pharmacy (PharmD) students to track their daily number of steps, activity levels, and minutes of sleep. Individual data from these devices were collected using a cloud-based data aggregation platform. The outcome variables of interest were student grade point average (GPA) in core courses, as well as examination grades for 17 examinations administered across eight required courses during the study period. After exploratory analyses, the primary research questions relating steps and sleep to academic performance were addressed with a series of linear regression models. Results. No significant, identifiable relationships were found between examination grades or course GPA and the variables of interest. There was a significant negative relationship between the number of steps students took 72-hours before an examination and performance on the examination where students in the low activity group significantly outperformed those in the high activity group by an average of two points. Participants took an average of 1,466 fewer steps prior to an examination. Conclusion. Sleep and physical activity were not robust predictors of examination scores and course grades in this cohort of PharmD students. While the fitness tracker served as an impetus for the students to be more cognizant of their activity, the capital expenditure for the devices did not result in improved academic performance.

Feasible but Not Yet Efficacious: A Scoping Review of Wearable Activity Monitors in Interventions Targeting Physical Activity, Sedentary Behavior, and Sleep

Purpose of Review

The present review aimed to explore the range and characteristics of interventions that utilize WAM and descriptively summarize the efficacy of these interventions.

Recent Findings

A total of 65 articles (61 studies) were included in this review. Most of the WAM-based interventions (n=58) were designed to improve physical activity (PA). Interventions targeting sedentary behavior (SB) were much less common (n=12), and even less frequent were WAM-based sleep interventions (n=3). Most studies tested the feasibility of WAM-based interventions; hence, efficacy of these interventions in improving PA, SB, and/or sleep could not be conclusively determined. Nonetheless, WAM-based interventions showed considerable potential in increasing PA and decreasing SB.

Summary

WAM-based PA interventions exhibited preliminary efficacy in increasing PA. Although not as many interventions were focused on SB, current interventions also showed potential in decreasing sedentary time. Meanwhile, more evidence is needed to determine the utility of WAM in improving sleep. Major challenges with including WAM as part of interventions are reduced engagement in using the devices over time and the rapid changes in technology resulting in devices becoming obsolete soon after completion of an efficacy trial.

The effectiveness of wearable technologies as physical activity interventions in weight control: A systematic review and meta-analysis of randomized controlled trials

Wearable technologies represent a novel approach in the prevention of obesity and overweight that encourages users to engage in physical activities aided by technological assistance. This is the first meta-analysis to investigate the effects of wearable technologies as physical activity interventions on weight control. Various electronic databases were searched to select eligible articles, including EBSCO, ScienceDirect, and PubMed, from the first available date to January 9, 2019. All analyses were performed using a random-effects model. Moderator analyses were conducted to investigate differences in the effect size. This meta-analysis of 19 randomized controlled trials indicated that wearable technologies as a physical activity intervention achieved a moderate and significant effect size on body weight and waist circumference and large and significant effect sizes on the body mass index. A subgroup analysis confirmed that wearable technologies were more efficient for weight control in individuals with obesity and chronic diseases. A duration of using wearable technologies for a total of more than or equal to 12 weeks was more effective. Meta-regressions have also revealed that the body weight of individuals who received an additional week of treatment could be reduced by more than 0.37%. Wearable technologies offer innovative platforms of physical activity interventions and an efficient method for weight control.

Impact of wearable physical activity monitoring devices with exercise prescription or advice in the maintenance phase of cardiac rehabilitation: systematic review and meta-analysis

BACKGROUND

Physical activity (PA) is a component of cardiac rehabilitation (CR). However, life-long engagement in PA is required to maintain benefits gained. Wearable PA monitoring devices (WPAM) are thought to increase PA. There appear to be no reviews which investigate the effect of WPAM in cardiac populations. We firstly aimed to systematically review randomised controlled trials within the cardiac population that investigated the effect WPAM had through the maintenance phase of CR. We specifically examined the effect on cardiorespiratory fitness (CRF), amount and intensity of daily PA, and sedentary time. Secondly, we aimed to collate outcome measures reported, reasons for drop out, adverse events, and psychological impact from utilising a WPAM.

METHODS

A systematic search (up to January 2019) of relevant databases was completed, followed by a narrative synthesis, meta-analysis and qualitative analysis.

RESULTS

Nine studies involving 1,352 participants were included. CRF was improved to a greater extent in participants using WPAM with exercise prescription or advice compared with controls (MD 1.65 mL/kg/min;95% confidence interval [CI; 0.64-2.66]; p = 0.001; I2 = 0%). There was no significant between group difference in six-minute walk test distance. In 70% of studies, step count was greater in participants using a WPAM with exercise prescription or advice, however the overall effect was not significant (SMD 0.45;95% [CI; - 0.17-1.07] p = 0.15; I2 = 81%). A sensitivity analysis resulted in significantly greater step counts in participants using a WPAM with exercise prescription or advice and reduced the heterogeneity from 81 to 0% (SMD 0.78;95% [CI;0.54-1.02]; p < 0.001; I2 = 0%). Three out of four studies reporting on intensity, found significantly increased time spent in moderate and moderate-vigorous intensity PA. No difference between groups was found for sedentary time. Three of six studies reported improved psychological benefits.No cardiac adverse events related to physical activity were reported and 62% of non-cardiac adverse events were primarily musculoskeletal injuries. Reasons for dropping out included medical conditions, lack of motivation, loss of interest, and technical difficulties.

CONCLUSIONS

Our meta-analysis showed WPAM with exercise prescription or advice are superior to no device in improving CRF in the maintenance phase of CR and no cardiac adverse events were reported with WPAM use. Our qualitative analysis showed evidence in favour of WPAM with exercise prescription or advice for both CRF and step count. WPAM with exercise prescription or advice did not change sedentary time. Psychological health and exercise intensity may potentially be enhanced by WPAM with exercise prescription or advice, however further research would strengthen this conclusion.

TRIAL REGISTRATION

PROSPERO Registration Number: CRD42019106591.

Use of Physical Activity Monitoring Devices by Families in Rural Communities: Qualitative Approach

BACKGROUND

Several studies support the impact of information communication technology-based interventions to promote physical activity among youth. However, little is known on how technology can be used by the entire family to encourage healthy behavior. Previous studies showed that children and youth rely and are dependent upon the decisions and values of their caregivers when it comes to having a healthy lifestyle. Thus, the exploration of behavior and attitudes of the entire family is needed.

OBJECTIVE

The study aimed to explore (1) perceptions of how the use of physical activity tracking devices (Fitbit Zip) by families in rural communities influence their patterns of participation in physical activity, (2) how attitudes toward physical activity change as a result of using physical activity tracking devices as a family, and (3) what factors influence participation in physical activity among families in rural communities.

METHODS

A total of 11 families with 1 to 3 children of different ages (7-13 years) took part in semistructured group interviews following 2 weeks of using physical activity tracking devices (Fitbit Zip) as a family. The participants were asked to discuss their experience using the Fitbit Zip as a family, the motivation to be physically active, the changes in their pattern of participation in those activities, the level of engagement by different family members, and the factors that affected their participation. All interviews were voice-recorded with the participants' permission and later transcribed verbatim using pseudonyms. To analyze the data, the principal investigator (IS) used open, axial, and selective coding techniques.

RESULTS

A total of 3 themes and several subthemes appeared from the data. The families in rural communities reported no or minimal changes in physical activities as a result of using physical activity tracking devices (Fitbit Zip) because of a lack of interest or an already active lifestyle. However, the attitude toward physical activity was altered. The family members reported an increased awareness of their activity level, introduced more conversations about active and healthy lifestyles, and changed their view of physical activity to a more positive one. The participants described the changes they were able to make and the constraining factors that stopped them from making further changes in their lifestyle.

CONCLUSIONS

Technology might serve as a facilitator to participation in physical activity among families. Technology can motivate the change in attitude toward active recreation. As long-term changes in lifestyle require internal motivation, the change in the attitude might have a more long-lasting impact than the change in the immediate behavior. More longitudinal studies are needed to further explore long-term change in both behavior and attitude toward physical activity. Additional exploration of constraints to participation in physical activity among families is also an important area of exploration.