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)

Automated lifestyle interventions and weight loss: a systematic review of randomized controlled trials

BACKGROUND/OBJECTIVES

Overweight and obesity drive cardiometabolic disease and high-intensity lifestyle interventions are standard. However, many health-systems cannot offer these interventions and many patients cannot participate even when available. Trials have assessed automated digital lifestyle interventions to improve accessibility. This systematic review identified automated digital lifestyle interventions and assessed their impact on weight loss.

SUBJECTS/METHODS

The review (CRD42023435700) identified randomized controlled trials of at least 3-months duration assessing automated digital lifestyle interventions' impact on weight loss. Data were managed through Covidence with double-blinded screening of titles/abstracts and double-blinded full-text review to determine study inclusion. Data extraction was completed by one reviewer (NWC) and verified by a second (MM, JS, TE, CE). The Cochrane Collaboration's tool was used to assess bias risk and study quality was rated as High, Moderate, Low, or Very Low.

RESULTS

The search identified 1817 citations. The full-text of 60 reports were assessed and 17 reports of 16 studies were included. The majority (63%) were of moderate quality. No intervention produced 5% weight loss from baseline. Intervention components with the largest impact were text message encouragement and education with a cognitive behavioral approach. No specific form of self-monitoring was most effective, though some form of self-monitoring was included in most trials.

CONCLUSIONS

Some components of the automated digital lifestyle interventions showed promise. Research is needed to optimize these components (e.g., tailored messaging, cognitive-behavioral approaches) balanced with human contact. Considering the magnitude of the problem and its disproportionate impact on low socioeconomic and minority patients, interventions optimized for effect and scalability are needed to address overweight and obesity.

Recommender systems use in weight management mHealth interventions: A scoping review

The use of recommender systems in mobile health apps for weight control has grown, but user app uptake and engagement remain limited. The objective of our scoping review was to explore the influence of recommender systems on mHealth app user engagement, identify the theoretical frameworks that have been applied on digital health interventions designed for weight management, and examine the key aspects that support tailoring user engagement through recommender systems. Based on existing literature, we identified 13 articles on recommender systems for weight management. Themes emerged, including theoretical underpinnings, authors' domain knowledge, user motivation, and design. Most studies used constructs from the social cognitive theory. We found inconsistencies between authors' domain knowledge and the intervention's content, with few professionals from the health and psychology fields. Only 46% of articles measured user engagement, whereas gamification and tailored messages were common app features. Despite some positive weight change results, more attention is needed toward implementing behavior theory and other strategies to promote app user engagement. Future studies should more accurately measure user motivation and identify the best features and behavioral constructs to increase app user interaction. Larger studies with a more diverse population are needed to generalize findings and evaluate weight loss maintenance and physical activity habits among users of recommender system.

Obesity and cardiovascular disease: an ESC clinical consensus statement

The global prevalence of obesity has more than doubled over the past four decades, currently affecting more than a billion individuals. Beyond its recognition as a high-risk condition that is causally linked to many chronic illnesses, obesity has been declared a disease per se that results in impaired quality of life and reduced life expectancy. Notably, two-thirds of obesity-related excess mortality is attributable to cardiovascular disease. Despite the increasingly appreciated link between obesity and a broad range of cardiovascular disease manifestations including atherosclerotic disease, heart failure, thromboembolic disease, arrhythmias, and sudden cardiac death, obesity has been underrecognized and sub-optimally addressed compared with other modifiable cardiovascular risk factors. In the view of major repercussions of the obesity epidemic on public health, attention has focused on population-based and personalized approaches to prevent excess weight gain and maintain a healthy body weight from early childhood and throughout adult life, as well as on comprehensive weight loss interventions for persons with established obesity. This clinical consensus statement by the European Society of Cardiology discusses current evidence on the epidemiology and aetiology of obesity; the interplay between obesity, cardiovascular risk factors and cardiac conditions; the clinical management of patients with cardiac disease and obesity; and weight loss strategies including lifestyle changes, interventional procedures, and anti-obesity medications with particular focus on their impact on cardiometabolic risk and cardiac outcomes. The document aims to raise awareness on obesity as a major risk factor and provide guidance for implementing evidence-based practices for its prevention and optimal management within the context of primary and secondary cardiovascular disease prevention.

Obesity and cardiovascular disease: an ESC clinical consensus statement

The global prevalence of obesity has more than doubled over the past four decades, currently affecting more than a billion individuals. Beyond its recognition as a high-risk condition that is causally linked to many chronic illnesses, obesity has been declared a disease per se that results in impaired quality of life and reduced life expectancy. Notably, two-thirds of obesity-related excess mortality is attributable to cardiovascular disease. Despite the increasingly appreciated link between obesity and a broad range of cardiovascular disease manifestations including atherosclerotic disease, heart failure, thromboembolic disease, arrhythmias, and sudden cardiac death, obesity has been underrecognized and sub-optimally addressed compared with other modifiable cardiovascular risk factors. In the view of major repercussions of the obesity epidemic on public health, attention has focused on population-based and personalized approaches to prevent excess weight gain and maintain a healthy body weight from early childhood and throughout adult life, as well as on comprehensive weight loss interventions for persons with established obesity. This clinical consensus statement by the European Society of Cardiology discusses current evidence on the epidemiology and aetiology of obesity; the interplay between obesity, cardiovascular risk factors and cardiac conditions; the clinical management of patients with cardiac disease and obesity; and weight loss strategies including lifestyle changes, interventional procedures, and anti-obesity medications with particular focus on their impact on cardiometabolic risk and cardiac outcomes. The document aims to raise awareness on obesity as a major risk factor and provide guidance for implementing evidence-based practices for its prevention and optimal management within the context of primary and secondary cardiovascular disease prevention.

The role of mobile health applications (mHealth apps) in reshaping the body weight for better healthcare: A cross-sectional study

Objectives

Obesity is a chronic, multifaceted, leading health problem causing numerous non-communicable diseases with a huge burden on the global healthcare system and economies. Worldwide, multiple interventions have been familiarized for weight reduction strategies, however, in recent years, mobile health applications (mHealth apps) for reshaping weight reduction have been introduced. Therefore, this study aimed to investigate the role of mobile health applications in reducing weight among users in Riyadh, Saudi Arabia.

Methods

This questionnaire-based cross-sectional study was conducted in the Department of Family and Community Medicine, and Medical Education, College of Medicine, King Saud University, Riyadh from May 2019 to December 2022. A total of 502 participants, 332 (66.1%) females and 170 (33.9%) males aged 18-50 years, using smartphones, residing in Riyadh, Saudi Arabia were recruited. The questionnaire was distributed via social media platforms including WhatsApp, and emails and information were recorded.

Results

Among 502 participants, 221 (44.02%) were using mobile health applications and 281 (55.98%) did not use mobile health applications. The results revealed that the participants who have been using mHealth apps for the last six months had significantly decreased body weight compared to those who did not use the mHealth apps (p=0.001).

Conclusions

The study participants using mobile health applications (mHealth apps) had significantly reduced their body weight and felt healthier. The mHealth apps provide health-related information regularly to individuals to track their weight, monitor diet, and physical activity, and information about their overall health.

Shining a spotlight on sarcopenia and myosteatosis in liver disease and liver transplantation: Potentially modifiable risk factors with major clinical impact

Muscle-wasting and disease-related malnutrition are highly prevalent in patients with chronic liver diseases (CLD) as well as in liver transplant (LT) candidates. Alterations of body composition (BC) such as sarcopenia, myosteatosis and sarcopenic obesity and associated clinical frailty were tied to inferior clinical outcomes including hospital admissions, length of stay, complications, mortality and healthcare costs in various patient cohorts and clinical scenarios. In contrast to other inherent detrimental individual characteristics often observed in these complex patients, such as comorbidities or genetic risk, alterations of the skeletal muscle and malnutrition are considered as potentially modifiable risk factors with a major clinical impact. Even so, there is only limited high-level evidence to show how these pathologies should be addressed in the clinical setting. This review discusses the current state-of-the-art on the role of BC assessment in clinical outcomes in the setting of CLD and LT focusing mainly on sarcopenia and myosteatosis. We focus on the disease-related pathophysiology of BC alterations. Based on these, we address potential therapeutic interventions including nutritional regimens, physical activity, hormone and targeted therapies. In addition to summarizing existing knowledge, this review highlights novel trends, and future perspectives and identifies persisting challenges in addressing BC pathologies in a holistic way, aiming to improve outcomes and quality of life of patients with CLD awaiting or undergoing LT.

Using explainable machine learning and fitbit data to investigate predictors of adolescent obesity

Sociodemographic and lifestyle factors (sleep, physical activity, and sedentary behavior) may predict obesity risk in early adolescence; a critical period during the life course. Analyzing data from 2971 participants (M = 11.94, SD = 0.64 years) wearing Fitbit Charge HR 2 devices in the Adolescent Brain Cognitive Development (ABCD) Study, glass box machine learning models identified obesity predictors from Fitbit-derived measures of sleep, cardiovascular fitness, and sociodemographic status. Key predictors of obesity include identifying as Non-White race, low household income, later bedtime, short sleep duration, variable sleep timing, low daily step counts, and high heart rates (AUCMean = 0.726). Findings highlight the importance of inadequate sleep, physical inactivity, and socioeconomic disparities, for obesity risk. Results also show the clinical applicability of wearables for continuous monitoring of sleep and cardiovascular fitness in adolescents. Identifying the tipping points in the predictors of obesity risk can inform interventions and treatment strategies to reduce obesity rates in adolescents.

Evaluation of physical activity before and after respiratory rehabilitation in normal weight individuals with asthma: a feasibility study

Background

Individuals with asthma spend less time engaging in physical activity compared to the general population. Increasing physical activity has become a patient-centered goal for the treatment of treatable traits of individuals with asthma. There are data showing the possible effects of a pulmonary rehabilitation program on physical activity in obese individuals with asthma but not in normal-weight asthmatics. The objective of this feasibility study is to estimate the number of daily steps and time spent on activity in normal-weight individuals with asthma, measured before and after a pulmonary rehabilitation program.

Methods

Normal-weight individuals with moderate to severe asthma were evaluated. The individuals measured their daily steps with an accelerometer for 5 days before and after a pulmonary rehabilitation program. The study was registered on ClinicalTrials.gov: NCT05486689.

Results

In total, 17 participants were enrolled; one dropout and data on the time in activity of two individuals are missing due to a software error during the download. Data from 16 patients were analyzed. The median number of steps/day at baseline was 5,578 (25th, 75th percentiles = 4,874, 9,685) while the median activity time was 214 min (25th, 75th percentiles = 165, 239). After the rehabilitation program, the number of daily steps increased by a median value of 472 (p-value = 0.561) and the time in activity reduced by 17 min (p-value = 0.357). We also found a significant difference in quality of life, muscle strength, and exercise capacity.

Conclusions

The results of this study make it possible to calculate the sample size of future studies whose main outcome is daily steps in normal-weight individuals with asthma. The difficulties encountered in downloading time in activity data do not allow the same for this outcome.

Clinical Trial Registration

ClinicalTrials.gov, identifier NCT05486689.

Can Digital Technologies Be Useful for Weight Loss in Individuals with Overweight or Obesity? A Systematic Review

Digital technologies have greatly developed and impacted several aspects of life, including health and lifestyle. Activity tracking, mobile applications, and devices may also provide messages and goals to motivate adopting healthy behaviors, namely physical activity and dietary changes. This review aimed to assess the effectiveness of digital resources in supporting behavior changes, and thus influencing weight loss, in people with overweight or obesity. A systematic review was conducted according to the PRISMA guidelines. The protocol was registered in PROSPERO (CRD42023403364). Randomized Controlled Trials published from the database's inception to 8 November 2023 and focused on digital-based technologies aimed at increasing physical activity for the purpose of weight loss, with or without changes in diet, were considered eligible. In total, 1762 studies were retrieved and 31 met the inclusion criteria. Although they differed in the type of technology used and in their design, two-thirds of the studies reported significantly greater weight loss among electronic device users than controls. Many of these studies reported tailored or specialist-guided interventions. The use of digital technologies may be useful to support weight-loss interventions for people with overweight or obesity. Personalized feedback can increase the effectiveness of new technologies in motivating behavior changes.

Mobile health (m-health) smartphone interventions for adolescents and adults with overweight or obesity

BACKGROUND

Obesity is considered to be a risk factor for various diseases, and its incidence has tripled worldwide since 1975. In addition to potentially being at risk for adverse health outcomes, people with overweight or obesity are often stigmatised. Behaviour change interventions are increasingly delivered as mobile health (m-health) interventions, using smartphone apps and wearables. They are believed to support healthy behaviours at the individual level in a low-threshold manner.

OBJECTIVES

To assess the effects of integrated smartphone applications for adolescents and adults with overweight or obesity.

SEARCH METHODS

We searched CENTRAL, MEDLINE, PsycINFO, CINAHL, and LILACS, as well as the trials registers ClinicalTrials.gov and World Health Organization International Clinical Trials Registry Platform on 2 October 2023 (date of last search for all databases). We placed no restrictions on the language of publication.

SELECTION CRITERIA

Participants were adolescents and adults with overweight or obesity. Eligible interventions were integrated smartphone apps using at least two behaviour change techniques. The intervention could target physical activity, cardiorespiratory fitness, weight loss, healthy diet, or self-efficacy. Comparators included no or minimal intervention (NMI), a different smartphone app, personal coaching, or usual care. Eligible studies were randomised controlled trials of any duration with a follow-up of at least three months.

DATA COLLECTION AND ANALYSIS

We used standard Cochrane methodology and the RoB 2 tool. Important outcomes were physical activity, body mass index (BMI) and weight, health-related quality of life, self-efficacy, well-being, change in dietary behaviour, and adverse events. We focused on presenting studies with medium- (6 to < 12 months) and long-term (≥ 12 months) outcomes in our summary of findings table, following recommendations in the core outcome set for behavioural weight management interventions.

MAIN RESULTS

We included 18 studies with 2703 participants. Interventions lasted from 2 to 24 months. The mean BMI in adults ranged from 27 to 50, and the median BMI z-score in adolescents ranged from 2.2 to 2.5. Smartphone app versus no or minimal intervention Thirteen studies compared a smartphone app versus NMI in adults; no studies were available for adolescents. The comparator comprised minimal health advice, handouts, food diaries, smartphone apps unrelated to weight loss, and waiting list. Measures of physical activity: at 12 months' follow-up, a smartphone app compared to NMI probably reduces moderate to vigorous physical activity (MVPA) slightly (mean difference (MD) -28.9 min/week (95% confidence interval (CI) -85.9 to 28; 1 study, 650 participants; moderate-certainty evidence)). We are very uncertain about the results of estimated energy expenditure and cardiorespiratory fitness at eight months' follow-up. A smartphone app compared with NMI probably results in little to no difference in changes in total activity time at 12 months' follow-up and leisure time physical activity at 24 months' follow-up. Anthropometric measures: a smartphone app compared with NMI may reduce BMI (MD of BMI change -2.6 kg/m2, 95% CI -6 to 0.8; 2 studies, 146 participants; very low-certainty evidence) at six to eight months' follow-up, but the evidence is very uncertain. At 12 months' follow-up, a smartphone app probably resulted in little to no difference in BMI change (MD -0.1 kg/m2, 95% CI -0.4 to 0.3; 1 study; 650 participants; moderate-certainty evidence). A smartphone app compared with NMI may result in little to no difference in body weight change (MD -2.5 kg, 95% CI -6.8 to 1.7; 3 studies, 1044 participants; low-certainty evidence) at 12 months' follow-up. At 24 months' follow-up, a smartphone app probably resulted in little to no difference in body weight change (MD 0.7 kg, 95% CI -1.2 to 2.6; 1 study, 245 participants; moderate-certainty evidence). A smartphone app compared with NMI may result in little to no difference in self-efficacy for a physical activity score at eight months' follow-up, but the results are very uncertain. A smartphone app probably results in little to no difference in quality of life and well-being at 12 months (moderate-certainty evidence) and in little to no difference in various measures used to inform dietary behaviour at 12 and 24 months' follow-up. We are very uncertain about adverse events, which were only reported narratively in two studies (very low-certainty evidence). Smartphone app versus another smartphone app Two studies compared different versions of the same app in adults, showing no or minimal differences in outcomes. One study in adults compared two different apps (calorie counting versus ketogenic diet) and suggested a slight reduction in body weight at six months in favour of the ketogenic diet app. No studies were available for adolescents. Smartphone app versus personal coaching Only one study compared a smartphone app with personal coaching in adults, presenting data at three months. Two studies compared these interventions in adolescents. A smartphone app resulted in little to no difference in BMI z-score compared to personal coaching at six months' follow-up (MD 0, 95% CI -0.2 to 0.2; 1 study; 107 participants). Smartphone app versus usual care Only one study compared an app with usual care in adults but only reported data at three months on participant satisfaction. No studies were available for adolescents. We identified 34 ongoing studies.

AUTHORS' CONCLUSIONS

The available evidence is limited and does not demonstrate a clear benefit of smartphone applications as interventions for adolescents or adults with overweight or obesity. While the number of studies is growing, the evidence remains incomplete due to the high variability of the apps' features, content and components, which complicates direct comparisons and assessment of their effectiveness. Comparisons with either no or minimal intervention or personal coaching show minor effects, which are mostly not clinically significant. Minimal data for adolescents also warrants further research. Evidence is also scarce for low- and middle-income countries as well as for people with different socio-economic and cultural backgrounds. The 34 ongoing studies suggest sustained interest in the topic, with new evidence expected to emerge within the next two years. In practice, clinicians and healthcare practitioners should carefully consider the potential benefits, limitations, and evolving research when recommending smartphone apps to adolescents and adults with overweight or obesity.

Enhancing Behavioural Changes: A Narrative Review on the Effectiveness of a Multifactorial APP-Based Intervention Integrating Physical Activity

The rapid evolution of technologies is a key innovation in the organisation and management of physical activities (PA) and sports. The increase in benefits and opportunities related to the adoption of technologies for both the promotion of a healthy lifestyle and the management of chronic diseases is evident. In the field of telehealth, these devices provide personalised recommendations, workout monitoring and injury prevention. The study aimed to provide an overview of the landscape of technology application to PA organised to promote active lifestyles and improve chronic disease management. This review identified specific areas of focus for the selection of articles: the utilisation of mobile APPs and technological devices for enhancing weight loss, improving cardiovascular health, managing diabetes and cancer and preventing osteoporosis and cognitive decline. A multifactorial intervention delivered via mobile APPs, which integrates PA while managing diet or promoting social interaction, is unquestionably more effective than a singular intervention. The main finding related to promoting PA and a healthy lifestyle through app usage is associated with "behaviour change techniques". Even when individuals stop using the APP, they often maintain the structured or suggested lifestyle habits initially provided by the APP. Various concerns regarding the excessive use of APPs need to be addressed.

Efficacy of an app-based multimodal lifestyle intervention on body weight in persons with obesity: results from a randomized controlled trial

BACKGROUND

Despite an increasing number of smartphone applications (apps) addressing weight management, data on the effect of app-based multimodal obesity treatment approaches on weight loss is limited. This study aimed to examine the effect of a digital multimodal weight loss intervention program delivered by an app on body weight in persons with obesity.

METHODS

For this single-centre randomized controlled study, 168 adults with a body mass index (BMI) between 30.0 and 40.0 kg/m2 without severe comorbidities were recruited in the region of Munich and randomized into two intervention groups. The ADHOC group received an app-based multimodal weight loss program from baseline on for 12 weeks plus 12 weeks of follow-up. The EXPECT group received the app-based intervention for 12 weeks after 12 weeks of "waiting" (no intervention). Anthropometric data, data on quality of life (EuroQol, EQ-5D-5L), and app usage data were collected.

RESULTS

64.3% of study participants were women, mean age was 46.8 ± 11.0 years, and mean BMI was 34.2 ± 2.8 kg/m2. The completers analysis resulted in a weight loss of 3.2 ± 3.2 kg (3.2 ± 3.0%) in the ADHOC group and 0.4 ± 2.6 kg (0.3 ± 2.6%) in the EXPECT group after 12 weeks, with a significant difference between the groups (β [95% CI] = -2.9 [-3.8; -1.9], p < 0.001). Completers in the ADHOC group showed weight maintenance after 24 weeks. The time spent on the app was associated with weight reduction (β [95% CI] = -0.10 [-0.18; -0.01], p = 0.03).

CONCLUSIONS

Application of a multimodal app-based weight loss program results in moderate weight loss in persons with obesity.

TRIAL REGISTRATION

This study was registered in the German Clinical Trials Register (Registration number: DRKS00025291).

The Efficacy of an mHealth App in Facilitating Weight Loss Among Japanese Fitness Center Members: Regression Analysis Study

BACKGROUND

Self-tracking smartphone apps have emerged as promising tools to encourage healthy behaviors. In this longitudinal study, we used gym use data from members of a major fitness club that operates gyms throughout Japan from January 2014 to December 2019.

OBJECTIVE

Our objective was to assess the extent to which a health and fitness self-tracking mobile app introduced to gym members on January 1, 2018, contributed to their weight loss. The app allows users to input information regarding diet, sleep, weight, and gym exercise so that they can receive personalized feedback from an artificial intelligence chatbot to improve their health behaviors.

METHODS

We used linear regression to quantify the association between app use and weight loss. The primary outcome of the study was the weight loss achieved by each gym user, which was calculated as the difference between their initial and final weights in kilograms, as recorded in the app. Individuals who did not attend the gym or failed to use the mobile app at least twice during the study period were excluded from the analysis. The model accounted for age, gender, distance between the gym and the member's residence, average weekly number of times a member used the gym, user's gym membership length in weeks, average weekly number of times a member input information into the app, and the number of weeks that the app was used at least once.

RESULTS

Data from 26,589 participants were analyzed. Statistically significant associations were detected between weight loss and 2 metrics related to app use: the average weekly frequency of use and the total number of weeks in which the app was used at least once. One input per week was found to be associated with a loss of 62.1 (95% CI 53.8-70.5) g, and 1 week of app use was associated with 21.7 (95% CI 20.5-22.9) g of weight loss from the day of the first input to that of the final input to the app. Furthermore, the average number of times that a member used the gym weekly was also shown to be statistically significantly associated with weight loss: 1 use per week was associated with 255.5 (95% CI 228.5-282.6) g of weight loss.

CONCLUSIONS

This empirical study demonstrated a significant association between weight loss among gym members and not only the frequency of weekly gym use but also the use of a health and fitness self-tracking app. However, further work is needed to examine the mechanisms through which mobile apps affect health behaviors and to identify the specific app features that are most effective in promoting weight loss.

Validity and reliability of a mobile digital imaging analysis trained by a four-compartment model

BACKGROUND

Digital imaging analysis (DIA) estimates collected from mobile applications comprise a novel technique that can collect body composition estimates remotely without the inherent restrictions of other research-grade devices. However, the accuracy of the artificial intelligence used in DIA is reliant on the accuracy of the developmental methods. Few DIA applications are trained by multicompartment models, but this developmental strategy may be most accurate. Thus, the aim of the present study was to assess the precision and agreement of a DIA application with developmental software trained by a four-compartment (4C) model using an actual 4C model as the criterion method.

METHODS

For this cross-sectional study, body composition estimations were collected from 102 participants (63 females, 39 males) using the methods necessary for a rapid 4C model and a DIA application using two different smartphones.

RESULTS

Intraclass correlation coefficients (0.96-0.99; all p < 0.001) and root mean square coefficients of variation (0.5%-3.0%) showed good reliability for body fat percentage, fat mass and fat-free mass. There were no significant mean differences between the 4C model or the DIA estimates for the total sample, by sex, and for non-Hispanic White (n = 61) and Black/African-American (n = 32) participants (all p > 0.050). DIA estimates demonstrated equivalence with the 4C model for all variables but revealed proportional biases that underestimated body fat percentage (both β = -0.25; p < 0.001) and fat mass (both β = -0.07; p < 0.010) at higher degrees of each variable.

CONCLUSIONS

DIA applications trained by a 4C model are reliable and produce body composition estimates equivalent to an actual 4C model.

Digital Health Solutions for Weight Loss and Obesity: A Narrative Review

Personal exercise programmes have long been used and prescribed for weight loss and the improvement of quality of life in obese patients. While individualised programmes are usually the preferred option, they can be more costly and challenging to deliver in person. A move to digital programmes with a wider reach has commenced, and demand has increased due to the SARS-CoV-2 pandemic. In this review, we evaluate the current status of digital exercise programme delivery and its evolution over the past decade, with a focus on personalisation. We used specific keywords to search for articles that met our predetermined inclusion and exclusion criteria in order to provide valuable evidence and insights for future research. We identified 55 studies in total in four key areas of focus, from the more recent development of apps and personal digital assistants to web-based programmes and text or phone call interventions. In summary, we observed that apps may be useful for a low-intensity approach and can improve adherence to programmes through self-monitoring, but they are not always developed in an evidence-based manner. Engagement and adherence are important determinants of weight loss and subsequent weight maintenance. Generally, professional support is required to achieve weight loss goals.

Feasibility and Acceptability of an Internet of Things-Enabled Sedentary Behavior Intervention: Mixed Methods Study

BACKGROUND

Encouraging office workers to break up prolonged sedentary behavior (SB) at work with regular microbreaks can be beneficial yet challenging. The Internet of Things (IoT) offers great promise for delivering more subtle and hence acceptable behavior change interventions in the workplace. We previously developed an IoT-enabled SB intervention, called WorkMyWay, by applying a combination of theory-informed and human-centered design approaches. According to the Medical Research Council's framework for developing and evaluating complex interventions such as WorkMyWay, process evaluation in the feasibility phase can help establish the viability of novel modes of delivery and identify facilitators and barriers to successful delivery.

OBJECTIVE

This study aims to evaluate the feasibility and acceptability of the WorkMyWay intervention and its technological delivery system.

METHODS

A mixed methods approach was adopted. A sample of 15 office workers were recruited to use WorkMyWay during work hours for 6 weeks. Questionnaires were administered before and after the intervention period to assess self-report occupational sitting and physical activity (OSPA) and psychosocial variables theoretically aligned with prolonged occupational SB (eg, intention, perceived behavioral control, prospective memory and retrospective memory of breaks, and automaticity of regular break behaviors). Behavioral and interactional data were obtained through the system database to determine adherence, quality of delivery, compliance, and objective OSPA. Semistructured interviews were conducted at the end of the study, and a thematic analysis was performed on interview transcripts.

RESULTS

All 15 participants completed the study (attrition=0%) and on average used the system for 25 tracking days (out of a possible 30 days; adherence=83%). Although no significant change was observed in either objective or self-report OSPA, postintervention improvements were significant in the automaticity of regular break behaviors (t₁₄=2.606; P=.02), retrospective memory of breaks (t₁₄=7.926; P<.001), and prospective memory of breaks (t₁₄=-2.661; P=.02). The qualitative analysis identified 6 themes, which lent support to the high acceptability of WorkMyWay, though delivery was compromised by issues concerning Bluetooth connectivity and factors related to user behaviors. Fixing technical issues, tailoring to individual differences, soliciting organizational supports, and harnessing interpersonal influences could facilitate delivery and enhance acceptance.

CONCLUSIONS

It is acceptable and feasible to deliver an SB intervention with an IoT system that involves a wearable activity tracking device, an app, and a digitally augmented everyday object (eg, cup). More industrial design and technological development work on WorkMyWay is warranted to improve delivery. Future research should seek to establish the broad acceptability of similar IoT-enabled interventions while expanding the range of digitally augmented objects as the modes of delivery to meet diverse needs.

Effectiveness of Telemedicine for Reducing Cardiovascular Risk: A Systematic Review and Meta-Analysis

BACKGROUND

Cardiovascular diseases are the leading cause of death globally. There are six cardiovascular risk factors: diabetes, hypertension, hypercholesterolemia, overweight, sedentary lifestyle and smoking. Due to the low attendance of healthy people in the health system, the use of telemedicine can influence the acquisition of a heart-healthy lifestyle.

OBJECTIVE

this systematic review and meta-analysis aimed to determine the effectiveness of telemedicine and e-health in reducing cardiovascular risk.

METHODS

A systematic review and meta-analysis were carried out using the PubMed, Scopus, Cinhal and WOS databases. Randomized controlled studies between 2017 and 2022 in which telemedicine was used to reduce any of the risk factors were included. The methodological quality was assessed using the "PEDro" scale.

RESULTS

In total, 763 studies were obtained; after the review, 28 target articles were selected and finally grouped as follows: 13 studies on diabetes, six on hypertension, seven on obesity and two on physical activity. For all of the risk factors, a small effect of the intervention was seen.

CONCLUSIONS

although the current evidence is heterogeneous regarding the statistically significant effects of telemedicine on various cardiovascular risk factors, its clinical relevance is undeniable; therefore, its use is recommended as long as the necessary infrastructure exists.

T-stage-specific abdominal visceral fat, haematological nutrition indicators and inflammation as prognostic factors in patients with clear renal cell carcinoma

Clear cell renal carcinoma (ccRCC) is the most common histological type of renal cancer and has the highest mortality. Several studies have been conducted on the relationship between adipose tissue and ccRCC prognosis, however, the results have been inconsistent to date. The current study aimed at establishing a link between abdominal fat composition and short-term prognosis in patients with ccRCC after T-stage stratification. We retrospectively analysed 250 patients with pathologically confirmed ccRCC (173 low T-stage and 77 high T-stage) in our hospital. The computed tomography (CT) images were evaluated using ImageJ. Then, subcutaneous and visceral fat areas (SFA and VFA), total fat areas (TFA) and the relative VFA (rVFA) were measured and computed. Meanwhile, biochemical indices of blood serum were analysed. The results showed that rVFA in low T-stage cohort who had a history of short-term postoperative complications were significantly lower than those who did not. No such association was observed in the high T-stage cohort. Further investigation revealed that the correlations between biochemical indexes and fat area-related variables varied across T-stage groups. As a result, rVFA is a reliable independent predictor of short-term prognosis in patients with low T-stage ccRCC but not in patients with high T-stage ccRCC.

Visual body composition assessment methods: A 4-compartment model comparison of smartphone-based artificial intelligence for body composition estimation in healthy adults

BACKGROUND & AIMS

Visual body composition (VBC) estimates produced from smartphone-based artificial intelligence represent a user-friendly and convenient way to automate body composition remotely and without the inherent geographical and monetary restrictions of other body composition methods. However, there are limited studies that have assessed the reliability and agreement of this method and thus, the aim of this study was to evaluate VBC estimates compared to a 4-compartment (4C) criterion model.

METHODS

A variety of body composition assessments were conducted across 184 healthy adult participants (114 F, 70 M) including dual-energy X-ray absorptiometry and bioimpedance spectroscopy for utilization in the 4C model and automated assessments produced from two smartphone applications (Amazon Halo®, HALO; and myBVI®) using either Apple® or Samsung® phones. Body composition components were compared to a 4C model using equivalence testing, root mean square error (RMSE), and Bland-Altman analysis. Separate analyses by sex and racial/ethnic groups were conducted. Precision metrics were conducted for 183 participants using intraclass correlation coefficients (ICC), root mean squared coefficients of variation (RMS-%CV) and precision error (PE).

RESULTS

Only %fat produced from HALO devices demonstrated equivalence with the 4C model although mean differences for HALO were <±1.0 kg for FM and FFM. RMSEs ranged from 3.9% to 6.2% for %fat and 3.1-5.2 kg for FM and FFM. Proportional bias was apparent for %fat across all VBC applications but varied for FM and FFM. Validity metrics by sex and specific racial/ethnic groups varied across applications. All VBC applications were reliable for %fat, fat mass (FM), and fat-free mass (FFM) with ICCs ≥0.99, RMS-%CV between 0.7% and 4.3%, and PEs between 0.3% and 0.6% for %fat and 0.2-0.5 kg for FM and FFM including assessments between smartphone types.

CONCLUSIONS

Smartphone-based VBC estimates produce reliable body composition estimates but their equivalence with a 4C model varies by the body composition component being estimated and the VBC being employed. VBC estimates produced by HALO appear to have the lowest error, but proportional bias and estimates by sex and race vary across applications.

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.

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.

The Effectiveness of Wearable Devices as Physical Activity Interventions for Preventing and Treating Obesity in Children and Adolescents: Systematic Review and Meta-analysis

Background

The prevalence of obesity in children and adolescents remains a global public health issue. Wearable devices may offer new opportunities for prevention and intervention in obesity. Previous systematic reviews have only examined the effect of the wearable device interventions on preventing and treating obesity in adults. However, no systematic review has provided an evaluation of wearable devices as physical activity interventions for preventing and treating obesity in children and adolescents.

Objective

The purpose of this review and meta-analysis was to evaluate the effectiveness of wearable devices as physical activity interventions on obesity-related anthropometric outcomes in children and adolescents.

Methods

Research articles retrieved from PubMed, EMBASE, Cochrane Library, Scopus, and EBSCO from inception to February 1, 2021, were reviewed. The search was designed to identify studies utilizing wearable devices for preventing and treating obesity in children and adolescents. The included studies were evaluated for risk of bias following the Cochrane recommendation. Meta-analyses were conducted to evaluate the effectiveness of wearable devices as physical activity interventions on body weight, body fat, BMI z-score (BMI-Z), BMI, and waist circumference. Subgroup analyses were performed to determine whether the characteristics of the interventions had an impact on the effect size.

Results

A total of 12 randomized controlled trials (3227 participants) were selected for meta-analysis. Compared with the control group, wearable device interventions had statistically significant beneficial effects on BMI (mean difference [MD] –0.23; 95% CI –0.43 to –0.03; P=.03; I²=2%), BMI-Z (MD –0.07; 95% CI –0.13 to –0.01; P=.01; I²=81%), body weight (MD –1.08; 95% CI –2.16 to –0.00; P=.05; I²=58%), and body fat (MD –0.72; 95% CI –1.19 to –0.25; P=.003; I²=5%). However, no statistically significant effect was found on waist circumference (MD 0.55; 95% CI –0.21 to 1.32; P=.16; I²=0%). The subgroup analysis showed that for participants with overweight or obesity (MD –0.75; 95% CI –1.18 to –0.31; P<.01; I²=0%), in the short-term (MD –0.62; 95% CI –1.03 to –0.21; P<.01; I²=0%), wearable-based interventions (MD –0.56; 95% CI –0.95 to –0.18; P<.01; I²=0%) generally resulted in greater intervention effect size on BMI.

Conclusions

Evidence from this meta-analysis shows that wearable devices as physical activity interventions may be useful for preventing and treating obesity in children and adolescents. Future research is needed to identify the most effective physical activity indicators of wearable devices to prevent and treat obesity in children and adolescents.

The Effectiveness of Combining Nonmobile Interventions With the Use of Smartphone Apps With Various Features for Weight Loss: Systematic Review and Meta-analysis

Background

The effectiveness of smartphone apps for weight loss is limited by the diversity of interventions that accompany such apps. This research extends the scope of previous systematic reviews by including 2 subgroup analyses based on nonmobile interventions that accompanied smartphone use and human-based versus passive behavioral interventions.

Objective

The primary objective of this study is to systematically review and perform a meta-analysis of studies that evaluated the effectiveness of smartphone apps on weight loss in the context of other interventions combined with app use. The secondary objective is to measure the impact of different mobile app features on weight loss and mobile app adherence.

Methods

We conducted a systematic review and meta-analysis of relevant studies after an extensive search of the PubMed, MEDLINE, and EBSCO databases from inception to January 31, 2022. Gray literature, such as abstracts and conference proceedings, was included. Working independently, 2 investigators extracted the data from the articles, resolving disagreements by consensus. All randomized controlled trials that used smartphone apps in at least 1 arm for weight loss were included. The weight loss outcome was the change in weight from baseline to the 3- and 6-month periods for each arm. Net change estimates were pooled across the studies using random-effects models to compare the intervention group with the control group. The risk of bias was assessed independently by 2 authors using the Cochrane Collaboration tool for assessing the risk of bias in randomized trials.

Results

Overall, 34 studies were included that evaluated the use of a smartphone app in at least 1 arm. Compared with controls, the use of a smartphone app–based intervention showed a significant weight loss of –1.99 kg (95% CI –2.19 to –1.79 kg; I²=81%) at 3 months and –2.80 kg (95% CI –3.03 to –2.56 kg; I²=91%) at 6 months. In the subgroup analysis, based on the various intervention components that were added to the mobile app, the combination of the mobile app, tracker, and behavioral interventions showed a statistically significant weight loss of –2.09 kg (95% CI –2.32 to –1.86 kg; I²=91%) and –3.77 kg (95% CI –4.05 to –3.49 kg; I²=90%) at 3 and 6 months, respectively. When a behavioral intervention was present, only the combination of the mobile app with intensive behavior coaching or feedback by a human coach showed a statistically significant weight loss of –2.03 kg (95% CI –2.80 to –1.26 kg; I²=83%) and –2.63 kg (95% CI –2.97 to –2.29 kg; I²=91%) at 3 and 6 months, respectively. Neither the type nor the number of mobile app features was associated with weight loss.

Conclusions

Smartphone apps have a role in weight loss management. Nevertheless, the human-based behavioral component remained key to higher weight loss results.

Impacts on Context Aware Systems in Evidence-Based Health Informatics: A Review

BACKGROUND

The application of Context Aware Computing (CAC) can be an effective, useful, feasible, and acceptable way to advance medical research and provide health services.

METHODS

This review was conducted in accordance with the principles of the development of a mixed methods review and existing knowledge in the field via the Synthesis Framework for the Assessment of Health Information Technology to evaluate CAC implemented by Evidence-Based Health Informatics (EBHI). A systematic search of the literature was performed during 18 November 2021-22 January 2022 in Cochrane Library, IEEE Xplore, PUBMED, Scopus and in the clinical registry platform Clinicaltrials.gov. The author included the articles in the review if they were implemented by EBHI and concerned with CAC technologies.

RESULTS

29 articles met the inclusion criteria and refer to 26 trials published between 2011 and 2022. The author noticed improvements in healthcare provision using EBHI in the findings of CAC application. She also confirmed that CAC systems are a valuable and reliable method in health care provision.

CONCLUSIONS

The use of CAC systems in healthcare is a promising new area of research and development. The author presented that the evaluation of CAC systems in EBHI presents positive effects on the state of health and the management of long-term diseases. These implications are presented in this article in a detailed, clear, and reliable manner.

Long-term Effectiveness of a Smartphone App Combined With a Smart Band on Weight Loss, Physical Activity, and Caloric Intake in a Population With Overweight and Obesity (Evident 3 Study): Randomized Controlled Trial

BACKGROUND

Multicomponent mobile health approaches can improve lifestyle intervention results, although little is known about their long-term effectiveness.

OBJECTIVE

This study aims to evaluate the long-term effectiveness (12 months) of a multicomponent mobile health intervention-combining a smartphone app, an activity tracker wristband, and brief counseling, compared with a brief counseling group only-on weight loss and improving body composition, physical activity, and caloric intake in Spanish sedentary adults with overweight or obesity.

METHODS

We conducted a randomized controlled, multicenter clinical trial (Evident 3). A total of 650 participants were recruited from 5 primary care centers, with 318 participants in the intervention group (IG) and 332 in the control group (CG). All participants were briefly counseled about a healthy diet and physical activity at the baseline visit. For the 3-month intervention period, the IG received training to use the app to promote healthy lifestyles and the smart band (Mi Band 2, Xiaomi). All measurements were performed at baseline and at 3 and 12 months. Physical activity was measured using the International Physical Activity Questionnaire-Short Form. Nutritional habits were assessed using the Food Frequency Questionnaire and Adherence to Mediterranean diet questionnaire.

RESULTS

Of the 650 participants included, 563 (86.6%) completed the 3-month visit and 443 (68.2%) completed the 12-month visit. After 12 months, the IG showed net differences in weight (-0.26, 95% CI -1.21 to 0.70 kg; P=.02), BMI (-0.06, 95% CI -0.41 to 0.28 points; P=.01), waist-height ratio (-0.25, 95% CI -0.94 to 0.44; P=.03), body adiposity index (-0.33, 95% CI -0.77 to 0.11; P=.03), waist circumference (-0.48, 95% CI -1.62 to 0.66 cm, P=.04) and hip circumference (-0.69, 95% CI -1.62 to 0.25 cm; P=.03). Both groups lowered daily caloric intake and increased adherence to the Mediterranean diet, with no differences between the groups. The IG increased light physical activity time (32.6, 95% CI -30.3 to 95.04 min/week; P=.02) compared with the CG. Analyses by subgroup showed changes in body composition variables in women, people aged >50 years, and married people.

CONCLUSIONS

The low-intensity intervention of the Evident 3 study showed, in the IG, benefits in weight loss, some body composition variables, and time spent in light physical activity compared with the CG at 3 months, but once the devices were collected, the downward trend was not maintained at the 12-month follow-up. No differences in nutritional outcomes were observed between the groups.

TRIAL REGISTRATION

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

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1097/MD.0000000000009633.

The nudge strategies for weight loss in adults with obesity and overweight: A systematic review and meta-analysis

Obesity and overweight conditions have become major health challenges worldwide. The exploration of effective weight loss strategies is essential. Nudges are currently advancing approaches that represent a new and better method for changing the behaviors of people. However, the effectiveness of nudge interventions on weight loss in overweight people who may be obese has not been synthesized in a systematic manner. In this study, a systematic literature search was performed. Only randomized controlled trials (RCTs) were considered. Weighted mean differences (WMDs) and 95% confidence intervals (CIs) were calculated as summary statistics. In total, 25 RCTs involving a population of 5,929 individuals were included. Significant effects of the nudge strategy on weight loss (WMD: -0.96 kg, 95% CI: -1.49 to -0.43), body mass index (WMD: -0.3 kg/m², 95% CI: -0.41 to -0.19) and waist circumference (WMD: -0.75 cm, 95% CI: -1.23 to -0.27) were observed. The subgroup analysis showed that the reduction in body weight associated with nudge interventions was significant in younger and more obese people. Moreover, the effect of nudge intervention on weight loss weakened over time. Overall, the nudge strategy can promote changes in weight loss, body mass index and waist circumference of adults, albeit at a mild magnitude and in particular types of individuals. Nudge strategies can be recommended to clinical practitioners and policy-makers to promote obesity management.

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.