Mobile Phone Apps to Promote Weight Loss and Increase Physical Activity: A Systematic Review and Meta-Analysis

Effects of Mobile Health Care App "Asmile" on Physical Activity of 80,689 Users in Osaka Prefecture, Japan: Longitudinal Observational Study

BACKGROUND

Lifestyle-related diseases can be controlled by improving individuals' lifestyles; however, improving and maintaining a healthy lifestyle is difficult. Mobile health (mHealth) applications have recently attracted attention as tools for maintaining and improving health, and their use may also increase physical activity.

OBJECTIVE

This study aimed to verify the effect of registration in Asmile, an mHealth application provided by the Osaka Prefectural Government, on step counts using a Causal Impact approach based on the step count data recorded in the Asmile application.

METHODS

This observational study included Osaka residents aged 20-79 years, newly registered to Asmile, between the fiscal years 2020 and 2023. Of these, 80,689 participants with step count records for 4 weeks before and after the day they registered to Asmile were included in the analysis. We used daily step counts that were automatically transferred from a standard smartphone health care app into Asmile. We used a Causal Impact model to estimate the increase in step count after registration to Asmile.

RESULTS

Of the 80,689 participants analyzed, 38.5% (31,082/80,689) were men, and the mean age was 51.6 (SD 13.2) years. The mean step count before registration was 5923 (SD 4860) steps per day, with the highest proportion of new users registered in spring (38,389/80,689, 47.6%) and in fiscal year 2020 (34,491/80,689, 42.7%). The analysis revealed that the effect of Asmile registration on step counts was 360 steps (95% CI 331-389) per day and 10,041 steps (95% CI 9632-10,450) over 4 weeks. Stratified analysis showed that the impact of increased step count was more pronounced in younger groups and groups with fewer step counts before registration. Conversely, the effect of registration on step count was relatively minor in the groups registered in summer or winter.

CONCLUSIONS

This study demonstrates increased physical activity among users registered with the Asmile app. These findings suggest that mHealth apps such as Asmile can effectively promote healthier lifestyles and potentially reduce the risk of lifestyle-related diseases.

The Role of Mobile Apps in Obesity Management: Systematic Review and Meta-Analysis

BACKGROUND

Obesity is a growing public health concern worldwide, significantly contributing to premature mortality and noncommunicable diseases. Weight reduction through lifestyle interventions, including diet and physical activity, is the primary approach to combating obesity, with studies showing that a 5% to 10% reduction in body weight can notably reduce obesity-related complications. Recently, smartphone apps have emerged as popular tools to aid in weight loss. However, the effectiveness of smartphone-only apps for weight management in people with overweight or obesity without comorbidities remains unclear.

OBJECTIVE

This meta-analysis aims to evaluate the efficacy of these apps in supporting weight loss and improving body composition in such populations.

METHODS

A systematic review and meta-analysis were conducted following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, with a search across databases including PubMed, Scopus, Cochrane Library, and others. The inclusion criteria were randomized controlled trials involving adults (aged ≥18 years) with overweight or obesity (BMI≥25 kg/m2) and assessing the use of smartphone-only apps for weight loss. Studies using additional devices or involving participants with comorbidities were excluded. Data extraction focused on weight loss, BMI, waist circumference, and body fat percentage, and the risk of bias was assessed using the Revised Cochrane Risk-of-Bias tool.

RESULTS

A total of 11 randomized controlled trials with 1717 participants were included in the meta-analysis. The interventions, lasting between 60 days and 12 months, involved diet and exercise monitoring via smartphone apps. At 4-6 months of follow-up, app-based interventions significantly reduced body weight (standardized mean difference -0.33, 95% CI -0.48 to -0.17; P<.001; I2=49%) and BMI (mean difference [MD] -0.76, 95% CI -1.42 to -0.10; P=.02). Reductions in body fat percentage were also observed at 3 months (MD -0.79, 95% CI -1.38 to -0.20; P=.009) and between 4 and 6 months (MD -0.46, 95% CI -0.71 to -0.20; P<.001). However, no significant effects on waist circumference were noted (P=.07).

CONCLUSIONS

Smartphone apps demonstrate a modest but statistically significant effect on weight loss and BMI reduction over a 4- to 6-month period in individuals with overweight or obesity. The effectiveness of these interventions appears limited beyond 6 months, with a tendency for weight regain. Many apps lack the personalized support necessary to sustain long-term weight loss, contributing to high dropout rates. Future development of weight loss apps should focus on enhanced customization to improve user adherence and long-term outcomes.

TRIAL REGISTRATION

PROSPERO CRD42024570999; https://tinyurl.com/2xw6j4fy.

Status in using wearable devices as surveillance tools in public health research among people with disabilities: preliminary analysis of 2017 BRFSS

Purpose: The study aims to examine the association between disability status and willingness to share wearable devices and mobile apps data for public health research using the 2017 Behavioral risk Factor Surveillance System (BRFSS) through secondary data analysis.

Materials and Methods: Current wearable device and mobile apps users at the time of the 2017 BRFSS survey administration from eight states were included in the analysis. Descriptive, chi-square analysis, and multivariable logistic regressions were performed to examine the associations. Subsample analyses were also conducted for individuals with disabilities and different types of disability, including visual impairments, hearing impairments, cognitive disability, independent living disability, self-care disability, and mobility disability on their willingness to share wearable device and mobile app data.

Results: Among the 1575 wearable device and mobile app users, 17.8% (95% CI [14.6, 22.0]) were participants with disabilities. Less than half of the participants (43.8%, 95% CI [38.0, 50.0]) were willing to share their data for public health research with no significant differences between those with and without disabilities or among specific disability types.

Conclusion: The findings underscore a general reluctance to share information for public health research. To address this reluctance, it is crucial to enhance public awareness of the potential benefits and educate users on how sharing data could contribute to understanding health behaviors and identifying public health needs.

Precision nutrition for cardiometabolic diseases

Precision nutrition is a vibrant and rapidly evolving field of scientific research and innovation with the potential to deliver health, societal and economic benefits by improving healthcare delivery and policies. Advances in deep phenotyping technologies, digital tools and artificial intelligence have made possible early proof-of-concept research that expands the understanding of within- and between-person variability in responses to diet. These studies illustrate the promise of precision nutrition to complement the traditional 'one size fits all' dietary guidelines, which, while considering broad life-stage and disease-specific nutritional requirements, often lack the granularity to account fully for individual variations in nutritional needs and dietary responses. Despite these developments, however, considerable challenges remain before precision nutrition can be implemented on a broader scale. This Review examines the current state of precision nutrition research, with a focus on its application to reducing the incidence and burden of cardiometabolic diseases. We critically examine the evidence base, explore the potential benefits and discuss the challenges and opportunities ahead.

Smartphones and Web 2.0. interventions for weight management

Introduction

This systematic review and meta-analysis examine the effectiveness of smartphone and Web 2.0 interventions for weight management compared to traditional control interventions. The potential of smartphones and Web 2.0. technologies to transform health care and clinical intervention in the community are tremendous. This potential is incredibly increased by increasing adoption rates for smartphones and internet technologies.

Methodology

Ten randomized control trials published between 2015 and 2024 searched through PubMed and ScienceDirect were included. All studies with open access that assessed a smartphone or app intervention compared to a control group in randomized control trials, with weight-related body measures (i.e., body weight, BMI, waist circumference) and physical activity changes (steps/day) expressed in terms of mean and standard deviation performed in a population of adults were included. Review Manager software, version 5.4 (The Nordic Cochrane Centre, The Cochrane Collaboration) was used for statistical analysis.

Results

The results of our study indicate that digital interventions, particularly those utilizing direct communication methods like text messages and social media, significantly promote weight loss and reduce waist circumference (mean difference of -2.12 and -2.81 for weight change and waist circumstances respectively). While reductions in body mass index (BMI) with mean difference of -0.53 were less pronounced, they still favored intervention groups. Subgroup analyses performed to find out the source of heterogeneity revealed that three-arm randomized control trials, studies with larger sample sizes, and interventions lasting around six months showed more consistent and significant effects whereas for sensitivity analysis no significant change in heterogeneity was observed for all parameters. High heterogeneity among studies suggests the need for standardized study designs and intervention protocols in future research.

Conclusions

Despite limitations such as technological issues and engagement variability, these findings underscore the potential of digital health interventions in addressing the global burden of obesity and related non-communicable diseases.

Risk aversion or adaptation? Public choices in sports participation under climate risks

Introduction

The increasing frequency and severity of climate risks have significantly impacted public health behaviors, particularly sports participation. Understanding how individuals respond to these environmental shocks is crucial for designing effective health and climate adaptation policies. This study examines the short-term and long-term effects of climate risks on sports participation among middle-aged and young adults, exploring the underlying mechanisms driving these behavioral changes.

Methods

Using data from the 2014 to 2022 China Family Panel Studies (CFPS), this study employs fixed-effects models, two-stage least squares (2SLS) estimation, and a four-stage mediation model to address potential endogeneity and uncover causal relationships. Climate risks are assessed using multiple proxy variables, and robustness checks ensure the reliability of the findings.

Results

In the short term, climate risks significantly reduce the frequency of sports participation. This effect remains consistent across different model specifications and estimation methods. Mechanism analysis reveals that climate risks lower life satisfaction and increase digital engagement, both of which influence individuals' physical and mental health. While climate risks initially discourage sports participation, long-term adaptation occurs through digital engagement and indoor exercise, leading to improved health outcomes. Heterogeneity analysis indicates that the negative short-term effects are more pronounced in urban and western regions, with rural and western areas experiencing no significant long-term positive effects.

Discussion

This study highlights both the inhibitive short-term effects and adaptive long-term responses to climate risks in sports participation. The findings provide insights into how individuals adjust their health-related behaviors under environmental stress and offer policy recommendations to promote climate adaptation and public health through targeted interventions.

Promoting active transportation through technology: a scoping review of mobile apps for walking and cycling

BACKGROUND

Incorporating active transportation (AT), such as walking and cycling, into daily routines is a promising solution for meeting the World Health Organization's physical activity recommendations and contributes to reducing the risk of many noncommunicable diseases. Smartphone apps offer versatile platforms for embedding health behavior promotion strategies to encourage AT.

OBJECTIVE

This scoping review aimed to provide an overview of how mobile apps are being used to promote AT through reviews of the academic literature and commercial app stores.

METHODS

We searched six academic databases (Embase, Medline, Web of Science, PsychINFO, Transport Database, and Google Scholar) for academic literature. The literature was included if it presented a developed app to promote AT behaviors. AT promotion strategies and theories were extracted and analyzed for their impact on changing behaviors and behavioral intentions toward AT. Commercial apps were searched in two app stores (the Apple App Store and the Google Play Store) across six countries, one per continent. Apps were included if they promoted and encouraged AT behavior. We evaluated the apps on the basis of user engagement and their quality and potential to change behaviors, as assessed via the Mobile App Rating Scale (MARS) and the App Behavior Change Scale (ABACUS).

RESULTS

The academic literature search identified 38 articles, presenting 29 apps. All the studies that evaluated behavioral intentions reported success in raising awareness and changing behavioral intentions. A promising strategy to motivate behavior involves providing multiple relevant feedback (calories burned, money saved, time saved, and CO2/particulate matter emissions) on behavioral impacts alongside action plans (route recommendations and personalized travel plans). Only two apps from the literature search were publicly available. The commercial app search identified 78 apps. Apps with high-quality engagement, functionality, aesthetics, and information presented greater user engagement than those that did not; therefore, they were more likely to succeed.

CONCLUSION

Mobile apps have great potential to motivate changes and be part of a comprehensive system to promote AT. Given the rapid growth of app-based interventions, leveraging mobile apps to encourage AT warrants further exploration. Upon development, these apps should be maintained and made publicly accessible.

Measuring the influence of depressive symptoms on engagement, adherence, and weight loss in an eHealth intervention

BACKGROUND

Digital behavior change interventions (eHealth, mHealth) are known to be capable of promoting clinically significant weight loss among some participants. However, these programs can struggle with declining engagement and adherence over time, which can hamper their effectiveness. This analysis examines the extent that depression symptoms may negatively influence engagement, adherence, and 6 month weight change in an eHealth intervention.

METHODS

Structural equation modeling is applied to test the effects of baseline depression symptoms on weight change outcomes, mediated through latent constructs of engagement and adherence, respectively. These constructs were highly correlated within this dataset and necessitated two separate models to be tested. Engagement was indicated by 6 month sums of website logins, user-created goals, visiting various webpages, and posts on the online discussion boards. Adherence was indicated by 6 month sums of weeks exercise goals met, days weight logged, and days of complete dietary tracking.

RESULTS

Depression symptoms showed no direct association with weight change (p's ≥ 0.6), but were negatively associated with both constructs of engagement and adherence (p's < 0.001), which in turn were negatively associated with weight change in both models (p's < 0.001). It was determined depression symptoms had a positive indirect association with weight change fully mediated through these variables, meaning less weight loss or possible weight gain (p < 0.001).

DISCUSSION

This analysis shows that depression symptoms had a significant, undesirable effect on weight loss outcomes within this eHealth intervention, fully mediated through measured participant engagement and adherence. Further research is needed to test these constructs within a longitudinal model to better understand their dynamic interrelationships, and consider means to address depression in future digital interventions.

Behavioral and Dietary Strategies for Weight Loss and Weight Loss Maintenance Among Black/African American Adults and the Potential Role of Media: A Narrative Review

BACKGROUND

Research shows that media-based dietary and behavioral strategies can aid weight loss, but limited studies have been conducted among Black/African American adults.

OBJECTIVE

This review examines the literature on dietary and behavioral strategies for weight loss and maintenance among Black/African American adults, identifying the types of media used alongside these strategies.

METHODS

The PubMed, Web of Science, CINAHL, and Communication & Mass Media databases were searched for peer-reviewed articles with no restrictions on the publication date. Two reviewers conducted the screening. Studies were included if they had >75% Black/African American adult participants (18 years and older), included behavioral or dietary strategies, had a media component, weight loss or maintenance as an outcome, and published in English language.

RESULTS

Nine studies (randomized control trials (n = 5), mixed-method studies (n = 2) and qualitative studies (n = 2)) were included. Behavioral strategies used to lose and maintain weight included goal setting (n = 4), self-monitoring (n = 5), and weekly self-weighing (n = 2). Limiting sugary drinks (n = 3), limiting junk and high fat foods (n = 5), aiming for a set number of calories per day (n = 3), portion control (n = 4), and increasing fruits and vegetable intake (n = 3) were the most common dietary strategies used to lose and maintain weight. Media used in the intervention studies included mHealth text messaging (n = 2), Facebook (n = 2), a website (n = 1), television (n = 1) and a mobile app (n = 1).

CONCLUSIONS

The findings highlight the limited research on the utilization of media for behavioral and dietary weight loss strategies among Black/African American adults, indicating a need for future studies to explore and optimize media-based strategies for this population.

A scoping review of the types and features of technology used to deliver exercise prescription and improve exercise adherence

OBJECTIVE

Exercise adherence and motivation can benefit from technology, but the specific factors influencing these improvements remain unclear. This scoping review aimed to outline the types and features of technology used in exercise prescription within healthcare, focusing on enhancing users' adherence to exercise.

METHODS

A comprehensive systematic literature search was conducted from January 2000 to February 2023 across Web of Science, Google Scholar, and MEDLINE via PubMed. The review sought studies on technology-based exercise prescriptions for adults ≥ 18 years, evaluating features that enhance motivation or adherence.

RESULTS

Out of 1724 articles reviewed, 45 met the criteria, demonstrating that mobile applications, exercise gaming, wearable trackers, and websites are commonly used technologies for prescribing exercise in healthcare setting. Common features, special features, and motivating features were found to be important in all technology-based exercise tools to enhance users' adherence and motivation.

CONCLUSION

This review provides a comprehensive overview of the technological types and approaches that can support and improve exercise adherence among health service users. The findings also emphasize on specific features that can address current gaps in technology-driven fitness interventions.

PRACTICE IMPLICATIONS

Healthcare professionals should make informed decisions when recommending these tools to health service users, since technology does play a significant role in promoting long-term adherence to exercise programs.

Fluctuations in mHealth engagement following receipt of goal-discrepant feedback messages

Objective

Digital behavior change interventions can successfully promote change in behavioral outcomes, but often suffer from steep decreases in engagement over time, which hampers their effectiveness. Providing feedback on goal performance is an established technique to promote goal attainment; however, theory indicates that sending goal-discrepant feedback messages could cause some users to respond more negatively than others. This analysis assessed whether goal-discrepant messaging was negatively associated with participant engagement, and if this relationship was exacerbated by baseline depressive symptoms within the context of a three-month weight loss pilot mHealth intervention.

Methods

This analysis applied a generalization of log-linear regression analysis with n = 52 participants (78.8% female, 61.5% white, ages 21-35) to assess the likelihood of reading consecutive program messages following receipt of messages with goal-discrepant content.

Results

Receipt of goal-discrepant messages was associated with a significantly lower likelihood (RR = 0.89) of participants reading the next program message sent, compared to receiving positive/neutral messages or no message, but these relationships were not influenced by depressive symptoms in this sample.

Conclusion

Feedback on goal performance remains an important behavior change technique; however, sending push messages that alert participants to their goal-discrepant status seems to reduce the likelihood that participants will read future program messages. Sending messages containing positive or neutral content does not seem to carry this negative risk among individuals in goal-discrepant states.

A Novel Web App for Dietary Weight Management: Development, Implementation, and Usability Study

BACKGROUND

Online weight loss programs have ambiguous efficacy. There is a growing body of evidence that weight loss programs when combined with apps have better outcomes; however, many apps lack an evidence-based approach to dietary changes for weight loss and do not rely on a theoretical framework for behavior change.

OBJECTIVE

This study aimed to describe the development and the preliminary usability and acceptability testing of a web app that uses behavior change techniques (BCTs) to support users of a comprehensive online weight loss program.

METHODS

The weight loss program intervention components were nutrient and weight tracking charts that needed a remotely accessible and online format. The app was designed by nutrition researchers and developers in a collaborative effort. A review of BCTs in weight loss and web apps was performed as well as an assessment of user needs to inform the initial prototype. A preliminary app prototype, version 1.0, was provided to participants of a weight loss trial (N=30) to assess for feasibility of its use. A full app prototype, version 2.0, was feasibility and acceptability tested by trial participants (n=11) with formal feedback by Likert-scale survey and open-ended questions. In the final round of testing, a user group of scientists and developers (n=11) was selected to provide a structured 3-month review through which the group met weekly for collective feedback sessions.

RESULTS

The process resulted in a fully developed web app, MealPlot, by the Applied Research Institute, for meal planning and weight tracking that can be used by weight loss users and health professionals to track their patients. MealPlot includes a weight chart, a protein-fiber chart, and a chat feature. In addition, MealPlot has 2 distinct platforms, 1 for weight loss users and 1 for health professionals. Selected BCTs for incorporation into the app were goal setting, feedback, problem-solving, self-monitoring, and social support. Version 1.0 was used successfully to provide a functioning, online weight chart over the course of a 1-year trial. Version 2.0 provided a functional weight chart and meal planning page, but 8 out of 11 participants indicated MealPlot was difficult to use. Version 3.0 was developed based on feedback and strategies provided from user group testing.

CONCLUSIONS

The web app, MealPlot, was developed to improve outcomes and functionality of an online weight loss program by providing a remote method of tracking weight, food intake, and connecting users to health professionals for consistent guidance that is not otherwise available in a traditional in-person health care setting. The final version 3.0 of the web app will be refined based on findings of a review study gathering feedback from health professionals and from actual weight loss users who are part of a clinical weight loss trial.

[Strategies for the prevention and non-pharmacological treatment of obesity. Models of care]

The prevalence of obesity has increased in recent years worldwide. In this context, strategies for management obesity in primary care are essential. The first step in the treatment of obesity are lifestyle intervention programs. The three pillars of these programs, ideally of high intensity (high frequency of visits), are dietary intervention, exercise and behavioral therapy. There is no universal model of care for patients with obesity, but it must take into account key aspects, such as facilitating the access and adherence of the patient and a multidisciplinary and coordinated care among professionals at different levels of healthcare. The components of the model of care and its format should be defined according to the resources available and the characteristics of the population to be treated.

Combining anchoring with financial incentives to increase physical activity: a randomized controlled trial among college students

The purpose of this study was to: (1) compare the relative efficacy of different combinations of three behavioral intervention strategies (i.e., personalized reminders, financial incentives, and anchoring) for establishing physical activity habits using an mHealth app and (2) to examine the effects of these different combined interventions on intrinsic motivation for physical activity and daily walking habit strength. A four-arm randomized controlled trial was conducted in a sample of college students (N = 161) who had a self-reported personal wellness goal of increasing their physical activity. Receiving cue-contingent financial incentives (i.e., incentives conditional on performing physical activity within ± one hour of a prespecified physical activity cue) combined with anchoring resulted in the highest daily step counts and greatest odds of temporally consistent walking during both the four-week intervention and the full eight-week study period. Cue-contingent financial incentives were also more successful at increasing physical activity and maintaining these effects post-intervention than traditional non-cue-contingent incentives. There were no differences in intrinsic motivation or habit strength between study groups at any time point. Financial incentives, particularly cue-contingent incentives, can be effectively used to support the anchoring intervention strategy for establishing physical activity habits. Moreover, mHealth apps are a feasible method for delivering the combined intervention technique of financial incentives with anchoring.

Smartphone-Based Digital Peer Support for a Walking Intervention Among Public Officers in Kanagawa Prefecture: Single-Arm Pre- and Postintervention Evaluation

BACKGROUND

Digital peer support, defined as peer support delivered through technology such as smartphone apps, may be promising to promote activity in the form of step counts. Interactions among users have a positive impact on retention rates, and apps with social elements show significant improvements in daily step count. However, the feasibility of digital peer support in promoting physical activity (PA) is unknown; therefore, its effectiveness on step count and the clinical implications remain unconfirmed.

OBJECTIVE

This study aimed to assess the feasibility of digital peer support over a 3-month intervention period using the retention rate as the outcome. Moreover, changes in daily step count and physical measurements were compared between pre- and postintervention.

METHODS

The study design was a 3-month 1-arm intervention with participants from local government offices in Kanagawa, Japan. We used an available smartphone app, Minchalle, as the tool for the group intervention. Participants were required to report their daily step count to a maximum of 5 members composed exclusively of study participants. The primary outcome was the retention rate. Secondary outcomes included daily step count, the rate of achieving daily step goals, physical measurements, and lifestyle characteristics. Descriptive statistics and the Pearson coefficient were used to examine the relationship between goal achievement and step count, as well as changes in step count and various variables including physical measurements.

RESULTS

Of the 63 participants, 62 completed the intervention. The retention rate was 98% (62/63). The average daily step count during the intervention was 6993 (SD 2328) steps, an 1182-step increase compared with the count observed 1 week before the intervention began. The rate of achieving the daily step count during the intervention was 53.5% (SD 26.2%). There was a significant correlation (r=0.27, P=.05) between achieving daily step goals and increasing daily step count. Comparative analyses showed that changes in weight (68.56, SD 16.97 kg vs 67.30, SD 16.86 kg; P<.001), BMI (24.82, SD 4.80 kg/m2 vs 24.35, SD 4.73 kg/m2; P<.001), somatic fat rate (28.50%, SD 7.44% vs 26.58%, SD 7.90%; P=.005), systolic blood pressure (130.42, SD 17.92 mm Hg vs 122.00, SD 15.06 mm Hg; P<.001), and diastolic blood pressure (83.24, SD 13.27 mm Hg vs 77.92, SD 11.71 mm Hg; P=.002) were significantly different before and after the intervention. Similarly, the daily amount of PA significantly improved from 5.77 (SD 3.81) metabolic equivalent (MET)-hours per day to 9.85 (SD 7.84) MET-hours per day (P<.001).

CONCLUSIONS

This study demonstrated that digital peer support is feasible for maintaining a high retention rate and can, therefore, effectively promote PA. It can be a promising tool to improve daily step count, subjective PA, and clinical outcomes, such as weight and somatic fat rate.

TRIAL REGISTRATION

UMIN Clinical Trials Registry UMIN000042520; https://tinyurl.com/46c4nm8z.

A smartphone coaching program ("Bouge Grossesse") improves daily physical activity in pregnant women

BACKGROUND

Physical activity has been shown to reduce obstetrical risks however pregnant women reduce their physical activity and sedentary behaviors increase.

OBJECTIVE

Our aim was to evaluate the impact of a smartphone application developed to increase daily physical activity in pregnant women.

METHODS

We enrolled 250 pregnant women in a prospective randomized controlled study. These women were instructed to download either an intervention application called «Bouge Grossesse» (coaching program and a pedometer; n=125) or a Placebo application (pedometer only; n=125). Primary outcome was defined as a daily increase of 2000 steps/day between day 1 and day 90 or 10 000 steps/week between week 1 and week 12. Data was analyzed with intention to treat. Secondary outcomes were the number of steps at week 12 and the evolution of quality of life measured by WHO score, EIFEL score and SPIEGEL scale, and on maternal and fetal outcomes.

RESULTS

Patients were enrolled between August 2017 and February 2019. They were retrospectively registered after September 2018. We found a significant difference in the primary outcome between the two groups in favor of the intervention group (22.4% success vs 3.2% in the control group, P<.001) but only 43 women in the intervention group (34.4%) and 16 women in the placebo group (12.8%) completed the 12-week coaching program. There were no significant differences in the SPIEGEL, EIFEL and WHO scores. The mean number of daily steps at week 12 was significantly higher in the intervention group (6900.0 vs 4371.9, P<.001).

CONCLUSION

The mobile health intervention « Bouge Grossesse » significantly increased physical activity in pregnant women but we observed a high percentage of withdrawals from the 12-week program.

TRIAL REGISTRATION

This clinical trial was registered under the number NCT03688087 ClinicalTrials.gov.

The AI Future of Emergency Medicine

In the coming years, artificial intelligence (AI) and machine learning will likely give rise to profound changes in the field of emergency medicine, and medicine more broadly. This article discusses these anticipated changes in terms of 3 overlapping yet distinct stages of AI development. It reviews some fundamental concepts in AI and explores their relation to clinical practice, with a focus on emergency medicine. In addition, it describes some of the applications of AI in disease diagnosis, prognosis, and treatment, as well as some of the practical issues that they raise, the barriers to their implementation, and some of the legal and regulatory challenges they create.

Designing sustainable mobile weight management applications: information technology (IT) experts perspectives

Background

Weight management mobile applications have become increasingly popular as a tool for individuals to achieve their weight loss goals. However, key challenges with mobile weight management applications are sustaining user engagement and promoting long-term behavior change. This study examines the key functions and features of weight management mobile applications from the viewpoint of information technology (IT) experts. We have developed a framework that outlines the optimal design strategies for mobile apps to support sustainable weight management.

Methods

We conducted face-to-face interviews with five experts to evaluate and give input on the proposed framework.

Results

Eight specialized functionalities have been categorized and defined based on initial framework system features and recommended features based on experts' feedback: (I) customization; (II) usability; (III) integration; (IV) online support; (V) tracking; (VI) nutrition database; (VII) gamification; and (VIII) notification. In addition, common functionalities were identified as (I) registration/sign in; (II) data privacy; (III) security; and (IV) user feedback. An online discussion indicates the system functionality in four themes: (I) configuration; (II) data analytics; (III) support/performance; and (IV) platform: iOS, Android, Native.

Conclusions

These functionalities and features will be incorporated into a framework to design mobile applications for sustainable weight management. Also, to be part of user interface development for the user experience experiments.

Smartphone Applications to Prevent Type 2 Diabetes: A Systematic Review and Meta-Analysis

INTRODUCTION

Evidence supporting the use of apps for lifestyle behavior change and diabetes prevention in people at high risk of diabetes is lacking. The aim of this systematic review was to determine the acceptability and effectiveness of smartphone applications (apps) for the prevention of type 2 diabetes.

METHODS

PubMed, Embase, CINAHL and PsychInfo were searched from 2008 to 2023. Included studies involved adults at high risk of developing diabetes evaluating an app intervention with the aim of preventing type 2 diabetes. Random-effects meta-analyses were conducted for weight loss, body mass index (BMI), glycated hemoglobin, and waist circumference. Narrative synthesis was conducted for all studies, including qualitative studies exploring user perspectives.

RESULTS

Twenty-four studies (n=2,378) were included in this systematic review, including 9 randomized controlled trials (RCTs) with an average duration of 6 months, 10 quasi-experimental and 7 qualitative studies. Socially disadvantaged groups were poorly represented. Six RCTs were combined in meta-analyses. Apps were effective at promoting weight loss [mean difference (MD) -1.85; 95% CI -2.90 to -0.80] and decreasing BMI [MD -0.90, 95% CI -1.53 to -0.27], with no effect on glycated hemoglobin and waist circumference. No studies reported on diabetes incidence. Qualitative studies highlighted the need for app personalization.

DISCUSSION

Smartphone apps have a promising effect on preventing type 2 diabetes by supporting weight loss. Future robust trials should include diverse populations in co-design and evaluation of apps and explore the role of artificial intelligence in further personalizing interventions for higher engagement and effectiveness.

Effectiveness of a Smartphone App (Heia Meg) in Improving Decisions About Nutrition and Physical Activity: Prospective Longitudinal Study

BACKGROUND

Obesity is a prevalent and serious chronic condition associated with abnormal or excessive fat buildup that poses significant health risks. The rates of overweight and obesity in adults and children continue to rise, with global rates of children with overweight or obesity aged 5-19 years growing from 4% to 18% between 1975 and 2016. Furthermore, in 2017, nearly 4 million people died due to complications arising from being overweight or obese.

OBJECTIVE

This study aims to investigate the potential impact of the mobile app Heia Meg on promoting healthier lifestyle choices regarding nutrition and physical activity.

METHODS

A prospective longitudinal study was conducted in collaboration with the Norwegian Directorate of Health. Participants were recruited through the Heia Meg app and were asked to complete a questionnaire before and after using the app. A total of 199 responses were included in the first (preintervention) questionnaire, while 99 valid responses were obtained in the second (postintervention) questionnaire.

RESULTS

The majority (159/199, 79.9%) of participants were female, and their age ranged from 18 years to 70 years and older. The results show a reduction in BMI after the digital intervention. However, some variables influence the BMI reduction effect: sex, age, education, and smoking. The group that obtained the most benefit from the intervention consisted of those who were male, aged 30-39 years, highly educated, and nonsmokers. Although positive, some of the findings are slightly above the statistical significance threshold and therefore should be interpreted carefully.

CONCLUSIONS

Our study found weak evidence to support the effectiveness of the Heia Meg app in promoting healthier lifestyle choices. However, limitations and confounding factors suggest that further research in different populations with larger sample sizes is needed to confirm or disprove our findings.

Infusing behavior science into large language models for activity coaching

Large language models (LLMs) have shown promise for task-oriented dialogue across a range of domains. The use of LLMs in health and fitness coaching is under-explored. Behavior science frameworks such as COM-B, which conceptualizes behavior change in terms of capability (C), Opportunity (O) and Motivation (M), can be used to architect coaching interventions in a way that promotes sustained change. Here we aim to incorporate behavior science principles into an LLM using two knowledge infusion techniques: coach message priming (where exemplar coach responses are provided as context to the LLM), and dialogue re-ranking (where the COM-B category of the LLM output is matched to the inferred user need). Simulated conversations were conducted between the primed or unprimed LLM and a member of the research team, and then evaluated by 8 human raters. Ratings for the primed conversations were significantly higher in terms of empathy and actionability. The same raters also compared a single response generated by the unprimed, primed and re-ranked models, finding a significant uplift in actionability and empathy from the re-ranking technique. This is a proof of concept of how behavior science frameworks can be infused into automated conversational agents for a more principled coaching experience.

Mobile health behaviour change support system as independent treatment tool for obesity: a randomized controlled trial

BACKGROUND/OBJECTIVES

Digital health interventions are increasingly utilized as an adjunct to face-to-face counselling in the treatment of obesity. However, previous studies have shown inconsistent efficacy when digital interventions are used as stand-alone treatment. The purpose of this study was to investigate whether a mobile health behaviour change support system (mHBCSS) is effective in weight reduction and weight loss maintenance without additional counselling. Furthermore, changes in cardiometabolic risk factors were investigated.

METHODS

In this randomized controlled trial, a mHBCSS intervention was conducted for 200 volunteers with obesity (BMI 30-40 kg/m² and age 18-65 years). The study participants were randomly assigned into two groups: immediate access to mHBCSS intervention or wait-list control with access to mHBCSS after 6 months. Anthropometric and metabolic traits were also measured. The primary outcome was weight loss from the baseline to the 6-month visit.

RESULTS

Among 200 participants (88.5% women), mean BMI (SD) was 34.3 kg/m² (2.8) and age 46.5 years (9.5). The retention rate was 98.5% and 89.0% at the 6- and 12-month visits, respectively. At the 6-month visit, those with immediate access to mHBCSS had significantly greater weight loss (-2.5%, 95% CI -3.4 to -1.6, p < 0.001) compared with the wait-list control group (0.2%, 95% CI -0.4 to 0.9, p = 0.466; between groups p < 0.001). Weight loss was maintained until the 12-month time point in the mHBCSS group (-2.1%, 95% CI -3.3 to -0.9, p = 0.001). The usage of mHBCSS had no significant effect on metabolic traits.

CONCLUSION

The mHBCSS as a stand-alone treatment of obesity results in weight reduction and weight loss maintenance with remarkable adherence rate. Further studies are needed to establish how to best implement the scalable and resource-efficient mHBCSS into the standard care of obesity to achieve optimal weight loss results.

Behavioral Lifestyle Intervention Program Using Mobile Application Improves Diet Quality in Adults With Prediabetes (D'LITE Study): A Randomized Controlled Trial

BACKGROUND

Mobile health applications (mHealth apps) are increasingly being used in weight loss interventions. However, evidence on the effects of such interventions on diet quality and their correlation with weight loss is lacking.

OBJECTIVE

The objective of this study was to examine whether changes in the diet quality of adults with prediabetes followed the use of an mHealth-enabled lifestyle intervention, compared with those who did not, and whether these changes correlated with weight loss.

DESIGN

A secondary analysis of a 6-month randomized controlled trial Diabetes Lifestyle Intervention using Technology Empowerment (D'LITE) was conducted, with participants recruited from October 2017 to September 2019.

PARTICIPANTS/SETTING

Community-dwelling adults (n = 148) in Singapore diagnosed with prediabetes and body mass index (BMI) ≥23 were included in this study.

INTERVENTION

Participants were randomized to receive either a 6-month mHealth-enabled lifestyle intervention program (diet and physical activity) or standard care dietary advice.

MAIN OUTCOME MEASURES

Dietary data were collected in the form of 2-day food records at baseline, 3, and 6 months. Changes in Alternate Healthy Eating Index-2010 (AHEI-2010) scores and food groups (servings/day), calculated from the dietary data, and correlation between changes in AHEI-2010 and weight loss at 3 and 6 months, were examined.

STATISTICAL ANALYSES

Between-group comparisons of continuous variables and within-participants variation were performed using longitudinal mixed-effect models, intention-to-treat principles. The models included treatment groups, time (baseline, 3 months, and 6 months), and covariates (age, sex, and BMI), as well as the group × time interactions, as fixed variables and within-participant variation in outcome values as random variable. The random intercept for participants accounted for the dependence of repeated measures. A likelihood ratio test was also conducted to test random effect variance. Spearman correlation test was used to examine correlation between changes in AHEI-2010 scores and weight loss.

RESULTS

There was a significant improvement in overall diet quality as ascertained by the AHEI-2010, by 6.2 points (95% confidence interval [CI], 3.8-8.7; P < 0.001) in the intervention group as compared with the control. The participants in the intervention group had a significantly greater reduction in intake of sugar-sweetened beverages (SSB) by 0.5 servings/day (95% CI, -0.8, -0.2; P < 0.001) and sodium by 726 mg/day (95% CI, -983, -468; P < .001), compared with those receiving standard care. At 3 and 6 months, a significant decrease in SSB (0.8 servings/day; 0.7 servings/day, respectively) and sodium (297 mg/day; 296 mg/day, respectively) intakes were reported compared with baseline intakes. Small positive correlations (r = 0.2; P < 0.05) were observed between changes in AHEI-2010 scores from baseline and percentage weight loss at 3 and 6 months.

CONCLUSION

For adults with prediabetes in Singapore, diet quality can be improved with an mHealth-enabled lifestyle intervention program. A small positive correlation exists between AHEI-2010 scores and weight loss.

Motivated information avoidance in an mHealth weight loss intervention: Associations between unmet behavioral goals and likelihood of viewing program messages

Background

Program engagement is positively associated with improved outcomes in mobile health (mHealth) interventions, but little is known about which factors may increase or decrease the likelihood of participants viewing program messages. This study examined the association between daily behavioral goal achievement and likelihood of reading daily messages, and if this relationship is moderated by baseline depressive symptoms in an mHealth weight loss intervention.

Methods

Data come from a 12-week microrandomized pilot mHealth weight management trial that tested the effects of daily messages on behavioral goals among 52 young adults (78.8% female, 61.5% white, ages 21-35). Conditional growth curve modeling was used to regress message viewing indicators onto the number of daily behavioral goals that participants had not met at the time of message receipt, with testing for moderation by depressive symptoms and controlling for covariates clustered within participants over time.

Results

For each additional goal not met at the time of message receipt, participants were 34.8% less likely to read any message sent (p < 0.0001), and this relationship did not appear to be related to depressive symptoms (p = 0.1).

Conclusions

Participants may tend to avoid reading program messages when they know they are not meeting goals in a program, possibly due to motivated information avoidance to prevent negative emotional reactions from anticipated negative feedback messages. Future interventions may want to consider ways to contact participants who may be struggling in programs and also avoiding viewing standard message pushes in order to reduce the risk of disengagement.

Unveiling Consumer Preferences and Intentions for Cocreated Features of a Combined Diet and Physical Activity App: Cross-Sectional Study in 4 European Countries

BACKGROUND

Numerous mobile health apps are marketed globally, and these have specific features including physical activity tracking, motivational feedback, and recipe provision. It is important to understand which features individuals prefer and whether these preferences differ between consumer groups.

OBJECTIVE

In this study, we aimed to identify consumers' most preferred features and rewards for a mobile app that targets healthy eating and physical activity and to reduce the number of individual mobile health app features to a smaller number of key categories as perceived by consumers. In addition, we investigated the impact of differences in consumers' BMI and self-efficacy on their intention to use and willingness to pay for such an app. Finally, we identified the characteristics of different target groups of consumers and their responses toward app features via cluster analysis.

METHODS

A total of 212 participants from France, Italy, the United Kingdom, and Germany were recruited via the web to answer questions about app features, motivation, self-efficacy, demographics, and geographic factors. It is important to note that our study included an evenly distributed sample of people in the age range of 23 to 50 years (23-35 and 35-50 years). The app features in question were generated from a 14-day cocreation session by a group of consumers from the United Kingdom and the Republic of Ireland.

RESULTS

"Home work out suggestions," "exercise tips," and "progress charts" were the most preferred app features, whereas "gift vouchers" and "shopping discounts" were the most preferred rewards. "Connections with other communication apps" was the least preferred feature, and "charitable giving" was the least preferred reward. Importantly, consumers' positive attitude toward the "social support and connectedness and mindfulness" app feature predicted willingness to pay for such an app (β=.229; P=.004). Differences in consumers' health status, motivational factors, and basic demographics moderated these results and consumers' intention to use and willingness to pay for such an app. Notably, younger and more motivated consumers with more experience and knowledge about health apps indicated more positive attitudes and intentions to use and willingness to pay for this type of app.

CONCLUSIONS

This study indicated that consumers tend to prefer app features that are activity based and demonstrate progress. It also suggested a potential role for monetary rewards in promoting healthy lifestyle behaviors. Moreover, the results highlighted the role of consumers' health status, motivational factors, and socioeconomic status in predicting their app use. These results provide up-to-date, practical, and pragmatic information for the future design and operation of mobile health apps.

Mobile technologies for rehabilitation in non-specific spinal disorders: a systematic review of the efficacy and potential for implementation in low- and middle-income countries

PURPOSE

The aim of this systematic review was primarily to identify the types of mHealth technologies for the rehabilitation of non-specific spinal disorders, second to evaluate their efficacy, and finally to determine their applicability in LMICs.

METHODS

Three databases (Scopus, PubMed, and Web of Science) were searched for randomized controlled trials and clinical trials from January 2012 until December 2022. Studies were found eligible when using mHealth technologies for the rehabilitation of non-specific spinal disorders. To evaluate efficacy, the primary outcome was pain intensity, and the secondary outcomes were disability and quality of life. To evaluate the applicability in LMICs, information about financial and geographical accessibility, offline usability, and languages was extracted.

RESULTS

Fifteen studies were included comprising 1828 participants who suffer from non-specific low back pain (86.05%) and non-specific neck pain (13.95%). Fourteen distinct smartphone-based interventions and two sensor system interventions were found, with a duration ranging from four weeks to six months. All mHealth interventions demonstrated efficacy for the improvement of pain, disability and quality of life in non-specific spinal disorders, particularly low back pain. Five of the evaluated smartphone applications were free of charge accessible and had language features that could be adapted for use in LMICs.

CONCLUSION

mHealth interventions can be used and integrated into the conventional treatment of non-specific spinal disorders in rehabilitation. They have demonstrated efficacy and could be implemented in LMICs with minor adaptations to overcome language barriers and the absolute necessity of the internet.

Associations between behaviour change technique clusters and weight loss outcomes of automated digital interventions: a systematic review and meta-regression

Automated digital interventions for weight loss represent a highly scalable and potentially cost-effective approach to treat obesity. However, current understanding of the active components of automated digital interventions is limited, hindering efforts to improve efficacy. Thus, the current systematic review and meta-analysis (preregistration: PROSPERO 2021-CRD42021238878) examined relationships between utilisation of behaviour change techniques (BCTs) and the efficacy of automated digital interventions for producing weight loss. Electronic database searches (December 2020 to March 2021) were used to identify trials of automated digital interventions reporting weight loss as an outcome. BCT clusters were coded using Michie's 93-item BCT taxonomy. Mixed-effects meta-regression was used to examine moderating effects of BCT clusters and techniques on both within-group and between-group measures of weight change. One hundred and eight conditions across sixty-six trials met inclusion criteria (13,672 participants). Random-effects meta-analysis revealed a small mean post-intervention weight loss of -1.37 kg (95% CI, -1.75 to -1.00) relative to control groups. Interventions utilised a median of five BCT clusters, with goal-setting, feedback and providing instruction on behaviour being most common. Use of Reward and Threat techniques, and specifically social incentive/reward BCTs, was associated with a higher between-group difference in efficacy, although results were not robust to sensitivity analyses.

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

Background

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

Methods

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

Findings

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

Interpretation

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

Funding

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

Communication strategies and effectiveness of early childhood obesity-related prevention programs for linguistically diverse communities: A rapid review

Children from culturally and linguistically diverse backgrounds experience higher rates of obesity and have poorer outcomes in obesity prevention studies. Interventions tailored to specific cultural groups may be limited within linguistically diverse, multicultural communities, and thus, alternative approaches to childhood obesity prevention in these communities are needed. This study aims to describe communication strategies used in interventions targeting prevention of obesity/obesity-related behaviors, among children 0-5 years, from linguistically diverse communities, and assess their effectiveness. A rapid review was conducted by systematically searching Medline, Embase, and CINAHL. The inclusion criteria are as follows: Studies reported an intervention tailored to linguistically diverse communities targeting at least one obesity-related behavior among children 0-5 years. The exclusion criteria are as follows: Interventions used simple language translations, targeted one language group, or treated obesity. A total of 4677 articles were identified with 14 studies meeting inclusion criteria. Key communication strategies included materials in multiple languages, English text written at a set readability level, and multimodal delivery. Six studies reported effectiveness data, of which five had effective primary or secondary outcomes. This is the first rapid review to identify communication strategies used in childhood obesity prevention interventions for linguistically diverse communities, highlighting a need for future research to incorporate and evaluate the communication strategies identified.

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.

Implementing smoking cessation in routine primary care-a qualitative study

Background

The use of digital tools has been proposed as a solution to some of the challenges of providing preventative services in primary care. Although there is a general acceptance among patients to use digital self-help tools to quit smoking, and healthcare organizations are increasingly urged to incorporate these tools in clinical practice, it is unclear how and for whom these innovations can be incorporated into clinical practice.

Objectives

To explore health care professionals' perceptions about smoking cessation practice in routine primary care and the use of digital tools in this work.

Methods

A qualitative study with nine in-depth telephone interviews with health care professionals working in primary care in Sweden. Convenience sampling and snowball technique was used as recruitment strategy. Informants included registered, district and auxiliary nurses as well as behavioral therapists. All informants were female, between 43 and 57 years old and experience of working with smoking cessation in primary care and possibility to recommend digital interventions to smokers.

Results

Informants described smoking cessation practice in primary care as (i) identifying smoking patients, (ii) pursuing standardized routines for smoking cessation practice and (iii) keeping smoking cessation practice on the agenda. Digital tools were described by informants to be used in different ways: (i) replicating practice, (ii) complementing practice and (iii) enabling access to health care practitioners. Finally, the analysis showed that patients' expectations and behaviors contributed to how and when smoking cessation practice was conducted, including the use of digital tools.

Conclusions

Implementing smoking cessation practice in primary care in Sweden encompass continuous work of reaching smoking patients, building buy-in among peers and keeping tobacco on the practice agenda. Digital interventions are used to replicate, complement and enabling access to care. The findings suggest that poor continuity of staff and negative attitudes towards preventative work may challenge smoking cessation practice. However, societal changes in the awareness of the health risks of tobacco use including shifting social norms regarding the acceptance of smoking may contribute to a normalization of speaking about smoking in primary care practice. Increased knowledge is needed on how, and for whom digital tools can be incorporated in clinical practice.

Effects of Digital Physical Activity Interventions for Breast Cancer Patients and Survivors: A Systematic Review and Meta-Analysis

OBJECTIVES

The benefits of physical activity (PA) for breast cancer (BC) patients and survivors are well documented. With the widespread use of the internet and mobile phones, along with the recent coronavirus disease 2019 pandemic, there has been a growing interest in digital health interventions. This study conducted a systematic review and meta-analysis to evaluate the effects of digital PA interventions for BC patients and survivors in improving PA and quality of life (QoL).

METHODS

We searched eight databases, including PubMed, CINAHL, Embase, Scopus, Web of Science, Cochrane Central Register of Controlled Trials in the Cochrane Library, RISS, and DBpia. Studies were included if they provided digital PA interventions, assessed PA and QoL among BC patients and survivors, and were published from inception to December 31, 2022.

RESULTS

In total, 18 studies were identified. The meta-analysis showed significant improvement in the total PA duration (five studies; standardized mean difference [SMD] = 0.71; 95% confidence interval [CI], 0.25-1.18; I2 = 86.64%), functional capacity (three studies; SMD = 0.38; 95% CI, 0.10-0.66; I2 = 14.36%), and QoL (nine studies; SMD = 0.45; 95% CI, 0.22-0.69; I2 = 65.55%).

CONCLUSIONS

Digital PA interventions for BC patients and survivors may significantly improve PA, functional capacity, and QoL. Future research should focus on the long-term effects of digital PA interventions, using objective outcome measures.

Effect of a Smartphone Application on Physical Activity and Weight Loss After Bariatric Surgery-Results from a Randomized Controlled Trial

PURPOSE

Ways to motivate and support patients in being physically active after bariatric surgery are needed. This trial was aimed at evaluating the effect of using a smartphone application targeting physical activity during 12 weeks on moderate-to-vigorous physical activity (MVPA, primary outcome) and secondary outcomes of inactivity, light physical activity (LPA), body mass index (BMI), and percent total weight loss (%TWL) after bariatric surgery.

MATERIALS AND METHODS

Data from a randomized controlled trial comprising 146 patients (79.5% women) undergoing bariatric surgery was analyzed. Mean age and BMI pre-surgery were 40.9 years and 40.5 kg/m2, respectively. Participants were randomized 1:1 to an intervention or a control group. Physical activity and body weight were objectively measured at baseline pre-surgery and post-surgery follow-ups after 6 weeks (weight only), 18 weeks, 6 months, and 1 year. Linear mixed models were fitted to assess longitudinal differences in outcomes between the groups.

RESULTS

A significant effect of the intervention (group-by-time interaction 16.2, 95% CI 3.5 to 28.9) was seen for MVPA at 18 weeks; the intervention group had increased their MVPA since baseline, while the control group had decreased their MVPA. The control group had lowered their BMI approximately 1 kg/m2 more than the intervention group at follow-up after 18 weeks and 12 months, yet, mean BMI did not differ between the groups. No intervention effect was seen on inactivity, LPA, or %TWL.

CONCLUSION

Our results indicate that use of a smartphone application targeting physical activity may have the potential to promote short-term MVPA post bariatric surgery.

TRIAL REGISTRATION

Clinicaltrials.gov : NCT03480464.

The effect of a lifestyle intervention program using a mobile application versus the effect of a program using a booklet for adults with metabolic syndrome: A three-arm randomized controlled trial

PURPOSE

The research aimed to examine the effect of a lifestyle intervention program using mobile application versus booklet for adults with metabolic syndrome in Hong Kong. The outcomes comprised body weight (primary outcome), exercise amount, improvement of cardiometabolic risk factors, cardiovascular endurance, perceived stress scale, and exercise self-efficacy.

DESIGN

A three-arm randomized controlled trial namely App group, Booklet group, and control group was adopted.

METHODS

Two hundred sixty-four adults with metabolic syndrome were recruited from community centers from 2019 to December 2021. Inclusion criteria are those adults with metabolic syndrome, able to use a smart phone. All participants received a 30-min health talk. App group additionally received a mobile application, while Booklet group received a booklet, and the control group received a placebo booklet. Data were collected at baseline, Weeks 4, 12, and 24. SPSS and generalized estimating equations (GEE) model were employed for data analysis.

FINDINGS

Attrition rates were minimal, ranged from 2.65% to 6.44%. Both app and booklet group showed significant improvement in outcomes (exercise amount, waist circumference) when compared to control group. However, statistically significant and superior results were observed in app group, including body weight, exercise amount, waist circumference, body mass index, and systolic blood pressure when compared to booklet group.

CONCLUSION

The lifestyle intervention supported with app was found to be superior to the booklet support for reducing body weight and maintaining exercise.

CLINICAL RELEVANCE

The lifestyle intervention program using mobile application support could be used widely for adults with metabolic syndrome in the community. Suggest nurses may incorporate this program in their health promotion strategies focusing on a healthy lifestyle to reduce the risk of progression to metabolic syndrome.

Family Medicine and Primary Healthcare: The Past, Present and Future

As defined by the World Health Organisation in the conference held in Alma Ata, Kazakhstan, in 1978, "Primary health care is essential health care based on practical, scientifically sound, and socially acceptable methods and technology made universally accessible to individuals and families in the community through their full participation and at a cost that the community and country can afford to maintain at every stage of their development in the spirit of self-reliance and self-determination" [...].

The Application of Digital Technologies and Artificial Intelligence in Healthcare: An Overview on Nutrition Assessment

In the last decade, artificial intelligence (AI) and AI-mediated technologies have undergone rapid evolution in healthcare and medicine, from apps to computer software able to analyze medical images, robotic surgery and advanced data storage system. The main aim of the present commentary is to briefly describe the evolution of AI and its applications in healthcare, particularly in nutrition and clinical biochemistry. Indeed, AI is revealing itself to be an important tool in clinical nutrition by using telematic means to self-monitor various health metrics, including blood glucose levels, body weight, heart rate, fat percentage, blood pressure, activity tracking and calorie intake trackers. In particular, the application of the most common digital technologies used in the field of nutrition as well as the employment of AI in the management of diabetes and obesity, two of the most common nutrition-related pathologies worldwide, will be presented.

Artificial Intelligence and Public Health: Evaluating ChatGPT Responses to Vaccination Myths and Misconceptions

Artificial intelligence (AI) tools, such as ChatGPT, are the subject of intense debate regarding their possible applications in contexts such as health care. This study evaluates the Correctness, Clarity, and Exhaustiveness of the answers provided by ChatGPT on the topic of vaccination. The World Health Organization's 11 "myths and misconceptions" about vaccinations were administered to both the free (GPT-3.5) and paid version (GPT-4.0) of ChatGPT. The AI tool's responses were evaluated qualitatively and quantitatively, in reference to those myth and misconceptions provided by WHO, independently by two expert Raters. The agreement between the Raters was significant for both versions (p of K < 0.05). Overall, ChatGPT responses were easy to understand and 85.4% accurate although one of the questions was misinterpreted. Qualitatively, the GPT-4.0 responses were superior to the GPT-3.5 responses in terms of Correctness, Clarity, and Exhaustiveness (Δ = 5.6%, 17.9%, 9.3%, respectively). The study shows that, if appropriately questioned, AI tools can represent a useful aid in the health care field. However, when consulted by non-expert users, without the support of expert medical advice, these tools are not free from the risk of eliciting misleading responses. Moreover, given the existing social divide in information access, the improved accuracy of answers from the paid version raises further ethical issues.

Conversational Agents for Body Weight Management: Systematic Review

BACKGROUND

Obesity is a public health issue worldwide. Conversational agents (CAs), also frequently called chatbots, are computer programs that simulate dialogue between people. Owing to better accessibility, cost-effectiveness, personalization, and compassionate patient-centered treatments, CAs are expected to have the potential to provide sustainable lifestyle counseling for weight management.

OBJECTIVE

This systematic review aimed to critically summarize and evaluate clinical studies on the effectiveness and feasibility of CAs with unconstrained natural language input for weight management.

METHODS

PubMed, Embase, the Cochrane Library (CENTRAL), PsycINFO, and ACM Digital Library were searched up to December 2022. Studies were included if CAs were used for weight management and had a capability for unconstrained natural language input. No restrictions were imposed on study design, language, or publication type. The quality of the included studies was assessed using the Cochrane risk-of-bias assessment tool or the Critical Appraisal Skills Programme checklist. The extracted data from the included studies were tabulated and narratively summarized as substantial heterogeneity was expected.

RESULTS

In total, 8 studies met the eligibility criteria: 3 (38%) randomized controlled trials and 5 (62%) uncontrolled before-and-after studies. The CAs in the included studies were aimed at behavior changes through education, advice on food choices, or counseling via psychological approaches. Of the included studies, only 38% (3/8) reported a substantial weight loss outcome (1.3-2.4 kg decrease at 12-15 weeks of CA use). The overall quality of the included studies was judged as low.

CONCLUSIONS

The findings of this systematic review suggest that CAs with unconstrained natural language input can be used as a feasible interpersonal weight management intervention by promoting engagement in psychiatric intervention-based conversations simulating treatments by health care professionals, but currently there is a paucity of evidence. Well-designed rigorous randomized controlled trials with larger sample sizes, longer treatment duration, and follow-up focusing on CAs' acceptability, efficacy, and safety are warranted.

Physical Activity and Sedentary Behavior in High School Students: A Quasi Experimental Study via Smartphone during the COVID-19 Pandemic

The objective of this study was to evaluate whether exposure to information about physical activity and its barriers can increase the level of physical activity and reduce the time exposed to sedentary behaviors in high school students involved in integrated professional and technological education during the coronavirus disease 2019 pandemic. This quasi experimental study was conducted with integrated education high school students, divided into two groups: Intervention Group (IG; n = 59) and Control Group (CG; n = 54). Physical activity and sedentary behavior were identified and measured using the International Physical Activity Questionnaire pre-and post-intervention for both groups. IG students received educational material thrice a week for four weeks. The focus of the material was the importance of physical activity and need to reduce the time exposed to sedentary behavior. The results revealed that IG students showed an average daily reduction of 47.14 min in time exposed to sedentary behaviors, while the CG students showed an increase of 31.37 min. Despite this, the intervention was not effective in improving physical activity levels in the IG and the mean reduction in the time exposed to sedentary behavior was not significant (p = 0.556). The intervention was ineffective in increasing the practice of physical activity and reducing the time exposed to sedentary behavior.

The development of a family-based wearable intervention using behaviour change and co-design approaches: move and connect

BACKGROUND

Previous research has explored the effectiveness of wearable activity trackers (wearables) for increasing child physical activity (PA) levels, but there have been mixed results. The use of theoretical frameworks and co-design techniques are recognised ways of increasing an intervention's acceptability and effectiveness.

AIMS

This study aims to use co-design workshops and an evidence-based theoretical framework (the Behaviour Change Wheel) to develop a family-based PA intervention using wearables.

METHODS

Three stages of intervention development outlined by the Behaviour Change Wheel were used. Co-design workshops with seven families (11 parents and 12 children) and seven PA experts were conducted where stakeholders discussed how to overcome previously identified barriers to families being active and using wearables. This resulted in the intervention's components being developed, with each component's mechanisms of action (e.g. intervention functions and behaviour change techniques) being retrospectively identified.

RESULTS

The 'Move & Connect' intervention was developed, which targets family PA and wearable use. The intervention takes a flexible approach and includes eight components, including wearable devices (Fitbit Alta HR), support resources, an introductory workshop, collective challenges, goal setting and reviewing, engagement prompts, social support and health-related resources (e.g. educational videos). The intervention incorporates six intervention functions targeting PA and wearable use: education, training, modelling, persuasion, incentivisation and environmental restructuring and 24 behaviour change techniques, including goal setting, social comparison, feedback on behaviour and graded task.

CONCLUSIONS

This is the first known study to use an evidence-based framework and co-design to develop a family-based wearable intervention. The identification of the intervention's mechanisms of action will prove useful when implementing and evaluating the 'Move & Connect' intervention and allow researchers to replicate its components.

Using Ballistocardiogram and Impedance Plethysmogram for Minimal Contact Measurement of Blood Pressure Based on a Body Weight-Fat Scale

Electronic health (eHealth) is a strategy to improve the physical and mental condition of a human, collecting daily physiological data and information from digital apparatuses. Body weight and blood pressure (BP) are the most popular and important physiological data. The goal of this study is to develop a minimal contact BP measurement method based on a commercial body weight-fat scale, capturing biometrics when users stand on it. The pulse transit time (PTT) is extracted from the ballistocardiogram (BCG) and impedance plethysmogram (IPG), measured by four strain gauges and four footpads of a commercial body weight-fat scale. Cuffless BP measurement using the electrocardiogram (ECG) and photoplethysmogram (PPG) serves as the reference method. The BP measured by a commercial BP monitor is considered the ground truth. Twenty subjects participated in this study. By the proposed model, the root-mean-square errors and correlation coefficients (r2s) of estimated systolic blood pressure and diastolic blood pressure are 7.3 ± 2.1 mmHg and 4.5 ± 1.8 mmHg, and 0.570 ± 0.205 and 0.284 ± 0.166, respectively. This accuracy level achieves the C grade of the corresponding IEEE standard. Thus, the proposed method has the potential benefit for eHealth monitoring in daily application.

Can a Single Variable Predict Early Dropout From Digital Health Interventions? Comparison of Predictive Models From Two Large Randomized Trials

BACKGROUND

A single generalizable metric that accurately predicts early dropout from digital health interventions has the potential to readily inform intervention targets and treatment augmentations that could boost retention and intervention outcomes. We recently identified a type of early dropout from digital health interventions for smoking cessation, specifically, users who logged in during the first week of the intervention and had little to no activity thereafter. These users also had a substantially lower smoking cessation rate with our iCanQuit smoking cessation app compared with users who used the app for longer periods.

OBJECTIVE

This study aimed to explore whether log-in count data, using standard statistical methods, can precisely predict whether an individual will become an iCanQuit early dropout while validating the approach using other statistical methods and randomized trial data from 3 other digital interventions for smoking cessation (combined randomized N=4529).

METHODS

Standard logistic regression models were used to predict early dropouts for individuals receiving the iCanQuit smoking cessation intervention app, the National Cancer Institute QuitGuide smoking cessation intervention app, the WebQuit.org smoking cessation intervention website, and the Smokefree.gov smoking cessation intervention website. The main predictors were the number of times a participant logged in per day during the first 7 days following randomization. The area under the curve (AUC) assessed the performance of the logistic regression models, which were compared with decision trees, support vector machine, and neural network models. We also examined whether 13 baseline variables that included a variety of demographics (eg, race and ethnicity, gender, and age) and smoking characteristics (eg, use of e-cigarettes and confidence in being smoke free) might improve this prediction.

RESULTS

The AUC for each logistic regression model using only the first 7 days of log-in count variables was 0.94 (95% CI 0.90-0.97) for iCanQuit, 0.88 (95% CI 0.83-0.93) for QuitGuide, 0.85 (95% CI 0.80-0.88) for WebQuit.org, and 0.60 (95% CI 0.54-0.66) for Smokefree.gov. Replacing logistic regression models with more complex decision trees, support vector machines, or neural network models did not significantly increase the AUC, nor did including additional baseline variables as predictors. The sensitivity and specificity were generally good, and they were excellent for iCanQuit (ie, 0.91 and 0.85, respectively, at the 0.5 classification threshold).

CONCLUSIONS

Logistic regression models using only the first 7 days of log-in count data were generally good at predicting early dropouts. These models performed well when using simple, automated, and readily available log-in count data, whereas including self-reported baseline variables did not improve the prediction. The results will inform the early identification of people at risk of early dropout from digital health interventions with the goal of intervening further by providing them with augmented treatments to increase their retention and, ultimately, their intervention outcomes.

Feasibility, Usability and Acceptability of a mHealth Intervention to Reduce Cardiovascular Risk in Rural Hispanic Adults: Descriptive Study

BACKGROUND

Mobile health (mHealth) technology using apps or devices to self-manage health behaviors is an effective strategy to improve lifestyle-related health problems such as hypertension, obesity, and diabetes. However, few studies have tested an mHealth intervention with Hispanic/Latino adults, and no studies were found testing mHealth with rural Hispanic/Latino adults, the fastest-growing population in rural areas.

OBJECTIVE

The purpose of this study was to evaluate the feasibility, usability, and acceptability of an mHealth cardiovascular risk self-management intervention with rural Hispanic/Latino adults.

METHODS

A descriptive study using quantitative and qualitative methods was used to evaluate the feasibility, usability, and acceptability of delivering a 12-week mHealth self-management intervention to reduce cardiovascular risk with rural Hispanic/Latino adults who were randomized to 1 of 2 groups. Both groups were asked to use MyFitnessPal to self-monitor daily steps, weight, and calories. The intervention group received support to download, initiate, and troubleshoot technology challenges with MyFitnessPal (Under Armour) and a smart scale, while the enhanced usual care group received only a general recommendation to use MyFitnessPal to support healthy behaviors. The usability of MyFitnessPal and the smart scale was measured using an adapted Health Information Technology Usability EvaluationScale (Health-ITUES). Adherence data in the intervention group (daily steps, weight, and calories) were downloaded from MyFitnessPal. Acceptability was evaluated using semistructured interviews in a subsample (n=5) of intervention group participants.

RESULTS

A sample of 70 eligible participants (enhanced usual care group n=34; intervention group n=36) were enrolled between May and December 2019. The overall attrition was 28% at 12 weeks and 54% at 24 weeks. mHealth usability in the intervention group increased at each time point (6, 12, and 24 weeks). Adherence to self-monitoring using mHealth in the intervention group after week 1 was 55% for steps, 39% for calories, and 35% for weights; at the end of the 12-week intervention, the adherence to self-monitoring was 31% for steps, 11% for weight, and 8% for calories. Spikes in adherence coincided with scheduled in-person study visits. Structured interviews identified common technology challenges including scale and steps not syncing with the app and the need for additional technology support for those with limited mHealth experience.

CONCLUSIONS

Recruitment of rural Hispanic/Latino adults into the mHealth study was feasible using provider and participant referrals. The use of MyFitnessPal, the smart scale, and SMS text messages to self-monitor daily steps, weights, and calories was acceptable and feasible if technology support was provided. Future research should evaluate and support participants' baseline technology skill level, provide training if needed, and use a phone call or SMS text message follow-ups as a strategy to minimize attrition. A wearable device, separate from the smartphone app, is recommended for activity tracking.

Self-Monitoring Physical Activity, Diet, and Weight Among Adults Who Are Legally Blind: Exploratory Investigation

BACKGROUND

Obesity is a global pandemic. Lifestyle approaches have been shown effective for weight loss and weight loss maintenance. Central to these evidence-based approaches are increased physical activity, decreased caloric intake, regular self-weighing, and the tracking of these behaviors.

OBJECTIVE

This exploratory descriptive study surveyed adults who are legally blind to identify strategies related to tracking physical activity, diet, and weight. These health behaviors are essential components to evidence-based weight loss programs. We also identified areas where we can better support adults who are legally blind in their independent efforts to change these behaviors and improve their health.

METHODS

Participants (≥18 years of age) who self-identified as being legally blind were recruited using email announcements in low vision advocacy groups. They completed an interviewer-administered survey on the telephone and an in-person visit for standardized assessment of height and weight.

RESULTS

The participants (N=18) had an average age of 31.2 (SD 13.4) years; 50% (9/18) had normal weight (BMI 18.5 to <25); 44% (8/18) were female; 44% (8/18) were Black; and 39% (7/18) were Non-Hispanic White. Most participants (16/18, 89%) used their smartphone to access the internet daily, and 67% (12/18) had at least 150 mins of exercise per week. Although 78% (14/18) of the participants indicated tracking their weight, only 61% (11/18) could indicate how they tracked their weight, and 22% (4/18) indicated they tracked it mentally. Providing individuals with a talking scale was the most consistent recommendation (12/18, 67%) to facilitate independence in managing weight through lifestyle changes. Even though 50% (9/18) of the participants indicated using an app or electronic notes to track some portion of their diet, participants reported challenges with determining portion size and corresponding calorie counts. Most participants (17/18, 94%) reported using apps, electronic notes, smartphones, or wearable devices to track their physical activity. Although strategies such as using wearables and smartphones could provide measurements (eg, step counts) as well as recording data, they also pose financial and technology literacy barriers.

CONCLUSIONS

Technology-based solutions were identified for tracking weight, diet, and physical activity for weight management. These strategies have financial and technology literacy barriers. A range of strategies for adopting and tracking health behaviors will be needed to assist individuals with varying skills and life experiences.

Adherence to a caloric budget and body weight change vary by season, gender, and BMI: An observational study of daily users of a mobile health app

Objective

Self-monitoring, one of the most important behaviors for successful weight loss, can be facilitated through mobile health applications (mHealth apps). Therefore, it is of interest to determine whether consistent users of these apps succeed in achieving their weight goals. This study used data from an mHealth app that enabled tracking of caloric intake, body weight, and physical activity and provided a caloric budget depending on weight goal. The primary objective was to evaluate adherence to caloric budget and body weight change among the most consistent (i.e., daily) trackers of caloric intake over a calendar year (n = 9372, 50% male).

Methods

Gender-stratified linear mixed models were conducted to examine the effects of quarter of year (Q1-Q4 as season proxies) and body mass index (BMI) group (normal weight, overweight, obesity) on adherence to a caloric budget (kcal/day). Change in body weight was analyzed using a subset of users (n = 5808) who entered their weight in the app at least once per week, once per month, or once in Q1 and Q4. Physical activity entries were evaluated in exploratory analyses.

Results

Only users with obesity met their caloric budget in Q1. Deviation from budget increased for all groups from Q1 to Q2 (mean change[±standard error of the mean]: +23.7[±1.8] and +39.7[±2.2] kcal/day for female and male users, p < 0.001), was stable between Q2 and Q3, and fluctuated thereafter depending on gender and BMI, with greater deviation among males with overweight. Users with obesity with weight entries at least once per month lost the most weight (-6.1[±0.3] and -4.5[±0.3] kg for females and males, p < 0.001). Physical activity was highest in the summer months.

Conclusions

Among consistent calorie trackers, adherence to a caloric budget and body weight vary by season, gender, and BMI. Self-monitoring of body weight in addition to calorie tracking may lead to improved weight loss outcomes.

Validity of muscular fitness self-assessments in the ecofit smartphone application: A correlation study

BACKGROUND

Mobile app-based interventions have the potential for wide-reach and therefore may be a useful tool in up-scaling physical activity interventions. In larger-scale interventions, face-to-face assessments are less cost-effective, and researchers often rely on surveys or activity trackers to assess outcomes. However, there is limited evidence of valid muscular fitness assessments that can be self-administered within mHealth interventions. As such, this study will evaluate the concurrent validity of upper and lower body muscular fitness that have been independently assessed by participants via the ecofit app, and face-to-face assessments conducted by a trained researcher.

METHODS

This study compared baseline data from two muscular fitness tests from the ecofit two-armed randomised controlled trial and self-assessed data collected via the ecofit smartphone app (i.e., validated 90-degree push-up and 60-second sit-to-stand test). To assess the concurrent validity, the self-assessed push-up and sit-to-stand tests (i.e., collected via the ecofit app) were correlated using Spearman's correlation coefficient against the researcher-assessed results (i.e., objective results collected during baseline assessment for the ecofit trial). Bland-Altman plots were also used to allow visualisation of the differences between the self- and research-assessed tests.

RESULTS

Participants (N = 54) completed the push-up (24.1%) and sit-to-stand (100%) tests within 14-days of receiving the app. The results revealed a strong significant correlation for the push-up test (0.83, p<0.001) and a moderate significant correlation for the sit-to-stand test (0.63, p<0.001).

CONCLUSION

This study provides support for the concurrent validity of self-reported upper and lower body muscular fitness assessments (i.e., the push-up and sit-to-stand tests) in mHealth. While these tests may be a feasible option for large scale physical activity interventions, more research is needed to determine the generalisability of these results.

The effects of information platform-based nursing on preventing venous thromboembolism in patients with hip fractures

PURPOSE

Venous thromboembolism (VTE) is a major health issue among hip fracture patients. This study aimed to develop an information platform based on a mobile application and then evaluate whether information platform-based nursing could improve patient's drug compliance and reduce the incidence of VTE in hip fracture patients.

METHODS

This study retrospectively analyzed hip fracture patients who were treated with conventional prevention and intervention methods for VTE (control group) between January 2008 and November 2012, and prospectively analyzed hip fracture patients who were treated with nursing intervention based on the information platform (study group) between January 2016 and September 2017. All the patients included in the both groups were hip fracture patients who had an age over 50 years, treated with surgery, and hospitalized ≥ 48 h. Patients were excluded if they admitted to hospital due to old fractures, had a severe bleeding after 72 h of admission, diagnosed with any type of VTE, or refused to participate in the study. The information platform was divided into medical, nursing, and patient interface. Based on the information platform, medical practitioners and nurses could perform risk assessments, monitoring management and early warnings, preventions and treatments, health educations, follow-up, and other aspects of nursing interventions for patients. This study compared essential characteristics, drug compliance, VTE occurrence, and mean length of hospitalization between the two groups. Besides, a subgroup analysis was performed in the study group according to different drug compliances. SPSS 18.0 software (IBM Corp., NY, and USA) was used for statistical analysis.

RESULTS

Altogether 1177 patients were included in the control group, and 491 patients in the study group. Regarding baseline data, patients in the study group had more morbidities than those in the control group (p < 0.05). The difference of drug compliance between the two groups was statistically significant (p < 0.001): 761 (64.7%) of the patients in the control group and only 30 (6.1%) patients in the study group had poor drug compliance. In terms of VTE, 10.7% patients (126/1177) in the control group had VTE, and the rate in the study group was 7.1% (35/491), showing a statistically significant difference (p = 0.02). Moreover, the average length of hospitalization in the study group was also significantly lower than that in the control group (10.4 days vs. 13.7 days, p < 0.001). Subgroup analyses of the study group showed that the incidence of VTE in patients with poor, partial, and good compliances were 56.7% (17/30), 5.8% (10/171), and 2.8% (8/290), respectively, revealing a significantly huge difference (p < 0.001).

CONCLUSIONS

Poor drug compliance leads to higher VTE occurrence. The information platform-based nursing can effectively improve the compliance of hip fracture patients and thus considerably reduce the incidence of VTE. The mobile application may be an effective tool to prevent VTE in hip fracture patients.

Nutrition-related mobile applications - Should they be used for dietary prevention and treatment of cardiovascular diseases?

BACKGROUND AND AIMS

There is no prior research on the usefulness that popular nutrition-related mobile applications would have in assessing fatty acids intake. In this study, we examine these applications through their utilization in the assessment of consumption of saturated (SFAs) and polyunsaturated (PUFAs) fatty acids against the Polish reference method (RM, Dieta 6.0). This report does also include the information about monounsaturated fatty acids and cholesterol intake.

METHODS AND RESULTS

SFAs and PUFAs intake was assessed using two-day dietary recalls obtained from 120 individuals by 3 selected mobile applications (App1 = Yazio, App2 = MyFitnessPal, App3 = Fitatu) and compared with RM. Despite strong (SFAs by App1 and App3) and moderate (SFAs by App2 and PUFAs by App1, App2, App3) correlations with RM, Bland-Altman analyses showed relevant biases and wide range between limits of agreement. Considering SFAs and MUFAs intake, App1 had the best agreement. App1 had high sensitivity (94.6%) in recognition of subjects with SFAs intake >10% with moderate specificity (67.9%), while App2 had poor sensitivity (27.2%) and high specificity (100%). App3 showed moderate sensitivity and specificity (77.2% and 75%, respectively).

CONCLUSIONS

Mobile applications are not accurate tools in SFAs and PUFAs assessment when compared to the RM. Nonetheless, their ability to recognize SFAs intake >10% energy intake may suggest that further development of mobile applications could potentially become an attractive tool in clinical practice.

Assessing the Pragmatic Nature of mHealth Interventions Promoting Physical Activity: A Systematic Review and Meta-Analysis (Preprint)

BACKGROUND

Mobile health (mHealth) apps can promote physical activity; however, the pragmatic nature (ie, how well research translates into real-world settings) of these studies is unknown. The impact of study design choices, for example, intervention duration, on intervention effect sizes is also understudied.

OBJECTIVE

This review and meta-analysis aims to describe the pragmatic nature of recent mHealth interventions for promoting physical activity and examine the associations between study effect size and pragmatic study design choices.

METHODS

The PubMed, Scopus, Web of Science, and PsycINFO databases were searched until April 2020. Studies were eligible if they incorporated apps as the primary intervention, were conducted in health promotion or preventive care settings, included a device-based physical activity outcome, and used randomized study designs. Studies were assessed using the Reach, Effectiveness, Adoption, Implementation, Maintenance (RE-AIM) and Pragmatic-Explanatory Continuum Indicator Summary-2 (PRECIS-2) frameworks. Study effect sizes were summarized using random effect models, and meta-regression was used to examine treatment effect heterogeneity by study characteristics.

RESULTS

Overall, 3555 participants were included across 22 interventions, with sample sizes ranging from 27 to 833 (mean 161.6, SD 193.9, median 93) participants. The study populations' mean age ranged from 10.6 to 61.5 (mean 39.6, SD 6.5) years, and the proportion of males included across all studies was 42.8% (1521/3555). Additionally, intervention lengths varied from 2 weeks to 6 months (mean 60.9, SD 34.9 days). The primary app- or device-based physical activity outcome differed among interventions: most interventions (17/22, 77%) used activity monitors or fitness trackers, whereas the rest (5/22, 23%) used app-based accelerometry measures. Data reporting across the RE-AIM framework was low (5.64/31, 18%) and varied within specific dimensions (Reach=44%; Effectiveness=52%; Adoption=3%; Implementation=10%; Maintenance=12.4%). PRECIS-2 results indicated that most study designs (14/22, 63%) were equally explanatory and pragmatic, with an overall PRECIS-2 score across all interventions of 2.93/5 (SD 0.54). The most pragmatic dimension was flexibility (adherence), with an average score of 3.73 (SD 0.92), whereas follow-up, organization, and flexibility (delivery) appeared more explanatory with means of 2.18 (SD 0.75), 2.36 (SD 1.07), and 2.41 (SD 0.72), respectively. An overall positive treatment effect was observed (Cohen d=0.29, 95% CI 0.13-0.46). Meta-regression analyses revealed that more pragmatic studies (-0.81, 95% CI -1.36 to -0.25) were associated with smaller increases in physical activity. Treatment effect sizes were homogenous across study duration, participants' age and gender, and RE-AIM scores.

CONCLUSIONS

App-based mHealth physical activity studies continue to underreport several key study characteristics and have limited pragmatic use and generalizability. In addition, more pragmatic interventions observe smaller treatment effects, whereas study duration appears to be unrelated to the effect size. Future app-based studies should more comprehensively report real-world applicability, and more pragmatic approaches are needed for maximal population health impacts.

TRIAL REGISTRATION

PROSPERO CRD42020169102; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=169102.