Physical Activity Behavior Change Driven by Engagement With an Incentive-Based App: Evaluating the Impact of Sweatcoin

Gamified Mobile Health Strategies for Promoting Physical Activity in Autistic Adults

Physical inactivity and sedentarism among autistic adults are a growing public health concern. By integrating behavior change theories and emphasizing unique preferences for visuospatial learning and gaming technology, we hypothesize that gamified mobile health (mHealth) applications can be effective at increasing free-living physical activity and reducing sedentary behavior in autistic adults.

Tracked Physical Activity Levels Before and After a Change in Incentive Strategy Among UK Adults Using a Rewards App: Retrospective Quasi-Experimental Study

BACKGROUND

Financial incentives delivered via apps appear to be effective in encouraging physical activity. However, the literature on different incentive strategies is limited, and the question remains whether financial incentives offer a cost-effective intervention that could be funded at the population level.

OBJECTIVE

This study aimed to explore patterns of tracked physical activity by users of an incentive-based app before and after a change in incentive strategy. A business decision to alter the incentives in a commercially available app offered a natural experiment to explore GPS-tracked data in a retrospective, quasi-experimental study. The purpose of this exploratory analysis was to inform the design of future controlled trials of incentives delivered via an app to optimize their usability and cost-effectiveness.

METHODS

Weekly minutes of tracked physical activity were explored among a sample of 1666 participants. A Friedman test was used to determine differences in physical activity before and after the change in incentive strategies. Post hoc Wilcoxon tests were used to assess minutes of physical activity in the 2 weeks before and after the change. A secondary analysis explored longitudinal patterns of physical activity by plotting the mean and median minutes of physical activity from 17 weeks before and 13 weeks after the change in incentive strategy. CIs were calculated using bias-corrected bootstraps. Demographics were also explored in this way.

RESULTS

There were significant differences in the weekly minutes of activity before and after the change in incentive strategy (Friedman χ22=42, P<.001). However, a longitudinal view of the data showed a more complex and marked variation in activity over time that undermined the conclusions of the before/after analysis.

CONCLUSIONS

Short-term before-and-after observational studies of app-tracked physical activity may result in misleading conclusions about the effectiveness of incentive strategies. Longitudinal views of the data show that important fluctuations are occurring over time. Future studies of app-tracked physical activity should explore such variations by using longitudinal analyses and accounting for possible moderating variables to better understand what an effective incentive might be, for whom, and at what cost.

Home-based exercise training by using a smartphone app in patients with Parkinson's disease: a feasibility study

Background

Parkinson's disease (PD) patients experience deterioration in mobility with consequent inactivity and worsened health and social status. Physical activity and physiotherapy can improve motor impairments, but several barriers dishearten PD patients to exercise regularly. Home-based approaches (e.g., via mobile apps) and remote monitoring, could help in facing this issue.

Objective

This study aimed at testing the feasibility, usability and training effects of a home-based exercise program using a customized version of Parkinson Rehab® application.

Methods

Twenty PD subjects participated in a two-month minimally supervised home-based training. Daily session consisted in performing PD-specific exercises plus a walking training. We measured: (i) feasibility (training adherence), usability and satisfaction (via an online survey); (ii) safety; (iii) training effects on PD severity, mobility, cognition, and mood. Evaluations were performed at: baseline, after 1-month of training, at the end of training (T2), and at 1-month follow-up (T3).

Results

Eighteen out of twenty participants completed the study without important adverse events. Participants' adherence was 91% ± 11.8 for exercise and 105.9% ± 30.6 for walking training. Usability and satisfaction survey scored 70.9 ± 7.7 out of 80. Improvements in PD severity, mobility and cognition were found at T2 and maintained at follow-up.

Conclusion

The home-based training was feasible, safe and seems to positively act on PD-related symptoms, mobility, and cognition in patients with mild to moderate stage of PD disease. Additionally, the results suggest that the use of a mobile app might increase the amount of daily physical activity in our study population. Remote monitoring and tailored exercise programs appear to be key elements for promoting exercise. Future studies in a large cohort of PD participants at different stages of disease are needed to confirm these findings.

New App-Based Dietary and Lifestyle Intervention on Weight Loss and Cardiovascular Health

Consumer digital technology is rapidly evolving, allowing users to manage their health in a simple, non-invasive manner. However, there are few studies revealing if using digital technology as part of an intervention really has an impact in consumer health compared with traditional strategies. The objective of the current study is to compare two groups (MTB; n = 18, 46.1 ± 10.4 years and MTBAPP; n = 19, 45.3 ± 6.40 years) of overweight, prehypertensive individuals in losing weight and lowering their blood pressure. Both were provided with nutritionist-guided recommendations, a wearable tracking device and a dietary supplement that has previously been proven to help lose body weight and lower blood pressure. In addition, one of the groups (MTBAPP) used a mobile app specifically designed for the intervention. Blood pressure, body composition, triglyceride level, peak expiratory flow, forced expiratory volume in the first second and maximum oxygen volume were measured at different time points. In addition, participants were monitored with an activity bracelet throughout the intervention. As a result, both groups significantly lost body weight, while the group using the app additionally improved blood pressure levels and lowered fat mass. Furthermore, the app users significantly increased the number of daily steps and decreased sedentary time. In conclusion, the addition of a mobile app with daily reminders to follow healthy lifestyle recommendations increased physical activity and overall improved blood pressure and fat mass levels when compared with a group performing the same intervention but in absence of the mobile application.

Changes in blood lipid levels after a digitally-enabled, cardiometabolic preventive health program: a pre-post study in an adult, Dutch general population cohort (Preprint)

Background

Despite widespread education, many individuals fail to follow basic health behaviors such as consuming a healthy diet and exercising. Positive changes in lifestyle habits are associated with improvements in multiple cardiometabolic health risk factors, including lipid levels. Digital lifestyle interventions have been suggested as a viable complement or potential alternative to conventional health behavior change strategies. However, the benefit of digital preventive interventions for lipid levels in a preventive health context remains unclear.

Objective

This observational study aimed to determine how the levels of lipids, namely total cholesterol, high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, non-HDL cholesterol, and triglycerides, changed over time in a Dutch general population cohort undergoing a digital preventive health program. Moreover, we looked to establish associations between lifestyle factors at baseline and lipid levels.

Methods

We included 348 adults from the Dutch general population who underwent a digitally enabled preventive health program at Ancora Health between January 2020 and October 2021. Upon enrollment, participants underwent a baseline assessment involving a comprehensive lifestyle questionnaire, a blood biochemistry panel, physical measurements, and cardiopulmonary fitness measurements. Thereafter, users underwent a lifestyle coaching program and could access the digital application to register and track health behaviors, weight, and anthropometric data at any time. Lipid levels were categorized as normal, elevated, high, and clinical dyslipidemia according to accepted international standards. If at least one lipid marker was high or HDL was low, participants received specific coaching and advice for cardiometabolic health. We retrospectively analyzed the mean and percentage changes in lipid markers in users who were remeasured after a cardiometabolic health–focused intervention, and studied the association between baseline user lifestyle characteristics and having normal lipid levels.

Results

In our cohort, 199 (57.2%) participants had dyslipidemia at baseline, of which 104 participants were advised to follow a cardiometabolic health–focused intervention. Eating more amounts of favorable food groups and being more active were associated with normal lipid profiles. Among the participants who underwent remeasurement 9 months after intervention completion, 57% (17/30), 61% (19/31), 56% (15/27), 82% (9/11), and 100% (8/8) showed improvements at remeasurement for total, LDL, HDL, and non-HDL cholesterol, and triglycerides, respectively. Moreover, between 35.3% and 77.8% showed a return to normal levels. In those with high lipid levels at baseline, total cholesterol decreased by 0.5 mmol/L (7.5%), LDL cholesterol decreased by 0.39 mmol/L (10.0%), non-HDL cholesterol decreased by 0.44 mmol/L (8.3%), triglycerides decreased by 0.97 mmol/L (32.0%), and HDL increased by 0.17 mmol/L (15.6%), after the intervention.

Conclusions

A cardiometabolic screening program in a general population cohort identified a significant portion of individuals with subclinical and clinical lipid levels. Individuals who, after screening, actively engaged in a cardiometabolic health–focused lifestyle program improved their lipid levels.

Stay home and stay active? The impact of stay-at-home restrictions on physical activity routines in the UK during the COVID-19 pandemic

We investigated which population groups were impacted most in terms of physical activity levels during the restrictions applied during the COVID-19 pandemic. We surveyed UK residents, sampled through users of a rewards-for-exercise app (Sweatcoin; n = 749) and an online panel (Prolific; n = 907). Of the app users, n = 487 further provided daily step-count data collected by the app, prior to, and during the periods of restrictions in the UK between March-June 2020. Regression models were used to investigate factors associated with self-reported change in physical activity and change in daily step-count during the periods of restrictions. Significant factors associated with self-reported change in physical activity included rural residents (positive, b = 0.87, p < 0.001), relative to urban dwellers, people classed as obese (negative, b = -0.51, p = 0.008, relative to healthy weight) and gym users (negative, b = -1.10, p < 0.001, relative to walkers). All groups had reduced step counts during restrictions, with Black, Asian and minority ethnic groups showing greater reductions compared to White British ethnicity (negative, b = -0.18, p = 0.008). Targeted interventions are required to ensure that physical and mental health impacts of sedentary behaviour are not exacerbated over the long-term by significant reductions in physical activity identified in these groups particularly those who are also more vulnerable to COVID-19.

A Focus Group Study Among Inactive Adults Regarding the Perceptions of a Theory-Based Physical Activity App

Background: Despite the increasing attention for the positive effects of physical activity (PA), nearly half of the Dutch citizens do not meet the national PA guidelines. A promising method for increasing PA are mobile exercise applications (apps), especially if they are embedded with theoretically supported persuasive strategies (e.g., goal setting and feedback) that align with the needs and wishes of the user. In addition, it is argued that the operationalization of the persuasive strategies could increase the effectiveness of the app, such as the actual content or visualization of feedback. Although much research has been done to examine the preferences for persuasive strategies, little is known about the needs, wishes, and preferences for the design and operationalization of persuasive strategies.

Objective: The purpose of this study was to get insight in the needs, wishes, and preferences regarding the practical operationalization of persuasive strategies in a mobile application aimed at promoting PA in healthy inactive adults.

Methods: Five semistructured focus groups were performed. During the focus groups, the participants were led into a discussion about the design and operationalization of six predefined theory-based persuasive strategies (e.g., self-monitoring, feedback, goal setting, reminders, rewards, and social support) directed by two moderators. The audio-recorded focus groups were transcribed verbatim and analyzed following the framework approach.

Results: Eight men and 17 women between 35 and 55 years (mean age, 49.2) participated in the study. Outcomes demonstrated diverse preferences for implementation types and design characteristics of persuasive strategies in mobile applications. Basic statistics (such as distance, time and calories), positive feedback based on easy-to-achieve goals that relate to health guidelines, and motivating reminders on a relevant moment were preferred. Participants had mixed preferences regarding rewards and a social platform to invite other users to join PA.

Conclusions: Findings indicated that in mHealth applications for healthy but inactive adults, persuasive strategies should be designed and implemented in a way that they relate to health guidelines. Moreover, there is a need for an app that can be adapted or can learn based on personal preferences as, for example, preferences with regard to timing of feedback and reminders differed between people.

Effects of an mHealth App (Kencom) With Integrated Functions for Healthy Lifestyles on Physical Activity Levels and Cardiovascular Risk Biomarkers: Observational Study of 12,602 Users

Background

Mobile health (mHealth) apps are considered to be potentially powerful tools for improving lifestyles and preventing cardiovascular disease (CVD), although only few have undergone large, well-designed epidemiological research. “kencom” is a novel mHealth app with integrated functions for healthy lifestyles such as monitoring daily health/step data, providing tailored health information, or facilitating physical activity through group-based game events. The app is linked to large-scale Japanese insurance claims databases and annual health check-up databases, thus comprising a large longitudinal cohort.

Objective

We aimed to assess the effects of kencom on physical activity levels and CVD risk factors such as obesity, hypertension, dyslipidemia, and diabetes mellitus in a large population in Japan.

Methods

Daily step count, annual health check-up data, and insurance claim data of the kencom users were integrated within the kencom system. Step analysis was conducted by comparing the 1-year average daily step count before and after kencom registration. In the CVD risk analysis, changes in CVD biomarkers following kencom registration were evaluated among the users grouped into the quintile according to their change in step count.

Results

A total of 12,602 kencom users were included for the step analysis and 5473 for the CVD risk analysis. The participants were generally healthy and their mean age was 44.1 (SD 10.2) years. The daily step count significantly increased following kencom registration by a mean of 510 steps/day (P<.001). In particular, participation in “Arukatsu” events held twice a year within the app was associated with a remarkable increase in step counts. In the CVD risk analysis, the users of the highest quintile in daily step change had, compared with those of the lowest quartile, a significant reduction in weight (–0.92 kg, P<.001), low-density lipoprotein cholesterol (–2.78 mg/dL, P=.004), hemoglobin A_1c (HbA_1c; –0.04%, P=.004), and increase in high-density lipoprotein cholesterol (+1.91 mg/dL, P<.001) after adjustment of confounders.

Conclusions

The framework of kencom successfully integrated the Japanese health data from multiple data sources to generate a large, longitudinal data set. The use of the kencom app was significantly associated with enhanced physical activity, which might lead to weight loss and improvement in lipid profile.

Can a 'rewards-for-exercise app' increase physical activity, subjective well-being and sleep quality? An open-label single-arm trial among university staff with low to moderate physical activity levels

BACKGROUND

This study examined the impact of a 'rewards-for-exercise' mobile application on physical activity, subjective well-being and sleep quality among 148 employees in a UK university with low to moderate physical activity levels.

METHODS

A three-month open-label single-arm trial with a one-year follow-up after the end of the trial. Participants used the Sweatcoin application which converted their outdoor steps into a virtual currency used for the purchase of products available at the university campus' outlets, using an in-app marketplace. The primary outcome measure was self-reported physical activity. Secondary measures included device-measured physical activity, subjective well-being (i.e., life satisfaction, positive affect, negative affect), and self-reported sleep quality.

RESULTS

The findings show an increase in self-reported physical activity (d = 0.34), life satisfaction (d = 0.31), positive affect (d = 0.29), and sleep quality (d = 0.22) during the three-month trial period.

CONCLUSION

The study suggests that mobile incentives-for-exercise applications might increase physical activity levels, positive affect, and sleep quality, at least in the short term. The observed changes were not sustained 12 months after the end of the trial.

Designing the Optimal Digital Health Intervention for Patients' Use Before and After Elective Orthopedic Surgery: Qualitative Study

Background

Health behavior changes made by patients during the perioperative period can impact the outcomes and success of elective surgeries. However, there remains a limited understanding of how best to support patients during this time, particularly through the use of digital health interventions. Recognizing and understanding the potential unmet needs of elective orthopedic surgery patients is central to motivating healthier behavior change, improving recovery, and optimizing overall surgical success in the short and long term.

Objective

The aim of this study is to explore patient perspectives on technology features that would help support them to change their lifestyle behaviors during the pre- and postoperative periods, and that could potentially maintain long-term healthy lifestyles following recovery.

Methods

Semistructured interviews with pre- and postoperative elective orthopedic patients were conducted between May and June 2020 using telephone and video call–based software. Patient perspectives on the use of digital technologies to complement current surgical care and support with lifestyle behavior changes were discussed. Interviews were audio recorded and transcribed verbatim. Reflexive thematic analysis enabled the development of themes from the data, with QSR NVivo software (version 12) facilitating data management. Ethical approval was obtained from the National Health Service Health Research Authority.

Results

A total of 18 participants were interviewed. Four themes were developed from the data regarding the design and functionality of digital technologies to best support the perioperative journey. These center around an intervention’s ability to incorporate interactive, user-centered features; direct a descriptive and structured recovery; enable customizable, patient-controlled settings; and deliver both general and specific surgical advice in a timely manner. Interventions that are initiated preoperatively and continued postoperatively were perceived as beneficial. Interventions designed with personalized milestones were found to better guide patients through a structured recovery. Individualized tailoring of preparatory and recovery information was desired by patients with previously high levels of physical activity before surgery. The use of personalized progression-based exercises further encouraged physical recovery; game-like rewards and incentives were regarded as motivational for making and sustaining health behavior change. In-built video calling and messaging features offered connectivity with peers and clinicians for supported care delivery.

Conclusions

Specific intervention design and functionality features can provide better, structured support for elective orthopedic patients across the entire surgical journey and beyond. This study provides much-needed evidence relating to the optimal design and timing of digital interventions for elective orthopedic surgical patients. Findings from this study suggest a desire for personalized perioperative care, in turn, supporting patients to make health behavior changes to optimize surgical success. These findings should be used to influence future co-design projects to enable the design and implementation of patient-focused, tailored, and targeted digital health technologies within modern health care settings.

Towards Secure Fitness Framework Based on IoT-Enabled Blockchain Network Integrated with Machine Learning Algorithms

Blockchain technology has recently inspired remarkable attention due to its unique features, such as privacy, accountability, immutability, and anonymity, to name of the few. In contrast, core functionalities of most Internet of Things (IoT) resources make them vulnerable to security threats. The IoT devices, such as smartphones and tablets, have limited capacity in terms of network, computing, and storage, which make them easier for vulnerable threats. Furthermore, a massive amount of data produced by the IoT devices, which is still an open challenge for the existing platforms to process, analyze, and unearth underlying patterns to provide convenience environment. Therefore, a new solution is required to ensure data accountability, improve data privacy and accessibility, and extract hidden patterns and useful knowledge to provide adequate services. In this paper, we present a secure fitness framework that is based on an IoT-enabled blockchain network integrated with machine learning approaches. The proposed framework consists of two modules: a blockchain-based IoT network to provide security and integrity to sensing data as well as an enhanced smart contract enabled relationship and inference engine to discover hidden insights and useful knowledge from IoT and user device network data. The enhanced smart contract aims to support users with a practical application that provides real-time monitoring, control, easy access, and immutable logs of multiple devices that are deployed in several domains. The inference engine module aims to unearth underlying patterns and useful knowledge from IoT environment data, which helps in effective decision making to provide convenient services. For experimental analysis, we implement an intelligent fitness service that is based on an enhanced smart contract enabled relationship and inference engine as a case study where several IoT fitness devices are used to securely acquire user personalized fitness data. Furthermore, a real-time inference engine investigates user personalized data to discover useful knowledge and hidden insights. Based on inference engine knowledge, a recommendation model is developed to recommend a daily and monthly diet, as well as a workout plan for better and improved body shape. The recommendation model aims to facilitate a trainer formulating effective future decisions of trainee's health in terms of a diet and workout plan. Lastly, for performance analysis, we have used Hyperledger Caliper to access the system performance in terms of latency, throughput, resource utilization, and varying orderer and peers nodes. The analysis results imply that the design architecture is applicable for resource-constrained IoT blockchain platform and it is extensible for different IoT scenarios.

Mobile physical activity planning and tracking: a brief overview of current options and desiderata for future solutions

Consistent and enjoyable physical activity (PA) can be a crucial component to improving or maintaining one's overall health status. Using advanced features on smartphones (GPS, Bluetooth, motion sensing, etc.) coupled with an app or game that is able to assist mobile users to not only track location, but also to interact socially with others based in real-life (IRL), virtual reality (VR), or alternate-reality (ARG), has the potential to give health experts better tools to encourage higher compliance to protocols, rehabilitation, behaviour change and health outcomes. This paper outlines the available mHealth apps that capitalize on pervasive smartphone features coupled with sensors, and suggests which features might impact future PA patterns. The authors argue that the ultimate mobile PA planning and tracking app/platform will be the one capable of supporting both precision and accuracy health (offering truly individualized PA advice and coaching while preserving user privacy) and precision and accuracy public health (providing public health decision makers with community-level PA indicators obtained from app data aggregates of user populations).

Needs and Requirements in the Designing of Mobile Interventions for Patients With Peripheral Arterial Disease: Questionnaire Study

Background

The development of mobile interventions for noncommunicable diseases has increased in recent years. However, there is a dearth of apps for patients with peripheral arterial disease (PAD), who frequently have an impaired ability to walk.

Objective

Using a patient-centered approach for the development of mobile interventions, we aim to describe the needs and requirements of patients with PAD regarding the overall care situation and the use of mobile interventions to perform supervised exercise therapy (SET).

Methods

A questionnaire survey was conducted in addition to a clinical examination at the vascular outpatient clinic of the West-German Heart and Vascular Center of the University Clinic Essen in Germany. Patients with diagnosed PAD were asked to answer questions on sociodemographic characteristics, PAD-related need for support, satisfaction with their health care situation, smartphone and app use, and requirements for the design of mobile interventions to support SET.

Results

Overall, a need for better support of patients with diagnosed PAD was identified. In total, 59.2% (n=180) expressed their desire for more support for their disease. Patients (n=304) had a mean age of 67 years and half of them (n=157, 51.6%) were smartphone users. We noted an interest in smartphone-supported SET, even for people who did not currently use a smartphone. “Information,” “feedback,” “choosing goals,” and “interaction with physicians and therapists” were rated the most relevant components of a potential app.

Conclusions

A need for the support of patients with PAD was determined. This was particularly evident with regard to disease literacy and the performance of SET. Based on a detailed description of patient characteristics, proposals for the design of mobile interventions adapted to the needs and requirements of patients can be derived.

Effect of Pokémon Go on Self-Harm Using Population-Based Interrupted Time-Series Analysis: Quasi-Experimental Study

BACKGROUND

Pokémon Go is a very popular location-based augmented reality game with widespread influences over the world. An emerging body of research demonstrates that playing Pokémon Go can lead to improvements in physical activity and psychosocial well-being; however, whether Pokémon Go reduces self-harm incidence at the population-level is still questionable.

OBJECTIVE

This study aimed to quantify how the launch of Pokémon Go in Hong Kong affected the incidence of self-harm using a quasi-experimental design.

METHODS

An interrupted time-series design with Poisson segmented regression adjusted for time and seasonality trends was used on data from 2012 to 2018 to detect any changes in the number of accident and emergency attendances due to self-harm, after Pokémon Go was launched. The findings were validated using a baseline control period and using other intentional injuries and minor noninjuries as control outcomes. We also assessed intervention effects by age group.

RESULTS

From January 1, 2012 to July 31, 2018, there were 13,463 accident and emergency attendances due to self-harm in Hong Kong. During the period after launching Pokémon Go, self-harm attendances dropped by 34% (adjusted incidence rate ratio: 0.66, 95% CI 0.61-0.73). When analyzed by age group, a reduction in self-harm incidence was only apparent in adults (18 to 24 years of age: adjusted incidence rate ratio: 0.78, P=.02; 25 to 39 years of age: adjusted incidence rate ratio: 0.75, P<.001; 40 years of age and older: adjusted incidence rate ratio: 0.57, P<.001).

CONCLUSIONS

Self-harm incidence in the population, particularly in adults, showed a significant decline in the period after Pokémon Go was launched. Augmented reality games such as Pokémon Go show great promise as a tool to enhance psychosocial well-being and improve mental health.

Commercial app use linked with sustained physical activity in two Canadian provinces: a 12-month quasi-experimental study

Background

Top tier commercial physical activity apps rarely undergo peer-reviewed evaluation. Even fewer are assessed beyond six months, the theoretical threshold for behaviour maintenance. The purpose of this study was to examine whether a multi-component commercial app rewarding users with digital incentives for walking was associated with an increase in physical activity over one year.

Methods

This 12-month quasi-experimental study was conducted in two Canadian provinces (n = 39,113 participants). Following a two-week baseline period, participants earned digital incentives ($0.04 CAD/day) every day they reached a personalized daily step goal. Mixed-effects models estimated changes in weekly mean daily step count between the baseline period and the last two recorded weeks. Models were fit for several engagement groups and separately by baseline physical activity status within engagement groups.

Results

Nearly half of participants (43%) were categorized as physically inactive at baseline (fewer than 5000 daily steps), and 60% engaged with the app for at least six months [‘Regular’ (24–51 weeks of step data) or ‘Committed’ sub-groups (52 weeks)]. Weekly mean daily step count increased for physically inactive users regardless of engagement status (P < .0001). The increase was largest for ‘Regular’ and ‘Committed’ participants—1215 and 1821 steps/day, respectively. For physically active participants, step count increases were only observed in the ‘Committed’ sub-group (P < .0001). Effect sizes were modest-to-medium depending on the sub-group analyzed.

Conclusions

A commercial app providing small but immediate digital incentives for individualized goals was associated with an increased weekly mean daily step count on a population-scale over one year. This effect was more evident for physically inactive and more engaged participants.