Loss-Framed Financial Incentives and Personalized Goal-Setting to Increase Physical Activity Among Ischemic Heart Disease Patients Using Wearable Devices: The ACTIVE REWARD Randomized Trial

Investigating racial and gender disparities in virtual randomized clinical trial enrollment: Insights from the BE ACTIVE study

Randomized clinical trials (RCTs) often suffer from a lack of representation from historically marginalized populations, and it is uncertain whether virtual RCTs (vRCTs) enhance representativeness or if elements of their consent and enrollment processes may instead contribute to underrepresentation of these groups. In this study, we aimed to identify disparities in enrollment demographics in a vRCT, the BE ACTIVE study, which recruited patients within a single health system. We discovered that the proportions of eligible patients who were randomized differed significantly by gender and race/ethnicity (men 1.2%, women 2.0%, P < .001; White 1.8%, Black 1.3%, Hispanic 0.7%, Asian 0.9%; P < .001), and compared with White patients, non-White patients were less likely to have a valid email address on file and were less likely to click on the email link to the study webpage and begin enrollment.

A randomized trial of behavioral interventions yielding sustained reductions in distracted driving

Distracted driving is responsible for nearly 1 million crashes each year in the United States alone, and a major source of driver distraction is handheld phone use. We conducted a randomized, controlled trial to compare the effectiveness of interventions designed to create sustained reductions in handheld use while driving (NCT04587609). Participants were 1,653 consenting Progressive® Snapshot® usage-based auto insurance customers ages 18 to 77 who averaged at least 2 min/h of handheld use while driving in the month prior to study invitation. They were randomly assigned to one of five arms for a 10-wk intervention period. Arm 1 (control) got education about the risks of handheld phone use, as did the other arms. Arm 2 got a free phone mount to facilitate hands-free use. Arm 3 got the mount plus a commitment exercise and tips for hands-free use. Arm 4 got the mount, commitment, and tips plus weekly goal gamification and social competition. Arm 5 was the same as Arm 4, plus offered behaviorally designed financial incentives. Postintervention, participants were monitored until the end of their insurance rating period, 25 to 65 d more. Outcome differences were measured using fractional logistic regression. Arm 4 participants, who received gamification and competition, reduced their handheld use by 20.5% relative to control (P < 0.001); Arm 5 participants, who additionally received financial incentives, reduced their use by 27.6% (P < 0.001). Both groups sustained these reductions through the end of their insurance rating period.

Effect of gamification with a support partner to increase physical activity in older adults at risk for Alzheimer's disease: The STEP 4Life randomized clinical trial

INTRODUCTION

Physical activity is associated with reduced risk of cognitive and functional decline but scalable, sustainable interventions for populations at risk for Alzheimer's disease (AD) and AD and related dementias (ADRD) are lacking.

METHODS

A 12-week randomized-controlled trial was conducted with a 3-week follow-up using a national AD prevention registry (GeneMatch). The control group (n = 50) set step goals and received daily feedback. The intervention group (n = 44) also received a behaviorally designed game based on achieving step goals and reinforced by a support partner.

RESULTS

Intervention participants (94 participants, mean age 70, 78% female) had greater change in mean daily step count than control of 1699 steps/day (95% confidence interval [CI], 1149-2249), P < 0.0001, which was sustained in the follow-up period at 1219 steps/day (95% CI, 455-1983), P = 0.0018. Carriers of the apolipoprotein E ε4 gene (high risk) did not perform differently than non-carriers; however, high self-reported risk perception was associated with higher activity.

DISCUSSION

A gamified intervention was effective in promoting and sustaining higher physical activity in older adults at genetic risk for AD/ADRD.

HIGHLIGHTS

A simple game played with a support partner increased walking in older adults at risk for Alzheimer's disease (AD). The game also increased minutes of moderate-to-vigorous physical activity per day. Perception of lifelong AD risk was associated with increased activity but genetic risk (apolipoprotein E ε4+) was not.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT05069155.

Hourly step recommendations to achieve daily goals for working and older adults

BACKGROUND

The widespread use of physical activity trackers enables the collection of high-resolution health data, such as hourly step counts, to evaluate health promotion programmes. We aim to investigate how participants meet their daily step goals.

METHODS

We used 24-h steps data from the National Steps ChallengeTM Season 3, wherein participants were rewarded with vouchers when achieving specified goals of 5000, 7500, and 10,000 steps per day. We extracted data from 3075 participants' including a total of 52,346 participant-days. We modelled the hourly step counts using a two-part model, in which the distribution for step counts was allowed to depend on the sum of step counts up to the previous hour and participant demographics.

RESULTS

Participants have a mean age of 44.2 years (standard deviation = 13.9), and 40.4% are males. We show that on weekdays, the hourly mean step counts among participants aged 60 and above are higher than participants aged 30 to 59 from the start of the day till 6 p.m. We also find that participants who accumulate at least 7000 steps by 7 p.m. are associated with higher success of achieving 10,000 steps.

CONCLUSIONS

We provide recommendations on the hourly targets to achieve daily goals, based on different participants' characteristics. Future studies could experimentally test if prompts and nudges at the recommended times of day could promote reaching step goals.

Older Veteran Experiences of using Technology during a Multicomponent Telerehabilitation Program: A Convergent Mixed Methods Study

Less than half of U.S. veterans meet physical activity guidelines. Even though changing physical activity can be challenging, prior studies have demonstrated that it is possible. Older adults are using technology to aid in such behavior change. However, research that explores the mechanisms of how technology can aid in behavior change is lacking, especially among older veterans. Thus, the purpose of this secondary, convergent mixed methods study was to explore how older veterans engaged with technologies that were used during a multicomponent telerehabilitation program. The study included veterans aged ≥60 years with ≥3 chronic medical conditions and physical function limitation. Quantitative data were collected during the primary randomized controlled trial, and qualitative data were collected via individual interviews following completion of the telerehabilitation program. Data were merged and then analyzed by high vs. low technology engagement groups. Key similarities and differences between groups were identified in five domains: satisfaction with the virtual environment, coping self-efficacy, perceptions of Annie (automated text messaging platform), experiences using the activity monitor, and self-management skills. Findings can help inform the successful integration of similar technologies into physical rehabilitation programs. Further study is warranted to understand additional factors and mechanisms that influence technology engagement in telerehabilitation.

Effect of Gamification, Financial Incentives, or Both to Increase Physical Activity Among Patients at High Risk of Cardiovascular Events: The BE ACTIVE Randomized Controlled Trial

BACKGROUND

Physical activity is associated with a lower risk of major adverse cardiovascular events, but few individuals achieve guideline-recommended levels of physical activity. Strategies informed by behavioral economics increase physical activity, but their longer-term effectiveness is uncertain. We sought to determine the effect of behaviorally designed gamification, loss-framed financial incentives, or their combination on physical activity compared with attention control over 12-month intervention and 6-month postintervention follow-up periods.

METHODS

Between May 2019 and January 2024, participants with clinical atherosclerotic cardiovascular disease or a 10-year risk of myocardial infarction, stroke, or cardiovascular death of ≥7.5% by the Pooled Cohort equation were enrolled in a pragmatic randomized clinical trial. Participants received a wearable device to track daily steps, established a baseline, selected a step goal increase, and were randomly assigned to control (n=151), behaviorally designed gamification (n=304), loss-framed financial incentives (n=302), or gamification+financial incentives (n=305). The primary outcome of the trial was the change in mean daily steps from baseline through the 12-month intervention period.

RESULTS

A total of 1062 patients (mean±SD age, 67±8; 61% female; 31% non-White) were enrolled. Compared with control subjects, participants had significantly greater increases in mean daily steps from baseline during the 12-month intervention in the gamification arm (adjusted difference, 538.0 [95% CI, 186.2-889.9]; P=0.0027), financial incentives arm (adjusted difference, 491.8 [95% CI, 139.6-844.1]; P=0.0062), and gamification+financial incentives arm (adjusted difference, 868.0 [95% CI, 516.3-1219.7]; P<0.0001). During the 6-month follow-up, physical activity remained significantly greater in the gamification+financial incentives arm than in the control arm (adjusted difference, 576.2 [95% CI, 198.5-954]; P=0.0028), but it was not significantly greater in the gamification (adjusted difference, 459.8 [95% CI, 82.0-837.6]; P=0.0171) or financial incentives (adjusted difference, 327.9 [95% CI, -50.2 to 706]; P=0.09) arms after adjustment for multiple comparisons.

CONCLUSIONS

Behaviorally designed gamification, loss-framed financial incentives, and the combination of both increased physical activity compared with control over a 12-month intervention period, with the largest effect in gamification+financial incentives. These interventions could be a useful component of strategies to reduce cardiovascular risk in high-risk patients.

REGISTRATION

URL: https://clinicaltrials.gov; Unique Identifier: NCT03911141.

Gamification-augmented home-based exercise for peripheral artery disease: Rationale and design of the GAMEPAD Study

BACKGROUND

Supervised exercise therapy improves walking performance, functional capacity, and quality of life in patients with peripheral artery disease (PAD). However, few patients with PAD are enrolled in supervised exercise programs, and there are a number of logistical and financial barriers to their participation. A home-based walking intervention is likely to be more accessible to patients with PAD, but no fully home-based walking program has demonstrated efficacy. Concepts from behavioral economics have been used to design scalable interventions that increase daily physical activity in patients with atherosclerotic vascular disease, but whether a similar program would be effective in patients with PAD is uncertain.

STUDY DESIGN AND OBJECTIVES

GAMEPAD (NCT04536012) is a pragmatic, virtual, randomized controlled trial designed to evaluate the effectiveness of a gamification strategy informed by concepts from behavioral economics to increase daily physical activity in patients with PAD who are seen in cardiology and vascular surgery clinics affiliated with the University of Pennsylvania Health System. Patients are contacted by email or text message, and complete enrollment and informed consent on the Penn Way to Health online platform. A GAMEPAD substudy will evaluate the effectiveness of opt-in versus opt-out framing when approaching patients for study participation. Patients are then provided with a wearable fitness tracker, establish a baseline daily step count, set a goal to increase daily step count by 33%-50%, and are randomized 1:1 to the gamification or control arms. Interventions continue for 16 weeks, including a 4-week period during which goal step count is gradually increased in the gamification arm, with follow-up for an additional 8 weeks to evaluate the durability of behavior change. The trial has met its enrollment goal of 102 participants, with a primary endpoint of change from baseline in daily steps over the 16-week intervention period. Key secondary endpoints include change from baseline in daily steps over the 8-week postintervention follow-up period and changes in patient-reported measures of PAD symptoms and quality of life over the intervention and follow-up periods.

CONCLUSIONS

GAMEPAD is a virtual, pragmatic randomized clinical trial of a novel, fully home-based walking intervention informed by concepts from behavioral economics to increase physical activity and PAD-specific quality of life in patients with PAD. Its results will have important implications for the application of behavioral economic concepts to scalable home-based strategies to promote physical activity in patients with PAD and other disease processes where physical activity is limited by exertional symptoms.

CLINICAL TRIAL REGISTRATION

clinicaltrials.gov; NCT04536012.

A randomized, controlled, prehabilitation intervention to maximize early recovery (PRIMER) in liver transplantation

Frailty and impaired functional status are associated with adverse outcomes on the liver transplant (LT) waitlist and after transplantation. Prehabilitation prior to LT has rarely been tested. We conducted a 2-arm patient-randomized pilot trial to evaluate the feasibility and efficacy of a 14-week behavioral intervention to promote physical activity prior to LT. Thirty patients were randomized 2:1 to intervention (n = 20) versus control (n = 10). The intervention arm received financial incentives and text-based reminders linked to wearable fitness trackers. Daily step goals were increased by 15% in 2-week intervals. Weekly check-ins with study staff assessed barriers to physical activity. The primary outcomes were feasibility and acceptability. Secondary outcomes included mean end-of-study step counts, short physical performance battery, grip strength, and body composition by phase angle. We fit regression models for secondary outcomes with the arm as the exposure adjusting for baseline performance. The mean age was 61, 47% were female, and the median Model for End-stage Liver Disease sodium (MELD-Na) was 13. One-third were frail or prefrail by the liver frailty index, 40% had impaired mobility by short physical performance battery, nearly 40% had sarcopenia by bioimpedance phase angle, 23% had prior falls, and 53% had diabetes. Study retention was 27/30 (90%; 2 unenrolled from intervention, 1 lost to follow-up in control arm). Self-reported adherence to exercise during weekly check-ins was about 50%; the most common barriers were fatigue, weather, and liver-related symptoms. End-of-study step counts were nearly 1000 steps higher for intervention versus control: adjusted difference 997, 95% CI, 147-1847; p = 0.02. On average, the intervention group achieved daily step targets 51% of the time. A home-based intervention with financial incentives and text-based nudges was feasible, highly accepted, and increased daily steps in LT candidates with functional impairment and malnutrition.

Testing an insurance-based monetary incentive program for exercise: RCT design and rationale

Participation in regular physical activity (PA) has numerous health benefits; however, as few as 10% of U.S. adults meet guidelines when device-based assessments of PA are used. The present paper presents the design and rationale for an RCT examining the efficacy of an exercise incentive program currently offered by at least three major US insurance companies, in which participants must attend a YMCA fitness facility at least 50 times within 6 months to receive an incentive. In a factorial design, incentive amount ($200, $100, $0) is crossed with a comparison of the standard gain-framed incentive program and a loss-framed incentive condition in which participants are told their membership fee is being held and will be returned or forfeited depending on their fitness facility attendance. Participants (N = 330) are randomized to gain-framed $100 incentive (n = 55), gain-framed $200 incentive (n = 55), loss-framed $100 incentive (n = 55), loss-framed $200 incentive (n = 55), or control (n = 110). Each participant is enrolled in the same condition for two consecutive 6-month periods for a total of 12 months per participant. The primary outcome is number of visits to the fitness facility over each 6-month period, verified by objective swipe-card data. Secondary outcomes include total moderate-to-vigorous PA (MVPA) over 7-day periods assessed at 3-month intervals through accelerometers (Actigraph wGT3x-BT) and self-report. Habit formation and anticipated regret are putative mediators and household income is a putative moderator of the incentive-based programs. A payer-perspective, within-trial cost-utility analysis will quantify the incremental costs per (a) quality-adjusted life year gained, (b) YMCA attendance, and (c) change in MVPA.

Remote Patient-Reported Outcomes and Activity Monitoring to Improve Patient-Clinician Communication Regarding Symptoms and Functional Status: A Randomized Controlled Trial

PURPOSE

Routine collection of patient-generated health data (PGHD) may promote earlier recognition of symptomatic and functional decline. This trial assessed the impact of an intervention integrating remote PGHD collection with patient nudges on symptom and functional status understanding between patients with advanced cancer and their oncology team.

METHODS

This three-arm randomized controlled trial was conducted from November 19, 2020, to December 17, 2021, at a large tertiary oncology practice. We enrolled patients with stage IV GI and lung cancers undergoing chemotherapy. Over 6 months, patients in two intervention arms received PROStep-weekly text message-based symptom surveys and passive activity monitoring using a wearable accelerometer. PGHD were summarized in dashboards given to patients' oncology team before appointments. One intervention arm received an additional text-based active choice prompt to discuss worsening symptoms or functional status with their clinician. Control patients did not receive PROStep. The coprimary outcomes patient perceptions of oncology team symptom and functional understanding at 6 months were measured on a 1-5 Likert scale (5 = high understanding).

RESULTS

One hundred eight patients enrolled: 55% male, 81% White, and 77% had GI cancers. Patient-reported clinician understanding did not differ between control and intervention arms for symptoms (4.5 v 4.5; P = .87) or functional status (4.5 v 4.3; P = .31). In the intervention arms, combined patient adherence to weekly symptom reports and daily activity monitoring was 64% and 53%, respectively. Intervention patients in the PROStep versus PROStep + active choice arms reported low burden from wearing the accelerometer (mean burden [standard deviation], 2.7 [1.3] v 2.1 [1.3]; P = .15) and completing surveys (2.1 [1.2] v 1.9 [1.3]; P = .44).

CONCLUSION

Patients receiving PROStep reported high understanding of symptoms and functional status from their oncology team, although this did not differ from controls.

Benefits and Harms of Digital Health Interventions Promoting Physical Activity in People With Chronic Conditions: Systematic Review and Meta-Analysis

BACKGROUND

Digital health interventions for managing chronic conditions have great potential. However, the benefits and harms are still unclear.

OBJECTIVE

This systematic review and meta-analysis aimed to investigate the benefits and harms of digital health interventions in promoting physical activity in people with chronic conditions.

METHODS

We searched the MEDLINE, Embase, CINAHL, and Cochrane Central Register of Controlled Trials databases from inception to October 2022. Eligible randomized controlled trials were included if they used a digital component in physical activity promotion in adults with ≥1 of the following conditions: depression or anxiety, ischemic heart disease or heart failure, chronic obstructive pulmonary disease, knee or hip osteoarthritis, hypertension, or type 2 diabetes. The primary outcomes were objectively measured physical activity and physical function (eg, walk or step tests). We used a random effects model (restricted maximum likelihood) for meta-analyses and meta-regression analyses to assess the impact of study-level covariates. The risk of bias was assessed using the Cochrane Risk of Bias 2 tool, and the certainty of the evidence was assessed using the Grading of Recommendations Assessment, Development, and Evaluation.

RESULTS

Of 14,078 hits, 130 randomized controlled trials were included. Compared with usual care or minimal intervention, digital health interventions increased objectively measured physical activity (end of intervention: standardized mean difference [SMD] 0.29, 95% CI 0.21-0.37; follow-up: SMD 0.17, 95% CI 0.04-0.31) and physical function (end of intervention: SMD 0.36, 95% CI 0.12-0.59; follow-up: SMD 0.29, 95% CI 0.01-0.57). The secondary outcomes also favored the digital health interventions for subjectively measured physical activity and physical function, depression, anxiety, and health-related quality of life at the end of the intervention but only subjectively measured physical activity at follow-up. The risk of nonserious adverse events, but not serious adverse events, was higher in the digital health interventions at the end of the intervention, but no difference was seen at follow-up.

CONCLUSIONS

Digital health interventions improved physical activity and physical function across various chronic conditions. Effects on depression, anxiety, and health-related quality of life were only observed at the end of the intervention. The risk of nonserious adverse events is present during the intervention, which should be addressed. Future studies should focus on better reporting, comparing the effects of different digital health solutions, and investigating how intervention effects are sustained beyond the end of the intervention.

TRIAL REGISTRATION

PROSPERO CRD42020189028; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=189028.

A Randomized Trial of Incentivization to Maximize Retention for Real-Time Symptom and Activity Monitoring Using Ecological Momentary Assessment in Pediatric Concussion

OBJECTIVE

The aims of this study were to determine the incentivization strategy that maximizes patient adherence to report symptoms and activity via ecological momentary assessment (EMA) after pediatric concussion, and assess the feasibility of tracking concussed youth using EMA from the emergency department (ED) setting.

METHODS

This study was a randomized controlled trial of participants ages 13 to 18 years with concussion presenting to an urban, academic pediatric ED within 5 days of injury. Participants were randomized to 1 of 4 incentive arms: 2 dynamic (loss-based and streak) and 2 control flat-rate (monetary and electronic device). Participants reported symptoms 3 times per day and cognitive activity once each evening for 3 weeks. Physical activity (step count) and sleep were monitored using a Fitbit (kept by participants in the device flat-rate arm). The primary outcome was proportion of prompts to which participants responded. Secondary outcomes included differential response rates by demographics, and comparison of outcome determination between EMA and subsequent clinical visits.

RESULTS

Thirty participants were enrolled, with a median age of 15.5 years and 60% female. Median cumulative proportion of prompts responded to was 68.3% (interquartile range, 47.6%-82.5%) in the dynamic arms versus 54.0% (interquartile range. 20.6%-68.3%) in the flat-rate arms, P = 0.065. There were nonsignificant differences in median response by sex (65.9% for female vs 40.0% for male, P = 0.072), race/ethnicity (61.9% for non-Hispanic White vs 43.7% for non-Hispanic Black participants, P = 0.097), and insurance (61.9% for private insurance vs 47.6% for public insurance, P = 0.305). Recovery at 3 weeks was discernible for all but 2 participants (93.3%) using EMA data, compared with only 9 participants (30.0%) ( P < 0.001) from clinical visits.

CONCLUSIONS

Dynamic incentivization showed higher rates of response to tridaily symptom prompts compared with flat-rate incentivization. These data show tracking concussed youth using EMA from the ED is feasible using a dynamic incentivization strategy, with improved ability to discern outcomes compared with prospective monitoring using follow-up clinical visits.

A randomized controlled trial of gamification, financial incentives, or both to increase physical activity among patients with elevated risk for cardiovascular disease: rationale and design of the be active study

BACKGROUND

Higher levels of physical activity are associated with improvements in cardiovascular health, and consensus guidelines recommend that individuals with or at risk for atherosclerotic cardiovascular disease (ASCVD) participate in regular physical activity. However, most adults do not achieve recommended levels of physical activity. Concepts from behavioral economics have been used to design scalable interventions that increase physical activity over short time periods, but the longer-term efficacy of these strategies is uncertain.

STUDY DESIGN AND OBJECTIVES

BE ACTIVE (NCT03911141) is a pragmatic, virtual, randomized controlled trial designed to evaluate the effectiveness of 3 strategies informed by behavioral economic concepts to increase daily physical activity in patients with established ASCVD or 10-year ASCVD risk > 7.5% who are seen in primary care and cardiology clinics affiliated with the University of Pennsylvania Health System. Patients are contacted by email or text message, and complete enrollment and informed consent on the Penn Way to Health online platform. Patients are then provided with a wearable fitness tracker, establish a baseline daily step count, set a goal to increase daily step count by 33% to 50%, and are randomized 1:2:2:2 to control, gamification, financial incentives, or both gamification and financial incentives. Interventions continue for 12 months, with follow-up for an additional 6 months to evaluate the durability of behavior change. The trial has met its enrollment goal of 1050 participants, with a primary endpoint of change from baseline in daily steps over the 12-month intervention period. Key secondary endpoints include change from baseline in daily steps over the 6-month post-intervention follow-up period and change in moderate to vigorous physical activity over the intervention and follow-up periods. If the interventions prove effective, their effects on life expectancy will be compared with their costs in cost-effectiveness analysis.

CONCLUSIONS

BE ACTIVE is a virtual, pragmatic randomized clinical trial powered to demonstrate whether gamification, financial incentives, or both are superior to attention control in increasing physical activity. Its results will have important implications for strategies to promote physical activity in patients with or at risk for ASCVD, as well as for the design and implementation of pragmatic virtual clinical trials within health systems.

Role of wearable devices in cardiac telerehabilitation: A scoping review

BACKGROUND

Cardiac rehabilitation (CR) is an evidence-based comprehensive program that includes exercise training, health education, physical activity promotion, and extensive counseling for the management of cardiovascular risk factors. Wearable devices monitor certain physiological functions, providing biometric data such as heart rate, movement, sleep, ECG analysis, blood pressure, energy expenditure, and numerous other parameters. Recent evidence supports wearable devices as a likely relevant component in cardiovascular risk assessment and disease prevention. The purpose of this scoping review is to better understand the role of wearable devices in home-based CR (HBCR) and to characterize the evidence regarding the incorporation of wearable devices in HBCR programs and cardiovascular outcomes.

METHODS & FINDINGS

We created a search strategy for multiple databases, including PubMed, Embase (Elsevier), CINAHL (Ebsco), Cochrane CENTRAL (Wiley), and Scopus (Elsevier). Studies were included if the patients were eligible for CR per Medicare guidelines and >18 years of age and if some type of wearable device was utilized during HBCR. Our search yielded 57 studies meeting all criteria. The studies were classified into 4 groups: patients with coronary heart disease (CHD) without heart failure (HF); patients with HF; patients with heart valve repair or replacement; and patients with exposure to center-based CR. In three groups, there was an upward trend toward improvement in quality of life (QOL) and peak VO2, less sedentary time, and an increase in daily step count in the intervention groups compared to control groups.

CONCLUSIONS

HBCR using wearable devices can be a comparable alternative or adjunct to center-based CR for patients with CHD and HF. More studies are needed to draw conclusions about the comparability of HBCR to center-based CR in patients with heart valve repair or replacement.

Using remotely monitored patient activity patterns after hospital discharge to predict 30 day hospital readmission: a randomized trial

Hospital readmission prediction models often perform poorly, but most only use information collected until the time of hospital discharge. In this clinical trial, we randomly assigned 500 patients discharged from hospital to home to use either a smartphone or wearable device to collect and transmit remote patient monitoring (RPM) data on activity patterns after hospital discharge. Analyses were conducted at the patient-day level using discrete-time survival analysis. Each arm was split into training and testing folds. The training set used fivefold cross-validation and then final model results are from predictions on the test set. A standard model comprised data collected up to the time of discharge including demographics, comorbidities, hospital length of stay, and vitals prior to discharge. An enhanced model consisted of the standard model plus RPM data. Traditional parametric regression models (logit and lasso) were compared to nonparametric machine learning approaches (random forest, gradient boosting, and ensemble). The main outcome was hospital readmission or death within 30 days of discharge. Prediction of 30-day hospital readmission significantly improved when including remotely-monitored patient data on activity patterns after hospital discharge and using nonparametric machine learning approaches. Wearables slightly outperformed smartphones but both had good prediction of 30-day hospital-readmission.

Smartphone-based gamification intervention to increase physical activity participation among patients with coronary heart disease: A randomized controlled trial

INTRODUCTION

Despite proven benefits, patients with coronary heart disease (CHD) typically fail to participate in sufficient physical activity (PA). Effective interventions should be implemented to help patients maintain a healthy lifestyle and modify their present behavior. Gamification is the use of game design features (such as points, leaderboards, and progress bars) to improve motivation and engagement. It shows the potential for encouraging patients to engage in PA. However, empirical evidence on the efficacy of such interventions among patients with CHD is still emerging.

PURPOSE

The aim of the study is to explore whether a smartphone-based gamification intervention could increase PA participation and other physical and psychological outcomes in CHD patients.

METHODS

Participants with CHD were randomly assigned to three groups (control group, individual group, and team group). The individual and team groups received gamified behavior intervention based on behavioral economics. The team group combined gamified intervention with social interaction. The intervention lasted for 12 weeks, and the follow-up was12 weeks. The primary outcomes included the change in daily steps and the proportion of patient days that step goals were achieved. The secondary outcomes included competence, autonomy, relatedness, and autonomous motivation.

RESULTS

For the individual group, smartphone-based gamification intervention significantly increased PA among CHD patients over the 12-week period (step count difference 988; 95% CI 259-1717; p < 0.01) and had a good maintenance effect during the follow-up period (step count difference 819; 95% CI 24-1613; p < 0.01). There are also significant differences in competence, autonomous motivation, body mass index (BMI), and waist circumference in 12 weeks between the control group and individual group. For the team group, gamification intervention with collaboration didn't result in significant increases in PA. But patients in this group had a significant increase in competence, relatedness, and autonomous motivation.

CONCLUSION

A smartphone-based gamification intervention was proven to be an effective way to increase motivation and PA engagement, with a substantial maintenance impact (Chinese Clinical Trial Registry Identifier: ChiCTR2100044879).

The Effectiveness of Wearable Devices in Non-Communicable Diseases to Manage Physical Activity and Nutrition: Where We Are?

Wearable devices are increasingly popular in clinical and non-clinical populations as a tool for exercise prescription, monitoring of daily physical activity and nutrition, and health-related parameters management. In this regard, smart devices not only assist people in pursuing a healthier lifestyle, but also provide a constant stream of physiological and metabolic data for management of non-communicable diseases (NCDs). Although the benefits of lifestyle-based interventions (exercise and nutrition) for NCDs are well known, the potential of wearable devices to promote healthy behaviors in clinical populations is still controversial. In this narrative review, we aimed to discuss the current application of wearable devices in NCDs, highlighting their role in prescribing and monitoring daily physical activity and dietary habits in the population living with chronic diseases. None of the studies considered specifically addressed the efficacy of the use of wearable devices, and limited are those that incorporate monitoring of both physical activity and nutrition for NCDs. However, there is evidence that such devices have helped improve physical activity levels, physical fitness, body composition, and metabolic and psychological parameters. Therefore, the authors believe that the benefits obtained from the use of wearable devices are likely to translate to public health and represent one of the important tools for the development of prevention plans in everyday life and clinical practice for optimal patient management.

Effects of Loss and Gain Incentives on Adherence in Pediatric Weight Management: Preliminary Studies and Economic Evaluation of a Theoretical Trial

Pediatric weight management is often hampered by poor engagement and adherence. Incentives based on loss have been shown to be more effective than gain-based incentives in improving outcomes among children with health conditions other than obesity. In preparation for a clinical trial comparing loss-framed to gain-framed incentives, a survey of youth and caregiver attitudes on weight management incentives, reasons for program attendance, and an economic evaluation of a theoretical trial were conducted. Ninety of 835 (11%) surveys were completed by caregiver and child. The economic evaluation showed that loss-framed incentives had a preferable incremental cost-effectiveness ratio (a lower value is considered preferable) than gain-based incentives. Most youth and caregivers felt a gain incentive would be superior, agreed that the full incentive should go to the youth (vs. the caregiver), and identified "improving health" as a top reason for pursuing weight management.

Study design of BETTER-BP: Behavioral economics trial to enhance regulation of blood pressure

Background

Nonadherence to antihypertensive medications remains a persistent problem that leads to preventable morbidity and mortality. Behavioral economic strategies represent a novel way to improve antihypertensive medication adherence, but remain largely untested especially in vulnerable populations which stand to benefit the most. The Behavioral Economics Trial To Enhance Regulation of Blood Pressure (BETTER-BP) was designed in this context, to test whether a digitally-enabled incentive lottery improves antihypertensive adherence and reduces systolic blood pressure (SBP).

Design

BETTER-BP is a pragmatic randomized trial conducted within 3 safety-net clinics in New York City: Bellevue Hospital Center, Gouveneur Hospital Center, and NYU Family Health Centers - Park Slope. The trial will randomize 435 patients with poorly controlled hypertension and poor adherence (<80% days adherent) in a 2:1 ratio (intervention:control) to receive either an incentive lottery versus passive monitoring. The incentive lottery is delivered via short messaging service (SMS) text messages that are delivered based on (1) antihypertensive adherence tracked via a wireless electronic monitoring device, paired with (2) a probability of lottery winning with variable incentives and a regret component for nonadherence. The study intervention lasts for 6 months, and ambulatory systolic blood pressure (SBP) will be measured at both 6 and 12 months to evaluate immediate and durable lottery effects.

Conclusions

BETTER-BP will generate knowledge about whether an incentive lottery is effective in vulnerable populations to improve antihypertensive medication adherence. If successful, this could lead to the implementation of this novel strategy on a larger scale to improve outcomes.

Comparison of Participation in Strength Activity Between Wearable Device Users and Nonusers: 2017 Behavioral Risk Factors Surveillance System

BACKGROUND

There are many benefits associated with engaging in strength physical activity. Many studies did not examine the engagement of strength activity among wearable device users. This study aimed to examine the association between wearable device usage and engagement of strength activity in free-living settings using nationally representative data.

METHODS

A total of 8250 adult wearable device users and nonusers from 8 states of the 2017 Behavioral Risk Factors Surveillance System were included in analysis. Multiple regression models were performed to determine the association between the dependent variables of strength activities and the independent variable of wearable devices.

RESULTS

Wearable device users were 1.26 (95% confidence interval, 1.01-1.81) times the odds of nonusers in engaging in strength activity. Users also had higher odds of meeting both the strength and aerobic physical activity guidelines than nonusers (odds ratio = 1.49; 95% confidence interval, 1.07-2.06; adjusted odds ratio = 1.43; 95% confidence interval, 1.02-2.00). No associations were found between wearable device utilization and frequency of strength activity per week.

CONCLUSION

Wearable device users were more likely to engage in strength activity than nonusers. However, additional studies are needed to determine the effectiveness of wearable devices in promoting strength activity.

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

Objective

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

Design

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

Data sources

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

Eligibility criteria

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

Data extraction and synthesis

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

Results

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

Conclusion

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

PROSPERO registered number

CRD42020199482.

Patient and clinician nudges to improve symptom management in advanced cancer using patient-generated health data: study protocol for the PROStep randomised controlled trial

INTRODUCTION

Patients with advanced cancers often face significant symptoms from their cancer and adverse effects from cancer-associated therapy. Patient-generated health data (PGHD) are routinely collected information about symptoms and activity levels that patients either directly report or passively record using devices such as wearable accelerometers. The objective of this study was to test the impact of an intervention integrating remote collection of PGHD with clinician and patient nudges to inform communication between patients with advanced cancer and their oncology team regarding symptom burden and functional status.

METHODS AND ANALYSIS

This single-centre prospective randomised controlled trial randomises patients with metastatic gastrointestinal or lung cancers into one of three arms: (A) usual care, (B) an intervention that integrates PGHD (including weekly text-based symptom surveys and passively recorded step counts) into a dashboard delivered to oncology clinicians at each visit and (C) the same intervention as arm B but with an additional text-based active choice intervention to patients to encourage discussing their symptoms with their oncology team. The study will enrol approximately 125 participants. The coprimary outcomes are patient perceptions of their oncology team's understanding of their symptoms and their functional status. Secondary outcomes are intervention utility and adherence.

ETHICS AND DISSEMINATION

This study has been approved by the institutional review board at the University of Pennsylvania. Study results will be disseminated using methods that describe the results in ways that key stakeholders can best understand and implement.

TRIAL REGISTRATION NUMBERS

NCT04616768 and 843 616.

Wearable Devices for Physical Monitoring of Heart: A Review

Cardiovascular diseases (CVDs) are the leading cause of death globally. An effective strategy to mitigate the burden of CVDs has been to monitor patients' biomedical variables during daily activities with wearable technology. Nowadays, technological advance has contributed to wearables technology by reducing the size of the devices, improving the accuracy of sensing biomedical variables to be devices with relatively low energy consumption that can manage security and privacy of the patient's medical information, have adaptability to any data storage system, and have reasonable costs with regard to the traditional scheme where the patient must go to a hospital for an electrocardiogram, thus contributing a serious option in diagnosis and treatment of CVDs. In this work, we review commercial and noncommercial wearable devices used to monitor CVD biomedical variables. Our main findings revealed that commercial wearables usually include smart wristbands, patches, and smartwatches, and they generally monitor variables such as heart rate, blood oxygen saturation, and electrocardiogram data. Noncommercial wearables focus on monitoring electrocardiogram and photoplethysmography data, and they mostly include accelerometers and smartwatches for detecting atrial fibrillation and heart failure. However, using wearable devices without healthy personal habits will cause disappointing results in the patient's health.

Exploring Wearables to Focus on the “Sweet Spot” of Physical Activity and Sleep After Hospitalization: Secondary Analysis

Background

Inadequate sleep and physical activity are common during and after hospitalization, but their impact on patient-reported functional outcomes after discharge is poorly understood. Wearable devices that measure sleep and activity can provide patient-generated data to explore ideal levels of sleep and activity to promote recovery after hospital discharge.

Objective

This study aimed to examine the relationship between daily sleep and physical activity with 6 patient-reported functional outcomes (symptom burden, sleep quality, physical health, life space mobility, activities of daily living, and instrumental activities of daily living) at 13 weeks after hospital discharge.

Methods

This secondary analysis sought to examine the relationship between daily sleep, physical activity, and patient-reported outcomes at 13 weeks after hospital discharge. We utilized wearable sleep and activity trackers (Withings Activité wristwatch) to collect data on sleep and activity. We performed descriptive analysis of device-recorded sleep (minutes/night) with patient-reported sleep and device-recorded activity (steps/day) for the entire sample with full data to explore trends. Based on these trends, we performed additional analyses for a subgroup of patients who slept 7-9 hours/night on average. Differences in patient-reported functional outcomes at 13 weeks following hospital discharge were examined using a multivariate linear regression model for this subgroup.

Results

For the full sample of 120 participants, we observed a “T-shaped” distribution between device-reported physical activity (steps/day) and sleep (patient-reported quality or device-recorded minutes/night) with lowest physical activity among those who slept <7 or >9 hours/night. We also performed a subgroup analysis (n=60) of participants that averaged the recommended 7-9 hours of sleep/night over the 13-week study period. Our key finding was that participants who had both adequate sleep (7-9 hours/night) and activity (>5000 steps/day) had better functional outcomes at 13 weeks after hospital discharge. Participants with adequate sleep but less activity (<5000 steps/day) had significantly worse symptom burden (z-score 0.93, 95% CI 0.3 to 1.5; P=.02), community mobility (z-score –0.77, 95% CI –1.3 to –0.15; P=.02), and perceived physical health (z-score –0.73, 95% CI –1.3 to –0.13; P=.003), compared with those who were more physically active (≥5000 steps/day).

Conclusions

Participants within the “sweet spot” that balances recommended sleep (7-9 hours/night) and physical activity (>5000 steps/day) reported better functional outcomes after 13 weeks compared with participants outside the “sweet spot.” Wearable sleep and activity trackers may provide opportunities to hone postdischarge monitoring and target a “sweet spot” of recommended levels for both sleep and activity needed for optimal recovery.

Trial Registration

ClinicalTrials.gov NCT03321279; https://clinicaltrials.gov/ct2/show/NCT03321279

Mobile health-based gamification intervention to increase physical activity participation among patients with coronary heart disease: study protocol of a randomised controlled trial

INTRODUCTION

Despite proven benefits, physical activity participation remains low in patients with coronary heart disease (CHD). Scientific evidence suggests that mobile health (mHealth)-based gamification interventions could increase physical activity levels. However, several systematic reviews demonstrated that most gamification intervention designs do not appropriately leverage theories from health behaviour models, and empirical evidence on the efficacy of such interventions among patients with CHD is still emerging. This study embeds the principles of behavioural economics into a gamification intervention based on a smartphone app (WeChat applet) to explore whether a mHealth-based gamification intervention can improve participation in physical activity and other related physical and psychological outcomes in patients with CHD.

METHODS

We propose a single-blinded three-arm randomised controlled trial with 108 patients with CHD, who will be randomly divided into three groups (Control group: WeChat applet+step goal setting; Individual group: WeChat applet+step goal setting+gamification; Team group: WeChat applet+step goal setting+gamification+collaboration). The interventions will last for 12 weeks and follow-up for 12 weeks. All patients will receive only WeChat applet-based step goal setting in the follow-up period. The primary outcome is physical activity participation, which includes a change in daily steps and self-reported physical activity from the baseline to 12 and 24 weeks, and the proportion of patient-days that step goals achieved in 12 and 24 weeks. The secondary outcomes include biomedical and lifestyle-related risk factors, intrinsic motivation, enjoyment, competence, autonomy and relatedness, social support and mental health and patients' satisfaction, perceptions and intervention experience.

ETHICS AND DISSEMINATION

The Human Research Ethics Committee of the School of Nursing, Jilin University (HREC 2020122401) approved this. The results will be published in peer-reviewed journals and presented at conferences.

TRIAL REGISTRATION NUMBER

ChiCTR2100044879; Pre-results.

OUP accepted manuscript

The increasing volume and richness of healthcare data collected during routine clinical practice have not yet translated into significant numbers of actionable insights that have systematically improved patient outcomes. An evidence-practice gap continues to exist in healthcare. We contest that this gap can be reduced by assessing the use of nudge theory as part of clinical decision support systems (CDSS). Deploying nudges to modify clinician behaviour and improve adherence to guideline-directed therapy represents an underused tool in bridging the evidence-practice gap. In conjunction with electronic health records (EHRs) and newer devices including artificial intelligence algorithms that are increasingly integrated within learning health systems, nudges such as CDSS alerts should be iteratively tested for all stakeholders involved in health decision-making: clinicians, researchers, and patients alike. Not only could they improve the implementation of known evidence, but the true value of nudging could lie in areas where traditional randomized controlled trials are lacking, and where clinical equipoise and variation dominate. The opportunity to test CDSS nudge alerts and their ability to standardize behaviour in the face of uncertainty may generate novel insights and improve patient outcomes in areas of clinical practice currently without a robust evidence base.

Exercise-based cardiac rehabilitation for coronary heart disease

BACKGROUND

Coronary heart disease (CHD) is the most common cause of death globally. However, with falling CHD mortality rates, an increasing number of people living with CHD may need support to manage their symptoms and prognosis. Exercise-based cardiac rehabilitation (CR) aims to improve the health and outcomes of people with CHD. This is an update of a Cochrane Review previously published in 2016.

OBJECTIVES

To assess the clinical effectiveness and cost-effectiveness of exercise-based CR (exercise training alone or in combination with psychosocial or educational interventions) compared with 'no exercise' control, on mortality, morbidity and health-related quality of life (HRQoL) in people with CHD.

SEARCH METHODS

We updated searches from the previous Cochrane Review, by searching CENTRAL, MEDLINE, Embase, and two other databases in September 2020. We also searched two clinical trials registers in June 2021.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) of exercise-based interventions with at least six months' follow-up, compared with 'no exercise' control. The study population comprised adult men and women who have had a myocardial infarction (MI), coronary artery bypass graft (CABG) or percutaneous coronary intervention (PCI), or have angina pectoris, or coronary artery disease.

DATA COLLECTION AND ANALYSIS

We screened all identified references, extracted data and assessed risk of bias according to Cochrane methods. We stratified meta-analysis by duration of follow-up: short-term (6 to 12 months); medium-term (> 12 to 36 months); and long-term ( > 3 years), and used meta-regression to explore potential treatment effect modifiers. We used GRADE for primary outcomes at 6 to 12 months (the most common follow-up time point).  MAIN RESULTS: This review included 85 trials which randomised 23,430 people with CHD. This latest update identified 22 new trials (7795 participants). The population included predominantly post-MI and post-revascularisation patients, with a mean age ranging from 47 to 77 years. In the last decade, the median percentage of women with CHD has increased from 11% to 17%, but females still account for a similarly small percentage of participants recruited overall ( < 15%). Twenty-one of the included trials were performed in low- and middle-income countries (LMICs). Overall trial reporting was poor, although there was evidence of an improvement in quality over the last decade. The median longest follow-up time was 12 months (range 6 months to 19 years). At short-term follow-up (6 to 12 months), exercise-based CR likely results in a slight reduction in all-cause mortality (risk ratio (RR) 0.87, 95% confidence interval (CI) 0.73 to 1.04; 25 trials; moderate certainty evidence), a large reduction in MI (RR 0.72, 95% CI 0.55 to 0.93; 22 trials; number needed to treat for an additional beneficial outcome (NNTB) 75, 95% CI 47 to 298; high certainty evidence), and a large reduction in all-cause hospitalisation (RR 0.58, 95% CI 0.43 to 0.77; 14 trials;  NNTB 12, 95% CI 9 to 21; moderate certainty evidence). Exercise-based CR likely results in little to no difference in risk of cardiovascular mortality (RR 0.88, 95% CI 0.68 to 1.14; 15 trials; moderate certainty evidence), CABG (RR 0.99, 95% CI 0.78 to 1.27; 20 trials; high certainty evidence), and PCI (RR 0.86, 95% CI 0.63 to 1.19; 13 trials; moderate certainty evidence) up to 12 months' follow-up. We are uncertain about the effects of exercise-based CR on cardiovascular hospitalisation, with a wide confidence interval including considerable benefit as well as harm (RR 0.80, 95% CI 0.41 to 1.59; low certainty evidence). There was evidence of substantial heterogeneity across trials for cardiovascular hospitalisations (I2 = 53%), and of small study bias for all-cause hospitalisation, but not for all other outcomes. At medium-term follow-up, although there may be little to no difference in all-cause mortality (RR 0.90, 95% CI 0.80 to 1.02; 15 trials), MI (RR 1.07, 95% CI 0.91 to 1.27; 12 trials), PCI (RR 0.96, 95% CI 0.69 to 1.35; 6 trials), CABG (RR 0.97, 95% CI 0.77 to 1.23; 9 trials), and all-cause hospitalisation (RR 0.92, 95% CI 0.82 to 1.03; 9 trials), a large reduction in cardiovascular mortality was found (RR 0.77, 95% CI 0.63 to 0.93; 5 trials). Evidence is uncertain for difference in risk of cardiovascular hospitalisation (RR 0.92, 95% CI 0.76 to 1.12; 3 trials). At long-term follow-up, although there may be little to no difference in all-cause mortality (RR 0.91, 95% CI 0.75 to 1.10), exercise-based CR may result in a large reduction in cardiovascular mortality (RR 0.58, 95% CI 0.43 to 0.78; 8 trials) and MI (RR 0.67, 95% CI 0.50 to 0.90; 10 trials). Evidence is uncertain for CABG (RR 0.66, 95% CI 0.34 to 1.27; 4 trials), and PCI (RR 0.76, 95% CI 0.48 to 1.20; 3 trials). Meta-regression showed benefits in outcomes were independent of CHD case mix, type of CR, exercise dose, follow-up length, publication year, CR setting, study location, sample size or risk of bias. There was evidence that exercise-based CR may slightly increase HRQoL across several subscales (SF-36 mental component, physical functioning, physical performance, general health, vitality, social functioning and mental health scores) up to 12 months' follow-up; however, these may not be clinically important differences. The eight trial-based economic evaluation studies showed exercise-based CR to be a potentially cost-effective use of resources in terms of gain in quality-adjusted life years (QALYs).

AUTHORS' CONCLUSIONS

This updated Cochrane Review supports the conclusions of the previous version, that exercise-based CR provides important benefits to people with CHD, including reduced risk of MI, a likely small reduction in all-cause mortality, and a large reduction in all-cause hospitalisation, along with associated healthcare costs, and improved HRQoL up to 12 months' follow-up. Over longer-term follow-up, benefits may include reductions in cardiovascular mortality and MI. In the last decade, trials were more likely to include females, and be undertaken in LMICs, increasing the generalisability of findings. Well-designed, adequately-reported RCTs of CR in people with CHD more representative of usual clinical practice are still needed. Trials should explicitly report clinical outcomes, including mortality and hospital admissions, and include validated HRQoL outcome measures, especially over longer-term follow-up, and assess costs and cost-effectiveness.

Association between behavioral phenotypes and sustained use of smartphones and wearable devices to remotely monitor physical activity

Smartphones and wearable devices can be used to remotely monitor health behaviors, but little is known about how individual characteristics influence sustained use of these devices. Leveraging data on baseline activity levels and demographic, behavioral, and psychosocial traits, we used latent class analysis to identify behavioral phenotypes among participants randomized to track physical activity using a smartphone or wearable device for 6 months following hospital discharge. Four phenotypes were identified: (1) more agreeable and conscientious; (2) more active, social, and motivated; (3) more risk-taking and less supported; and (4) less active, social, and risk-taking. We found that duration and consistency of device use differed by phenotype for wearables, but not smartphones. Additionally, "at-risk" phenotypes 3 and 4 were more likely to discontinue use of a wearable device than a smartphone, while activity monitoring in phenotypes 1 and 2 did not differ by device type. These findings could help to better target remote-monitoring interventions for hospitalized patients.

The Role of Behavioral Economics in Improving Cardiovascular Health Behaviors and Outcomes

PURPOSE OF REVIEW

Behavioral economics represents a promising set of principles to inform the design of health-promoting interventions. Techniques from the field have the potential to increase quality of cardiovascular care given suboptimal rates of guideline-directed care delivery and patient adherence to optimal health behaviors across the spectrum of cardiovascular care delivery.

RECENT FINDINGS

Cardiovascular health-promoting interventions have demonstrated success in using a wide array of principles from behavioral economics, including loss framing, social norms, and gamification. Such approaches are becoming increasingly sophisticated and focused on clinical cardiovascular outcomes in addition to health behaviors as a primary endpoint. Many approaches can be used to improve patient decisions remotely, which is particularly useful given the shift to virtual care in the context of the COVID-19 pandemic. Numerous applications for behavioral economics exist in the cardiovascular care delivery space, though more work is needed before we will have a full understanding of ways to best leverage such applications in each clinical context.

Effect of Goal-Setting Approaches Within a Gamification Intervention to Increase Physical Activity Among Economically Disadvantaged Adults at Elevated Risk for Major Adverse Cardiovascular Events: The ENGAGE Randomized Clinical Trial

Importance

Health promotion efforts commonly communicate goals for healthy behavior, but the best way to design goal setting among high-risk patients has not been well examined.

Objective

To test the effectiveness of different ways to set and implement goals within a behaviorally designed gamification intervention to increase physical activity.

Design, Setting, and Participants

Evaluation of the Novel Use of Gamification With Alternative Goal-setting Experiences was conducted from January 15, 2019, to June 1, 2020. The 24-week randomized clinical trial included a remotely monitored 8-week introductory intervention period, 8-week maintenance intervention period, and 8-week follow-up period. A total of 500 adults from lower-income neighborhoods in and around Philadelphia, Pennsylvania, who had either an atherosclerotic cardiovascular disease (ASCVD) condition or a 10-year ASCVD risk score greater than or equal to 7.5% were enrolled. Participants were paid for enrolling in and completing the trial.

Interventions

All participants used a wearable device to track daily steps, established a baseline level, and were then randomly assigned to an attention control or 1 of 4 gamification interventions that varied only on how daily step goals were set (self-chosen or assigned) and implemented (immediately or gradually).

Main Outcome Measures

The primary outcome was change in mean daily steps from baseline to the 8-week maintenance intervention period. Other outcomes included changes in minutes of moderate to vigorous physical activity. All randomly assigned participants were included in the intention-to-treat analysis.

Results

Of the 500 participants, 331 individuals (66.2%) were Black, 114 were White (22.8%), and 348 were women (69.6%). Mean (SD) age was 58.5 (10.8) years and body mass index was 33.2 (7.8). A total of 215 participants (43.0%) had an ASCVD condition. Compared with the control arm, participants with self-chosen and immediate goals had significant increases in the number of daily steps during the maintenance intervention period (1384; 95% CI, 805-1963; P < .001) that were sustained during the 8-week follow-up (1391; 95% CI, 785-1998; P < .001). This group also had significant increases in daily minutes of moderate to vigorous physical activity during the maintenance intervention (4.1; 95% CI, 1.8-6.4; P < .001) that were sustained during follow-up (3.5; 95% CI, 1.1-5.8; P = .004). No other gamification arms had consistent increases in physical activity compared with the control arm. No major adverse events were reported.

Conclusions and Relevance

In this trial among economically disadvantaged adults at elevated risk for major adverse cardiovascular events, a gamification intervention led to increases in physical activity that were sustained during 8 weeks of follow-up when goals were self-chosen and implemented immediately.

Trial Registration

ClinicalTrials.gov Identifier: NCT03749473.

Effect of Gamification With and Without Financial Incentives to Increase Physical Activity Among Veterans Classified as Having Obesity or Overweight: A Randomized Clinical Trial

IMPORTANCE

Gamification is increasingly being used for health promotion but has not been well tested with financial incentives or among veterans.

OBJECTIVE

To test the effectiveness of gamification with social support, with and without a loss-framed financial incentive, to increase physical activity among veterans classified as having overweight and obesity.

DESIGN, SETTING, AND PARTICIPANTS

This 3-group randomized clinical trial had a 12-week intervention period and an 8-week follow-up period. Participants included veterans with a body mass index greater than or equal to 25 who were receiving care from a single site in Philadelphia, Pennsylvania. Participants underwent a remotely monitored intervention from March 19, 2019, to August 9, 2020. Data analyses were conducted between October 1, 2020, and November 14, 2020.

INTERVENTIONS

All participants received a wearable device to track step counts and selected a step goal. The control group received feedback from their devices only. Participants in the 2 gamification groups were entered into a 12-week game with points and levels designed using behavioral economic principles and selected a support partner to receive weekly updates. Participants in the loss-framed financial incentive group had $120 allocated to a virtual account and lost $10 if weekly goals were not achieved.

MAIN OUTCOMES AND MEASURES

The primary outcome was the change in mean daily steps from baseline during the intervention. Secondary outcomes include proportion of days goals were achieved and changes during follow-up.

RESULTS

A total of 180 participants were randomized, 60 to the gamification with social support group, 60 to the gamification with social support and loss-framed financial incentives group, and 60 to the control group. The participants had a mean (SD) age of 56.5 (12.9) years and a mean (SD) body mass index of 33.0 (5.6); 71 participants (39.4%) were women, 90 (50.0%) were White, and 67 (37.2%) were Black. During the intervention period, compared with control group participants, participants in the gamification with financial incentives group had a significant increase in mean daily steps from baseline (adjusted difference, 1224 steps; 95% CI, 451 to 1996 steps; P = .005), but participants in the gamification without financial incentives group did not (adjusted difference, 433 steps; 95% CI, -337 to 1203 steps; P = .81). The increase for the gamification with financial incentives group was not sustained during the follow-up period, and the step count was not significantly different than that of the control group (adjusted difference, 564 steps; 95% CI, -261 to 1389 steps; P = .37). Compared with the control group, participants in the intervention groups had a significantly higher adjusted proportion of days meeting their step goal during the main intervention and follow-up period (gamification with social support group, adjusted difference from control, 0.21 participant-day; 95% CI, 0.18-0.24 participant-day; P < .001; gamification with social support and loss-framed financial incentive group, adjusted difference from control, 0.34 participant-day; 95% CI, 0.31-0.37 participant-day; P < .001).

CONCLUSIONS AND RELEVANCE

Among veterans classified as having overweight and obesity, gamification with social support combined with loss-framed financial incentives was associated with a modest increase in physical activity during the intervention period, but the increase was not sustained during follow-up. Gamification without incentives did not significantly change physical activity.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT03563027.

Wearables in cardiology: Here to stay

The adoption of wearables in medicine has rapidly expanded worldwide. New generations of wearables are emerging, driven by consumers' demand to monitor their own health. With the ongoing development of new features capable of assessing real-time biometric data, the impact of wearables on cardiovascular management has become inevitable. Smartwatches, among other wearable devices, offer a user-friendly noninvasive approach to continuously monitor for health parameters. With advancements in artificial intelligence, the photoplethysmography-generated pulse waveform has the potential to accurately detect episodes of atrial fibrillation and one day could replace conventional diagnostic and long-term monitoring methods. Clinical benefits that could arise from the use of such devices include refining stroke prevention strategies, personalizing AF management, and optimizing the patient-physician relationship. Wearables are changing not only the way clinicians conduct research but also the future of cardiovascular preventive and therapeutic care. As such, wearables are here to stay.

Leveraging insights from behavioral economics to improve mobility for adults with stroke: Design and rationale of the BE Mobile clinical trial

Physical inactivity post-stroke can negatively impact long-term health outcomes and contribute to cardiovascular deconditioning, muscle loss, and increased risk for recurrent stroke. The limited number of interventions designed to improve daily physical activity post-stroke have lacked precision in step goals, are resource intensive, and difficult to scale. The purpose of the Leveraging Insights from Behavioral Economics to Improve Mobility for Adults with Stroke (BE Mobile) trial is to examine the preliminary effectiveness of a novel gamification with social incentives intervention for improving physical activity post-stroke. This trial includes adults who have experienced an ischemic or hemorrhagic stroke ≥3 months prior to the time of recruitment who are randomized to a control or gamification arm. All participants receive a Fitbit Inspire 2 wearable device to quantify daily steps and complete a 2-week baseline run-in period followed by an 8-week intervention period. All participants select a daily step goal and the gamification arm is enrolled in a game with loss-framed points and levels to help participants achieve their daily step goal. Participants in the gamification arm also select a support partner who receives weekly updates on their progress in the game. The primary outcome is change in daily steps from baseline during the intervention period. The secondary outcome is difference in the proportion of days participants achieved their daily step goal. Results from this trial will inform future, larger studies that leverage insights from behavioral economics to help improve daily physical activity post-stroke. Trial registration: NCT #04607811.

Characterisation of ICU sleep by a commercially available activity tracker and its agreement with patient-perceived sleep quality

Background

A low-cost, quantitative method to evaluate sleep in the intensive care unit (ICU) that is both feasible for routine clinical practice and reliable does not yet exist. We characterised nocturnal ICU sleep using a commercially available activity tracker and evaluated agreement between tracker-derived sleep data and patient-perceived sleep quality.

Patients and methods

A prospective cohort study was performed in a 40-bed ICU at a community teaching hospital. An activity tracker (Fitbit Charge 2) was applied for up to 7 ICU days in English-speaking adults with an anticipated ICU stay ≥2 days and without mechanical ventilation, sleep apnoea, delirium, continuous sedation, contact isolation or recent anaesthesia. The Richards-Campbell Sleep Questionnaire (RCSQ) was administered each morning by a trained investigator.

Results

Available activity tracker-derived data for each ICU study night (20:00–09:00) (total sleep time (TST), number of awakenings (#AW), and time spent light sleep, deep sleep and rapid eye movement (REM) sleep) were downloaded and analysed. Across the 232 evaluated nights (76 patients), TST and RCSQ data were available for 232 (100%), #AW data for 180 (78%) and sleep stage data for 73 (31%). Agreement between TST (349±168 min) and RCSQ Score was moderate and significant (r=0.34; 95% CI 0.18 to 0.48). Agreement between #AW (median (IQR), 4 (2–9)) and RCSQ Score was negative and non-significant (r=−0.01; 95% CI −0.19 to 0.14). Agreement between time (min) spent in light (259 (182 to 328)), deep (43±29), and REM (47 (28–72)) sleep and RCSQ Score was moderate but non-significant (light (r=0.44, 95% CI −0.05 to 0.36); deep sleep (r=0.44, 95% CI −0.11 to 0.15) and REM sleep (r=0.44; 95% CI −0.21 to 0.21)).

Conclusions

A Fitbit Charge 2 when applied to non-intubated adults in an ICU consistently collects TST data but not #AW or sleep stage data at night. The TST moderately correlates with patient-perceived sleep quality; a correlation between either #AW or sleep stages and sleep quality was not found.

Association of Behavioral Phenotypes With Changes in Sleep During a Workplace Wellness Program

PURPOSE

Examine changes in sleep duration by 3 behavioral phenotypes during a workplace wellness program with overweight and obese adults.

DESIGN

Secondary analysis of a randomized clinical trial.

SETTING

Remotely monitored intervention conducted across the United States.

SUBJECTS

553 participants with a body mass index ≥25.

INTERVENTION

Participants were randomized to 1 of 4 study arms: control, gamification with support, gamification with collaboration, and gamification with competition to increase their physical activity. All participants were issued a wrist-worn wearable device to record their daily physical activity and sleep duration.

MEASURES

The primary outcome was change in daily sleep duration from baseline during the 24 week intervention and follow-up period by study arm within behavioral phenotype class.

ANALYSIS

Linear mixed effects regression.

RESULTS

Participants who had a phenotype of less physically active and less social at baseline, in the gamification with collaboration arm, significantly increased their sleep duration during the intervention period (30.2 minutes [95% CI 6.9, 53.5], P = 0.01), compared to the control arm. There were no changes in sleep duration among participants who were more extroverted and motivated or participants who were less motivated and at-risk.

CONCLUSIONS

Changes in sleep during a physical activity intervention varied by behavioral phenotype. Behavioral phenotypes may help to precisely identify who is likely to improve sleep duration during a physical activity intervention.

Effect of Behaviorally Designed Gamification With Social Incentives on Lifestyle Modification Among Adults With Uncontrolled Diabetes: A Randomized Clinical Trial

IMPORTANCE

Gamification is increasingly being used to promote healthy behaviors. However, it has not been well tested among patients with chronic conditions and over longer durations.

OBJECTIVE

To test the effectiveness of behaviorally designed gamification interventions to enhance support, collaboration, or competition to promote physical activity and weight loss among adults with uncontrolled type 2 diabetes.

DESIGN, SETTING, AND PARTICIPANTS

A 4-arm randomized clinical trial with a 1-year intervention was conducted from January 23, 2017, to January 27, 2020, with remotely monitored intervention. Analyses were conducted between February 10 and October 6, 2020. Participants included 361 adults with type 2 diabetes with hemoglobin A1c levels greater than or equal to 8% and body mass index greater than or equal to 25.

INTERVENTIONS

All participants received a wearable device, smart weight scale, and laboratory testing. Participants in the control group received feedback from their devices but no other interventions. Participants in the gamification arms conducted goal setting and were entered into a 1-year game designed using insights from behavioral economics with points and levels for achieving step goals and weight loss targets. The game varied by trial arm to promote either support, collaboration, or competition.

MAIN OUTCOMES AND MEASURES

Co-primary outcomes included daily step count, weight, and hemoglobin A1c level. Secondary outcome was low-density lipoprotein cholesterol level. Intention-to-treat analysis was used.

RESULTS

Participants had a mean (SD) age of 52.5 (10.1) years; hemoglobin A1c level, 9.6% (1.6%); daily steps, 4632 (2523); weight, 107.4 kg (20.8 kg); and body mass index, 37.1 (6.6). Of the 361 participants, 202 (56.0%) were women, 143 (39.6%) were White, and 185 (51.2%) were Black; with 87 (24.1%) randomized to control; 92 (25.4%) randomized to gamification with support and intervention; 95 (26.3%) randomized to gamification with collaboration; and 87 (24.1%) randomized to gamification with competition. Compared with the control group over 1 year, there was a significant increase in mean daily steps from baseline among participants receiving gamification with support (adjusted difference relative to control group, 503 steps; 95% CI, 103 to 903 steps; P = .01) and competition (606 steps; 95% CI, 201 to 1011 steps; P = .003) but not collaboration (280 steps; 95% CI, -115 to 674 steps; P = .16). All trial arms had significant reductions in weight and hemoglobin A1c levels from baseline, but there were no significant differences between any of the intervention arms and the control arm. There was only 1 adverse event reported that may have been related to the trial (arthritic knee pain).

CONCLUSIONS AND RELEVANCE

Among adults with uncontrolled type 2 diabetes, a behaviorally designed gamification intervention in this randomized clinical trial significantly increased physical activity over a 1-year period when designed to enhance either support or competition but not collaboration. No differences between intervention and control groups were found for other outcomes.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT02961192.

Theory Integration for Lifestyle Behavior Change in the Digital Age: An Adaptive Decision-Making Framework

Despite the growing popularity of digital health interventions, limitations of traditional behavior change theories and a lack of theory integration hinder theory-driven behavior change applications. In this paper, we aim to review theories relevant to lifestyle behavior change from the broader psychology literature and then integrate these theories into a new theoretical framework called adaptive decision-making to address two specific problems. First, our framework represents lifestyle behaviors at two levels-one of individual daily decisions (action level) and one of larger behavioral episodes (reflection level)-to more closely match the temporal characteristics of lifestyle behaviors and their associated digital data. Second, the framework connects decision-making theories and learning theories to explain how behaviors and cognitive constructs dynamically influence each other, making it a suitable scaffold for building computational models. We map common digital intervention techniques onto the behavioral and cognitive processes in the framework and discuss possible contributions of the framework to both theory development and digital intervention design.

Effect of Behaviorally Designed Gamification With a Social Support Partner to Increase Mobility After Hospital Discharge: A Randomized Clinical Trial

IMPORTANCE

Hospitalization is associated with decreased mobility and functional decline. Behaviorally designed gamification can increase mobility in community settings but has not been tested among patients at risk for functional decline during a high-risk transition period after hospitalization.

OBJECTIVE

To test a behaviorally designed gamification intervention with a social support partner to increase patient mobility after hospital discharge.

DESIGN, SETTING, AND PARTICIPANTS

This study is a randomized clinical trial of a 12-week intervention without follow-up. Enrollment occurred from January 2018 to June 2019 at a referral hospital with a remote at-home monitoring intervention among patients living predominantly in 3 states (Pennsylvania, New Jersey, and Delaware). Participants included adult patients discharged from general medicine and oncology units to home. Data analysis was performed from October 2019 to March 2020.

INTERVENTIONS

All participants received a wearable device to track daily steps. The control group received feedback from the device but no other interventions. The intervention group entered into a 12-week game informed by behavioral economics to assign points and levels for achieving step goals and reinforced by a support partner who received updates on participant progress.

MAIN OUTCOMES AND MEASURES

The primary outcome was change in mean daily steps from baseline through the 12-week intervention. Secondary measures were change in functional status and urgent care utilization (ie, emergency department visits and hospital readmissions) within this period.

RESULTS

A total of 232 participants were enrolled in the study (118 randomized to control and 114 randomized to the intervention). Participants had a mean (SD) age of 40 (14) years, 141 (61%) were female, 101 (43%) were White, and 103 (44%) had an annual household income less than $50 000. Daily step counts increased from 3795 to 4652 steps (difference, 857 steps; 95% CI, 488 to 1224 steps) among intervention participants and increased from 3951 to 4499 steps (difference, 548 steps; 95% CI, 193 to 903 steps) among control participants. The change in mean daily step count from baseline was not significantly different for participants in the intervention group vs the control group (adjusted difference, 270 steps; 95% CI, -214 to 754 steps; P = .27). Among the subgroup of 76 participants with higher levels of social engagement, post hoc exploratory analyses showed a significant increase in mobility for intervention vs control (adjusted difference, 1125 steps; 95% CI, 409 to 1841 steps; P = .002). Fewer participants in this subgroup experienced functional decline (1 of 36 participants [4%] in the intervention group vs 5 of 40 participants [12%] in the control group) and hospital readmission at 30 days (3 of 36 participants [8%] in the intervention group vs 6 of 40 participants [15%] in the control group), but the differences were not statistically significant. There were no significant differences in these secondary outcomes for the overall sample.

CONCLUSIONS AND RELEVANCE

Gamification with social incentives did not affect mobility or functional decline in all participants, but post hoc analysis suggests positive findings for both outcomes for patients with higher social engagement.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT03321279.

Project Step: A Randomized Controlled Trial Investigating the Effects of Frequent Feedback and Contingent Incentives on Physical Activity

BACKGROUND

Financial incentives and feedback on behavior offer promise for promoting physical activity. However, evidence for the effect of each of these techniques is inadequate. The present study evaluated the effects of daily versus weekly feedback and incentives contingent on reaching a daily walking goal versus noncontingent incentives in a 2 × 2 trial.

METHODS

Participants (N = 57) had a body mass index >25 kg/m2 and were insufficiently active. Participants received a daily walking goal that adapted weekly.

RESULTS

Participants receiving daily feedback increased daily steps (P = .03) more than those receiving weekly feedback. Participants receiving contingent incentives did not significantly increase steps (P = .12) more than those receiving noncontingent incentives. A trend-level effect (P = .09) suggested that there may be an interaction such that the combination of daily feedback and contingent incentives is most effective.

CONCLUSIONS

Results indicate that feedback is an important component of remotely delivered PA interventions and that evaluating each component of low-intensity interventions may help to improve efficacy. Moreover, results indicate that possible synergistic effects of feedback and rewards should be investigated further to help optimize interventions.

The role of a clinician amid the rise of mobile health technology

Mobile health (mHealth) interventions have demonstrated promise in improving outcomes by motivating patients to adopt and maintain healthy lifestyle changes as well as improve adherence to guideline-directed medical therapy. Early results combining behavioral economic strategies with mHealth delivery have demonstrated mixed results. In reviewing these studies, we propose that the success of a mHealth intervention links more strongly with how well it connects patients back to routine clinical care, rather than its behavior modification technique in isolation. This underscores the critical role of clinician-patient partnerships in the design and delivery of such interventions, while also raising important questions regarding long-term sustainability and scalability. Further exploration of our hypothesis may increase opportunities for multidisciplinary clinical teams to connect with and engage patients using mHealth technologies in unprecedented ways.

The Age Limit Does Not Exist: A Pilot Usability Assessment of a SMS-Messaging and Smartwatch-Based Intervention for Older Adults with Depression

Current treatments for major depressive disorder are either less effective for older adults (i.e. pharmacotherapy) or are challenging to extend to community settings (i.e. psychotherapy). To improve and extend mental health treatment for older adults, our team has expanded a previously developed streamlined talk-therapy model to incorporate a technology package that includes patient-reported outcome questions (sent via SMS) and a smartwatch. The goal of this pilot study was to assess and improve the usability, usefulness, and acceptability of the technology package. We completed a pilot feasibility and usability assessment with 15 older adults. Participants demonstrated the feasibility of use of the intervention, successfully completing 99% of their assigned tasks during the pilot. Findings were used to address usability barriers in preparation for future clinical trials. Our results highlight the importance completing usability assessment and involving older adults in the intervention design process when incorporating technology into care.

Incentivizing physical activity through activity monitoring interventions in PAD - a pilot study

Background: There is ample evidence to show that supervised exercise is efficacious and cost effective for improving claudication symptoms in patients with peripheral artery disease (PAD). Home based exercise therapy can be an effective alternative to supervised exercise however, the results of this is variable depending on the level of motivation and engagement of the patient. Patients and methods: We performed a pilot study in 41 patients to determine whether a home based exercise program with the use of an activity tracking device with personalized feedback and financial incentives can increase daily activity, improve walking and sustain engagement in the exercise regimen in patients with PAD. In this randomized pilot study, the patients in the study group were fitted with an activity monitoring device and given behavioral monitoring, motivational updates and feedback regarding their exercise program. This study group was further divided in to two groups. One half of these patients in the study group were also given financial incentives if they reached their set targets. The control group wore the device with no feedback or ability to see their number of steps walked. Results: Results showed that at the end of the 12 week period, patients in the study groups walked more compared to the controls and the financial incentive structure resulted in an additional 38-63% increase in average daily steps. Conclusions: This pilot study revealed that a home-based exercise program with activity monitoring, feedback and financial incentives resulted increased daily steps, 6-minute walking distance and overall compliance with the program in PAD patients with claudication.

Wearable Devices to Monitor and Reduce the Risk of Cardiovascular Disease: Evidence and Opportunities

There is a growing interest in using wearable devices to improve cardiovascular risk factors and care. This review evaluates how wearable devices are used for cardiovascular disease monitoring and risk reduction. Wearables have been evaluated for detecting arrhythmias (e.g., atrial fibrillation) as well as monitoring physical activity, sleep, and blood pressure. Thus far, most interventions for risk reduction have focused on increasing physical activity. Interventions have been more successful if the use of wearable devices is combined with an engagement strategy such as incorporating principles from behavioral economics to integrate social or financial incentives. As the technology continues to evolve, wearable devices could be an important part of remote-monitoring interventions but are more likely to be effective at improving cardiovascular care if integrated into programs that use an effective behavior change strategy.

Prescribing Behavior Change: Opportunities and Challenges for Clinicians to Embrace Digital and Mobile Health

Individual behaviors impact physical and mental health. Everyday behaviors such as physical activity, diet, sleep, and tobacco use have been associated with a range of acute and chronic medical conditions. Educating, motivating, and promoting sustained healthy behaviors can be challenging for clinical providers attempting to manage their patients’ health. The ubiquity and integration of mobile and digital health devices (eg, wearable step counters, smartphone-based apps) allow for individuals to generate and record enormous amounts of patient-generated health data. Research studies have begun to reveal how mobile and digital devices offer promise in motivating individual behavior change but they have not had consistent results. In this viewpoint, we discuss the potential synergy of digital health modalities and behavioral strategies as an approach for clinicians to prescribe, motivate, monitor, and sustain healthy behaviors. We discuss the strengths, challenges, and opportunities for the future of promoting health behaviors.

Effects of Incentives on Adherence to a Web-Based Intervention Promoting Physical Activity: Naturalistic Study

Background

Despite many advantages of web-based health behavior interventions such as wide accessibility or low costs, these interventions are often accompanied by high attrition rates, particularly in usage under real-life conditions. It would therefore be helpful to implement strategies such as the use of financial incentives to motivate program participation and increase adherence.

Objective

This naturalistic study examined real-life usage data of a 12-week web-based physical activity (PA) intervention (Fitness Coach) among insurants who participated in an additional incentive program (incentive group) and those who did not (nonincentive group). Users in the incentive group had the perspective of receiving €30 (about US $33) cash back at the end of the intervention.

Methods

Registration and real-life usage data as part of routine data management and evaluation of the Fitness Coach were analyzed between September 2016 and June 2018. Depending on the duration of use and the weekly recording of tasks, 4 adherence groups (low, occasional, strong, and complete adherence) were defined. Demographic characteristics were collected by a self-reported questionnaire at registration. We analyzed baseline predictors and moderators of complete adherence such as participation in the program, age, gender, and BMI using binary logistic regressions.

Results

A total of 18,613 eligible persons registered for the intervention. Of these, 15,482 users chose to participate in the incentive program (incentive group): mean age 42.4 (SD 14.4) years, mean BMI 24.5 (SD 4.0) kg/m², median (IQR) BMI 23.8 (21.7-26.4) kg/m²; 65.12% (10,082/15,482) female; and 3131 users decided not to use the incentive program (nonincentive group): mean age 40.7 (SD 13.4) years, mean BMI 26.2 (SD 5.0) kg/m², median BMI 25.3 (IQR 22.6-28.7) kg/m²; 72.18% (2260/3131) female. At the end of the intervention, participants in the incentive program group showed 4.8 times higher complete adherence rates than those in the nonincentive program group (39.2% vs 8.1%), also yielding significantly higher odds to complete the intervention (odds ratio [OR] 12.638) for the incentive program group. Gender significantly moderated the effect with men in the incentive group showing higher odds to be completely adherent than women overall and men in the nonincentive group (OR 1.761). Furthermore, older age and male gender were significant predictors of complete adherence for all participants, whereas BMI did not predict intervention completion.

Conclusions

This is the first naturalistic study in the field of web-based PA interventions that shows the potential of even small financial incentives to increase program adherence. Male users, in particular, seem to be strongly motivated by incentives to complete the intervention. Based on these findings, health care providers can use differentiated incentive systems to increase regular participation in web-based PA interventions.

Incentives and Physical Activity: An Assessment of the Association Between Vitality's Active Rewards with Apple Watch Benefit and Sustained Physical Activity Improvements

The benefits of physical activity include a lowered risk of some major non-communicable diseases and improving wellbeing and mental health. However, roughly about one third of the global adult population is not meeting the minimum weekly level of physical activity recommended by the World Health Organisation. Discovery, a South African multi-national insurance group, offers two types of incentives to its members: Vitality Active Rewards and Vitality Active Rewards with Apple Watch. The Vitality Active Rewards scheme, a gain-framed incentive, rewards individuals for tracking and reaching different thresholds of physical activity, whereas the Vitality Active Rewards with Apple Watch benefit makes monthly repayments for an Apple Watch in amounts linked to different levels of physical activity thresholds that the individual reaches per month. Discovery commissioned RAND Europe to conduct an independent assessment on whether the Vitality Active Rewards with Apple Watch benefit is associated with increased physical activity levels for Vitality members that take up the benefit, compared to those individuals that only participate in the Vitality Active Rewards programme. The study also examined whether these associations persist over time. The findings of this study suggest that incentivising physical activity to tackle inactivity and a sedentary lifestyle can lead to better activity levels. When more unhealthy individuals take up an incentive of this kind, the results can lead on average to a more pronounced behaviour change than we see in already relatively more active and healthy individuals. This is important when designing health promotion programmes.

Usability of Wearable Devices to Remotely Monitor Sleep Patterns Among Patients With Ischemic Heart Disease: Observational Study

Background

There is growing interest in using wearable devices to remotely monitor patient behaviors. However, there has been little evaluation of how often these technologies are used to monitor sleep patterns over longer term periods, particularly among more high-risk patients.

Objective

The goal of the research was to evaluate the proportion of time that patients with ischemic heart disease used wearable devices to monitor their sleep and identify differences in characteristics of patients with higher versus lower use.

Methods

We evaluated wearable device data from a previously conducted clinical trial testing the use of wearable devices with personalized goal-setting and financial incentives. Patients with ischemic heart disease established a sleep baseline and were then followed for 24 weeks. The proportion of days that sleep data was collected was compared over the 24 weeks and by study arm. Characteristics of patients were compared to groups with high, low, or no sleep data.

Results

The sample comprised 99 patients with ischemic heart disease, among which 79% (78/99) used the wearable device to track their sleep. During the 6-month trial, sleep data were collected on 60% (10,024/16,632) of patient-days. These rates declined over time from 77% (4292/5544) in months 1 and 2 to 58% (3188/5544) in months 3 and 4 to 46% (2544/5544) in months 5 and 6. Sleep data were collected at higher rates among the intervention group compared with control (67% vs 55%, P<.001). In the main intervention period (months 3 and 4), patients with higher rates of sleep data were on average older (P=.03), had a history of smoking (P=.007), and had higher rates of commercial health insurance (P=.03).

Conclusions

Among patients with ischemic heart disease in a physical activity trial, a high proportion used wearable devices to track their sleep; however, rates declined over time. Future research should consider larger evaluations coupled with behavioral interventions.

Trial Registration

ClinicalTrials.gov NCT02531022; https://clinicaltrials.gov/ct2/show/NCT02531022