Adding Team-Based Financial Incentives to the Carrot Rewards App Increases Daily Step Count on a Population Scale: A 24-Week Matched Pairs Study

Abstract Background Mobile health applications (mHealth apps) targeting physical inactivity have increased in popularity yet are usually limited by low engagement. This study examined the impact of adding team-based incentives (Step Together Challenges, STCs) to an existing mHealth app (Carrot Rewards) that rewarded individual physical activity achievements. Methods A 24-week quasi-experimental study (retrospective matched pairs design) was conducted in three Canadian provinces (pre-intervention: weeks 1–12; intervention: weeks 13–24). Participants who used Carrot Rewards and STCs (experimental group) were matched with those who used Carrot Rewards only (controls) on age, gender, province and baseline mean daily step count (± 500 steps/d). Carrot Rewards users earned individual-level incentives (worth $0.04 CAD) each day they reached a personalized daily step goal. With a single partner, STC users could earn team incentives ($0.40 CAD) for collaboratively reaching individual daily step goals 10 times in seven days (e.g., Partner A completes four goals and Partner B completes six goals in a week). Results The main analysis included 61,170 users (mean age = 32yrs; % female = 64). Controlling for pre-intervention mean daily step count, a significant difference in intervention mean daily step count favoured the experimental group (p < 0.0001; ηp2 = 0.024). The estimated marginal mean group difference was 537 steps per day, or 3759 steps per week (about 40 walking min/wk). Linear regression suggested a dose-response relationship between the number of STCs completed (app engagement) and intervention mean daily step count (adjusted R2 = 0.699) with each new STC corresponding to approximately 200 more steps per day. Conclusion Despite an explosion of physical activity app interest (100,000 + published apps), low engagement leading to small or no effects remains an industry hallmark. In this paper, we found that adding modest team-based incentives to the Carrot Rewards app increased mean daily step count, and importantly, app engagement moderated this effect. Others should consider novel small-teams based approaches to boost engagement and effects.

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Adding team-based financial incentives to the Carrot Rewards physical activity app increases daily step count on a population scale: a 24-week matched case control study

International Journal of Behavioral Nutrition and Physical Activity ◽

10.1186/s12966-020-01043-1 ◽

2020 ◽

Vol 17 (1) ◽

Author(s):

Emma Pearson ◽

Harry Prapavessis ◽

Christopher Higgins ◽

Robert Petrella ◽

Lauren White ◽

...

Keyword(s):

Physical Activity ◽

Financial Incentives ◽

Step Count ◽

Daily Step ◽

Individual Level ◽

Significant Difference ◽

Daily Step Count ◽

Steps Per Day ◽

The Impact ◽

Experimental Group

Abstract Background Mobile health applications (mHealth apps) targeting physical inactivity have increased in popularity yet are usually limited by low engagement. This study examined the impact of adding team-based incentives (Step Together Challenges, STCs) to an existing mHealth app (Carrot Rewards) that rewarded individual physical activity achievements. Methods A 24-week quasi-experimental study (retrospective matched pairs design) was conducted in three Canadian provinces (pre-intervention: weeks 1–12; intervention: weeks 13–24). Participants who used Carrot Rewards and STCs (experimental group) were matched with those who used Carrot Rewards only (controls) on age, gender, province and baseline mean daily step count (±500 steps/d). Carrot Rewards users earned individual-level incentives (worth $0.04 CAD) each day they reached a personalized daily step goal. With a single partner, STC users could earn team incentives ($0.40 CAD) for collaboratively reaching individual daily step goals 10 times in seven days (e.g., Partner A completes four goals and Partner B completes six goals in a week). Results The main analysis included 61,170 users (mean age = 32 yrs.; % female = 64). Controlling for pre-intervention mean daily step count, a significant difference in intervention mean daily step count favoured the experimental group (p < 0.0001; ηp2 = 0.024). The estimated marginal mean group difference was 537 steps per day, or 3759 steps per week (about 40 walking min/wk). Linear regression suggested a dose-response relationship between the number of STCs completed (app engagement) and intervention mean daily step count (adjusted R2 = 0.699) with each new STC corresponding to approximately 200 more steps per day. Conclusion Despite an explosion of physical activity app interest, low engagement leading to small or no effects remains an industry hallmark. In this paper, we found that adding modest team-based incentives to the Carrot Rewards app increased mean daily step count, and importantly, app engagement moderated this effect. Others should consider novel small-teams based approaches to boost engagement and effects.

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Adding team-based financial incentives to the Carrot Rewards physical activity app increases daily step count on a population scale: A 24-week matched case control study

10.21203/rs.3.rs-54028/v3 ◽

2020 ◽

Author(s):

Emma Pearson ◽

Harry Prapavessis ◽

Christopher Higgins ◽

Robert Petrella ◽

Lauren White ◽

...

Keyword(s):

Physical Activity ◽

Financial Incentives ◽

Step Count ◽

Daily Step ◽

Individual Level ◽

Significant Difference ◽

Daily Step Count ◽

Steps Per Day ◽

The Impact ◽

Experimental Group

Abstract Background: Mobile health applications (mHealth apps) targeting physical inactivity have increased in popularity yet are usually limited by low engagement. This study examined the impact of adding team-based incentives (Step Together Challenges, STCs) to an existing mHealth app (Carrot Rewards) that rewarded individual physical activity achievements.Methods: A 24-week quasi-experimental study (retrospective matched pairs design) was conducted in three Canadian provinces (pre-intervention: weeks 1-12; intervention: weeks 13-24). Participants who used Carrot Rewards and STCs (experimental group) were matched with those who used Carrot Rewards only (controls) on age, gender, province and baseline mean daily step count (±500 steps/d). Carrot Rewards users earned individual-level incentives (worth $0.04 CAD) each day they reached a personalized daily step goal. With a single partner, STC users could earn team incentives ($0.40 CAD) for collaboratively reaching individual daily step goals 10 times in seven days (e.g., Partner A completes four goals and Partner B completes six goals in a week).Results: The main analysis included 61,170 users (mean age=32yrs; % female=64). Controlling for pre-intervention mean daily step count, a significant difference in intervention mean daily step count favoured the experimental group (p<0.0001; ηp2=0.024). The estimated marginal mean group difference was 537 steps per day, or 3759 steps per week (about 40 walking min/wk). Linear regression suggested a dose-response relationship between the number of STCs completed (app engagement) and intervention mean daily step count (adjusted R2=0.699) with each new STC corresponding to approximately 200 more steps per day.Conclusion: Despite an explosion of physical activity app interest, low engagement leading to small or no effects remains an industry hallmark. In this paper, we found that adding modest team-based incentives to the Carrot Rewards app increased mean daily step count, and importantly, app engagement moderated this effect. Others should consider novel small-teams based approaches to boost engagement and effects.

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Adding team-based financial incentives to the Carrot Rewards physical activity app increases daily step count on a population scale: A 24-week matched case control study

10.21203/rs.3.rs-54028/v2 ◽

2020 ◽

Author(s):

Emma Pearson ◽

Harry Prapavessis ◽

Christopher Higgins ◽

Robert Petrella ◽

Lauren White ◽

...

Keyword(s):

Physical Activity ◽

Financial Incentives ◽

Step Count ◽

Daily Step ◽

Individual Level ◽

Significant Difference ◽

Daily Step Count ◽

Steps Per Day ◽

The Impact ◽

Experimental Group

Abstract Background: Mobile health applications (mHealth apps) targeting physical inactivity have increased in popularity yet are usually limited by low engagement. This study examined the impact of adding team-based incentives (Step Together Challenges, STCs) to an existing mHealth app (Carrot Rewards) that rewarded individual physical activity achievements. Methods: A 24-week quasi-experimental study (retrospective matched pairs design) was conducted in three Canadian provinces (pre-intervention: weeks 1-12; intervention: weeks 13-24). Participants who used Carrot Rewards and STCs (experimental group) were matched with those who used Carrot Rewards only (controls) on age, gender, province and baseline mean daily step count (±500 steps/d). Carrot Rewards users earned individual-level incentives (worth $0.04 CAD) each day they reached a personalized daily step goal. With a single partner, STC users could earn team incentives ($0.40 CAD) for collaboratively reaching individual daily step goals 10 times in seven days (e.g., Partner A completes four goals and Partner B completes six goals in a week). Results: The main analysis included 61,170 users (mean age=32yrs; % female=64). Controlling for pre-intervention mean daily step count, a significant difference in intervention mean daily step count favoured the experimental group (p<0.0001; ηp2=0.024). The estimated marginal mean group difference was 537 steps per day, or 3759 steps per week (about 40 walking min/wk). Linear regression suggested a dose-response relationship between the number of STCs completed (app engagement) and intervention mean daily step count (adjusted R2=0.699) with each new STC corresponding to approximately 200 more steps per day. Conclusion: Despite an explosion of physical activity app interest, low engagement leading to small or no effects remains an industry hallmark. In this paper, we found that adding modest team-based incentives to the Carrot Rewards app increased mean daily step count, and importantly, app engagement moderated this effect. Others should consider novel small-teams based approaches to boost engagement and effects.

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Cutoff Points for Step Count to Predict 1-year All-Cause Mortality in Patients with Idiopathic Pulmonary Fibrosis

Respiration ◽

10.1159/000517030 ◽

2021 ◽

pp. 1-7

Author(s):

Kazuya Shingai ◽

Toshiaki Matsuda ◽

Yasuhiro Kondoh ◽

Tomoki Kimura ◽

Kensuke Kataoka ◽

...

Keyword(s):

Physical Activity ◽

Idiopathic Pulmonary Fibrosis ◽

Pulmonary Fibrosis ◽

Step Count ◽

Cutoff Point ◽

Daily Step ◽

All Cause Mortality ◽

Cutoff Points ◽

Daily Step Count ◽

Steps Per Day

Background: Although physical activity is associated with mortality in patients with idiopathic pulmonary fibrosis (IPF), reference values to interpret levels of physical activity are lacking. Objectives: This study aimed to investigate the prognostic significance of physical activity assessed by step count and its cutoff points for all-cause mortality. Methods: We measured physical activity (steps per day) using an accelerometer in patients with IPF at the time of diagnosis. Relationships among physical activity and mortality, as well as cutoff points of daily step count to predict all-cause mortality were examined. Results: Eighty-seven patients (73 males) were enrolled. Forty-four patients (50.1%) died during the follow-up (median 54 months). In analysis adjusting for Gender-Age-Physiology stage and 6-min walk distance, daily step count was an independent predictor of all-cause mortality (hazard ratio (HR) = 0.820, 95% confidence interval (CI) = 0.694–0.968, p = 0.019). The optimal cutoff point (receiving operating characteristic analysis) for 1-year mortality was 3,473 steps per day (sensitivity = 0.818 and specificity = 0.724). Mortality was significantly lower in patients with a daily step count exceeding 3,473 steps than in those whose count was 3,473 or less (HR = 0.395, 95% CI = 0.218–0.715, p = 0.002). Conclusions: Step count, an easily interpretable measurement, was a significant predictor of all-cause mortality in patients with IPF. At the time of diagnosis, a count that exceeded the cutoff point of 3,473 steps/day more than halved mortality. These findings highlight the importance of assessing physical activity in this patient population.

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IMPACT OF PHYSICIAN LED LIFE STYLE MODIFICATIONS (DIET AND DAILY STEP COUNT BY USING PEDOMETER) ON GLYCEMIC CONTROL OF PATIENTS WITH TYPE II DIABETIC

Pakistan Armed Forces Medical Journal ◽

10.51253/pafmj.v71i2.2788 ◽

2021 ◽

Vol 71 (2) ◽

pp. 478-81

Author(s):

Rimsha Azhar ◽

Khurshid Uttra ◽

Andaleeb Khan ◽

Marriam Hussain Awan ◽

Ayesha Anwer ◽

...

Keyword(s):

Glycemic Control ◽

Life Style ◽

Step Count ◽

Diabetic Patients ◽

Care Hospital ◽

Type Ii ◽

Daily Step ◽

Significant Difference ◽

Daily Step Count ◽

The Impact

Objective: To determine the impact of physician led life style modifications (diet and daily step count by using pedometer) on glycemic control of type II diabetic patients Study Design: Quasi experimental study. Place and Duration of Study: Pak Emirates Military Hospital, Rawalpindi, Aug 2018 to Feb 2019. Methodology: The sample population comprised of 200 diabetic patients reporting for the routine follow-up at a tertiary care hospital in Rawalpindi. Patients were divided into two groups by random method. Group A had the patients with continuation of the routine anti-diabetic medication while group received the physician led life style modifications in addition to the routine anti diabetic medication. Values of HBA1c among the groups were compared three months after the start of study. Results: Mean age of the patients was 42.19 ± 6.175 years. Mean duration of DM in the study participants was 4.52 ± 4.166 years. Out of 115 patients were male while 85 were female. HBA1c in the intervention group was 7.96% ± 0.39 while in the control group was 7.04% ± 0.81. Difference between the two groups was statistically significant (p-value<0.01). Conclusion: This study showed a significant difference in glycemic control of patients who received physician led life style modification in addition to conventional biological treatment than those who only received the routine anti-diabetic medication. Physicians should be trained to impart this sort of education to the diabetic patients in routine diabetic clinics.

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

10.1101/2021.01.31.21250863 ◽

2021 ◽

Cited By ~ 1

Author(s):

Victoria Eshelby ◽

Muhammed Sogut ◽

Kate Jolly ◽

Ivo Vlaev ◽

Mark T. Elliott

Keyword(s):

Physical Activity ◽

Urban Areas ◽

Step Count ◽

Daily Step ◽

Physical And Mental Health ◽

Targeted Interventions ◽

Factors Associated ◽

Daily Step Count ◽

The Uk ◽

The Impact

ABSTRACTGovernment restrictions applied during the COVID-19 pandemic in the UK led to the disruption of many people’s physical activity routines, with sports and leisure facilities closed and outdoor exercise only permitted once per day. In this study we investigated which population groups were impacted most in terms of reduced physical activity levels during these periods, and which groups benefitted in terms of increasing their usual level of physical activity. We surveyed UK residents, sampled through users of a rewards-for-exercise app (Sweatcoin; n=749) and an online panel (Prolific; n=907). Of the app users, n=487 further provided daily step-count data collected by the app, prior to, and during the periods of restrictions between March and June 2020. Regression models were applied to investigate factors associated with subjective change (perceived change in physical activity) and objective change (log-percentage change in daily step-count) in physical activity during the periods of restrictions. ANOVAs were used to further investigate the significant factors identified. Key factors associated with a substantial subjective reduction in physical activity included those classed as obese, gym users and people living in urban areas. All participants had a reduced step count during restrictions, with Black, Asian and minority ethnic (BAME) groups, students and urban dwellers showing the largest reductions. Therefore, targeted interventions are required to ensure that the physical and mental health impacts of sedentary behaviour are not exacerbated over the long-term by significant reductions in physical activity identified in these groups, particularly those who are also more vulnerable to the COVID-19 virus.

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The translation of preschoolers’ physical activity guidelines into a daily step count target

Journal of Sports Sciences ◽

10.1080/02640414.2014.981850 ◽

2014 ◽

Vol 33 (10) ◽

pp. 1051-1057 ◽

Cited By ~ 24

Author(s):

Marieke De Craemer ◽

Ellen De Decker ◽

Ilse De Bourdeaudhuij ◽

Maïté Verloigne ◽

Yannis Manios ◽

...

Keyword(s):

Physical Activity ◽

Step Count ◽

Daily Step ◽

Physical Activity Guidelines ◽

Daily Step Count

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Abstract 11: mActive: A Blinded, Randomized mHealth Trial Supporting Digital Tracking and Smart Texting for Promotion of Physical Activity

Circulation ◽

10.1161/circ.131.suppl_1.11 ◽

2015 ◽

Vol 131 (suppl_1) ◽

Author(s):

Seth S Martin ◽

David I Feldman ◽

Roger S Blumenthal ◽

Steven R Jones ◽

Wendy S Post ◽

...

Keyword(s):

Physical Activity ◽

Phase I ◽

Real Time ◽

Phase Ii ◽

The United States ◽

Step Count ◽

Daily Step ◽

Baseline Activity ◽

Daily Step Count ◽

Digital Tracking

Introduction: The recent advent of smartphone-linked wearable pedometers offers a novel opportunity to promote physical activity using mobile health (mHealth) technology. Hypothesis: We hypothesized that digital activity tracking and smart (automated, real-time, personalized) texting would increase physical activity. Methods: mActive (NCT01917812) was a 5-week, blinded, sequentially-randomized, parallel group trial that enrolled patients at an academic preventive cardiovascular center in Baltimore, MD, USA from January 17 th to May 20 th , 2014. Eligible patients were 18-69 year old smartphone users who reported low leisure-time physical activity by a standardized survey. After establishing baseline activity during a 1-week blinded run-in, we randomized 2:1 to unblinded or blinded tracking in phase I (2 weeks), then randomized unblinded participants 1:1 to receive or not receive smart texts in phase II (2 weeks). Smart texts provided automated, personalized, real-time coaching 3 times/day towards a daily goal of 10,000 steps. The primary outcome was change in daily step count. Results: Forty-eight patients (22 women, 26 men) enrolled with a mean (SD) age of 58 (8) years, body mass index of 31 (6), and baseline daily step count of 9670 (4350). The phase I change in activity was non-significantly higher in unblinded participants versus blinded controls by 1024 steps/day (95% CI -580-2628, p=0.21). In phase II, smart text receiving participants increased their daily steps over those not receiving texts by 2534 (1318-3750, p<0.001) and over blinded controls by 3376 (1951-4801, p<0.001). The unblinded-texts group had the highest proportion attaining the 10,000 steps/day goal (p=0.02) (Figure). Conclusions: In present-day adult smartphone users receiving preventive cardiovascular care in the United States, a technologically-integrated mHealth strategy combining digital tracking with automated, personalized, real-time text message coaching resulted in a large short-term increase in physical activity.

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Neural Network–Based Algorithm for Adjusting Activity Targets to Sustain Exercise Engagement Among People Using Activity Trackers: Retrospective Observation and Algorithm Development Study

JMIR mhealth and uhealth ◽

10.2196/18142 ◽

2020 ◽

Vol 8 (9) ◽

pp. e18142

Author(s):

Ramin Mohammadi ◽

Mursal Atif ◽

Amanda Jayne Centi ◽

Stephen Agboola ◽

Kamal Jethwani ◽

...

Keyword(s):

Neural Network ◽

Physical Activity ◽

Machine Learning ◽

Learning Model ◽

Step Count ◽

Daily Step ◽

Activity Tracker ◽

Activity Trackers ◽

Machine Learning Model ◽

Daily Step Count

Background It is well established that lack of physical activity is detrimental to the overall health of an individual. Modern-day activity trackers enable individuals to monitor their daily activities to meet and maintain targets. This is expected to promote activity encouraging behavior, but the benefits of activity trackers attenuate over time due to waning adherence. One of the key approaches to improving adherence to goals is to motivate individuals to improve on their historic performance metrics. Objective The aim of this work was to build a machine learning model to predict an achievable weekly activity target by considering (1) patterns in the user’s activity tracker data in the previous week and (2) behavior and environment characteristics. By setting realistic goals, ones that are neither too easy nor too difficult to achieve, activity tracker users can be encouraged to continue to meet these goals, and at the same time, to find utility in their activity tracker. Methods We built a neural network model that prescribes a weekly activity target for an individual that can be realistically achieved. The inputs to the model were user-specific personal, social, and environmental factors, daily step count from the previous 7 days, and an entropy measure that characterized the pattern of daily step count. Data for training and evaluating the machine learning model were collected over a duration of 9 weeks. Results Of 30 individuals who were enrolled, data from 20 participants were used. The model predicted target daily count with a mean absolute error of 1545 (95% CI 1383-1706) steps for an 8-week period. Conclusions Artificial intelligence applied to physical activity data combined with behavioral data can be used to set personalized goals in accordance with the individual’s level of activity and thereby improve adherence to a fitness tracker; this could be used to increase engagement with activity trackers. A follow-up prospective study is ongoing to determine the performance of the engagement algorithm.

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A Pilot Study Comparing Pedometer Counts with Reported Physical Activity in Elementary Schoolchildren

Pediatric Exercise Science ◽

10.1123/pes.16.4.355 ◽

2004 ◽

Vol 16 (4) ◽

pp. 355-367 ◽

Cited By ~ 18

Author(s):

Greet Cardon ◽

Ilse De Bourdeaudhuij

Keyword(s):

Physical Activity ◽

Pilot Study ◽

Vigorous Physical Activity ◽

Step Count ◽

Regression Equations ◽

Moderate Correlation ◽

Daily Step ◽

Step Counts ◽

Daily Step Count

In this study pedometer counts were recorded for 6 consecutive days for 92 children (mean age = 9.6 years; range 6.5–12.7) and were compared with the number of minutes per day in which the participants engaged in moderate-to-vigorous physical activity (MVPA). Diaries filled out with the assistance of one of the children’s parents were used to determine minutes of MVPA. The average daily step count was significantly higher in boys than in girls, although the average daily MVPA engagement in minutes did not vary significantly between genders. Based on the regression equations, 60 min of MVPA was equivalent to 15,340 step counts in boys, 11,317 step counts in girls, and 13,130 step counts when results for both genders were combined. A moderate correlation (r = .39, p < .001) was found between pedometer step counts and reported minutes of MVPA. According to the present study findings, however, predictions and promotion of daily MVPA engagement in children based on pedometer counts per day should be made with caution.

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