Individual Versus Team-Based Financial Incentives to Increase Physical Activity: A Randomized, Controlled Trial

Abstract

BACKGROUND: More than half of adults in the United States do not attain the minimum recommended level of physical activity to achieve health benefits. The optimal design of financial incentives to promote physical activity is unknown. OBJECTIVE: To compare the effectiveness of individual versus team-based financial incentives to increase physical activity. DESIGN: Randomized, controlled trial comparing three interventions to control. PARTICIPANTS: Three hundred and four adult employees from an organization in Philadelphia formed 76 four-member teams. INTERVENTIONS: All participants received daily feedback on performance towards achieving a daily 7000 step goal during the intervention (weeks 1-13) and follow-up (weeks 14-26) periods. The control arm received no other intervention. In the three financial incentive arms, drawings were held in which one team was selected as the winner every other day during the 13-week intervention. A participant on a winning team was eligible as follows: $50 if he or she met the goal (individual incentive), $50 only if all four team members met the goal (team incentive), or $20 if he or she met the goal individually and $10 more for each of three teammates that also met the goal (combined incentive). MAIN MEASURES: Mean proportion of participantdays achieving the 7000 step goal during the intervention. KEY RESULTS: Compared to the control group during the intervention period, the mean proportion achieving the 7000 step goal was significantly greater for the com- There were no significant differences between arms during the follow-up period (weeks 14-26). CONCLUSIONS: Financial incentives rewarded for a combination of individual and team performance were most effective for increasing physical activity. TRIAL REGISTRATION: Clinicaltrials.gov identifier: NCT02001194.

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

“…First, a key element of our study design was the use of loss aversion, a principle from behavioral economics 13, 17, 18, 19, 28, 29, 30, 31, 32, 33, 34. Most previous financial incentive‐based physical activity interventions have used gain‐framed incentives16, 39, 40, 41—individuals earn a reward after the behavior is achieved.…”

“…The study was conducted using Way to Health, a research technology platform at the University of Pennsylvania used previously for physical activity interventions 17, 18, 19, 22. Patients used the study website to create an account, provide informed consent online, and completed baseline eligibility surveys and the MacNew heart disease quality of life questionnaire 23, 24.…”

“…Power calculations (a priori) were based on previous work17, 18, 19 and assumed a baseline mean step count of 6000 steps in the control group with an SD of 2000 steps, a 15% dropout rate, and a 2‐sided α of 0.05. It was estimated that a sample of 148 patients (74 per arm) would ensure at least 80% power to detect a 1000‐step difference between the incentive and control arms in the change in mean daily steps from baseline to the maintenance incentive phase.…”

“…For the prespecified main analysis, we used multiple imputation for data that were missing and step values less than 1000. We have used this method in previous work17, 18, 19, 25 and in this study because evidence indicates that step values less than 1000 may not represent accurate data capture 26, 27. Five imputations were conducted using the mice package in R (R Foundation for Statistical Computing, Vienna, Austria), which allows for patient random effects with this data structure 37.…”

“…However, thus far there is limited evidence of interventions that use these devices to effectively sustain behavior change among high‐risk patients 13, 15, 16. Our previous work found that financial incentive‐based approaches that use mobile technologies can be effective in increasing physical activity,17, 18, 19 but only if they are designed to appropriately leverage insights from behavioral economics—a field that incorporates insights from psychology to design interventions that address predictable barriers to behavior change 20, 21. For example, we found that the framing of financial incentives significantly impacted their effectiveness 18.…”