Framing Financial Incentives to Increase Physical Activity Among Overweight and Obese Adults

Abstract

Background Financial incentive designs to increase physical activity have not been well-examined. Objective To test the effectiveness of 3 methods to frame financial incentives to increase physical activity among overweight and obese adults. Design Randomized, controlled trial. (ClinicalTrials.gov: NCT 02030119) Setting University of Pennsylvania. Participants 281 adult employees (body mass index ≥27 kg/m2). Intervention 13-week intervention. Participants had a goal of 7000 steps per day and were randomly assigned to a control group with daily feedback or 1 of 3 financial incentive programs with daily feedback: a gain incentive ($1.40 given each day the goal was achieved), lottery incentive (daily eligibility [expected value approximately $1.40] if goal was achieved), or loss incentive ($42 allocated monthly upfront and $1.40 removed each day the goal was not achieved). Participants were followed for another 13 weeks with daily performance feedback but no incentives. Measurements Primary outcome was the mean proportion of participant-days that the 7000-step goal was achieved during the intervention. Secondary outcomes included the mean proportion of participant-days achieving the goal during follow-up and the mean daily steps during intervention and follow-up. Results The mean proportion of participant-days achieving the goal was 0.30 (95% CI, 0.22 to 0.37) in the control group, 0.35 (CI, 0.28 to 0.42) in the gain-incentive group, 0.36 (CI, 0.29 to 0.43) in the lottery-incentive group, and 0.45 (CI, 0.38 to 0.52) in the loss-incentive group. In adjusted analyses, only the loss-incentive group had a significantly greater mean proportion of participant-days achieving the goal than control (adjusted difference, 0.16 [CI, 0.06 to 0.26]; P = 0.001), but the adjusted difference in mean daily steps was not significant (861 [CI, 24 to 1746]; P = 0.056). During follow-up, daily steps decreased for all incentive groups and were not different from control. Limitation Single employer. Conclusion Financial incentives framed as a loss were most effective for achieving physical activity goals. Primary Funding Source National Institute on Aging.

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

“…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.…”

“…The balance was refreshed with $14 every week on Monday. This design leveraged 4 important psychological principles: Individuals tend to be more motivated by losses than gains,18, 28 favor immediate over delayed gratification,29 try to avoid the feeling of regret,30, 31, 32, 33 and tend to be more driven for aspirational behavior around temporal landmarks such as the beginning of the week (the fresh start effect) 34…”

“…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.…”

“…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.…”

“…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. A “gain‐framed” incentive that used the standard economic approach of rewarding individuals only after physical activity goals were achieved was not effective.…”