Roy Rosin

Framing Financial Incentives to Increase Physical Activity Among Overweight and Obese Adults: A Randomized, Controlled Trial

Context Financial incentives are commonly used in workplace wellness programs aimed at increasing physical activity. The most effective approach to offering incentives, however, is not known. Contribution In this trial, the up-front allocation of a financial reward and subsequent loss when physical activity goals were not met resulted in greater daily exercise than no incentive. Providing a reward when goals were met, however, did not increase physical activity. Implication The manner in which financial incentives are offered may influence the success of health promotion programs. Higher levels of regular physical activity are associated with lower rates of cardiovascular disease, diabetes, obesity, hypertension, and all-cause mortality (15). However, more than half of adults in the United States do not attain the minimum recommended level of physical activity to have these health benefits (6, 7). The Centers for Disease Control and Prevention and many state public health departments have recommended the workplace as an environment to implement interventions to increase physical activity (811). But evidence suggests that most workplace physical activity interventions are not effective, particularly for more sedentary persons (1214). Workplace wellness programs are growing in popularity throughout the United States, and more than 80% of large employers now use some form of financial incentive for health promotion (1517). Beginning in 2014, the Patient Protection and Affordable Care Act increased the proportion of employee health insurance premiums that can be used as outcome-based wellness incentives from 20% to 30% and as high as 50% if tobacco use is targeted (18, 19). This provides a significant opportunity to use incentive-based programs to change health behaviors, but the optimal design of financial incentives to increase physical activity has not been well-examined (20). Behavioral economics incorporates principles from psychology to help understand why persons make decisions that are not in line with longer-term health goals. Many persons know physical activity is good for their health but do not do enough of it. Instead, they often deviate from these goals in a predictable manner and from a common set of decision errors (18, 19, 21). For example, persons tend to be more motivated by immediate rather than delayed gratification (22) and by losses rather than gains (23), and they tend to avoid the feeling of regret (24). These insights reveal that the design and delivery of an incentive has an important influence on its effectiveness. The objective of this study was to test the effectiveness of 3 financial incentive designs, each with the same expected economic value. In the gain-incentive group, participants received a fixed amount of money each day the step goal was achieved. This design follows traditional economic principles in that it is largely transactional: A certain constant reward is promised for a predetermined effort. Persons in the 2 other incentive groups were offered incentives of the same expected value, but those incentives were designed to leverage the fact that persons tend to be loss averse, are more engaged by variable reinforcement than by constant reinforcement, and tend to avoid the feeling of regret. Methods Design Overview We conducted a 26-week randomized, controlled trial between 6 March and 6 September 2014, consisting of 13-week intervention and follow-up periods. A total of 281 participants gave their informed consent and were randomly assigned to a control group or to 1 of 3 groups with different financial incentive designs, each with the same expected economic value. All participants were given a goal of achieving at least 7000 steps per day, and this target reflects several deliberate design elements. First, this level of physical activity is endorsed by the American College of Sports Medicine to be approximately equivalent to meeting the federal guidelines for the minimum recommended levels of physical activity needed to achieve health benefits (25, 26). Second, this level is 40% higher than the average daily step count of 5000 among U.S. adults (27, 28). Prior studies using an even higher goal of 10000 steps have found that more sedentary persons may be less likely to participate, and it was a priority in this study to engage as many persons as possible (12). Third, instead of simply asking participants to increase steps, a minimum threshold puts greater emphasis on encouraging more sedentary persons to be physically active and less emphasis on getting highly active persons to be even more active. Step counts were tracked using the Moves smartphone application (ProtoGeo Oy), which uses accelerometers within the phone and has been shown by our prior work to be accurate (29). Each participant was given a unique personal identification number to enter into the smartphone application and verify permission that the study team could access step-count data. Once the application was installed on the phone, the participant never had to reopen it, although they could as often as they wished. Instead, participants had to allow the application to run passively on the phone, have the phone powered on, and carry it with them (for example, in a pocket or on a belt clip or arm band) while they were active. The University of Pennsylvania Institutional Review Board approved this study. Setting and Participants Eligible participants were employees of the University of Pennsylvania in Philadelphia, Pennsylvania, were aged 18 years or older, and had a body mass index (BMI) of at least 27 kg/m2 (estimated from self-reported height and weight). We chose this BMI threshold to help ensure that our sample represented overweight or obese persons. Participants were recruited by e-mail from February to March 2014 and excluded if they were already participating in another physical activity study, were not able or willing to carry an iPhone (Apple) or Android (Google) smartphone with the mobile application installed, were pregnant or lactating, intended to become pregnant within 6 months, or stated that they could not complete the study. E-mails were sent to all University of Pennsylvania staff employees (approximately 10000 persons). All eligible participants provided electronic informed consent, completed a sociodemographic questionnaire, self-reported measures of height and weight, and reported recent physical activity using the long form of the International Physical Activity Questionnaire (30). Randomization and Interventions Participants enrolled online using Way to Health, an automated technology platform based at the University of Pennsylvania that integrates wireless devices, conducts clinical trial randomization and enrollment processes, delivers messaging (text message or e-mail) and surveys, automates transfers of financial incentives, and securely captures data for research purposes (31). Way to Health was used in prior behavioral intervention studies (3234). All participants received

A Randomized Trial of Social Comparison Feedback and Financial Incentives to Increase Physical Activity.

25 for enrolling and

Association of Rideshare-Based Transportation Services and Missed Primary Care Appointments: A Clinical Trial

75 for participating through the primary end point at 13 weeks along with completion of a survey on their experience. However, there was no participation incentive for the follow-up period. Participants were mailed a bank check at the end of each month with all accumulated earnings. All participants selected whether they preferred to receive study communications by e-mail, text message, or both. Participants were electronically randomly assigned to the control group or to 1 of 3 intervention groups with an equivalent expected economic value of

Change In Length of Stay and Readmissions among Hospitalized Medical Patients after Inpatient Medicine Service Adoption of Mobile Secure Text Messaging.

1.40, which is a value used in prior work (34). For 26 weeks, participants in all 4 groups received daily feedback on whether they had achieved the 7000-step goal in the prior day. The control group received no other intervention aside from daily feedback. For the 13-week intervention, the intervention groups included a gain incentive in which participants received

Rideshare-Based Medical Transportation for Medicaid Patients and Primary Care Show Rates: A Difference-in-Difference Analysis of a Pilot Program

1.40 for each day they met the goal, a loss incentive in which

A Randomized, Controlled Trial of Lottery-Based Financial Incentives to Increase Physical Activity Among Overweight and Obese Adults

1.40 was taken away from a monthly incentive (

Effect of Outreach Messages on Medicaid Enrollment

42 allocated upfront) each time the daily goal was not met, or a daily lottery incentive. Persons in the lottery-incentive group selected a 2-digit number between 00 and 99. One winning number was randomly selected daily during the intervention period. If a participants number had a single-digit match (an 18% chance), he or she won

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

5. If the participants number had a 2-digit match (a 1% chance), he or she won

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50. Participants were eligible to collect the reward only if the 7000-step goal was achieved on the prior day. Ineligible participants were informed what they would have won if they had achieved the goal, drawing on evidence that the desire to avoid regret can be motivating (23, 24, 35, 36). Incentives were offered only during the 13-week intervention, but daily performance feedback was delivered for the entire 26 weeks. Outcomes and Follow-up The primary outcome was the mean proportion of participant-days that the 7000-step goal was achieved during the 13-week intervention. We hypothesized that participants in all 3 financial-incentive groups would have a significantly greater mean proportion of participant-days achieving the goal than the control group, with participants in the loss- and lottery-incentive groups performing the best. Secondary outcomes included the number of steps per day during intervention and follow-up and the mean proportion of participant-days that the 7000-step goal was achieved during follow-up. Neither the participants nor the study coordinator could be blinded to the group assignment. All investigators, statisticians, and data analysts were blinded to group assignments until the 26-week study ended. Statistical Analysis One participant randomly assigned to the gain-incentive group was later found to be ineligible because of enrollment in another physical activity study. One participant randomly assigned to the lottery-incentive group swit

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Purpose: To compare the effectiveness of different combinations of social comparison feedback and financial incentives to increase physical activity. Design: Randomized trial (Clinicaltrials.gov number, NCT02030080). Setting: Philadelphia, Pennsylvania. Participants: Two hundred eighty-six adults. Interventions: Twenty-six weeks of weekly feedback on team performance compared to the 50th percentile (n = 100) or the 75th percentile (n = 64) and 13 weeks of weekly lottery-based financial incentive plus feedback on team performance compared to the 50th percentile (n = 80) or the 75th percentile (n = 44) followed by 13 weeks of only performance feedback. Measures: Mean proportion of participant-days achieving the 7000-step goal during the 13-week intervention. Analysis: Generalized linear mixed models adjusting for repeated measures and clustering by team. Results: Compared to the 75th percentile without incentives during the intervention period, the mean proportion achieving the 7000-step goal was significantly greater for the 50th percentile with incentives group (0.45 vs 0.27, difference: 0.18, 95% confidence interval [CI]: 0.04 to 0.32; P = .012) but not for the 75th percentile with incentives group (0.38 vs 0.27, difference: 0.11, 95% CI: −0.05 to 0.27; P = .19) or the 50th percentile without incentives group (0.30 vs 0.27, difference: 0.03, 95% CI: −0.10 to 0.16; P = .67). Conclusion: Social comparison to the 50th percentile with financial incentives was most effective for increasing physical activity.