Walk the Extra Mile! Assessing Motivational Tools to Promote Physical Activity
Last registered on February 25, 2020

Pre-Trial

Trial Information
General Information
Title
Walk the Extra Mile! Assessing Motivational Tools to Promote Physical Activity
RCT ID
AEARCTR-0005493
Initial registration date
February 24, 2020
Last updated
February 25, 2020 5:56 PM EST
Location(s)
Region
Primary Investigator
Affiliation
University of Vechta
Other Primary Investigator(s)
PI Affiliation
University of Vechta
PI Affiliation
Technion Haifa
PI Affiliation
University of Vechta
Additional Trial Information
Status
On going
Start date
2019-11-07
End date
2020-09-01
Secondary IDs
Abstract
Individuals are highly sensitive to rare events in their planning decisions, but their implementation decisions reflect a bias to the opposite: the underweighting of rare events indicates a dependence on only a few past observations, so even a few failures in the attempt to achieve their goal lead to non-implementation. To overcome this bias, we designed a commitment device based on micro-incentive repeated bets in order to help them adhere to their plans during ongoing decisions. We assume that repeated betting is more cost-efficient and more effective (in the short and long run) than other monetary bonus systems. We test this device in a field experiment with individuals who want to be more physically active. We quantify their objectives in that we define individual goals based on their previous performance. Afterwards, we study goal attainment in a setting without incentives in a pre-intervention phase and goal attainment in a setting where we systematically vary the type of support. We do so by offering different monetary incentives to clarify under which conditions the participants will overcome the mentioned planning-ongoing gap.
External Link(s)
Registration Citation
Citation
Erev, Ido et al. 2020. "Walk the Extra Mile! Assessing Motivational Tools to Promote Physical Activity ." AEA RCT Registry. February 25. https://doi.org/10.1257/rct.5493-1.0.
Experimental Details
Interventions
Intervention(s)
The approach consists of offering two different commitment devices (repeated bet and single bet) and a bonus system to support participants in achieving their individual goals. All subjects are randomized into the following treatments: T0 [Control], T1 [Bonus], T2 [Single Bet] and T3 [Repeated Bet]. Depending on the treatment, the test persons have the opportunity to use their participation fee of 25 euros proportionally to participate in an optional self-binding or bonus-policy. After completing an application survey, respondents receive access to a smartphone app that counts their daily steps. The app records all steps taken as well as the usage of the app. After a baseline phase and a pre-intervention-survey, subjects receive an individual target based on the data collected so far. We observe target achievement over a certain period of time without treatment interventions. Then, we have an intervention phase of 91 days. During study time, subjects will not be influenced by any further feedback or any information. Participants can individually check if they were successful by consulting the app. Following a post-intervention survey, the incentives are cut off and a further observation phase begins to see whether the interventions had a lasting effect on participants’ behavior, which is indicative for habit formation.
Intervention Start Date
2020-03-15
Intervention End Date
2020-09-01
Primary Outcomes
Primary Outcomes (end points)
Based on previous findings on time inconsistency and experience-based learning, we predict a higher average degree of target achievement, in comparison to the control group, when individuals accept the commitment device in the betting conditions. Furthermore, individuals who are taking part in the bet will open the app more often to actively check their current success and to actively send data. We assume that this effect will be stronger in the repeating betting than in the one-shot-betting condition. Even if the individuals within the betting conditions do not reach their goal, the experience-based learning theory suggests that they will come closer to their goals than individuals in the control group. We assume this pattern being an indicator that these people are still trying to implement their decisions from the planning-phase. We expect a decreasing performance in the control group over time while the other treatments are able to support participants sufficiently in keeping a certain average degree of target achievement. Because previous studies have shown that the bonus payments do not lead to long-term changes in behavior, we also assume that this effect will occur in contrast to the betting condition once the incentives are removed. We expect the repeated betting mechanism to be effective and highly cost-efficient, even in the long run.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
By using our app, the participants are able to keep checking how many steps they have taken during the current day. This function helps the participants to identify goal attainment and deviations thereof, positive and negative. We expect that individuals use this information from the pre-intervention phase to self-select in or out of the two betting-treatments: those with high goal attainment rates rather accept the bettings compared to the control group.
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
The outlined research will study a mechanism for repeated betting in a field experiment to address the planning-ongoing gap described above, and test it against various other incentive schemes and a control group. We focus on an environment in which participants try to increase their physical activity by taking more steps each day. The counted steps are measured, showed and sent via a specifically designed smartphone app. We have implemented four treatment groups. All four conditions start with a 15-day baseline to measure individuals’ initial performance. Based on this data, we calculate the median for each participant, which will be used as an individual goal for the rest of the study. We then inform each participant of their target and start collecting data for another 15 days. At time of running the baseline and pre-intervention phase, participants are not aware that we assign them an individual goal and how it will be determined. Once the previous phase is completed, the experimental manipulation begins: Participants in the control condition are simply told that they will get a participation fee (25 Euro) at the end of the study, regardless of how often and to what extent they have achieved their goal. In the "bonus" condition, we offer participants a bonus: participants will receive the same information as in the control condition but gain an additional bonus (0.25 Euro) for each day on which they have reached or exceeded their individual goal. Within the "one shot betting" condition, subjects are offered the option (which they can accept or decline) to deposit a percentage of their participation fee (20 Euro) to double this stake if they reach their goal on 90% of the days. In case the subjects accept this commitment device but fail, they lose their stake. In the last condition, "repeated betting", participants are offered to take part in a daily bet where they could earn additional money (0.25 Euro) for each day they achieve or exceed their goal and lose money (2.00 Euro) if they fail. By further observing participants’ physical activity once the incentives are removed, potential long-term effects and sustainable behavior changes are finally examined.
Experimental Design Details
Not available
Randomization Method
Randomization into the four treatment groups is done by a computerized random draw.
Randomization Unit
Individual
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
300 people
Sample size: planned number of observations
300
Sample size (or number of clusters) by treatment arms
75
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
German Association for Experimental Economic Research e.V.
IRB Approval Date
2019-10-19
IRB Approval Number
No. Hh86CJtC