Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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TERMINATED
NA
70 participants
INTERVENTIONAL
2023-11-03
2024-11-18
Brief Summary
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Detailed Description
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Incentive-based interventions have gained popularity among behavioral scientists and policymakers as a tool for improving health-related behaviors. But there are drawbacks - first, monetary incentives are often not cost-effective, and therefore scalability is limited. Second, behaviors often return to baseline when monetary incentives are removed, i.e., healthy habits are hard to maintain when incentives are limited in duration. Third, there is a concern that monetary incentives crowd out intrinsic motivation to engage in health-promoting behaviors.
In light of the limited success of incentive-based behavior change programs, the investigators propose to design and evaluate alternative incentives that address these challenges of scalability, habit formation and crowd-out. The investigators will aim to encourage physical activity through alternative incentives - by making a meal donations on behalf of participants (prosocial incentives) and give participants monetary incentives (personal incentives). Both types of incentives have underpinnings in behavioral economics.
Meal donations harness prosocial preferences, which may be more powerful and less likely to reduce intrinsic motivation than equivalent monetary incentives.
The overall aim is to evaluate the impact of alternative incentives on step count of older adults in the short-term and long-term. Exploratory analysis will also evaluate the impact on physical and mental health. The investigators will recruit 200 older adults and randomize half of them to receive additional prosocial and personal incentives for their walking behavior. The other half will not receive these incentives. The investigators will track step count of these two groups for 8 weeks using a Fitbit device. Under the treatment functionality, participants accrue a meal donation and a point for Feeding America for each day that they meet the step goal.
The investigators plan to recruit older adults ages 55 and above at grocery stores and other locations around San Diego, CA. Recruitment will be on a rolling basis. PI Samek has recruited participants at grocery stores in prior studies, hence the investigators believe this is feasible. Participation will be limited to individuals who own a smart phone (61% of older adults in the US own a smart phone, and the investigators expect this number to grow as the population ages). Studies have shown that older adults are open to using app-based technologies, for example older adults are accepting of mindfulness apps.
The research team will be given access to participants' Fitbit data through Fitabase, a research platform that collects data from internet connected consumer activity devices. The investigators identified 7,500 steps as an appropriate goal as studies show older adults walk 4,000 steps on average. For the treatment group, meals will be donated by the research team to Feeding America for each day they meet the step goal of 7,500 steps. They will also receive money for each day they meet the step goal of 7,500 steps a day, for up to 5 days a week. The control group will not receive these incentives for their walking behavior, but their daily step count data will be collected.
Participants will receive a Fitbit upon enrollment. The investigators will collect their physical activity data for 1 week, as their baseline physical activity. After 1 week, individuals who on average less than 6000 per day, will be randomized to the treatment group, which receives the incentives for 4 weeks, or to a control group which does not.
The investigators will also collect follow up data for 1 weeks.
Individuals who on average walk more than 6000 steps per day during the 1 week baseline period will be dropped from the study.
Conditions
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Study Design
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RANDOMIZED
PARALLEL
OTHER
NONE
Study Groups
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Treatment
Fitabase collects data from Fitbits worn by the participants. Under the treatment functionality, participants earn a meal donation for each day that they meet the step goal and a monetary incentive for each day they meet the step goal (for upto 5 days a week). The investigators identified 7,500 steps as an appropriate goal as studies show older adults walk 4,000 steps on average. Meals are donated by the investigators on behalf of participants.
Incentives for Physical Activity
Participants earn a meal donation and monetary incentives for each day that they reach 7,500 steps. Meals are donated by the investigators on behalf of participants.
Control
The control group will not have the functionality to earn meal donations or monetary incentives by walking, and will only be asked to wear their Fitbit so that step count data can be collected.
No interventions assigned to this group
Interventions
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Incentives for Physical Activity
Participants earn a meal donation and monetary incentives for each day that they reach 7,500 steps. Meals are donated by the investigators on behalf of participants.
Eligibility Criteria
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Inclusion Criteria
* own a smartphone
* can walk independently
* how often they walked outside their home or yard for fun or exercise in the past week - Never, Seldom (1-2 days), Sometimes (3-4 days), or Often (5-7 days)? They can participate if they respond never or seldom.
Exclusion Criteria
* do not own a smartphone
* unable to walk independently
* how often they walked outside their home or yard for fun or exercise in the past week
* Never, Seldom (1-2 days), Sometimes (3-4 days), or Often (5-7 days)? They can not participate if they respond sometimes or often.
55 Years
ALL
Yes
Sponsors
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National Institute on Aging (NIA)
NIH
University of Southern California
OTHER
University of California, San Diego
OTHER
Responsible Party
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Anya Samek
Associate Professor of Economics and Strategy
Locations
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Northgate Market Barrio Logan
San Diego, California, United States
Northgate Market National City
San Diego, California, United States
Countries
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References
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Watson KB, Carlson SA, Gunn JP, Galuska DA, O'Connor A, Greenlund KJ, Fulton JE. Physical Inactivity Among Adults Aged 50 Years and Older - United States, 2014. MMWR Morb Mortal Wkly Rep. 2016 Sep 16;65(36):954-8. doi: 10.15585/mmwr.mm6536a3.
Thaler, R., Mental accounting and consumer choice. Marketing science, 1985. 4(3): p. 199-214.
Cunningham C, O' Sullivan R, Caserotti P, Tully MA. Consequences of physical inactivity in older adults: A systematic review of reviews and meta-analyses. Scand J Med Sci Sports. 2020 May;30(5):816-827. doi: 10.1111/sms.13616. Epub 2020 Feb 4.
de Rezende LF, Rey-Lopez JP, Matsudo VK, do Carmo Luiz O. Sedentary behavior and health outcomes among older adults: a systematic review. BMC Public Health. 2014 Apr 9;14:333. doi: 10.1186/1471-2458-14-333.
Bherer L, Erickson KI, Liu-Ambrose T. A review of the effects of physical activity and exercise on cognitive and brain functions in older adults. J Aging Res. 2013;2013:657508. doi: 10.1155/2013/657508. Epub 2013 Sep 11.
Carlson SA, Fulton JE, Pratt M, Yang Z, Adams EK. Inadequate physical activity and health care expenditures in the United States. Prog Cardiovasc Dis. 2015 Jan-Feb;57(4):315-23. doi: 10.1016/j.pcad.2014.08.002. Epub 2014 Aug 9.
Schneider EL, Guralnik JM. The aging of America. Impact on health care costs. JAMA. 1990 May 2;263(17):2335-40.
Charness, G. and U. Gneezy, Incentives to exercise. Econometrica, 2009. 77(3): p. 909-931.
Volpp KG, John LK, Troxel AB, Norton L, Fassbender J, Loewenstein G. Financial incentive-based approaches for weight loss: a randomized trial. JAMA. 2008 Dec 10;300(22):2631-7. doi: 10.1001/jama.2008.804.
Tambor M, Pavlova M, Golinowska S, Arsenijevic J, Groot W. Financial incentives for a healthy life style and disease prevention among older people: a systematic literature review. BMC Health Serv Res. 2016 Sep 5;16 Suppl 5(Suppl 5):426. doi: 10.1186/s12913-016-1517-0.
Mantzari E, Vogt F, Shemilt I, Wei Y, Higgins JP, Marteau TM. Personal financial incentives for changing habitual health-related behaviors: A systematic review and meta-analysis. Prev Med. 2015 Jun;75:75-85. doi: 10.1016/j.ypmed.2015.03.001. Epub 2015 Apr 2.
Gneezy, U., S. Meier, and P. Rey-Biel, When and why incentives (don't) work to modify behavior. The Journal of Economic Perspectives, 2011. 25(4): p. 191-209.
Deci, E.L., Effects of externally mediated rewards on intrinsic motivation. Journal of personality and Social Psychology, 1971. 18(1): p. 105.
Marcel Bilger, E.F., Uri Gneezy, Ho Teck Hua, Increasing the Effectiveness of Incentives by Changing Their Meaning: A Mental Accounting Mechanism for Behavior Change. Work in progress., 2017.
Bassett DR Jr, Wyatt HR, Thompson H, Peters JC, Hill JO. Pedometer-measured physical activity and health behaviors in U.S. adults. Med Sci Sports Exerc. 2010 Oct;42(10):1819-25. doi: 10.1249/MSS.0b013e3181dc2e54.
Fonda, S. and A.R. Herzog, Documentation of physical functioning measured in the Health and Retirement Study and the Asset and Health Dynamics among the Oldest Old Study. Ann Arbor: University of Michigan Survey Research Center, 2004.
Steffick, D.E., Documentation of affective functioning measures in the Health and Retirement Study. Ann Arbor, MI: HRS Health Working Group, 2000.
Sadoff S, Samek A, & C Sprenger. Dynamic Inconsistency in Food Choice: Experimental Evidence from Two Food Deserts. The Review of Economic Studies, 2020. 87(4): p. 1954-1988.
Pew Research Center: Internet, Science, & Tech. Demographics of Mobile Device Ownership and Adoption in the United States. 2021, Pew Research Center.
Mahlo L, Windsor TD. Feasibility, Acceptability, and Preliminary Efficacy of an App-Based Mindfulness-Meditation Program Among Older Adults. Gerontologist. 2021 Jul 13;61(5):775-786. doi: 10.1093/geront/gnaa093.
Other Identifiers
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805439
Identifier Type: -
Identifier Source: org_study_id