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Clinical Trial Details — Status: Recruiting

Administrative data

NCT number NCT05948709
Other study ID # 805439
Secondary ID P30AG024968
Status Recruiting
Phase N/A
First received
Last updated
Start date November 3, 2023
Est. completion date January 15, 2025

Study information

Verified date May 2024
Source University of California, San Diego
Contact n/a
Is FDA regulated No
Health authority
Study type Interventional

Clinical Trial Summary

Inactivity is the fourth leading risk factor for global mortality, leading to chronic diseases. Much of the world's population is inactive, and older adults are at highest risk. Incentive-based interventions show promise for improving activity levels. The investigators propose to conduct a study to evaluate the impact of incentives on physical activity of older adults (55 and above). Half the participants will receive additional incentives for walking throughout the study. Their step count and physical/mental health will be compared to a control group. The investigators will track the physical activity of participants using Fitbits and will encourage physical activity through making meal donations on behalf of participants (prosocial incentives) and giving them gift cards that can be redeemed at local businesses (personal incentives). Physical and mental health before and after the study will also be assessed using a written survey.


Description:

Inactivity is the fourth leading risk factor for global mortality, leading to chronic diseases (e.g., heart disease, diabetes) and contributing to the obesity epidemic. Much of the world's population is inactive and older adults are at highest risk. Inactivity in older adults is linked to age-related diseases and cognitive decline. Inactivity also imposes social costs through increased medical expenses, which are already high among the growing older adult population in the US. 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.


Recruitment information / eligibility

Status Recruiting
Enrollment 200
Est. completion date January 15, 2025
Est. primary completion date November 15, 2024
Accepts healthy volunteers Accepts Healthy Volunteers
Gender All
Age group 55 Years and older
Eligibility Inclusion Criteria - 55 years old or older - 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 - below 55 years - 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.

Study Design


Related Conditions & MeSH terms


Intervention

Other:
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.

Locations

Country Name City State
United States Northgate Market Barrio Logan San Diego California
United States Northgate Market National City San Diego California

Sponsors (3)

Lead Sponsor Collaborator
University of California, San Diego National Institute on Aging (NIA), University of Southern California

Country where clinical trial is conducted

United States, 

References & Publications (20)

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. — View Citation

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. — View Citation

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. — View Citation

Charness, G. and U. Gneezy, Incentives to exercise. Econometrica, 2009. 77(3): p. 909-931.

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. — View Citation

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. — View Citation

Deci, E.L., Effects of externally mediated rewards on intrinsic motivation. Journal of personality and Social Psychology, 1971. 18(1): p. 105.

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.

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.

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. — View Citation

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. — View Citation

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.

Pew Research Center: Internet, Science, & Tech. Demographics of Mobile Device Ownership and Adoption in the United States. 2021, Pew Research Center.

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.

Schneider EL, Guralnik JM. The aging of America. Impact on health care costs. JAMA. 1990 May 2;263(17):2335-40. — View Citation

Steffick, D.E., Documentation of affective functioning measures in the Health and Retirement Study. Ann Arbor, MI: HRS Health Working Group, 2000.

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. — View Citation

Thaler, R., Mental accounting and consumer choice. Marketing science, 1985. 4(3): p. 199-214.

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. — View Citation

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. — View Citation

* Note: There are 20 references in allClick here to view all references

Outcome

Type Measure Description Time frame Safety issue
Primary Change in step count Indicator of change in physical activity, recorded daily using Fitabase and averaged across a week. A baseline step count at the beginning of the study will be compared to the step count at the end of the study. Week 1 and week 6.
Secondary Change in CES-D (Center for Epidemiologic Studies Depression Scale) Score Measured during baseline and endline survey, indicator of mental health. CES-D scores range from 0-60, with higher scores being more indicative of depression. Week 1 and week 6.
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