Behavioral Economic Attributes of Recreation (BEAR)
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About
Risk for developing and dying from heart disease, type 2 diabetes, stroke, and other cardiometabolic conditions is strongly influenced by behavioral risk factors, including poor diet, physical inactivity, and tobacco and alcohol abuse. Behavioral economic models predict engagement in these behaviors as a function of their subjective value, ability to provide immediate gratification, and availability of competing alternatives. A key implication of the behavioral economic model is that increasing the accessibility of compelling alternative sources of reinforcement may displace engagement in unhealthy behaviors. Developing interventions that leverage these insights requires both a clear understanding of the characteristics of the "reward landscape" of U.S. adults, and the impact of altering the reward landscape on behavioral economic processes and health behavior.
This pilot study uses a trial within a cohort (TwiC) design to pursue these objectives. A representative sample of adults (N=120) will be enrolled into an observational cohort. Cardiometabolic health will be assessed and quantified based on the Life's Essential 8 (LE8) scoring system,4 which includes 4 behavioral (physical activity, diet quality, sleep, tobacco use) and 4 biomedical (non-HDL cholesterol, glucose, weight status, and blood pressure) factors. Structured home audit tools and an ecological momentary assessment (EMA) protocol will be used to measure environmental access to, demand for, and engagement in various rewarding activities, including different categories of recreational activity, electronic entertainment, social activities, and consumable rewards including food, tobacco products, and alcohol. The inter-relationships between different types of rewarding behaviors as substitutes or complements, and their links with cardiometabolic health, will be examined overall and with stratification by socioeconomic status.
Following completion of the first assessment, a subset of participants will be selected for randomization to a recreation-focused intervention or continued observation within the cohort based on their baseline status and protocol adherence. In TwiC designs, the "control" group simply continues to complete observational assessments within the cohort and is not notified that an intervention is ongoing. The BEAR "intervention" group will be approached for consent to participate in a 6-month behavioral economic intervention in which recreational activities are promoted as a strategy to displace cardiometabolic risk behaviors. The scientific aims of the randomized trial component of the study include examining change in LE8 scores, demand for various rewarding activities, discounting rates, and health behaviors. BEAR will also address several feasibility aims, including demonstrating the ability to measure and categorize access to rewarding activities, document recreation-related expenditures by participants, and estimate intervention uptake and acceptability.
Full description
Behavioral risk factors such as poor diet, physical inactivity, and tobacco and alcohol abuse account for a significant proportion of chronic disease incidence in the U.S. and globally. Understanding the processes that drive engagement in these behaviors could inform individual-level and societal interventions aimed at reducing cardiometabolic risk. Behavioral economics offers several key insights that could be leveraged for this purpose. Contemporary behavioral economic models identify three processes that drive problematic levels of engagement in cardiometabolic risk behaviors:
Demand - the degree to which a behavior is valued or desirable Discounting - immediate rewards are preferred to delayed rewards Choice context - behaviors are selected from the landscape of available options
Individuals vary in the subjective value they place on different rewarding activities. People who find alcohol, drugs of abuse, junk food, and sedentary activity most reinforcing (demonstrate the greatest demand) engage in these behaviors more often. Delay discounting refers to the human preference for immediate rewards, which can lead to instances in which people select less preferred, immediately available options over more valued delayed alternatives. Such occurrences are called preference reversals. Preference reversals lead to engaging in behaviors that provide immediate gratification but increase cardiometabolic risk (e.g., smoking, binge watching TV) for two reasons. First, long-term health outcomes are highly devalued as they always occur months to years in the future relative to the point of decision. Second, competing options that might displace risk behaviors often require planning or preparation, and are therefore less immediately accessible (and therefore discounted in value) at key decision points. For example, the need to plan and prepare to go fishing, engage in a hobby, or socialize with a friend is not trivial compared to the virtually instant access to screens and junk food that most adults have. A third hypothesized influence on cardiometabolic risk behavior is the choice context, or the "reward landscape". Access to alternative reinforcers in the environment can dramatically affect the rate of engaging in target behaviors, particularly if those alternative reinforcers are "behavioral substitutes" that tend to displace the target behavior. A key implication of this behavioral economic model is that increasing access to compelling, immediately available alternative sources of reinforcement may displace engagement in unhealthy behaviors.
To date, interventions based on these insights have mostly focused on reducing substance use. The Icelandic Prevention Model achieved substantial reductions in adolescent substance use at the national level by increasing access to after school recreational programming in local communities. The substance-free activity session is a 2-session intervention that reduces problematic alcohol use by encouraging individuals to identify rewarding alternative behaviors (social activity, recreation, etc). Few studies have applied this approach to improve cardiometabolic health, despite the relevance of the behavioral economic model to eating, sedentary activity, tobacco use, and potentially other cardiometabolic risk factors such as poor sleep, depression, and physical activity.
We recently reported that promoting recreational activities (arts and crafts, puzzles, games, hobbies) as alternative sources of reinforcement reduced children's intake of junk food and use of electronic entertainment in a pilot study with 60 families. Similar studies in adults are lacking. Presumably, recreational activities (broadly defined) represent equally potent alternatives for displacing cardiometabolic risk behaviors in adults.
Interventions that leverage recreation to displace cardiometabolic risk behaviors have strong theoretical support, but further development is needed prior to their implementation. Specifically, intervention development would benefit from a more detailed characterization of the "reward landscapes" of the U.S. adult population. It is known that palatable food and screens dominate most choice contexts, but less is known about the accessibility, cost, and level of demand for various alternative rewarding behaviors, including those available in community settings vs. at home. The Behavioral Economic Attributes of Recreation (BEAR) pilot study includes an observational cohort component aimed at developing methods to characterize the reward landscapes of U.S. adults, and a pilot RCT designed to test preliminary effects of leveraging recreation to displace cardiometabolic risk behaviors.
The following specific aims are proposed:
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Test whether limited access to alternative reinforcing activities such as recreation is a risk factor for cardiometabolic health
- Characterize the association between access to alternative reinforcing activities and Life's Essential 8 (LE8) scores
- Identify specific behavioral pathways (diet, physical activity, sedentary time, sleep) linking recreation to health
- Test whether access to recreation accounts for socioeconomic differences in LE8 scores and cardiometabolic health behaviors
- Determine the relative contribution of community/neighborhood based vs. personal forms of recreation to health
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Examine whether uptake of recreation leads to a reduction in discounting rates or demand for cardiometabolic risk behaviors
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Evaluate the impact of recreation uptake on markers of cardiometabolic health
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Demonstrate the feasibility of relevant methods
- Develop and validate a theoretically meaningful framework for categorizing recreational activities
- Develop and refine a reliable methodology for documenting recreation-related expenditures
Enrollment
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Inclusion and exclusion criteria
Eligibility criteria for BEAR main cohort enrollment (N=120):
- Age 18 years or older
- Fluent in English
- Lives within 10 miles of the study site
- Not planning to move outside the study region in the next 6 months
- Has a working Android or iOS mobile device they are willing to use for EMA surveys and communication with the study team
- No apparent cognitive deficits that would suggest a lack of capacity to consent or complete study procedures
- No uncontrolled serious mental illness, marked by an inpatient hospitalization, increase or change in antipsychotic or mood stabilizing medication, or suicidal intent in the past 6 months.
Eligibility for selection into the RCT component (n=60):
- At least 75% adherence to EMA surveys during the initial assessment
- Complete baseline data within the observational cohort component
- Participant endorses engagement in recreation less than 4 times per week based on EMA surveys
- LE8 score <70, reflecting low to moderate cardiometabolic health.
- No serious substance abuse problem based on an ASSIST score of ≥27 for any substance other than tobacco or cannabis
- Willing and able to try recreational activities for the next 6 months
Trial design
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Interventional model
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120 participants in 2 patient groups
Trial contacts and locations
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Central trial contact
Bradley Appelhans, PhD
Data sourced from clinicaltrials.gov
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