Abstract

BackgroundThe decision to initiate or maintain a healthy habit, such as physical activity involves a trade-off between a short-term cost, such as time and effort, which are commonly identified as barriers to physical activity, and a long-term health benefit. Research suggests that individual time preference may be associated with unhealthy behaviors. However, empirical evidence of this for physical activity is scant. This study investigated the relationship between time preference and physical activity, and how this might influence behavior change.MethodsEmployees (n = 176; mean age 42.2 years) who participated in a physical activity intervention were invited to take part in a behavioral economic field experiment. Two economic experiments, using multiple price lists and monetary trade-off tables involving real money choices, were conducted face-to-face with participants to measure the two components of time preference, namely present-bias and discount rate. Together with individual risk preferences, these three variables were jointly estimated by maximum likelihood. These three parameters were expressed as a linear function of the levels of physical activity while controlling for socio-demographic variables within the same maximum likelihood framework.ResultsThose who were present-biased and who had higher discount rates did significantly less physical activity than their patient and non present-biased counterparts. A 3% lower discount rate and 1.14 unit decrement in the present-bias parameter was associated with a 30 min increase of physical activity per week. This negative association was more significant for certain sub-groups, such as younger and married adults and those with higher staff grade and those who have children. Participants who dropped out of the study earlier were more present-biased.ConclusionsResults demonstrated that discount rate and present-biasedness have a significant impact on physical activity levels. Such concepts have been largely overlooked and underutilized in physical activity interventions. Promising implications include 1) utilizing individuals’ time preferences to better target interventions; 2) taking account of time preferences in the intervention design; 3) interventions attempting to correct for present-biasedness.

Highlights

  • The decision to initiate or maintain a healthy habit, such as physical activity involves a trade-off between a short-term cost, such as time and effort, which are commonly identified as barriers to physical activity, and a long-term health benefit

  • The physical activity loyalty (PAL) scheme The Physical Activity Loyalty (PAL) card scheme (12-week intervention) was a quasi-experimental study where 406 office-based employees from a workplace setting were each given a loyalty card to monitor their physical activity levels during office hours, by swiping their card at sensors placed along designated routes within the grounds of their workplace [27]

  • Utilizing time preferences for behavior change Our results suggest that understanding time preferences has implications for physical activity behavior change and should be utilized to help target interventions more effectively

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Summary

Introduction

The decision to initiate or maintain a healthy habit, such as physical activity involves a trade-off between a short-term cost, such as time and effort, which are commonly identified as barriers to physical activity, and a long-term health benefit. This study investigated the relationship between time preference and physical activity, and how this might influence behavior change. Changing health-related behaviors is not straight forward and there have been a number of high level government reports [2], and influential academic literature that invokes the need to seek innovative and effective interventions by integrating much broader behavioral economics, psychological and socioecological theories [3,4,5]. The UK Government has supported the role of behavioral economics (i.e. the intersection of psychology and economics) [7]. Such approaches have shown potential in public health [8]; we know little about how best to utilize and “exploit” such approaches for population level behavior change

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