Physical inactivity is a major contributor to increased disease prevalence and reduced quality of life. Measuring behavioral economic demand for exercise may enable more effective physical activity intervention development. In study one, we developed the leisure-time-as-price exercise purchase task (LT-EPT), wherein participants (n = 175) indicate hypothetical likelihood to trade leisure time for access to exercise time. We observed weak to moderate correlations between demand indices (Q1%, α, BP1, and Pmax) generated from the LT-EPT and self-reported leisure and exercise time, demonstrating initial validation of the LT-EPT. In study two, we examine the effect of episodic future thinking (EFT; vivid, personalized prospection of future events) in adults not meeting physical activity guidelines (n = 127) on demand for exercise and delay discounting (sensitivity to delayed rewards). We observed reduced delay discounting in participants randomized to engage in EFT, but no difference between EFT and health information thinking (HIT) controls. In study three, we further examined the effect of EFT on demand for exercise in adults with type 2 diabetes and obesity participating in a 24-week randomized controlled trial (n = 71). All participants engaged in a multicomponent behavioral intervention focused on weight loss and glycemic control; additionally, participants were randomized to engage in EFT or HIT thrice daily beginning in week 3. We measured demand for exercise and delay discounting (among other outcomes) at weeks 0, 8, and 24, observing no differences between EFT or HIT groups in demand indices (Q1%, α) or delay discounting at any time point. In conclusion, early evidence suggests that the LT-EPT may be a valid method to measure behavioral economic demand for exercise; however, EFT may not be an effective intervention to increase demand for exercise. / Doctor of Philosophy / Physical inactivity poses a significant threat to our well-being, contributing to increased disease rates and a diminished quality of life. This dissertation details a novel method to measure how people value exercise and the effect of a behavioral intervention to increase exercise valuation. In the first study, we introduce the leisure-time-as-price exercise purchase task (LT-EPT), a tool designed to gauge individuals' willingness to trade leisure time for exercise time (i.e., exercise demand). Initial results show promising correlations between LT-EPT metrics and self-reported leisure and exercise time, providing a foundation for its potential as a valuable measurement tool. The second study examines the impact of episodic future thinking (EFT), a technique involving vivid and personalized visualization of future events, on exercise demand. While participants engaging in EFT showed increased preference for larger, delayed rewards over smaller, sooner rewards (i.e., reduced delay discounting), no significant difference was found between EFT and the health information thinking (HIT) control in terms of exercise demand. The third study expands our investigation to adults with type 2 diabetes and obesity undergoing a 24-week intervention. All participants engaged in a comprehensive behavioral program, while half were randomized to engage in EFT or HIT three times per day. No discernible differences were observed in exercise demand or delay discounting at any measurement point. In summary, our findings suggest that the LT-EPT may be a valid measure of exercise demand. However, the effectiveness of EFT in increasing demand for exercise remains inconclusive. These insights contribute to the ongoing efforts to develop more targeted and impactful interventions for promoting physical activity and improving overall health.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/118837 |
| Date | 06 May 2024 |
| Creators | Brown, Jeremiah M. |
| Contributors | Human Nutrition, Foods and Exercise, Stein, Jeffrey S., Rockwell, Michelle S., DiFeliceantonio, Alexandra Gold, Davis, George C. |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Dissertation |
| Format | ETD, application/pdf |
| Rights | Creative Commons Attribution 4.0 International, http://creativecommons.org/licenses/by/4.0/ |
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