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Neural Predictors of Exercise Adherence

Gujral, Swathi (2015) Neural Predictors of Exercise Adherence. Master's Thesis, University of Pittsburgh. (Unpublished)

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Abstract

Exercise is an important factor in maintaining physical and cognitive health throughout the lifespan. However, adherence to exercise regimens is poor with approximately 50% of older adults dropping out within 6 months, which makes it difficult to observe exercise-induced biological changes. Unfortunately, there are few known predictors for exercise adherence, but it is likely that a combination of social-cognitive factors, including self-efficacy, social support, personality traits, executive functions, and self-regulation all relate to exercise adherence. Importantly, all of these factors may rely upon the structural integrity of brain networks. In this study we tested whether grey matter volume prior to the initiation of an exercise intervention would predict adherence to the intervention. Participants included 159 adults aged 60-80 that were randomly assigned to either a moderate-intensity aerobic walking condition or a non-aerobic stretching and toning condition. Participants engaged in supervised exercise 3 times per week for 12 months. Structural magnetic resonance images were collected on individuals before randomization and used for analysis. An optimized voxel based morphometry (VBM) protocol was used to analyze gray matter volume using FSL. We used ordinary least squares regression models with bootstrapping using the Bootstrap Regression Analysis of Voxelwise Observations (BRAVO) toolbox to test the association between voxel-based grey matter volume and exercise adherence. We found a broad array of regions that significantly predicted exercise adherence (p<.01), including medial prefrontal cortex, superior parietal cortex, inferior temporal cortex, and cerebellum. Greater volume in these regions explained 20% of variance in adherence, above and beyond variance explained by self-efficacy. Our results suggest that greater gray matter volume predicts more successful adherence to a 12-month supervised exercise regimen.


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Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Gujral, Swathiswh24@pitt.eduSWH24
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairErickson, Kirk I.kiericks@pitt.eduKIERICKS
Committee MemberGianaros, Peter J.gianaros@pitt.eduGIANAROS
Committee MemberMarsland, Annamarsland@pitt.eduMARSLAND
Date: 8 June 2015
Date Type: Publication
Defense Date: 9 December 2014
Approval Date: 8 June 2015
Submission Date: 13 April 2015
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 57
Institution: University of Pittsburgh
Schools and Programs: Dietrich School of Arts and Sciences > Psychology
Degree: MS - Master of Science
Thesis Type: Master's Thesis
Refereed: Yes
Uncontrolled Keywords: Exercise Adherence, Brain, Self-Efficacy
Date Deposited: 08 Jun 2015 18:11
Last Modified: 15 Nov 2016 14:27
URI: http://d-scholarship.pitt.edu/id/eprint/24815

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