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Description
Sticking to healthy behaviors is difficult. The lack of long-term behavior maintenance negatively impacts health outcomes and increases healthcare costs. Current methods for improving behavior maintenance yield varying and often limited results. This dissertation designs and tests quantitative methods for identifying behavioral strategies associated with long-term maintenance the long-term maintenance of three different health behaviors. Data were collected from three settings: mindfulness through a commercial app, walking from a randomized controlled trial, and pill-taking from a commercial app-based intervention. Novel pattern-detection methodologies were employed to measure temporal consistency and identify key behavioral strategies.
For mindfulness and walking behaviors, the impact of individual phenotypes on long-term behavior maintenance was analyzed. For medication adherence, the optimal window of time in which pills should be taken was empirically determined, and the impact of consistent timing on long-term medication adherence was analyzed. To perform these analyses, robust and regularized models, panel data models, statistical tests, and clustering algorithms were used. For mindfulness meditation, both consistent and inconsistent phenotypes were associated with long-term engagement. In the walking intervention, those with a consistent phenotype experienced greater increases in walking after the study than inconsistent individuals. However, the effect of consistency was strongest for individuals who either exercised less than 10 or more than 30 minutes per day. Lastly, in the medication adherence incentive program, consistently taking medication within 55 minutes of the goal time had the strongest association with future adherence.
This dissertation demonstrates that certain phenotypes are more advantageous than others for long-term maintenance and interventions. Temporal consistency is likely helpful for maintaining behaviors that offer delayed physical benefits, such as regular walking or medicating for chronic illnesses, but less helpful for cognitive behaviors like mindfulness, which can provide more immediate satisfaction. When designing interventions, the nature of the behavior and observable phenotypes should be taken into consideration. Generally, focusing on consistency is likely to contribute to long-term success; however, this is individual and context dependent. Future research should investigate this further by examining the relationship between behavioral phenotypes and psychological measurement tools to gain a deeper understanding of the successful maintenance of healthy behaviors.
ContributorsFowers, Rylan (Author) / Stetcher, Chad (Thesis advisor) / Chung, Yunro (Thesis advisor) / Ghasemzadeh, Hassan (Committee member) / Arizona State University (Publisher)
Created2023
Description
Chronic pain is common during childhood and has negative immediate and long-term implications for physical and mental health. Prior research points to physical activity and sleep as protective health-promoting behaviors predicting lower chronic pain intensity and disability during adulthood. No study has yet examined the interaction of physical activity and sleep parameters in prediction of chronic pain in a community sample of children. Guided by the biopsychosocial model of pediatric chronic pain, this study explored objectively assessed physical activity and sleep patterns at age 8 as predictors of childhood chronic pain at age 9 in a racially/ethnically and socioeconomically diverse sample of 896 twins participating in the longitudinal Arizona Twin Project. It was hypothesized that parameters of physical activity levels and sleep health would independently predict chronic pain one year later, and that sleep parameters would moderate the association between physical activity and chronic pain. Monthly chronic pain was common, with 57.1% of participants reporting at least one pain location. Headaches, stomachaches, and backaches were the most frequent chronic pain presentations. Participants exceeded physical activity guidelines but did not meet sleep recommendations for their age group. Multilevel modeling analyses revealed that physical activity and sleep parameters at age 8 did not predict chronic pain one year later, and that sleep parameters did not moderate the associations between physical activity and chronic pain. The present study provides evidence that the associations between objectively assessed physical activity and sleep and chronic pain are not yet evident during middle childhood in this community sample compared to patient samples who have existing pain, suggesting that these health behaviors may play distinct roles in pain development versus pain management. They also point to the need to pinpoint the time frame during which these health behaviors become relevant and potentially interact to predict chronic pain development and maintenance. Longitudinal research tracking these health behaviors and pain using both subjective and objective methods as children transition into and through adolescence can help to identify optimal developmental stages at which to target prevention and intervention efforts to promote long term health.
ContributorsBartsch, Eva Marie (Author) / Davis, Mary C (Thesis advisor) / Doane, Leah D (Committee member) / Lemery-Chalfant, Kathryn (Committee member) / Arizona State University (Publisher)
Created2023