Theses and Dissertations
This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students.
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- All Subjects: Social Support
Description
Spousal loss is a common, significant life event that can negatively affect multiple facets of individual health and psychological adjustment. Social support is one factor that is shown to improve adjustment following spousal loss, but much less is known regarding which facet of social support is most predictive of positive adjustment outcomes following spousal loss. This study examined the course of changes in mental health and well-being following spousal loss and which facets of social support are associated with better outcomes following spousal loss. Latent growth curve modeling was applied to data from 265 widowed individuals, ages 65 and older, across four assessments (baseline, and 6-, 18-, and 48- months following spousal loss). I examined the following research questions: (1) adjustment following spousal loss will follow a trajectory of an increase in depressive symptoms and anxiety and decrease in well-being with a leveling-off over time, with between-person differences, and (2) emotional support and instrumental support given will lead to more positive adjustment outcomes over time. Depressive symptoms followed the hypothesized trajectory but anxiety and well-being showed relative stability before and after spousal loss. Instrumental support was the most beneficial facet of social support, such that receiving more instrumental support was associated with lower levels of depressive symptoms and anxiety 6-months following spousal loss. Giving more instrumental support led to an increase in well-being following spousal loss. Instrumental support given and received led to increases in well-being as a function of spousal loss. The discussion focuses on whether and how these findings can help to identify ways through which support and help can be given to individuals to improve adjustment to spousal loss and fully recover.
ContributorsSullivan, Colleen Elizabeth (Author) / Infurna, Frank (Thesis director) / Luthar, Suniya (Committee member) / Davis, Mary (Committee member) / Department of Psychology (Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
Description
Built upon Control Value Theory, this dissertation consists of two studies that examine university students’ future-oriented motivation, socio-emotional regulation, and diurnal cortisol patterns in understanding students’ well-being in the academic-context. Study 1 examined the roles that Learning-related Hopelessness and Future Time Perspective Connectedness play in predicting students’ diurnal cortisol patterns, diurnal cortisol slope (DS) and cortisol awakening response (CAR). Self-reported surveys were collected (N = 60), and diurnal cortisol samples were provided over two waves, the week before a mid-term examination (n = 46), and the week during students’ mid-term (n = 40). Using multi-nomial logistic regression, results showed that Learning-related Hopelessness was not predictive of diurnal cortisol pattern change after adjusting for key covariates; and that Future Time Perspective Connectedness predicted higher likelihood for students to have low CAR across both waves of data collection. Study 2 examined students’ future-oriented motivation (Future Time Perspective Value) and socio-emotional regulation (Effortful Control and Social Support) in predicting diurnal cortisol patterns over the course of a semester. Self-reported surveys were collected (N = 67), and diurnal cortisol samples were provided over three waves of data collection, at the beginning of the semester (n = 63), during a stressful academic period (n = 47), and during a relaxation phase near the end of the semester (n = 43). Results from RM ANCOVA showed that Non-academic Social Support was negatively associated with CAR at the beginning of the semester. Multi-nomial logistics regression results indicated that Future Time Perspective Value and Academic Social Support jointly predicted CAR pattern change. Specifically, the interaction term marginally predicted a higher likelihood of students switching from having high CAR at the beginning or stressful times in the semester to having low CAR at the end the semester, compared to those who had low CAR over all three waves. The two studies have major limits in sample size, which restricted the full inclusion of all hypothesized covariates in statistical models, and compromised interpretability of the data. However, the methodology and theoretical implications are unique, providing contributions to educational research, specifically with regard to post-secondary students’ academic experience and well-being.
ContributorsCheng, Katherine C (Author) / Husman, Jenefer (Thesis advisor) / Lemery-Chalfant, Kathryn (Committee member) / Granger, Douglas (Committee member) / Eggum-Wilkens, Natalie D (Committee member) / Pekrun, Reinhard (Committee member) / Arizona State University (Publisher)
Created2017