Understanding the dynamic nature of well-being: a multilevel SEM framework to capture intra- and inter-individual associations across multiple timescales and levels of analysis

dc.contributor.authorRush, Jonathan
dc.contributor.supervisorHofer, Scott M.
dc.date.accessioned2018-05-18T18:16:51Z
dc.date.copyright2018en_US
dc.date.issued2018-05-18
dc.degree.departmentDepartment of Psychologyen_US
dc.degree.levelDoctor of Philosophy Ph.D.en_US
dc.description.abstractThe study of well-being has a long history of investigation from a nomothetic (between-person) perspective that aimed to understand characteristic levels of well-being and individual difference variables that account for stable differences across people. Recent investigations have demonstrated that levels of well-being have the capacity to rapidly fluctuate within people over short intervals and also exhibit slower changes over longer intervals, highlighting the importance of considering the ideographic (within-person) nature of well-being. The aim of this dissertation was to help build on such within-person understanding by demonstrating how theories of well-being may be empirically evaluated using innovative research designs (e.g., intensive repeated measurement designs) and analytic techniques (e.g., multilevel structural equation models [MSEM]) that can fully capture the complexity and dynamic nature of well-being. Three distinct research studies employing intensive repeated measurement designs and an MSEM analytic framework addressed a variety of research questions concerning intra- and inter-individual predictors of well-being. Study one (Chapter 2) simultaneously examined the multilevel moderation and mediation effects of cognitive interference on stress reactivity estimated in a 14-day daily diary design. Study two (Chapter 3) utilized measurement burst data from a large U.S. sample of adults, assessed across multiple time-scales, to examine long-term changes in short-term within-person associations. Random within-person slopes were specified as exogenous predictor variables of individual differences in global levels of psychological well-being. Study three (Chapter 4) used simulation data to examine the conditions where specifying within-person measurement scales as latent variables compared to unit-weighted composite scores optimized detection of within-person effects. This dissertation demonstrates the importance of innovative design and analysis to appropriately model and understand the complex, dynamic associations that operate within and across individuals in predicting their experiences of well-being.en_US
dc.description.embargo2019-05-14
dc.description.scholarlevelGraduateen_US
dc.identifier.urihttp://hdl.handle.net/1828/9384
dc.languageEnglisheng
dc.language.isoenen_US
dc.rightsAvailable to the World Wide Weben_US
dc.subjectmultilevel structural equation modelingen_US
dc.subjectstress reactivityen_US
dc.subjectintensive measurement designsen_US
dc.subjectwell-beingen_US
dc.titleUnderstanding the dynamic nature of well-being: a multilevel SEM framework to capture intra- and inter-individual associations across multiple timescales and levels of analysisen_US
dc.typeThesisen_US

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Rush_Jonathan_PhD_2018.pdf
Size:
1.93 MB
Format:
Adobe Portable Document Format
Description:
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description: