|Title||Social Networks over the Life Course: Continuity, Context, and Consequences|
|Year of Publication||2018|
|Number of Pages||188|
|University||University of Michigan|
|City||Ann Arbor, MI|
|Keywords||0451:Social psychology, Lifespan, Psychology, Social psychology, Social relations|
Social relations have far-reaching influences on health and well-being across the lifespan. Social networks refer to the constellation of different interpersonal relationships that individuals maintain through their lives. Considering life course perspectives has illuminated the ways in which social networks develop and influence health and well-being at different life stages. The aim of this dissertation is to examine the multidimensionality, continuity, and consequences of social networks for well-being. The tenets of the convoy model are used as a guiding framework in conjunction with lifespan developmental perspectives to capture the unique challenges and circumstances of each developmental period examined. Most studies of children’s social relations focus on specific relationships, despite robust evidence that children’s social networks are comprised of a diverse range of social partners. The first study identified patterns of social relations among a regionally representative sample of children aged 7 to 14 (N=203), and investigated distinguishing sociodemographic factors between them. Further, links to childhood depressive symptomology were examined. Three typologies were identified: Varied Family (55%), Close Family (22.5%), and Friend and Family (22.5%). Whites were more likely to be in the Friend and Family networks. There were no other sociodemographic differences between typologies. Additionally, membership in the Friend and Family typology was associated with greater depressive symptomology, but this link was not observed after accounting for significant life events. The findings highlight the importance of family-centric networks in childhood. Previous studies document differences in social networks across the lifespan, but longitudinal studies of intraindividual change in social networks are limited. The second study investigated continuity in social networks from childhood to adulthood using three waves of longitudinal data spanning 23 years. Results of growth curve analyses indicated that the majority of social network characteristics changed. Four patterns of social networks were identified in early adulthood (Mage=23): Diverse Distal, Varied Family, Close Family, and Friend-Focused. Descriptive data on transitions between social network patterns from childhood to adulthood suggest that most respondents experienced an expansion and diversification of social networks. This study demonstrated that changes in social networks from childhood to adulthood are consistent with the developmental goals of the transition to adulthood. The third study focused on older adults’ social networks and loneliness. Given the prominence of activity engagement in models of successful and active aging, the broader social integration derived from activity engagement was expected to protect against loneliness. The purpose of this study was to identify activity engagement patterns, and use these patterns to disentangle links between activity engagement, social network characteristics, and loneliness. Three classes of activity engagement were identified in a sample from the Health and Retirement Study (N=7,731): Restricted Activities (24%), Average Activities (46%), and Diverse Activities (30%). Activity engagement had direct and moderating effects on loneliness. Specifically, diverse activity engagement buffered the negative effects of having few close ties with children. These findings suggest that social integration through activity engagement may compensate for inadequate social networks. Taken together, these findings underscore the importance of studying social networks with a consideration for the developmental context in which they are formed, evolve, and exert influences on well-being. Using innovative pattern-centered approaches, these studies illuminate alternative ways of conceptualizing and measuring social networks. Findings from this dissertation provide insight into how social networks can be most effectively leveraged to promote successful development and aging.
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