Graduate Thesis Or Dissertation
 

A Bioecological Model of Grief Recovery : Theory and Test of the Model

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https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/1n79h744d

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  • A primary aim of bereavement research is to alleviate suffering and promote well-being at the junction of life and death for the survivor in an attachment relationship. Bereavement research in the last decade has focused primarily on examining grief recovery within the context of intrapersonal processes. This emphasis has often ignored peer, family, and cultural influences on adjustment to loss. As a result, targeted grief interventions have largely been limited to adaptive and maladaptive factors within the individual. Evidence from recent research suggests the importance of taking into account contextual factors within the social environment that have bidirectional influences on the individual, and function as potential deficits or resources for grief recovery over time. Thus, a comprehensive framework for the simultaneous consideration of person-environment transactions, rather than just a strict emphasis on intrapersonal processes, is essential to advancing the current understanding of grief recovery. To address this gap, this study presents a bioecological model of grief recovery with the addition of a 'loss system' level of influence--capturing characteristics of the deceased, circumstances of the death, and the relationship between the bereaved and the deceased prior to the death--to simultaneously account for the person- and environment-level systems of influence. The implications of this theoretical model are described for two different types of loss: death of spouse in older adults and death of a child. To move this model from theory to real-world application, the viability of the model was tested by empirically contrasting it with an individual-level (intrapersonal) model of grief recovery as applied to spousal bereavement in later life. An archived longitudinal data set (the Changing Lives of Older Couples data) was the basis for growth curve models examining the trajectory of grief several years after death of spouse. The individual-level model focused on the intrapersonal predictors known to influence grief recovery, while the bioecological model included the same intrapersonal predictors as well as loss system predictors. In sum, the analyses provided evidence that having relatively high levels of death acceptance and religiosity prior to the death of a spouse is associated with improved psychological health in the early stages of widowhood. Although the bioecological growth curve model did not evidence a better fit than the individual model in this study, it remains a useful framework accounting for a broader range of influences, with the loss system as a key to advancing bereavement research. Moreover, psychological adjustment to the death of a loved one is merely one type of life event that can be understood using this model of grief recovery. Although the theoretical and empirical models presented here represent only a limited approximation of the more complex phenomena of a human reaction when a spouse dies, it provides a new, more comprehensive framework for understanding grief and how it changes over time. Perhaps its greatest utility lies in its theoretical conceptualization of a loss system, and how that loss system can be tested using growth curve statistical models as described in Manuscript 2. This novel approach holds great promise for bereavement researchers. In addition, Manuscript 1 showed how researchers can adapt this framework to model different types of loss experiences, particularly those with strong parallels to the death of a loved one, such as relationship dissolution and divorce. Similarly, this model could be applied empirically to loss experiences such as progressive illness, disability, infertility, and disaster. Variables included in the bioecological systems should be modified accordingly to reflect and allow measurement of the type of loss, life circumstances, culture, and context of the population under study.
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