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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

A Hierarchical Linear Modeling Approach to Predicting Trajectories of Posttraumatic Growth in Veterans Following Acquired Physical Disability

Goldberg Looney, Lisa 01 January 2017 (has links)
The purpose of this study was to examine potential predictors of PTG across time in Veterans with acquired physical disabilities. Specifically, this study aimed to understand how various demographic and injury characteristics, coping styles, appraisals of injury, and social support might predict trajectories of PTG from discharge from inpatient rehabilitation through 12 months after baseline. Initial curvature analyses suggested that a cubic polynomial trend best fit the movement of PTG over time, generally conforming to an initial increase, decrease, and then plateau or slight increase. Four HLMs were run to examine whether demographic and injury characteristics, coping styles, appraisals of injury, and social support predicted the height of this cubic architecture of PTG across baseline, 1, 3, 6, and 12-month follow ups, and a final HLM examined whether any statistically significant fixed effects in the first four HLMs interacted with time in the prediction of participants’ PTG trajectories. Estimated premorbid IQ was negatively associated, while age was positively associated with the height of PTG over time. Reframing and religious coping were positively associated with PTG over time, as were challenge appraisals. Three types of social support did not independently predict PTG trajectories, although bivariate correlations suggested the presence of isolated relationships between different types of social support and PTG at certain time points. None of the significant predictors interacted with time in predicting participants’ PTG trajectories.

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