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Understanding Unpredictable Chronic Illness and its Links to Posttraumatic Stress and Growth: The Case of Multiple Sclerosis

The present study was conducted to help understand the impact of living with multiple sclerosis (MS), an unpredictable, chronic illness that is widely known to have a large influence on psychosocial functioning, mental health, and life satisfaction (Motl & Gosney, 2007; Weiner, 2004). Recent research has begun to position certain chronic illnesses, such as MS, as traumatic events that influence mental health in both beneficial and detrimental ways. Thus, the present study investigated the positive and negative consequences of centralizing one’s identity within their MS experiences as related to trauma, growth, and psychosocial influences via a path model with 616 individuals with MS. The results indicate strong support for the hypothesized paths between the variables of interest—centrality of MS, posttraumatic stress, posttraumatic growth, social support, personal mastery, depression, and life satisfaction. Specifically, results indicate that posttraumatic stress and posttraumatic growth partially mediated the relations between centrality of MS with depression and life satisfaction. Moderation analyses indicated that social support and personal mastery did not moderate any relations between centrality of MS with depression and life satisfaction. Rather, additional analyses suggest social support and personal mastery may be viewed as additional mediators between centrality and posttraumatic stress and posttraumatic growth. The results of the present study is the first known study to extend trauma literature to the population of MS in order to provide an approach to help understand the high rates of depression and inconsistent findings on quality of life for this population. Implications for practice, theory and research are discussed.

Identiferoai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/D8JM29WB
Date January 2016
CreatorsEsposito, Jessica
Source SetsColumbia University
LanguageEnglish
Detected LanguageEnglish
TypeTheses

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