Multiple Sclerosis (MS) is a chronic neurological condition, which affects around 2.5 million people worldwide. At a time when there is yet no recognised cure, it is imperative that MS patients learn to cope and adjust well to living with the illness. However, research has found high rates of psychological distress associated with MS (Minden & Schiffer, 1991). This highlights the need for research to investigate the psychological factors, which make MS patients vulnerable to psychological distress. One popular social cognition model called the Self-Regulation Model (Leventhal et al., 1980) has been found to successfully predict adjustment in a range of chronic illnesses. However, previous research applying the SRM to understand adjustment to MS has been limited. The current research therefore represented the first attempt to successfully apply the full SRM to an MS population prospectively. The present thesis is comprised of three studies and employed a mixed quantitative and qualitative research design method. Studies 1 (N=103) and 3 (N=150) were both quantitative studies, which applied an extended SRM model to clinical samples of MS patients and assessed indices of psychological distress over time. Study 2 (N=15) however was a qualitative study, designed to investigate MS patients experiences of living with the condition. By combining both quantitative and qualitative methods, the findings provided a fuller understanding of the psychological factors underlying successful adjustment to MS. Overall the findings provided some support for the utility of the extended SRM in predicting adjustment to MS and highlighted the importance of positive mind states and acceptance for successful adjustment to the condition. The findings also had a number of clinical implications, which are also discussed.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:513718 |
| Date | January 2008 |
| Creators | Fergusson-White, Christy A. J. |
| Contributors | O'Connor, Rory C. |
| Publisher | University of Stirling |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/1893/471 |
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