Patients’ beliefs about their illness are known to influence their experiences of illness, its psychological impact, their health behaviours, and overall health outcomes. Research into illness beliefs has typically involved written or oral methods, yet recent studies have suggested that patients’ beliefs about their illness may be embodied in visual form, in their mental images of the disease. Beliefs embedded in mental images may not be captured via traditional modes of assessment, and thus far the possible significance of this kind of ‘visual knowledge’, has been largely overlooked. Studies using visual methods to explore patients’ mental images suggest this is a viable and useful approach which may provide additional insights into their illness beliefs. Research of this kind is in its infancy however, and there are several fundamental questions concerning the existence and nature of mental images, how best to access such images, and their relationship to illness beliefs, which are as yet unanswered. This thesis employed qualitative methods to address these issues and explore the significance of mental images within the context of head and neck cancer. It consists of three empirical phases – a methodological pilot study, a qualitative meta-synthesis, and a longitudinal study. The findings indicate that many patients do generate a mental image of their cancer, and this is significant in terms of their understanding of both the disease and its treatments. Images appear to enhance patients’ comprehension of what is going on inside their bodies, and may both reflect and influence illness beliefs. In this thesis these findings are considered with reference to the methodological issues intrinsic to researching mental images, and the implications for future research and clinical practice.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:578752 |
Date | January 2010 |
Creators | Lang, Heidi |
Contributors | Humphris, Gerry M. |
Publisher | University of Dundee |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | https://discovery.dundee.ac.uk/en/studentTheses/c17cd584-34b2-46bc-8290-b8cd3e6ad2c4 |
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