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Title: Developing a model of quality of life for people with coronary heart disease
Author: Lin, Zin-Rong
ISNI:       0000 0001 3610 4301
Awarding Body: Loughborough University
Current Institution: Loughborough University
Date of Award: 2001
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Quality of life (QOL) is an extremely important concept in the promotion of appropriate and successful health care programmes. However, there is a need for conceptual clarity to unravel the complexities of terminology in different medical conditions and the underlying factors that have a direct influence on the quality of life for people with coronary heart disease. The primary objective of this thesis is to propose a theoretical model which specifies the domains of QOL and the interrelationships among these domains. The objectives of the study are four-fold: (1) To examine whether a cardiac rehabilitation programme has a beneficial effect on cardiac heart disease patients; (2) To evaluate the primary components of generic health-related quality of life assessment tools for people with coronary heart disease; (3) To identify the main factors governing disease-specific health-related quality of life assessment tools amongst patients with coronary heart disease; (4) To examine a variety of conceptual models of QOL and to determine their relevance to cardiac patients. First, in order to provide conceptual clarity, a comprehensive review of QOL measures was undertaken. Second, data was collected on a cardiac rehabilitation programme in a county hospital using Short Form-36 (SF-36) and Quality of Life for Myocardial Infarction (QLMI) instruments. This data was analysed using a number of techniques including (l)meta-analysis; (2)discriminant analysis; (3)factor analysis and (4)structural equation modelling. Analysing the data in this way enabled the development and clarification of the specific domains of the quality of life model. Meta-analysis involved pooling the results of several studies, these were then analysed to provide a systematic, quantitative review of the data. The results found that the related studies did not have consistent outcomes to support the positive effects of a cardiac exercise rehabilitation programme on quality of life in coronary patients. Findings from the SF-36 indicate that older people with coronary heart disease gain more pain relief than their younger counterparts. After a cardiac exercise rehabilitation progranune, statistically significant improvements occurred in physical function, social function, role limitation/physical, energy/vitality, body pain, and change in health-related dimensions of quality of life. The first-order five domains model includes the symptom domain, the restriction domain, the confidence domain, the self-esteem domain and the emotion domain. This model represents an appropriate model of quality of life for people with coronary heart disease compared to the three-domain model and the four-domain model. In terms of the second-order QOL model, the five-domain model also has an adequate fit to the data. According to the result of structural equation modelling, three models, including the null model, the alternative model I and the alternative model n, did not fit the data perfectly. However, the construct of full latent variable model gradually increased the fit statistics from the null model to the alternative model I and from the null model to alternative model n. Therefore, it can be concluded that the paths and indicators of the three models need to be further adjusted in order to provide a more appropriate model. Nevertheless, this is a first trial to examine a full model of quality of life for people with coronary heart disease using the structural equation analyses. As such, this study provides a new approach to examining the difference between empirical studies and theoretical approaches.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Cardiac rehabilitation programme ; Quality of life ; Coronary heart disease ; SF-36 ; QLMI ; Structural equation modelling ; QOL model ; Meta-analysis ; Discriminant analysis ; Factor analysis