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A model to evaluate diabetes self-management programmes

Alshehri, Abdullah R. (2010) A model to evaluate diabetes self-management programmes University of Southampton, School of Management, Doctoral Thesis , 213pp.

Record type: Thesis (Doctoral)


Self-management has emerged as an approach to enhance quality of care for patients suffering from long term conditions, and to control costs of health services. So far, however, the effects of this approach as adopted by the Saudi healthcare system in the early 1990s remain unclear. Although current models define the concept of self-management, they do not provide a systematic development or an explanatory theory of how self management affects the outcomes of care. The objective of this research is to develop a framework applicable to the evaluation of self-management programmes. The evaluation model is built on patient-related intervention. The effectiveness of these interventions is determined by the levels of patient engagement and effective participation. Therefore, studying factors that influence patients‘ adherence to self-management activities is crucial to explain the outcomes of these interventions. We apply this framework to the case of diabetes mellitus, one of the most common chronic conditions in Saudi Arabia, causing huge burdens on patients and healthcare providers.

A non-experimental retrospective cross-sectional survey research design has been employed to conduct this research using a self-administered questionnaire. Closed-ended questions were used to measure all study variables related to model construction. One open-ended question was used to investigate barriers to diabetes self-management. A non-probability convenient sample design was used to select diabetes centres participated in this study and a systematic approach for selecting patients in these centres. Research data were collected from five diabetes centres and clinics in the main five regions in Saudi Arabia. Quantitative data were analysed using simple, multiple and logistic regressions, whereas a directed content analysis approach was used to analyse qualitative data.

The results of this study revealed that diabetes self-management improves clinical outcomes and reduces utilization of health services. The theoretical approaches underpinning self-management were based on established models from the field of health psychology. By investigating the effect of self-efficacy patients‘ beliefs, and locus of control on self-management, we found that these behavioural theories support the core assumptions of self-management. Self-efficacy was the most significant predictor of self-management followed by patient beliefs. Social support, effective communication between patients and health providers in addition to diabetes knowledge were all important factors to positively influence diabetes self-management. However a new construct, misconception of fatalism from the Islamic point of view, was found to play a negative role in diabetes management. The research model also suggests that diabetes knowledge was influenced by several factors. Education level was the most significant predictor of diabetes knowledge followed by age and diabetes education. It was also found that group education improves diabetes knowledge more than individual education.

This model is a valid tool that could be used to evaluate self-management programmes in other chronic diseases. It can be used as a decision making supporting tool; to identify different components of self-management interventions, and to compare outcomes of programmes. It can also be used to group patients into different categories to facilitate providing tailored services suitable for each group. It could assist health providers to plan new interventions or to refine existing ones by allocating efforts and financial resources toward the most influential factors that affect patients‘ adherence to self-management activities.

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Published date: June 2010
Organisations: University of Southampton


Local EPrints ID: 172565
PURE UUID: 086f5a13-ea2d-4b0a-9fff-89ef20026998

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Date deposited: 04 Feb 2011 15:02
Last modified: 18 Jul 2017 12:14

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Author: Abdullah R. Alshehri
Thesis advisor: Sally Brailsford
Thesis advisor: Dila Agrizzi

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