The elements and features of cognitive rehabilitation for stroke and 'mild cognitive impairment' in relation to everyday functioning and quality of life

Chai, Chung Han (2021) The elements and features of cognitive rehabilitation for stroke and 'mild cognitive impairment' in relation to everyday functioning and quality of life. Doctoral thesis, University of East Anglia.

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Abstract

Context: Stroke and dementia are neuropsychological deficits that impact an individual's quality of life. Computerised cognitive training (CCT) is an intervention aimed to ameliorate the deficits.
Aim: The current thesis portfolio aims to provide an updated review on CCT efficacy concerning the quality of life and mild cognitive impairment (MCI). Additionally, the thesis aims to understand better the cognitive domains that best predict the quality of life in stroke individuals.
Method: The systematic review examined the efficacy of existing computerised cognitive training at improving everyday functioning in MCI individuals. Additionally, the review aggregated CCT features that are commonly used in the reviewed CCTs. The empirical paper examined the cognitive variables best-predicting quality of life, focusing specifically on functional outcomes.
Results: The systematic review showed tentative evidence for CCT at improving everyday functioning in MCI individuals. The review identified preliminary evidence suggesting socio/emotional factors that might contribute to CCT efficacy. The empirical paper found non-spatial attention as a significant contributor to one model of quality of life. However, this significance was only attainable when depression and motivation subscales were removed from the model.
Conclusion: The findings provide tentative evidence supporting CCT at improving everyday functioning and identified possible cognitive domains that best predict life quality. Implications of the findings were discussed further in the discussion chapter. More studies are needed before a firm conclusion can be made about CCT efficacy, and the cognitive domains best predict the quality of life.

Item Type: Thesis (Doctoral)
Faculty \ School: Faculty of Medicine and Health Sciences > Norwich Medical School
Depositing User: Jackie Webb
Date Deposited: 18 Nov 2021 09:51
Last Modified: 18 Nov 2021 09:51
URI: https://ueaeprints.uea.ac.uk/id/eprint/82211
DOI:

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