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Title: Exploring the relationship between hemi-inattention and functional recovery in the first six months after stroke : a longitudinal study with a multilevel modelling approach to data analysis
Author: Stein, Stella (Maria)
ISNI:       0000 0004 5351 2667
Awarding Body: Brunel University
Current Institution: Brunel University
Date of Award: 2015
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In recent years, the functional outcomes of patients with right hemisphere stroke (RHS) received considerable attention due to their impact on disability, independent living, quality of life and economic burden. Hemi-inattention (HI) is a complex condition which often accompanies RHS. It is characterised by reduced alertness, attention and low spatial awareness levels. Past studies reported poor outcomes in patients with HI and inconsistent findings in regard to the relationship of HI with functional outcome. Literature review of 13 relevant studies highlighted poor research methodology which complicated interpretation of previous results. Aims: The aim of this study was to address the clinically important question “What is the relationship between early HI status (HI±) and functional change in the 1st six months after right hemisphere stroke?” by improving on research methodology from past studies. Methods: An all-inclusive stroke severity RHS sample (58 with and 35 without HI) were recruited from two stroke units and assessed on motor and cognitive factors with validated measurement tools on four occasions; baseline, hospital discharge, 6 weeks after discharge, and 6 months after stroke. A multi-level modelling approach was used to analyse change in functional progress over time with potential explanatory motor and cognitive factors. Results: HI status was only statistically significant when modelled alone. Its predictive importance greatly diminished when modelled with other factors e.g. stroke severity, time since stroke and age. Conclusion: On average, HI group membership at baseline is unrelated to functional recovery when other influential factors are also considered. The findings extend current knowledge in stroke recovery research and provide suggestions for optimal therapeutic and rehabilitation outcomes. In contrast with traditional methods of regression analysis, multi-level modelling techniques enabled important relationships to be studied in depth. This resulted in new insights into the data which can be used to inform patient management and future research in the field.
Supervisor: Reynolds, F.; Kilbride, C.; Maskill, D. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Functional outcome ; Right hemisphere stroke ; Hemi-neglect ; Predictors ; Linear mixed method