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|Title: ||Health related quality of life over one year post stroke: identifying response shift susceptible constructs|
|Authors: ||Barclay-Goddard, Ruth|
|Supervisor: ||Mayo, Nancy (Division of Clinical Epidemiology, McGill University)|
|Examining Committee: ||Lix, Lisa (School of Public Health, University of Saskatchewan)
Tate, Robert (Department of Community Health Sciences)
Weinberg, Leah (Department of Physical Therapy, School of Medical Rehabilitation)
Hanna, Steven (Department of Clinical Epidemiology and Biostatistics, McMaster University)|
|Graduation Date: ||October 2008|
health related quality of life
structural equation modeling
|Issue Date: ||11-Sep-2008|
|Abstract: ||Problem: Many individuals with chronic illnesses such as stroke and ongoing activity limitations report self-perceived health related quality of life (HRQL) that is similar to that of healthy individuals. This phenomenon is termed response shift (RS). RS describes how people change: internal standards in assessing HRQL (recalibration), values (reprioritization), or how they define HRQL (reconceptualization), after an event such as stroke. Changes in HRQL post stroke may be inaccurate if RS is not taken into account. Increased knowledge of RS may affect the way in which HRQL measures are used, both clinically and in research. The overall objective was to assess RS in construct specific HRQL models post stroke: physical function, mental health, and participation.
Methods: Data were analysed from the longitudinal study “Understanding Quality of Life Post-Stroke: A Study of Individuals and their Caregivers”. Six-hundred and seventy- eight persons with stroke at 1, 3, 6, and 12 months post stroke participated. Generic and stroke specific HRQL measures were collected. Descriptive analysis was completed with SAS, and identification of RS utilized structural equation modeling with LISREL.
Results: Mean age of participants was 67 years (SD 14.8), and 45% were female. RS was identified in mental health using a framework which was developed for identifying RS statistically with multiple time points. RS was also identified in physical function where it had not been expected, possibly due to the self perceived nature of the response options. The effect size of change in physical function was affected by the presence of RS. The timing of RS in mental health and physical function was primarily around the 12 month time period, and predominantly recalibration RS. RS was also identified in participation.
Conclusions: The framework that was developed was useful in identifying RS and incorporated important issues such as multiple testing and validation of the model. The presence of RS affects measurement of HRQL constructs post stroke; recalibration RS can be measured clinically with specific methods to account for RS. RS should also be measured in research studies to ensure accurate measurement of change. Future research should evaluate additional models in stroke and other populations.|
|Appears in Collection(s):||FGS - Electronic Theses & Dissertations (Public)|
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