14th World Congress on Brain Injury Abstracts

Abstract

Background/Aim: Cerebrovascular accident or stroke has become one of the main causes of death and disability in the world. Even in mild cases, the sequels are long-lasting or permanent, which produces significant changes in the life of the person and their families. Traditionally, health-related quality of life models has been used, omitting variables of interest in people who have suffered a stroke years ago (e.g., self-determination, rights). Therefore, the aim of this research is to analyze the predictive variables of quality of life levels following a multidimensional model such as that of Schalock and Verdugo (2002/2003). Method: A longitudinal 1-year follow-up of 78 adults (59% men, mean age 60.7 years) who sustained a stroke in Spain some time ago (mean time 5,4 years). Socio-demographics (gender, age, educational level, relationship status, employment) and injury severity (degree of dependence, time since injury, cerebral location, comorbidity of health conditions) were recorded at baseline. The Social Support Questionnaire- 6 (SSQ-6), Connor-Davidson resilience scale (CD-RISC), Community Integration Questionnaire (CIQ) and Patient health questionnaire (PHQ-9) were assessed at baseline and 1- year follow-up. Also, self-reported quality of life was reported using the CAVIDACE scale. Possible predictors of quality of life levels were assessed with hierarchical regression analyses. Results: At baseline, the mean SSQ-6 was 2 for number of social supports and 5 for satisfaction with them (low social support but moderate satisfaction), the mean CD-RISC was 64 (moderate resilience), the mean CIQ score was 9 (very reduced community integration), and the mean PHQ-9 8 (low depression). The mean CAVIDACE self-report score was 106 (37% reporting impaired HRQL), quite similar to the mean obtained at baseline (103). In the final multivariate regression model, dependency level (β - 0.557, p < 0.01) and depression (β - 0.507, p = <0.001) significantly predicted 1 year followup quality of life, explaining 47% (adjusted R2) of the variance in quality of life. Conclusions: Although the quality of life after a stroke depends to a large extent on its severity, that is, on the resulting degree of dependency, the great importance of other factors such as levels of depression has been shown. It would be of great interest to analyze the different dimensions of the quality of life model separately, allowing optimization of the interventions carried out with this population and their families.