Factors predicting quality of life in stroke patients: A cross-sectional study

Abstract

Aims: Stroke affects the quality of life by affecting daily activities. This study aimed at determining the factors predicting quality of life in patients with stroke referring to Shahid Beheshti Hospital in Kashan. Materials and Methods: In this cross-sectional study, sampling was done by census method during 2019 and in the first 6 months of 2020, and 188 patients with stroke referring to Shahid Beheshti Hospital in Kashan who had at least 2 months after stroke were evaluated. Data collection tools were questionnaire of Stroke Impact Scale-16 and possible factors associated with stroke. Data were analyzed using SPSS software version 16 using the tests of Mann–Whitney, Kruskal–Wallis, independent t-test, Pearson's correlation coefficient (Spearman), and multivariate linear regression analysis. Findings: The mean quality of life was 50.92 ± 24.97. In univariate analysis, the quality of life was significantly associated with gender, marital status, education level, type of stroke, use of rehabilitation services, spouse's education level, occupation, number of children, regular exercise, history of hypertension, and previous history of stroke. Based on the results of multivariate analysis, 62.4% of variance was explained by four factors of the required number of rehabilitation sessions, history of previous stroke, level of education, and severity of stroke (F = 11.597, R2 = 0.624, and P < 0.001). The most important factor was the number of rehabilitation sessions required. Conclusion: To improve the stroke patients' quality of life, healthcare professionals should pay attention to the predictive role of low education level, more need for rehabilitation, severity, and history of stroke in their programs and procedures.