Quality of Life among Community-Dwelling Stroke Survivors

Panidchakul, K ., Boonsin, S .


Background: The prevalence of stroke has been
increasing. Post-stroke survivors often have deformities
which impact their quality of life. Objective: To examine
the relationship between demographic data, ability of daily
living, depression, social supports.and quality of life in
post-stroke survivors. Methods: A cross-sectional,
descriptive correlational design was used in the study. One
hundred and three stroke survivors were selected from
Saraburi hospital by using purposive sampling technique,
and completed Socio-demographic characteristics, Barthel
Activity of daily Living index, Thai Geriatric Depression
Scale, Social Support Measure, and World Health
Organization Quality of Life in Brief version. The overall
reliability was 0.93. Data analysis: Data were analyzed by
using percentage arithmetic means, standard deviation,
Chi-square, and Pearson’s Product Moment Correlation
Results: Most of participants were males (56.3%), and
married (63.1%), primary school educated (71.8%).
Participants were, on average 62.59 years old and 54.01
months post-stroke. Average monthly income was 2231.07
bath. The major symptoms were hemiparesis (100%),
imbalance movement (39.8%), aspirate and constipation
(20.4%) respectively. Moreover, the majority showed
depression at a normal level (65%), were able to perform
their daily living activities (75.7%), the mean overall social
support score was moderate level (M = 87.35, SD = 19.61),
especially material and financial support (M =18.37, SD =
4.32). Regarding the quality of life, most participants
perceived their quality of life either overall or individual
dimension at a moderate level (M = 78.59, SD = 15.2).
Chi-square and Pearson’s Product Moment Correlation
Coefficient were conducted to explore the relationships
between those variables and quality of life. The results
showed that social support, ability of daily living, and
educational level were statistically significant positive
relationships with the quality of life (r=0.74, p<0.01, r=0.27,
p<0.01, r=0.28, p<0.01) respectively. In addition, there was
statistically significant negative relationships between
length of diagnosis with stroke, depression level and quality
of life (r= -0.21, p<0.05, r = -0.23, p<0.05). These results
implied that the participants who had received more social
support, more independence to perform their daily living,
higher education, lower depression level, and shorter
periods of stroke diagnosis were more likely to have a
better quality of life. Conclusion: This finding will guide
health care professionals to strengthen social support for
improving quality of life in community- dwelling stroke


quality of life stroke survivors

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