We have located links that may give you full text access.
Health-Related Quality of Life Among Patients With Stroke: A Cross-Sectional Study.
Archives of Clinical Neuropsychology : the Official Journal of the National Academy of Neuropsychologists 2024 Februrary 14
PURPOSE: To assess levels and predictive factors of health-related quality of life (HRQOL) among stroke patients.
METHODS: The study employed a cross-sectional predictive correlational design. Levels of HRQOL were assessed using the Stroke-Specific Quality of Life (SS-QOL) scale, and the Hospital Anxiety and Depression Scale was employed to assess psychological aspects among 209 Saudi stroke patients. The analysis included demographic and medical variables to comprehensively explore influencing factors.
RESULTS: A two-step hierarchical multiple regression analysis was performed. The overall SS-QOL summary score (49 items) showed a mean score of 94.4 (SD = 8.1), indicating poor functioning. Nine predictor variables were found to significantly predict HRQOL levels, including age (β = -0.212, p ≤ .001), female (β = -5.33, p ≤ .001), unmarried (β = 2.48, p ≤ .001), low gross monthly income (GMI) (β = -9.02, p ≤ .001), medium GMI (β = -8.36, p ≤ .001), having a medical history of hypertension (β = 2.7, p ≤ .01), time since stroke (β = 3.26 p ≤ .001), and being a probable case of anxiety (β = -4.29, p ≤ .001) and/or depression (β = -2.75, p ≤ .001). These variables collectively explained ~76% of the variance in HRQOL scores (adjusted R2 = .762, F (16,192) = 42.6, p ≤ .001).
CONCLUSIONS: Stroke patients exhibited poor HRQOL levels influenced by various factors. Clinicians should consider these predictors and intervene early to enhance HRQOL among patients at risk, emphasizing the importance of optimizing patient outcomes.
METHODS: The study employed a cross-sectional predictive correlational design. Levels of HRQOL were assessed using the Stroke-Specific Quality of Life (SS-QOL) scale, and the Hospital Anxiety and Depression Scale was employed to assess psychological aspects among 209 Saudi stroke patients. The analysis included demographic and medical variables to comprehensively explore influencing factors.
RESULTS: A two-step hierarchical multiple regression analysis was performed. The overall SS-QOL summary score (49 items) showed a mean score of 94.4 (SD = 8.1), indicating poor functioning. Nine predictor variables were found to significantly predict HRQOL levels, including age (β = -0.212, p ≤ .001), female (β = -5.33, p ≤ .001), unmarried (β = 2.48, p ≤ .001), low gross monthly income (GMI) (β = -9.02, p ≤ .001), medium GMI (β = -8.36, p ≤ .001), having a medical history of hypertension (β = 2.7, p ≤ .01), time since stroke (β = 3.26 p ≤ .001), and being a probable case of anxiety (β = -4.29, p ≤ .001) and/or depression (β = -2.75, p ≤ .001). These variables collectively explained ~76% of the variance in HRQOL scores (adjusted R2 = .762, F (16,192) = 42.6, p ≤ .001).
CONCLUSIONS: Stroke patients exhibited poor HRQOL levels influenced by various factors. Clinicians should consider these predictors and intervene early to enhance HRQOL among patients at risk, emphasizing the importance of optimizing patient outcomes.
Full text links
Related Resources
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app
All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.
By using this service, you agree to our terms of use and privacy policy.
Your Privacy Choices
You can now claim free CME credits for this literature searchClaim now
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app