Shahnaz M Ayasrah, Muayyad M Ahmad, Fuad H Abuadas, Hana M Abu-Snieneh, Iman A Basheti
{"title":"Health-Related Quality of Life Among Patients With Stroke: A Cross-Sectional Study.","authors":"Shahnaz M Ayasrah, Muayyad M Ahmad, Fuad H Abuadas, Hana M Abu-Snieneh, Iman A Basheti","doi":"10.1093/arclin/acae007","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>To assess levels and predictive factors of health-related quality of life (HRQOL) among stroke patients.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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).</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1093/arclin/acae007","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 0
Abstract
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.