{"title":"脑卒中幸存者恢复期冷漠的预测因素。","authors":"Pao-Chen Wang, Hsiang-Chu Pai","doi":"10.1097/JNN.0000000000000737","DOIUrl":null,"url":null,"abstract":"<p><strong>Abstract: </strong>BACKGROUND: Apathy may be an important predictor of depression and significantly negatively affect the quality of life and functional recovery of stroke survivors. However, the evidence reflects the inconsistent findings of studies on the impact of individual-related variables on apathy in patients with stroke. OBJECTIVES: This study examines the relationships among stroke survivors' individual characteristics, background variables, disease-related variables, and apathy; furthermore, we identify predictors of apathy. METHODS: In this cross-sectional correlational study, the participants were recruited from a medical university hospital. Three measurement tools were used: individual and background variables, the modified Rankin Scale, and the Apathy Evaluation Scale. Hierarchical multiple regression analysis was used to identify the predictors of apathy. RESULTS: Participants included 100 stroke survivors with a mean age of 59.9 (12.1) years. The prevalence of apathy among stroke survivors was 27%. Stroke survivors' economic sources (β = 0.430, P = .001), perceived family support (β = -0.163, P = .048), and modified Rankin Scale (β = 0.283, P = .001) accounted for 43.7% of the variance in survivor apathy. CONCLUSION: The results of this study clarified which individual characteristics, background variables, and disease-related variables are key predictors of apathy in patients with stroke.</p>","PeriodicalId":94240,"journal":{"name":"The Journal of neuroscience nursing : journal of the American Association of Neuroscience Nurses","volume":" ","pages":"25-30"},"PeriodicalIF":0.0000,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Predictive Factors of Apathy in Stroke Survivors During the Recovery Period.\",\"authors\":\"Pao-Chen Wang, Hsiang-Chu Pai\",\"doi\":\"10.1097/JNN.0000000000000737\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Abstract: </strong>BACKGROUND: Apathy may be an important predictor of depression and significantly negatively affect the quality of life and functional recovery of stroke survivors. However, the evidence reflects the inconsistent findings of studies on the impact of individual-related variables on apathy in patients with stroke. OBJECTIVES: This study examines the relationships among stroke survivors' individual characteristics, background variables, disease-related variables, and apathy; furthermore, we identify predictors of apathy. METHODS: In this cross-sectional correlational study, the participants were recruited from a medical university hospital. Three measurement tools were used: individual and background variables, the modified Rankin Scale, and the Apathy Evaluation Scale. Hierarchical multiple regression analysis was used to identify the predictors of apathy. RESULTS: Participants included 100 stroke survivors with a mean age of 59.9 (12.1) years. The prevalence of apathy among stroke survivors was 27%. Stroke survivors' economic sources (β = 0.430, P = .001), perceived family support (β = -0.163, P = .048), and modified Rankin Scale (β = 0.283, P = .001) accounted for 43.7% of the variance in survivor apathy. CONCLUSION: The results of this study clarified which individual characteristics, background variables, and disease-related variables are key predictors of apathy in patients with stroke.</p>\",\"PeriodicalId\":94240,\"journal\":{\"name\":\"The Journal of neuroscience nursing : journal of the American Association of Neuroscience Nurses\",\"volume\":\" \",\"pages\":\"25-30\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The Journal of neuroscience nursing : journal of the American Association of Neuroscience Nurses\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1097/JNN.0000000000000737\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2023/11/19 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Journal of neuroscience nursing : journal of the American Association of Neuroscience Nurses","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1097/JNN.0000000000000737","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/11/19 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
摘要:背景:冷漠可能是抑郁的重要预测因子,对脑卒中幸存者的生活质量和功能恢复有显著的负面影响。然而,证据反映了个体相关变量对脑卒中患者冷漠影响的研究结果不一致。目的:本研究探讨脑卒中幸存者的个体特征、背景变量、疾病相关变量和冷漠之间的关系;此外,我们确定了冷漠的预测因素。方法:在横断面相关研究中,参与者从某医科大学附属医院招募。采用三种测量工具:个体变量和背景变量、修正Rankin量表和冷漠评价量表。采用层次多元回归分析确定冷漠的预测因素。结果:参与者包括100名中风幸存者,平均年龄为59.9(12.1)岁。中风幸存者中冷漠的患病率为27%。脑卒中幸存者的经济来源(β = 0.430, P = .001)、感知到的家庭支持(β = -0.163, P = .048)和修正Rankin量表(β = 0.283, P = .001)占幸存者冷漠方差的43.7%。结论:本研究结果阐明了哪些个体特征、背景变量和疾病相关变量是脑卒中患者冷漠的关键预测因素。
Predictive Factors of Apathy in Stroke Survivors During the Recovery Period.
Abstract: BACKGROUND: Apathy may be an important predictor of depression and significantly negatively affect the quality of life and functional recovery of stroke survivors. However, the evidence reflects the inconsistent findings of studies on the impact of individual-related variables on apathy in patients with stroke. OBJECTIVES: This study examines the relationships among stroke survivors' individual characteristics, background variables, disease-related variables, and apathy; furthermore, we identify predictors of apathy. METHODS: In this cross-sectional correlational study, the participants were recruited from a medical university hospital. Three measurement tools were used: individual and background variables, the modified Rankin Scale, and the Apathy Evaluation Scale. Hierarchical multiple regression analysis was used to identify the predictors of apathy. RESULTS: Participants included 100 stroke survivors with a mean age of 59.9 (12.1) years. The prevalence of apathy among stroke survivors was 27%. Stroke survivors' economic sources (β = 0.430, P = .001), perceived family support (β = -0.163, P = .048), and modified Rankin Scale (β = 0.283, P = .001) accounted for 43.7% of the variance in survivor apathy. CONCLUSION: The results of this study clarified which individual characteristics, background variables, and disease-related variables are key predictors of apathy in patients with stroke.