探討中風病人自我管理之相關因素研究

背景: 腦中風引起的身心殘障會影響病人日常生活功能。因此，中風是疾病護理中不容忽視的健康問題。此外，為了提高病人從入院到出院的護理和自我管理的連續性，了解影響其自我管理的相關因素至關重要。目的: 了解腦中風病人社會人口學特徵、健康狀況、連續性照護、自我管理的概況及影響自我管理的重要預測因素。方法: 採橫斷式相關性研究，以初次罹患腦中風6個月內的150位20歲以上中風病人採方便取樣進行的，採用結構化問卷，以中風病人社會人口學資料、健康狀況、連續性照護量表及自我管理量表來收集數據，研究對象以台灣中部某醫學中心的神經內外科病房為主。此外，研究結果以SPSS 25.0電腦套裝軟體進行分析。結果: 腦中風病人自我管理平均得分110.50分(30-150分)，連續性照護平均得分46.61分(12-60分)。從逐步迴歸分析結果顯示:整體迴歸模式可以解釋自我管理約44.5%的變異情形，教育程度(10.8%)、每週運動次數(2.1%)、罹病時間(2.4%)、連續性照護(29.2%)是影響腦中風病人自我管理最主要的預測因子。結論/實務應用為提升中風病人之自我管理，醫療團隊應促進及維持病人日常生活功能，並針對教育程度低、無運動習慣及中風罹病時間1個月內者，提供適當的連續性照護，以使病人達到最佳的自我管理行為。

關鍵字

腦中風；連續性照護；自我管理

並列摘要

Background: The physical and mental disabilities caused by stroke affect patients’ activities of daily living. Thus, stroke is a health issue that must not be ignored in disease care. Moreover, to improve patients’ continuity of care and self-management from admission to discharge, understanding relevant factors affecting their self-management is essential. Purposes: To investigate the patients’ socio-demographic characteristics, health status, continuity of care, self-management, and other predictors that affect their self-management. Methods: This cross-sectional correlational study was conducted on a convenient sample of 150 patients aged 20 above who were diagnosed within the past 6 months. This design employed structured questionnaires, such as scales on socio-demographic data, health status, continuity of care, and patient’s self-management to collect data. The research subjects were selected from the Division of Neurology, Department of Internal Medicine/Department of Surgery in a medical center in central Taiwan. In addition, statistical analyses were performed upon the collected data using the SPSS 25.0 package software. Results: The mean score of self-management of patients with stroke was 110.50 points (30-150 points), and that of continuity of care was 46.61 points (12-60 points). As shown in the stepwise regression analysis, the overall regression model explained approximately 44.5% of the variance of self-management. Educational level (10.8%), frequency of exercise per week (2.1%), time of suffering from stroke (2.4%), and continuity of care (29.2%) were the main predictors affecting the self-management of stroke patients. Conclusions/ Implications for practice: To improve stroke patients’ self-management, medical teams should provide appropriate continuity of care to those with lower educational levels, those without exercise habits, and those who experienced a stroke within the past 1 months. The findings of this study can provide patients with complete healthcare to improve their self-management.