臺北市獨居老人社會融入之階層化迴歸分析

Hierarchical Regression Analysis of Social Inclusion among the Elderly Living Alone: An Example of Taipei City

研究嘗試從社會融入觀點瞭解臺北市獨居老人的境況，並且從下列四個面向：（一）個人特質；（二）健康狀況；（三）獨居環境情形；以及（四）社區資源去預測社會融入。以臺北市社會局列冊之獨居老人為母體，依行政區以及性別比例分層隨機抽樣，再以面對面訪談方法完成結構化之自陳問卷，總計328人。社會融入面向係以英國社會排除單位所做貫時性研究的7個面向為參考架構並參考國情自行設計，另分別採因素分析重構量表涵蓋12個次面向。量表整體信度高達0.911。最後本研究採階層化多元迴歸模式分析前述四大類變項預測整體社會融入之效果。研究結果發現四類變項共可解釋高達49.2%的變異量。本研究確認四類變項對於獨居老人社會融入的預測力，最後並提出實務與政策上的建議。

Purpose: The study intends to predict social inclusion among the elderly living alone from four dimensions: the individual characteristics of the elderly, the health status and condition, environmental condition of living alone situation, and community resources. Method: The subjects were selected by gender and administrative district from enrolled list of elderly living alone in Taipei City. Three hundred and twenty eight subjects were collected by using face to face interviews with a structuredquestionnaire. The research is the first one which use individual report as the data source. Items were configured and redesigned from seven dimensions of social exclusion/inclusion report of an English study. Twelve restructured subdimensions are created using factor analysis. The overall reliability is .911. The hierarchical regression analysis is used to predict social inclusion. Results: The individual characteristics of the elderly could predict 29.6% of the variance. Adding the health status and condition variables, the total variance explained is 44%. The third model by adding variables of living alone situation explains 47.5% of the total variance. Entering all variables of four levels, the total variance explained is 49.2%. Conclusion: This study provides an understanding of social inclusion and its prediction. The practice and policy implications are also provided.