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作 者:徐曼[1] 柴云[2] 李涛[2] 卢丽[3] 刘冰[2]
机构地区:[1]辽宁医学院湖北医药学院校外培养基地,中国湖北十堰442000 [2]湖北医药学院,442000 [3]东风总医院,442000
出 处:《中国健康心理学杂志》2015年第12期1823-1828,共6页China Journal of Health Psychology
基 金:湖北医药学院2013年度研究生启动金项目(编号:K1212304)
摘 要:目的:以多重线性回归和路径分析深入探讨城乡居民主观幸福感影响因素及其相互作用关系。方法:应用简单随机抽样方法选取1480名城乡居民运用Campbell主观幸福感指数量表进行问卷调查,数据采用多重线性回归和路径分析进行对比分析。结果:城乡居民总体幸福感指数平均得分为(11.17±1.99)。多重线性回归分析显示,未来目标、压力应对方式、自评健康状况、兴趣爱好、城乡居住地、休闲时间是幸福感指数的预测因素,标准化偏回归数分别为0.261、0.182、0.152、0.066、0.071、0.051。路径分析发现,未来目标、压力应对方式、自评健康状况直接作用于幸福感指数,路径系数为0.285、0.191、0.160,兴趣爱好、个人月收入、受教育程度、年龄间接作用于幸福感指数,间接效应为0.08、-0.04、0.10、-0.07。结论:主观幸福感与个体生理、心理、社会因素等多个内外部因素有关,多重线性回归和路径分析在探讨居民主观幸福感影响因素及其作用关系过程中各有侧重,相互补充。Objective:To further explore the subjective wellbeing among urban and rural residents and their influencing factors and the factors'interactions by multiple linear regression analyses and path analy-ses .Methods:By simple random sampling method ,a questionnaire survey was conducted among 1480 ur-ban and rural residents using Compbell subjective well -being index Scale ,and data were compared and analyzed by multiple linear regression analyses and path analyses .Results:The average of urban and rural residents'general well-being index was(11.17 ±1.99).Multiple linear regression analysis showed that future goals,stress coping styles,self-rated health status,hobbies,place from urban and rural residence and leisure time were predictors of well -being index ,and their standardized partial regression coefficient were 0.26,0.18,0.15,0.07,0.07 and 0.05,separately.Path analysis found that future goals ,stress cop-ing style ,self-rated health status played direct roles on well -being index , with path coefficient being 0.29,0.19,0.16,and hobbies,personal monthly income ,level of education and age had indirect effects on it with indirect effect being 0.08,-0.04,0.10 and-0.07.Conclusion:Subjective well -being is asso-ciated with physiological ,psychological ,social factors and more related internal and external factors of in-dividuals .In the process of exploring the wellbeing's influencing factors and their interactions among resi-dents,both multiple regression analyses and path analyses have their own focus;The results can be mutu-ally complementary to each other .
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