成功老龄化:人格变量的贡献

Elina Van Dendaele, K. Pothier, Nathalie Bailly
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引用次数: 0

摘要

“了解社会、经济和心理因素对促进老年人健康很重要。Rowe和Kahn(1997)描述了“成功老龄化”(SA)的三个主要组成部分:避免残疾和疾病,高认知和身体能力,积极参与生活。心理维度(即人格)尚未得到充分研究。然而,它们可以被视为定义SA。本研究旨在确定身体、认知、社会和人格因素是否与SA相关。共有2109名参与者住在家中(男性53.39%;image =75,38±8.11)——来自欧洲健康、老龄化和退休调查(SHARE数据集2017年7.0.0版)——完成了测量身体(活动能力、疾病数量、IADL、BMI)和认知(记忆、执行功能)健康、社会参与和个性(大五量表)的问卷调查。这些变量被收集成三个不同的块:社会人口特征(年龄、性别)、模型的Rowe和Kahn变量(身体、认知、社会参与)和个性。SA采用欧元萧条量表进行评估。计算相关矩阵来检验所有变量之间的相互关系。然后在适当的时候进行线性回归分析。较高水平的运动和认知能力与较低水平的抑郁症状相关(r=0.34;p <措施;r = .20;p <措施;r =。;p <措施)。疾病数量与抑郁症状呈正相关(r=0.26;p <措施)。人们越投入,抑郁症状就越少(r=0.09;p = .019)。受教育程度对抑郁症状的影响(F(5,847)= 7.06;P < 0.001)发现:受教育程度高的人抑郁得分低于受教育程度低的人。较低水平的神经质、较高水平的亲和性和尽责性与较低水平的抑郁症状显著相关(r=0.41;p <措施;r = .09点;p < .028;r =。08;p = .028)。线性回归分析显示,人格变量解释了11%的抑郁得分差异,超过了社会人口统计学特征(年龄、性别)(9%)和罗和卡恩模型中的变量(10%)。这三个部分加在一起,解释了29%的抑郁得分差异。与Rowe和Kahn的模型(1997)一致,结果显示SHARE研究中的身体、认知和社会因素部分解释了SA(即这里没有抑郁症状)。有趣的是,性格变量也解释了很大比例的抑郁症状。个性可能在解决SA方面发挥重要作用:调整护理和预防,以鼓励老年人参与身体,社会或认知活动。”
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SUCCESSFUL AGING: THE CONTRIBUTION OF PERSONALITY VARIABLES
"Understanding social, economic, and psychological factors are important for promoting elderly health. Rowe and Kahn (1997) described three main components for ""successful aging"" (SA): avoiding disability and disease, high cognitive and physical capacities, and active engagement in one's life. Psychological dimensions (i.e., personality) have not been sufficiently studied yet. However, they could be considered to define SA. This study aimed to determine whether physical, cognitive, social, and personality factors were associated with SA. A total of 2109 participants living at home (53.39% men; mage =75,38±8.11) – from the Survey of Health, Aging, and Retirement in Europe (SHARE dataset release 7.0.0 of 2017) – completed questionnaires measuring physical (mobility, number of diseases, IADL, BMI) and cognitive (memory, executive function) health, social engagement, and personality (Big Five Inventory). These variables were gathered into three distinct blocks: sociodemographic characteristics (age, sex), model’s Rowe and Kahn variables (physical, cognitive, social engagement), and personality. SA was assessed by the Euro depression scale. A correlation matrix was computed to examine the interrelationships between all variables. We then performed linear regression analysis when it was appropriate. A higher level of motor and cognitive abilities correlated with a lower level of depressive symptoms (r=0.34; p<.001; r=-.20; p<.001; r=-.17; p<.001). The number of diseases was positively correlated with depressive symptoms (r=0.26; p<.001). The more engaged people were, the fewer depressive symptoms they had (r=0.09; p=.019). An effect of the level of education on depressive symptoms (F(5,847)= 7.06; p<.001) was found: people with a higher educational level had a lower depression score than those with a lower educational level. A lower level of neuroticism, higher level of agreeableness, and conscientiousness were significantly correlated with a lower level of depressive symptoms (r=0.41; p<.001; r=-.09; p<.028; r=-.08; p=.028). Linear regression analyses showed that personality variables explained 11% of the variance of depression scores, beyond sociodemographic characteristics (age, sex) (9%) and variables in the Rowe and Kahn model (10%). The three blocks, all together, explained 29% of the variance of the depression scores. In line with Rowe and Kahn’s model (1997), results showed that physical, cognitive, and social factors from the SHARE study partially explained SA (i.e., absence of depressive symptoms here). Interestingly, personality variables also explained a significant proportion of depressive symptoms. Personality may have an important role in addressing SA: adapting the care as well as the prevention to encourage the elderly to engage in physical, social, or cognitive activities."
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