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INVESTIGATION OF PERSONALITY USING DIFFERENT TIME MATRICES CONTROL VARIABLES AND INCLUSION GROUPS

机译:使用不同的时间矩阵控制变量和包含组调查人格

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摘要

Two studies suggest that personality change may be an early indicator of dementia (Balsis et al, 2005; Smith-Gamble et al, 2001); however, these studies did not assess personality trait change. Although Yoneda et al (2015) prospectively examined personality traits, the nature of the analyses did not allow comparison between trajectories in normal and abnormal aging. The current study includes comparison of trajectories of extraversion and neuroticism personality traits in individuals who did and did not receive a dementia diagnosis.This study used data from the OCTO-Twin Study, Longitudinal Aging Study Amsterdam, Swedish Adoption Twin Study of Aging, and Einstein Aging Study. For each dataset, a series of latent growth curve models were run examining each personality trait, first including a subsample of individuals eventually diagnosed with dementia and time-to-dementia metric, and second including the entire dataset, dementia diagnosis as a variable, and time-in-study metric.Controlling for sex, age, education, depressive symptoms, and the interaction between age and education, the first series of analyses revealed a consistent pattern of personality change preceding dementia diagnosis across datasets, specifically linear increases in neuroticism and stability in extraversion. The second series of analyses revealed a less stable pattern of results: dementia diagnosis was only a significant predictor of neuroticism trajectories in some datasets. These findings will be discussed.Identification of early indicators of dementia, specifically how personality changes differ for healthy individuals compared to individuals eventually diagnosed with dementia, may aid in early care strategies and facilitate development of screening assessments.
机译:两项研究表明,人格改变可能是痴呆症的早期指标(Balsis等,2005; Smith-Gamble等,2001);然而,这些研究并未评估人格特质的变化。尽管Yoneda等人(2015)前瞻性地检查了人格特质,但分析的性质不允许比较正常和异常衰老的轨迹。目前的研究包括比较患有痴呆症和没有患有痴呆症的个体的外向性和神经质人格特质的轨迹。这项研究使用了OCTO-Twin研究,阿姆斯特丹纵向老龄化研究,瑞典老龄化领养双胞胎研究和爱因斯坦的数据衰老研究。对于每个数据集,运行一系列潜在的生长曲线模型,检查每个人格特征,首先包括最终被诊断出患有痴呆症的人的子样本和达到痴呆时间的指标,其次包括整个数据集,痴呆症诊断为变量,以及第一个系列分析显示,在控制性别,年龄,教育程度,抑郁症状以及年龄和教育程度之间的相互作用之后,揭示了在整个数据集中进行痴呆症诊断之前人格变化的一致模式,特别是神经质和外向性的稳定性。第二系列分析显示了不稳定的结果模式:痴呆诊断只是某些数据集中神经质运动轨迹的重要预测指标。这些结果将进行讨论。识别痴呆症的早期指标,特别是健康个体与最终诊断为痴呆症的个体相比,人格变化如何不同,可能有助于早期护理策略并促进筛查评估的发展。

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