Bergeman C S, Deboeck Pascal R
University of Notre Dame.
University of Kansas.
Res Hum Dev. 2014;11(2):108-125. doi: 10.1080/15427609.2014.906736. Epub 2014 May 14.
Daily data from the NDHWB (n = 783; age range 37-90) were analyzed to produce 'dynamic characteristic' estimates of stress input and dissipation. These were used in multi-level modeling (with age and trait stress resistance) to predict depression and health trajectories. Main effects suggest that dissipation and stress resistance predict lower depression and better health, but lower stress input was only related to lower depression. Interactions revealed that subjects with above average stress resistance had lower depression irrespective of their ability to dissipate stress, but for individuals low in trait resistance those with better stress dissipation show lower depression and better health.
对来自国家抑郁症健康与福祉数据库(样本量n = 783;年龄范围37 - 90岁)的每日数据进行分析,以得出压力输入和消散的“动态特征”估计值。这些估计值被用于多层次建模(结合年龄和特质抗压能力),以预测抑郁和健康轨迹。主效应表明,压力消散和抗压能力可预测较低的抑郁水平和较好的健康状况,但较低的压力输入仅与较低的抑郁水平相关。交互作用显示,抗压能力高于平均水平的受试者,无论其压力消散能力如何,抑郁水平都较低;但对于特质抗压能力较低的个体而言,压力消散能力较好的人抑郁水平较低且健康状况较好。