Personality and Well-Being Trajectories in Adulthood

描述（由申请人提供）：我们将研究人格和心理健康的变化，以及这种变化与身体健康之间的关系，通过自我报告、每日皮质醇水平和死亡率来评估。性格和幸福的变量可以塑造标志着老年的健康变化，但这些变化往往与健康本身一样不断变化和动态。因此，对变化的研究提供了一个机会，可以更好地了解导致健康好坏的社会心理途径。我们将研究持续数年的变化（目标1），以及持续数天的变化（目标3）。在一个新的目标中，我们将研究人格和幸福感的变化是否能预测死亡率（目标2）。为了做到这一点，我们将使用过去40年VA规范老龄化研究（MAS）中现有的纵向数据，我们在1-5年收集的这些男性及其妻子的新数据，以及我们将在6-10年收集的新数据。对于目标2和目标3，我们还将利用MIDUS II研究（P01-AG020166），与国家数据进行比较。我们将专注于3个目标：1)模型在人格，幸福感和身体健康的个体内部的变化，并检查变化的预测因素，使用个人增长模型和耦合变化增长模型。2)利用人格和幸福感及其与环境因素的相互作用建立时间到死亡率的模型。截至2004年6月，45%的NAS参与者已经死亡，从而可以通过风险率模型预测死亡率。我们还将把目标1和目标2结合起来，利用人格和幸福感的变化来预测死亡率。3)建立情感、记忆和皮质醇的日常变化模型，作为日常压力源和整体人格和幸福感的函数。我们将在我们的纵向研究中使用日记研究的“测量爆发”，以更好地理解老年人的日常经历、幸福感、个性和压力的生物指标（皮质醇）之间的相互作用。这项研究的结果将阐明社会心理变量的变化——在多年和日常水平上——如何导致健康状况良好、健康状况不佳和死亡率。

DESCRIPTION (provided by applicant): We will study change in personality and psychological well-being, and the relationship between such change and physical health, as assessed by self-reports, daily cortisol levels, and mortality. Personality and well being variables can shape the changes in health that mark older age, yet these are often as changing and dynamic as health itself. Thus, studies of change offer an opportunity to gain greater understanding of the psychosocial pathways that lead to good or bad health. We will study change that unfolds over years (Aim 1), as well as change that unfolds over days (Aim 3). In a new aim, we will study whether changes in personality and well-being predict mortality (Aim 2). To do this, we will use existing longitudinal data from the past 40 years of the VA Normative Aging Study (MAS), new data we have collected on these men and their wives in Years 1-5, and new data that we will collect in Years 6-10. For Aims 2 and 3, we will also utilize the MIDUS II study (P01-AG020166), providing comparisons with national data. We will focus on 3 aims: 1) Model intraindividual change in personality, well-being, and physical health overtime, and examine predictors of change, using individual growth models and coupled-change growth models. 2) Model time to mortality using personality and well-being and their interactions with contextual factors. As of June, 2004, 45 percent of the NAS participants have died, permitting prediction of mortality from hazard rate models. We will also bring together Aims 1 and 2 by using change in personality and well-being to predict mortality. 3) Model daily variation in affect, memory, and cortisol as a function of daily stressors and global personality and wellbeing. We will use "measurement bursts" of diary studies nested within our longitudinal study to better understand the interplay between daily experience, well-being, personality and biological indicators of stress (cortisol) in older adults. Findings from this study will illuminate how changes in psychosocial variables-at both the multi-year and daily levels-lead to good health, bad health, and mortality.