Decades of research have identified average patterns of normative personality development across the lifespan. However, it is unclear how well these correspond to trajectories of individual development. Past work beyond general personality development might suggest these average patterns are oversimplifications, necessitating novel examinations of how personality develops and consideration of new individual difference metrics. This study uses five longitudinal data sets from Germany, Australia, the Netherlands, and the United States (N = 128,345; Mage = 45.42; 53% female) to examine personality development using mixed-effects location scale models. These models quantify individual differences in within-person residual variability, or sigma, around trajectories-thereby testing if models that assume sigma is homogeneous, unsystematic noise are appropriate. We investigate if there are individual differences in longitudinal within-person variability for Big Five trajectories, if there are variables associated with this heterogeneity, and if person-level sigma values can uniquely predict an outcome. Results indicated that, across all models, there was meaningful heterogeneity in sigma-the magnitude of which was comparable to and often even greater than that of intercepts and slopes. Individual differences in sigma were further associated with covariates central to personality development and had robust predictive utility for health status, an outcome with long-established personality associations. Collectively, these findings underscore the presence, degree, validity, and potential utility of heterogeneity in longitudinal within-person variability and indicate the typical linear model does not adequately depict individual development. We suggest it should become the default to consider this individual difference metric in personality development research. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

中文翻译：

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围绕人格轨迹的纵向人内变异。


数十年的研究已经确定了一生中规范人格发展的平均模式。然而，尚不清楚这些与个人发展轨迹的对应程度如何。过去超越一般人格发展的工作可能表明这些平均模式过于简单化，需要对人格如何发展进行新的检查并考虑新的个体差异指标。本研究使用来自德国、澳大利亚、荷兰和美国的五个纵向数据集（N = 128,345；Mage = 45.42；53% 女性），使用混合效应位置尺度模型来检查人格发展。这些模型量化了轨迹周围的人内剩余变异性或西格玛的个体差异，从而测试假设西格玛是同质的、非系统噪声的模型是否合适。我们研究大五轨迹的纵向人内变异是否存在个体差异，是否存在与这种异质性相关的变量，以及个人水平的西格玛值是否可以唯一地预测结果。结果表明，在所有模型中，西格玛都存在有意义的异质性，其大小与截距和斜率相当，甚至常常更大。西格玛的个体差异进一步与人格发展的核心协变量相关，并且对健康状况具有强大的预测效用，这是长期建立的人格关联的结果。总的来说，这些发现强调了人内纵向变异性异质性的存在、程度、有效性和潜在效用，并表明典型的线性模型不能充分描述个体发展。 我们建议在人格发展研究中默认考虑这种个体差异指标。 （PsycInfo 数据库记录 (c) 2024 APA，保留所有权利）。