Individual differences in the forms of personality trait trajectories.

心理学 特质 人格 社会心理学 五大性格特征 特质理论 五大人格特质与文化 发展心理学 计算机科学 程序设计语言
作者
Amanda Jo Wright,Joshua J. Jackson
出处
期刊:Journal of Personality and Social Psychology [American Psychological Association]
卷期号:127 (5): 1062-1088 被引量:5
标识
DOI:10.1037/pspp0000520
摘要

Changes in personality are often modeled linearly or curvilinearly. It is a simplifying-yet untested-assumption that the chosen sample-level model form accurately depicts all person-level trajectories within the sample. Given the complexity of personality development, it seems unlikely that imposing a single model form across all individuals is appropriate. Although typical growth models can estimate individual trajectories that deviate from the average via random effects, they do not explicitly test whether people differ in the forms of their trajectories. This heterogeneity is valuable to uncover, though, as it may imply that different processes are driving change. The present study uses data from four longitudinal data sets (N = 26,469; Mage = 47.55) to empirically test the degree that people vary in best-fitting model forms for their Big Five personality development. Across data sets, there was substantial heterogeneity in best-fitting forms. Moreover, the type of form someone had was directly associated with their net and total amount of change across time, and these changes were substantially misquantified when a worse-fitting form was used. Variables such as gender, age, trait levels, and number of waves were also associated with people's types of forms. Lastly, comparisons of best-fitting forms from individual- and sample-level models indicated that consequential discrepancies arise from different levels of analysis (i.e., individual vs. sample) and alternative modeling choices (e.g., choice of time metric). Our findings highlight the importance of these individual differences for understanding personality change processes and suggest that a flexible, person-level approach to understanding personality development is necessary. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
墨羽完成签到,获得积分10
刚刚
Jasper应助JX采纳,获得10
刚刚
kouxinyao完成签到 ,获得积分10
刚刚
刚刚
bossyu应助LaTeXer采纳,获得50
1秒前
小马甲应助Li采纳,获得10
1秒前
辛勤的振家完成签到 ,获得积分10
1秒前
1秒前
kk完成签到,获得积分10
2秒前
搜集达人应助布丁采纳,获得10
2秒前
czzzy发布了新的文献求助10
2秒前
2秒前
昵称发布了新的文献求助10
3秒前
3秒前
科研发布了新的文献求助30
3秒前
无极微光应助FU采纳,获得20
3秒前
ZMH完成签到,获得积分10
3秒前
4秒前
彩色的初晴完成签到,获得积分10
4秒前
4秒前
zuhayr发布了新的文献求助10
4秒前
Jam发布了新的文献求助10
5秒前
john2333发布了新的文献求助10
5秒前
5秒前
赘婿应助huihui采纳,获得10
6秒前
Han完成签到 ,获得积分10
6秒前
6秒前
我是老大应助momo采纳,获得10
6秒前
6秒前
Lily完成签到,获得积分10
7秒前
无花果应助可爱的龙猫采纳,获得10
7秒前
7秒前
7秒前
笑点低的孤容完成签到,获得积分10
8秒前
鱼木完成签到,获得积分10
8秒前
8秒前
文静幼荷完成签到 ,获得积分10
9秒前
9秒前
9秒前
li完成签到 ,获得积分10
9秒前
高分求助中
Overcoming Stigma and Bias in Obesity Management 1200
Signals, Systems, and Signal Processing 610
Software that combines deep learning,3D reconstruction and CFD to analyze the state of carotid arteries from ultrasound imaging 500
Bounds for Statistical Estimation in Semiparametric Models 500
Forced degradation and stability indicating LC method for Letrozole: A stress testing guide 500
Ideology and Meaning-Making under the Putin Regime 450
Adhesion Science: Principles & Practice 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6490880
求助须知:如何正确求助?哪些是违规求助? 8289002
关于积分的说明 17686518
捐赠科研通 5581931
什么是DOI,文献DOI怎么找? 2914885
邀请新用户注册赠送积分活动 1891993
关于科研通互助平台的介绍 1749720