Beyond Age and Generations

How Considering Period Effects Reshapes Our Understanding of Personality Change

Roemer, Lena
Bonner, Cavan V.
Rammstedt, Beatrice
Gosling, Samuel D.
Potter, Jeff
Roberts, Brent W.

Department of Psychology, Michigan State University
Department of Psychology, University of Illinois Urbana-Champaign
GESIS-Leibniz Institute for the Social Sciences, Mannheim, Germany
Department of Psychology, University of Texas at Austin
School of Psychological Sciences, University of Melbourne
Atof Inc., Cambridge, Massachusetts, United States
Hector Research Institute of Education Sciences and Psychology, University of Tübingen

Eranda Jayawickreme served as action editor.

The current project was based on a preregistration. In the accompanying Open Science Framework repository (https://osf.io/efz8u), the authors provide the preregistration, analysis code, and supplemental results and mention and explain deviations from the preregistration.

Data used for this project are freely available via application and/or data use agreements; details are provided in the subsections “Data and Participants.” This article uses data from the National Educational Panel Study (see Blossfeld & Roßbach, 2019). The National Educational Panel Study is carried out by the Leibniz Institute for Educational Trajectories (Germany) in cooperation with a nationwide network.

This article uses data from Waves 1, 13, and 37 of the German Internet Panel (DOI: https://doi.org/10.4232/1.12607, https://doi.org/10.4232/1.12619, and https://doi.org/10.4232/1.13584; Blom, Bossert, Funke, et al., 2016; Blom, Bossert, Gebhard, et al., 2016; Blom et al., 2020). A study description can be found in Blom et al. (2015). The German Internet Panel is funded by the German Research Foundation as part of the Collaborative Research Center (SFB) 884 (SFB 884; Project No. 139943784; Project Z1). This article uses data from the Survey of Health, Ageing and Retirement in Europe (SHARE) Waves 7 and 8 (DOI: https://doi.org/10.6103/SHARE.w7.900 and https://doi.org/10.6103/SHARE.w8.900) see Börsch-Supan et al. (2013) for methodological details. The SHARE data collection has been funded by the European Commission, DG RTD through FP5 (QLK6-CT-2001-00360), FP6 (SHARE-I3: RII-CT-2006-062193, COMPARE: CIT5-CT-2005-028857, SHARELIFE: CIT4-CT-2006-028812), FP7 (SHARE-PREP: GA No. 211909, SHARE-LEAP: GA No. 227822, SHARE M4: GA No. 261982, DASISH: GA No. 283646) and Horizon 2020 (SHARE-DEV3: GA No. 676536, SHARE-COHESION: GA No. 870628, SERISS: GA No. 654221, SSHOC: GA No. 823782, SHARE-COVID19: GA No. 101015924) and by DG Employment, Social Affairs and Inclusion through VS 2015/0195, VS 2016/0135, VS 2018/0285, VS 2019/0332, VS 2020/0313 and SHARE-EUCOV: GA No. 101052589 and EUCOVII: GA No. 101102412. Additional funding from the German Ministry of Education and Research, the Max Planck Society for the Advancement of Science, the U.S. National Institute on Aging (U01_AG09740-13S2, P01_AG005842, P01_AG08291, P30_AG12815, R21_AG025169, Y1-AG-4553-01, IAG_BSR06-11, OGHA_04-064, BSR12-04, R01_AG052527-02, HHSN271201300071C, RAG052527A) and from various national funding sources is gratefully acknowledged (see https://www.share-eric.eu).

The authors have no known conflicts of interest to disclose. Lena Roemer was partly funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation, Project No. 536023374). Cavan V. Bonner was supported by the National Science Foundation Graduate Research Fellowship Program (Grant DGE 21-46756).

Lena Roemer played a lead role in formal analysis, methodology, visualization, and writing–original draft and an equal role in conceptualization and writing–review and editing. Cavan V. Bonner played a supporting role in formal analysis and writing–original draft and an equal role in conceptualization and writing–review and editing. Beatrice Rammstedt played a supporting role in conceptualization and an equal role in writing–review and editing. Samuel D. Gosling played an equal role in data curation and writing–review and editing. Jeff Potter played a supporting role in writing–review and editing and an equal role in data curation. Brent W. Roberts played a supporting role in writing–original draft and an equal role in conceptualization and writing–review and editing.

Lena Roemer, Department of Psychology, Michigan State University, 316 Physics Road, East Lansing, MI 48824, United States [email protected]

Received November 27, 2024

revised April 5, 2025

Accepted April 9, 2025

Journal of Personality and Social Psychology Publish Ahead of Print, June 26, 2025. | DOI: 10.1037/pspp0000562

Age, cohort, and period effects are three ways to explain personality trait change over time. While past research mostly focused on age differences, showing relatively consistent patterns, evidence for cohort differences is more mixed, and period differences have hardly been examined. However, age, period, and cohort are exactly collinear (age = period − cohort), such that estimates are likely confounded and always hinge on so-called identification assumptions. Identification assumptions shape substantive conclusions, and inappropriate or inconsistent strategies may explain past discrepant findings. To address this age–period–cohort identification problem in personality change, we leveraged four large-scale (N_total > 2 Mio) repeated cross-sectional data sets from 2003 to 2022. Our aims were to demonstrate how identification assumptions common in personality studies impact estimates for age, cohort, and period and to use weaker, substantively informed assumptions to narrow down the range of plausible solutions. Results showed that common identification strategies of constraining one temporal effect to zero can dramatically affect conclusions—less for age-graded, but more for generational differences. Using weaker assumptions, our results indicated that all three factors—age, cohort, and period—likely contribute to trait differences over time. Assuming age-graded change in a certain direction revealed cohort-related decreases in extraversion, openness, and neuroticism and increases in agreeableness, alongside period-related increases in extraversion, openness, and conscientiousness. This suggests that several previously assumed cohort differences may actually be driven by period effects, overlooked due to strong identification assumptions. Overall, highlighting the importance of appropriate identification strategies, our results offer unique insights into factors driving trait differences over time.