Detecting Idiographic Personality Change

Abstract

Personality changes across the lifespan, but strong evidence regarding the mechanisms responsible for personality change remains elusive. Studies of personality change and life events, for example, suggest that personality is difficult to change. But there are two key issues with assessing personality change. First, most change models optimize population-level, not individual-level, effects, which ignores heterogeneity in patterns of change. Second, optimizing change as mean-levels of self-reports fails to incorporate methods for assessing personality dynamics, such as using changes in variances of and correlations in multivariate time series data that often proceed changes in mean-levels, making variance change detection a promising technique for the study of change. Using a sample of N = 388 participants (total N = 21,790) assessed weekly over 60 weeks, we test a permutation-based approach for detecting individual-level personality changes in multivariate time series and compare the results to event-based methods for assessing change. We find that a non-trivial number of participants show change over the course of the year but that there was little association between these change points and life events they experienced. We conclude by highlighting the importance in idiographic and dynamic investigations of change.

Open Scholarship

This article has earned the Center for Open Science badges for Open Data, Open Materials and Preregistered through Open Practices Disclosure. The data and materials are openly accessible at https://github.com/emoriebeck/KCP, https://osf.io/mfn8w/ and https://osf.io/zbkta. To obtain the author's disclosure form, please contact the Editor.

Notes

1 Our preregistration included six steps. The eight steps included here represent splitting the calculation of Gaussian similarity and average within-phase variance into two separate steps and an additional step for locating the location of the change points that was unintentionally omitted due to a fuller discussion of its existing in a separate paper.

2 Notably, some events, like getting married (1) and engaged (4), were reported by multiple participants in sequential weeks. Because were interested in whether change points occurred roughly around the time events were experienced, we allowed these multiple responses to remain as they resulted only in a somewhat larger window in which a change point could fall.

Additional information

Funding

Emorie Beck was supported by National Institute on Aging Grants T32 AG00030-3, 5R01AG067622-02, and 5R01AG018436-20. Open materials on GitHub (https://github.com/emoriebeck/KCP) and the Open Science Framework (https://osf.io/mfn8w/) contain results and code used to conduct the analyses in this manuscript as well as a number of additional analyses. This study was preregistered on the Open Science Framework (https://osf.io/zbkta).