Special Issue Article
Equilibria in Personality States: A Conceptual Primer for Dynamics in Personality States
Alexander F. Danvers,
Richard Wundrack,
Matthias Mehl,
Corresponding Author
Alexander F. Danvers
Psychology, University of Arizona, Tucson, AZ, USA
Correspondence to:
Alexander F. Danvers, Psychology, University of Arizona, Tucson, AZ 85721, USA.
E-mail: adanvers@email.arizona.edu
Search for more papers by this authorRichard Wundrack
Personality Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
Search for more papers by this authorMatthias Mehl
Psychology, University of Arizona, Tucson, AZ, USA
Search for more papers by this authorAlexander F. Danvers,
Richard Wundrack,
Matthias Mehl,
Corresponding Author
Alexander F. Danvers
Psychology, University of Arizona, Tucson, AZ, USA
Correspondence to:
Alexander F. Danvers, Psychology, University of Arizona, Tucson, AZ 85721, USA.
E-mail: adanvers@email.arizona.edu
Search for more papers by this authorRichard Wundrack
Personality Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
Search for more papers by this authorMatthias Mehl
Psychology, University of Arizona, Tucson, AZ, USA
Search for more papers by this authorThis article earned Open Data badge through Open Practices Disclosure from the Center for Open Science: https://osf.io/tvyxz/wiki. All data are permanently and openly accessible at https://osf.io/dps4w/. Author's disclosure form may also be found at the Supporting Information in the online version.
Abstract
We provide a basic, step-by-step introduction to the core concepts and mathematical fundamentals of dynamic systems modelling through applying the Change as Outcome model, a simple dynamical systems model, to personality state data. This model characterizes changes in personality states with respect to equilibrium points, estimating attractors and their strength in time series data. Using data from the Personality and Interpersonal Roles study, we find that mean state is highly correlated with attractor position but weakly correlated with attractor strength, suggesting strength provides added information not captured by summaries of the distribution. We then discuss how taking a dynamic systems approach to personality states also entails a theoretical shift. Instead of emphasizing partitioning trait and state variance, dynamic systems analyses of personality states emphasize characterizing patterns generated by mutual, ongoing interactions. Change as Outcome modelling also allows for estimating nuanced effects of personality development after significant life changes, separating effects on characteristic states after the significant change and how strongly she or he is drawn towards those states (an aspect of resiliency). Estimating this model demonstrates core dynamics principles and provides quantitative grounding for measures of ‘repulsive’ personality states and ‘ambivert’ personality structures. © 2020 European Association of Personality Psychology
Open Research
Open Research Badges
This article earned Open Data badge through Open Practices Disclosure from the Center for Open Science: https://osf.io/tvyxz/wiki. All data are permanently and openly accessible at https://osf.io/dps4w/. Author's disclosure form may also be found at the Supporting Information in the online version.
Supporting Information
| Filename | Description |
|---|---|
| PER2239-sup-0001-Open-Practices-Disclosure-Form.pdfPDF document, 652.7 KB |
Open Science Disclosure Form |
Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
REFERENCES
- Aiken, L. S., West, S. G., & Reno, R. R. (1991). Multiple regression: Testing and interpreting interactions. Thousand Oaks, CA: Sage.
- Asparouhov, T., Hamaker, E. L., & Muthén, B. (2018). Dynamic structural equation models. Structural Equation Modeling: A Multidisciplinary Journal, 25(3), 359–388.
- Barlow, D. H., & Nock, M. K. (2009). Why can't we be more idiographic in our research? Perspectives on Psychological Science, 4, 19–21.
- Baumert, A., Schmitt, M., Perugini, M., Johnson, W., Blum, G., Borkenau, P., … Jayawickreme, E. (2017). Integrating personality structure, personality process, and personality development. European Journal of Personality, 31, 503–528. https://doi.org/10.1002/per.2115.
- Beck, E. D., & Jackson, J. J. (2018, February 21). Consistency and change in idiographic personality: A longitudinal ESM network study. Journal of Personality and Social Psychology. https://doi.org/10.17605/OSF.IO/PB92Q.
- Beer, R. D. (2000). Dynamical approaches to cognitive science. Trends in Cognitive Science, 4(3), 91–99.
- Benet-Martínez, V., Donnellan, M. B., Fleeson, W., Fraley, R. C., Gosling, S. D., King, L. A., … Funder, D. C. (2015). Six visions for the future of personality psychology. APA Handbook of Personality and Social Psychology, 4, 665–689.
- Brown, A. D. (2017 ). TheDynamics of Affect: Using Newtonian Mechanics, Reinforcement Sensitivity Theory, and the Cues-Tendencies-Actions Model to Simulate Individual Differences in Emotional Experience (Doctoral dissertation, Northwestern University).
- Butner, J. E., Berg, C. A., Baucom, B. R., & Wiebe, D. J. (2014). Modeling coordination in multiple simultaneous latent change scores. Multivariate behavioral research, 49(6), 554–570.
- Butner, J. E., Gagnon, K. T., Geuss, M. N., Lessard, D. A., & Story, T. N. (2014). Utilizing topology to generate and test theories of change. Psychological Methods, 20, 1.
- Chow, S. M., Ram, N., Boker, S. M., Fujita, F., & Clore, G. (2005). Emotion as a thermostat: representing emotion regulation using a damped oscillator model. Emotion, 5(2), 208–225.
- Colman, D. E., Vineyard, J., & Letzring, T. D. (2017). Exploring beyond simple demographic variables: Differences between traditional laboratory samples and crowdsourced online samples on the Big Five personality traits. Personality and Individual Differences. Advance online publication, 133, 41–46. https://doi.org/10.1016/j.paid.2017.06.023.
- Cook, J., Tyson, R., White, J., Rushe, R., Gottman, J., & Murray, J. (1995). Mathematics of marital conflict: Qualitative dynamic mathematical modeling of marital interaction. Journal of Family Psychology, 9, 110.
- Cooper, W. H., & Withey, M. J. (2009). The strong situation hypothesis. Personality and Social Psychology Review, 13(1), 62–72.
- Costantini, G., Epskamp, S., Borsboom, D., Perugini, M., Mõttus, R., Waldorp, L. J., & Cramer, A. O. (2015). State of the aRt personality research: A tutorial on network analysis of personality data in R. Journal of Research in Personality, 54, 13–29.
- De Bot, K., Lowie, W., & Verspoor, M. (2007). A dynamic view as a complementary perspective. Bilingualism: language and Cognition, 10(1), 51–55.
- Deboeck, P. R., & Bergeman, C. S. (2013). The reservoir model: A differential equation model of psychological regulation. Psychological Methods, 18(2), 237–256. https://doi.org/10.1037/a0031603
- de Haan-Rietdijk, S., Voelkle, M. C., Keijsers, L., & Hamaker, E. L. (2017). Discrete-vs. continuous-time modeling of unequally spaced experience sampling method data. Frontiers in Psychology, 8, 1849.
- Edwards, T., & Holtzman, N. S. (2017). A meta-analysis of correlations between depression and first person singular pronoun use. Journal of Research in Personality, 68, 63–68. https://doi.org/10.1016/j.jrp.2017.02.005.
- Endler, N. S., & Magnusson, D. (1976). Toward an interactional psychology of personality. Psychological Bulletin, 83(5), 956–974.
- Epskamp, S., Borsboom, D., & Fried, E. I. (2018). Estimating psychological networks and their accuracy: A tutorial paper. Behavior Research Methods, 50(1), 195–212.
- Ferrer, E., & McArdle, J. J. (2010). Longitudinal modeling of developmental changes in psychological research. Current Directions in Psychological Science, 19, 149–154.
- Finnigan, K. M., & Vazire, S. (2017). The incremental validity of average state self-reports over global self-reports of personality. Journal of Personality and Social Psychology. Advance online publication, 115, 321–337. https://doi.org/10.1037/pspp0000136.
- Fisher, A. J., Medaglia, J. D., & Jeronimus, B. F. (2018). Lack of group-to-individual generalizability is a threat to human subjects research. Proceedings of the National Academy of Sciences, 115, E6106–E6115.
- Fleeson, W. (2001). Toward a structure-and process-integrated view of personality: Traits as density distributions of states. Journal of Personality and Social Psychology, 80, 1011–1027.
- Fleeson, W. (2004). Moving personality beyond the person-situation debate: The challenge and the opportunity of within-person variability. Current Directions in Psychological Science, 13, 83–87.
- Fleeson, W., & Jayawickreme, E. (2015). Whole trait theory. Journal of Research in Personality, 56, 82–92. https://doi.org/10.1016/j.jrp.2014.10.009.
- Ghahramani, A., Pantelic, J., Lindberg, C., Mehl, M., Srinivasan, K., Gilligan, B., & Arens, E. (2018). Learning occupants’ workplace interactions from wearable and stationary ambient sensing systems. Applied energy, 230, 42–51.
- Gottman, J., Swanson, C., & Murray, J. (1999). The mathematics of marital conflict: Dynamic mathematical nonlinear modeling of newlywed marital interaction. Journal of Family Psychology, 13, 3.
- Gottman, J., Swanson, C., & Swanson, K. (2002). A general systems theory of marriage: Nonlinear difference equation modeling of marital interaction. Personality and Social Psychology Review, 6, 326–340.
- Grimm, K., Zhang, Z., Hamagami, F., & Mazzocco, M. (2013). Modeling nonlinear change via latent change and latent acceleration frameworks: Examining velocity and acceleration of growth trajectories. Multivariate Behavioral Research, 48, 117–143. https://doi.org/10.1080/00273171.2012.755111.
- Haken, H., Kelso, J. S., & Bunz, H. (1985). A theoretical model of phase transitions in human hand movements. Biological cybernetics, 51(5), 347–356.
- Hinich, M. J. (1982). Testing for Gaussianity and linearity of a stationary time series. Journal of Time Series Analysis, 3, 169–176.
10.1111/j.1467-9892.1982.tb00339.x Google Scholar
- Hinich, M. J., & Wolinsky, M. A. (1988). A test for aliasing using bispectral analysis. Journal of the American Statistical Association, 83, 499–502.
- Hudson, N. W., & Fraley, R. C. (2015). Volitional personality trait change: Can people choose to change their personality traits? Journal of Personality and Social Psychology, 109, 490–507. https://doi.org/10.1037/pspp0000021.
- Jayasuriya, B. (1996). Testing for polynomial regression using nonparametric regression techniques. Journal of the American Statistical Association, 91, 1626–1631.
- John, O. P., & Srivastava, S. (1999). The Big Five trait taxonomy: History, measurement, and theoretical perspectives. Handbook of Personality: Theory and Research, 2, 102–138.
- Lerner, R. M. (1996). Relative plasticity, integration, temporality, and diversity in human development: A developmental contextual perspective about theory, process, and method. Developmental psychology, 32(4), 781–786.
- Lorenz, E. (2000). The butterfly effect. World Scientific Series on Nonlinear Science Series A, 39, 91–94.
10.1142/9789812386472_0007 Google Scholar
- Lucas, R. E. (2007). Adaptation and the set-point model of subjective well-being: Does happiness change after major life events?. Current Directions in Psychological Science, 16(2), 75–79.
- Magnusson, D., & Torestad, B. (1993). A holistic view of personality: A model revisited. Annual review of psychology, 44(1), 427–452.
- Mayer, J. D. (2015). The personality systems framework: Current theory and development. Journal of Research in Personality, 56, 4–14. https://doi.org/10.1016/j.jrp.2015.01.001.
- McArdle, J. J. (2009). Latent variable modeling of differences and changes with longitudinal data. Annual Review of Psychology, 60, 577–605. https://doi.org/10.1146/annurev.psych.60.110707.163612.
- McArdle, J. J., & Grimm, K. J. (2010). Five steps in latent curve and latent change score modeling with longitudinal data. In Longitudinal research with latent variables (pp. 245–273). Berlin, Heidelberg: Springer.
- McArdle, J. J., & Nesselroade, J. R. (2014). Longitudinal data analysis using structural equation models. Washington, DC: American Psychological Association.
10.1037/14440-000 Google Scholar
- McCabe, K. O., & Fleeson, W. (2012). What is extraversion for? Integrating trait and motivational perspectives and identifying the purpose of extraversion. Psychological science, 23(12), 1498–1505.
- McElreath, R., & Boyd, R. (2008). Mathematical models of social evolution: A guide for the perplexed. University of Chicago Press.
- Mischel, W., & Shoda, Y. (1995). A cognitive-affective system theory of personality: Reconceptualizing situations, dispositions, dynamics, and invariance in personality structure. Psychological Review, 102, 246–268. https://doi.org/10.1037/0033-295x.102.2.246.
- Mischel, W., Shoda, Y., & Mendoza-Denton, R. (2002). Situation-behavior profiles as a locus of consistency in personality. Current Directions in Psychological Science, 11(2), 50–54.
- Molenaar, P. C. (2004). A manifesto on psychology as idiographic science: Bringing the person back into scientific psychology, this time forever. Measurement, 2, 201–218.
10.1207/s15366359mea0204_1 Google Scholar
- Molenaar, P. C., & Campbell, C. G. (2009). The new person-specific paradigm in psychology. Current Directions in Psychological Science, 18, 112–117.
- Nason, G. P., Powell, B., Elliott, D., & Smith, P. A. (2017). Should we sample a time series more frequently?: Decision support via multirate spectrum estimation. Journal of the Royal Statistical Society: Series A (Statistics in Society), 180, 353–407.
- Nowak, M. A. (2006). Evolutionary dynamics: exploring the equations of life. Harvard University Press.
10.2307/j.ctvjghw98 Google Scholar
- Oravecz, Z., Tuerlinckx, F., & Vandekerckhove, J. (2016). Bayesian data analysis with the bivariate hierarchical Ornstein-Uhlenbeck process model. Multivariate Behavioral Research, 51(1), 106–119.
- Otto, S. P., & Day, T. (2011). A biologist's guide to mathematical modeling in ecology and evolution. Princeton University Press.
10.2307/j.ctvcm4hnd Google Scholar
- Pelham, B. W. (1993). The idiographic nature of human personality: Examples of the idiographic self-concept. Journal of Personality and Social Psychology, 64, 665–677. https://doi.org/10.1037//0022-3514.64.4.665.
- Prentice, M., Jayawickreme, E., & Fleeson, W. (2019). Integrating whole trait theory and self-determination theory. Journal of personality, 87(1), 56–69.
- Rabinovich, M. I., Varona, P., Selverston, A. I., & Abarbanel, H. D. (2006). Dynamical principles in neuroscience. Reviews of modern physics, 78(4), 1213.
- Ram, N., & Gerstorf, D. (2009). Time-structured and net intraindividual variability: Tools for examining the development of dynamic characteristics and processes. Psychology and aging, 24(4), 778–791.
- Read, S. J., Droutman, V., & Miller, L. C. (2017). Virtual personalities: A neural network model of the structure and dynamics of personality. In Computational social psychology (pp. 15–37). Abingdon, Oxon: Routledge.
10.4324/9781315173726-2 Google Scholar
- Read, S. J., & Miller, L. C. (2002). Virtual personalities: A neural network model of personality. Personality and Social Psychology Review, 6, 357–369.
- Revelle, W., & Condon, D. M. (2015). A model for personality at three levels. Journal of Research in Personality, 56, 70–81.
- Richardson, M. J., Dale, R., & Marsh, K. L. (2014). Complex dynamical systems in social and personality psychology. Handbook of research methods in social and personality psychology, 253.
- Roberts, B. W., Luo, J., Briley, D. A., Chow, P. I., Su, R., & Hill, P. L. (2017). A systematic review of personality trait change through intervention. Psychological Bulletin, 143, 117–141. https://doi.org/10.1037/bul0000088.
- Roberts, B. W., & Mroczek, D. (2008). Personality trait change in adulthood. Current Directions in Psychological Science, 17, 31–35. https://doi.org/10.1111/j.1467-8721.2008.00543.x.
- Schmittmann, V. D., Cramer, A. O., Waldorp, L. J., Epskamp, S., Kievit, R. A., & Borsboom, D. (2013). Deconstructing the construct: A network perspective on psychological phenomena. New ideas in psychology, 31(1), 43–53.
- Smaldino, P., Lukaszewski, A., Von Rueden, C., & Gurven, M. (2019). Niche diversity can explain cross-cultural differences in personality structure. Pre-print on PsyArXiv: https://psyarxiv.com/53wxg/
- Solomon, B. C., & Vazire, S. (2014). You are so beautiful … to me: Seeing beyond biases and achieving accuracy in romantic relationships. Journal of Personality and Social Psychology, 107, 516–528. https://doi.org/10.1037/a0036899.
- Sosnowska, J., Kuppens, P., De Fruyt, F., & Hofmans, J. (2019). A dynamic systems approach to personality: The Personality Dynamics (PersDyn) model. Personality and Individual Differences, 144, 11–18. https://doi.org/10.1016/j.paid.2019.02.013.
- Specht, J., Egloff, B., & Schmukle, S. C. (2011). Stability and change of personality across the life course: the impact of age and major life events on mean-level and rank-order stability of the Big Five. Journal of Personality and Social Psychology, 101(4), 862–882.
- Sun, J., Schwartz, H. A., Son, Y., Kern, M. L., & Vazire, S. (2019). The language of well-being: Tracking fluctuations in emotion experience through everyday speech.
- Sun, J., & Vazire, S. (2018). Do people know what they're like in the moment? Psychological Science, 0956797618818476.
- Vallacher, R. R., Read, S. J., & Nowak, A. (Eds.). (2017). Computational social psychology. Abingdon, Oxon: Routledge.
10.4324/9781315173726 Google Scholar
- Van Geert, P. (1991). A dynamic systems model of cognitive and language growth. Psychological review, 98(1), 3–53.
- Vazire, S., & Sherman, R. A. (2017). Introduction to the special issue on within-person variability in personality.
- Vazire, S., Wilson, R. E., Solomon, B., Bollich, K., Harris, K., Weston, S., & Jackson, J. J. (2015). Personality and Interpersonal Roles (PAIRS). Study in progress.
- Wilson, R. E., Harris, K., & Vazire, S. (2015). Personality and friendship satisfaction in daily life: Do everyday social interactions account for individual differences in friendship satisfaction? European Journal of Personality, 29, 173–186. https://doi.org/10.1002/per.1996.
- Wilson, R. E., Thompson, R. J., & Vazire, S. (2017). Are fluctuations in personality more than just fluctuations in affect? Journal of Research in Personality, 69, 110–123. https://doi.org/10.1016/j.jrp.2016.06.006.
- Wrzus, C., & Roberts, B. W. (2017). Processes of personality development in adulthood: The TESSERA framework. Personality and Social Psychology Review, 21(3), 253–277.
- Zimmerman, M., Harris, L., Martin, J., & McGonigal, P. (2018). Reliability and validity of a self-report scale for daily assessments of the severity of depressive symptoms. Psychiatry research, 270, 581–586.
Citing Literature
Special Issue:New approaches towards conceptualizing and assessing personality
November/December 2020
Pages 999-1016
