Abstract
This study explored the use of dynamical systems modeling techniques to evaluate self- and co-regulation of affect in couples’ interactions before and after the transition to parenthood, and the impact of the Family Foundations program on these processes. Thirty-four heterosexual couples, randomized to intervention and control conditions, participated in videotaped dyadic interaction tasks at pretest (during pregnancy) and posttest (1 year after birth). Husbands’ and wives’ positivity and negativity were micro-coded throughout interactions. Individual negativity set-points, self-regulation, and partner co-regulatory processes during interactions were examined using a coupled oscillators model. Regarding self-regulatory processes, men exhibited amplification of negativity at the prenatal assessment that did not change at the postnatal assessment; women demonstrated no significant damping or amplification at pretest and a marginally significant change towards greater amplification at the postnatal assessment. In terms of partner-influenced regulatory dynamics, men’s positive behaviors changed from damping to amplifying women’s negative behaviors in the control group following the transition to parenthood, but exerted an even stronger damping effect on women’s negative behaviors in the intervention group. The study highlights the advantages of dynamic modeling approaches in testing specific hypotheses in the study of self- and co-regulatory couple dynamics and demonstrates the potential of studying dynamic processes to further understanding of developmental and intervention-related change mechanisms.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Notes
This was justified due to the randomization procedure used to assign families to the intervention vs. the control group at pretest.
We also explored the need to allow for between-couple differences in the modeling parameters by incorporating random effects in subsets of the parameters sequentially and evaluating the magnitudes of the random effects SDs as well as the changes in model fit when these random effects were included vs. excluded from the model. Even though almost all of the modeling parameters were characterized by statistically significant between-couple differences (namely, the 95% confidence intervals (CIs) of the associated random effects SDs did not include 0), we had to limit the number of random effects included in our final model due to the limited sample size of the present study.
References
Belsky, J. (1986). Transition to parenthood. Medical Aspects of Human Sexuality, 20, 56–59.
Boker, S. M., & Graham, J. (1998). A dynamical systems analysis of adolescent substance abuse. Multivariate Behavioral Research, 33, 479–507. doi:10.1207/s15327906mbr3304_3.
Boker, S. M., & Laurenceau, J.-P. (2007). Coupled dynamics and mutually adaptive context. In T. D. Little, J. A. Bovaird, & N. A. Card (Eds.), Modeling contextual effects in longitudinal studies (Vol. Vol. viii, pp. 299–324). Mahwah: Lawrence Erlbaum Associates Publishers.
Boker, S. M., Schreiber, T., Pompe, B., & Bertenthal, B. (1997). Nonlinear analysis of perceptual-motor coupling in the development of postural control. In H. H. G. Meyer-Kress, A. G. Kurths (Eds.), Nonlinear techniques in physiological time series analysis. Berlin: Springer-Verlag.
Chow, S., Bendezú, J. J., Cole, P. M., & Ram, N. (2016). A comparison of two-stage approaches for fitting nonlinear ordinary differential equation (ODE) models with mixed effects. Multivariate Behavioral Research, 51, 154–184.
Chow, S. M., Lu, O., Cohn, J. F., & Messinger, D. S. (2017). Representing self-organization and non-stationarities in dyadic interaction processes using dynamic systems modeling techniques. In A. Von Davier & P. Kyllonen (Eds.), Innovative assessment of collaboration. Switzerland: Springer International Publishing.
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, 208–225.
Cowan, C. P., & Cowan, P. A. (2000). When partners become parents: The big life change for couples. Mahwah: Lawrence Erlbaum Associates, Inc., Publishers.
Feinberg, M. (2002). Coparenting and the transition to parenthood: A framework for prevention. Clinical Child & Family Psychology Review, 5, 173–195.
Feinberg, M. E., Jones, D., Roettger, M., Hostetler, M., Sakuma, K., Paul, I., & Ethrenthal, D. (2015). Preventive effects on birth outcomes: Buffering impact of maternal stress, depression, & anxiety. Maternal and Child Health Journal. doi:10.1007/s10995-015-1801-3.
Feinberg, M. E., Jones, D. E., Kan, M. L., & Goslin, M. C. (2010). Effects of family foundations on parents and children: 3.5 years after baseline. Journal of Family Psychology, 24, 532–542.
Feinberg, M. E., & Kan, M. L. (2008). Establishing Family Foundations: Intervention effects on coparenting, parent/infant well-being, and parent-child relations. Journal of Family Psychology, 22, 253–263.
Feinberg, M. E., Kan, M. L., & Goslin, M. C. (2009). Enhancing coparenting, parenting, and child self-regulation: Effects of Family Foundations 1 year after birth. Prevention Science, 10, 276–285. doi:10.1007/s11121-009-0142-0.
Ferrer, E., & Helm, J. L. (2013). Dynamical systems modeling of physiological coregulation in dyadic interactions. International Journal of Psychophysiology, 88, 296–308.
Ferrer, E., & Nesselroade, J. R. (2003). Modeling affective processes in dyadic relations via dynamic factor analysis. Emotion, 3, 344–360.
Fosco, G. M., Bumbarger, B., Bamberger, K. T., & Van Ryzin, M. J. (2016). Thinking systematically for enduring family change. In M. Van Ryzin, K. Kumpfer, G.M. Fosco, & M. Greenberg (Eds.), Family-based prevention programs for children and adolescents: theory, research, and large-scale dissemination. New York: Routledge.
Gottman, J. M., Swanson, C., & Murray, J. (1999). The mathematics of marital conflict: Dynamic mathematical nonlinear modeling of newlywed marital interaction. Journal of Family Psychology, 13, 3–19.
Gottman, J. M., Swanson, C., & Swanson, K. A. (2002). General systems theory of marriages: Nonlinear difference equation modeling of marital interaction. Personality and Social Psychology Review, 6, 326–340.
Granic, I., O'Hara, A., Pepler, D., & Lewis, M. D. (2007). A dynamic systems analysis of parent-child changes associated with successful “real-world” interventions for aggressive children. Journal of Abnormal Child Psychology, 35, 845–857. doi:10.1007/s10802-007-9133-4.
Heron, J., O'Connor, T. G., Evans, J., Golding, J., & Glover, V. (2004). The course of anxiety and depression through pregnancy and the postpartum in a community sample. Journal of Affective Disorders, 80, 65–73.
Heyman, R. E. (2004). Rapid marital interaction coding system. In P. K. Kerig & D. H. Baucom (Eds.), Couple observational coding systems (pp. 67–94). Mahwah: Routledge Taylor & Francis Group.
Heyman, R. E., & Vivian, D. (2011). Rapid marital interaction coding system. www.psychology.sunysb.edu/ftrlab. Stony Brook.
Hu, Y., Boker, S. M., Neale, M., & Klump, K. L. (2014). Coupled latent differential equation with moderators: Simulation and application. Psychological Methods, 19, 56–71. doi:10.1037/a0032476.
Kan, M. L., & Feinberg, M. E. (2014). Can a family-focused, transition-to-parenthood program prevent parent and partner aggression among couples with young children? Violence and Victims, 29, 967–980.
Kazdin, A. E. (2007). Mediators and mechanisms of change in psychotherapy research. Annual Review of Clinical Psychology, 3, 1–27. doi:10.1146/annurev.clinpsy.3.022806.091432.
Larsen, R. J. (1985). A mulitrait-multimethod examination of affect structure: Hedonic level and emotional intensity. Personality and Individual Differences, 6, 631–636.
Larsen, R. J., Diener, E., & Emmons, R. A. (1986). Affect intensity and reactions to daily life events. Journal of Personality and Social Psychology, 51, 803.
Liddle, H. A. (2004). Family-based therapies for adolescent alcohol and drug use: Research contributions and future research needs. Addiction, 99, 76–92. doi:10.1111/j.1360-0443.2004.00856.x.
Moskowitz, D. S. (1982). Coherence and cross-situational generality in personality: A new analysis of old problems. Journal of Personality and Social Psychology, 43, 754–768. doi:10.1037/0022-3514.43.4.754.
Pinheiro, J., Bates, D., DebRoy, S., Sarkar, D., & R Core Team. (2014). Linear and nonlinear mixed effects models. http://CRAN.R-project.org/package=nlme.
Ramsay, J. O., Hooker, G., & Graves, S. (2009). Functional data analysis with R and MATLAB. New York: Springer-Verlag.
Ramsay, J. O., & Silverman, B. W. (2005). Functional data analysis (Second ed.). New York: Springer.
Richards, J. M., Butler, E. A., & Gross, J. J. (2003). Emotion regulation in romantic relationships: The cognitive consequences of concealing feelings. Journal of Social and Personal Relationships, 20, 599–620.
Sandler, I. N., Schoenfelder, E. N., Wolchik, S. A., & MacKinnon, D. P. (2011). Long-term impact of prevention programs to promote effective parenting: Lasting effects but uncertain processes. Annual Review of Psychology, 62, 299–329. doi:10.1146/annurev.psych.121208.131619.
Trail, J. B., Collins, L. M., Rivera, D. E. L., Li, R., Piper, M. E., & Baker, T. B. (2013). Functional data analysis for dynamical system identification of behavioral processes. Psychological Methods, 19, 175–182.
Van Ryzin, M. J., Kumpfer, K. L., Fosco, G. M. G., & M.T. (2015). Family-based prevention programs for children and adolescents: Theory, research, and large-scale dissemination. New York: Psychology Press.
Vohs, K. D., & Heatherton, T. F. (2000). Self-regulatory failure: A resource-depletion approach. Psychological Science, 11, 249–254.
Xu, S., & Lorber, M. F. (2014). Interrater agreement statistics with skewed data: Evaluation of alternatives to Cohen’s kappa. Journal of Consulting and Clinical Psychology, 82, 1219–1227.
Acknowledgments
The authors would like to thank the participating families in this study.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Funding
The data collection was funded by a grant from the National Institute of Child Health and Development (HD058529) to Mark Feinberg, PI, for a trial of Family Foundations. Sy-Miin Chow’s work on this project was supported by NSF grant SES-1357666 and NIH grant GM105004.
Conflict of Interest
Dr. Feinberg created Family Foundations and is the owner of a private company that disseminates the program. Dr. Feinberg’s company has been reviewed by the Institutional Review Board and the Conflict of Interest Committee at Pennsylvania State University for potential financial gain.
Ethical Approval
The Penn State IRB approved this research.
Informed Consent
Participants completed IRB-approved consent forms.
Electronic supplementary material
ESM 1
(DOCX 71 kb)
Rights and permissions
About this article
Cite this article
Feinberg, M.E., Xia, M., Fosco, G.M. et al. Dynamical Systems Modeling of Couple Interaction: a New Method for Assessing Intervention Impact Across the Transition to Parenthood. Prev Sci 18, 887–898 (2017). https://doi.org/10.1007/s11121-017-0803-3
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11121-017-0803-3