Abstract
Parental burnout results from chronic stress in parenting, and it can be accompanied by harmful behaviors such as parental neglect and violence (Mikolajczak & Roskam, 2018). Network analysis examines psychological phenomena within a system of its constituents, and thus it is promising for understanding the distinct features of parental burnout and behaviors related to it. Recently, Blanchard et al. (2021) conducted the first network analysis of parental burnout and related harmful behaviors in the family context, but did so using an outdated measure and conceptualization of parental burnout. In the present study, in a sample of French-speaking parents (N = 3144, from five different previous studies), we aimed to investigate how each of the four features in the new conceptualization of parental burnout (i.e., emotional exhaustion, feeling fed up, emotional distance, and contrast with the previous parental self) interact with one another and with parental neglect and violence in a network system. In this preregistered reanalysis, we generated two network models commonly used with cross-sectional data: a Graphical Gaussian Model and a Directed Acyclic Graph. Our results point to emotional exhaustion and feeling fed up as key driving forces of the network structure, while emotional distance appears as a critical feature tying parental burnout with parental neglect and violence.
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Preregistration and data availability
The data analysis for this study was preregistered on the Open Science Framework (https://osf.io/vqmzb). The anonymized aggregated data is available on the Open Science Framework (https://osf.io/bpz65/), as is the R code used for analyses (https://osf.io/xkb9r/).
Notes
When administering the PBA, a global score is calculated by summing all items. However, we were interested in the subscale scores, and for the purposes of our network analyses we wanted all subscale scores to be on the scale, and so we calculated the mean of each subscale. In doing so, we followed our preregistration.
References
Arikan, G., Üstündağ-Budak, A. M., Akgün, E., Mikolajczak, M., & Roskam, I. (2020). Validation of the Turkish version of the Parental Burnout Assessment (PBA). New Directions for Child and Adolescent Development, 2020(174), 15–32. https://doi.org/10.1002/cad.20375
Aunola, K., Sorkkila, M., & Tolvanen, A. (2020). Validity of the Finnish version of the Parental Burnout Assessment (PBA). Scandinavian Journal of Psychology, 61(5), 714–722. https://doi.org/10.1111/sjop.12654
Barabási, A.-L., & Albert, R. (1999). Emergence of Scaling in Random Networks. Science, 286(5439), 509–512. https://doi.org/10.1126/science.286.5439.509
Bavelas, J. B., & Segal, L. (1982). Family Systems Theory: Background and Implications. Journal of Communication, 32(3), 99–107. https://doi.org/10.1111/j.1460-2466.1982.tb02503.x
Bernstein, E. E., Heeren, A., & McNally, R. J. (2019). Reexamining trait rumination as a system of repetitive negative thoughts: A network analysis. Journal of Behavior Therapy and Experimental Psychiatry, 63, 21–27. https://doi.org/10.1016/J.JBTEP.2018.12.005
Blanchard, A., & Heeren, A. (2022). Ongoing and Future Challenges of the Network Approach to Psychopathology: From Theoretical Conjectures to Clinical Translations (pp. 32–46). https://doi.org/10.1016/B978-0-12-818697-8.00044-3
Blanchard, M. A., Roskam, I., Mikolajczak, M., & Heeren, A. (2021). A network approach to parental burnout. Child Abuse and Neglect, 111(November 2020), 1–12. https://doi.org/10.1016/j.chiabu.2020.104826
Blanchard, M. A., & Heeren, A. (2020). Why we should move from reductionism and embrace a network approach to parental burnout. New Directions for Child and Adolescent Development, 2020(174), 159–168. https://doi.org/10.1002/cad.20377
Borgatti, S. (2005). Centrality and Network Flow. Social Networks, 27, 55–71. https://doi.org/10.1016/j.socnet.2004.11.008
van Borkulo, C., van Bork, R., Boschloo, L., Kossakowski, J., Tio, P., Schoevers, R., Borsboom, D., & Waldorp, L. (2017). Comparing network structures on three aspects: A permutation test. https://doi.org/10.13140/RG.2.2.29455.38569
Bornstein, M. H. (2012). Cultural Approaches to Parenting. Parenting, Science and Practice, 12(2–3), 212. https://doi.org/10.1080/15295192.2012.683359
Borsboom, D. (2017). A network theory of mental disorders. World Psychiatry, 16(1), 5–13. https://doi.org/10.1002/wps.20375
Borsboom, D., & Cramer, A. O. J. (2013). Network Analysis: An Integrative Approach to the Structure of Psychopathology. Annual Review of Clinical Psychology, 9(1), 91–121. https://doi.org/10.1146/annurev-clinpsy-050212-185608
Borsboom, D., Cramer, A. O. J., Schmittmann, V. D., Epskamp, S., & Waldorp, L. J. (2011). The small world of psychopathology. PLoS ONE, 6(11), 1–11. https://doi.org/10.1371/journal.pone.0027407
Brianda, M. E., Roskam, I., Gross, J. J., Franssen, A., Kapala, F., Gérard, F., & Mikolajczak, M. (2020). Treating parental burnout: Impact of two treatment modalities on burnout symptoms, emotions, hair cortisol, and parental neglect and violence. Psychotherapy and Psychosomatics, 89(5), 330–332. https://doi.org/10.1159/000506354
Bringmann, L. F., Elmer, T., Epskamp, S., Krause, R. W., Schoch, D., Wichers, M., Wigman, J. T. W., & Snippe, E. (2019). What do centrality measures measure in psychological networks? Journal of Abnormal Psychology. https://doi.org/10.1037/ABN0000446
Contreras, A., Nieto, I., Valiente, C., Espinosa, R., & Vazquez, C. (2019). The study of psychopathology from the network analysis perspective: A systematic review. Psychotherapy and Psychosomatics, 88, 1–13. https://doi.org/10.1159/000497425
Costenbader, E., & Valente, T. W. (2003). The stability of centrality measures when networks are sampled. Social Networks, 25(4), 283–307. https://doi.org/10.1016/S0378-8733(03)00012-1
Csardi, G., & Nepusz, T. (2006). The igraph software package for complex network research. InterJournal Complex Systems, Complex Sy (1695), 1695. http://igraph.sf.net
Delima, J., & Vimpani, G. (2021). The neurobiological effects of childhood maltreatment: An often overlooked narrative related to the long-term effects of early childhood trauma? Family Matters. https://doi.org/10.3316/ielapa.717010661945019
Dupont, S., Mikolajczak, M., & Roskam, I. (2022). The Cult of the Child: A Critical Examination of Its Consequences on Parents, Teachers and Children. Social Sciences 2022, Vol. 11, Page 141, 11(3), 141. https://doi.org/10.3390/SOCSCI11030141
Elliott, H., Jones, P. J., & Schmidt, U. (2019). Central Symptoms Predict Posttreatment Outcomes and Clinical Impairment in Anorexia Nervosa: A Network Analysis. Clinical Psychological Science, 8(1), 139–154. https://doi.org/10.1177/2167702619865958
Epskamp, S., & Fried, E. I. (2018). A tutorial on regularized partial correlation networks. Psychological Methods, 23(4), 617–634. https://doi.org/10.1037/met0000167
Epskamp, S., Borsboom, D., & Fried, E. I. (2018). Estimating psychological networks and their accuracy: A tutorial paper. Behavior Research Methods, 50(1), 195–212. https://doi.org/10.3758/s13428-017-0862-1
Foygel, R., & Drton, M. (2011). Bayesian model choice and information criteria in sparse generalized linear models. https://doi.org/10.48550/arxiv.1112.5635
Friedman, J.H., Hastie, T., & Tibshirani, R. (2014). Glasso: graphical lasso- estimation of Gaussian graphical models. R package version 1.8.
Furutani, K., Kawamoto, T., Alimardani, M., & Nakashima, K. (2020). Exhausted parents in Japan: Preliminary validation of the Japanese version of the Parental Burnout Assessment. New Directions for Child and Adolescent Development, 2020(174), 33–49. https://doi.org/10.1002/cad.20371
Gannagé, M., Besson, E., Harfouche, J., Roskam, I., & Mikolajczak, M. (2020). Parental burnout in Lebanon: Validation psychometric properties of the Lebanese Arabic version of the Parental Burnout Assessment. New Directions for Child and Adolescent Development, 2020(174), 51–65. https://doi.org/10.1002/cad.20383
Heeren, A., Bernstein, E. E., & McNally, R. J. (2020). Bridging maladaptive social self-beliefs and social anxiety: A network perspective. Journal of Anxiety Disorders, 74, 102267. https://doi.org/10.1016/j.janxdis.2020.102267
Hittner, J. B., May, K., & Silver, N. C. (2003). A monte carlo evaluation of tests for comparing dependent correlations. Journal of General Psychology, 130(2), 149–168. https://doi.org/10.1080/00221300309601282
Hubert, S., & Aujoulat, I. (2018). Parental burnout: When exhausted mothers open up. Frontiers in Psychology, 9(JUN), 1–9. https://doi.org/10.3389/fpsyg.2018.01021
Jiang, H., Fei, X., Liu, H., Roeder, K., Lafferty, J., Wasserman, L., Li, X., & Zhao, T. (2019). Huge: High-dimensional undirected graph estimation. R package version 1.3.2. https://CRAN.R-project.org/package=huge
Jones, P. J., Ma, R., & McNally, R. J. (2019). Bridge Centrality: A Network Approach to Understanding Comorbidity. Multivariate Behavioral Research, 1–15. https://doi.org/10.1080/00273171.2019.1614898
Kawamoto, T., Furutani, K., & Alimardani, M. (2018). Preliminary validation of Japanese version of the parental burnout inventory and its relationship with perfectionism. Frontiers in Psychology, 9(JUN), 970. https://doi.org/10.3389/FPSYG.2018.00970/BIBTEX
Le Vigouroux, S., Charbonnier, E., & Scola, C. (2022). Profiles and age-related differences in the expression of the three parental burnout dimensions. European Journal of Developmental Psychology, 1–20,. https://doi.org/10.1080/17405629.2021.1990749
Matias, M., Aguiar, J., César, F., Braz, A. C., Barham, E. J., Leme, V., Elias, L., Gaspar, M. F., Mikolajczak, M., Roskam, I., & Fontaine, A. M. (2020). The Brazilian-Portuguese version of the Parental Burnout Assessment: Transcultural adaptation and initial validity evidence. New Directions for Child and Adolescent Development, 2020(174), 67–83. https://doi.org/10.1002/cad.20374
McNally, R. J. (2016). Can network analysis transform psychopathology? Behaviour Research and Therapy, 86, 95–104. https://doi.org/10.1016/j.brat.2016.06.006
McNally, R. J., Heeren, A., & Robinaugh, D. J. (2017). A Bayesian network analysis of posttraumatic stress disorder symptoms in adults reporting childhood sexual abuse. European Journal of Psychotraumatology, 8(sup3), 1341276. https://doi.org/10.1080/20008198.2017.1341276
Mikolajczak, M., Brianda, M. E., Avalosse, H., & Roskam, I. (2018). Consequences of parental burnout: Its specific effect on child neglect and violence. Child Abuse and Neglect, 80(March), 134–145. https://doi.org/10.1016/j.chiabu.2018.03.025
Mikolajczak, M., Gross, J. J., & Roskam, I. (2019). Parental Burnout: What Is It, and Why Does It Matter? Clinical Psychological Science, 7(6), 1319–1329. https://doi.org/10.1177/2167702619858430
Mikolajczak, M., & Roskam, I. (2018). A theoretical and clinical framework for parental burnout: The balance between risks and resources (BR2). Frontiers in Psychology, 9(JUN). https://doi.org/10.3389/fpsyg.2018.00886
National Scientific Council on the Developing Child. (2010). Early experiences can alter gene expression and affect long-term development: working paper. Center on the Developing Child at Harvard University, 1(10), 1–12. http://doi.wiley.com/10.1111/j.1151-2916.1918.tb17232.x
Papini, S., Rubin, M., Telch, M., Smits, J., & Hien, D. (2019). Pretreatment PTSD symptom network metrics predict the strength of the association between node change and network change during treatment. Journal of Traumatic Stress. https://doi.org/10.1002/jts.22379
Reichardt, J., & Bornholdt, S. (2006). Statistical mechanics of community detection. Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, 74(1), 1–14. https://doi.org/10.1103/PhysRevE.74.016110
Robinaugh, D. J., Hoekstra, R. H. A., Toner, E. R., & Borsboom, D. (2020). The network approach to psychopathology: A review of the literature 2008–2018 and an agenda for future research. Psychological Medicine, 50(3), 353–366. https://doi.org/10.1017/S0033291719003404
Roskam, I., Aguiar, J., Akgun, E., Arikan, G., Artavia, M., & Avalosse, H. (2021). Parental Burnout Around the Globe : A 42-Country Study. Affective Science, 2(1), 58–79.
Roskam, I., Raes, M. E., & Mikolajczak, M. (2017). Exhausted parents: Development and preliminary validation of the parental burnout inventory. Frontiers in Psychology, 8(FEB), 1–12. https://doi.org/10.3389/fpsyg.2017.00163
Roskam, I., Brianda, M. E., & Mikolajczak, M. (2018). A step forward in the conceptualization and measurement of parental burnout: The Parental Burnout Assessment (PBA). Frontiers in Psychology, 9(JUN), 1–12. https://doi.org/10.3389/fpsyg.2018.00758
Scutari, M., & Nagarajan, R. (2013). Identifying significant edges in graphical models of molecular networks. Artificial Intelligence in Medicine, 57(3), 207–217. https://doi.org/10.1016/J.ARTMED.2012.12.006
Scutari, M. (2010). Learning Bayesian Networks with the bnlearn R Package. Journal of Statistical Software; Vol 1, Issue 3 (2010) . https://www.jstatsoft.org/v035/i03
Sodi, T., Kpassagou, L. B., Hatta, O., Ndayizigiye, A., Ndayipfukamiye, J.-M., Tenkué, J. N., Bahati, C., & Sezibera, V. (2020). Parenting and parental burnout in Africa. New Directions for Child and Adolescent Development, 2020(174), 101–117. https://doi.org/10.1002/cad.20386
Sorkkila, M., & Aunola, K. (2020). Risk Factors for Parental Burnout among Finnish Parents: The Role of Socially Prescribed Perfectionism. Journal of Child and Family Studies, 29(3), 648–659. https://doi.org/10.1007/S10826-019-01607-1/FIGURES/3
Szczygieł, D., Sekulowicz, M., Kwiatkowski, P., Roskam, I., & Mikolajczak, M. (2020). Validation of the Polish version of the Parental Burnout Assessment (PBA). New Directions for Child and Adolescent Development, 2020(174), 137–158. https://doi.org/10.1002/cad.20385
Terluin, B., De Boer, M. R., & De Vet, H. C. W. (2016). Differences in connection strength between mental symptoms might be explained by differences in variance: Reanalysis of network data did not confirm staging. PLoS ONE, 11(11), e0155205. https://doi.org/10.1371/JOURNAL.PONE.0155205
Traag, V. A., & Bruggeman, J. (2009). Community detection in networks with positive and negative links. Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, 80(3), 1–6. https://doi.org/10.1103/PhysRevE.80.036115
Weston, S. J., Ritchie, S. J., Rohrer, J. M., & Przybylski, A. K. (2019). Recommendations for increasing the transparency of analysis of preexisting data sets. Advances in Methods and Practices in Psychological Science, 2(3), 214–227. https://doi.org/10.1177/2515245919848684
Funding
M. Annelise Blanchard, Moïra Mikolajczak, Isabelle Roskam, and Alexandre Heeren were supported by a Coordinated Research Grant (“BParent”) from the French Community of Belgium (ARC Grant 19/24–100). Alexandre Heeren (FRS-FNRS Research Associate, Grant 1.C.059.18F) and M. Annelise Blanchard (Research Fellow) are both also funded by the FRS-FNRS Belgian National Science Foundation. These funds did not exert any influence or censorship of any kind on the present work.
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This study reanalyzes data that was already collected. These original studies were approved by the institutional review board of the Psychological Sciences Research Institute (UCLouvain, Belgium) and conducted according to the Declaration of Helsinki, with all participants giving their informed consent.
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Moïra Mikolajczak. and Isabelle Roskam have founded the “Training Institute for Parental Burnout”, which delivers training on parental burnout to professionals. The institute did not participate in the funding of this study, nor did it influence the process or the results in any manner. Alexandre Heeren receives honoraria for his editorial work from Elsevier. The other authors have no known conflict of interest to disclose.
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Kalkan, R.B., Blanchard, M.A., Mikolajczak, M. et al. Emotional exhaustion and feeling fed up as the driving forces of parental burnout and its consequences on children: insights from a network approach. Curr Psychol 42, 22278–22289 (2023). https://doi.org/10.1007/s12144-022-03311-8
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DOI: https://doi.org/10.1007/s12144-022-03311-8