Abstract
Research suggests that self-esteem, individuals´ expectancies regarding their ability to deal with future stressors and cognitive control are related and participate in the process of stress regulation. In the current study, 286 participants (51 men and 235 women; ranging from 18 to 89 years old; mean age = 27.53, SD = 10.64) completed online questionnaires to assess self-esteem, expectancy, cognitive control (assessed using measures of attentional and anxiety control), perceived stress, rumination, and symptoms of distress. Network analysis was used to obtain a comprehensive, data-driven view on the complex interplay between these variables. Our analysis shows that high self-esteem is related to more self-efficacy (a measure of expectancy). Self-efficacy, in turn, shows a strong association with more attentional and anxiety control, which are related to lower overall perceived stress during the past month. Moreover, higher perceived stress was related to more symptoms of distress via higher scores in rumination. This study is the first to provide a data-driven test of how individuals with low self-esteem and expectancy, and deficits in cognitive control processes may have difficulties in dealing with daily stressful situations.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data availability
The data that support the findings of this study are available from the corresponding author upon reasonable request.
Code Availability
Code is provided in supplementary materials.
Change history
21 May 2022
A Correction to this paper has been published: https://doi.org/10.1007/s12144-022-03212-w
References
Abel, M. H. (1996). Self-esteem: Moderator or mediator between perceived stress and expectancy of success? Psychological Reports, 79(2), 635–641. https://doi.org/10.2466/pr0.1996.79.2.635
Ahern E., Bockting C. L., & Semkovska M. (2019). A hot-cold cognitive model of depression: integrating the neuropsychological approach into the cognitive theory framework. Clinical Psychology in Europe, 1(3), 1–35. https://doi.org/10.32872/cpe.v1i3.34396
Bandura, A., Reese, L., & Adam, N. E. (1982). Microanalysis of action and fear arousal as a function of diferential levels of perceived self-efficacy. Journal of Personality and Social Psychology, 43, 5–21. https://doi.org/10.1037/0022-3514.43.1.5
Beard C., Millner A. J., Forgeard M. J., Fried E. I., Hsu K. J., Treadway M. T., ... & Björgvinsson T. (2016). Network analysis of depression and anxiety symptom relationships in a psychiatric sample. Psychological Medicine, 46(16), 3359-3369. https://doi.org/10.1017/S0033291716002300
Bringmann L. F., Elmer T., Epskamp S., Krause R. W., Schoch D., Wichers M., ... & Snippe E. (2019). What do centrality measures measure in psychological networks?. Journal of Abnormal Psychology, 128(8), 892-903. https://doi.org/10.1037/abn0000446
Bringmann, L., & Eronen, M. K. (2018). Don’t blame the model: Reconsidering the network approach to psychopathology. Psychological Review, 125(4), 606–615. https://doi.org/10.1037/rev0000108
Borsboom, D., & Cramer, A. O. J. (2013). Networkanalysis: An integrative approach to the structure of psychopathology. Annual Review of Clinical Psychology, 9, 91–121. https://doi.org/10.1146/annurev-clinpsy-050212-185608
Brosschot, J. F., Gerin, W., & Thayer, J. F. (2006). The perseverative cognition hypothesis: A review of worry, prolonged stress-related physiological activation, and health. Journal of Psychosomatic Research, 60, 113–124. https://doi.org/10.1016/j.jpsychores.2005.06.07
Cohen, S., Kamarck, T., & Mermelstein, R. (1983). A global measure of perceived stress. Journal of Health Social Behavior, 24, 385–396. https://doi.org/10.2307/2136404
Costantini, G., Epskamp, S., Borsboom, D., Perugini, M., Mottus, R., Waldorp, L. J., & Cramer, A. O. J. (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. https://doi.org/10.1016/j.jrp.2014.07.003
de Beurs, E., den Hollander-Gijsman, M. E., Helmich, S., & Zitman, F. G. (2007). The tripartite model for assessing symptoms of anxiety and depression: Psychometrics of the Dutch version of the mood and anxiety symptoms questionnaire. Behaviour Research and Therapy, 45(7), 1609–1617. https://doi.org/10.1016/j.brat.2006.07.004
De Raedt, R., & Hooley, J. M. (2016). The role of expectancy and proactive control in stress regulation: A neurocognitive framework for regulation expectation. Clinincal Psychology Review, 45, 45–55. https://doi.org/10.1016/j.cpr.2016.03.005
De Raedt R., & Koster E. H., (2010). Understanding vulnerability for depression from a cognitive Neurosci. perspective: a reappraisal of attentional factors and a new conceptual framework. Cognitive Affective and Behavioral Neuroscience, 10(1), 50–70. https://doi.org/10.3758/CABN.10.1.50.
Derryberry, D., & Reed, M. A. (2002). Anxiety-related attentional biases and their regulation by attentional control. Journal of Abnormal Psychology, 111(2), 225. https://doi.org/10.1037/0021-843X.111.2.225
Eisenberger, N. I., Inagaki, T. K., Muscatell, K. A., Byrne Haltom, K. E., & Leary, M. R. (2011). The neural sociometer: Brain mechanisms underlying state self-esteem. Journal of Cognitive Neuroscience, 23(11), 3448–3455. https://doi.org/10.1162/jocn_a_00027
Epskamp, S., & Fried, E. I. (2018). A tutorial on regularized partial correlation networks. Psychological Methods, 23(4), 617.
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
Epskamp, S., Cramer, A. O., Waldorp, L. J., Schmittmann, V. D., & Borsboom, D. (2012). qgraph: Network visualizations of relationships in psychometric data. Journal of Statistical Software, 48(4), 1–18.
Franck, E., De Raedt, R., Barbez, C., & Rosseel, Y. (2008). Psychometric properties of the Dutch Rosenberg self-esteem scale. Psychologica Belgica, 48(1), 25–35. https://doi.org/10.5334/pb-48-1-25
FruchtermanT. M. & Reingold E. M. (1991). Graph drawing by force directed placement. Software: Practice and Experience, 21, 1129–1164. https://doi.org/10.1002/spe.4380211102
Hankin, B. L. (2008). Cognitive vulnerability-stress model of depression during adolescence: Investigating depressive symptom specificity in amulti-wave prospective study. Journal of Abnormal Child Psychology, 36(7), 999–1014. https://doi.org/10.1007/s10802-008-9228-6
Hittner, E. F., Rim, K. L., & Haase, C. M. (2019). Socioeconomic status as a moderator of the link between reappraisal and anxiety: Laboratory-based and longitudinal evidence. Emotion, 19(8), 1478. https://doi.org/10.1037/emo0000539
Hoorelbeke, K., Koster, E. H., Vanderhasselt, M. A., Callewaert, S., & Demeyer, I. (2015). The influence of cognitive control training on stress reactivity and rumination in response to a lab stressor and naturalistic stress. Behaviour Research and Therapy, 69, 1–10. https://doi.org/10.1016/j.brat.2015.03.010
Judge, T. A., Erez, A., Bono, J. E., & Thoresen, C. J. (2002). Are measures of self-esteem, neuroticism, locus of control, and generalized self-efficacy indicators of a common core construct? Journal of Personality and Social Psychology, 83(3), 693. https://doi.org/10.1037/0022-3514.83.3.693
Kogler L., Seidel E. M., Metzler H., Thaler H., Boubela R. N., Pruessner J. C., ... & Derntl B. (2017). Impact of self-esteem and sex on stress reactions. Scientific reports, 7(1), 1-9. https://doi.org/10.1038/s41598-017-17485-w
Koster, E. H., De Lissnyder, E., Derakshan, N., & De Raedt, R. (2011). Understanding depressive rumination from a cognitive science perspective: The impaired disengagement hypothesis. Clinical Psychology Review, 31(1), 138–145. https://doi.org/10.1016/j.cpr.2010.08.005
LeMoult, J., & Gotlib, I. (2019). Depression: A cognitive perspective. Clinical Psychology Review, 69, 51–66. https://doi.org/10.1016/j.cpr.2018.06.008
Monroe, S. M., & Harkness, K. L. (2005). Life stress, the" kindling" hypothesis, and the recurrence of depression: Considerations from a life stress perspective. Psychological Review, 112(2), 417. https://doi.org/10.1037/0033-295X.112.2.417
Nasso, S., Vanderhasselt, M. A., Demeyer, I., & De Raedt, R. (2019). Autonomic regulation in response to stress: The influence of anticipatory emotion regulation strategies and trait rumination. Emotion, 19(3), 443. https://doi.org/10.1037/emo0000448
Nasso, S., Vanderhasselt, M. A., & De Raedt, R. (2020). Testing the neurocognitive framework for regulation expectation: The relationship between actual/ideal self-esteem and proactive/reactive autonomic stress regulation. Journal of Behavior Therapy and Experimental Psychiatry, 69, 101598. https://doi.org/10.1016/j.jbtep.2020.101598
Nolen-Hoeksema, S. (1991). Responses to depression and their effects on the duration of depressive episodes. Journal of Abnormal Psychology, 100(4), 569–582.
Nolen-Hoeksema, S., & Morrow, J. (1991). A prospective study of depression and posttraumatic stress symptoms after a natural disaster: The 1989 Loma Prieta earthquake. Journal of Personality and Social Psychology, 61(1), 115–121. https://doi.org/10.1037/0022-3514.61.1.115
Nolen-Hoeksema, S. (2004). The response styles theory. In C. Papageorgiou & A. Wells (Eds.), Depressive rumination: Nature, theory, and treatment (pp. 107–124). Wiley.
Pulopulos, M. M., Baeken, C., & De Raedt, R. (2020a). Cortisol response to stress: The role of expectancy and anticipatory stress regulation. Hormones and Behavior, 117, 104587. https://doi.org/10.1016/j.yhbeh.2019.104587
Pulopulos M. M., Schmausser M., De Smet S., Vanderhasselt M. A., Baliyan S., Venero C., ... & De Raedt R. (2020c). The effect of HF-rTMS over the left DLPFC on stress regulation as measured by cortisol and heart rate variability. Hormones and Behavior, 124, 104803. https://doi.org/10.1016/j.yhbeh.2020.104803
Pulopulos M., Allaert J., Vanderhasselt M. A., Sanchez-Lopez A., De Witte S., Baeken C., & De Raedt R. (2020b). Effects of HF-rTMS over the left and right DLPFC on proactive and reactive cognitive control. Social Cognitive and Affective Neuroscience, nsaa082. https://doi.org/10.1093/scan/nsaa082
Pulopulos, M. M., Vanderhasselt, M. A., & De Raedt, R. (2018a). Association between changes in heart rate variability during the anticipation of a stressful situation and the stress-induced cortisol response. Psychoneuroendocrinology, 94, 63–71. https://doi.org/10.1016/j.psyneuen.2018.05.004
Pulopulos, M. M., Hidalgo, V., Puig-Pérez, S., & Salvador, A. (2018b). Psychophysiological response to social stressors: Relevance of sex and age. Psicothema, 30(2), 171–176. https://doi.org/10.7334/psicothema2017.200
Raes, F., Hermans, D., & Eelen, P. (2003). De Nederlandstalige versie van de ruminative response scale en de rumination on sadness scale (the Dutch version of the rumination response scale and the rumination on sadness scale). Gedragstherapie, 36, 97–104.
Rapee, R. M., Craske, M. G., Brown, T. A., & Barlow, D. H. (1996). Measurement of perceived control over anxiety-related events. Behavior Therapy, 27(2), 279–293. https://doi.org/10.1016/S0005-7894(96)80018-9
Rosenberg, M. (1965). Society and the Adolescent Self-Image. Princeton University Press.
Schmitz, C. (2012). LimeSurvey: An open-source survey tool. LimeSurvey Project Hamburg, Germany. URL http://www.limesurvey.org.
Schulkin, J. (2011). Social allostasis: Anticipatory regulation of the internal milieu. Frontiers in Evolutionary Neuroscience, 2, 111. https://doi.org/10.3389/fnevo.2010.00111
Schwarzer R., & Jerusalem M. (1995). Optimistic self-beliefs as a resource factor in coping with stress. In: Extreme Stress and Communities: Impact and Intervention. Springer Netherlands, Dordrecht, pp. 159–177. https://doi.org/10.1007/978-94-015-8486-9_7.
Smith, J. M., & Alloy, L. B. (2009). A roadmap to rumination: A review of the definition, assessment, and conceptualization of this multifaceted construct. Clinical Psychology Review, 29(2), 116–128. https://doi.org/10.1016/j.cpr.2008.10.003
Schulte-van Maaren, Y. W., Carlier, I. V., Zitman, F. G., van Hemert, A. M., de Waal, M. W., van Noorden, M. S., & Giltay, E. J. (2012). Reference values for generic instruments used in routine outcome monitoring: The Leiden routine outcome monitoring study. BMC Psychiatry, 12, 203. https://doi.org/10.1186/1471-244X-12-203
Tafet, G. E., & Nemeroff, C. B. (2016). The links between stress and depression: Psychoneuroendocrinological, genetic, and environmental interactions. The Journal of Neuropsychiatry and Clinical Neurosciences, 28(2), 77–88. https://doi.org/10.1176/appi.neuropsych.15030053
Teeuw, B., Schwarzer, R., Jerusalem, M. (1994). Dutch Adaptation of the General Self-efficacy Scale. Berlin. Retrieved August 12, 2018, from. http://userpage.fu-berlin.de/~health/dutch.htm.
Thayer, J. F., Hansen, A. L., Saus-Rose, E., & Johnsen, B. H. (2009). Heart rate variability, prefrontal neural function, and cognitive performance: The neurovisceral integration perspective on self-regulation, adaptation, and health. Annals of Behavioral Medicine, 37(2), 141–153. https://doi.org/10.1007/s12160-009-9101-z
Vanderhasselt, M. A., Remue, J., Ng, K. K., Mueller, S. C., & De Raedt, R. (2015). The regulation of positive and negative social feedback: A psychophysiological study. Cognitive Affective and Behavioral Neuroscience, 15(3), 553–563. https://doi.org/10.3758/s13415-015-0345-8
Verwoerd J., Cieraad R. & de Jong P.J. (2007) Nederlandse vertaling van de Attentional control scale (ACS). Original author: Derryberry, D., Reed, M.A. (2002).
Wardenaar, K. J., Giltay, E. J., van Veen, T., Zitman, F. G., & Penninx, B. W. (2012). Symptom dimensions as predictors of the two-year course of depressive and anxiety disorders. Journal of Affective Disorders, 136(3), 1198–1203. https://doi.org/10.1016/j.jad.2011.11.037
Witten, D. M., Friedman, J. H., & Simon, N. (2011). New insights and faster computations for the graphical lasso. Journal of Computational and Graphical Statistics, 20(4), 892–900. https://doi.org/10.1198/jcgs.2011.11051a
Zhao T., Wang Z., & Liu H. (2015). Nonconvex low rank matrix factorization via inexact first order oracle. Advances in Neural Information Processing Systems.
Funding
This study was supported by Grant BOF16/GOA/017 for a Concerted Research Action of Ghent University awarded to Rudi De Raedt. Matias M. Pulopulos and Kristof Hoorelbeke were supported by the Research Foundation Flanders (MMP: FWO18/PDO/174; KH: FWO18/PDO/119).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Additional declarations for articles in life science journals that report the results of studies involving humans and/or animals
Not applicable.
Ethics approval
The study was approved by the Ethical Committee of the Faculty of Psychology at Ghent University.
Consent to participate (include appropriate statements)
All participants provided informed consent prior to completing the survey.
Consent for publication (include appropriate statements)
Not applicable.
Conflicts of interest/Competing interests
None.
Additional information
Publisher's note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
The original vision of this article has been revised. Table 1 entries has been correctly aligned.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Pulopulos, M.M., Hoorelbeke, K., Vandenbroucke, S. et al. The interplay between self-esteem, expectancy, cognitive control, rumination, and the experience of stress: A network analysis. Curr Psychol 42, 15403–15411 (2023). https://doi.org/10.1007/s12144-022-02840-6
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12144-022-02840-6