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Emotion network density describes the degree of interdependence among emotion states across time. Higher density is theorized to reflect rigidity in emotion functioning and has been associated with depression in adult samples. This paper extended research on emotion networks to adolescents and examined associations between emotion network density and: 1) emotion regulation and 2) symptoms of depression. Data from a daily diary study (t = 21 days) of adolescents (N = 151; 61.59% female; mean age = 14.60 years) were used to construct emotion network density scores. Emotion regulation was measured using The Difficulties in Emotion Regulation Scale Short Form (DERS-SF). Depression was measured using the Revised Child Anxiety and Depression Scale-Short Version (RCADS-SV). Associations between emotion network density and DERS-SF were examined through Pearson correlations. Multiple regression analyses examined associations between emotion network density and depression. Emotion network density was not associated with the DERS-SF. Follow-up analyses showed that it was positively associated with non-acceptance of emotions (a subscale of the DERS-SF). Emotion network density was positively associated with RCADS-SV depression. Non-acceptance of emotions may encourage the spread of emotion across time and states given that a feature of non-acceptance is to have secondary emotional responses to one’s emotions. Emotion networks that are self-predictive may be a risk factor for adolescent depression.
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Aldao, A., Nolen-Hoeksema, S., & Schweizer, S. (2010). Emotion-regulation strategies across psychopathology: A meta-analytic review. Clinical Psychology Review, 2, 217–237. CrossRef
American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington: American Psychiatric Publishing. CrossRef
Anand, D., Wilt, J., & Revelle, W. (2016). Within-subject covariation between depression-and anxiety-related affect. Cognition and Emotion, 31, 1055–1061. https://doi.org/10.1080/02699931.2016.1184625. CrossRefPubMed
Beedie, C., Terry, P., & Lane, A. (2005). Distinctions between emotion and mood. Cognition & Emotion, 19(6), 847–878. CrossRef
Berenbaum, H., Raghavan, C., Le, H. N., Vernon, L. L., & Gomez, J. J. (2003). A taxonomy of emotional disturbances. Clinical Psychology: Science and Practice, 10, 206–226.
Birmaher, B., Ryan, N. D., Williamson, D. E., Brent, D. A., Kaufman, J., Dahl, R. E., et al. (1996). Childhood and adolescent depression: A review of the past 10 years. Part I. Journal of the American Academy of Child & Adolescent Psychiatry, 35, 1427–1439. CrossRef
Bolger, N., & Laurenceau, J.-P. (2013). Intensive longitudinal methods: An introduction to diary and experience sampling research. New York, NY: Guilford Press.
Campos, J. J., Campos, R. G., & Barrett, K. C. (1989). Emergent themes in the study of emotional development and emotion regulation. Developmental Psychology, 25, 394–402. CrossRef
Casey, B. J., Jones, R. M., & Hare, T. A. (2008). The adolescent brain (Vol. 1124, pp. 111–126). Annals of the New York Academy of Sciences.
Cicchetti, D., Ackerman, B. P., & Izard, C. E. (1995). Emotions and emotion regulation in developmental psychopathology. Development and Psychopathology, 7, 1–10. CrossRef
Csikszentmihalyi, M., & Larson, R. (2014). Validity and reliability of the experience-sampling method. In M. Csikszentmihalyi (Ed.), Flow and the foundations of positive psychology (pp. 35–54). The Netherlands: Springer.
Ebesutani, C., Reise, S. P., Chorpita, B. F., Ale, C., Regan, J., Young, J., Higa-McMillan, C., & Weisz, J. R. (2012). The revised child anxiety and depression scale-short version: Scale reduction via exploratory bifactor modeling of the broad anxiety factor. Psychological Assessment, 24, 833–845. CrossRefPubMed
Epskamp, S., Cramer, A. O. J., Waldorp, L. J., Scmittmann, V. D., & Borsboom, D. (2012). Qgraph: Network visualizations of relationships in psychometric data. Journal of Statistical Software, 48, 1–18. CrossRef
Epskamp, S., Waldorp, L. J., Mõttus, R., & Borsboom, D. (2016). Discovering psychological dynamics: The Gaussian graphical model in cross-sectional and time-series data. arXiv preprint arXiv:1609.04156.
Fosco, G. M., & Lydon-Staley, D. M. (2017). A within-family examination of interparental conflict, cognitive appraisals, and adolescent mood and well-being. Child Development. https://doi.org/10.1111/cdev.12997.
Fricker, R. D., & Schonlau, M. (2002). Advantages and disadvantages of internet research surveys: Evidence from the literature. Field Methods, 14, 347–367. CrossRef
Frijda, N. (1986). The emotions. Cambridge, UK: Cambridge University Press.
Gratz, K. L., & Roemer, L. (2004). Multidimensional assessment of emotion regulation and dysregulation: Development, factor structure, and initial validation of the difficulties in emotion regulation scale. Journal of Psychopathology and Behavioral Assessment, 26, 41–54. CrossRef
Gross, J. J. (2015). The extended process model of emotion regulation: Elaborations, applications. and future directions. Psychological Inquiry, 26, 130–137. CrossRef
Gross, J. J., & Muñoz, R. F. (1995). Emotion regulation and mental health. Clinical Psychology: Science and Practice, 2, 151–164.
Gruber, J., Kogan, A., Quoidbach, J., Mauss, I. B. (2013) Happiness is best kept stable: Positive emotion variability is associated with poorer psychological health. Emotion, 13, (1):1-6
Hale, J. B., & Fitzer, K. R. (2015). Evaluating orbital-ventral medial system regulation of personal attention: A critical need for neuropsychological assessment and intervention. Applied Neuropsychology: Child, 4(2), 106–115. CrossRef
Hale, J.B., Reddy, L.A., & Weissman, A.S. (2018). Recognizing frontal-subcortical circuit dimensions in child and adolescent neuropsychopathology. In J.N. Butcher, & P.C. Kendall (Eds.), APA handbooks in psychology series. APA handbook of psychopathology: Child and adolescent psychopathology (pp. 97-122). Washington, D.C.: American Psychological Association.
Hale, J.B., Reddy, L.A., Wilcox, G., McLaughlin, A., Hain, L., Stern, A., Henzel, J., & Eusebio, E. (2009). Assessment and intervention for children with ADHD and other frontal-striatal circuit disorders. In D.C. Miller (Ed.), Best practices in school neuropsychology: Guidelines for effective practice, assessment, and evidence-based intervention (pp. 224-279). Hoboken, NJ: John Wiley & Sons, Inc.
Hollenstein, T. (2015). This time, it's real: Affective flexibility, time scales, feedback loops, and the regulation of emotion. Emotion Review, 7, 308–315. CrossRef
Hollenstein, T., Lichtwarck-Aschoff, A., & Potoworowski, G. (2013). A model of socioemotional flexibility at three time scales. Emotion Review, 5, 397–405. CrossRef
Kaufman, E. A., Xia, M., Fosco, G., Yaptangco, M., Skidmore, C. R., & Crowell, S. E. (2016). The difficulties in emotion regulation scale short form (DERS-SF): Validation and replication in adolescent and adult samples. Journal of Psychopathology and Behavioral Assessment, 28, 443–455. CrossRef
Kuppens, P. (2015). It’s about time: A special section on affect dynamics. Emotion Review, 7(4), 297–300. CrossRef
Kuppens, P., & Verduyn, P. (2015). Looking at emotion regulation through the window of emotion dynamics. Psychological Inquiry, 26, 72–79. CrossRef
Larson, R., & Csikszentmihalyi, M. (1983). The experience sampling method. In H. T. Reis (Ed.), New directions for methodology of social and behavioral sciences (Vol. 15, pp. 41–56). San Francisco, CA: Jossey-Bass.
Larson, R., & Ham, M. (1993). Stress and “storm and stress” in early adolescence: The relationship of negative events with dysphoric affect. Developmental Psychology, 29, 130–140. CrossRef
Liverant, G. I., Brown, T. A., Barlow, D. H., & Roemer, L. (2008). Emotion regulation in unipolar depression: The effects of acceptance and suppression of subjective emotional experience on the intensity and duration of sadness and negative affect. Behaviour Research and Therapy, 46, 1201–1209. CrossRefPubMed
Lougheed, J. P., & Hollenstein, T. (2012). A limited repertoire of emotion regulation strategies is associated with internalizing problems in adolescence. Social Development, 21(4), 704–721. CrossRef
Lydon, D. M., Galvan, A., & Geier, C. F.(2015). Adolescence and addiction: Vulnerability, opportunity, and the role of brain development. In S. J. Wilson (Ed.), The Wiley-Blackwell handbook of the cognitive neuroscience of addiction (pp. 292–310). Chichester, UK: John Wiley.
Lydon-Staley, D. M., & Bassett, D. S. (2018). The promise and challenges of intensive repeated measures for cognitive neuroscience models of adolescent substance use. Frontiers in Psychology, 9. https://doi.org/10.3389/fpsyg.2018.01576.
Mennin, D., & Farach, F. (2007). Emotion and evolving treatments for adult psychopathology. Clinical Psychology: Science and Practice, 14, 329–352.
Pe, M. L., Kircanski, K., Thompson, R. J., Bringmann, L. F., Tuerlinckx, F., Mestdagh, M., et al. (2015). Emotion-network density in major depressive disorder. Clinical Psychological Science, 3, 292–300. CrossRef
Pinheiro, J., Bates, D., DebRoy, S., Sarkar, D., & Core Team, R. (2015). Nlme: Linear and nonlinear mixed effects models. R Package version, 3, 1–120 http://CRAN.R-project.org/package=nlme.
Shiffman, S., Stone, A. A., Hufford, M. R. (2008) Ecological Momentary Assessment. Annual Review of Clinical Psychology, 4, (1):1-32
Schuurman, N. K., Ferrer, E., de Boer-Sonnenschein, M., & Hamaker, E. L. (2016). How to compare cross-lagged associations in a multilevel autoregressive model. Psychological Methods, 21, 206–221.
Shulman, E. P., Smith, A. R., Silva, K., Icenogle, G., Duell, N., Chein, J., & Steinberg, L. (2016). The dual systems model: Review, reappraisal, and reaffirmation. Developmental Cognitive Neuroscience, 17, 103–117.
Snijders, T. A. B., & Bosker, R. J. (2012). Multilevel analysis: An introduction to basic and advanced multilevel modeling (2nd ed.). London, UK: Sage Publishers.
Terry, P. C., Lane, A. M., & Fogarty, G. J. (2003). Construct validity of the profile of mood states—Adolescents for use with adults. Psychology of Sport and Exercise, 4, 125–139.
Thompson, R.A. (1990). Emotion and Self-Regulation. In R.A. Thompson (Ed.), Socioemotional development. Nebraska symposium on motivation (vol. 36, pp. 367–467). Lincoln, NE: University of Nebraska Press.
Thompson, R.A. (1994). Emotion regulation: A theme in search of definition. In N.A. Fox (Ed.), The development of emotion regulation and dysregulation: Biological and behavioral aspects. Monographs of the Society for Research in child development, 59, 25–52 (serial no. 240).
Trapletti, A., & Hornik, K. (2018). tseries: Time series analysis and computational finance. R package version 0.10–45.
Wigman, J. T. W., Van Os, J., Borsboom, D., Wardenaar, K. J., Epskamp, S., Klippel, A., et al. (2015). Exploring the underlying structure of mental disorders: Cross-diagnostic differences and similarities from a network perspective using both a top-down and a bottom-up approach. Psychological Medicine, 45, 2375–2387. CrossRefPubMed
Zelazo, P. D., & Cunningham, W. A. (2007). Executive function: Mechanisms underlying emotion regulation. In J. J. Gross (Ed.), Handbook of emotion regulation (pp. 135–158). New York, NY: Guilford Press.
Zimmermann, P., & Iwanski, A. (2014). Emotion regulation from early adolescence to emerging adulthood and middle adulthood age differences, gender differences, and emotion-specific developmental variations. International Journal of Behavioral Development, 38, 182–194. CrossRef
- Adolescent Emotion Network Dynamics in Daily Life and Implications for Depression
D. M. Lydon-Staley
H. W. Mak
G. M. Fosco
- Springer US
Journal of Abnormal Child Psychology
An official publication of the International Society for Research in Child and Adolescent Psychopathology
Print ISSN: 0091-0627
Elektronisch ISSN: 1573-2835