Hostname: page-component-8448b6f56d-mp689 Total loading time: 0 Render date: 2024-04-24T22:51:07.771Z Has data issue: false hasContentIssue false
  • English
  • Français

Childhood anxious/withdrawn behaviour and later anxiety disorder: a network outcome analysis of a population cohort

Published online by Cambridge University Press:  24 August 2021

Nathan J. Monk Open the ORCID record for Nathan J. Monk [Opens in a new window] ,
Geraldine F. H. McLeod Open the ORCID record for Geraldine F. H. McLeod [Opens in a new window] ,
Roger T. Mulder Open the ORCID record for Roger T. Mulder [Opens in a new window] ,
Janet K. Spittlehouse Open the ORCID record for Janet K. Spittlehouse [Opens in a new window]  and
Joseph M. Boden Open the ORCID record for Joseph M. Boden [Opens in a new window]
Nathan J. Monk*
Affiliation:
Christchurch Health and Development Study, Department of Psychological Medicine, University of Otago, Canterbury, New Zealand
Geraldine F. H. McLeod
Affiliation:
Christchurch Health and Development Study, Department of Psychological Medicine, University of Otago, Canterbury, New Zealand
Roger T. Mulder
Affiliation:
Christchurch Health and Development Study, Department of Psychological Medicine, University of Otago, Canterbury, New Zealand
Janet K. Spittlehouse
Affiliation:
Christchurch Health and Development Study, Department of Psychological Medicine, University of Otago, Canterbury, New Zealand
Joseph M. Boden
Affiliation:
Christchurch Health and Development Study, Department of Psychological Medicine, University of Otago, Canterbury, New Zealand
*
Author for correspondence: Nathan J. Monk, E-mail: nathan.monk@postgrad.otago.ac.nz
Get access Rights & Permissions [Opens in a new window]

Abstract

Background

Several previous studies have identified a continuity between childhood anxiety/withdrawal and anxiety disorder (AD) in later life. However, not all children with anxiety/withdrawal problems will experience an AD in later life. Previous studies have shown that the severity of childhood anxiety/withdrawal accounts for some of the variability in AD outcomes. However, no studies to date have investigated how variation in features of anxiety/withdrawal may relate to continuity prognoses. The present research addresses this gap.

Methods

Data were gathered as part of the Christchurch Health and Development Study, a 40-year population birth cohort of 1265 children born in Christchurch, New Zealand. Fifteen childhood anxiety/withdrawal items were measured at 7–9 years and AD outcomes were measured at various interviews from 15 to 40 years. Six network models were estimated. Two models estimated the network structure of childhood anxiety/withdrawal items independently for males and females. Four models estimated childhood anxiety/withdrawal items predicting adolescent AD (14–21 years) and adult AD (21–40 years) in both males and females.

Results

Approximately 40% of participants met the diagnostic criteria for an AD during both the adolescent (14–21 years) and adult (21–40 years) outcome periods. Outcome networks showed that items measuring social and emotional anxious/withdrawn behaviours most frequently predicted AD outcomes. Items measuring situation-based fears and authority figure-specific anxious/withdrawn behaviour did not consistently predict AD outcomes. This applied across both the male and female subsamples.

Conclusions

Social and emotional anxious/withdrawn behaviours in middle childhood appear to carry increased risk for AD outcomes in both adolescence and adulthood.

Keywords

Childhood anxiety/withdrawalanxiety disorderlongitudinalpopulation cohortnetwork analysisnetwork outcome analysis
Type
Original Article
Information
Psychological Medicine , Volume 53 , Issue 4 , March 2023 , pp. 1343 - 1354
Check for updates
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

American Psychiatric Association (1987). Diagnostic and statistical manual of mental disorders (DSM-III-R). Washington, DC: American Psychiatric Association.Google Scholar
World Health Organization. (1993). Composite international diagnostic interview (CIDI), version 1.1: World Health Organization.Google Scholar
American Psychiatric Association (1994). Diagnostic and statistical manual of mental disorders (DSM-IV). Washington, DC: American Psychiatric Association.Google Scholar
R Core Team. (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing.Google Scholar
Achenbach, T. M., Conners, C. K., Quay, H. C., Verhulst, F. C., & Howell, C. T. (1989). Replication of empirically derived syndromes as a basis for taxonomy of child/adolescent psychopathology. Journal of Abnormal Child Psychology, 17(3), 299–323.CrossRefGoogle ScholarPubMed
Achenbach, T. M., & Edelbrock, C. S. (1978). The classification of child psychopathology: A review and analysis of empirical efforts. Psychological Bulletin, 85(6), 1275–1301.CrossRefGoogle ScholarPubMed
Alonso, J., Angermeyer, M. C., Bernert, S., Bruffaerts, R., Brugha, T. S., Bryson, H., … Vollebergh, W. A. M. (2004). Disability and quality of life impact of mental disorders in Europe: Results from the European Study of the Epidemiology of Mental Disorders (ESEMeD) project. Acta Psychiatrica Scandinavica, 109(s420), 38–46. doi:10.1111/j.1600-0047.2004.00329.xCrossRefGoogle Scholar
Anderson, J. C., Williams, S., McGee, R., & Silva, P. A. (1987). DSM-III disorders in preadolescent children: Prevalence in a large sample from the general population. Archives of General Psychiatry, 44(1), 69–76.CrossRefGoogle Scholar
Beesdo-Baum, K., & Knappe, S. (2012). Developmental epidemiology of anxiety disorders. Child and Adolescent Psychiatric Clinics of North America, 21(3), 457–478. doi:https://doi.org/10.1016/j.chc.2012.05.001CrossRefGoogle ScholarPubMed
Bender, P. K., Reinholdt-Dunne, M. L., Esbjørn, B. H., & Pons, F. (2012). Emotion dysregulation and anxiety in children and adolescents: Gender differences. Personality and Individual Differences, 53(3), 284–288. doi:10.1016/j.paid.2012.03.027CrossRefGoogle Scholar
Blanken, T. F., Borsboom, D., Penninx, B. W., & Van Someren, E. J. (2019). Network outcome analysis identifies difficulty initiating sleep as a primary target for prevention of depression: A 6-year prospective study. Sleep, 43(5), 1–6. doi:10.1093/sleep/zsz288.Google Scholar
Borsboom, D. (2017). A network theory of mental disorders. World Psychiatry, 16(1), 5–13. doi:10.1002/wps.20375CrossRefGoogle ScholarPubMed
Borsboom, D., Fried, E. I., Epskamp, S., Waldorp, L. J., van Borkulo, C. D., van der Maas, H. L., & Cramer, A. O. (2017). False alarm? A comprehensive reanalysis of ‘Evidence that psychopathology symptom networks have limited replicability’ by Forbes, Wright, Markon, and Krueger (2017). Journal of Abnormal Psychology, 126(7), 989–999.CrossRefGoogle ScholarPubMed
Briganti, G., Kempenaers, C., Braun, S., Fried, E. I., & Linkowski, P. (2018). Network analysis of empathy items from the interpersonal reactivity index in 1973 young adults. Psychiatry Research, 265, 87–92. doi:10.1016/j.psychres.2018.03.082CrossRefGoogle ScholarPubMed
Caspi, A., Moffitt, T. E., Newman, D. L., & Silva, P. A. (1996). Behavioral observations at age 3 years predict adult psychiatric disorders: Longitudinal evidence from a birth cohort. Archives of General Psychiatry, 53(11), 1033–1039.CrossRefGoogle ScholarPubMed
Chmielewski, M., & Watson, D. (2008). The heterogeneous structure of schizotypal personality disorder: Item-level factors of the schizotypal personality questionnaire and their associations with obsessive-compulsive disorder symptoms, dissociative tendencies, and normal personality. Journal of Abnormal Psychology, 117(2), 364–376.CrossRefGoogle ScholarPubMed
Clark, L. A., Watson, D., & Reynolds, S. (1995). Diagnosis and classification of psychopathology: Challenges to the current system and future directions. Annual Review of Psychology, 46(1), 121–153.CrossRefGoogle Scholar
Conners, C. K. (1969). A teacher rating scale for use in drug studies with children. American Journal of Psychiatry, 126(6), 884–888.CrossRefGoogle ScholarPubMed
Conners, C. K. (1970). Symptom patterns in hyperkinetic, neurotic, and normal children. Child Development, 41(3), 667–682. doi:https://doi.org/10.2307/1127215CrossRefGoogle Scholar
Costello, A., Edelbrock, C., Kalas, R., Kessler, M., & Klaric, S. (1982). Diagnostic interview schedule for children (DISC). Bethesda, MD. National Institute of Mental Health.Google Scholar
Côté, S. M., Boivin, M., Liu, X., Nagin, D. S., Zoccolillo, M., & Tremblay, R. E. (2009). Depression and anxiety symptoms: Onset, developmental course and risk factors during early childhood. Journal of Child Psychology and Psychiatry, 50(10), 1201–1208. doi:10.1111/j.1469-7610.2009.02099.xCrossRefGoogle ScholarPubMed
Csardi, G., & Nepusz, T. (2006). The Igraph software package for complex network research. InterJournal, Complex Systems, 1695(5), 1–9.Google Scholar
De Beurs, D., Fried, E. I., Wetherall, K., Cleare, S., O’ Connor, D. B., Ferguson, E., … O’ Connor, R. C. (2019). Exploring the psychology of suicidal ideation: A theory driven network analysis. Behaviour Research and Therapy, 120, 103419. doi:10.1016/j.brat.2019.103419CrossRefGoogle ScholarPubMed
Epskamp, S., Borsboom, D., & Fried, E. I. (2018). Estimating psychological networks and their accuracy: A tutorial paper. Behavior Research Methods, 50(1), 195–212. doi:10.3758/s13428-017-0862-1CrossRefGoogle ScholarPubMed
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.CrossRefGoogle Scholar
Epskamp, S., & Fried, E. I. (2018). A tutorial on regularized partial correlation networks. Psychological Methods, 23(4), 617–634.CrossRefGoogle ScholarPubMed
Fergusson, D. M., & Horwood, L. J. (1993). The structure, stability and correlations of the trait components of conduct disorder, attention deficit and anxiety/withdrawal reports. Journal of Child Psychology and Psychiatry, 34(5), 749–766.CrossRefGoogle ScholarPubMed
Fergusson, D. M., & Lynskey, M. T. (1998). Conduct problems in childhood and psychosocial outcomes in young adulthood: A prospective study. Journal of Emotional and Behavioral Disorders, 6(1), 2–18.CrossRefGoogle Scholar
Forbes, M. K., Wright, A. G. C., Markon, K. E., & Krueger, R. F. (2017a). Evidence that psychopathology symptom networks have limited replicability. Journal of Abnormal Psychology, 126(7), 969–988. doi:https://dx.doi.org/10.1037%2Fabn0000276CrossRefGoogle ScholarPubMed
Forbes, M. K., Wright, A. G. C., Markon, K. E., & Krueger, R. F. (2017b). Further evidence that psychopathology networks have limited replicability and utility: Response to Borsboom et al. (2017) and Steinley et al. (2017). Journal of Abnormal Psychology, 126(7), 1011–1016. doi: 10.1037/abn0000313CrossRefGoogle ScholarPubMed
Forslund, T., Brocki, K. C., Bohlin, G., Granqvist, P., & Eninger, L. (2016). The heterogeneity of attention-deficit/hyperactivity disorder symptoms and conduct problems: Cognitive inhibition, emotion regulation, emotionality, and disorganized attachment. British Journal of Developmental Psychology, 34(3), 371–387.CrossRefGoogle ScholarPubMed
Foygel, R., & Drton, M. (2010). Extended Bayesian information criteria for Gaussian graphical models. Paper presented at the advances in neural information processing systems.Google Scholar
Fried, E. I. (2020). Lack of theory building and testing impedes progress in the factor and network literature. Psychological Inquiry, 31(4), 271–288. doi:10.1080/1047840x.2020.1853461CrossRefGoogle Scholar
Fried, E. I., & Cramer, A. O. J. (2017). Moving forward: Challenges and directions for psychopathological network theory and methodology. Perspectives on Psychological Science, 12(6), 999–1020. doi:10.1177/1745691617705892CrossRefGoogle ScholarPubMed
Fried, E. I., Epskamp, S., Nesse, R. M., Tuerlinckx, F., & Borsboom, D. (2016). What are ‘good’ depression symptoms? Comparing the centrality of DSM and non-DSM symptoms of depression in a network analysis. Journal of Affective Disorders, 189, 314–320. doi:10.1016/j.jad.2015.09.005CrossRefGoogle Scholar
Fried, E. I., & Robinaugh, D. J. (2020). Systems all the way down: Embracing complexity in mental health research. BMC Medicine, 18(1), Article 205. doi:10.1186/s12916-020-01668-wCrossRefGoogle ScholarPubMed
Fried, E. I., Van Borkulo, C. D., Cramer, A. O. J., Boschloo, L., Schoevers, R. A., & Borsboom, D. (2017). Mental disorders as networks of problems: A review of recent insights. Social Psychiatry and Psychiatric Epidemiology, 52(1), 1–10. doi:10.1007/s00127-016-1319-zCrossRefGoogle ScholarPubMed
Fried, E. I., Van Borkulo, C. D., & Epskamp, S. (2020). On the importance of estimating parameter uncertainty in network psychometrics: A response to Forbes et al. (2019). Multivariate Behavioral Research, 1–6. doi:10.1080/00273171.2020.1746903Google ScholarPubMed
Gazelle, H. (2008). Behavioral profiles of anxious solitary children and heterogeneity in peer relations. Developmental Psychology, 44(6), 1604–1624. doi:10.1037/a0013303CrossRefGoogle ScholarPubMed
Goodwin, R. D., Fergusson, D. M., & Horwood, L. J. (2004). Early anxious/withdrawn behaviours predict later internalising disorders. Journal of Child Psychology and Psychiatry, 45(4), 874–883. doi:10.1111/j.1469-7610.2004.00279.xCrossRefGoogle ScholarPubMed
Haslbeck, J. M. B., & Waldorp, L. J. (2020). mgm: Structure estimation for time-varying mixed graphical models in high-dimensional data. Journal of Statistical Software, 93, 8. doi:10.18637/jss.v093.i08CrossRefGoogle Scholar
Hasler, G., Drevets, W. C., Manji, H. K., & Charney, D. S. (2004). Discovering endophenotypes for major depression. Neuropsychopharmacology, 29(10), 1765–1781. doi:10.1038/sj.npp.1300506CrossRefGoogle ScholarPubMed
Hayward, C., & Sanborn, K. (2002). Puberty and the emergence of gender differences in psychopathology. Journal of Adolescent Health, 30(4, Supplement 1), 49–58. doi:https://doi.org/10.1016/S1054-139X(02)00336-1CrossRefGoogle ScholarPubMed
Hendriks, S. M., Spijker, J., Licht, C. M. M., Hardeveld, F., de Graaf, R., Batelaan, N. M., … Beekman, A. T. F. (2016). Long-term disability in anxiety disorders. BMC Psychiatry, 16, 248. doi:10.1186/s12888-016-0946-yCrossRefGoogle ScholarPubMed
Isvoranu, A.-M., & Epskamp, S. (2021). Gaussian and ordered categorical data in network psychometrics: Which estimation method to choose? Deriving guidelines for applied researchers. PsyArXiv. doi:10.31234/osf.io/mbycnGoogle ScholarPubMed
Jakobsen, I. S., Horwood, L. J., & Fergusson, D. M. (2012). Childhood anxiety/withdrawal, adolescent parent–child attachment and later risk of depression and anxiety disorder. Journal of Child and Family Studies, 21(2), 303–310. doi:10.1007/s10826-011-9476-xCrossRefGoogle Scholar
Jones, P. J., Heeren, A., & McNally, R. J. (2017). Commentary: A network theory of mental disorders. Frontiers in Psychology, 8, Article 1305. doi:10.3389/fpsyg.2017.01305CrossRefGoogle ScholarPubMed
Jones, P. J., Ma, R., & McNally, R. J. (2019). Bridge centrality: A network approach to understanding comorbidity. Multivariate Behavioral Research, 1–15. doi:10.1080/00273171.2019.1614898Google ScholarPubMed
Jones, P. J., Williams, D. R., & McNally, R. J. (2019). Sampling variability is not nonreplication: A Bayesian reanalysis of Forbes, Wright, Markon, & Krueger. Multivariate Behavioral Research, 1–7. doi:10.1080/00273171.2020.1797460Google Scholar
Kendler, K. S. (2017). DSM disorders and their criteria: How should they inter-relate? Psychological Medicine, 47(12), 2054–2060. doi:10.1017/s0033291717000678CrossRefGoogle ScholarPubMed
Lewinsohn, P. M., Gotlib, I. H., Lewinsohn, M., Seeley, J. R., & Allen, N. B. (1998). Gender differences in anxiety disorders and anxiety symptoms in adolescents. Journal of Abnormal Psychology, 107(1), 109–117.CrossRefGoogle ScholarPubMed
Miers, A. C., Weeda, W. D., Blöte, A. W., Cramer, A. O., Borsboom, D., & Westenberg, P. M. (2020). A cross-sectional and longitudinal network analysis approach to understanding connections among social anxiety components in youth. Journal of Abnormal Psychology, 129(1), 82–91.CrossRefGoogle ScholarPubMed
Moffitt, T. E., Caspi, A., Taylor, A., Kokaua, J., Milne, B. J., Polanczyk, G., & Poulton, R. (2010). How common are common mental disorders? Evidence that lifetime prevalence rates are doubled by prospective versus retrospective ascertainment. Psychological Medicine, 40(6), 899–909. doi:10.1017/s0033291709991036CrossRefGoogle ScholarPubMed
Montazeri, F., De Bildt, A., Dekker, V., & Anderson, G. M. (2019). Network analysis of behaviors in the depression and autism realms: Inter-relationships and clinical implications. Journal of Autism and Developmental Disorders, 50, 1580–1595. doi:10.1007/s10803-019-03914-4.CrossRefGoogle Scholar
Pearl, J. (2000). Causality: Models, reasoning, and inference. New York, NY: Cambridge University Press.Google Scholar
Pine, D. S., & Fox, N. A. (2015). Childhood antecedents and risk for adult mental disorders. Annual Review of Psychology, 66(1), 459–485. doi:10.1146/annurev-psych-010814-015038CrossRefGoogle ScholarPubMed
Prior, M., Smart, D., Sanson, A., & Oberklaid, F. (2000). Does shy-inhibited temperament in childhood lead to anxiety problems in adolescence? Journal of the American Academy of Child & Adolescent Psychiatry, 39(4), 461–468. doi:10.1097/00004583-200004000-00015CrossRefGoogle ScholarPubMed
Robinaugh, D. J., Hoekstra, R. H. A., Toner, E. R., & Borsboom, D. (2019). The network approach to psychopathology: A review of the literature 2008–2018 and an agenda for future research. Psychological Medicine, 50(3), 1–14. doi:10.1017/s0033291719003404.Google Scholar
Robinaugh, D. J., Millner, A. J., & McNally, R. J. (2016). Identifying highly influential nodes in the complicated grief network. Journal of Abnormal Psychology, 125(6), 747–757. doi:10.1037/abn0000181CrossRefGoogle ScholarPubMed
Rouquette, A., Pingault, J.-B., Fried, E. I., Orri, M., Falissard, B., Kossakowski, J. J., … Borsboom, D. (2018). Emotional and behavioral symptom network structure in elementary school girls and association with anxiety disorders and depression in adolescence and early adulthood. JAMA Psychiatry, 75(11), 1173–1181. doi:10.1001/jamapsychiatry.2018.2119CrossRefGoogle ScholarPubMed
Roza, S. J., Hofstra, M. B., Van Der Ende, J., & Verhulst, F. C. (2003). Stable prediction of mood and anxiety disorders based on behavioral and emotional problems in childhood: A 14-year follow-up during childhood, adolescence, and young adulthood. American Journal of Psychiatry, 160(12), 2116–2121. doi:10.1176/appi.ajp.160.12.2116CrossRefGoogle ScholarPubMed
Rutter, M., Tizard, J., & Whitmore, K. (1970). Health, education, and behaviour. London, UK: Longmans Green.Google Scholar
Sonuga-Barke, E. J. S., Thompson, M., Stevenson, J., & Viney, D. (1997). Patterns of behaviour problems among pre-school children. Psychological Medicine, 27(4), 909–918. doi:10.1017/s0033291797005291CrossRefGoogle ScholarPubMed
Van Borkulo, C. D. (2015). Network comparison test: permutation-based test of differences in strength of networks. Retrieved from https://github.com/cvborkulo/NetworkComparisonTest.Google Scholar
Van Borkulo, C. D., Borsboom, D., Epskamp, S., Blanken, T. F., Boschloo, L., Schoevers, R. A., & Waldorp, L. J. (2015). A new method for constructing networks from binary data. Scientific Reports, 4, 1. doi:10.1038/srep05918Google Scholar
Vigo, D., Thornicroft, G., & Atun, R. (2016). Estimating the true global burden of mental illness. The Lancet Psychiatry, 3(2), 171–178.CrossRefGoogle ScholarPubMed
Waschbusch, D. A., Porter, S., Carrey, N., Kazmi, S. O., Roach, K. A., & D'Amico, D. A. (2004). Investigation of the heterogeneity of disruptive behaviour in elementary-age children. Canadian Journal of Behavioural Science/Revue canadienne des sciences du comportement, 36(2), 97–112. doi:https://psycnet.apa.org/doi/10.1037/h0087221CrossRefGoogle Scholar
Weems, C. (2008). Developmental trajectories of childhood anxiety: Identifying continuity and change in anxious emotion. Developmental Review, 28(4), 488–502. doi:10.1016/j.dr.2008.01.001CrossRefGoogle Scholar
Westenberg, P. M., Siebelink, B. M., & Treffers, P. D. (2001). Psychosocial developmental theory in relation to anxiety and its disorders. Cambridge, UK: Cambridge University Press.Google Scholar
Whiteford, H. A., Ferrari, A. J., Degenhardt, L., Feigin, V., & Vos, T. (2015). The global burden of mental, neurological and substance use disorders: An analysis from the global burden of disease study 2010. PLoS ONE, 10(2), e0116820. doi:10.1371/journal.pone.0116820CrossRefGoogle ScholarPubMed
Yang, Z., Algesheimer, R., & Tessone, C. J. (2016). A comparative analysis of community detection algorithms on artificial networks. Scientific Reports, 6(1), 30750. doi:10.1038/srep30750CrossRefGoogle ScholarPubMed
Zimmerman, M., Ellison, W., Young, D., Chelminski, I., & Dalrymple, K. (2015). How many different ways do patients meet the diagnostic criteria for major depressive disorder? Comprehensive Psychiatry, 56, 29–34. doi:10.1016/j.comppsych.2014.09.007CrossRefGoogle ScholarPubMed
Supplementary material: File

Monk et al. supplementary material

Monk et al. supplementary material

Download Monk et al. supplementary material(File)
File 280.1 KB