Abstract
Anxiety and depressive symptoms frequently co-occur in adolescence and confer greater distress compared to experiencing either symptom alone. A causal model (anxiety symptoms predicting depressive symptoms), a correlated liabilities model (vulnerabilities interacting with stressors to predict both symptoms), and a diathesis-anxiety model (vulnerabilities interacting with anxiety symptoms to predict depressive symptoms) have all been proposed as explanations for the relation between depression and anxiety. To date, however, research has mostly examined these models among North American/Western European adolescents. In response, the present study sought to identify the best explanatory model concerning the relationship between anxiety and depressive symptoms among Chinese adolescents. 494 10th grade students were assessed for their perceived levels of family cohesion and conflict, stressors, and depressive and anxiety symptoms. Every 3 months for 18 months, youth reported their symptoms and stressors. Symptoms and stressors were person-mean and grand-mean centered to compare nomothetic and idiographic conceptualizations of vulnerability. Overall, evidence suggested a reciprocal, versus causal, relation between anxiety and depressive symptoms. Further, while cohesion and conflict independently predicted anxiety and depressive symptoms, their interactions with stressors were not supported. Ultimately, strong support was found for a diathesis-anxiety model using an idiographic conceptualization of anxiety, such that low perceived family cohesion interacted with within-subject fluctuations of anxiety to predict prospective depressive symptoms. This study provides cross-cultural support for a diathesis-anxiety model and shows the importance of distinguishing between positive and negative family functioning when examining vulnerability in Chinese adolescents. Research and clinical implications of these findings are discussed.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Notes
A confirmatory factor analysis was conducted to investigate whether the four different forms of anxiety could be adequately distinguished within the current sample. We found little support for a four-factor model (χ2/df = 2.664; p < .001; CFI = .760; RMSEA = .058; SRMR = .097). Thus, consistent with past research (e.g., Cohen et al. 2014), the total score of the MASC was used to test the hypotheses of this study.
Although the simultaneous model did find initial support for cohesion interacting with both idiographic, β = -0.001; SE = 0.000; t(1585) = -2.628; p < 0.01; reffect size = 0.07, and nomothetic, β = 0.001; SE = 0.000; t(1303) = 3.966; p < 0.01; reffect size = 0.11, anxiety symptoms (T-1) and time, these finding were not replicated when tested individually, ps > 0.05. Thus, these results were conceptualized as suppressor effects and non-significant.
References
Abela, J. R., Aydin, C., & Auerbach, R. P. (2006). Operationalizing the “vulnerability” and “stress” components of the hopelessness theory of depression: A multi-wave longitudinal study. Behaviour Research and Therapy, 44(11), 1565–1583. https://doi.org/10.1016/j.brat.2005.11.010
Abela, J. R., Fishman, M. B., Cohen, J. R., & Young, J. F. (2012). Personality predispositions to depression in children of affectively-ill parents: The buffering role of self-esteem. Journal of Clinical Child & Adolescent Psychology, 41(4), 391–401. https://doi.org/10.1080/15374416.2012.654463
Abela, J. R., & Hankin, B. L. (2011). Rumination as a vulnerability factor to depression during the transition from early to middle adolescence: a multiwave longitudinal study. Journal of Abnormal Psychology, 120(2), 259. https://doi.org/10.1037/a0022796
Abela, J. R., McGirr, A., & Skitch, S. A. (2007). Depressogenic inferential styles, negative events, and depressive symptoms in youth: An attempt to reconcile past inconsistent findings. Behaviour Research and Therapy, 45(10), 2397–2406. https://doi.org/10.1016/j.brat.2007.03.012
Abela, J. R., Stolow, D., Mineka, S., Yao, S., Zhu, X. Z., & Hankin, B. L. (2011). Cognitive vulnerability to depressive symptoms in adolescents in urban and rural Hunan, China: A multiwave longitudinal study. Journal of Abnormal Psychology, 120(4), 765–778. https://doi.org/10.1037/a0025295
Avenevoli, S., Stolar, M., Li, J., Dierker, L., & Merikangas, K. R. (2001). Comorbidity of depression in children and adolescents: Models and evidence from a prospective high-risk family study. Biological Psychiatry, 49(12), 1071–1081. https://doi.org/10.1016/s0006-3223(01)01142-8
Barlow, D. H., & Nock, M. K. (2009). Why can’t we be more idiographic in our research? Perspectives on Psychological Science, 4(1), 19–21. https://doi.org/10.1111/j.1745-6924.2009.01088.x
Beauchaine, T. P., & Thayer, J. F. (2015). Heart rate variability as a transdiagnostic biomarker of psychopathology. International Journal of Psychophysiology, 98(2), 338–350. https://doi.org/10.1016/j.ijpsycho.2015.08.004
Boyd-Franklin, N. (2003). Black families in therapy: Understanding the African American experience (2nd ed). New York. NY: Guilford Publications. https://doi.org/10.1177/0095798405278637.
Chen, X., Wang, L., & Cao, R. (2011). Shyness-sensitivity and unsociability in rural Chinese children: Relations with social, school, and psychological adjustment. Child Development, 82(5), 1531–1543. https://doi.org/10.1111/j.1467-8624.2011.01616.x
Cohen, J. R., Hankin, B. L., Gibb, B. E., Hammen, C., Hazel, N. A., Ma, D., et al. (2013). Negative attachment cognitions and emotional distress in mainland Chinese adolescents: A prospective multiwave test of vulnerability-stress and stress generation models. Journal of Clinical Child & Adolescent Psychology, 42(4), 531–544. https://doi.org/10.1080/15374416.2012.749787
Cohen, J. R., Sheshko, D. M., Ames, A. M., Young, J. F., Hansford, A. P., Zhu, X., et al. (2015). Self-Perceived Competence in Mainland China: A Multiwave Longitudinal Examination of Internalizing Symptoms in Chinese Adolescents. Journal of Research on Adolescence, 25(3), 564–579. https://doi.org/10.1111/jora.12146
Cohen, J. R., Spiro, C. N., Young, J. F., Gibb, B. E., Hankin, B. L., & Abela, J. R. (2015). Interpersonal risk profiles for youth depression: A person-centered, multi-wave, longitudinal study. Journal of Abnormal Child Psychology, 43(8), 1415–1426. https://doi.org/10.1007/s10802-015-0023
Cohen, J. R., Young, J. F., Gibb, B. E., Hankin, B. L., & Abela, J. R. (2014). Why are anxiety and depressive symptoms comorbid in youth? A multi-wave, longitudinal examination of competing etiological models. Journal of Affective Disorders, 161, 21–29. https://doi.org/10.1016/j.jad.2014.02.042
Crocetti, E., Hale, W. W., Dimitrova, R., Abubakar, A., Gao, C. H., & Pesigan, I. J. A. (2015). Generalized anxiety symptoms and identity processes in cross-cultural samples of adolescents from the general population. In Child & Youth Care Forum (Vol. 44, No. 2, pp. 159–174). Springer US. https://doi.org/10.1007/s10566-014-9275-9.
Cummings, C. M., Caporino, N. E., & Kendall, P. C. (2014). Comorbidity of anxiety and depression in children and adolescents: 20 years after. Psychological Bulletin, 140(3), 816. https://doi.org/10.1037/a0034733
De Los Reyes, A., Augenstein, T. M., Wang, M., Thomas, S. A., Drabick, D. A., Burgers, D. E., & Rabinowitz, J. (2015). The validity of the multi-informant approach to assessing child and adolescent mental health. Psychological Bulletin, 141(4), 858. https://doi.org/10.1037/a0038498
Delvecchio, E., Mabilia, D., Di Riso, D., Miconi, D., & Li, J. B. (2015). A comparison of anxiety symptoms in community-based Chinese and Italian adolescents. Journal of Child and Family Studies, 24(8), 2418–2431. https://doi.org/10.1007/s10826-014-0045-y
Epkins, C. C., & Heckler, D. R. (2011). Integrating etiological models of social anxiety and depression in youth: Evidence for a cumulative interpersonal risk model. Clinical Child and Family Psychology Review, 14(4), 329–376. https://doi.org/10.1007/s10567-011-0101-8
Fisher, A. J. (2015). Toward a dynamic model of psychological assessment: Implications for personalized care. Journal of Consulting and Clinical Psychology, 83(4), 825–836. https://doi.org/10.1037/ccp0000026
Flannery-Schroeder, E. C. (2006). Reducing anxiety to prevent depression. American Journal of Preventive Medicine, 31(6), 136–142. https://doi.org/10.1016/j.amepre.2006.07.006
Franić, S., Middeldorp, C. M., Dolan, C. V., Ligthart, L., & Boomsma, D. I. (2010). Childhood and adolescent anxiety and depression: beyond heritability. Journal of the American Academy of Child & Adolescent Psychiatry, 49(8), 820–829. https://doi.org/10.1016/j.jaac.2010.05.013
Greenberger, E., Chen, C., Tally, S. R., & Dong, Q. (2000). Family, peer, and individual correlates of depressive symptomatology among US and Chinese adolescents. Journal of Consulting and Clinical Psychology, 68(2), 209–219. https://doi.org/10.1037/0022-006x.68.2.209
Gibb, B. E., & Coles, M. E. (2005). Cognitive vulnerability-stress models of psychopathology. Development of psychopathology: A vulnerability-stress perspective. https://doi.org/10.4135/9781452231655.n5
Hammen, C. L. (2015). Stress and depression: old questions, new approaches. Current Opinion in Psychology, 4, 80–85. https://doi.org/10.1016/j.copsyc.2014.12.024
Hankin, B. L. (2008). Cognitive vulnerability–stress model of depression during adolescence: Investigating depressive symptom specificity in a multi-wave prospective study. Journal of Abnormal Child Psychology, 36(7), 999–1014. https://doi.org/10.1007/s10802-008-9228-6
Hankin, B. L., & Abramson, L. Y. (2002). Measuring cognitive vulnerability to depression in adolescence: Reliability, validity, and gender differences. Journal of Clinical Child and Adolescent Psychology, 31(4), 491–504. https://doi.org/10.1207/s15374424jccp3104_8
Hedeker, D., & Gibbons, R. D. (2006). Longitudinal data analysis (Vol. 451). John Wiley & Sons, Inc., Hoboken, NJ. https://doi.org/10.1002/0470036486.
Herman, K. C., Ostrander, R., & Tucker, C. M. (2007). Do family environments and negative cognitions of adolescents with depressive symptoms vary by ethnic group? Journal of Family Psychology, 21(2), 325–330. https://doi.org/10.1037/0893-3200.21.2.325
Ho, S. M., Dai, D. W. T., Mak, C., & Liu, K. W. K. (2018). Cognitive factors associated with depression and anxiety in adolescents: A two-year longitudinal study. International Journal of Clinical and Health Psychology, 18(3), 227–234. https://doi.org/10.1016/j.ijchp.2018.04.001
Ho, L. Y., & Lau, A. S. (2011). Do self-report measures of social anxiety reflect cultural bias or real difficulties for Asian American college students? Cultural Diversity and Ethnic Minority Psychology, 17(1), 52. https://doi.org/10.1037/a0022533
Ingram, R. E., & Siegle, G. J. (2002). Contemporary methodological issues in the study of depression: Not your father's Oldsmobile. In I. H. Gotlib & C. L. Hammen (Eds.), Handbook of depression (p. 86–114). The Guilford Press.
Jacobson, N. C., & Newman, M. G. (2017). Anxiety and depression as bidirectional risk factors for one another: A meta-analysis of longitudinal studies. Psychological Bulletin, 143(11), 1155–1200. https://doi.org/10.1037/bul0000111
Kessler, R. C., Avenevoli, S., & Merikangas, K. R. (2001). Mood disorders in children and adolescents: an epidemiologic perspective. Biological Psychiatry, 49(12), 1002–1014. https://doi.org/10.1016/S0006-3223(01)01129-5
Koydemir, S., & Essau, C. A. (2018). Anxiety and Anxiety Disorders in Young People: A Cross-Cultural Perspective. In Understanding Uniqueness and Diversity in Child and Adolescent Mental Health (pp. 115–134). Academic Press. https://doi.org/10.1016/B978-0-12-815310-9.00005-8.
Lee, M. T., Wong, B. P., Chow, B. W. Y., & McBride-Chang, C. (2006). Predictors of suicide ideation and depression in Hong Kong adolescents: Perceptions of academic and family climates. Suicide and Life-Threatening Behavior, 36(1), 82–96. https://doi.org/10.1521/suli.2006.36.1.82
Leong, F. T., Okazaki, S., & Tak, J. (2003). Assessment of depression and anxiety in East Asia. Psychological Assessment, 15(3), 290–305. https://doi.org/10.1037/1040-3590.15.3.290
Lewinsohn, P. M., Rohde, P., & Seeley, J. R. (1998). Major depressive disorder in older adolescents: prevalence, risk factors, and clinical implications. Clinical Psychology Review, 18(7), 765–794. https://doi.org/10.1016/S0272-7358(98)00010-5
Mathew, A. R., Pettit, J. W., Lewinsohn, P. M., Seeley, J. R., & Roberts, R. E. (2011). Co-morbidity between major depressive disorder and anxiety disorders: shared etiology or direct causation? Psychological Medicine, 41(10), 2023–2034. https://doi.org/10.1017/s0033291711000407
March, J. S., Parker, J. D., Sullivan, K., Stallings, P., & Conners, C. K. (1997). The Multidimensional Anxiety Scale for Children (MASC): factor structure, reliability, and validity. Journal of the American Academy of Child & Adolescent Psychiatry, 36(4), 554–565. https://doi.org/10.1097/00004583-199704000-00019
Markus, H. R., & Kitayama, S. (1991). Culture and the self: Implications for cognition, emotion, and motivation. Psychological Review, 98(2), 224–253. https://doi.org/10.1037/0033-295x.98.2.224
Markus, H. R., Uchida, Y., Omoregie, H., Townsend, S. S., & Kitayama, S. (2006). Going for the gold: Models of agency in Japanese and American contexts. Psychological Science, 17(2), 103–112. https://doi.org/10.1111/j.1467-9280.2006.01672.x
McKeever, V. M., & Huff, M. E. (2003). A diathesis-stress model of posttraumatic stress disorder: Ecological, biological, and residual stress pathways. Review of General Psychology, 7(3), 237–250. https://doi.org/10.1037/1089-2680.7.3.237
Menon, S. V., Cohen, J. R., Shorey, R. C., & Temple, J. R. (2018). The impact of intimate partner violence exposure in adolescence and emerging adulthood: A developmental psychopathology approach. Journal of Clinical Child & Adolescent Psychology, 47(sup1), S497–S508. https://doi.org/10.1080/15374416.2018.1437736
Moos, R. H. (1990). Conceptual and empirical approaches to developing family-based assessment procedures: Resolving the case of the Family Environment Scale. Family Process, 29(2), 199–208. https://doi.org/10.1111/j.1545-5300.1990.00199.x
Neale, M. C., & Kendler, K. S. (1995). Models of comorbidity for multifactorial disorders. American Journal of Human Genetics, 57(4), 935–953. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1801512/pdf/ajhg00036-0199.pdf.
Ng, M. Y., & Weisz, J. R. (2016). Annual research review: Building a science of personalized intervention for youth mental health. Journal of Child Psychology and Psychiatry, 57(3), 216–236. https://doi.org/10.1111/jcpp.12470
O’Neil, K. A., Podell, J. L., Benjamin, C. L., & Kendall, P. C. (2010). Comorbid depressive disorders in anxiety-disordered youth: Demographic, clinical, and family characteristics. Child Psychiatry & Human Development, 41(3), 330–341. https://doi.org/10.1007/s10578-009-0170-9
Radloff, L. S. (1977). The CES-D scale: A self-report depression scale for research in the general population. Applied Psychological Measurement, 1(3), 385–401. https://doi.org/10.1177/014662167700100306
Schafer, J. L., & Graham, J. W. (2002). Missing data: our view of the state of the art. Psychological Methods, 7(2), 147. https://doi.org/10.1037/1082-989x.7.2.147
Shanahan, L., Copeland, W., Jane Costello, E., & Angold, A. (2008). Specificity of putative psychosocial risk factors for psychiatric disorders in children and adolescents. Journal of Child Psychology and Psychiatry, 49(1), 34–42. https://doi.org/10.1111/j.1469-7610.2007.01822.x
Sheeber, L., Hops, H., Alpert, A., Davis, B., & Andrews, J. (1997). Family support and conflict: Prospective relations to adolescent depression. Journal of Abnormal Child Psychology, 25(4), 333–344.
Shek, D. T. L. (2001). Chinese Adolescents and Their Parents’ Views on a Happy Family: Implications for Family Therapy. Family Therapy, 28(2), 73–103.
Shrive, F. M., Stuart, H., Quan, H., & Ghali, W. A. (2006). Dealing with missing data in a multi-question depression scale: a comparison of imputation methods. BMC Medical Research Methodology, 6(1), 57. https://doi.org/10.1186/1471-2288-6-57
Singer, J. D., & Willett, J. B. (2003). Applied longitudinal data analysis: Modeling change and event occurrence. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780195152968.001.0001
Starr, L. R., & Davila, J. (2008). Differentiating interpersonal correlates of depressive symptoms and social anxiety in adolescence: Implications for models of comorbidity. Journal of Clinical Child & Adolescent Psychology, 37(2), 337–349. https://doi.org/10.1080/15374410801955854
Starr, L. R., Stroud, C. B., & Li, Y. I. (2016). Predicting the transition from anxiety to depressive symptoms in early adolescence: Negative anxiety response style as a moderator of sequential comorbidity. Journal of Affective Disorders, 190, 757–763. https://doi.org/10.1016/j.jad.2015.10.065
Tang, X., Tang, S., Ren, Z., & Wong, D. F. K. (2020). Psychological Risk and Protective Factors Associated with Depressive Symptoms among Adolescents in Secondary Schools in China: A Systematic Review and Meta-Analysis. Children and Youth Services Review, 108, 104680. https://doi.org/10.1016/j.childyouth.2019.104680
Tepper, P., Liu, X., Guo, C., Zhai, J., Liu, T., & Li, C. (2008). Depressive symptoms in Chinese children and adolescents: parent, teacher, and self reports. Journal of Affective Disorders, 111(2–3), 291–298. https://doi.org/10.1016/j.jad.2008.03.013
van Brakel, A. M., Muris, P., Bögels, S. M., & Thomassen, C. (2006). A multifactorial model for the etiology of anxiety in non-clinical adolescents: Main and interactive effects of behavioral inhibition, attachment and parental rearing. Journal of Child and Family Studies, 15(5), 568–578. https://doi.org/10.1007/s10826-006-9061-x
Woo, B. S., Chang, W. C., Fung, D. S., Koh, J. B., Leong, J. S., Kee, C. H., & Seah, C. K. (2004). Development and validation of a depression scale for Asian adolescents. Journal of Adolescence, 27(6), 677–689. https://doi.org/10.1016/j.adolescence.2003.12.004
Xin, Z., Zhang, L., & Liu, D. (2010). Birth cohort changes of Chinese adolescents’ anxiety: A cross-temporal meta-analysis, 1992–2005. Personality and Individual Differences, 48(2), 208–212. https://doi.org/10.1016/j.paid.2009.10.010
Xu, D. D., Rao, W. W., Cao, X. L., Wen, S. Y., Che, W. I., & Xiang, Y. T. (2018). Prevalence of major depressive disorder in children and adolescents in China: A systematic review and meta-analysis. Journal of Affective Disorders, 241, 592–598. https://doi.org/10.1016/j.jad.2018.07.083
Yao, S., Zou, T., Zhu, X., Abela, J. R., Auerbach, R. P., & Tong, X. (2007). Reliability and validity of the Chinese version of the multidimensional anxiety scale for children among Chinese secondary school students. Child Psychiatry and Human Development, 38(1), 1–16. https://doi.org/10.1007/s10578-006-0039-0
Yoon, J., & Lau, A. S. (2008). Maladaptive perfectionism and depressive symptoms among Asian American college students: Contributions of interdependence and parental relations. Cultural Diversity and Ethnic Minority Psychology, 14(2), 92–101. https://doi.org/10.1037/1099-9809.14.2.92
Yu, Y., Yang, X., Yang, Y., Chen, L., & Qiu, X…, He, J. . (2015). The role of family environment in depressive symptoms among university students: a large sample survey in China. PLoS ONE, 10(12), e0143612. https://doi.org/10.1371/journal.pone.0143612
Acknowledgements
We write this manuscript with gratitude to JRZ Abela, who continues to inspire those of us who knew him, as well as a new generation of developmental psychopathologists who never had the opportunity.
Funding
The research reported in this article was supported by a research grant from the Social Sciences and Research Council of Canada awarded to John R. Z. Abela.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research commitee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Appendices
Appendix A
Equations and summary of findings for the intercept models
Causal Model | Equations | Findings | Conclusions |
|---|---|---|---|
Anxiety predicting Depression | Depij = u0i + β0i + β1Age + β2Gender + β3iTimeti + β4iQuadTimeti + β5iCubicTimeti + β6iAnx(T)ti + β7iDep(T-1)ti + β8iAnx_I(T-1)ti + β9iAnx_N(T-1)ti + eij | Person-centered anxiety symptoms were found to significantly predict prospective depressive symptoms | Reciprocal Relationship |
Depression predicting Anxiety | Anxij = u0i + β0i + β1Age + β2Gender + β3iTimeti + β4iQuadTimeti + β5iDep(T)ti + β6iAnx(T-1)ti + β7iDep_I(T-1)ti + β8iDep_N(T-1)ti + eij | Person-centered depressive symptoms were found to significantly predict prospective anxiety symptoms | |
Correlated Liabilities Model | |||
Diathesis-Stress Component | |||
Stressor × Conflict | Depij = u0i + β0i + β1Age + β2Gender + β3iTimeti + β4iQuadTimeti + β5iCubicTimeti + β6iAnx(T) + β7iDep(T-1) + β8Cohesion(Conflict) + β9iStressor_Iti + β10iStressor_Nti + β11i Cohesion(Conflict) × Stressor_I ti + β12i Cohesion(Conflict) × Stressor_N ti + eij Anxij = u0i + β0i + β1Age + β2Gender + β3iTimeti + β4iQuadTimeti + β5iDep(T) + β6iAnx(T-1) + β7Cohesion(Conflict) + β8iStressor_Iti + β9iStressor_Nti + β10i Cohesion(Conflict) × Stressor_I ti + β11i Cohesion(Conflict) × Stressor_N ti + eij | Stressor × Conflict did not significantly predict prospective anxiety nor depressive symptoms | No support for the diathesis-stress component of the correlated-liabilities models |
Stressor × Cohesion | Stressor × Cohesion did not significantly predict prospective anxiety nor depressive symptoms | ||
Main Effects | |||
Family Conflict | Depij = u0i + β0i + β1Age + β2Gender + β3iTimeti + β4iQuadTimeti + β5iCubicTimeti + β6iAnx(T)ti + β7iDep(T-1)ti + β8Cohesion(Conflict) + eij Anxij = u0i + β0i + β1Age + β2Gender + β3iTimeti + β4iQuadTimeti + β5iDep(T)ti + β6iAnx(T-1)ti + β7Cohesion(Conflict) + eij | Family conflict significantly predicted both anxiety and depressive symptoms | Both family conflict and cohesion were predictive of depressive and anxiety symptoms |
Family Cohesion | Family cohesion significantly predicted both anxiety and depressive symptoms | ||
Diathesis-Anxiety Model | |||
Anxiety × Conflict | Depij = u0i + β0i + β1Age + β2Gender + β3iTimeti + β4iQuadTimeti + β5iCubicTimeti + β6iAnx(T)ti + β7iDep(T-1)ti + β8iAnx_I(T-1)ti + β9iAnx_N(T-1)ti + β10Cohesion(Conflict) + β11i Cohesion(Conflict) × Anx_I(T-1)ti + β12i Cohesion(Conflict) × Anx_N(T-1)ti + eij | Anxiety × Conflict did not significantly predict prospective levels of depressive symptoms | Family cohesion, but not family conflict, interacted significantly with an idiographic conceptualization of anxiety symptoms to predict depressive symptoms |
Anxiety × Cohesion | Anxiety_I × Cohesion did significantly predict prospective levels of depressive symptoms | ||
Diathesis-Depression Model | |||
Depression × Conflict | Anxij = u0i + β0i + β1Age + β2Gender + β3iTimeti + β4iQuadTimeti + β5iDep(T)ti + β6iAnx(T-1)ti + β7iDep_I(T-1)ti + β8iDep_N(T-1)ti + β9Cohesion(Conflict) + β10i Cohesion(Conflict) × Dep_I(T-1)ti + β11i Cohesion(Conflict) × Dep_N(T-1)ti + eij | Anxiety × Conflict did not significantly predict prospective levels of depressive symptoms | No support was found for a diathesis-depression model |
Depression × Cohesion | Anxiety × Conflict did not significantly predict prospective levels of depressive symptoms |
Appendix B
Parameter estimates for correlated-liabilities models
B | SE | T(df) | Reffect size | |
|---|---|---|---|---|
Effects on depression trajectory | ||||
Stressor_I \(\times\) Cohesion \(\times\) Timea | -0.012 | 0.058 | -0.214(1725) | 0.01 |
Stressor_N \(\times\) Cohesion \(\times\) Timea | 0.088 | 0.040 | 2.218(1648) | 0.06 |
Stressor_I \(\times\) Conflict \(\times\) Time | -0.124 | 0.318 | -0.391(1534) | 0.01 |
Stressor_N \(\times\) Conflict \(\times\) Time | 0.367 | 0.216 | 1.702(1510) | 0.04 |
Effects on depression levels | ||||
Stressor_I \(\times\) Cohesiona | -0.081 | 0.093 | -0.869(2396) | 0.02 |
Stressor_N \(\times\) Cohesiona | -0.217 | 0.088 | -2.466(2849)* | 0.05 |
Stressor_I \(\times\) Conflict | -0.499 | 0.742 | -0.673(1480) | 0.02 |
Stressor_N \(\times\) Conflict | -0.491 | 0.678 | -0.724(835) | 0.03 |
Effects on anxiety trajectory | ||||
Stressor_I \(\times\) Cohesion \(\times\) Time | -3.100 | 2.795 | -1.109(1610) | 0.03 |
Stressor_N \(\times\) Cohesion \(\times\) Time | 0.246 | 1.966 | 0.125(1687) | 0.00 |
Stressor_I \(\times\) Conflict \(\times\) Time | -5.534 | 12.602 | -0.439(1647) | 0.01 |
Stressor_N \(\times\) Conflict \(\times\) Time | 8.273 | 8.565 | 0.966(1669) | 0.02 |
Effects on anxiety levels | ||||
Stressor_I \(\times\) Cohesion | 0.463 | 6.651 | 0.071(1352) | 0.00 |
Stressor_N \(\times\) Cohesion | -8.731 | 6.072 | -1.438(795) | 0.05 |
Stressor_I \(\times\) Conflict | -25.819 | 28.676 | -0.900(1458) | 0.02 |
Stressor_N \(\times\) Conflict | -7.662 | 26.269 | -0.292(831) | 0.01 |
Rights and permissions
About this article
Cite this article
Choi, J., Hong, W., Abela, J.R.Z. et al. Comorbid Depression and Anxiety Symptoms in Chinese Adolescents: Testing the Explanatory Power of a Diathesis-Anxiety Model. Res Child Adolesc Psychopathol 49, 503–517 (2021). https://doi.org/10.1007/s10802-020-00730-8
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10802-020-00730-8