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Dynamic risk for first onset of depressive disorders in adolescence: does change matter?

Published online by Cambridge University Press:  22 November 2021

Wenting Mu*
Department of Psychology, Tsinghua University, Beijing, China
Kaiqiao Li
Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, USA
Yuan Tian
Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, USA
Greg Perlman
Department of Psychiatry, Stony Brook University, Stony Brook, NY, USA
Giorgia Michelini
Department of Psychiatry, Stony Brook University, Stony Brook, NY, USA Semel Institute for Neuroscience & Human Behavior, University of California Los Angeles, Los Angeles, CA, USA
David Watson
Department of Psychology, University of Notre Dame, Notre Dame, Indiana, USA
Hans Ormel
Department of Psychiatry, University Medical Center Groningen, Groningen, The Netherlands
Daniel N. Klein
Department of Psychology, Stony Brook University, Stony Brook, NY, USA
Roman Kotov*
Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, USA Department of Psychiatry, Stony Brook University, Stony Brook, NY, USA Semel Institute for Neuroscience & Human Behavior, University of California Los Angeles, Los Angeles, CA, USA
Author for correspondence: Wenting Mu, E-mail:; Roman Kotov, E-mail:
Author for correspondence: Wenting Mu, E-mail:; Roman Kotov, E-mail:



Risk factors for depressive disorders (DD) change substantially over time, but the prognostic value of these changes remains unclear. Two basic types of dynamic effects are possible. The ‘Risk Escalation hypothesis’ posits that worsening of risk levels predicts DD onset above average level of risk factors. Alternatively, the ‘Chronic Risk hypothesis’ posits that the average level rather than change predicts first-onset DD.


We utilized data from the ADEPT project, a cohort of 496 girls (baseline age 13.5–15.5 years) from the community followed for 3 years. Participants underwent five waves of assessments for risk factors and diagnostic interviews for DD. For illustration purposes, we selected 16 well-established dynamic risk factors for adolescent depression, such as depressive and anxiety symptoms, personality traits, clinical traits, and social risk factors. We conducted Cox regression analyses with time-varying covariates to predict first DD onset.


Consistently elevated risk factors (i.e. the mean of multiple waves), but not recent escalation, predicted first-onset DD, consistent with the Chronic Risk hypothesis. This hypothesis was supported across all 16 risk factors.


Across a range of risk factors, girls who had first-onset DD generally did not experience a sharp increase in risk level shortly before the onset of disorder; rather, for years before onset, they exhibited elevated levels of risk. Our findings suggest that chronicity of risk should be a particular focus in screening high-risk populations to prevent the onset of DDs. In particular, regular monitoring of risk factors in school settings is highly informative.

Original Article
Copyright © The Author(s), 2021. Published by Cambridge University Press

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American Psychiatric Association. (2020). Diagnostic and statistical manual of mental disorders (DSM-IV). Am Psychiatric Assoc.Google Scholar
Babor, T. F., Brown, J., & Del Boca, F. K. (1990). Validity of self-reports in applied research on addictive behaviors: Fact or fiction? Behavioral Assessment, 12, 531.Google Scholar
Bagby, R. M., Parker, J. D., Joffe, R. T., & Buis, T. (1994). Reconstruction and validation of the Depressive Experiences Questionnaire. Assessment, 1(1), 5968.CrossRefGoogle ScholarPubMed
Bagby, R. M., Quilty, L. C., & Ryder, A. C. (2008). Personality and depression. The Canadian Journal of Psychiatry, 53(1), 1425.CrossRefGoogle ScholarPubMed
Belsley, D. A., Kuh, E., & Welsch, R. E. (2005). Regression diagnostics: Identifying influential data and sources of collinearity (Vol. 571). New York: Wiley.Google Scholar
Bey, G. S., Waring, M. E., Jesdale, B. M., & Person, S. D. (2018). Gendered race modification of the association between chronic stress and depression among Black and White US adults. American Journal of Orthopsychiatry, 88(2), 151.CrossRefGoogle Scholar
Blatt, S. J., Afflitti, J. P., & Quinlan, D. M. (1976). Experiences of depression in normal young adults. Journal of Abnormal psychology, 85(4), 383.CrossRefGoogle ScholarPubMed
Bleys, D., Soenens, B., Claes, S., Vliegen, N., & Luyten, P. (2018). Parental psychological control, adolescent self-criticism, and adolescent depressive symptoms: A latent change modeling approach in Belgian adolescents. Journal of clinical psychology, 74(10), 18331853.CrossRefGoogle ScholarPubMed
Burkhouse, K. L., Uhrlass, D. J., Stone, L. B., Knopik, V. S., & Gibb, B. E. (2012). Expressed emotion-criticism and risk of depression onset in children. Journal of Clinical Child & Adolescent Psychology, 41(6), 771777.CrossRefGoogle ScholarPubMed
Cuijpers, P., Van Straten, A., & Smit, F. (2005). Preventing the incidence of new cases of mental disorders: A meta-analytic review. The Journal of Nervous and Mental Disease, 193(2), 119125.CrossRefGoogle ScholarPubMed
De Los Reyes, A., & Prinstein, M. J. (2004). Applying depression-distortion hypotheses to the assessment of peer victimization in adolescents. Journal of Clinical Child and Adolescent Psychology, 33(2), 325335.CrossRefGoogle Scholar
Fernandes, S., Davidson, J. G., & Guthrie, D. M. (2018). Changes in social engagement and depression predict incident loneliness among seriously ill home care clients. Palliative and supportive care, 16, 170179.Google Scholar
Furman, W., & Buhrmester, D. (2009). Methods and measures: The network of relationships inventory: Behavioral systems version. International Journal of Behavioral Development, 33(5), 470478.CrossRefGoogle Scholar
Fusar-Poli, P., Borgwardt, S., Bechdolf, A., Addington, J., Riecher-Rössler, A., Schultze-Lutter, F., … Valmaggia, L. (2013). The psychosis high-risk state: A comprehensive state-of-the-art review. JAMA Psychiatry, 70(1), 107120.CrossRefGoogle Scholar
Hammen, C., Hazel, N. A., Brennan, P. A., & Najman, J. (2012). Intergenerational transmission and continuity of stress and depression: Depressed women and their offspring in 20 years of follow-up. Psychological Medicine, 42(5), 931942.CrossRefGoogle ScholarPubMed
Hammen, C., Kim, E. Y., Eberhart, N. K., & Brennan, P. A. (2009). Chronic and acute stress and the prediction of major depression in women. Depression and Anxiety, 26(8), 718723.CrossRefGoogle ScholarPubMed
Hankin, B. L. (2008). Stability of cognitive vulnerabilities to depression: a short-term prospective multiwave study. Journal of abnormal psychology, 117(2), 324.CrossRefGoogle ScholarPubMed
Hankin, B. L. (2012). Future directions in vulnerability to depression among youth: Integrating risk factors and processes across multiple levels of analysis. Journal of Clinical Child & Adolescent Psychology, 41(5), 695718.CrossRefGoogle ScholarPubMed
Hankin, B. L., Abramson, L. Y., Moffitt, T. E., Silva, P. A., McGee, R., & Angell, K. E. (1998). Development of depression from preadolescence to young adulthood: Emerging gender differences in a 10-year longitudinal study. Journal of Abnormal Psychology, 107(1), 128.CrossRefGoogle Scholar
Hirschfeld, R. M., Klerman, G. L., Gouch, H. G., Barrett, J., Korchin, S. J., & Chodoff, P. (1977). A measure of interpersonal dependency. Journal of Personality Assessment, 41(6), 610618.CrossRefGoogle ScholarPubMed
Jacobson, N. S., & Truax, P. (1991). Clinical significance: A statistical approach to defining meaningful change in psychotherapy research. Journal of Consulting and Clinical Psychology, 59(1), 1219.CrossRefGoogle ScholarPubMed
Jeronimus, B. F., Kotov, R., Riese, H., & Ormel, J. (2016). Neuroticism's prospective association with mental disorders halves after adjustment for baseline symptoms and psychiatric history, but the adjusted association hardly decays with time: A meta-analysis on 59 longitudinal/prospective studies with 443 313 participants. Psychological Medicine, 46(14), 28832906.CrossRefGoogle Scholar
John, O. P., & Srivastava, S. (1999). The Big Five trait taxonomy: History, measurement, and theoretical perspectives. Handbook of Personality: Theory and Research, 2(1999), 102138.Google Scholar
Kaufman, J., Birmaher, B., Brent, D., Rao, U. M. A., Flynn, C., Moreci, P., … Ryan, N. (1997). Schedule for affective disorders and schizophrenia for school-age children-present and lifetime version (K-SADS-PL): Initial reliability and validity data. Journal of the American Academy of Child & Adolescent Psychiatry, 36(7), 980988.CrossRefGoogle ScholarPubMed
Kendall, T., & Langer, A. (2015). Critical maternal health knowledge gaps in low-and middle-income countries for the post-2015 era. Reproductive Health, 12(1), 55.CrossRefGoogle ScholarPubMed
Kendler, K. S., & Aggen, S. H. (2017). Symptoms of major depression: Their stability, familiality, and prediction by genetic, temperamental, and childhood environmental risk factors. Depression and anxiety, 34(2), 171177.CrossRefGoogle ScholarPubMed
Klein, D. K., Glenn, C. R., Kosty, D. B., Seeley, J. R., Rohde, P., & Lewinsohn, P. M. (2013). Predictors of first lifetime onset of major depressive disorder in young adulthood. Journal of Abnormal Psychology, 122, 16.CrossRefGoogle ScholarPubMed
Klein, D. N., Kotov, R., & Bufferd, S. J. (2011). Personality and depression: Explanatory models and review of the evidence. Annual Review of Clinical Psychology, 7, 269295.CrossRefGoogle ScholarPubMed
Klein, D. N., Shankman, S. A., Lewinsohn, P. M., & Seeley, J. R. (2009). Subthreshold depressive disorder in adolescents: Predictors of escalation to full-syndrome depressive disorders. Journal of the American Academy of Child & Adolescent Psychiatry, 48(7), 703710.CrossRefGoogle ScholarPubMed
Klimstra, T. A., Hale, W. W. III, Raaijmakers, Q. A., Branje, S. J., & Meeus, W. H. (2010). Identity formation in adolescence: Change or stability?. Journal of Youth and Adolescence, 39(2), 150162.CrossRefGoogle ScholarPubMed
Kopala-Sibley, D. C., Zuroff, D. C., Hankin, B. L., & Abela, J. R. (2015). The development of self-criticism and dependency in early adolescence and their role in the development of depressive and anxiety symptoms. Personality and Social Psychology Bulletin, 41(8), 10941109.CrossRefGoogle ScholarPubMed
Kushner, S. C., Bagby, R. M., & Harkness, K. L. (2017). Stress generation in adolescence: Contributions from five-factor model (FFM) personality traits and childhood maltreatment. Personality Disorders: Theory, Research, and Treatment, 8(2), 150.CrossRefGoogle ScholarPubMed
Laceulle, O. M., Ormel, J., Vollebergh, W. A., Van Aken, M. A., & Nederhof, E. (2014). A test of the vulnerability model: Temperament and temperament change as predictors of future mental disorders – the TRAILS study. Journal of Child Psychology and Psychiatry, 55(3), 227236.CrossRefGoogle ScholarPubMed
Liu, R. T., & Alloy, L. B. (2010). Stress generation in depression: A systematic review of the empirical literature and recommendations for future study. Clinical Psychology Review, 30(5), 582593.CrossRefGoogle ScholarPubMed
Mahaffey, B. L., Watson, D., Clark, L. A., & Kotov, R. (2016). Clinical and personality traits in emotional disorders: Evidence of a common framework. Journal of Abnormal Psychology, 125(6), 758.CrossRefGoogle ScholarPubMed
McCoach, D. B., & Siegle, D. (2003). The school attitude assessment survey-revised: A new instrument to identify academically able students who underachieve. Educational and Psychological Measurement, 63(3), 414429.CrossRefGoogle Scholar
Mu, W., Luo, J., Nickel, L., & Roberts, B. W. (2016). Generality or specificity? Examining the relation between personality traits and mental health outcomes using a bivariate bi-factor latent change model. European Journal of Personality, 30(5), 467483.CrossRefGoogle Scholar
Mu, W., Luo, J., Rieger, S., Trautwein, U., & Roberts, B. (2019). The relationship between self-esteem and depression when controlling for neuroticism. Collabra: Psychology, 5(1), 11.CrossRefGoogle Scholar
Naragon-Gainey, K., Gallagher, M. W., & Brown, T. A. (2013). Stable ‘trait’ variance of temperament as a predictor of the temporal course of depression and social phobia. Journal of Abnormal Psychology, 122(3), 611.CrossRefGoogle ScholarPubMed
Nelemans, S. A., Hale, W. W., Branje, S. J., Hawk, S. T., & Meeus, W. H. (2014). Maternal criticism and adolescent depressive and generalized anxiety disorder symptoms: A 6-year longitudinal community study. Journal of abnormal child psychology, 42(5), 755766.CrossRefGoogle ScholarPubMed
Nelson, B., McGorry, P. D., Wichers, M., Wigman, J. T., & Hartmann, J. A. (2017). Moving from static to dynamic models of the onset of mental disorder: A review. JAMA Psychiatry, 74(5), 528534.CrossRefGoogle ScholarPubMed
Nelson, B. D., Perlman, G., Klein, D. N., Kotov, R., & Hajcak, G. (2016). Blunted neural response to rewards as a prospective predictor of the development of depression in adolescent girls. American Journal of Psychiatry, 173(12), 12231230.CrossRefGoogle ScholarPubMed
Nocentini, A., Menesini, E., & Salmivalli, C. (2013). Level and change of bullying behavior during high school: A multilevel growth curve analysis. Journal of adolescence, 36(3), 495505.CrossRefGoogle Scholar
Nolen-Hoeksema, S. (1987). Sex differences in unipolar depression: evidence and theory. Psychological bulletin, 101(2), 259.CrossRefGoogle ScholarPubMed
Nolen-Hoeksema, S. (1991). Responses to depression questionnaire. Unpublished manuscript.Google Scholar
Roberts, B. W., Walton, K. E., & Viechtbauer, W. (2006). Patterns of mean-level change in personality traits across the life course: A meta-analysis of longitudinal studies. Psychological Bulletin, 132(1), 1.CrossRefGoogle ScholarPubMed
Rogosa, D. R. 1995. Myths and methods: ‘Myths about longitudinal research’ plus supplemental questions. In Gottman, J. M. (Ed.), The analysis of change (pp. 366). Mahwah, NJ: Erlbaum.Google Scholar
Sachs-Ericsson, N., Verona, E., Joiner, T., & Preacher, K. J. (2006). Parental verbal abuse and the mediating role of self-criticism in adult internalizing disorders. Journal of Affective Disorders, 93(1–3), 7178.CrossRefGoogle ScholarPubMed
Schafer, J. L., & Graham, J. W. (2002). Missing data: Our view of the state of the art. Psychological Methods, 7(2), 147.CrossRefGoogle ScholarPubMed
Shanahan, L., Copeland, W. E., Costello, E. J., & Angold, A. (2011). Child-, adolescent-and young adult-onset depressions: Differential risk factors in development? Psychological Medicine, 41(11), 22652274.CrossRefGoogle ScholarPubMed
Slavich, G. M., & Irwin, M. R. (2014). From stress to inflammation and major depressive disorder: A social signal transduction theory of depression. Psychological Bulletin, 140(3), 774.CrossRefGoogle ScholarPubMed
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), 337349.CrossRefGoogle ScholarPubMed
Steiger, A. E., Allemand, M., Robins, R. W., & Fend, H. A. (2014). Low and decreasing self-esteem during adolescence predict adult depression two decades later. Journal of Personality and Social Psychology, 106(2), 325.CrossRefGoogle ScholarPubMed
Stice, E., Ragan, J., & Randall, P. (2004). Prospective relations between social support and depression: Differential direction of effects for parent and peer support?. Journal of Abnormal Psychology, 113(1), 155.CrossRefGoogle ScholarPubMed
Swearer, S. M., Song, S. Y., Cary, P. T., Eagle, J. W., & Mickelson, W. T. (2001). Psychosocial correlates in bullying and victimization: The relationship between depression, anxiety, and bully/victim status. Journal of Emotional Abuse, 2(2–3), 95121.CrossRefGoogle Scholar
Van Voorhees, B. W., Paunesku, D., Kuwabara, S. A., Basu, A., Gollan, J., Hankin, B. L., … Reinecke, M. (2008). Protective and vulnerability factors predicting new-onset depressive episode in a representative of US adolescents. Journal of Adolescent Health, 42(6), 605616.CrossRefGoogle Scholar
Wang, J., Sareen, J., Patten, S., Bolton, J., Schmitz, N., & Birney, A. (2014). A prediction algorithm for first onset of major depression in the general population: Development and validation. Journal of Epidemiology & Community Health, 68(5), 418424.CrossRefGoogle ScholarPubMed
Watson, D., O'Hara, M. W., Naragon-Gainey, K., Koffel, E., Chmielewski, M., Kotov, R., … Ruggero, C. J. (2012). Development and validation of new anxiety and bipolar symptom scales for an expanded version of the IDAS (the IDAS-II). Assessment, 19(4), 399420.CrossRefGoogle ScholarPubMed
Wilson, S., Vaidyanathan, U., Miller, M. B., McGue, M., & Iacono, W. G. (2014). Premorbid risk factors for major depressive disorder: Are they associated with early onset and recurrent course?. Development and Psychopathology, 26, 1477.CrossRefGoogle ScholarPubMed
Yaroslavsky, I., Pettit, J. W., Lewinsohn, P. M., Seeley, J. R., & Roberts, R. E. (2013). Heterogeneous trajectories of depressive symptoms: Adolescent predictors and adult outcomes. Journal of affective disorders, 148(2-3), 391399.CrossRefGoogle ScholarPubMed
Young, M. A., Fogg, L. F., Scheftner, W., Fawcett, J., Akiskal, H., & Maser, J. (1996). Stable trait components of hopelessness: Baseline and sensitivity to depression. Journal of Abnormal Psychology, 105(2), 155.CrossRefGoogle ScholarPubMed
Zimet, G. D., Dahlem, N. W., Zimet, S. G., & Farley, G. K. (1988). The multidimensional scale of perceived social support. Journal of Personality Assessment, 52(1), 3041.CrossRefGoogle Scholar
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