Abstract
The hopelessness theory, Beck’s cognitive theory, and the response styles theory dominate our understanding and the treatment of depression in adolescents. However, research supporting them is largely based on White individuals. Further, the associations between stressors, cognitive vulnerabilities, and depressive symptoms in Black adolescents are not as one would expect based on the predictions from those theories. Both raise the question of if and to what degree these theories and previous findings can be generalized to Black adolescents. Additionally, without a theoretical basis, clinicians regularly use interventions developed based on one theory to influence vulnerabilities described in another theory. Thus, the purpose of our study was to examine the structure of an integrated cognitive stress-vulnerability model as well as the strengths of associations between stressors, cognitive vulnerabilities, and depressive symptoms in Black and White adolescents. In our study, 295 Black (37% female) and 213 White (49% female) ninth-grade students from a public high school participated. Network analyses demonstrated that the three original cognitive theories of depression can and should be integrated and that each variable we examined is comparably relevant for Black and White adolescents. At the same time, the structure of the two integrated networks differed significantly among Black and White adolescents, exhibiting specific distinctions at four edge levels. Furthermore, the predictability of the network is notably lower for Black adolescents than for White adolescents. Important theoretical and clinical implications can be derived.
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References
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), 259–271. https://doi.org/10.1037/a0022796.
Abramson, L. Y., Metalsky, G. I., & Alloy, L. B. (1989). Hopelessness depression: A theory-based subtype of depression. Psychological Review, 96(2), 358–372. https://doi.org/10.1037/0033-295X.96.2.358.
American Psychological Association, APA Task Force on Race and Ethnicity Guidelines in Psychology (2019). Race and Ethnicity Guidelines in Psychology: Promoting Responsiveness and Equity. Retrieved from http://www.apa.org/about/policy/race-and-ethnicity-in-psychology.pdf.
Bastiaansen, J. A., Kunkels, Y. K., Blaauw, F. J., Boker, S. M., Ceulemans, E., Chen, M., & Fisher, A. J. (2020). Time to get personal? The impact of researchers choices on the selection of treatment targets using the experience sampling methodology. Journal of Psychosomatic Research, 110211. https://doi.org/10.1016/j.jpsychores.2020.110211.
Beck, A. T. (1976). Cognitive therapy and the emotional disorders. International Universities.
Berghuis, K. J., Pössel, P., & Pittard, C. M. (2020). Perceived discrimination and depressive symptoms: Is the cognitive triad a moderator or mediator? Child & Youth Care Forum, 49, 647–660. https://doi.org/10.1007/s10566-019-09537-1.
Borsboom, D., & Cramer, A. O. (2013). Network analysis: 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.
Brunwasser, S. M., & Garber, J. (2016). Programs for the Prevention of Youth Depression: Evaluation of efficacy, effectiveness, and readiness for dissemination. Journal of Clinical Child and Adolescent Psychology, 45(6), 763–783. https://doi.org/10.1080/15374416.2015.1020541.
Bryant, B. E., Jordan, A., & Clark, U. S. (2022). Race as a social construct in psychiatry research and practice. JAMA Psychiatry, 79(2), 93–94. https://doi.org/10.1001/jamapsychiatry.2021.2877.
Bryant-Davis, T., Ullman, S. E., Tsong, Y., Tillman, S., & Smith, K. (2010). Struggling to survive: Sexual assault, poverty, and mental health outcomes of African American women. American Journal of Orthopsychiatry, 80(1), 61–70. https://doi.org/10.1111/j.19390025.2010.01007.x.
Burger, J., Isvoranu, A. M., Lunansky, G., Haslbeck, J. M. B., Epskamp, S., Hoekstra, R. H. A., Fried, E. I., Borsboom, D., & Blanken, T. F. (2023). Reporting standards for psychological network analyses in cross-sectional data. Psychological Methods, 28(4), 806–824. https://doi.org/10.1037/met0000471.
Cameron, A. C., & Windmeijer, F. A. (1997). An R-squared measure of goodness of fit for some common nonlinear regression models. Journal of Econometrics, 77(2), 329–342. https://doi.org/10.1016/S0304-4076(96)01818-0.
U.S. Census Bureau (2023). QuickFacts United States. https://www.census.gov/quickfacts/fact/table/US/RHI225221#RHI225221.
Centers for Disease Control and Prevention (2023). Youth Risk Behavior Survey. Data Summary & Trends Reporthttps://www.cdc.gov/healthyyouth/data/yrbs/pdf/YRBS_Data-Summary-Trends_Report2023_508.pdf.
Chowdhary, N., Jotheeswaran, A. T., Nadkarni, A., Hollon, S. D., King, M., Jordans, M. J., Rahman, A., Verdeli, H., Araya, R., & Patel, V. (2014). The methods and outcomes of cultural adaptations of psychological treatments for depressive disorders: A systematic review. Psychological Medicine, 44(6), 1131–1146. https://doi.org/10.1017/S0033291713001785.
Clark, R., Coleman, A. P., & Novak, J. D. (2004). Brief report: Initial psychometric properties of the everyday discrimination scale in Black adolescents. Journal of Adolescence, 27(3), 363–368. https://doi.org/10.1016/j.adolescence.2003.09.004.
Dalege, J., Borsboom, D., van Harreveld, F., van den Berg, H., Conner, M., & van der Maas, H. L. J. (2016). Toward a formalized account of attitudes: The causal attitude network (CAN) model. Psychological Review, 123(1), 2–22. https://doi.org/10.1037/a0039802.
Epskamp, S. (2016). Regularized gaussian psychological networks: Brief report on the performance of extended BIC model selection. arXiv Preprinthttps://arXiv.org/abs/1606.05771.
Epskamp, S., & Fried, E. I. (2018). A tutorial on regularized partial correlation networks. Psychological Methods, 23(4), 617–634. https://doi.org/10.1037/met0000167.
Faelens, L., Hoorelbeke, K., Fried, E., De Raedt, R., & Koster, E. H. (2019). Negative influences of Facebook use through the lens of network analysis. Computers in Human Behavior, 96, 13–22.
Gillham, J. E., Jaycox, L. H., Reivich, K. J., Seligman, M. E. P., & Silver, T. (1990). The Penn Resiliency Program. Unpublished manual. University of Pennsylvania.
Gotlib, I. H., & Neubauer, D. L. (2000). Information-processing approaches to the study of cognitive biases in depression. In S. L. Johnson, A. M. Hayes, T. M. Field, N. Schneiderman, & S. McCabe (Eds.), Stress, coping, and Depression (pp. 117–143). Erlbaum.
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/s15374424j ccp31 04_8.
Haslbeck, J. M. B., & Waldorp, L. J. (2018). How well do network models predict observations? On the importance of predictability in network models. Behavior Research Methods, 50, 853–861. https://doi.org/10.3758/s13428-017-0910-x.
Haslbeck, J. M. B., Borsboom, D., & Waldorp, L. J. (2021). Moderated Network models. Multivariate Behavioral Research, 56(2), 256–287. https://doi.org/10.1080/00273171.2019.1677207.
Hollon, S. D., & Kendall, P. C. (1980). Cognitive self-statements in depression: Development of an automatic thoughts questionnaire. Cognitive Therapy and Research, 4(4), 383–395. https://doi.org/10.1007/BF01178214.
Hoorelbeke, K., Marchetti, I., De Schryver, M., & Koster, E. H. (2016). The interplay between cognitive risk and resilience factors in remitted depression: A network analysis. Journal of Affective Disorders, 195, 96–104. https://doi.org/10.1016/j.jad.2016.02.001.
Hu, T., Zhang, D., & Yang, Z. (2015). The relationship between attributional style for negative outcomes and depression: A meta-analysis. Journal of Social and Clinical Psychology, 34(4), 304–321. https://doi.org/10.1521/jscp.2015.34.4.304.
Jakobsen, J. C., Gluud, C., Wetterslev, J., & Winkel, P. (2017). When and how should multiple imputation be used for handling missing data in randomised clinical trials–a practical guide with flowcharts. BMC Medical Research Methodology, 17, 1–10. https://doi.org/10.1186/s12874-017-0442-1.
James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An introduction to statistical learning: Withapplications in R. Springer.
Jefferson County Public Schools (2020). Free and reduced lunch trend data [Data set]. Cascade Data Portal. https://assessment.jefferson.kyschools.us/publicDatasets/PublicResources.aspx?id=511308.
Jefferson County Public Schools (2021). Jefferson County Public Schools Median Household Income for 2020. Cascade Data Portal. https://assessment.jefferson.kyschools.us/publicDatasets/pdf/2021/49_Median_Household_Income_by_zip_MAP.pdf.
Johnson, J. W. (2000). A Heuristic Method for estimating the relative weight of predictor variables in multiple regression. Multivariate Behavioral Research, 35(1), 1–19. https://doi.org/10.1207/S15327906MBR3501_1.
Kessler, R. C., Mickelson, K. D., & Williams, D. R. (1999). The prevalence, distribution, and mental health correlates of perceived discrimination in the United States. Journal of Health and Social Behavior, 40(3), 208–230. https://doi.org/10.2307/2676349.
Lavner, J. A., Hart, A. R., Carter, S. E., & Beach, S. R. H. (2022). Longitudinal effects of racial discrimination on depressive symptoms among Black Youth: Between- and within-person effects. Journal of the American Academy of Child and Adolescent Psychiatry, 61(1), 56–65. https://doi.org/10.1016/j.jaac.2021.04.020.
Leitenberg, H., Yost, L., & Carroll-Wilson, M. (1986). Negative cognitive errors in children: Questionnaire development, normative data, and comparisons between children with and without self-reported symptoms of depression, low self-esteem, and evaluation anxiety. Journal of Consulting and Clinical Psychology, 54(4), 528–536.
Kaslow, N.J., Stark, K. D., Printz, B., Livingston, R., & Tsai, S. L. (1992).Cognitive triad inventory for children: Development and relationship todepression and anxiety. Journal ofClinical Child Psychology, 21(4),339–347. https://doi.org/10.1207/s15374424jccp2104_3
Levin, K. A. (2006). Study design III: Cross-sectional studies. Evidence-BasedDentistry, 7(1), 24-25. https://doi.org/10.1038/sj.ebd.6400375
Lewinsohn, P. M., Roberts, R. E., Seeley, J. R., Rohde, P., Gotlib, I. H., & Hops, H. (1994). Adolescent psychopathology: II. Psychosocial risk factors for depression. Journal of Abnormal Psychology, 103(2), 302–315. https://doi.org/10.1037/0021-843X.103.2.302.
Lopez, C. M., Driscoll, K. A., & Kistner, J. A. (2009). Sex differences and response styles: Subtypes of rumination and associations with depressive symptoms. Journal of Clinical Child and Adolescent Psychology, 38(1), 27–35. https://doi.org/10.1080/15374410802575412.
Lu, W., Lindsey, M. A., Irsheid, S., & Nebbitt, V. E. (2017). Psychometric properties of the CES-D among black adolescents in public housing. Journal of the Society for Social Work and Research, 8(4), 595–619. https://doi.org/10.1086/694791.
Marchetti, I. (2019). Hopelessness: A network analysis. Cognitive Therapy and Research, 43(3), 611–619. https://doi.org/10.1007/s10608-018-9981-y.
Marchetti, I. (2023). The structure of compulsive sexual behavior: A network analysis study. Archives of Sexual Behavior, 52, 1271–1284. https://doi.org/10.1007/s10508-023-02549-y.
Marchetti, I., Pössel, P., & Koster, E. (2021). The architecture of cognitive vulnerability to depressive symptoms in adolescence: A longitudinal network analysis study. Research on Child and Adolescent Psychopathology, 49(1), 267–281. https://doi.org/10.1007/s10802-020-00733-5.
Moradi, B. (2013). Discrimination, objectification, and dehumanization: Toward a pantheoretical framework. In S. J. Gervais, S. J. Gervais (Eds.), Objectification and (de)humanization: 60th Nebraska symposium on motivation (pp. 153–181). Springer Science and Business Media. https://doi.org/10.1007/978-1-4614-6959-9_7.
National Institute of Mental Health (2022). Major Depression. https://www.nimh.nih.gov/health/statistics/major-depression.
National Center for Education Statistics. (2021). Enrollment characteristics: 2019–2020 school year U.S. Department of Education, Institute of Education Sciences. https://nces.ed.gov/ccd/schoolsearch/school_detail.asp?Search=1&InstName=Shawnee&State=21&DistrictName=Jefferson&SchoolType=1&SchoolType=2&SchoolType=3&SchoolType=4&SpecificSchlTypes=all&IncGrade=-1&LoGrade=-1&HiGrade=-1&ID=210299000777
Netemeyer, R. G., Williamson, D. A., Burton, S., Biswas, D., Jindal, S., Landreth, S., Mills, G., & Primeaux, S. (2002). Psychometric properties of shortened versions of the Automatic thoughts Questionnaire. Educational and Psychological Measurement, 62(1), 111–129. https://doi.org/10.1177/0013164402062001008.
Nolen-Hoeksema, S., Girgus, J. S., & Seligman, M. E. (1992). Predictors and consequences of childhood depressive symptoms: A 5-year longitudinal study. Journal of Abnormal Psychology, 101(3), 405–422. https://doi.org/10.1037/0021-843X.101.3.405.
Oud, M., De Winter, L., Vermeulen-Smit, E., Bodden, D., Nauta, M., Stone, L., & Stikkelbroek, Y. (2019). Effectiveness of CBT for children and adolescents with depression: A systematic review and meta-regression analysis. European Psychiatry, 57, 33–45. https://doi.org/10.1016/j.eurpsy.2018.12.008.
Pamplin, J. R. 2nd, & Bates, L. M. (2021). Evaluating hypothesized explanations for the black-white depression paradox: A critical review of the extant evidence. Social Science & Medicine (1982), 281, 114085. https://doi.org/10.1016/j.socscimed.2021.114085.
Pancost, S., & Pössel, P. (submitted). Do Dysfunctional Attitudes Moderate the Association Between Everyday Discrimination and Symptoms of Depression in Adolescents?.
Parry, G., & Brewin, C. R. (1988). Cognitive style and depression: symptom-related, event-related or independent provoking factor? British Journal of Clinical Psychology, 27(1), 23–35. https://doi.org/10.1111/j.2044-8260.1988.tb00750.x.
Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879.
Pössel, P., & Knopf, K. (2011). Bridging the gaps: An attempt to integrate three major cognitive depression models. Cognitive Therapy and Research, 35, 342–358. https://doi.org/10.1007/s10608-010-9325-z.
Randolph, J. J., Falbe, K., Manuel, A. K., & Baloun, J. L. (2014). A step-by-step guide to propensity score matching in R. Practical Assessment Research & Evaluation, 19(18). https://doi.org/10.7275/n3pv-tx27.
RosenfieldS (2012). Triple jeopardy? Mental health at the intersection of gender, race, and class. Social Science & Medicine (1982), 74(11), 1791–1801. https://doi.org/10.1016/j.socscimed.2011.11.010.
Rosenfield, S., Lennon, M. C., & White, H. R. (2005). The self and mental health: Self-salience and the emergence of internalizing and externalizing problems. Journal of Health and Social Behavior, 46(4), 323–340. https://doi.org/10.1177/002214650504600402.
Schäfer, J. Ö., Naumann, E., Holmes, E. A., Tuschen-Caffier, B., & Samson, A. C. (2017). Emotion regulation strategies in depressive and anxiety symptoms in Youth: A Meta-Analytic Review. Journal of Youth and Adolescence, 46(2), 261–276. https://doi.org/10.1007/s10964-016-0585-0.
Seely, H. D., Gaskins, J., Pössel, P., & Hautzinger, M. (2023). Comprehensive prevention: An evaluation of peripheral outcomes of a school-based prevention program. Research on Child and Adolescent Psychopathology, 51(7), 921–936. https://doi.org/10.1007/s10802-023-01043-2.
Shrider, E. A., Kollar, M., Chen, F., & Semega, J. (2021). U.S. Census Bureau, current Population reports, P60-273. Income and poverty in the United States: 2020. U.S. Government Publishing Office.
Southward, M. W., & Cheavens, J. S. (2018). Identifying core deficits in a dimensional model of borderline personality disorder features: A network analysis. Clinical Psychological Science, 6(5), 685–703. https://doi.org/10.1177/2167702618769560.
Substance Abuse and Mental Health Services Administration (2023). 2021 National Survey on Drug Use and Health (NSDUH). https://www.samhsa.gov/data/sites/default/files/reports/rpt39441/NSDUHDetailedTabs2021/NSDUHDetailedTabs2021/NSDUHDetTabsSect7pe2021.htm.
Tram, J. M., & Cole, D. A. (2000). Self-perceived competence and the relation between life events and depressive symptoms in adolescence: Mediator or moderator? Journal of Abnormal Psychology, 109(4), 753–760. https://doi.org/10.1037/0021-843X.109.4.753.
Treynor, W., Gonzalez, R., & Nolen-Hoeksema, S. (2003). Rumination reconsidered: A psychometric analysis. Cognitive Therapy and Research, 27(3), 247–259. https://doi.org/10.1023/A:1023910315561.
Turner, J. E. Jr., & Cole, D. A. (1994). Developmental differences in cognitive diatheses for child depression. Journal of Abnormal Child Psychology, 22(1), 15–31. https://doi.org/10.1007/BF02169254.
van Borkulo, C. D., & Millner, S. E. (2016). NetworkComparisonTest: Statistical comparison of two networks based on three invariance measures (Version 2.0.1). Retrieved from https://cran.r-project.org/web/packages/NetworkComparisonTest/index.html.
Van den Bergh, N., Marchetti, I., & Koster, E. H. W. (2021). Bridges over troubled waters: Mapping the interplay between anxiety, depression and stress through network analysis of the DASS-21. Cognitive Therapy and Research, 45(1), 46–60. https://doi.org/10.1007/s10608-020-10153-w.
Webb, C. A., Auerbach, R. P., & Derubeis, R. J. (2012). Processes of change in CBT of adolescent depression: Review and recommendations. Journal of Clinical Child and Adolescent Psychology, 41(5), 654–665. https://doi.org/10.1080/15374416.2012.704842.
Wilson, C. J., & Cottone, R. R. (2013). Using cognitive behavior therapy in clinical work with African American children and adolescents: A review of the literature. Journal of Multicultural Counseling and Development, 41(3), 130–143. https://doi.org/10.1002/j.2161-1912.2013.00032.x.
Ziegert, D. I., & Kistner, J. A. (2002). Response styles theory: Downward extension to children. Journal of Clinical Child and Adolescent Psychology, 31(3), 325–334. https://doi.org/10.1207/153744202760082586.
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Funding for the trial was provided by University of Louisville Office of Community Engagement. Igor Marchetti received funding from the Italian Research Projects of National Relevance – NextGeneration EU (grants 2022AKTAK8 and P20223PTH4).
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Pössel, P., Seely, H. & Marchetti, I. Similarities and Differences in the Architecture of Cognitive Vulnerability to Depressive Symptoms in Black and White American Adolescents: A Network Analysis Study. Res Child Adolesc Psychopathol (2024). https://doi.org/10.1007/s10802-024-01218-5
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DOI: https://doi.org/10.1007/s10802-024-01218-5