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Dimensions of adversity in association with adolescents’ depression symptoms: Distinct moderating roles of cognitive and autonomic function

Published online by Cambridge University Press:  17 December 2019

Rachel A. Vaughn-Coaxum Open the ORCID record for Rachel A. Vaughn-Coaxum [Opens in a new window] ,
Neha Dhawan ,
Margaret A. Sheridan ,
Mackenzie J. Hart  and
John R. Weisz
Rachel A. Vaughn-Coaxum*
Affiliation:
Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA Department of Psychology, Harvard University, Cambridge, MA, USA
Neha Dhawan
Affiliation:
Department of Psychology, Harvard University, Cambridge, MA, USA
Margaret A. Sheridan
Affiliation:
Department of Psychology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Mackenzie J. Hart
Affiliation:
Department of Psychology, University of South Carolina, Columbia, SC, USA
John R. Weisz
Affiliation:
Department of Psychology, Harvard University, Cambridge, MA, USA
*
Corresponding Author: Rachel A. Vaughn-Coaxum, 557 Bellefield Towers, 100 N. Bellefield Ave., Pittsburgh, PA15203, USA. E-mail: coauxmra@upmc.edu.
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Abstract

Exposure to adverse events is prevalent among youths and robustly associated with risk for depression, particularly during adolescence. The Dimensional Model of Adversity and Psychopathology (DMAP) distinguishes between adverse events that expose youths to deprivation versus threat, positing unique mechanisms of risk (cognitive functioning deficits for deprivation, and altered fear and emotion learning for threat) that may require different approaches to intervention. We examined whether deprivation and threat were distinctly associated with behavioral measures of cognitive processes and autonomic nervous system function in relation to depression symptom severity in a community sample of early adolescents (n = 117; mean age 12.73 years; 54.7% male). Consistent with DMAP, associations between threat and depression symptoms, and between economic deprivation and depression symptoms, were distinctly moderated by physiological and cognitive functions, respectively, at baseline but not follow-up. Under conditions of greater cognitive inhibition, less exposure to deprivation was associated with lower symptom severity. Under conditions of blunted resting-state autonomic response (electrodermal activity and respiratory sinus arrhythmia), greater exposure to threat was associated with higher symptom severity. Our findings support the view that understanding risk for youth depression requires parsing adversity: examining distinct roles played by deprivation and threat, and the associated cognitive and biological processes.

Keywords

childhood adversitydepressionthreatdeprivationpsychophysiology
Type
Regular Articles
Information
Development and Psychopathology , Volume 32 , Issue 3 , August 2020 , pp. 817 - 830
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Copyright
Copyright © Cambridge University Press 2019

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References

Appelhans, B. M., & Luecken, L. J. (2006). Heart rate variability as an index of regulated emotional responding. Review of General Psychology, 10, 229–240. doi:10.1037/1089-2680.10.3.229CrossRefGoogle Scholar
Beauchaine, T. P. (2015). Respiratory sinus arrhythmia: A transdiagnostic biomarker of emotion dysregulation and psychopathology. Current Opinion in Psychology, 3, 43–47. doi:10.1016/j.copsyc.2015.01.017CrossRefGoogle ScholarPubMed
Boucsein, W., Fowles, D. C., Grimnes, S., Ben-Shakhar, G., Roth, W. T., Dawson, M. E., & Filion, D. L. (2012). Publication recommendations for electrodermal measurements. Psychophysiology, 49, 1017–1034. doi:10.1111/j.1469-8986.2012.01384.xGoogle ScholarPubMed
Bradley, R. H., & Corwyn, R. F. (2002). Socioeconomic status and child development. Annual Review of Psychology, 53, 371–399. doi:10.1146/annurev.psych.53.100901.135233CrossRefGoogle ScholarPubMed
Brand, A. H., & Johnson, J. H. (1982). Note on reliability of the Life Events Checklist. Psychological Reports, 50, 1274–1274. doi:10.2466/pr0.1982.50.3c.1274CrossRefGoogle Scholar
Brand, S., & Kirov, R. (2011). Sleep and its importance in adolescence and in common adolescent somatic and psychiatric conditions. International Journal of General Medicine, 4, 425–442. doi:10.2147%2FIJGM.S11557CrossRefGoogle ScholarPubMed
Brooks-Gunn, J., Warren, M. P., Rosso, J., & Gargiulo, J. (1987). Validity of self-report measures of girls' pubertal status. Child Development, 58, 829–841.CrossRefGoogle ScholarPubMed
Busso, D. S., McLaughlin, K. A., & Sheridan, M. A. (2017). Dimensions of adversity, physiological reactivity, and externalizing psychopathology in adolescence: Deprivation and threat. Psychosomatic medicine, 7, 162–171. doi:10.1097/PSY.0000000000000369Google Scholar
Bylsma, L. M., Morris, B. H., & Rottenberg, J. (2008). A meta-analysis of emotional reactivity in major depressive disorder. Clinical Psychology Review, 28, 676–691 doi:10.1016/j.cpr.2007.10.001CrossRefGoogle ScholarPubMed
City of Boston (2017). Neighborhood Development. https://www.boston.gov/ departments/neighborhood-development/housing-and-urban-development-income-limits.Google Scholar
Clark, C., Caldwell, T., Power, C., & Stansfeld, S. A. (2010). Does the influence of childhood adversity on psychopathology persist across the lifecourse? A 45-year prospective epidemiologic study. Annals of epidemiology, 20, 385–394.CrossRefGoogle ScholarPubMed
Danese, A., Moffitt, T. E., Arseneault, L., Bleiberg, B. A., Dinardo, P. B., Gandelman, S. B., … Caspi, A. (2017). The origins of cognitive deficits in victimized children: Implications for neuroscientists and clinicians. American Journal of Psychiatry, 174, 349–361. doi:10.1176/appi.ajp.2016.16030333CrossRefGoogle ScholarPubMed
Daughters, S. B., Lejuez, C. W., Bornovalova, M. A., Kahler, C. W., Strong, D. R., & Brown, R. A. (2005). Distress tolerance as a predictor of early treatment dropout in a residential substance abuse treatment facility. Journal of Abnormal Psychology, 114, 729–734.CrossRefGoogle Scholar
De Los Reyes, A., & Kazdin, A. E. (2005). Informant discrepancies in the assessment of childhood psychopathology: A critical review, theoretical framework, and recommendations for further study. Psychological Bulletin, 131, 483–509.CrossRefGoogle ScholarPubMed
Dunn, E. C., Soare, T. W., Raffeld, M. R., Busso, D. S., Crawford, K. M., Davis, K. A., … Susser, E. S. (2018). What life course theoretical models best explain the relationship between exposure to childhood adversity and psychopathology symptoms: Recency, accumulation, or sensitive periods? Psychological Medicine, 48, 2562–2572. doi:10.1017/S0033291718000181CrossRefGoogle ScholarPubMed
Erath, S. A., Su, S., & Tu, K. M. (2018). Electrodermal reactivity moderates the prospective association between peer victimization and depressive symptoms in early adolescence. Journal of Clinical Child & Adolescent Psychology, 47, 992–1003, doi:10.1080/15374416.2016CrossRefGoogle ScholarPubMed
Evans, G. W., Li, D., & Whipple, S. S. (2013). Cumulative risk and child development. Psychological Bulletin, 139, 1342–1396. doi:10.1037/a0031808CrossRefGoogle ScholarPubMed
Farah, M. J. (2018). Socioeconomic status and the brain: Prospects for neuroscience-informed policy. Nature Reviews Neuroscience, 19, 428–438. doi:10.1038/s41583-018-0023-2CrossRefGoogle ScholarPubMed
Feng, C., Wang, H., Lu, N., Chen, T., He, H., Lu, Y., & Tu, X. M. (2014). Log-transformation and its implications for data analysis. Shanghai Archives of Psychiatry, 26, 105–9. doi:10.3969/j.issn.1002-0829.2014.02.009Google ScholarPubMed
Fields, A. (2013). Discovering statistics using IBM SPSS statistics. Sage.Google Scholar
Hamilton, J. L., & Alloy, L. B. (2016). Atypical reactivity of heart rate variability to stress and depression across development: Systematic review of the literature and directions for future research. Clinical Psychology Review, 50, 67–79. doi:10.1016/j.cpr.2016.09.003CrossRefGoogle ScholarPubMed
Hamlat, E. J., Snyder, H. R., Young, J. F., & Hankin, B. L. (2019). Pubertal timing as a transdiagnostic risk for psychopathology in youth. Clinical Psychological Science, 7, 411–429. doi:10.1177/2167702618810518CrossRefGoogle ScholarPubMed
Harkness, K. L., & Monroe, S. M. (2016). The assessment and measurement of adult life stress: Basic premises, operational principles, and design requirements. Journal of Abnormal Psychology, 125, 727–745. doi:10.1037/abn0000178CrossRefGoogle ScholarPubMed
Harris, K. M., King, R. B., & Gordon-Larsen, P. (2005). Healthy habits among adolescents: Sleep, exercise, diet and body image. In Moore, K. A., & Lippman, L. H. (Eds.), What Do Children Need to Flourish? Conceptualizing and measuring indicators of positive development (pp. 111–132). New York: Springer US.CrossRefGoogle Scholar
Hastings, T. L., & Kelley, M. L. (1997). Development and validation of the Screen for Adolescent Violence Exposure (SAVE). Journal of Abnormal Child Psychology, 25, 511–520.CrossRefGoogle Scholar
Hayes, A. F. (2017). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. New York: Guilford Press.Google Scholar
Heleniak, C., King, K. M., Monahan, K. C., & McLaughlin, K. A. (2018). Disruptions in emotion regulation as a mechanism linking community violence exposure to adolescent internalizing problems. Journal of Research on Adolescence, 28, 229–244. doi:10.1111/jora.12328CrossRefGoogle ScholarPubMed
Johnson, J. H., & McCutcheon, S. (1980). Assessing events in older children and adolescents: Preliminary findings with the lift events checklist. In Sarason, I. G. BrSpielberger, C. D. (Eds.), Stress and anxiety, 7, 111–125. Washington, DC: Hemisphere.Google Scholar
Kovacs, M. (2011). Children's Depression Inventory-2 (CDI-2). Toronto: Multi-Health Systems Inc.Google Scholar
Lambert, H. K., King, K. M., Monahan, K. C., & McLaughlin, K. A. (2017). Differential associations of threat and deprivation with emotion regulation and cognitive control in adolescence. Development and Psychopathology, 29, 929–940. doi:10.1017/S0954579416000584CrossRefGoogle ScholarPubMed
Machlin, L., Miller, A. B., Snyder, J., Mclaughlin, K. A., & Sheridan, M. A. (2019). Differential associations between deprivation and threat with cognitive control and fer conditioning in early childhood. Frontiers in Behavioral Neuroscience, 13, 1–14.CrossRefGoogle Scholar
Mash, E. and Wolfe, D. (2016). Abnormal child psychology. 6th ed.Boston: Cengage Learning.Google Scholar
McCrimmon, A. W., & Smith, A. D. (2013). Review of the Wechsler Abbreviated Scale of Intelligence, Second Edition (WASI-II). Journal of Psychoeducational Assessment, 31, 337–341. doi:10.1177/0734282912467756CrossRefGoogle Scholar
McLaughlin, K. A., Green, J. G., Gruber, M. J., Sampson, N. A., Zaslavsky, A. M., & Kessler, R. C. (2012). Childhood adversities and first onset of psychiatric disorders in a national sample of US adolescents. JAMA Psychiatry, 69, 1151–1160. doi:10.1001/archgenpsychiatry.2011.2277Google Scholar
McLaughlin, K. A., Rith-Najarian, L., Dirks, M. A., & Sheridan, M. A. (2015). Low vagal tone magnifies the association between psychosocial stress exposure and internalizing psychopathology in adolescents. Journal of Clinical Child & Adolescent Psychology, 44, 314–328. doi:10.1080/15374416.2013.843464CrossRefGoogle ScholarPubMed
McLaughlin, K. A., & Sheridan, M. A. (2016). Beyond cumulative risk: A dimensional approach to childhood adversity. Current Directions in Psychological Science, 25, 239–245.CrossRefGoogle ScholarPubMed
McLaughlin, K. A., Sheridan, M. A., Gold, A. L., Duys, A., Lambert, H. K., Peverill, M., … Pine, D. S. (2016). Maltreatment exposure, brain structure, and fear conditioning in children and adolescents. Neuropsychopharmacology, 41, 1956–1964. doi:10.1038/npp.2015.365CrossRefGoogle ScholarPubMed
McLaughlin, K. A., Sheridan, M. A., & Lambert, H. K. (2014). Childhood adversity and neural development: Deprivation and threat as distinct dimensions of early experience. Neuroscience & Biobehavioral Reviews, 47, 578–591.CrossRefGoogle ScholarPubMed
Merikangas, K., He, J., Burstein, M., Swanson, S. A., Avenevoli, S., Cui, L., & … Swendsen, J. (2010). Lifetime prevalence of mental disorders in U.S. adolescents: Results from the National Comorbidity Survey Replication-Adolescent Supplement (NCS-A). Journal Of The American Academy Of Child & Adolescent Psychiatry, 49, 980–989. doi:10.1016/j.jaac.2010.05.017CrossRefGoogle Scholar
Miller, A. B., Sheridan, M. A., Hanson, J. L., McLaughlin, K. A., Bates, J. E., Lansford, J. E., … Dodge, K. A. (2018). Dimensions of deprivation and threat, psychopathology, and potential mediators: A multi-year longitudinal analysis. Journal of Abnormal Psychology, 127, 160–170. doi:10.1037/abn0000331CrossRefGoogle ScholarPubMed
Nabkasorn, C., Miyai, N., Sootmongkol, A., Junprasert, S., Yamamoto, H., Arita, M., & Miyashita, K. (2006). Effects of physical exercise on depression, neuroendocrine stress hormones and physiological fitness in adolescent females with depressive symptoms. European Journal of Public Health, 16, 179–184.CrossRefGoogle ScholarPubMed
Nanni, V., Uher, R., & Danese, A. (2012). Childhood maltreatment predicts unfavorable course of illness and treatment outcome in depression: A meta-analysis. American Journal of Psychiatry, 169, 141–151. doi:10.1176/appi.ajp.2011.11020335CrossRefGoogle ScholarPubMed
Noble, K. G., McCandliss, B. D., & Farah, M. J. (2007). Socioeconomic gradients predict individual differences in neurocognitive abilities. Developmental Science, 10, 464–480. doi:10.1111/j.1467-7687.2007.00600.xCrossRefGoogle ScholarPubMed
Orpinas, P., & Frankowski, R. (2001). The Aggression Scale: A self-report measure of aggressive behavior for young adolescents. The Journal of Early Adolescence, 21, 50–67. doi:10.1177/0272431601021001003CrossRefGoogle Scholar
Petersen, A., Crockett, L., Richards, M., & Boxer, A. (1988). A self-report measure of pubertal status: Reliability, validity, and initial norms. Journal of Youth and Adolescence, 17, 117–133.CrossRefGoogle ScholarPubMed
Peverill, M., McLaughlin, K. A., Finn, A. S., & Sheridan, M. A. (2016). Working memory filtering continues to develop into late adolescence. Developmental Cognitive Neuroscience, 18, 78–88. doi:10.1016/j.dcn.2016.02.004CrossRefGoogle ScholarPubMed
Quon, E. C., & McGrath, J. J. (2014). Subjective socioeconomic status and adolescent health: A meta-analysis. Health Psychology, 33, 433–447. doi:10.1037/a0033716CrossRefGoogle ScholarPubMed
Runyan, D. K., Curtis, P. A., Hunter, W. M., Black, M. M., Kotch, J. B., Bangdiwala, S., … & Landsverk, J. (1998). LONGSCAN: A consortium for longitudinal studies of maltreatment and the life course of children. Aggression and Violent Behavior, 3, 275–285.CrossRefGoogle Scholar
Sheridan, M. A., & McLaughlin, K. A. (2014). Dimensions of early experience and neural development: deprivation and threat. Trends in Cognitive Sciences, 18, 580–585.CrossRefGoogle ScholarPubMed
Sheridan, M. A., McLaughlin, K. A., Winter, W., Fox, N., Zeanah, C., & Nelson, C. A. (2018). Early deprivation disruption of associative learning is a developmental pathway to depression and social problems. Nature Communications, 9, 1–8. doi:10.1038/s41467-018-04381-8CrossRefGoogle ScholarPubMed
Sheridan, M. A., Peverill, M., Finn, A. S., & McLaughlin, K. A. (2017). Dimensions of childhood adversity have distinct associations with neural systems underlying executive functioning. Development and Psychopathology, 29, 1777–1794.CrossRefGoogle ScholarPubMed
Silvers, J. A., Buhle, J. T., & Ochsner, K. N. (2014). The neuroscience of emotion regulation: Basic mechanisms and their role in development, aging, and psychopathology. In Ochsner, K. N. & Kosslyn, S. M. (Eds.), The Oxford handbook of cognitive neuroscience, Vol. 2. The cutting edges (pp. 52–78). New York, NY, US: Oxford University Press.Google Scholar
Sumner, J. A., Colich, N. L., Uddin, M., Armstrong, D., & McLaughlin, K. A. (2019). Early experiences of threat, but not deprivation, are associated with accelerated biological aging in children and adolescents. Biological Psychiatry, 85, 268–278.CrossRefGoogle Scholar
Tavitian, L. R., Ladouceur, C. D., Nahas, Z., Khater, B., Brent, D. A., & Maalouf, F. T. (2014). Neutral face distractors differentiate performance between depressed and healthy adolescents during an emotional working memory task. European Child & Adolescent Psychiatry, 23, 659–667. doi:10.1007/s00787-013-0492-9CrossRefGoogle ScholarPubMed
Teicher, M. H., & Samson, J. A. (2013). Childhood maltreatment and psychopathology: A case for ecophenotypic variants as clinically and neurobiologically distinct subtypes. American Journal of Psychiatry, 170, 1114–1133.CrossRefGoogle ScholarPubMed
Thapar, A., Collishaw, S., Pine, D. S., & Thapar, A. K. (2012). Depression in adolescence. Lancet, 379, 1056–67. doi:10.1016/S0140CrossRefGoogle ScholarPubMed
Thayer, J. F., Åhs, F., Fredrikson, M., Sollers Iii, J. J., & Wager, T. D. (2012). A meta-analysis of heart rate variability and neuroimaging studies: Implications for heart rate variability as a marker of stress and health. Neuroscience and Biobehavioral Reviews, 36, 747–756. doi:10.1016/j.neubiorev.2011.11.009CrossRefGoogle ScholarPubMed
U.S. Department of Health and Human Services, National Institutes of Health, National Institute of Mental Health. (2015). NIMH strategic plan for research (NIH Publication No. 02-2650). http://www.nimh.nih.gov/about/strategic-planning-reports/index.Google Scholar
Vasilev, C. A., Crowell, S. E., Beauchaine, T. P., Mead, H. K., & Gatzke-Kopp, L. M. (2009). Correspondence between physiological and self-report measures of emotion dysregulation: A longitudinal investigation of youth with and without psychopathology. Journal of Child Psychology and Psychiatry, 50, 1357–1364. doi:10.1111/j.1469-7610.2009.02172.xCrossRefGoogle ScholarPubMed
Vaughn-Coaxum, R. A., Wang, Y., Kiely, J., Weisz, J. R., & Dunn, E. C. (2018). Associations between trauma type, timing, and accumulation on current coping behaviors in adolescents: Results from a large, population-based sample. Journal of Youth and Adolescence, 47, 842–858. doi:10.1007/s10964-017-0693-5CrossRefGoogle ScholarPubMed
Wade, M., Madigan, S., Plamondon, A., Rodrigues, M., Browne, D., & Jenkins, J. M. (2017). Cumulative psychosocial risk, parental socialization, and child cognitive functioning: A longitudinal cascade model. Developmental Psychology, 54, 1038–1050. doi:10.1037/dev0000493CrossRefGoogle ScholarPubMed
Wagner, S., Müller, C., Helmreich, I., Huss, M., & Tadić, A. (2015). A meta-analysis of cognitive functions in children and adolescents with major depressive disorder. European Child & Adolescent Psychiatry, 24, 5–19. doi:10.1007/s00787-014-0559-2CrossRefGoogle ScholarPubMed
Wechsler, D. (2011). Wechsler Abbreviated Scale of Intelligence–Second Edition (WASI-II). San Antonio, TX: NCS PearsonGoogle Scholar
Westfall, P. H. & Young, S. S. (1993). Resampling-based multiple testing: Examples and methods for p-value adjustment. John Wiley & Sons.Google Scholar
Williams, D. P., Cash, C., Rankin, C., Bernardi, A., Koenig, J., & Thayer, J. F. (2015). Resting heart rate variability predicts self-reported difficulties in emotion regulation: A focus on different facets of emotion regulation. Frontiers in Psychology, 6, 1–8. doi:10.3389/fpsyg.2015.00261CrossRefGoogle ScholarPubMed
World Health Organization (2018). Depression. Geneva, Switzerland: Author. http://www.who.int/news-room/fact-sheets/detail/depressionGoogle Scholar
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