Hostname: page-component-cd9895bd7-hc48f Total loading time: 0 Render date: 2024-12-24T17:19:59.242Z Has data issue: false hasContentIssue false
  • English
  • Français

Predictors of depressive symptom trajectories in a prospective follow-up of late adolescents

Published online by Cambridge University Press:  02 October 2019

William Coryell Open the ORCID record for William Coryell [Opens in a new window] ,
James Mills ,
Lilian Dindo  and
Chadi A. Calarge
William Coryell*
Affiliation:
Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, IA, USA
James Mills
Affiliation:
Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, IA, USA
Lilian Dindo
Affiliation:
Department of Psychiatry, Baylor University, Baylor College of Medicine, Houston, TX, USA
Chadi A. Calarge
Affiliation:
Department of Psychiatry, Baylor University, Baylor College of Medicine, Houston, TX, USA
*
Author for correspondence: William Coryell, E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Background

Group-based trajectory modeling holds promise for the study of prognostic indicators in the mood disorders because the courses that the individuals with these disorders follow are so highly variable. However, trajectory analyses of major depressive disorder have so far not included some of the more robust predictors of mood disorder outcome, nor have they described interactions between these predictors.

Methods

A group of 186 individuals aged 15–20 years with past or current depressive symptoms, who had recently begun taking a serotonin reuptake inhibitors antidepressant, underwent extensive baseline evaluations and were then followed for up to 2 years. Trajectory analyses used weekly ratings of depressive symptoms and the resulting groups were compared by the risk factors of sex, psychiatric comorbidity, negative emotionality, and childhood adversity.

Results

A three-group solution provided the best statistical fit to the 2-year symptom trajectory. Negative emotionality and childhood adversity, though correlated, independently predicted membership in higher-morbidity groups. Female sex and comorbidity with generalized anxiety disorder (GAD) were also significantly more likely in the trajectory groups with higher symptom levels. However, the presence of GAD, rather than female sex, was the most important determinant of group membership. Negative emotionality was predictive of group membership only among women.

Conclusions

Trajectory analyses indicated that week-to-week variations in depressive symptoms across individuals could best be condensed into low, remitting and persistent symptom patterns. Female sex, anxiety symptoms, negative emotionality and childhood adversity were each independently associated with trajectories of higher morbidity but negative emotionality may be prognostically important only among women.

Keywords

Adolescentschildhood adversitydepressive symptomsfollow-uptrajectory
Type
Original Articles
Information
Psychological Medicine , Volume 50 , Issue 13 , October 2020 , pp. 2283 - 2288
Check for updates
Copyright
Copyright © Cambridge University Press 2019

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

Akaike, H (1974) A new look at the statistical model identification. IEEE Transactions on Automatic Control 19, 716–723.CrossRefGoogle Scholar
Barnhofer, T, Brennan, K, Crane, C, Duggan, D and Williams, JMG (2014) A comparison of vulnerability factors in patients with persistent and remitting lifetime symptom course of depression. Journal of Affective Disorders 152, 155–161.CrossRefGoogle Scholar
Bremner, JD, Bolus, R and Mayer, EA (2007) Psychometric properties of the early trauma inventory–self report. The Journal of Nervous and Mental Disease 195, 211.CrossRefGoogle Scholar
Brown, TA, Chorpita, BF and Barlow, DH (1998) Structural relationships among dimensions of the DSM-IV anxiety and mood disorders and dimensions of negative affect, positive affect, and autonomic arousal. Journal of Abnormal Psychology 107, 179.CrossRefGoogle Scholar
Calarge, CA, Butcher, BD, Burns, TL, Coryell, WH, Schlechte, JA and Zemel, BS (2014) Major depressive disorder and bone mass in adolescents and young adults. Journal of Bone and Mineral Research 29, 2230–2237.CrossRefGoogle Scholar
Calarge, CA, Mills, JA, Janz, KF, Burns, TL, Schlechte, JA, Coryell, WH and Zemel, BS (2017) The effect of depression, generalized anxiety, and selective serotonin reuptake inhibitors on change in bone metabolism in adolescents and emerging adults. Journal of Bone and Mineral Research 32, 2367–2374.CrossRefGoogle Scholar
Church, AT (1994) Relating the Tellegen and five-factor models of personality structure. Journal of Personality and Social Psychology 67, 898.CrossRefGoogle Scholar
Coryell, W, Solomon, DA, Fiedorowicz, JG, Endicott, J, Schettler, PJ and Judd, LL (2009) Anxiety and outcome in bipolar disorder. American Journal of Psychiatry 166, 1238–1243.CrossRefGoogle Scholar
Coryell, W, Fiedorowicz, JG, Solomon, D, Leon, AC, Rice, JP and Keller, MB (2012) Effects of anxiety on the long-term course of depressive disorders. The British Journal of Psychiatry 200, 210–215.CrossRefGoogle Scholar
Coryell, WH, Langbehn, DR, Norris, AW, Yao, J-R, Dindo, LN and Calarge, CA (2017) Polyunsaturated fatty acid composition and childhood adversity: independent correlates of depressive symptom persistence. Psychiatry Research 256, 305–311.CrossRefGoogle Scholar
Goodwin, RD and Gotlib, IH (2004) Gender differences in depression: the role of personality factors. Psychiatry Research 126, 135–142.CrossRefGoogle Scholar
Hengartner, MP, Cohen, LJ, Rodgers, S, Müller, M, Roessler, W and Ajdacic-Gross, V (2015) Association between childhood maltreatment and normal adult personality traits: exploration of an understudied field. Journal of Personality Disorders 29, 1–14.CrossRefGoogle Scholar
Jones, BL, Nagin, DS and Roeder, K (2001) A SAS procedure based on mixture models for estimating developmental trajectories. Sociological Methods & Research 29, 374–393.CrossRefGoogle Scholar
Keller, MB, Lavori, PW, Friedman, B, Nielsen, E, Endicott, J, Mcdonald-Scott, P and Andreasen, NC (1987) The longitudinal interval follow-up evaluation: a comprehensive method for assessing outcome in prospective longitudinal studies. Archives of General Psychiatry 44, 540–548.CrossRefGoogle Scholar
Kendler, KS and Gardner, CO (2014) Sex differences in the pathways to major depression: a study of opposite-sex twin pairs. American Journal of Psychiatry 171, 426–435.CrossRefGoogle Scholar
Kendler, KS, Neale, MC, Kessler, RC, Heath, AC and Eaves, LJ (1992) Major depression and generalized anxiety disorder: same genes, (partly) different environments? Archives of General Psychiatry 49, 716–722.CrossRefGoogle Scholar
Kessler, RC, Berglund, PA, Dewit, DJ, Bedirhan Üstün, T, Wang, PS and Wïttchen, HU (2002) Distinguishing generalized anxiety disorder from major depression: prevalence and impairment from current pure and comorbid disorders in the US and Ontario. International Journal of Methods in Psychiatric Research 11, 99–111.CrossRefGoogle Scholar
Kessler, RC, Berglund, P, Demler, O, Jin, R, Koretz, D, Merikangas, KR, Rush, AJ, Walters, EE and Wang, PS (2003) The epidemiology of major depressive disorder: results from the national comorbidity survey replication (NCS-R). JAMA 289, 3095–3105.CrossRefGoogle Scholar
Li, M, D'arcy, C and Meng, X (2016) Maltreatment in childhood substantially increases the risk of adult depression and anxiety in prospective cohort studies: systematic review, meta-analysis, and proportional attributable fractions. Psychological Medicine 46, 717–730.CrossRefGoogle Scholar
McCrae, RR and Costa, PT (1987) Validation of the five-factor model of personality across instruments and observers. Journal of Personality and Social Psychology 52, 81.CrossRefGoogle Scholar
Moffitt, TE, Caspi, A, Harrington, H, Milne, BJ, Melchior, M, Goldberg, D and Poulton, R (2007) Generalized anxiety disorder and depression: childhood risk factors in a birth cohort followed to age 32. Psychological Medicine 37, 441–452.CrossRefGoogle Scholar
Nagin, DS and Odgers, CL (2010) Group-based trajectory modeling in clinical research. Annual Review of Clinical Psychology 6, 109–138.CrossRefGoogle Scholar
Nelson, J, Klumparendt, A, Doebler, P and Ehring, T (2017) Childhood maltreatment and characteristics of adult depression: meta-analysis. The British Journal of Psychiatry 210, 96–104.CrossRefGoogle Scholar
Newman, MG, Llera, SJ, Erickson, TM, Przeworski, A and Castonguay, LG (2013) Worry and generalized anxiety disorder: a review and theoretical synthesis of evidence on nature, etiology, mechanisms, and treatment. Annual Review of Clinical Psychology 9, 275–297.CrossRefGoogle Scholar
Patrick, CJ, Curtin, JJ and Tellegen, A (2002) Development and validation of a brief form of the multidimensional personality questionnaire. Psychological Assessment 14, 150.CrossRefGoogle Scholar
Shaffer, D, Fisher, P, Lucas, CP, Dulcan, MK and Schwab-Stone, ME (2000) NIMH diagnostic interview schedule for children version IV (NIMH DISC-IV): description, differences from previous versions, and reliability of some common diagnoses. Journal of the American Academy of Child & Adolescent Psychiatry 39, 28–38.CrossRefGoogle Scholar
Shore, L, Toumbourou, JW, Lewis, AJ and Kremer, P (2018) Longitudinal trajectories of child and adolescent depressive symptoms and their predictors – a systematic review and meta-analysis. Child and Adolescent Mental Health 23, 107–120.CrossRefGoogle Scholar
Üstün, TB, Ayuso-Mateos, JL, Chatterji, S, Mathers, C and Murray, CJ (2004) Global burden of depressive disorders in the year 2000. The British Journal of Psychiatry 184, 386–392.CrossRefGoogle Scholar