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Associations Between Personality and Depressive Symptoms in an Adolescent Clinical Population: Consideration of Personality Stability

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Abstract

The study used trait-state-occasion TSO models to explore longitudinal personality stability in young adolescents with the onset of depressive symptoms and to quantify time-invariant and time-varying personality components in predicting the course of depressive symptoms. A total of 326 young clinical adolescents were recruited from high schools, and only 290 adolescents (112 boys; 178 girls) were followed up for 4 time points. Personality measures were implemented twice each year with an interval of 6 months, providing four assessment waves (T1 to T4); depression measures were administered at the initial stage (T1) and the third wave (T3), respectively. The results showed that five domains of personality in adolescents with depressive symptoms were largely characterized by the stable trait factor (65%–81%). The average autoregressive effects across the four waves were significant for all Big Five personality domains except openness. Moreover, excluding time-varying variance, conscientiousness, extraversion and agreeableness were negatively associated with T1 depressive symptoms; however, only the latter two domains retained significant relationships in the second year of intervention. An elevated level of neuroticism was consistently associated with higher levels of depressive symptoms over interventions. Trait factors of extraversion, agreeableness and neuroticism were associated with depressive symptoms in early adolsecnets, providing some implications for clinical practitioners.

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Data Availability

The data are available on reasonable request from the corresponding author. The data are not publicly available due to their containing information that could compromise the privacy of research participants.

References

  1. McCrae RR, Costa PT Jr (2008) The five-factor theory of personality. In: John OP, Robins RW, Pervin LA (eds) Handbook of personality: theory and research, 3rd edn. Guilford Press, New York, pp 159–181

    Google Scholar 

  2. Clark LA, Watson D, Mineka S (1994) Temperament, personality, and the mood and anxiety disorders. J Abnorm Psychol 103(1):103–116. https://doi.org/10.1037/0021-843X.103.1.103

    Article  Google Scholar 

  3. Kotov R, Gamez W, Schmidt F, Watson D (2010) Linking “big” personality traits to anxiety, depressive, and substance use disorders: a meta-analysis. Psychol Bull 136(5):768–821. https://doi.org/10.1037/a00203

    Article  Google Scholar 

  4. Malouff JM, Thorsteinsson EB, Schutte NS (2005) The relationship between the five-factor model of personality and symptoms of clinical disorders: a meta-analysis. J Psychopathol Behav Assess 27(2):101–114. https://doi.org/10.1007/s10862-005-5384-y

    Article  Google Scholar 

  5. Hakulinen C, Elovainio M, Pulkki-Råback L, Virtanen M, Kivimäki M, Jokela M (2015) Personality and depressive symptoms: individual participant meta-analysis of 10 cohort studies. Depress Anxiety 32(7):461–470. https://doi.org/10.1002/da.22376

    Article  Google Scholar 

  6. Kessler RC, Amminger GP, Aguilar-Gaxiola S, Alonso J, Lee S, Ustün TB (2007) Age of onset of mental disorders: a review of recent literature. Curr Opin Psychiatry 20(4):359–364. https://doi.org/10.1097/YCO.0b013e32816ebc8c

    Article  Google Scholar 

  7. Klein DN, Kotov R, Bufferd SJ (2011) Personality and depression: explanatory models and review of the evidence. Annu Rev Clin Psychol 7:269–295. https://doi.org/10.1146/annurev-clinpsy-032210-104540

    Article  Google Scholar 

  8. Kenny DA, Zautra A (2001) Trait–state models for longitudinal data. In: Collins LM, Sayer AG (eds) New methods for the analysis of change. American Psychological Association, New York, pp 243–263

    Chapter  Google Scholar 

  9. Naragon-Gainey K, Gallagher MW, Brown TA (2013) Stable “trait” variance of temperament as a predictor of the temporal course of depression and social phobia. J Abnorm Psychol 122(3):611–623. https://doi.org/10.1037/a0032997

    Article  Google Scholar 

  10. Griens AMGF, Jonker K, Spinhoven P, Blom MBJ (2002) The influence of depressive state features on trait measurement. J Affect Disord 70(1):95–99. https://doi.org/10.1016/S0165-0327(00)00371-2

    Article  Google Scholar 

  11. Karsten J, Penninx BW, Riese H, Ormel J, Nolen WA, Hartman CA (2012) The state effect of depressive and anxiety disorders on big five personality traits. J Psychiatr Res 46(5):644–650. https://doi.org/10.1016/j.jpsychires.2012.01.024

    Article  Google Scholar 

  12. Roberts BW, Luo J, Briley DA, Chow PI, Su R, Hill PL (2017) A systematic review of personality trait change through intervention. Psychol Bull 143(2):117–141. https://doi.org/10.1037/bul0000088

    Article  Google Scholar 

  13. Fraley RC, Roberts BW (2005) Patterns of continuity: a dynamic model for conceptualizing the stability of individual differences in psychological constructs across the life course. Psychol Rev 112(1):60–74. https://doi.org/10.1037/0033-295X.112.1.60

    Article  Google Scholar 

  14. Roberts BW, DelVecchio WF (2000) The rank-order consistency of personality traits from childhood to old age: a quantitative review of longitudinal studies. Psychol Bull 126(1):3–25. https://doi.org/10.1037/0033-2909.126.1.3

    Article  Google Scholar 

  15. Cole DA, Martin NC, Steiger JH (2005) Empirical and conceptual problems with longitudinal trait-state models: introducing a trait-state-occasion model. Psychol Methods 10(1):3–20. https://doi.org/10.1037/1082-989X.10.1.3

    Article  Google Scholar 

  16. Conway CC, Hopwood CJ, Morey LC, Skodol AE (2018) Borderline personality disorder is equally trait-like and state-like over ten years in adult psychiatric patients. J Abnorm Psychol 127(6):590–601. https://doi.org/10.1037/abn0000364

    Article  Google Scholar 

  17. Wagner J, Lüdtke O, Robitzsch A (2019) Does personality become more stable with age? Disentangling state and trait effects for the big five across the life span using local structural equation modeling. J Pers Soc Psychol 116(4):666–680. https://doi.org/10.1037/pspp0000203

    Article  Google Scholar 

  18. Wu PC (2021) Is personality stable in adolescence? Disentangling time-invariant and time-varying factors of personality in a trait–state–occasion model. Int J Psychol 56(3):425–434. https://doi.org/10.1002/ijop.12723

    Article  Google Scholar 

  19. Kovaleva A, Beierlein C, Kemper CJ, Rammstedt B (2013) Psychometric properties of the BFI-K: a cross-validation study. Int J Educ Psychol Assess 13(1):134–150

    Google Scholar 

  20. John OP, Donahue EM, Kentle RL (1991) The Big Five Inventory-Versions 4a and 54. University of California, Berkeley, Institute of Personality and Social Research, Berkeley

    Google Scholar 

  21. Beck AT, Steer RA, Brown GK (1996) BDI-II, beck depression inventory: manual, 2nd edn. Harcour, Brace, & Company, Boston

    Google Scholar 

  22. Byrne BM, Stewart SM, Lee PWH (2004) Validating the Beck depression inventory II for Hong Kong community adolescents. Int J Test 4(3):199–216. https://doi.org/10.1207/s15327574ijt0403_1

    Article  Google Scholar 

  23. Wu PC (2010) Differential functioning of the Chinese version of Beck depression inventory-II in adolescent gender groups: use of a multiple-group mean and covariance structure model. Soc Indic Res 96(3):535–550. https://doi.org/10.1007/s11205-009-9491-0

    Article  Google Scholar 

  24. Wu PC (2010) Measurement invariance and latent mean differences of the Beck depression inventory II across gender groups. J Psychoeduc Assess 28(6):551–563. https://doi.org/10.1007/s11205-009-949-0

    Article  Google Scholar 

  25. Eid M (2000) A multitrait-multimethod model with minimal assumptions. Psychometrika 65(2):241–261. https://doi.org/10.1007/BF02294377

    Article  Google Scholar 

  26. Geiser C, Lockhart G (2012) A comparison of four approaches to account for method effects in latent state–trait analyses. Psychol Methods 17(2):255–283. https://doi.org/10.1037/a0026977

    Article  Google Scholar 

  27. Meade AW, Kroustalis CM (2006) Problems with item parceling for confirmatory factor analytic tests of measurement invariance. Organ Res Methods 9(3):369–403. https://doi.org/10.1177/1094428105283384

    Article  Google Scholar 

  28. Browne MW, Cudeck R (1993) Alternative ways of assessing model fit. In: Bollen KA, Long JS (eds) Testing structural equation models. Sage, Newbury Park, CA, pp 445–455

    Google Scholar 

  29. Hu L, Bentler PM (1998) Fit indices in covariance structure modeling: sensitivity to under parameterization model misspecification. Psychol Methods 3(4):424–453

    Article  Google Scholar 

  30. Hu LT, Bentler PM (1999) Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Modeling 6(1):1–55. https://doi.org/10.1080/10705519909540118

    Article  Google Scholar 

  31. Satorra A, Bentler PM (2010) Ensuring positiveness of the scaled chi-square test statistic. Psychometrika 75(2):243–248. https://doi.org/10.1007/s11336-009-9135-y

    Article  Google Scholar 

  32. Chen FF (2007) Sensitivity of goodness of fit indexes to lack of measurement invariance. Struct Equ Modeling 14(3):464–504. https://doi.org/10.1080/10705510701301834

    Article  Google Scholar 

  33. Bentler PM (2018) EQS 6.4 structural equations program manual. Multivariate Software, Encino, CA

    Google Scholar 

  34. Anusic I, Schimmack U (2016) Stability and change of personality traits, self-esteem, and well-being: Introducing the meta-analytic stability and change model of retest correlations. J Pers Soc Psychol 110(5):766–781. https://doi.org/10.1037/pspp0000066

    Article  Google Scholar 

  35. Roberts BW, Jackson JJ (2008) Sociogenomic personality psychology. J Pers 76(6):1523–1544

    Article  Google Scholar 

  36. Ormel J, Rosmalen J, Farmer A (2004) Neuroticism: a non-informative marker of vulnerability to psychopathology. Soc Psychiatry Psychiatr Epidemiol 39:906–912. https://doi.org/10.1007/s00127-004-0873-y

    Article  Google Scholar 

  37. Pereira-Morales AJ, Adan A, Forero DA (2019) Perceived stress as a mediator of the relationship between neuroticism and depression and anxiety symptoms. Curr Psychol 38(1):66–74. https://doi.org/10.1007/s12144-017-9587-7

    Article  Google Scholar 

  38. Otonari J, Nagano J, Morita M, Budhathoki S, Tashiro N, Toyomura K et al (2012) Neuroticism and extraversion personality traits, health behaviours, and subjective well-being: the Fukuoka Study (Japan). Qual Life Res 21(10):1847–1855. https://doi.org/10.1007/s11136-011-0098-y

    Article  Google Scholar 

  39. Olino TM, Klein DN, Dyson MW, Rose SA, Durbin CE (2010) Temperamental emotionality in preschool-aged children and depressive disorders in parents: associations in a large community sample. J Abnorm Psychol 119(3):468–478. https://doi.org/10.1037/a0020112

    Article  Google Scholar 

  40. Jensen-Campbell LA, Adams R, Perry DG, Workman KA, Furdella JQ, Egan SK (2002) Agreeableness, extraversion, and peer relations in early adolescence: winning friends and deflecting aggression. J Res Pers 36(3):224–251. https://doi.org/10.1006/jrpe.2002.2348

    Article  Google Scholar 

  41. Prinstein MJ, Dodge KA (eds) (2008) Duke series in child development and public policy. Understanding peer influence in children and adolescents. The Guilford Press, New York

    Google Scholar 

  42. Rubin KH, Bukowski WM, Parker JG (2006) Peer Interactions, Relationships, and Groups. In: Eisenberg N, Damon W, Lerner RM (eds) Handbook of child psychology: social, emotional, and personality development. Wiley, New York, pp 571–645

    Google Scholar 

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Funding

This study was funded by Ministry of Science and Technology, Taiwan.

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Authors and Affiliations

  1. Department of Educational Psychology and Counseling, National PingTung University, No. 4-18 Ming Shen Road, PingTung, Taiwan, ROC

    Pei-Chen Wu

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Correspondence to Pei-Chen Wu.

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The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of human research ethics committee at National Cheng Kung University (No. 104-067).

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Wu, PC. Associations Between Personality and Depressive Symptoms in an Adolescent Clinical Population: Consideration of Personality Stability. Child Psychiatry Hum Dev 54, 84–95 (2023). https://doi.org/10.1007/s10578-021-01227-1

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