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Maternal depression and trajectories of child internalizing and externalizing problems: the roles of child decision making and working memory

Published online by Cambridge University Press:  20 December 2016

E. Flouri ,
A. Ruddy  and
E. Midouhas
E. Flouri*
Affiliation:
Department of Psychology and Human Development, UCL Institute of Education, University College London, London, UK
A. Ruddy
Affiliation:
Department of Psychology and Human Development, UCL Institute of Education, University College London, London, UK
E. Midouhas
Affiliation:
Department of Psychology and Human Development, UCL Institute of Education, University College London, London, UK
*
*Address for correspondence: E. Flouri, Department of Psychology and Human Development, UCL Institute of Education, University College London, 25 Woburn Square, London WC1H 0AA, UK. (Email: e.flouri@ucl.ac.uk)
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Abstract

Background

Maternal depression may affect the emotional/behavioural outcomes of children with normal neurocognitive functioning less severely than it does those without. To guide prevention and intervention efforts, research must specify which aspects of a child's cognitive functioning both moderate the effect of maternal depression and are amenable to change. Working memory and decision making may be amenable to change and are so far unexplored as moderators of this effect.

Method

Our sample was 17 160 Millennium Cohort Study children. We analysed trajectories of externalizing (conduct and hyperactivity) and internalizing (emotional and peer) problems, measured with the Strengths and Difficulties Questionnaire at the ages 3, 5, 7 and 11 years, using growth curve models. We characterized maternal depression, also time-varying at these ages, by a high score on the K6. Working memory was measured with the Cambridge Neuropsychological Test Automated Battery Spatial Working Memory Task, and decision making (risk taking and quality of decision making) with the Cambridge Gambling Task, both at age 11 years.

Results

Maternal depression predicted both the level and the growth of problems. Risk taking and poor-quality decision making were related positively to externalizing and non-significantly to internalizing problems. Poor working memory was related to both problem types. Neither decision making nor working memory explained the effect of maternal depression on child internalizing/externalizing problems. Importantly, risk taking amplified the effect of maternal depression on internalizing problems, and poor working memory that on internalizing and conduct problems.

Conclusions

Impaired decision making and working memory in children amplify the adverse effect of maternal depression on, particularly, internalizing problems.

Keywords

Decision makingemotional and behavioural problemsmaternal depressionMillennium Cohort Studyworking memory
Type
Original Articles
Information
Psychological Medicine , Volume 47 , Issue 6 , April 2017 , pp. 1138 - 1148
Copyright
Copyright © Cambridge University Press 2016 

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References

Arnsten, AF (2009). Stress signalling pathways that impair prefrontal cortex structure and function. Nature Reviews Neuroscience 10, 410–422.CrossRefGoogle ScholarPubMed
Baune, BT, Fuhr, M, Air, T, Hering, C (2014). Neuropsychological functioning in adolescents and young adults with major depressive disorder: a review. Psychiatry Research 218, 261–271.CrossRefGoogle Scholar
Beardslee, WR, Gladstone, TR, O'Connor, EE (2011). Transmission and prevention of mood disorders among children of affectively ill parents: a review. Journal of the American Academy of Child and Adolescent Psychiatry 50, 1098–1109.Google Scholar
Bechara, A, Damasio, H, Tranel, D, Anderson, SW (1998). Dissociation of working memory from decision making within the human prefrontal cortex. Journal of Neuroscience 18, 428–437.Google Scholar
Brewin, CR, Smart, L (2005). Working memory capacity and suppression of intrusive thoughts. Journal of Behaviour Therapy and Experimental Psychiatry 36, 61–68.Google Scholar
Castellanos, FX, Tannock, R (2002). Neuroscience of attention-deficit/hyper-activity disorder: the search for endophenotypes. Nature Reviews Neuroscience 3, 617–628.CrossRefGoogle Scholar
Cohen, G, Conway, MA (2008). Memory in the Real World, 3rd edn. Psychology Press: Hove.Google Scholar
Crone, E, van der Molen, M (2004). Developmental changes in real-life decision-making: performance on a gambling task previously shown to depend on the ventromedial prefrontal cortex. Developmental Neuropsychology 25, 251–279.CrossRefGoogle ScholarPubMed
Ernst, M, Grant, SJ, London, ED, Contoreggi, CS, Kimes, AS, Spurgeon, L (2003). Decision making in adolescents with behavior disorders and adults with substance abuse. American Journal of Psychiatry 160, 33–40.CrossRefGoogle ScholarPubMed
Fellows, LK, Farah, MJ (2005). Different underlying impairments in decision-making following ventromedial and dorsolateral frontal lobe damage in humans. Cerebral Cortex 15, 58–63.CrossRefGoogle ScholarPubMed
Galván, A, McGlennen, KM (2012). Daily stress increases risky decision-making in adolescents: a preliminary study. Developmental Psychobiology 54, 433–440.CrossRefGoogle ScholarPubMed
Gathercole, SE, Pickering, SJ, Ambridge, B, Wearing, H (2004). The structure of working memory from 4 to 15 years of age. Developmental Psychology 40, 177–190.CrossRefGoogle Scholar
Goodman, R (1997). The Strengths and Difficulties Questionnaire: a research note. Journal of Child Psychology and Psychiatry 38, 581–586.CrossRefGoogle ScholarPubMed
Goodman, SH, Rouse, MH, Connell, AM, Broth, MR, Hall, CM, Heyward, D (2011). Maternal depression and child psychopathology: a meta-analytic review. Clinical Child and Family Psychology Review 14, 1–27.Google Scholar
Gorka, SM, Liu, H, Klein, D, Daughters, SB, Shankman, SA (2015). Is risk-taking propensity a familial vulnerability factor for alcohol use? An examination in two independent samples. Journal of Psychiatric Research 68, 54–60.Google Scholar
Grenard, JL, Ames, SL, Wiers, RW, Thush, C, Sussman, S, Stacy, AW (2008). Working memory capacity moderates the predictive effects of drug-related associations on substance use. Psychology of Addictive Behaviors 22, 426–432.CrossRefGoogle ScholarPubMed
Hofmann, W, Schmeichel, BJ, Baddeley, AD (2012). Executive functions and self-regulation. Trends in Cognitive Sciences 16, 174–180.Google Scholar
Joormann, J, Levens, SM, Gotlib, IH (2011). Sticky thoughts depression and rumination are associated with difficulties manipulating emotional material in working memory. Psychological Science 22, 979–983.CrossRefGoogle ScholarPubMed
Kessler, RC, Barker, PR, Colpe, LJ, Epstein, JF, Gfroerer, JC, Hiripi, E, Howes, MJ, Normand, SL, Manderscheid, RW, Walters, EE, Zaslavsky, AM (2003). Screening for serious mental illness in the general population. Archives of General Psychiatry 60, 184–189.Google Scholar
Kiernan, KE, Mensah, FK (2009). Poverty, maternal depression, family status and children's cognitive and behavioural development in early childhood: a longitudinal study. Journal of Social Policy 38, 569–588.CrossRefGoogle Scholar
Klimes-Dougan, B, Ronsaville, D, Wiggs, EA, Martinez, PE (2006). Neuropsychological functioning in adolescent children of mothers with a history of bipolar or major depressive disorders. Biological Psychiatry 60, 957–965.Google Scholar
Klingberg, T, Forssberg, H, Westerberg, H (2002). Training of working memory in children with ADHD. Journal of Clinical and Experimental Neuropsychology 24, 781–791.CrossRefGoogle ScholarPubMed
Lewandowski, RE, Verdeli, H, Wickramaratne, P, Warner, V, Mancini, A, Weissman, M (2014). Predictors of positive outcomes in offspring of depressed parents and non-depressed parents across 20 years. Journal of Child and Family Studies 23, 800–811.CrossRefGoogle Scholar
Malmberg, LE, Flouri, E (2011). The comparison and interdependence of maternal and paternal influences on young children's behavior and resilience. Journal of Clinical Child and Adolescent Psychology 40, 434–444.Google Scholar
Manes, F, Sahakian, B, Clark, L, Rogers, R, Antoun, N, Aitken, M, Robbins, T (2002). Decision-making processes following damage to the prefrontal cortex. Brain 125, 624–639.CrossRefGoogle ScholarPubMed
Mannie, ZN, Williams, C, Browning, M, Cowen, PJ (2015). Decision making in young people at familial risk of depression. Psychological Medicine 45, 375–380.Google Scholar
Melby-Lervåg, M, Hulme, C (2013). Is working memory training effective? A meta-analytic review. Developmental Psychology 49, 270–291.CrossRefGoogle ScholarPubMed
McQuade, JD, Murray-Close, D, Shoulberg, EK, Hoza, B (2013). Working memory and social functioning in children. Journal of Experimental Child Psychology 115, 422–435.CrossRefGoogle ScholarPubMed
Morgan, JK, Shaw, DS, Forbes, EE (2014). Maternal depression and warmth during childhood predict age 20 neural response to reward. Journal of the American Academy of Child and Adolescent Psychiatry 53, 108–117.Google Scholar
Pargas, RCM, Brennan, PA, Hammen, C, Le Brocque, R (2010). Resilience to maternal depression in young adulthood. Developmental Psychology 46, 805–814.Google Scholar
Pickering, SJ (2001). The development of visuo-spatial working memory. Memory 9, 423–432.CrossRefGoogle ScholarPubMed
Rawal, A, Collishaw, S, Thapar, A, Rice, F (2013). The risks of playing it safe: a prospective longitudinal study of response to reward in the adolescent offspring of depressed parents. Psychological Medicine 43, 27–38.Google Scholar
Riglin, L, Collishaw, S, Shelton, KH, McManus, IC, Ng-Knight, T, Sellers, R, Thapar, AK, Fredrickson, N, Rice, F (2016). Higher cognitive ability buffers stress-related depressive symptoms in adolescent girls. Development and Psychopathology 28, 97–109.Google Scholar
Robbins, TW, James, M, Owen, AM, Sahakian, BJ, McInnes, L, Rabbitt, P (1994). Cambridge Neuropsychological Test Automated Battery (CANTAB): a factor analytic study of a large sample of normal elderly volunteers. Dementia 5, 266–281.Google ScholarPubMed
Rogers, RD, Owen, AM, Middleton, HC, Williams, EJ, Pickard, JD, Sahakian, BJ, Robbins, TW (1999). Choosing between small, likely rewards and large, unlikely rewards activates inferior and orbital prefrontal cortex. Journal of Neuroscience 15, 9029–9038.CrossRefGoogle Scholar
Rutter, M (2012). Resilience as a dynamic concept. Development and Psychopathology 24, 335–344.Google Scholar
Smith, AR, Chein, J, Steinberg, L (2013). Impact of socio-emotional context, brain development, and pubertal maturation on adolescent risk-taking. Hormones and Behavior 64, 323–332.CrossRefGoogle ScholarPubMed
Smith, DG, Xiao, L, Bechara, A (2012). Decision making in children and adolescents: impaired Iowa Gambling Task performance in early adolescence. Developmental Psychology 48, 1180–1187.CrossRefGoogle ScholarPubMed
Snijders, T, Bosker, R (1999). Multilevel Analysis: An Introduction to Basic and Applied Multilevel Analysis. Sage: Newbury Park, CA.Google Scholar
Steinberg, L (2005). Cognitive and affective development in adolescence. Trends in Cognitive Sciences 9, 69–74.CrossRefGoogle ScholarPubMed
Toplak, ME, Sorge, GB, Benoit, A, West, RF, Stanovich, KE (2010). Decision-making and cognitive abilities: a review of associations between Iowa Gambling Task performance, executive functions, and intelligence. Clinical Psychology Review 30, 562–581.Google Scholar
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