European Child & Adolescent Psychiatry

, Volume 28, Issue 2, pp 223–236 | Cite as

Psychosocial intervention in at-risk adolescents: using event-related potentials to assess changes in decision making and feedback processing

  • H. L. Pincham
  • D. Bryce
  • P. Fonagy
  • R. M. Pasco FearonEmail author
Original Contribution


Decision making and feedback processing are two important cognitive processes that are impacted by social context, particularly during adolescence. The current study examined whether a psychosocial intervention could improve psychological wellbeing in at-risk adolescent boys, thereby improving their decision making and feedback processing skills. Two groups of at-risk adolescents were compared: those who were relatively new to a psychosocial intervention, and those who had engaged over a longer time period. Electroencephalography was recorded while the young people participated in a modified version of the Taylor Aggression Paradigm. The late positive potential (LPP) was measured during the decision phase of the task (where participants selected punishments for their opponents). The feedback-related negativity (FRN) and P3 components were measured during the task’s outcome phase (where participants received ‘win’ or ‘lose’ feedback). Adolescents who were new to the intervention (the minimal-intervention group) were harsher in their punishment selections than those who had been engaged in the program for much longer. The minimal-intervention group also showed an enhanced LPP during the decision phase of the task, which may be indicative of immature decision making in that group. Analysis of the FRN and P3 amplitudes revealed that the minimal-intervention group was physiologically hypo-sensitive to feedback, compared with the extended-intervention group. Overall, these findings suggest that long-term community-based psychosocial intervention programs are beneficial for at-risk adolescents, and that event-related potentials can be employed as biomarkers of therapeutic change. However, because participants were not randomly allocated to treatment groups, alternative explanations cannot be excluded until further randomized controlled trials are undertaken.


Adolescent Event-related potential Intervention Psychosocial FRN LPP 



We would like to thank all of the participants, schools and key workers who took part in this study. We would like to especially thank the following individuals for their assistance with data collection and/or preparing the data for analysis: Charlotte Bargus, Elizabeth Harding, Danae Kokorikou, Jodie Walman and Anna Zonderman. This work was supported by the Waterloo Foundation (Grant code 564/709) and Kids Company, London.

Compliance with ethical standards

Ethical standards

Ethical approval for the study was provided by the Research Ethics Committee at University College London (ID: 3064/001), and debriefing occurred at the end of the study. This study has been performed in accordance with 1964 Declaration of Helsinki, and its later amendments.

Conflict of interest

This study was supported by the Waterloo Foundation and Kids Company. The Waterloo Foundation had no role in study design, data collection and analysis, the decision to publish, or preparation of the manuscript. Kids Company supported the recruitment of participants from their services, and provided lab space, equipment and top-up funding. Kids Company had no role in study design, data collection and analysis, the decision to publish, or preparation of the manuscript. Professor Peter Fonagy is chief executive of Anna Freud National Centre for Children and Families (a child mental health charity).


  1. 1.
    Moffitt TE, Caspi A, Rutter M, Silva PA (2001) Sex differences in antisocial behaviour: conduct disorder, delinquency, and violence in the Dunedin longitudinal study. Cambridge University Press, CambridgeGoogle Scholar
  2. 2.
    Scott S, Knapp M, Henderson J, Maughan B (2001) Financial cost of social exclusion: follow up study of antisocial children into adulthood. BMJ 323(7306):191–194Google Scholar
  3. 3.
    Pincham HL, Wu C, Killikelly C, Vuillier L, Fearon RMP (2015) Social provocation modulates decision making and feedback processing: examining the trajectory of development in adolescent participants. Dev Cogn Neurosci 15:58–66Google Scholar
  4. 4.
    Taylor SP (1967) Aggressive behavior and physiological arousal as a function of provocation and the tendency to inhibit aggression. J Pers 35(2):297–310Google Scholar
  5. 5.
    Cecil CAM, Viding E, Barker ED, Guiney J, McCrory EJ (2014) Double disadvantage: The influence of childhood maltreatment and community violence exposure on adolescent mental health. J Child Psychol Psychiatry 55(7):839–848Google Scholar
  6. 6.
    Pincham HL, Bryce D, Kokorikou D, Fonagy P, Fearon RMP (2016) Psychosocial intervention is associated with altered emotion processing: an event-related potential study in at-risk adolescents. PloS One 11(1):e0147357Google Scholar
  7. 7.
    McDermott JM, Troller-Renfree S, Vanderwert R, Nelson CA, Zeanah CH, Fox NA (2013) Psychosocial deprivation, executive functions, and the emergence of socio-emotional behavior problems. Front Hum Neurosci 7:167Google Scholar
  8. 8.
    McDermott JM, Westerlund A, Zeanah CH, Nelson CA, Fox NA (2012) Early adversity and neural correlates of executive function: implications for academic adjustment. Dev Cogn Neurosci 2:S59-S66Google Scholar
  9. 9.
    Pincham HL, Bryce D, Fearon RMP (2015) The neural correlates of emotion processing in juvenile offenders. Dev Sci 18(6):994–1005Google Scholar
  10. 10.
    Alexander JF, Robbins MS, Sexton TL (2000) Family-based interventions with older, at-risk youth: from promise to proof to practice. J Prim Prev 21(2):185–205Google Scholar
  11. 11.
    Cho H, Hallfors DD, Sánchez V (2005) Evaluation of a high school peer group intervention for at-risk youth. J Abnorm Child Psychol 33(3):363–374Google Scholar
  12. 12.
    Dishion TJ, Andrews DW (1995) Preventing escalation in problem behaviors with high-risk young adolescents: immediate and 1-year outcomes. J Consult Clin Psychol 63(4):538Google Scholar
  13. 13.
    Eggert LL, Thompson EA, Herting JR, Nicholas LJ (1995) Reducing suicide potential among high-risk youth: tests of a school-based prevention program. Suicide Life Threatening Behav 25(2):276–296Google Scholar
  14. 14.
    Keating LM, Tomishima MA, Foster S, Alessandri M (2002) The effects of a mentoring program on at-risk youth. Adolescence 37(148):717–734Google Scholar
  15. 15.
    Moody KA, Childs JC, Sepples SB (2002) Intervening with at-risk youth: evaluation of the youth empowerment and support program. Pediatr Nurs 29(4):263–270Google Scholar
  16. 16.
    Lewis MD, Granic I, Lamm C, Zelazo PD, Stieben J, Todd RM, Moadab I, Pepler D (2008) Changes in the neural bases of emotion regulation associated with clinical improvement in children with behavior problems. Dev Psychopathol 20(03):913–939Google Scholar
  17. 17.
    Roffman JL, Marci CD, Glick DM, Dougherty DD, Rauch SL (2005) Neuroimaging and the functional neuroanatomy of psychotherapy. Psychol Med 35(10):1385–1398Google Scholar
  18. 18.
    Woltering S, Granic I, Lamm C, Lewis MD (2011) Neural changes associated with treatment outcome in children with externalizing problems. Biol Psychiat 70(9):873–879Google Scholar
  19. 19.
    Shaw DS, Shelleby EC (2014) Early-starting conduct problems: intersection of conduct problems and poverty. Annu Rev Clin Psychol 10:503–528Google Scholar
  20. 20.
    Shonkoff JP, Garner AS (2012) Committee on Psychosocial Aspects of Child and Family Health; Committee on Early Childhood, Adoption, and Dependent Care; Section on Developmental and Behavioral Pediatrics. The lifelong effects of early childhood adversity and toxic stress. Pediatrics 129(1):e232–e246Google Scholar
  21. 21.
    Lane SD, Cherek DR (2001) Risk taking by adolescents with maladaptive behavior histories. Exp Clin Psychopharmacol 9(1):74Google Scholar
  22. 22.
    Fonseca A, Yule W (1995) Personality and antisocial behavior in children and adolescents: an enquiry into Eysenck’s and Gray’s theories. J Abnorm Child Psychol 23(6):767–781Google Scholar
  23. 23.
    Matthys W, van Goozen SH, Vries HD, Cohen-Kettenis PT, Engeland Hv (1998) The dominance of behavioural activation over behavioural inhibition in conduct disordered boys with or without attention deficit hyperactivity disorder. J Child Psychol Psychiatry 39(5):643–651Google Scholar
  24. 24.
    Bjork JM, Chen G, Smith AR, Hommer DW (2010) Incentive-elicited mesolimbic activation and externalizing symptomatology in adolescents. J Child Psychol Psychiatry 51(7):827–837Google Scholar
  25. 25.
    Finger EC, Marsh AA, Mitchell DG, Reid ME, Sims C, Budhani S, Kosson DS, Chen G, Towbin KE, Leibenluft E (2008) Abnormal ventromedial prefrontal cortex function in children with psychopathic traits during reversal learning. Arch Gen Psychiatry 65(5):586–594Google Scholar
  26. 26.
    White SF, Brislin S, Sinclair S, Fowler KA, Pope K, Blair RJR (2013) The relationship between large cavum septum pellucidum and antisocial behavior, callous–unemotional traits and psychopathy in adolescents. J Child Psychol Psychiatry 54(5):575–581Google Scholar
  27. 27.
    Gatzke-Kopp LM, Beauchaine TP, Shannon KE, Chipman J, Fleming AP, Crowell SE, Liang O, Johnson LC, Aylward E (2009) Neurological correlates of reward responding in adolescents with and without externalizing behavior disorders. J Abnorm Psychol 118(1):203–213Google Scholar
  28. 28.
    Finger EC, Marsh AA, Blair KS, Reid ME, Sims C, Ng P, Pine DS, Blair RJR (2011) Disrupted reinforcement signaling in the orbitofrontal cortex and caudate in youths with conduct disorder or oppositional defiant disorder and a high level of psychopathic traits. Am J Psychiatry 168(2):152–162Google Scholar
  29. 29.
    Rubia K, Smith A, Halari R, Matsukura F, Mohammad M, Taylor E, Brammer M (2009) Disorder-specific dissociation of orbitofrontal dysfunction in boys with pure conduct disorder during reward and ventrolateral prefrontal dysfunction in boys with pure ADHD during sustained attention. Am J Psychiatry 166(1):83–94Google Scholar
  30. 30.
    Crowley MJ, Wu J, Crutcher C, Bailey CA, Lejuez C, Mayes LC (2009) Risk-taking and the feedback negativity response to loss among at-risk adolescents. Dev Neurosci 31(1–2):137–148Google Scholar
  31. 31.
    Segalowitz SJ, Santesso DL, Willoughby T, Reker DL, Campbell K, Chalmers H, Rose-Krasnor L (2012) Adolescent peer interaction and trait surgency weaken medial prefrontal cortex responses to failure. Soc Cogn Affect Neurosci 7(1):115–124Google Scholar
  32. 32.
    Van Leijenhorst L, Zanolie K, Van Meel CS, Westenberg PM, Rombouts SA, Crone EA (2009) What motivates the adolescent? Brain regions mediating reward sensitivity across adolescence. Cereb Cortex 20(1):61–69Google Scholar
  33. 33.
    Krämer UM, Büttner S, Roth G, Münte TF (2008) Trait aggressiveness modulates neurophysiological correlates of laboratory-induced reactive aggression in humans. J Cogn Neurosci 20(8):1464–1477Google Scholar
  34. 34.
    Bauer LO, Hesselbrock VM (1999) P300 decrements in teenagers with conduct problems: implications for substance abuse risk and brain development. Biol Psychiatry 46(2):263–272Google Scholar
  35. 35.
    Bauer LO, Hesselbrock VM (2003) Brain maturation and subtypes of conduct disorder: interactive effects on P300 amplitude and topography in male adolescents. J Am Acad Child Adolesc Psychiatry 42(1):106–115Google Scholar
  36. 36.
    Gao Y, Raine A, Venables PH, Mednick SA (2013) The association between P3 amplitude at age 11 and criminal offending at age 23. J Clin Child Adolesc Psychol 42(1):120–130Google Scholar
  37. 37.
    Hicks BM, Bernat E, Malone SM, Iacono WG, Patrick CJ, Krueger RF, McGue M (2007) Genes mediate the association between P3 amplitude and externalizing disorders. Psychophysiology 44(1):98–105Google Scholar
  38. 38.
    Iacono WG, Carlson SR, Malone SM, McGue M (2002) P3 event-related potential amplitude and the risk for disinhibitory disorders in adolescent boys. Arch Gen Psychiatry 59(8):750–757Google Scholar
  39. 39.
    Bellebaum C, Polezzi D, Daum I (2010) It is less than you expected: the feedback-related negativity reflects violations of reward magnitude expectations. Neuropsychologia 48(11):3343–3350Google Scholar
  40. 40.
    Hajcak G, Holroyd CB, Moser JS, Simons RF (2005) Brain potentials associated with expected and unexpected good and bad outcomes. Psychophysiology 42(2):161–170Google Scholar
  41. 41.
    Hajcak G, Moser JS, Holroyd CB, Simons RF (2007) It’s worse than you thought: the feedback negativity and violations of reward prediction in gambling tasks. Psychophysiology 44(6):905–912Google Scholar
  42. 42.
    Holroyd CB, Hajcak G, Larsen JT (2006) The good, the bad and the neutral: electrophysiological responses to feedback stimuli. Brain Res 1105(1):93–101Google Scholar
  43. 43.
    Wu Y, Zhou X (2009) The P300 and reward valence, magnitude, and expectancy in outcome evaluation. Brain Res 1286:114–122Google Scholar
  44. 44.
    Gaskell C (2008) Kids Company help with the whole problem. Kids Company Research and Evaluation Programme, LondonGoogle Scholar
  45. 45.
    Jovchelovitch S, Concha N (2013) Kids Company: a diagnosis of the organisation and its interventions: executive summary. London School of Economics, London, UKGoogle Scholar
  46. 46.
    Capaldi DM, Rothbart MK (1992) Development and validation of an early adolescent temperament measure. J Early Adolesc 12(2):153–173Google Scholar
  47. 47.
    Goodman R (1997) The Strengths and Difficulties Questionnaire: a research note. J Child Psychol Psychiatry 38(5):581–586Google Scholar
  48. 48.
    Essau CA, Sasagawa S, Frick PJ (2006) Callous–unemotional traits in a community sample of adolescents. Assessment 13(4):454–469Google Scholar
  49. 49.
    Nolan H, Whelan R, Reilly R (2010) FASTER: fully automated statistical thresholding for EEG artifact rejection. J Neurosci Methods 192(1):152–162Google Scholar
  50. 50.
    Wiswede D, Taubner S, Münte TF, Roth G, Strüber D, Wahl K, Krämer UM (2011) Neurophysiological correlates of laboratory-induced aggression in young men with and without a history of violence. PLoS One 6(7):e22599Google Scholar
  51. 51.
    Cuthbert BN, Schupp HT, Bradley MM, Birbaumer N, Lang PJ (2000) Brain potentials in affective picture processing: covariation with autonomic arousal and affective report. Biol Psychol 52(2):95–111Google Scholar
  52. 52.
    Yeung N, Sanfey AG (2004) Independent coding of reward magnitude and valence in the human brain. J Neurosci 24(28):6258–6264Google Scholar
  53. 53.
    Zottoli TM, Grose-Fifer J (2012) The feedback-related negativity (FRN) in adolescents. Psychophysiology 49(3):413–420Google Scholar
  54. 54.
    Massar S, Rossi V, Schutter D, Kenemans J (2012) Baseline EEG theta/beta ratio and punishment sensitivity as biomarkers for feedback-related negativity (FRN) and risk-taking. Clin Neurophysiol 123(10):1958–1965Google Scholar
  55. 55.
    Potts GF, Martin LE, Burton P, Montague PR (2006) When things are better or worse than expected: the medial frontal cortex and the allocation of processing resources. J Cogn Neurosci 18(7):1112–1119Google Scholar
  56. 56.
    Smillie LD, Cooper AJ, Pickering AD (2011) Individual differences in reward–prediction–error: extraversion and feedback-related negativity. Soc Cogn Affect Neurosci 6(5):646–652Google Scholar
  57. 57.
    Pincham HL, Szűcs D (2012) Target Cueing Provides Support for Target- and Resource-Based Models of the Attentional Blink. PLoS ONE 7(5): e37596. Google Scholar
  58. 58.
    Cui J-f, Chen Y-h, Wang Y, Shum DH, Chan RC (2013) Neural correlates of uncertain decision making: ERP evidence from the Iowa Gambling task. Front Hum Neurosci 7:776Google Scholar
  59. 59.
    Gu R, Wu T, Jiang Y, Luo YJ (2011) Woulda, coulda, shoulda: the evaluation and the impact of the alternative outcome. Psychophysiology 48(10):1354–1360Google Scholar
  60. 60.
    Martin LE, Potts GF (2009) Impulsivity in decision-making: an event-related potential investigation. Pers Individ Differ 46(3):303–308Google Scholar
  61. 61.
    Connor DF, Carlson GA, Chang KD, Daniolos PT, Ferziger R, Findling RL, Hutchinson JG, Malone RP, Halperin JM, Plattner B (2006) Juvenile maladaptive aggression: a review of prevention, treatment, and service configuration and a proposed research agenda. J Clin Psychiatry 67(5):808–820Google Scholar
  62. 62.
    Bradley MM, Hamby S, Löw A, Lang PJ (2007) Brain potentials in perception: picture complexity and emotional arousal. Psychophysiology 44(3):364–373Google Scholar
  63. 63.
    Codispoti M, Ferrari V, Bradley MM (2007) Repetition and event-related potentials: distinguishing early and late processes in affective picture perception. J Cogn Neurosci 19(4):577–586Google Scholar
  64. 64.
    Naumann E, Bartussek D, Diedrich O, Laufer ME (1992) Assessing cognitive and affective information processing functions of the brain by means of the late positive complex of the event-related potential. J Psychophysiol 6(4):285–298Google Scholar
  65. 65.
    Gehring WJ, Willoughby AR (2002) The medial frontal cortex and the rapid processing of monetary gains and losses. Science 295(5563):2279–2282. Google Scholar
  66. 66.
    Goyer JP, Woldorff MG, Huettel SA (2008) Rapid electrophysiological brain responses are influenced by both valence and magnitude of monetary rewards. J Cogn Neurosci 20(11):2058–2069Google Scholar
  67. 67.
    Hajcak G, Moser JS, Holroyd CB, Simons RF (2006) The feedback-related negativity reflects the binary evaluation of good versus bad outcomes. Biol Psychol 71(2):148–154. Google Scholar
  68. 68.
    Steinberg L (2008) A social neuroscience perspective on adolescent risk-taking. Dev Rev 28(1):78–106Google Scholar
  69. 69.
    Larson MJ, Steffen PR, Primosch M (2013) The impact of a brief mindfulness meditation intervention on cognitive control and error-related performance monitoring. Front Hum Neurosci 7:308Google Scholar
  70. 70.
    Schoenberg PL, Hepark S, Kan CC, Barendregt HP, Buitelaar JK, Speckens AE (2014) Effects of mindfulness-based cognitive therapy on neurophysiological correlates of performance monitoring in adult attention-deficit/hyperactivity disorder. Clin Neurophysiol 125(7):1407–1416Google Scholar
  71. 71.
    Kujawa A, Weinberg A, Bunford N, Fitzgerald KD, Hanna GL, Monk CS, Kennedy AE, Klumpp H, Hajcak G, Phan KL (2016) Error-related brain activity in youth and young adults before and after treatment for generalized or social anxiety disorder. Prog Neuropsychopharmacol Biol Psychiatry 71:162–168Google Scholar
  72. 72.
    Horowitz-Kraus T (2016) Improvement of the error-detection mechanism in adults with dyslexia following reading acceleration training. Dyslexia 22(2):173–189Google Scholar
  73. 73.
    Toyomaki A, Murohashi H (2005) Discrepancy between feedback negativity and subjective evaluation in gambling. Neuroreport 16(16):1865–1868Google Scholar
  74. 74.
    Schupp HT, Markus J, Weike AI, Hamm AO (2003) Emotional facilitation of sensory processing in the visual cortex. Psychol Sci 14(1):7–13Google Scholar
  75. 75.
    Zukov I, Ptacek R, Kozelek P, Fischer S, Domluvilova D, Raboch J, Hruby T, Susta M (2009) Brain wave P300: a comparative study of various forms of criminal activity. Med Sci Monit 15(7):CR349-354Google Scholar
  76. 76.
    Morand-Beaulieu S, O’Connor KP, Sauvé G, Blanchet PJ, Lavoie ME (2015) Cognitive-behavioral therapy induces sensorimotor and specific electrocortical changes in chronic tic and Tourette’s disorder. Neuropsychologia 79:310–321Google Scholar
  77. 77.
    Naga Venkatesha Murthy P, Gangadhar B, Janakiramaiah N, Subbakrishna D (1997) Normalization of P300 amplitude following treatment in dysthymia. Biol Psychiatry 42(8):740–743Google Scholar
  78. 78.
    Smart CM (2014) Mindfulness training: A novel approach to intervening in older adults with subjective cognitive decline. Alzheimer’s Dement J Alzheimer’s Assoc 10(4):P164Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • H. L. Pincham
    • 1
  • D. Bryce
    • 2
  • P. Fonagy
    • 1
    • 3
  • R. M. Pasco Fearon
    • 1
    • 3
    Email author
  1. 1.Developmental Neuroscience UnitAnna Freud National Centre for Children and FamiliesLondonUK
  2. 2.Department of PsychologyUniversity of TübingenTübingenGermany
  3. 3.Research Department of Clinical, Educational and Health PsychologyUniversity College LondonLondonUK

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