Hostname: page-component-7f64f4797f-zzvtc Total loading time: 0 Render date: 2025-11-04T01:23:34.272Z Has data issue: false hasContentIssue false
  • English
  • Français

Differences in executive functioning between violent and non-violent offenders

Published online by Cambridge University Press:  08 February 2017

J. Meijers ,
J. M. Harte ,
G. Meynen  and
P. Cuijpers
J. Meijers*
Affiliation:
Department of Clinical, Neuro- and Developmental Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
J. M. Harte
Affiliation:
Department of Criminal Law and Criminology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
G. Meynen
Affiliation:
Department of Philosophy, Faculty of Humanities, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands Tilburg Law School, Tilburg University, Tilburg, The Netherlands
P. Cuijpers
Affiliation:
Department of Clinical, Neuro- and Developmental Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands EMGO Institute for Health and Care Research, Vrije Universiteit Amsterdam and VU Medical Centre Amsterdam, Amsterdam, The Netherlands
*
*Address for correspondence: J. Meijers, MSc, Department Clinical, Neuro- and Developmental Psychology, Faculty of Behavioural and Movement Sciences, Section Clinical Neuropsychology, Vrije Universiteit Amsterdam, Room 1F-66, Van der Boechorststraat 1, 1081 BT Amsterdam, The Netherlands. (Email: j.meijers@vu.nl)
Get access Rights & Permissions [Opens in a new window]

Abstract

Background

A growing body of neuropsychological and neurobiological research shows a relationship between functioning of the prefrontal cortex and criminal and violent behaviour. The prefrontal cortex is crucial for executive functions such as inhibition, attention, working memory, set-shifting and planning. A deficit in these functions – a prefrontal deficit – may result in antisocial, impulsive or even aggressive behaviour. While several meta-analyses show large effect sizes for the relationship between a prefrontal deficit, executive dysfunction and criminality, there are few studies investigating differences in executive functions between violent and non-violent offenders. Considering the relevance of identifying risk factors for violent offending, the current study explores whether a distinction between violent and non-violent offenders can be made using an extensive neuropsychological test battery.

Method

Male remand prisoners (N = 130) in Penitentiary Institution Amsterdam Over-Amstel were administered an extensive neuropsychological test battery (Cambridge Automated Neuropsychological Test Battery; CANTAB) measuring response inhibition, planning, attention, set-shifting, working memory and impulsivity/reward sensitivity.

Results

Violent offenders performed significantly worse on the stop-signal task (partial correlation r = 0.205, p = 0.024), a task measuring response inhibition. No further differences were found between violent and non-violent offenders. Explorative analyses revealed a significant relationship between recidivism and planning (partial correlation r = −0.209, p = 0.016).

Conclusion

Violent offenders show worse response inhibition compared to non-violent offenders, suggesting a more pronounced prefrontal deficit in violent offenders than in non-violent offenders.

Keywords

CANTABexecutive functioninhibitionneuropsychologyoffendersprison

Information

Type
Original Articles
Information
Psychological Medicine , Volume 47 , Issue 10 , July 2017 , pp. 1784 - 1793
Copyright
Copyright © Cambridge University Press 2017 

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.)

Article purchase

Temporarily unavailable

References

Andrews, DA, Bonta, J, Wormith, JS (2011). The Risk-Need-Responsivity (RNR) model does adding the good lives model contribute to effective crime prevention? Criminal Justice and Behavior 38, 735–755.Google Scholar
Baker, SF, Ireland, JL (2007). The link between dyslexic traits, executive functioning, impulsivity and social self-esteem among an offender and non-offender sample. International Journal of Law and Psychiatry 30, 492–503.Google Scholar
Bari, A, Robbins, TW (2013). Inhibition and impulsivity: behavioral and neural basis of response control. Progress in Neurobiology 108, 44–79.CrossRefGoogle ScholarPubMed
Barnett, JH, Blackwell, AD, Sahakian, BJ, Robbins, TW (2016). The Paired Associates Learning (PAL) test: 30 years of CANTAB translational neuroscience from laboratory to bedside in dementia research. In Translational Neuropsychopharmacology, vol. 28, pp. 449–474 (ed. Robbins, T. W. and Sahakian, B. J) (Current Topics in Behavioral Neurosciences). Springer International Publishing: Cham, Switzerland.CrossRefGoogle Scholar
Brand, EFJM (2005). PIJ-Dossiers 2003-C. Predictieve validiteit van de FPJ-lijst. Dienst Justitiele Inrichtingen: Den Haag.Google Scholar
Christodoulou, M (2012). Locked up and at risk of dementia. Lancet Neurology 11, 750–751.Google Scholar
Derogatis, LR (1996). SCL-90-R: Symptom Checklist-90-R: Administration, Scoring, and Procedures Manual. NCS Pearson: Minneapolis, MN.Google Scholar
Derogatis, LR, Savitz, KL (2000). The SCL–90–R and Brief Symptom Inventory (BSI) in primary care. In Handbook of Psychological Assessment in Primary Care (ed. Maruish, M. E.), pp. 297–334. Lawrence Erlbaum Associates Publishers: Mahwah, NJ: US.Google Scholar
Girard, TA, Axelrod, BN, Patel, R, Crawford, JR (2015). Wechsler adult intelligence scale-IV dyads for estimating global intelligence. Assessment 22, 441–448.Google Scholar
Glenn, AL, Raine, A (2014). Neurocriminology: implications for the punishment, prediction and prevention of criminal behaviour. Nature Reviews Neuroscience 15, 54–63.Google Scholar
Graham, JW, Olchowski, AE, Gilreath, TD (2007). How many imputations are really needed? Some practical clarifications of multiple imputation theory. Prevention Science 8, 206–213.CrossRefGoogle ScholarPubMed
Greenfield, R, Valliant, PM (2007). Moral reasoning, executive function, and personality in violent and nonviolent adult offenders. Psychological Reports 101, 323–333.Google Scholar
Hancock, M, Tapscott, JL, Hoaken, PN (2010). Role of executive dysfunction in predicting frequency and severity of violence. Aggressive Behavior 36, 338–349.Google Scholar
Hedden, T, Gabrieli, JD (2004). Insights into the ageing mind: a view from cognitive neuroscience. Nature Reviews Neuroscience 5, 87–96.CrossRefGoogle ScholarPubMed
Hoaken, PN, Allaby, DB, Earle, J (2007). Executive cognitive functioning and the recognition of facial expressions of emotion in incarcerated violent offenders, non-violent offenders, and controls. Aggressive Behavior 33, 412–421.Google Scholar
Hofmann, W, Schmeichel, BJ, Baddeley, AD (2012). Executive functions and self-regulation. Trends in Cognitive Sciences 16, 174–180.Google Scholar
Jurado, MB, Rosselli, M (2007). The elusive nature of executive functions: a review of our current understanding. Neuropsychology Review 17, 213–233.Google Scholar
Kalanthroff, E, Goldfarb, L, Henik, A (2013). Evidence for interaction between the stop signal and the Stroop task conflict. Journal of Experimental Psychology. Human Perception and Performance 39, 579–592.Google Scholar
Khng, KH, Lee, K (2014). The relationship between Stroop and stop-signal measures of inhibition in adolescents: influences from variations in context and measure estimation. PLoS ONE 9, e101356.CrossRefGoogle ScholarPubMed
Kordelaar, WFJM (2002). Beslissingsondersteuning onderzoek geestvermogens in het strafrecht voor volwassenen, p. 370. Tilburg University, Kluwer, Deventer.Google Scholar
Lacouture, Y, Cousineau, D (2008). How to use MATLAB to fit the ex-Gaussian and other probability functions to a distribution of response times. Tutorials in Quantitative Methods for Psychology 4, 35–45.Google Scholar
Lowe, C, Rabbitt, P (1998). Test/re-test reliability of the CANTAB and ISPOCD neuropsychological batteries: theoretical and practical issues. Cambridge Neuropsychological Test Automated Battery. International Study of Post-Operative Cognitive Dysfunction. Neuropsychologia 36, 915–923.CrossRefGoogle Scholar
Meijers, J, Harte, JM, Jonker, FA, Meynen, G (2015). Prison brain? Executive dysfunction in prisoners. Frontiers in Psychology 6, 43.Google Scholar
Morgan, AB, Lilienfeld, SO (2000). A meta-analytic review of the relation between antisocial behavior and neuropsychological measures of executive function. Clinical Psychology Review 20, 113–136.Google Scholar
Nordstrom, BR, Gao, Y, Glenn, AL, Peskin, M, Rudo-Hutt, AS, Schug, RA, Yang, Y, Raine, A (2011). Neurocriminology. Advances in Genetics 75, 255–283.Google Scholar
Ogilvie, JM, Stewart, AL, Chan, RCK, Shum, DHK (2011). Neuropsychological measures of executive function and antisocial behavior: a meta-analysis. Criminology 49, 1063–1107.CrossRefGoogle Scholar
Raine, A (2002). Annotation: the role of prefrontal deficits, low autonomic arousal, and early health factors in the development of antisocial and aggressive behavior in children. Journal of Child Psychology and Psychiatry 43, 417–434.CrossRefGoogle ScholarPubMed
Rubin, DB (2004). Multiple Imputation for Nonresponse in Surveys. John Wiley & Sons: Hoboken, NJ.Google Scholar
Sheehan, DV, Lecrubier, Y, Sheehan, KH, Janavs, J, Weiller, E, Hergueta, T, Baker, R, Dunbar, GC (1998). The Mini-International Neuropsychiatric Interview (MINI): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. Journal of Clinical Psychiatry 59, 22–33.Google ScholarPubMed
Van Vliet, IM, De Beurs, E (2007). [The MINI-International Neuropsychiatric Interview. A brief structured diagnostic psychiatric interview for DSM-IV en ICD-10 psychiatric disorders]. Tijdschrift voor Psychiatrie 393–397.Google ScholarPubMed
Vanderhoff, H, Jeglic, EL, Donovick, PJ (2011). Neuropsychological assessment in prisons: ethical and practical challenges. Journal of Correctional Health Care 17, 51–60.Google Scholar
Volkers, KM, Scherder, EJ (2011). Impoverished environment, cognition, aging and dementia. Reviews in the Neurosciences 22, 259–266.CrossRefGoogle ScholarPubMed
Ward, T, Yates, PM, Willis, GM (2012). The good lives model and the risk need responsivity model a critical response to Andrews, Bonta, and Wormith (2011). Criminal Justice and Behavior 39, 94–110.Google Scholar
Wood, AM, White, IR, Royston, P (2008). How should variable selection be performed with multiply imputed data? Statistics in Medicine 27, 3227–3246.Google Scholar
Yang, Y, Raine, A (2009). Prefrontal structural and functional brain imaging findings in antisocial, violent, and psychopathic individuals: a meta-analysis. Psychiatry Research: Neuroimaging 174, 81–88.CrossRefGoogle ScholarPubMed
Supplementary material: File

Meijers supplementary material

Appendices A and B

Download Meijers supplementary material(File)
File 32.4 KB