Personality and cognition offer robust frameworks to understand the individual differences associated with externalizing behaviors. However, these literatures have historically been separated in the study of the externalizing spectrum. In the present study, we used comprehensive tests of additive and interactive effects to examine the utility of integrating models of personality and cognition to understand externalizing behaviors in young adulthood (N = 1,179; Human Connectome Project) and late childhood (N = 11,448; Adolescent Brain Cognitive Development Study). Generally, the average effects of personality traits in young adulthood and the additive effects of impulsigenic traits and cognition in late childhood demonstrate the utility of integrating personality and cognition to understand incidence of early onset externalizing-spectrum behaviors. Although interaction effects were detected, they were small and practically negligible in their explanation of variance in externalizing behaviors. Results support primarily focusing on additively integrating these literatures to understand the individual differences related to externalizing behaviors.
AchenbachT. M. (1966). The classification of children’s psychiatric symptoms: A factor-analytic study. Psychological Monographs: General and Applied, 80(7), 1–37.
2.
AchenbachT. M.IvanovaM. Y.RescorlaL. A. (2017). Empirically based assessment and taxonomy of psychopathology for ages 1½–90+ years: Developmental, multi-informant, and multicultural findings. Comprehensive Psychiatry, 79, 4–18.
3.
AchenbachT. M.RescorlaL. A.McConaugheyS.PecoraP.WetherbeeK.RuffleT. (2003). Achenbach system of empirically based assessment. In ReynoldsC. R.KamphausR. W. (Eds.), Handbook of psychological and educational assessment of children: Personality, behavior, and context (2nd ed., pp. 406–432). The Guilford Press.
4.
AckermanP. L.HeggestadE. D. (1997). Intelligence, personality, and interests: Evidence for overlapping traits. Psychological Bulletin, 121(2), 219–245.
5.
AguinisH.BeatyJ. C.BoikR. J.PierceC. A. (2005). Effect size and power in assessing moderating effects of categorical variables using multiple regression: A 30-year review. Journal of Applied Psychology, 90(1), 94–107.
6.
AkshoomoffN.BeaumontJ. L.BauerP. J.DikmenS. S.GershonR. C.MungasD.SlotkinJ.TulskyD.WeintraubS.ZelazoP. D.HeatonR. K. (2013). VIII. NIH Toolbox Cognition Battery (CB): Composite scores of crystallized, fluid, and overall cognition. Monographs of the Society for Research in Child Development, 78(4), 119–132.
7.
AkshoomoffN.BrownT. T.BakemanR.HaglerD. J.Jr. (2018). Developmental differentiation of executive functions on the NIH Toolbox Cognition Battery. Neuropsychology, 32(7), 777–783.
8.
AnglimJ.DunlopP. D.WeeS.HorwoodS.WoodJ. K.MartyA. (2022). Personality and intelligence: A meta-analysis. Psychological Bulletin, 148(5–6), 301–336.
9.
Arel-BundockV. (2023). Marginaleffects: Predictions, comparisons, slopes, marginal means, and hypothesis tests. R Package Version 0.15, 1.
10.
BarangerD. A.FinsaasM. C.GoldsteinB. L.VizeC. E.LynamD. R.OlinoT. M. (2023). Tutorial: Power analyses for interaction effects in cross-sectional regressions. Advances in Methods and Practices in Psychological Science, 6(3). https://doi.org/10.1177/2515245923118753
11.
Baskin-SommersA. R.BaskinD. R.SommersI. B.NewmanJ. P. (2013). The intersectionality of sex, race, and psychopathology in predicting violent crimes. Criminal Justice and Behavior, 40(10), 1068–1091.
12.
BastianV. A.BurnsN. R.NettelbeckT. (2005). Emotional intelligence predicts life skills, but not as well as personality and cognitive abilities. Personality and Individual Differences, 39(6), 1135–1145.
13.
BergJ. M.LatzmanR. D.BliwiseN. G.LilienfeldS. O. (2015). Parsing the heterogeneity of impulsivity: A meta-analytic review of the behavioral implications of the UPPS for psychopathology. Psychological Assessment, 27(4), 1129–1146.
14.
BresinK. (2019). Impulsivity and aggression: A meta-analysis using the UPPS model of impulsivity. Aggression and Violent Behavior, 48, 124–140.
15.
BurtS. A.McGueM.IaconoW. G. (2009). Nonshared environmental mediation of the association between deviant peer affiliation and adolescent externalizing behaviors over time: Results from a cross-lagged monozygotic twin differences design. Developmental Psychology, 45(6), 1752–1760. https://doi.org/10.1037/a0016687
16.
CaseyB. J.CannonierT.ConleyM. I.CohenA. O.BarchD. M.HeitzegM. M.SoulesM. E.TeslovichT.DellarcoD. V.GaravanH.OrrC. A.WagerT. D.BanichM. T.SpeerN. K.SutherlandM. T.RiedelM. C.DickA. S.BjorkJ. M.ThomasK. M.. . . DaleA. M. (2018). The Adolescent Brain Cognitive Development (ABCD) Study: Imaging acquisition across 21 sites. Developmental Cognitive Neuroscience, 32, 43–54.
17.
CattellR. B. (1963). Personality, role, mood, and situation-perception: A unifying theory of modulators. Psychological Review, 70(1), 1–18.
18.
CattellR. B. (1971). Abilities: their structure, growth, and action. Houghton Mifflin.
19.
Chamorro-PremuzicT.FurnhamA.AckermanP. L. (2006). Ability and personality correlates of general knowledge. Personality and Individual Differences, 41(3), 419–429.
20.
CohenJ.CohenP.WestS. G.AikenL. S. (2003). Applied multiple regression/correlation analyses for the behavioral sciences (3rd ed.). Lawrence Earlbaum Associates.
21.
CostaP. T.Jr.McCraeR. R. (1992). The five-factor model of personality and its relevance to personality disorders. Journal of Personality Disorders, 6(4), 343–359.
22.
CydersM. A.SmithG. T.SpillaneN. S.FischerS.AnnusA. M.PetersonC. (2007). Integration of impulsivity and positive mood to predict risky behavior: Development and validation of a measure of positive urgency. Psychological Assessment, 19(1), 107–118.
23.
DeYoungC. G. (2020). Intelligence and personality. In SternbergR. J. (Ed.), The Cambridge handbook of intelligence (pp. 1011–1047). Cambridge University Press.
24.
DeYoungC. G.PetersonJ. B.SéguinJ. R.TremblayR. E. (2008). Externalizing behavior and the higher order factors of the Big Five. Journal of Abnormal Psychology, 117(4), 947–953.
25.
DeYoungC. G.QuiltyL. C.PetersonJ. B.GrayJ. R. (2014). Openness to experience, intellect, and cognitive ability. Journal of Personality Assessment, 96(1), 46–52.
26.
FarringtonD. P. (1998). Predictors, causes, and correlates of male youth violence. Crime and Justice, 24, 421–475.
27.
FlouriE.HickeyJ.MavroveliS.HurryJ. (2011). Adversity, emotional arousal, and problem behaviour in adolescence: The role of non-verbal cognitive ability as a resilience promoting factor. Child and Adolescent Mental Health, 16(1), 22–29.
28.
FurnhamA.BachtiarV. (2008). Personality and intelligence as predictors of creativity. Personality and Individual Differences, 45(7), 613–617.
29.
GornikA. E.ClarkD. A.DurbinC. E.ZuckerR. A. (2023). Individual differences in the development of youth externalizing problems predict a broad range of adult psychosocial outcomes. Development and Psychopathology, 35(2), 630–651.
30.
HeatonR. K.AkshoomoffN.TulskyD.MungasD.WeintraubS.DikmenS.BeaumontJ.CasalettoK. B.ConwayK.SlotkinJ.GershonR. (2014). Reliability and validity of composite scores from the NIH Toolbox Cognition Battery in adults. Journal of the International Neuropsychological Society, 20(6), 588–598.
31.
HornJ. L. (1968). Organization of abilities and the development of intelligence. Psychological Review, 75(3), 242–259. https://doi.org/10.1037/h0025662.
32.
HyattC. S.CroweM. L.WestS. J.VizeC. E.CarterN. T.ChesterD. S.MillerJ. D. (2022). An empirically based power primer for laboratory aggression research. Aggressive Behavior, 48(3), 279–289.
33.
HyattC. S.SharpeB. M.OwensM. M.ListygB. S.CarterN. T.LynamD. R.MillerJ. D. (2022). Searching high and low for meaningful and replicable morphometric correlates of personality. Journal of Personality and Social Psychology, 123(2), 463–480.
34.
IaconoW. G.MaloneS. M.McGueM. (2003). Substance use disorders, externalizing psychopathology, and P300 event-related potential amplitude. International Journal of Psychophysiology, 48(2), 147–178.
35.
JackmanS. (2024). pscl: Classes and methods for R developed in the political science computational laboratory. R package version 1.5.9. University of Sydney. https://github.com/atahk/pscl/
36.
JonesS. E.MillerJ. D.LynamD. R. (2011). Personality, antisocial behavior, and aggression: A meta-analytic review. Journal of Criminal Justice, 39(4), 329–337.
37.
JudgeT. A.JacksonC. L.ShawJ. C.ScottB. A.RichB. L. (2007). Self-efficacy and work-related performance: The integral role of individual differences. Journal of Applied Psychology, 92(1), 107–127.
38.
Karaca-MandicP.NortonE. C.DowdB. (2012). Interaction terms in nonlinear models. Health Services Research, 47(1, Pt. 1), 255–274.
39.
KotovR.KruegerR. F.WatsonD.AchenbachT. M.AlthoffR. R.BagbyR. M.BrownT. A.CarpenterW. T.CaspiA.ClarkL. A.EatonN. R.ForbesM. K.ForbushK. T.GoldbergD.HasinD.HymanS. E.IvanovaM. Y.LynamD. R.MarkonK.. . . ZimmermanM. (2017). The Hierarchical Taxonomy of Psychopathology (HiTOP): A dimensional alternative to traditional nosologies. Journal of Abnormal Psychology, 126(4), 454–477.
40.
KruegerR. F.CaspiA.MoffittT. E.SilvaP. A. (1998). The structure and stability of common mental disorders (DSM-III-R): A longitudinal-epidemiological study. Journal of Abnormal Psychology, 107(2), 216–227.
41.
LiuJ. (2004). Childhood externalizing behavior: Theory and implications. Journal of Child and Adolescent Psychiatric Nursing, 17(3), 93–103.
42.
LoeberR.MentingB.LynamD. R.MoffittT. E.Stouthamer-LoeberM.StallingsR.FarringtonD. P.PardiniD. (2012). Findings from the Pittsburgh Youth Study: Cognitive impulsivity and intelligence as predictors of the age–crime curve. Journal of the American Academy of Child & Adolescent Psychiatry, 51(11), 1136–1149.
43.
LüdeckeD.LüdeckeM. D. (2015). Package ‘sjPlot’. R package Version, 1(9), 1–49.
44.
LynamD. R.MillerJ. D. (2019). The basic trait of antagonism: An unfortunately underappreciated construct. Journal of Research in Personality, 81, 118–126.
45.
LynamD. R.MoffittT. E.Stouthamer-LoeberM. A. (1993). Explaining the relation between IQ and delinquency: Class, race, test motivation, school achievement, or self-control?Journal of Abnormal Psychology, 102, 187–196.
46.
Maples-KellerJ. L.BerkeD. S.FewL. R.MillerJ. D. (2016). A review of sensation seeking and its empirical correlates: Dark, bright, and neutral hues. In Zeigler-HillV.MarcusD. K. (Eds.), The dark side of personality: Science and practice in social, personality, and clinical psychology (pp. 137–156). American Psychological Association.
47.
MarmorsteinN. R. (2013). Associations between dispositions to rash action and internalizing and externalizing symptoms in children. Journal of Clinical Child & Adolescent Psychology, 42(1), 131–138.
48.
McCabeC. J.HalvorsonM. A.KingK.CaoX.KimD. (2021). modglm: An R package for testing, interpreting, and displaying interactions in generalized linear models of discrete data [Preprint]. https://osf.io/preprints/psyarxiv/6vmsa_v1
49.
McCabeC. J.HalvorsonM. A.KingK. M.CaoX.KimD. S. (2022). Interpreting interaction effects in generalized linear models of nonlinear probabilities and counts. Multivariate Behavioral Research, 57(2–3), 243–263.
50.
McClellandG. H.JuddC. M. (1993). Statistical difficulties of detecting interactions and moderator effects. Psychological Bulletin, 114(2), 376–390.
51.
McGrewK. S.FlanaganD. P.KeithT. Z.VanderwoodM. (1997). Beyond g: The impact of Gf-Gc specific cognitive abilities research on the future use and interpretation of intelligence tests in the schools. School Psychology Review, 26(2), 189–210.
52.
McNeishD.StapletonL. M.SilvermanR. D. (2017). On the unnecessary ubiquity of hierarchical linear modeling. Psychological Methods, 22(1), 114–140.
53.
MillerJ. D.LynamD. (2001). Structural models of personality and their relation to antisocial behavior: A meta-analytic review. Criminology, 39(4), 765–798.
54.
MillerJ. D.LynamD. R. (2003). Psychopathy and the five-factor model of personality: A replication and extension. Journal of Personality Assessment, 81(2), 168–178.
55.
MizeT. D. (2019). Best practices for estimating, interpreting, and presenting nonlinear interaction effects. Sociological Science, 6, 81–117.
56.
MoffittT. E. (1993a). Life-course-persistent and adolescence-limited antisocial behavior: A developmental taxonomy. Psychological Review, 100(4), 674–701.
57.
MoffittT. E. (1993b). The neuropsychology of conduct disorder. Development and Psychopathology, 5(1–2), 135–151.
58.
MoffittT. E. (2017). The new look of behavioral genetics in developmental psychopathology: Gene-environment interplay in antisocial behaviors. In BeaverK. M. (Ed.), Biosocial theories of crime (pp. 183–204). Routledge.
59.
MorganA. B.LilienfeldS. O. (2000). A meta-analytic review of the relation between antisocial behavior and neuropsychological measures of executive function. Clinical Psychology Review, 20(1), 113–136.
60.
MoylanC. A.HerrenkohlT. I.SousaC.TajimaE. A.HerrenkohlR. C.RussoM. J. (2010). The effects of child abuse and exposure to domestic violence on adolescent internalizing and externalizing behavior problems. Journal of Family Violence, 25, 53–63.
61.
MurphyK. R.RussellC. J. (2017). Mend it or end it: Redirecting the search for interactions in the organizational sciences. Organizational Research Methods, 20(4), 549–573.
62.
MusselP. (2013). Intellect: A theoretical framework for personality traits related to intellectual achievements. Journal of Personality and Social Psychology, 104(5), 885–906.
63.
NagelkerkeN. J. (1991). A note on a general definition of the coefficient of determination. Biometrika, 78(3), 691–692.
64.
NavradyL. B.RitchieS. J.ChanS. W.KerrD. M.AdamsM. J.HawkinsE. H.PorteousD.DearyI. J.GaleC. R.BattyG. D.McIntoshA. M. (2017). Intelligence and neuroticism in relation to depression and psychological distress: Evidence from two large population cohorts. European Psychiatry, 43, 58–65.
65.
OgilvieJ. M.StewartA. L.ChanR. C.ShumD. H. (2011). Neuropsychological measures of executive function and antisocial behavior: A meta-analysis. Criminology, 49(4), 1063–1107.
66.
PerkinsA. M.CorrP. J. (2006). Cognitive ability as a buffer to neuroticism: Churchill’s secret weapon?Personality and Individual Differences, 40(1), 39–51.
67.
PetersenI. T.BatesJ. E.DodgeK. A.LansfordJ. E.PettitG. S. (2015). Describing and predicting developmental profiles of externalizing problems from childhood to adulthood. Development and Psychopathology, 27(3), 791–818.
68.
Posit Team. (2023). RStudio: Integrated development for R. RStudio. http://www.rstudio.com/
69.
R Core Team. (2023). R: A language and environment for statistical computing. R Foundation for Statistical Computing.
70.
RaineA. (1997). The psychopathology of crime: Criminal behavior as a clinical disorder. Gulf Professional Publishing.
71.
RevelleW.RevelleM. W. (2015). Package ‘psych.’The Comprehensive R Archive Network, 337(338).
72.
RingwaldW. R.AbramovitchA.van RentergemJ. A.KotovR. (2024). Do cognitive functions belong in the Hierarchical Taxonomy of Psychopathology (HiTOP) model? A meta-analysis [Preprint]. https://osf.io/preprints/psyarxiv/8r2vq_v1
73.
RipleyB.VenablesB.BatesD. M.HornikK.GebhardtA.FirthD.RipleyM. B. (2013). Package ‘mass.’Cran r, 538, 113–120.
74.
RobertsW.PetersJ. R.AdamsZ. W.LynamD. R.MilichR. (2014). Identifying the facets of impulsivity that explain the relation between ADHD symptoms and substance use in a nonclinical sample. Addictive Behaviors, 39, 1272–1277.
75.
RuizM. A.PincusA. L.SchinkaJ. A. (2008). Externalizing pathology and the five-factor model: A meta-analysis of personality traits associated with antisocial personality disorder, substance use disorder, and their co-occurrence. Journal of Personality Disorders, 22(4), 365–388.
76.
Sanchez de RiberaO.KavishN.KatzI. M.BoutwellB. B. (2019). Untangling intelligence, psychopathy, antisocial personality disorder, and conduct problems: A meta–analytic review. European Journal of Personality, 33(5), 529–564.
77.
SchoemakerK.MulderH.DekovićM.MatthysW. (2013). Executive functions in preschool children with externalizing behavior problems: A meta-analysis. Journal of Abnormal Child Psychology, 41(3), 457–471.
78.
SimmonsJ. P.NelsonL. D.SimonsohnU. (2011). False-positive psychology: Undisclosed flexibility in data collection and analysis allows presenting anything as significant. Psychological Science, 22(11), 1359–1366.
79.
SommetN.WeissmanD. L.CheutinN.ElliotA. J. (2023). How many participants do I need to test an interaction? Conducting an appropriate power analysis and achieving sufficient power to detect an interaction. Advances in Methods and Practices in Psychological Science, 6(3). https://doi.org/10.1177/25152459231178728
80.
StanekK. C.OnesD. S. (2023). Meta-analytic relations between personality and cognitive ability. Proceedings of the National Academy of Sciences, 120(23), Article e2212794120. https://doi.org/10.1073/pnas.2212794120
81.
Van EssenD. C.SmithS. M.BarchD. M.BehrensT. E.YacoubE.UgurbilK.; Wu-Minn HCP Consortium. (2013). The WU-Minn human connectome project: An overview. Neuroimage, 80, 62–79.
82.
VizeC. E.BarangerD. A.FinsaasM. C.GoldsteinB. L.OlinoT. M.LynamD. R. (2023). Moderation effects in personality disorder research. Personality Disorders: Theory, Research, and Treatment, 14(1), 118–126.
83.
VizeC. E.MillerJ. D.LynamD. R. (2018). FFM facets and their relations with different forms of antisocial behavior: An expanded meta-analysis. Journal of Criminal Justice, 57, 67–75.
84.
WattsA. L.SmithG. T.BarchD. M.SherK. J. (2020). Factor structure, measurement and structural invariance, and external validity of an abbreviated youth version of the UPPS-P Impulsive Behavior Scale. Psychological Assessment, 32(4), 336–347.
85.
WhitesideS. P.LynamD. R. (2001). The five factor model and impulsivity: Using a structural model of personality to understand impulsivity. Personality and Individual Differences, 30(4), 669–689.
86.
WickhamH.AverickM.BryanJ.ChangW.McGowanL. D. A.FrançoisR.GrolemundG.HayesA.HenryL.HesterJ.KuhnM.PedersenT. L.MillerE.BacheS. M.MüllerK.OomsJ.RobinsonD.SeidelD. P.SpinuV.. . . YutaniH. (2019). Welcome to the Tidyverse. Journal of Open Source Software, 4(43), Article 1686. https://doi.org/10.21105/joss.01686
87.
YangY.ShieldsG. S.ZhangY.WuH.ChenH.RomerA. L. (2022). Child executive function and future externalizing and internalizing problems: A meta-analysis of prospective longitudinal studies. Clinical Psychology Review, 97, Article 102194. https://doi.org/10.1016/j.cpr.2022.102194
88.
ZeileisA.KöllS.GrahamN. (2020). Various versatile variances: An object-oriented implementation of clustered covariances in R. Journal of Statistical Software, 95(1), 1–36. https://doi.org/10.18637/jss.v095.i01
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
