Premorbid Personality Traits as Risk Factors for Behavioral Addictions: A Systematic Review of a Vulnerability Hypothesis
Abstract
:1. Introduction
2. Materials and Methods
2.1. Design
2.2. Search Strategy
2.3. Study Selection
2.4. Data Analysis
3. Results
3.1. Personality Traits and Addictive Behaviors in the Reviews
3.2. Personality Traits and Individual Behavioral Addictions in the Empirical Studies
4. Discussion
4.1. Personality Traits and Behavioral Addiction
4.2. Heritability and Neuro-Anatomical Substrate of Personality
4.3. Vulnerability Hypothesis
5. Limitations
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Grant, J.E.; Atmaca, M.; Fineberg, N.A.; Fontenelle, L.F.; Matsunaga, H.; Reddy, Y.C.J.; Simpson, H.B.; Thomsen, P.H.; van den Heuvel, O.A.; Veale, D. Impulse control disorders and “behavioural addictions” in the ICD-11. World Psychiatry 2014, 13, 125. [Google Scholar] [CrossRef] [Green Version]
- de Hesselle, L.C.; Rozgonjuk, D.; Sindermann, C.; Pontes, H.M.; Montag, C. The associations between Big Five personality traits, gaming motives, and self-reported time spent gaming. Pers. Individ. Dif. 2021, 171, 110483. [Google Scholar] [CrossRef]
- Floros, G.; Siomos, K. Excessive Internet use and personality traits. Curr. Behav. Neurosci. Rep. 2014, 1, 19–26. [Google Scholar] [CrossRef] [Green Version]
- Kayiş, A.R.; Satici, S.A.; Yilmaz, M.F.; Şimşek, D.; Ceyhan, E.; Bakioğlu, F. Big five-personality trait and internet addiction: A meta-analytic review. Comput. Human Behav. 2016, 63, 35–40. [Google Scholar] [CrossRef]
- Gervasi, A.M.; La Marca, L.; Costanzo, A.; Pace, U.; Guglielmucci, F.; Schimmenti, A. Personality and internet gaming disorder: A systematic review of recent literature. Curr. Addict. Rep. 2017, 4, 293–307. [Google Scholar] [CrossRef]
- Şalvarlı, Ş.İ.; Griffiths, M.D. The association between internet gaming disorder and impulsivity: A systematic review of literature. Int. J. Ment. Health Addict. 2019, 29, 92–118. [Google Scholar] [CrossRef] [Green Version]
- Smirni, D.; Garufo, E.; Di Falco, L.; Lavanco, G. The Playing Brain. The Impact of Video Games on Cognition and Behavior in Pediatric Age at the Time of Lockdown: A Systematic Review. Pediatr. Rep. 2021, 13, 47. [Google Scholar] [CrossRef] [PubMed]
- Griffiths, M. Adolescent Gambling; Psychology Press: Hove, East Sussex, UK, 1995; ISBN 0415058341. [Google Scholar]
- Griffiths, M. Internet addiction-time to be taken seriously? Addict. Res. 2000, 8, 413–418. [Google Scholar] [CrossRef]
- Griffiths, M. The educational benefits of videogames. Educ. Health 2002, 20, 47–51. [Google Scholar]
- Griffiths, M. Online therapy for addictive behaviors. CyberPsychol. Behav. 2005, 8, 555–561. [Google Scholar] [CrossRef]
- Orford, J. Addiction as excessive appetite. Addiction 2001, 96, 15–31. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Carnes, P. Out of the Shadows: Understanding Sexual Addiction; Hazelden Publishing: Minnesota, MN, USA, 2001; ISBN 1568386214. [Google Scholar]
- Terry, A.; Szabo, A.; Griffiths, M. The exercise addiction inventory: A new brief screening tool. Addict. Res. Theory 2004, 12, 489–499. [Google Scholar] [CrossRef]
- Peele, S.; Brodsky, A. Love and Addiction; Taplinger: Brick, NJ, USA, 1975. [Google Scholar]
- Potenza, M.N. Should addictive disorders include non-substance-related conditions? Addiction 2006, 101, 142–151. [Google Scholar] [CrossRef] [PubMed]
- Lesieur, H.R.; Blume, S.B. Pathological gambling, eating disorders, and the psychoactive substance use disorders. J. Addict. Dis. 1993, 12, 89–102. [Google Scholar] [CrossRef]
- Albrecht, U.; Kirschner, N.E.; Grüsser, S.M. Diagnostic instruments for behavioural addiction: An overview. GMS Psycho-Soc. Med. 2007, 4, 1–11. [Google Scholar]
- Marlatt, G.A.; Baer, J.S.; Donovan, D.M.; Kivlahan, D.R. Addictive behaviors: Etiology and treatment. Annu. Rev. Psychol. 1988, 39, 223–252. [Google Scholar] [CrossRef]
- Cipolotti, L.; Molenberghs, P.; Dominguez, J.; Smith, N.; Smirni, D.; Xu, T.; Shallice, T.; Chan, E. Fluency and rule breaking behaviour in the frontal cortex. Neuropsychologia 2020, 137, 107308. [Google Scholar] [CrossRef]
- Pastorino, G.M.G.; Operto, F.F.; Padovano, C.; Vivenzio, V.; Scuoppo, C.; Pastorino, N.; Roccella, M.; Vetri, L.; Carotenuto, M.; Coppola, G. Social cognition in neurodevelopmental disorders and epilepsy. Front. Neurol. 2021, 12, 658823. [Google Scholar] [CrossRef]
- Kuss, D.J.; Griffiths, M.D.; Pontes, H.M. DSM-5 diagnosis of Internet Gaming Disorder: Some ways forward in overcoming issues and concerns in the gaming studies field: Response to the commentaries. J. Behav. Addict. 2017, 6, 133–141. [Google Scholar] [CrossRef] [Green Version]
- Turel, O.; Serenko, A. The benefits and dangers of enjoyment with social networking websites. Eur. J. Inf. Syst. 2012, 21, 512–528. [Google Scholar] [CrossRef]
- Xu, H.; Tan, B.C.Y. Why Do I Keep Checking Facebook: Effects of Message Characteristics on the Formation of Social Network Services Addiction. In Proceedings of the Thirty Third International Conference on Information Systems; Orlando, FL, USA, 16–19 December 2012.
- Griffiths, M.D.; Kuss, D.J.; Demetrovics, Z. Social networking addiction: An overview of preliminary findings. Behav. Addict. 2014, 119–141. [Google Scholar] [CrossRef]
- Tsitsika, A.K.; Tzavela, E.C.; Janikian, M.; Ólafsson, K.; Iordache, A.; Schoenmakers, T.M.; Tzavara, C.; Richardson, C. Online social networking in adolescence: Patterns of use in six European countries and links with psychosocial functioning. J. Adolesc. Health 2014, 55, 141–147. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- De Cock, R.; Vangeel, J.; Klein, A.; Minotte, P.; Rosas, O.; Meerkerk, G.-J. Compulsive use of social networking sites in Belgium: Prevalence, profile, and the role of attitude toward work and school. Cyberpsychol. Behav. Soc. Netw. 2014, 17, 166–171. [Google Scholar] [CrossRef] [PubMed]
- Kuss, D.J.; Shorter, G.W.; van Rooij, A.J.; Griffiths, M.D.; Schoenmakers, T.M. Assessing internet addiction using the parsimonious internet addiction components model—A preliminary study. Int. J. Ment. Health Addict. 2014, 12, 351–366. [Google Scholar] [CrossRef] [Green Version]
- Valk, S.L.; Hoffstaedter, F.; Camilleri, J.A.; Kochunov, P.; Yeo, B.T.T.; Eickhoff, S.B. Personality and local brain structure: Their shared genetic basis and reproducibility. Neuroimage 2020, 220, 117067. [Google Scholar] [CrossRef]
- American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders (DSM-5®); American Psychiatric Pub: Washington, DC, USA, 2013; ISBN 0890425574. [Google Scholar]
- World Health Organization. International Classification of Diseases, 11th ed.; WHO: Geneva, Switzerland, 2019. [Google Scholar]
- Grant, J.E.; Chamberlain, S.R. Expanding the definition of addiction: DSM-5 vs. ICD-11. CNS Spectr. 2016, 21, 300–303. [Google Scholar] [CrossRef] [Green Version]
- Grant, J.E.; Chamberlain, S.R. Gambling disorder and its relationship with substance use disorders: Implications for nosological revisions and treatment. Am. J. Addict. 2015, 24, 126–131. [Google Scholar] [CrossRef]
- Dong, G.; Huang, J.; Du, X. Enhanced reward sensitivity and decreased loss sensitivity in Internet addicts: An fMRI study during a guessing task. J. Psychiatr. Res. 2011, 45, 1525–1529. [Google Scholar] [CrossRef]
- Kuss, D.J.; Shorter, G.W.; van Rooij, A.J.; van de Mheen, D.; Griffiths, M.D. The Internet addiction components model and personality: Establishing construct validity via a nomological network. Comput. Human Behav. 2014, 39, 312–321. [Google Scholar] [CrossRef]
- Kuss, D.J.; Van Rooij, A.J.; Shorter, G.W.; Griffiths, M.D.; van de Mheen, D. Internet addiction in adolescents: Prevalence and risk factors. Comput. Human Behav. 2013, 29, 1987–1996. [Google Scholar] [CrossRef] [Green Version]
- Wu, X.; Chen, X.; Han, J.; Meng, H.; Luo, J.; Nydegger, L.; Wu, H. Prevalence and factors of addictive Internet use among adolescents in Wuhan, China: Interactions of parental relationship with age and hyperactivity-impulsivity. PLoS ONE 2013, 8, e61782. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Dalbudak, E.; Evren, C.; Aldemir, S.; Taymur, I.; Evren, B.; Topcu, M. The impact of sensation seeking on the relationship between attention deficit/hyperactivity symptoms and severity of Internet addiction risk. Psychiatry Res. 2015, 228, 156–161. [Google Scholar] [CrossRef] [PubMed]
- Ko, C.-H.; Yen, J.-Y.; Chen, C.-C.; Chen, S.-H.; Wu, K.; Yen, C.-F. Tridimensional personality of adolescents with internet addiction and substance use experience. Can. J. Psychiatry 2006, 51, 887–894. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Blachnio, A.; Przepiorka, A.; Díaz-Morales, J.F. Facebook use and chronotype: Results of a cross-sectional study. Chronobiol. Int. 2015, 32, 1315–1319. [Google Scholar] [CrossRef] [PubMed]
- Costa, P.T.; McCrae, R.R. Neo Personality Inventory-Revised (NEO PI-R); Psychological Assessment Resources: Odessa, TX, USA, 1992. [Google Scholar]
- Kornør, H.; Nordvik, H. Five-factor model personality traits in opioid dependence. BMC Psychiatry 2007, 7, 37. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Costa, P.T.; McCrae, R.R. Longitudinal stability of adult personality. In Handbook of Personality Psychology; Elsevier: Amsterdam, The Netherlands, 1997; pp. 269–290. [Google Scholar]
- Feher, A.; Vernon, P.A. Looking beyond the Big Five: A selective review of alternatives to the Big Five model of personality. Pers. Individ. Dif. 2021, 169, 110002. [Google Scholar] [CrossRef]
- Ashton, M.C.; Lee, K.; Perugini, M.; Szarota, P.; De Vries, R.E.; Di Blas, L.; Boies, K.; De Raad, B. A six-factor structure of personality-descriptive adjectives: Solutions from psycholexical studies in seven languages. J. Pers. Soc. Psychol. 2004, 86, 356. [Google Scholar] [CrossRef]
- Ashton, M.C.; Lee, K. Empirical, theoretical, and practical advantages of the HEXACO model of personality structure. Personal. Soc. Psychol. Rev. 2007, 11, 150–166. [Google Scholar] [CrossRef] [Green Version]
- Paunonen, S.V. Design and construction of the Supernumerary Personality Inventory. In Research Bulletin; University of Western Ontario: London, UK, 2002; Volume 763. [Google Scholar]
- Cloninger, C.R.; Svrakic, D.M.; Przybeck, T.R. A psychobiological model of temperament and character. Arch. Gen. Psychiatry 1993, 50, 975–990. [Google Scholar] [CrossRef]
- Buckels, E.E.; Jones, D.N.; Paulhus, D.L. Behavioral confirmation of everyday sadism. Psychol. Sci. 2013, 24, 2201–2209. [Google Scholar] [CrossRef]
- Bar-On, R.; Brown, J.M.; Kirkcaldy, B.D.; Thome, E.P. Emotional expression and implications for occupational stress; an application of the Emotional Quotient Inventory (EQ-i). Pers. Individ. Dif. 2000, 28, 1107–1118. [Google Scholar] [CrossRef]
- Petrides, K.V. Psychometric properties of the trait emotional intelligence questionnaire (TEIQue). In Assessing Emotional Intelligence; Springer: Berlin/Heidelberg, Germany, 2009; pp. 85–101. [Google Scholar]
- Digman, J.M. Personality structure: Emergence of the five-factor model. Annu. Rev. Psychol. 1990, 41, 417–440. [Google Scholar] [CrossRef]
- Goldberg, L.R. The structure of phenotypic personality traits. Am. Psychol. 1993, 48, 26. [Google Scholar] [CrossRef] [PubMed]
- McCrae, R.R.; Costa, P.T. Personality trait structure as a human universal. Am. Psychol. 1997, 52, 509. [Google Scholar] [CrossRef] [PubMed]
- Wiggins, J.S. The Five-Factor Model of Personality: Theoretical Perspectives; Guilford Press: New York, NY, USA, 1996; ISBN 157230068X. [Google Scholar]
- Wiggins, J.S.; Trapnell, P.D. Personality structure: The return of the Big Five. In Handbook of Personality Psychology; Elsevier: Amsterdam, The Netherlands, 1997; pp. 737–765. [Google Scholar]
- Asendorpf, J.B.; Van Aken, M.A.G. Validity of Big Five personality judgments in childhood: A 9 year longitudinal study. Eur. J. Pers. 2003, 17, 1–17. [Google Scholar] [CrossRef] [Green Version]
- Shiner, R.L. Linking childhood personality with adaptation: Evidence for continuity and change across time into late adolescence. J. Pers. Soc. Psychol. 2000, 78, 310. [Google Scholar] [CrossRef]
- Operto, F.F.; Pastorino, G.M.G.; Marciano, J.; de Simone, V.; Volini, A.P.; Olivieri, M.; Buonaiuto, R.; Vetri, L.; Viggiano, A.; Coppola, G. Digital Devices Use and Language Skills in Children between 8 and 36 Month. Brain Sci. 2020, 10, 656. [Google Scholar] [CrossRef]
- Huey, S.J., Jr.; Weisz, J.R. Ego control, Ego resiliency, and the Five-Factor Model as predictors of behavioral and emotional problems in clinic-referred children and adolescents. J. Abnorm. Psychol. 1997, 106, 404. [Google Scholar] [CrossRef]
- Robins, J.M. Correcting for non-compliance in randomized trials using structural nested mean models. Commun. Stat. Methods 1994, 23, 2379–2412. [Google Scholar] [CrossRef]
- Nevid, J.S.; Gordon, A.J.; Miele, A.S.; Keating, L.H. Personality Profiles of Individuals with Substance Use Disorders: Historical Overview and Current Directions. J. Ment. Health Clin. Psychol. 2020, 4, 38–44. [Google Scholar] [CrossRef]
- Jorgenson, A.G.; Hsiao, R.C.-J.; Yen, C.-F. Internet addiction and other behavioral addictions. Child Adolesc. Psychiatr. Clin. 2016, 25, 509–520. [Google Scholar] [CrossRef] [PubMed]
- Derevensky, J.L.; Hayman, V.; Gilbeau, L. Behavioral addictions: Excessive gambling, gaming, Internet, and smartphone use among children and adolescents. Pediatr. Clin. 2019, 66, 1163–1182. [Google Scholar]
- Kuss, D.J.; Griffiths, M.D. Social networking sites and addiction: Ten lessons learned. Int. J. Environ. Res. Public Health 2017, 14, 311. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Romano, J.L. Prevention in the twenty-first century: Promoting health and well-being in education and psychology. Asia Pac. Educ. Rev. 2014, 15, 417–426. [Google Scholar] [CrossRef]
- Griffiths, M. Internet addiction: Fact or fiction? Psychologist 1999, 12, 246–250. [Google Scholar]
- Carotenuto, M.; Ruberto, M.; Fontana, M.L.; Catania, A.; Misuraca, E.; Precenzano, F.; Lanzara, V.; Messina, G.; Roccella, M.; Smirni, D. Executive functioning in autism spectrum disorders: A case-control study in preschool children. Curr. Pediatric. Res. 2019, 23, 112–116. [Google Scholar]
- Operto, F.F.; Smirni, D.; Scuoppo, C.; Padovano, C.; Vivenzio, V.; Quatrosi, G.; Carotenuto, M.; Precenzano, F.; Maria, G.; Pastorino, G. Neuropsychological Profile, Emotional/Behavioral Problems, and Parental Stress in Children with Neurodevelopmental Disorders. Brain Sci. 2021, 11, e584. [Google Scholar] [CrossRef]
- Liberati, M.; Tetzlaff, J.; Altman, D.G.; the PRISMA Group. Preferred Reporting items for systematic reviews and meta analyses: THE PRISMA statement. PLoS Med. 2009, 151, 264–269. [Google Scholar]
- Aromataris, E.; Fernandez, R.; Godfrey, C.M.; Holly, C.; Khalil, H.; Tungpunkom, P. Summarizing systematic reviews: Methodological development, conduct and reporting of an umbrella review approach. JBI Evid. Implement. 2015, 13, 132–140. [Google Scholar] [CrossRef] [Green Version]
- Wehrli, S. Personality on social network sites: An application of the five factor model. (Working Pap. No. 7); ETH Sociology: Zurich, Switzerland, 2008. [Google Scholar]
- Goldberg, I. Internet addiction disorder. CyberPsychol. Behav. 1996, 3, 403–412. [Google Scholar]
- Young, K. Internet addiction: The emergence of a new clinical disorder. Cyber Psychol. Behav. 1996, 3, 237–244. [Google Scholar] [CrossRef] [Green Version]
- Young, K.S. Psychology of computer use: XL. Addictive use of the Internet: A case that breaks the stereotype. Psychol. Rep. 1996, 79, 899–902. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Costa, P.T.; McCrae, R.R. Normal Personality Assessment in Clinical Practice: The NEO Personality Inventory. Psychol. Assess. 1992, 4, 5–13. [Google Scholar] [CrossRef]
- Montag, C.; Flierl, M.; Markett, S.; Walter, N.; Jurkiewicz, M.; Reuter, M. Internet addiction and personality in first-person-shooter video gamers. J. Media Psychol. 2012, 23, 163–173. [Google Scholar] [CrossRef]
- Jiménez-Murcia, S.; Fernández-Aranda, F.; Granero, R.; Chóliz, M.; La Verde, M.; Aguglia, E.; Signorelli, M.S.; Sá, G.M.; Aymamí, N.; Gómez-Peña, M. Video game addiction in gambling disorder: Clinical, psychopathological, and personality correlates. BioMed Res. Int. 2014, 2014, 315062. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Mehroof, M.; Griffiths, M.D. Online gaming addiction: The role of sensation seeking, self-control, neuroticism, aggression, state anxiety, and trait anxiety. Cyberpsychol. Behav. Soc. Netw. 2010, 13, 313–316. [Google Scholar] [CrossRef] [PubMed]
- Li, H.; Zou, Y.; Wang, J.; Yang, X. Role of stressful life events, avoidant coping styles, and neuroticism in online game addiction among college students: A moderated mediation model. Front. Psychol. 2016, 7, 1794. [Google Scholar] [CrossRef] [Green Version]
- Andreassen, C.S.; Griffiths, M.D.; Gjertsen, S.R.; Krossbakken, E.; Kvam, S.; Pallesen, S. The relationships between behavioral addictions and the five-factor model of personality. J. Behav. Addict. 2013, 2, 90–99. [Google Scholar] [CrossRef] [Green Version]
- Kuss, D.J.; Griffiths, M.D.; Binder, J.F. Internet addiction in students: Prevalence and risk factors. Comput. Human Behav. 2013, 29, 959–966. [Google Scholar] [CrossRef] [Green Version]
- Müller, K.W.; Koch, A.; Dickenhorst, U.; Beutel, M.E.; Duven, E.; Wölfling, K. Addressing the question of disorder-specific risk factors of internet addiction: A comparison of personality traits in patients with addictive behaviors and comorbid internet addiction. BioMed Res. Int. 2013, 2013, 546342. [Google Scholar] [CrossRef] [Green Version]
- Müller, K.W.; Beutel, M.E.; Egloff, B.; Wölfling, K. Investigating risk factors for Internet gaming disorder: A comparison of patients with addictive gaming, pathological gamblers and healthy controls regarding the big five personality traits. Eur. Addict. Res. 2014, 20, 129–136. [Google Scholar] [CrossRef]
- Wang, C.-W.; Ho, R.T.H.; Chan, C.L.W.; Tse, S. Exploring personality characteristics of Chinese adolescents with internet-related addictive behaviors: Trait differences for gaming addiction and social networking addiction. Addict. Behav. 2015, 42, 32–35. [Google Scholar] [CrossRef]
- Wittek, C.T.; Finserås, T.R.; Pallesen, S.; Mentzoni, R.A.; Hanss, D.; Griffiths, M.D.; Molde, H. Prevalence and predictors of video game addiction: A study based on a national representative sample of gamers. Int. J. Ment. Health Addict. 2016, 14, 672–686. [Google Scholar] [CrossRef] [Green Version]
- Vaghefi, I.; Qahri-Saremi, H. Personality predictors of IT addiction. In Proceedings of the 51st Hawaii International Conference on System Sciences, Hilton Waikoloa Village, HI, USA, 3–6 January 2018. [Google Scholar]
- Reyes, M.E.S.; Davis, R.D.; Lim, R.A.N.N.; Lim, K.R.S.; Paulino, R.F.; Carandang, A.M.D.; Azarraga, M.G.S. Five-factor model traits as predictors of pathological gaming among selected Filipino gamers. Psychol. Stud. 2019, 64, 213–220. [Google Scholar] [CrossRef]
- Dieris-Hirche, J.; Pape, M.; te Wildt, B.T.; Kehyayan, A.; Esch, M.; Aicha, S.; Herpertz, S.; Bottel, L. Problematic gaming behavior and the personality traits of video gamers: A cross-sectional survey. Comput. Human Behav. 2020, 106, 106272. [Google Scholar] [CrossRef]
- Barker, V. Older adolescents’ motivations for social network site use: The influence of gender, group identity, and collective self-esteem. Cyberpsychol. Behav. 2009, 12, 209–213. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kraut, R.; Patterson, M.; Lundmark, V.; Kiesler, S.; Mukophadhyay, T.; Scherlis, W. Internet paradox: A social technology that reduces social involvement and psychological well-being? Am. Psychol. 1998, 53, 1017. [Google Scholar] [CrossRef] [PubMed]
- Gentile, D.A.; Swing, E.L.; Lim, C.G.; Khoo, A. Video game playing, attention problems, and impulsiveness: Evidence of bidirectional causality. Psychol. Pop. Media Cult. 2012, 1, 62–70. [Google Scholar] [CrossRef] [Green Version]
- King, D.L.; Delfabbro, P.H.; Griffiths, M.D.; Gradisar, M. Assessing clinical trials of Internet addiction treatment: A systematic review and CONSORT evaluation. Clin. Psychol. Rev. 2011, 31, 1110–1116. [Google Scholar] [CrossRef] [PubMed]
- Vu, D. An Analysis of Operant Conditioning and its Relationship with Video Game Addiction. 2017. Available online: https://scholarworks.sjsu.edu/art108/6/ (accessed on 24 February 2023).
- Bushman, B.J. “Boom, Headshot!”: Violent first-person shooter (FPS) video games that reward headshots train individuals to aim for the head when shooting a realistic firearm. Aggress. Behav. 2019, 45, 33–41. [Google Scholar] [CrossRef]
- Costa, P.T.; McCrae, R.R. The Revised NEO Personality Inventory (NEO-PI-R); Sage Publications Inc.: London, UK, 2008; Volume 2. [Google Scholar] [CrossRef]
- Marwaha, S.; He, Z.; Broome, M.; Singh, S.P.; Scott, J.; Eyden, J.; Wolke, D. How is affective instability defined and measured? A systematic review. Psychol. Med. 2014, 44, 1793–1808. [Google Scholar] [CrossRef] [PubMed]
- Graham, L.T.; Gosling, S.D. Personality profiles associated with different motivations for playing World of Warcraft. Cyberpsychol Behav. Soc. Netw. 2013, 16, 189–193. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Liao, Z.; Huang, Q.; Huang, S.; Tan, L.; Shao, T.; Fang, T.; Chen, X.; Lin, S.; Qi, J.; Cai, Y. Prevalence of Internet Gaming Disorder and Its Association With Personality Traits and Gaming Characteristics Among Chinese Adolescent Gamers. Front. Psychiatry 2020, 11, 1266. [Google Scholar] [CrossRef] [PubMed]
- Kuss, D.J.; Griffiths, M.D. Internet and gaming addiction: A systematic literature review of neuroimaging studies. Brain Sci. 2012, 2, 347–374. [Google Scholar] [CrossRef]
- Cruz Gonzalez, P.; Fong, K.N.K.; Brown, T. The effects of transcranial direct current stimulation on the cognitive functions in older adults with mild cognitive impairment: A pilot study. Behav. Neurol. 2018, 2018, 5971385. [Google Scholar] [CrossRef] [Green Version]
- Verweij, K.J.H.; Yang, J.; Lahti, J.; Veijola, J.; Hintsanen, M.; Pulkki-Råback, L.; Heinonen, K.; Pouta, A.; Pesonen, A.; Widen, E. Maintenance of genetic variation in human personality: Testing evolutionary models by estimating heritability due to common causal variants and investigating the effect of distant inbreeding. Evol. Int. J. Org. Evol. 2012, 66, 3238–3251. [Google Scholar] [CrossRef] [Green Version]
- Smirni, D.; Smirni, P.; Carotenuto, M.; Parisi, L.; Quatrosi, G.; Roccella, M. Noli Me Tangere: Social Touch, Tactile Defensiveness, and Communication in Neurodevelopmental Disorders. Brain Sci. 2019, 9, 368. [Google Scholar] [CrossRef] [Green Version]
- Genetics of Personality Consortium. Meta-analysis of genome-wide association studies for neuroticism, and the polygenic association with major depressive disorder. JAMA Psychiatry 2015, 72, 642–650. [Google Scholar] [CrossRef] [Green Version]
- Owens, M.M.; Hyatt, C.S.; Gray, J.C.; Carter, N.T.; MacKillop, J.; Miller, J.D.; Sweet, L.H. Cortical morphometry of the five-factor model of personality: Findings from the Human Connectome Project full sample. Soc. Cogn. Affect. Neurosci. 2019, 14, 381–395. [Google Scholar] [CrossRef]
- Grasby, K.L.; Jahanshad, N.; Painter, J.N.; Colodro-Conde, L.; Bralten, J.; Hibar, D.P.; Lind, P.A.; Pizzagalli, F.; Ching, C.R.K.; McMahon, M.A.B. The genetic architecture of the human cerebral cortex. Science 2020, 367, eaay6690. [Google Scholar] [CrossRef] [Green Version]
- Kim, N.R.; Hwang, S.S.-H.; Choi, J.-S.; Kim, D.-J.; Demetrovics, Z.; Király, O.; Nagygyörgy, K.; Griffiths, M.D.; Hyun, S.Y.; Youn, H.C. Characteristics and psychiatric symptoms of internet gaming disorder among adults using self-reported DSM-5 criteria. Psychiatry Investig. 2016, 13, 58. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- De Moor, M.H.M.; Costa, P.T.; Terracciano, A.; Krueger, R.F.; De Geus, E.J.C.; Toshiko, T.; Penninx, B.W.J.H.; Esko, T.; Madden, P.A.F.; Derringer, J. Meta-analysis of genome-wide association studies for personality. Mol. Psychiatry 2012, 17, 337–349. [Google Scholar] [CrossRef] [Green Version]
- Lo, M.-T.; Hinds, D.A.; Tung, J.Y.; Franz, C.; Fan, C.-C.; Wang, Y.; Smeland, O.B.; Schork, A.; Holland, D.; Kauppi, K. Genome-wide analyses for personality traits identify six genomic loci and show correlations with psychiatric disorders. Nat. Genet. 2017, 49, 152–156. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Van Den Berg, S.; de Moor, M.H.M.; Verweij, K.J.H.; Krueger, R.F.; Luciano, M.; Vasquez, A.A.; Matteson, L.K.; Derringer, J.; Amin, N.; Gordon, S.D. Meta-analysis of genome-wide association studies for extraversion: Findings from the genetics of personality consortium. Behav. Genet. 2016, 46, 170–182. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Vukasović, T.; Bratko, D. Heritability of personality: A meta-analysis of behavior genetic studies. Psychol. Bull. 2015, 141, 769. [Google Scholar] [CrossRef] [Green Version]
- Johnson, A.M.; Vernon, P.A.; Feiler, A.R. Behavioral genetic studies of personality: An introduction and review of the results of 50+ years of research. SAGE Handb. Personal. Theory Assess. 2008, 1, 145–173. [Google Scholar]
- Van Den Berg, S.; De Moor, M.H.M.; McGue, M.; Pettersson, E.; Terracciano, A.; Verweij, K.J.H.; Amin, N.; Derringer, J.; Esko, T.; Van Grootheest, G. Harmonization of Neuroticism and Extraversion phenotypes across inventories and cohorts in the Genetics of Personality Consortium: An application of Item Response Theory. Behav. Genet. 2014, 44, 295–313. [Google Scholar] [CrossRef] [Green Version]
- Strike, L.T.; Hansell, N.K.; Couvy-Duchesne, B.; Thompson, P.M.; de Zubicaray, G.I.; McMahon, K.L.; Wright, M.J. Genetic complexity of cortical structure: Differences in genetic and environmental factors influencing cortical surface area and thickness. Cereb. Cortex 2019, 29, 952–962. [Google Scholar] [CrossRef]
- Winkler, A.M.; Kochunov, P.; Blangero, J.; Almasy, L.; Zilles, K.; Fox, P.T.; Duggirala, R.; Glahn, D.C. Cortical thickness or grey matter volume? The importance of selecting the phenotype for imaging genetics studies. Neuroimage 2010, 53, 1135–1146. [Google Scholar] [CrossRef] [Green Version]
- Riccelli, R.; Toschi, N.; Nigro, S.; Terracciano, A.; Passamonti, L. Surface-based morphometry reveals the neuroanatomical basis of the five-factor model of personality. Soc. Cogn. Affect. Neurosci. 2017, 12, 671–684. [Google Scholar] [CrossRef] [Green Version]
- DeYoung, C.G.; Hirsh, J.B.; Shane, M.S.; Papademetris, X.; Rajeevan, N.; Gray, J.R. Testing predictions from personality neuroscience: Brain structure and the big five. Psychol. Sci. 2010, 21, 820–828. [Google Scholar] [CrossRef] [PubMed]
- Avinun, R.; Israel, S.; Knodt, A.R.; Hariri, A.R. Little evidence for associations between the big five personality traits and variability in brain gray or white matter. Neuroimage 2020, 220, 117092. [Google Scholar] [CrossRef] [PubMed]
- Masouleh, S.K.; Eickhoff, S.B.; Hoffstaedter, F.; Genon, S.; Initiative, A.D.N. Empirical examination of the replicability of associations between brain structure and psychological variables. eLife 2019, 8, e43464. [Google Scholar] [CrossRef] [PubMed]
Review | Studies Sample | Theorethical Definition of Behavioral Addiction | Personality Model | Main Results |
---|---|---|---|---|
Floros and Siomos 2014 [3] | 40 studies Sample not reported | Excessive Internet use | FFM Eysenck’s PEN model Cloninger’s psychobiological model Zuckerman’s alternative FFM Cattell’s 16 personality factors | Positive correlations with neuroticism, emotional stability, psychoticism, sensation/excitement seeking, and openness. Negative correlations with extraversion, conscientiousness, agreeableness, reward dependence, and self-directedness. |
Kayiş et al., 2016 [4] | 12 studies n = 12019 | Internet addiction | FFM | Positive correlation with neuroticism, negative correlations with openness, conscientiousness, extraversion, and agreeableness. |
Gervasi et al., 2017 [5] | 27 empirical studies n = 36,340 | Online gamers and Internet addicted | FFM | High neuroticism, low agreeableness, extraversion, conscientiousness, and openness |
Şalvarlı and Griffiths, 2019 [6] | 21 empirical studies n = 16,536 | Internet gaming addiction | FFM | High neuroticism, low extroversion, conscientiousness, agreeableness, and openness. Some studies found a positive relationship with neuroticism; others found no relationship. Extraversion was negatively correlated in some studies; in others, it was unrelated. Conflicting results on the relationship with conscientiousness and agreeableness; negative association or no relationship with openness. |
Study | Sample | Addiction Behavior | Personality Traits |
---|---|---|---|
Andreassen et al., 2013 [81] | 218 university students (171 female), mean age 20.7 years ± 3.0 | Facebook, video game, Internet, exercise, mobile phone, compulsive buying, and study addiction | Neuroticism and extraversion positively associated with all the seven behavioral addictions, agreeablenes negatively correlated. Openness negatively associated with Facebook and mobile phone; conscientiousness negatively related to Facebook, video gaming, Internet, buying, and positively to exercise and studying. |
Kuss et al. (2013) [82] | 2257 university students (1.438 females) mean age 22.67 ± 6.34 range 18–64 | Internet gaming | Higher neuroticism and low agreeableness associated to Internet addiction; neuroticism was the strongest predictor factor. |
Müller et al., 2013 [83] | 70 male patients mean age 29.3 ± 10.66 range 16–64 | Internet addiction | Low conscientiousness as a risk factor, highest scores in neuroticism in patients with Internet addiction and depression. |
Müller et al., 2014 [84] | 115 internet gaming patients (mean age 22.9 years ± 6.13) 122 pathological gambling (mean age 32.3 years ± 11.53) 167 control subjects mean age 21.0 years ± 6.48 | Internet gaming gambling control group | High neuroticism, low conscientiousness, and low extraversion were characteristics of Internet gaming disorder, low conscientiousness was the strongest predictor. Internet gaming patients displayed lower extraversion than all the other groups, including pathological gamblers; gamblers were characterized by elevated extraversion. |
Wang et al. 2015 [85] | 920 Chinese adolescents (583 females) mean age sample 15.03 ± 1.59 females 14.98 ± 1.61 males 15.13 ± 1.56 | Internet use, gaming, and social networking | Higher neuroticism associated with Internet and social networking addiction but not gaming addiction. Low openness mildly significantly associated with gaming. Low conscientiousness significantly associated with gaming, but not social networking. Extraversion significantly associated with social networking; agreeableness was not related to any outcome measures. |
Wittek et al. (2016) [86] | 3389 gamers (1.351 females) aged 16–74 years mean age = 32.6 years | Video gaming | Video game addiction positively associated with neuroticism and negatively with conscientiousness. No relationship with extraversion and agreeableness. |
Vaghefi and Qahri-Saremi (2018) [87] | 275 students (51% women) mean age 21 ± 5.99 range 18–39 | Social networking sites | Positive effect of neuroticism and negative effect of conscientiousness, while agreeableness was not associated with addiction. High neuroticism displayed an indirect effect on addiction by reducing the moderating effect of conscientiousness. Conscientiousness was negatively associated with addiction, but it also displayed an indirect effect on addiction by moderating the relation between agreeableness and addiction. |
Reyes et al. (2019) [88] | 1026 (491 females) mean age 23.57 ± 4.72 | Gaming disorder | Neuroticism positively correlated with pathological gaming, the remaining Big Five personality traits were negatively correlated. Conscientiousness was the strongest predictor of pathological gaming. |
Dieris-Hirche et al. (2020) [89] | 820 video gamers (217 female) between the ages 12 and 66 (M = 25.25 ± 10.31). | Internet gaming disorder | High neuroticism and low conscientiousness were significant predictors for Internet gaming disorder. Problematic gamers showed significantly higher neuroticism and lower self-efficacy, extraversion, conscientiousness, and openness; no significant difference was found in agreeableness. The largest effects were found for conscientiousness. |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Smirni, D.; Smirni, P.; Lavanco, G.; Caci, B. Premorbid Personality Traits as Risk Factors for Behavioral Addictions: A Systematic Review of a Vulnerability Hypothesis. Children 2023, 10, 467. https://doi.org/10.3390/children10030467
Smirni D, Smirni P, Lavanco G, Caci B. Premorbid Personality Traits as Risk Factors for Behavioral Addictions: A Systematic Review of a Vulnerability Hypothesis. Children. 2023; 10(3):467. https://doi.org/10.3390/children10030467
Chicago/Turabian StyleSmirni, Daniela, Pietro Smirni, Gioacchino Lavanco, and Barbara Caci. 2023. "Premorbid Personality Traits as Risk Factors for Behavioral Addictions: A Systematic Review of a Vulnerability Hypothesis" Children 10, no. 3: 467. https://doi.org/10.3390/children10030467
APA StyleSmirni, D., Smirni, P., Lavanco, G., & Caci, B. (2023). Premorbid Personality Traits as Risk Factors for Behavioral Addictions: A Systematic Review of a Vulnerability Hypothesis. Children, 10(3), 467. https://doi.org/10.3390/children10030467