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Cited by 117Impact of Technology on AdolescentsPersonality Traits and PsychologySexuality, Behavior, and Technology

The DOI matches its Crossref record; 82 of the 84 references it cites were found in a registry or an index; none of the 55 sources its claims cite is checked for support yet.

The dark side of internet: Preliminary evidence for the associations of dark personality traits with specific online activities and problematic internet use

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Kircaburun, Kagan, Griffiths, Mark D.·2018·Journal of Behavioral Addictions
DOI 10.1556/2006.7.2018.109PMC PMC6376394
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Abstract

Background and aims: Research has shown that personality traits play an important role in problematic internet use (PIU). However, the relationship between dark personality traits (i.e., Machiavellianism, psychopathy, narcissism, sadism, and spitefulness) and PIU has yet to be investigated. Consequently, the objectives of this study were to investigate the relationships of dark traits with specific online activities (i.e., social media, gaming, gambling, shopping, and sex) and PIU. Methods: A total of 772 university students completed a self-report survey, including the Dark Triad Dirty Dozen Scale, Short Sadistic Impulse Scale, Spitefulness Scale, and an adapted version of the Bergen Facebook Addiction Scale. Results: Hierarchical regression analysis and a multiple mediation model indicated that being male was positively associated with higher online gaming, online sex, and online gambling, and negatively associated with social media and online shopping. Narcissism was related to higher social media use; Machiavellianism was related to higher online gaming, online sex, and online gambling; sadism was related to online sex; and spitefulness was associated with online sex, online gambling, and online shopping. Finally, Machiavellianism and spitefulness were directly and indirectly associated with PIU via online gambling, online gaming, and online shopping, and narcissism was indirectly associated with PIU through social media use. Discussion: Findings of this preliminary study show that individuals high in dark personality traits may be more vulnerable in developing problematic online use and that further research is warranted to examine the associations of dark personality traits with specific types of problematic online activities.

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TL;DR

This cross-sectional study of 772 Turkish university students found that dark personality traits were differentially linked to specific online activities, and some traits were directly and indirectly associated with problematic internet use through those activities. Machiavellianism and spitefulness had direct and indirect associations with PIU via gambling/gaming or gambling/shopping, while narcissism was indirectly associated via social media.

Key findings

  • Being male was positively associated with online gaming (β = 0.35, p < .001), online sex (β = 0.42, p < .001), and online gambling (β = 0.19, p < .001), and negatively with social media (β = −0.16, p < .001) and online shopping (β = −0.13, p < .001); age was associated only with social media use (β = −0.16, p < .001).
  • Narcissism was related to social media use (β = 0.18, p < .001); Machiavellianism was associated with online gaming (β = 0.11, p < .05), online sex (β = 0.09, p < .05), and online gambling (β = 0.14, p < .01); sadism was associated with online sex (β = 0.12, p < .01); spitefulness was associated with online sex (β = 0.10, p < .05), online gambling (β = 0.16, p < .001), and online shopping (β = 0.15, p < .01). Psychopathy was not significantly associated with any specific online activity in the reported hierarchical regressions.
  • In the mediation model, Machiavellianism was directly and indirectly associated with PIU through online gambling and online gaming (total β = 0.12, p < .05); narcissism was indirectly associated with PIU through social media use (β = 0.09, p < .05); spitefulness was directly and indirectly associated with PIU through online gambling and online shopping (β = 0.18, p < .001). The model explained 21% of the variance in PIU.
  • H1 and H3 were partially supported, while findings were not in line with H2.

Methods

  • Cross-sectional, paper-and-pencil self-report survey of 772 Turkish university students (64% female), aged 18–28 years (mean = 20.72, SD = 2.30).
  • Measures included the Dark Triad Dirty Dozen Scale, Short Sadistic Impulse Scale, Spitefulness Scale, and an adapted version of the Bergen Facebook Addiction Scale (Bergen Internet Addiction Scale); a personal information form assessed online gambling, gaming, shopping, social media, and sex use.
  • Analyses used hierarchical regression to predict specific online activities while controlling for gender and age, and a saturated multiple mediation model in AMOS with 5,000 bootstrapped samples and 95% bias-corrected confidence intervals.

Limitations

  • The paper states that data came from self-report questionnaires in a self-selected sample, which are prone to well-known biases; the cross-sectional design prevents drawing causal relationships; and the sample was Turkish undergraduates from a single university, limiting generalizability.
  • The paper also states that most effect sizes between variables were small and describes the study as preliminary.
  • Evident from the text: psychopathy was included in the models but showed no significant associations in the reported regression or mediation results, and the mediation findings cannot establish temporal ordering beyond the authors’ cross-sectional design limitation.

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Integrity signals

Registry

Crossref · 10.1556/2006.7.2018.109

Cites

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Figures

Figure 1. Final model of the significant path coefficients. Gender and age were adjusted for mediator and outcome variables in the model. For clarity, control variables and correlations between independent, control, and mediator variables have not been depicted in the figure. *p < .05. **p < .01. ***p < .001
Figure 1. Final model of the significant path coefficients. Gender and age were adjusted for mediator and outcome variables in the model. For clarity, control variables and correlations between independent, control, and mediator variables have not been depicted in the figure. *p < .05. **p < .01. ***p < .001CC BY-NC · PubMed Central

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40 Own result · 35 Not checked yet · 9 Own method · 4 Own interpretation · 2 No basis given

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  • It may state two separate claims as one. 18
  • The quote only partly states this claim. 1
  • Not yet classified. 1
  • Probably not a substantial claim. 15
32 of 32

  • The authors state this as an assumption.

    Engaging in online activities relates to higher problematic internet use and accounts for the relationships between dark personality traits and problematic internet use.

    “Therefore, it may be that engaging in these aforementioned online activities relate to higher PIU and account for the relationships between dark personality traits and PIU. Some empirical evidence appears to support this assumption”

  • The paper relies on this without support.

    No study has ever considered five different traits (the Dark Triad plus sadism and spitefulness) with uses of different online activities and problematic internet use simultaneously.

    “However, no study has ever considered five different traits (i.e., the Dark Triad in addition to sadism and spitefulness) with uses of different online activities and PIU simultaneously.”

  • The paper relies on this without support.

    The relationship between dark personality traits and problematic internet use has yet to be investigated.

    “However, the relationship between dark personality traits (i.e., Machiavellianism, psychopathy, narcissism, sadism, and spitefulness) and PIU has yet to be investigated.”

  • The authors state this as an assumption.

    This study is the first to investigate the direct and indirect associations of dark personality traits with problematic Internet use through specific online activities.

    “To the best of authors’ knowledge, this is the first study to investigate the direct and indirect associations of dark personality traits (i.e., Machiavellianism, psychopathy, narcissism, sadism, and spitefulness) with PIU through specific online activities (i.e., social media, online gaming, online gambling, online shopping, and online sex).”
    “Despite the limitations, this is the first study to examine the relationships between dark personality traits, specific online activities, and PIU.”
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Citations

Cites

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Research works printed but not linked: 80

  1. James, 2014, The Dark Triad, schadenfreude, and sensational interests: Dark personalities, dark emotions, and dark behaviors, Personality and Individual Differences,, 68,, 211, 10.1016/j.paid.2014.04.020 · DOI
  2. Gaskin, 2016, Gaskination’s statistics
  3. Griffiths, 2000, Internet addiction – Time to be taken seriously?, Addiction Research,, 8, 413, 10.3109/16066350009005587 · DOI · Paper page
  4. Stavropoulos, 2017, MMORPG gaming and hostility predict Internet addiction symptoms in adolescents: An empirical multilevel longitudinal study, Addictive Behaviors,, 64,, 294, 10.1016/j.addbeh.2015.09.001 · DOI
  5. Kayiş, 2016, Big Five-personality trait and Internet addiction: A meta-analytic review, Computers in Human Behavior,, 63,, 35, 10.1016/j.chb.2016.05.012 · DOI · Paper page
  6. Kopuničová, 2016, Personality, depression and problematic Internet use, Psychology and its Contexts,, 7, 81
  7. Gaskin, 2016, Gaskination’s statistics
  8. Griffiths, 2005, A ‘components’ model of addiction within a biopsychosocial framework, Journal of Substance Use,, 10, 191, 10.1080/14659890500114359 · DOI · Paper page
  9. Vitacco, 2001, Predictors of adolescent psychopathy: The role of impulsivity, hyperactivity, and sensation seeking, Journal of the American Academy of Psychiatry and the Law,, 29, 374
  10. Greitemeyer, 2017, The longitudinal relationship between everyday sadism and the amount of violent video game play, Personality and Individual Differences,, 104,, 238, 10.1016/j.paid.2016.08.021 · DOI
  11. van Geel, 2017, Which personality traits are related to traditional bullying and cyberbullying? A study with the Big Five, Dark Triad and sadism, Personality and Individual Differences,, 106,, 231, 10.1016/j.paid.2016.10.063 · DOI
  12. Kırcaburun, 2018, Problematic online behaviors among adolescents and emerging adults: Associations between cyberbullying perpetration, problematic social media use, and psychosocial factors, International Journal of Mental Health and Addiction
  13. Jonason, 2013, The emotional deficits associated with the Dark Triad traits: Cognitive empathy, affective empathy, and alexithymia, Personality and Individual Differences,, 55, 532, 10.1016/j.paid.2013.04.027 · DOI · Paper page
  14. Dalbudak, 2014, The severity of Internet addiction risk and its relationship with the severity of borderline personality features, childhood traumas, dissociative experiences, depression and anxiety symptoms among Turkish university students, Psychiatry Research,, 219, 577, 10.1016/j.psychres.2014.02.032 · DOI · Paper page
  15. Tosuntaş, 2018, A new phenomenon among emerging adults: Sofalizing and its relationship with social media addiction and psychosocial risk factors
  16. George, 2010, SPSS for windows step by step: A simple guide and reference, 17.0 update
  17. Mann, 2017, Behavioural addictions: Classification and consequences, European Psychiatry,, 44,, 187, 10.1016/j.eurpsy.2017.04.008 · DOI
  18. Jonason, 2010, The dirty dozen: A concise measure of the Dark Triad, Psychological Assessment,, 22, 420, 10.1037/a0019265 · DOI · Paper page
  19. Gervasi, 2017, Maladaptive personality traits and Internet addiction symptoms among young adults: A study based on the alternative DSM-5 model for personality disorders, Clinical Neuropsychiatry,, 14, 20
  20. Christie, 1970, Studies in Machiavellianism
  21. Tabachnick, 2001, Using multivariate statistics
  22. Buckels, 2014, Trolls just want to have fun, Personality and Individual Differences,, 67,, 97, 10.1016/j.paid.2014.01.016 · DOI · Paper page
  23. Casale, 2016, Grandiose and vulnerable narcissists: Who is at higher risk for social networking addiction?, Cyberpsychology, Behavior, and Social Networking,, 19, 510, 10.1089/cyber.2016.0189 · DOI
  24. Marcus, 2014, The psychology of spite and the measurement of spitefulness, Psychological Assessment,, 26, 563, 10.1037/a0036039 · DOI
  25. Alexandraki, 2018, Internet pornography viewing preference as a risk factor for adolescent Internet addiction: The moderating role of classroom personality factors, Journal of Behavioral Addictions,, 7, 423, 10.1556/2006.7.2018.34 · DOI
  26. Shim, 2007, Who responds to unsolicited sexually explicit materials on the Internet? The role of individual differences, CyberPsychology & Behavior,, 10, 71, 10.1089/cpb.2006.9990 · DOI
  27. Zeigler-Hill, 2018, Characterizing spitefulness in terms of the DSM-5 model of pathological personality traits, Current Psychology,, 37, 14, 10.1007/s12144-016-9484-5 · DOI
  28. Kardefelt-Winther, 2014, A conceptual and methodological critique of Internet addiction research: Towards a model of compensatory Internet use, Computers in Human Behavior,, 31,, 351, 10.1016/j.chb.2013.10.059 · DOI · Paper page
  29. O’Meara, 2011, The psychometric properties and utility of the Short Sadistic Impulse Scale (SSIS), Psychological Assessment,, 23,, 523, 10.1037/a0022400 · DOI
  30. Kircaburun, 2018b, The Dark Tetrad traits and problematic online gaming: The mediating role of online gaming motives and moderating role of game types, Personality and Individual Differences,, 135,, 298, 10.1016/j.paid.2018.07.038 · DOI
  31. Tran, 2018, “I’ll teach you differences”: Taxometric analysis of the Dark Triad, trait sadism, and the Dark Core of personality, Personality and Individual Differences,, 126,, 19, 10.1016/j.paid.2018.01.015 · DOI
  32. Arpaci, 2018, The moderating effect of gender in the relationship between narcissism and selfie-posting behavior, Personality and Individual Differences,, 134,, 71, 10.1016/j.paid.2018.06.006 · DOI · Paper page
  33. Birkás, 2015, Nothing ventured nothing gained: Strong associations between reward sensitivity and two measures of Machiavellianism, Personality and Individual Differences,, 74,, 112, 10.1016/j.paid.2014.09.046 · DOI
  34. Smoker, 2017, Predicting perpetration of intimate partner cyberstalking: Gender and the Dark Tetrad, Computers in Human Behavior,, 72,, 390, 10.1016/j.chb.2017.03.012 · DOI · Paper page
  35. Garcia, 2014, The dark side of Facebook: Semantic representations of status updates predict the Dark Triad of personality, Personality and Individual Differences,, 67,, 92, 10.1016/j.paid.2013.10.001 · DOI · Paper page
  36. Zeigler-Hill, 2015, Spitefulness and moral values, Personality and Individual Differences,, 77,, 86, 10.1016/j.paid.2014.12.050 · DOI
  37. Ostovar, 2016, Internet addiction and its psychosocial risks (depression, anxiety, stress and loneliness) among Iranian adolescents and young adults: A structural equation model in a cross-sectional study, International Journal of Mental Health and Addiction,, 14, 257, 10.1007/s11469-015-9628-0 · DOI
  38. West, 1995, Structural equation models with nonnormal variables: Problems and remedies, 56
  39. Richardson, 2016, Offensive defenses: The mind beneath the mask of the Dark Triad traits, Personality and Individual Differences,, 92,, 148, 10.1016/j.paid.2015.12.039 · DOI
  40. Kircaburun, 2018a, The Dark Tetrad traits and problematic social media use: The mediating role of cyberbullying and cybertrolling, Personality and Individual Differences,, 135,, 264, 10.1016/j.paid.2018.07.034 · DOI
  41. Andreassen, 2012, Development of a Facebook Addiction Scale, Psychological Reports,, 110, 501, 10.2466/02.09.18.pr0.110.2.501-517 · DOI · Paper page
  42. Austin, 2007, Emotional intelligence, Machiavellianism and emotional manipulation: Does EI have a dark side?, Personality and Individual Differences,, 43, 179, 10.1016/j.paid.2006.11.019 · DOI · Paper page
  43. Abell, 2014, Machiavellianism, self-monitoring, self-promotion and relational aggression on Facebook, Computers in Human Behavior,, 36,, 258, 10.1016/j.chb.2014.03.076 · DOI · Paper page
  44. Lin, 2002, Sensation seeking and Internet dependence of Taiwanese high school adolescents, Computers in Human Behavior,, 18, 411, 10.1016/s0747-5632(01)00056-5 · DOI
  45. Anderson, 2017, Internet use and problematic Internet use: A systematic review of longitudinal research trends in adolescence and emergent adulthood, International Journal of Adolescence and Youth,, 22, 430, 10.1080/02673843.2016.1227716 · DOI · Paper page
  46. Panek, 2013, Mirror or megaphone?: How relationships between narcissism and social networking site use differ on Facebook and Twitter, Computers in Human Behavior,, 29, 2004, 10.1016/j.chb.2013.04.012 · DOI
  47. Ladanyi, 2017, The development and validation of the Grief Play Scale (GPS) in MMORPGs, Personality and Individual Differences,, 114,, 125, 10.1016/j.paid.2017.03.062 · DOI
  48. Baughman, 2014, Four shades of sexual fantasies linked to the Dark Triad, Personality and Individual Differences,, 67,, 47, 10.1016/j.paid.2014.01.034 · DOI
  49. Vrabel, 2017, Spitefulness and humor styles, Personality and Individual Differences,, 105,, 238, 10.1016/j.paid.2016.10.001 · DOI
  50. Jonason, 2013, Different routes to limited empathy in the sexes: Examining the links between the Dark Triad and empathy, Personality and Individual Differences,, 54, 572, 10.1016/j.paid.2012.11.009 · DOI
  51. Andreassen, 2017, The relationship between addictive use of social media, narcissism, and self-esteem: Findings from a large national survey, Addictive Behaviors,, 64,, 287, 10.1016/j.addbeh.2016.03.006 · DOI · Paper page
  52. Craker, 2016, The dark side of Facebook®: The Dark Tetrad, negative social potency, and trolling behaviours, Personality and Individual Differences,, 102,, 79, 10.1016/j.paid.2016.06.043 · DOI
  53. Lu, 2017, Relationship between borderline personality symptoms and Internet addiction: The mediating effects of mental health problems, Journal of Behavioral Addictions,, 6, 434, 10.1556/2006.6.2017.053 · DOI
  54. Brand, 2016, Integrating psychological and neurobiological considerations regarding the development and maintenance of specific Internet-use disorders: An Interaction of Person-Affect-Cognition-Execution (I-PACE) model, Neuroscience and Biobehavioral Reviews,, 71,, 252, 10.1016/j.neubiorev.2016.08.033 · DOI · Paper page
  55. Jonason, 2017, Good v. evil: Predicting sinning with dark personality traits and moral foundations, Personality and Individual Differences,, 104,, 180, 10.1016/j.paid.2016.08.002 · DOI
  56. Király, 2014, Problematic Internet use and problematic online gaming are not the same: Findings from a large nationally representative adolescent sample, Cyberpsychology, Behavior, and Social Networking,, 17, 749, 10.1089/cyber.2014.0475 · DOI · Paper page
  57. Paulhus, 2002, The Dark Triad of personality: Narcissism, Machiavellianism, and psychopathy, Journal of Research in Personality,, 36, 556, 10.1016/s0092-6566(02)00505-6 · DOI · Paper page
  58. Jones, 2013, The core of darkness: Uncovering the heart of the Dark Triad, European Journal of Personality,, 27, 521, 10.1002/per.1893 · DOI
  59. Pantic, 2017, Association between physiological oscillations in self-esteem, narcissism and Internet addiction: A cross-sectional study, Psychiatry Research,, 258,, 239, 10.1016/j.psychres.2017.08.044 · DOI · Paper page
  60. Kuss, 2014, Internet addiction: A systematic review of epidemiological research for the last decade, Current Pharmaceutical Design,, 20, 4026, 10.2174/13816128113199990617 · DOI · Paper page
  61. Tosuntaş, 2018, A new phenomenon among emerging adults: Sofalizing and its relationship with social media addiction and psychosocial risk factors
  62. Kircaburun, 2018, Analyzing the links between problematic social media use, Dark Triad traits, and self-esteem, International Journal of Mental Health and Addiction
  63. Niemz, 2005, Prevalence of pathological Internet use among university students and correlations with self-esteem, the General Health Questionnaire (GHQ), and disinhibition, CyberPsychology & Behavior,, 8, 562, 10.1089/cpb.2005.8.562 · DOI
  64. Corry, 2008, The factor structure of the Narcissistic Personality Inventory, Journal of Personality Assessment,, 90, 593, 10.1080/00223890802388590 · DOI
  65. Kline, 2011, Principles and practices of structural equation modeling
  66. Spada, 2014, An overview of problematic Internet use, Addictive Behaviors,, 39, 3, 10.1016/j.addbeh.2013.09.007 · DOI
  67. Fox, 2015, The Dark Triad and trait self-objectification as predictors of men’s use and self-presentation behaviors on social networking sites, Personality and Individual Differences,, 76,, 161, 10.1016/j.paid.2014.12.017 · DOI · Paper page
  68. Douglas, 2012, Distinguishing the Dark Triad: Evidence from the five-factor model and the Hogan development survey, Psychology,, 3, 237, 10.4236/psych.2012.33033 · DOI
  69. Kim, 2008, The relationship between online game addiction and aggression, self-control and narcissistic personality traits, European Psychiatry,, 23, 212, 10.1016/j.eurpsy.2007.10.010 · DOI
  70. Kircaburun, 2018, Uses and gratifications of problematic social media use among university students: A simultaneous examination of the Big Five of personality traits, social media platforms, and social media use motives, International Journal of Mental Health and Addiction
  71. Clempner, 2017, A game theory model for manipulation based on Machiavellianism: Moral and ethical behavior, Journal of Artificial Societies & Social Simulation,, 20, 1, 10.18564/jasss.3301 · DOI
  72. Rauthmann, 2011, Acquisitive or protective self-presentation of dark personalities? Associations among the Dark Triad and self-monitoring, Personality and Individual Differences,, 51, 502, 10.1016/j.paid.2011.05.008 · DOI
  73. Marcus, 2018, A network of dark personality traits: What lies at the heart of darkness?, Journal of Research in Personality,, 73,, 56, 10.1016/j.jrp.2017.11.003 · DOI
  74. Montag, 2015, Is it meaningful to distinguish between generalized and specific Internet addiction? Evidence from a cross-cultural study from Germany, Sweden, Taiwan and China, Asia-Pacific Psychiatry,, 7, 20, 10.1111/appy.12122 · DOI · Paper page
  75. Özsoy, 2017, Reliability and validity of the Turkish versions of Dark Triad Dirty Dozen (DTDD-T), Short Dark Triad (SD3-T), and Single Item Narcissism Scale (SINS-T), Personality and Individual Differences,, 117,, 11, 10.1016/j.paid.2017.05.019 · DOI
  76. Zeigler-Hill, 2015, Dark personality features and emotion dysregulation, Journal of Social and Clinical Psychology,, 34, 692, 10.1521/jscp.2015.34.8.692 · DOI
  77. Egan, 2014, The Dark Triad, happiness and subjective well-being, Personality and Individual Differences,, 67,, 17, 10.1016/j.paid.2014.01.004 · DOI · Paper page
  78. Critselis, 2013, Internet gambling is a predictive factor of Internet addictive behavior among Cypriot adolescents, Journal of Behavioral Addictions,, 2, 224, 10.1556/jba.2.2013.4.5 · DOI
  79. Trumello, 2018, Relationship with parents, emotion regulation, and callous-unemotional traits in adolescents’ Internet addiction, BioMed Research International,, 2018,, 1, 10.1155/2018/7914261 · DOI
  80. Casale, 2018, Why narcissists are at risk for developing Facebook addiction: The need to be admired and the need to belong, Addictive Behaviors,, 76,, 312, 10.1016/j.addbeh.2017.08.038 · DOI

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Metadata

Authors
Kircaburun, K., & Griffiths, M. D.
Affiliations
  • 1 Faculty of Education, Department of Computer and Instructional Technologies, Duzce University, Duzce, Turkey
  • Nottingham Trent University (GB)
ORCID
Griffiths, Mark D.
Venue
Journal of Behavioral Addictions
Publisher
Akademiai Kiado Zrt.
Published
2018-11-14
Volume
7
Issue
4
Pages
993-1003
ISSN
  • 2062-5871 (ISSN-L)
  • 2063-5303
DOI
10.1556/2006.7.2018.109
PMC
PMC6376394
OpenAlex
W2900814476
Semantic Scholar
ed7facb6071eff9828e7f4cefc2a6b4382ea2b6a
Cited by
117
References
84
Citations by year
2026: 9 · 2025: 16 · 2024: 18 · 2023: 16 · 2022: 23 · 2021: 14 · 2020: 12 · 2019: 8 · 2018: 1
FWCI
19.91
Type
journal article
Language
en
Open access
Locations
  • Journal of Behavioral Addictions (publishedVersion)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
  • PubMed Central (publishedVersion, cc-by-nc)
  • PubMed (publishedVersion)
  • Nottingham Trent University's Institutional Repository (Nottingham Trent Repository) (acceptedVersion)
  • Repository of the Academy's Library (Library of the Hungarian Academy of Sciences) (acceptedVersion)
  • DSpace - Düzce (Duzce University) (submittedVersion, cc-by-nc-nd)
Topics
  • Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
  • Social Sciences › Psychology › Clinical Psychology › Personality Traits and Psychology
  • Social Sciences › Psychology › Clinical Psychology › Sexuality, Behavior, and Technology
Keywords
dark personality traits, Machiavellianism, psychopathy, narcissism, sadism, spitefulness, problematic internet use, online games, online gambling, online sex, social media use, online shopping, sexual addiction, gender differences, university students
MeSH terms
Adolescent, Adult, Antisocial Personality Disorder, Consumer Behavior, Female, Gambling, Humans, Machiavellianism, Male, Narcissism, Sadism, Sexual Behavior, Sex Factors, Students, Turkey, Universities, Behavior, Addictive, Video Games, Internet, Young Adult, Social Media

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