Self-Efficacy and Clinical Characteristics in Casual Gamers Compared to Excessive Gaming Users and Non-Gamers in Young Adults
Abstract
:1. Introduction
2. Materials and Methods
2.1. Participants and Procedure
2.2. Measures
2.2.1. DSM-5 Diagnostic Criteria for IGD
2.2.2. Y-IAT
2.2.3. Smartphone Addiction Scale (SAS)
2.2.4. General Self-Efficacy Scale (SES)
2.2.5. Aggression Questionnaire (AQ)
2.2.6. Behavioral Activation System (BAS) and Behavioral Inhibition System (BIS) Scale
2.2.7. Barratt Impulsiveness Scale-11 (BIS-11)
2.2.8. Beck Depression Inventory (BDI-II)
2.2.9. Beck Anxiety Inventory (BAI)
2.2.10. Psychosocial Well-Being Index (PWI)
2.3. Statistical Analyses
2.4. Ethical Approval
3. Results
3.1. Demographic Information
3.2. Comparisons of Self-Efficacy and Clinical Characteristics
3.3. Correlation of Self-Efficacy and Clinical Characteristics in Total Sample
4. Discussion
Author Contributions
Funding
Conflicts of Interest
References
- Mentzoni, R.A.; Brunborg, G.S.; Molde, H.; Myrseth, H.; Skouverøe, K.J.M.; Hetland, J.; Pallesen, S. Problematic Video Game Use: Estimated Prevalence and Associations with Mental and Physical Health. CyberPsychol. Behav. Soc. Netw. 2011, 14, 591–596. [Google Scholar] [CrossRef] [PubMed]
- Lam, L. Internet Gaming Addiction, Problematic Use of the Internet, and Sleep Problems: A Systematic Review. Curr. Psychiatry Rep. 2014, 16, 444. [Google Scholar] [CrossRef] [PubMed]
- Weaver, J.B.; Mays, D.; Weaver, S.S.; Kannenberg, W.; Hopkins, G.L.; Eroĝlu, D.; Bernhardt, J.M. Health-Risk Correlates of Video-Game Playing Among Adults. Am. J. Prev. Med. 2009, 37, 299–305. [Google Scholar] [CrossRef] [PubMed]
- Lemmens, J.S.; Valkenburg, P.M.; Peter, J. Psychosocial causes and consequences of pathological gaming. Comput. Hum. Behav. 2011, 27, 144–152. [Google Scholar] [CrossRef]
- Batthyany, D.; Müller, K.W.; Benker, F.; Woelfling, K. Computer game playing: Clinical characteristics of dependence and abuse among adolescents. Wien. Klin. Wochenschr. 2009, 121, 502–509. [Google Scholar]
- King, D.; Delfabbro, P. Understanding and assisting excessive players of video games: A community psychology perspective. Aust. Community Psychol. 2009, 21, 62–74. [Google Scholar]
- Liu, M.; Peng, W. Cognitive and psychological predictors of the negative outcomes associated with playing MMOGs (massively multiplayer online games). Comput. Hum. Behav. 2009, 25, 1306–1311. [Google Scholar] [CrossRef]
- Peng, W.; Liu, M. Online gaming dependency: A preliminary study in China. CyberPsychol. Behav. Soc. Netw. 2010, 13, 329–333. [Google Scholar] [CrossRef]
- Peters, C.S.; Malesky, L.A., Jr. Problematic Usage among Highly-Engaged Players of Massively Multiplayer Online Role Playing Games. CyberPsychol. Behav. 2008, 11, 481–484. [Google Scholar] [CrossRef]
- Yee, N. The psychology of MMORPGs: Emotional investment, motivations, relationship formation, and problematic usage. In Avatars at Work and Play; Springer: Dordrecht, The Netherlands, 2006; pp. 187–207. [Google Scholar]
- Yee, N. The Demographics, Motivations, and Derived Experiences of Users of Massively Multi-User Online Graphical Environments. Presence Teleoperators Virtual Environ. 2006, 15, 309–329. [Google Scholar] [CrossRef]
- Allison, S.E.; Shockley, T.; Gabbard, G.O.; Von Wahlde, L. The Development of the Self in the Era of the Internet and Role-Playing Fantasy Games. Am. J. Psychiatry 2006, 163, 381–385. [Google Scholar] [CrossRef] [PubMed]
- Chiu, S.-I.; Lee, J.-Z.; Huang, D.-H. Video game addiction in children and teenagers in Taiwan. CyberPsychol. Behav. 2004, 7, 571–581. [Google Scholar] [CrossRef] [PubMed]
- Caplan, S.E.; Williams, D.; Yee, N. Problematic Internet use and psychosocial well-being among MMO players. Comput. Hum. Behav. 2009, 25, 1312–1319. [Google Scholar] [CrossRef]
- 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]
- Ko, C.-H.; Yen, J.-Y.; Chen, C.-C.; Chen, S.-H.; Yen, C.-F. Gender Differences and Related Factors Affecting Online Gaming Addiction among Taiwanese Adolescents. J. Nerv. Ment. Dis. 2005, 193, 273–277. [Google Scholar] [CrossRef] [Green Version]
- Pawlikowski, M.; Brand, M. Excessive Internet gaming and decision making: Do excessive World of Warcraft players have problems in decision making under risky conditions? Psychiatry Res. Neuroimaging 2011, 188, 428–433. [Google Scholar] [CrossRef]
- Chan, P.A.; Rabinowitz, T. A cross-sectional analysis of video games and attention deficit hyperactivity disorder symptoms in adolescents. Ann. Gen. Psychiatry 2006, 5, 16. [Google Scholar] [CrossRef] [Green Version]
- Dworak, M.; Schierl, T.; Bruns, T.; Strüder, H.K. Impact of Singular Excessive Computer Game and Television Exposure on Sleep Patterns and Memory Performance of School-aged Children. Pediatrics 2007, 120, 978–985. [Google Scholar] [CrossRef]
- Achab, S.; Nicolier, M.; Mauny, F.; Monnin, J.; Trojak, B.; Vandel, P.; Sechter, D.; Gorwood, P.; Haffen, E. Massively multiplayer online role-playing games: Comparing characteristics of addict vs non-addict online recruited gamers in a French adult population. BMC Psychiatry 2011, 11, 144. [Google Scholar] [CrossRef] [Green Version]
- Collins, E.I.M.; Freeman, J.; Chamarro-Premuzic, T. Personality traits associated with problematic and non-problematic massively multiplayer online role playing game use. Pers. Individ. Differ. 2012, 52, 133–138. [Google Scholar] [CrossRef]
- Willoughby, T. A short-term longitudinal study of Internet and computer game use by adolescent boys and girls: Prevalence, frequency of use, and psychosocial predictors. Dev. Psychol. 2008, 44, 195–204. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kuss, D.J.; Griffiths, M.D. Internet Gaming Addiction: A Systematic Review of Empirical Research. Int. J. Ment. Health Addict. 2011, 10, 278–296. [Google Scholar] [CrossRef]
- Rho, M.J.; Lee, H.; Lee, T.-H.; Cho, H.; Jung, D.J.; Kim, D.J.; Choi, I.Y. Risk Factors for Internet Gaming Disorder: Psychological Factors and Internet Gaming Characteristics. Int. J. Environ. Res. Public Health 2017, 15, 40. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Braun, B.; Stopfer, J.M.; Müller, K.W.; Beutel, M.E.; Egloff, B. Personality and video gaming: Comparing regular gamers, non-gamers, and gaming addicts and differentiating between game genres. Comput. Hum. Behav. 2016, 55, 406–412. [Google Scholar] [CrossRef]
- Metcalf, O.; Pammer, K. Impulsivity and Related Neuropsychological Features in Regular and Addictive First Person Shooter Gaming. CyberPsychol. Behav. Soc. Netw. 2014, 17, 147–152. [Google Scholar] [CrossRef]
- Thalemann, R.; Wölfling, K.; Grüsser, S.M. Specific cue reactivity on computer game-related cues in excessive gamers. Behav. Neurosci. 2007, 121, 614–618. [Google Scholar] [CrossRef]
- Vauth, R.; Kleim, B.; Wirtz, M.; Corrigan, P.W. Self-efficacy and empowerment as outcomes of self-stigmatizing and coping in schizophrenia. Psychiatry Res. 2007, 150, 71–80. [Google Scholar] [CrossRef]
- Bandura, A.; Freeman, W.H.; Lightsey, R. Self-Efficacy: The Exercise of Control. J. Cogn. Psychother. 1999, 13, 158–166. [Google Scholar] [CrossRef]
- Harrison, A.W.; Rainer, R.K.; Hochwarter, W.A.; Thompson, K.R. Testing the Self-Efficacy—Performance Linkage of Social—Cognitive Theory. J. Soc. Psychol. 1997, 137, 79–87. [Google Scholar] [CrossRef]
- Salomon, G. Television is “easy” and print is “tough”: The differential investment of mental effort in learning as a function of perceptions and attributions. J. Educ. Psychol. 1984, 76, 647. [Google Scholar] [CrossRef]
- DiClemente, C.C. Self-Efficacy and the Addictive Behaviors. J. Soc. Clin. Psychol. 1986, 4, 302–315. [Google Scholar] [CrossRef]
- DiClemente, C.C.; Prochaska, J.O.; Gibertini, M. Self-efficacy and the stages of self-change of smoking. Cogn. Ther. Res. 1985, 9, 181–200. [Google Scholar] [CrossRef]
- Demmel, R.; Beck, B.; Reker, T.; Richter, D. Readiness to Change in a Clinical Sample of Problem Drinkers: Relation to Alcohol Use, Self-Efficacy, and Treatment Outcome. Eur. Addict. Res. 2004, 10, 133–138. [Google Scholar] [CrossRef] [PubMed]
- Linde, J.A.; Jeffery, R.W.; Levy, R.L.; E Sherwood, N.; Utter, J.; Pronk, N.P.; Boyle, R.G. Binge eating disorder, weight control self-efficacy, and depression in overweight men and women. Int. J. Obes. 2004, 28, 418–425. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Purkord, M.; Abolghasemi, A.; Narimani, M.; Rezaee, H. Direct and indirect impact of self-efficacy, impulsivity, behavioral activation-inhibition and social skills on substance abuse in students. Res. Addict. 2013, 7, 11–28. [Google Scholar]
- Ceyhan, A.A.; Ceyhan, E. Loneliness, Depression, and Computer Self-Efficacy as Predictors of Problematic Internet Use. CyberPsychol. Behav. 2008, 11, 699–701. [Google Scholar] [CrossRef]
- Shi, J.; Chen, Z.; Tian, M. Internet Self-Efficacy, the Need for Cognition, and Sensation Seeking as Predictors of Problematic Use of the Internet. CyberPsychol. Behav. Soc. Netw. 2011, 14, 231–234. [Google Scholar] [CrossRef]
- Odacı, H. Risk-taking behavior and academic self-efficacy as variables accounting for problematic internet use in adolescent university students. Child. Youth Serv. Rev. 2013, 35, 183–187. [Google Scholar] [CrossRef]
- Lin, M.-P.; Ko, H.-C.; Wu, J.Y.-W. The Role of Positive/Negative Outcome Expectancy and Refusal Self-Efficacy of Internet Use on Internet Addiction among College Students in Taiwan. CyberPsychol. Behav. 2008, 11, 451–457. [Google Scholar] [CrossRef]
- Festl, R.; Scharkow, M.; Quandt, T. Problematic computer game use among adolescents, younger and older adults. Addiction 2012, 108, 592–599. [Google Scholar] [CrossRef]
- Jeong, E.J.; Kim, D.H. Social Activities, Self-Efficacy, Game Attitudes, and Game Addiction. CyberPsychol. Behav. Soc. Netw. 2011, 14, 213–221. [Google Scholar] [CrossRef] [PubMed]
- Muris, P. Relationships between self-efficacy and symptoms of anxiety disorders and depression in a normal adolescent sample. Pers. Individ. Differ. 2002, 32, 337–348. [Google Scholar] [CrossRef]
- Moeini, B.; Shafii, F.; Hidarnia, A.; Babaii, G.R.; Birashk, B.; Allahverdipour, H. Perceived stress, self-efficacy and its relations to psychological well-being status in Iranian male high school students. Soc. Behav. Pers. Int. J. 2008, 36, 257–266. [Google Scholar] [CrossRef]
- Lee, B.; Lee, C.; Lee, P.; Choi, M.; Namkoong, K. Development of Korean version of alcohol use disorders identification test (AUDIT-K): Its reliability and validity. J. Korean Acad. Addict. Psychiatry 2000, 4, 83–92. [Google Scholar]
- American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders (DSM-5®); American Psychiatric Pub: Washington, DC, USA, 2013. [Google Scholar]
- Ko, C.-H.; Yen, J.-Y.; Chen, S.-H.; Wang, P.-W.; Chen, C.-S.; Yen, C.-F. Evaluation of the diagnostic criteria of Internet gaming disorder in the DSM-5 among young adults in Taiwan. J. Psychiatr. Res. 2014, 53, 103–110. [Google Scholar] [CrossRef]
- Young, K.S. Caught in the Net: How to Recognize the Signs of Internet Addiction—And a Winning Strategy for Recovery; John Wiley & Sons: Hoboken, NJ, USA, 1998. [Google Scholar]
- Lee, K.; Lee, H.-K.; Gyeong, H.; Yu, B.; Song, Y.-M.; Kim, D. Reliability and Validity of the Korean Version of the Internet Addiction Test among College Students. J. Korean Med Sci. 2013, 28, 763–768. [Google Scholar] [CrossRef] [Green Version]
- Shin, K.; Kim, D.; Jung, Y. Development of Korean Smart Phone Addiction Proneness Scale for Youth and Adults; Korean National Information Society Agency: Seoul, Korea, 2011. [Google Scholar]
- Schwarzer, R.; Jerusalem, M. Generalized Self-Efficacy Scale. In Measures in Health Psychology: A User’s Portfolio. Causal and Control Beliefs; Weinman, J., Wright, S., Johnston, M., Eds.; NFER-NELSON: Windsor, UK, 1995; pp. 35–37. [Google Scholar]
- Buss, A.H.; Perry, M. The aggression questionnaire. J. Personal. Soc. Psychol. 1992, 63, 452. [Google Scholar] [CrossRef]
- Seo, S.; Kwon, S. Validation study of the Korean version of the aggression questionnaire. Korean J. Clin. Psychol. 2002, 21, 487–501. [Google Scholar]
- Carver, C.S.; White, T.L. Behavioral inhibition, behavioral activation, and affective responses to impending reward and punishment: The BIS/BAS scales. J. Pers. Soc. Psychol. 1994, 67, 319. [Google Scholar] [CrossRef]
- Patton, J.H.; Stanford, M.S.; Barratt, E.S. Factor structure of the Barratt impulsiveness scale. J. Clin. Psychol. 1995, 51, 768–774. [Google Scholar] [CrossRef]
- Beck, A.T.; Steer, R.A.; Brown, G. Beck Depression Inventory–II. PsycTESTS Dataset 1996, 78, 490–498. [Google Scholar] [CrossRef]
- Beck, A.T.; Epstein, N.; Brown, G.; Steer, R.A. An inventory for measuring clinical anxiety: Psychometric properties. J. Consult. Clin. Psychol. 1988, 56, 893. [Google Scholar] [CrossRef] [PubMed]
- Kim, J.-H. The Reliability and Validity Test of psychosocial Well-being Index(PWI). J. Korean Acad. Nurs. 1999, 29, 304. [Google Scholar] [CrossRef]
- Suh, S.; Gwak, A.; Lim, J. Quality of life and psychosocial well-being in Internet gaming disorder: A comparison with alcohol-dependent and healthy control groups. J. Korean Acad. Addict. Psychiatry 2015, 19, 29–34. [Google Scholar]
- Alrekebat, A.F. Internet Addiction and Its Relationship with Self-Efficacy Level among Al-Hussein Bin Talal University Students. J. Educ. Pract. 2016, 7, 123–131. [Google Scholar]
- Iskender, M.; Akin, A. Social self-efficacy, academic locus of control, and internet addiction. Comput. Educ. 2010, 54, 1101–1106. [Google Scholar] [CrossRef]
- Seabra, L.; Loureiro, M.; Pereira, H.; Monteiro, S.; Afonso, R.M.; Esgalhado, G. Relationship Between Internet Addiction and Self-Esteem: Cross-Cultural Study in Portugal and Brazil. Interact. Comput. 2017, 29, 1–12. [Google Scholar] [CrossRef] [Green Version]
- Stajkovic, A.D.; Luthans, F. Social cognitive theory and self-efficacy: Goin beyond traditional motivational and behavioral approaches. Organ. Dyn. 1998, 26, 62–74. [Google Scholar] [CrossRef]
- Sariyska, R.; Reuter, M.; Bey, K.; Sha, P.; Li, M.; Chen, Y.-F.; Liu, W.-Y.; Zhu, Y.-K.; Li, C.-B.; Suárez-Rivillas, A.; et al. Self-esteem, personality and Internet Addiction: A cross-cultural comparison study. Pers. Individ. Differ. 2014, 61, 28–33. [Google Scholar] [CrossRef]
- Yen, C.-F.; Chou, W.-J.; Liu, T.-L.; Yang, P.; Hu, H.-F. The association of Internet addiction symptoms with anxiety, depression and self-esteem among adolescents with attention-deficit/hyperactivity disorder. Compr. Psychiatry 2014, 55, 1601–1608. [Google Scholar] [CrossRef]
- Park, J.H.; Han, U.H.; Kim, B.-N.; Cheong, J.H.; Lee, Y.-S. Correlations among Social Anxiety, Self-Esteem, Impulsivity, and Game Genre in Patients with Problematic Online Game Playing. Psychiatry Investig. 2016, 13, 297–304. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Thompson, M.S.; Keith, V.M. THE BLACKER THE BERRY. Gend. Soc. 2001, 15, 336–357. [Google Scholar] [CrossRef]
- Kim, M.-K.; Jung, Y.H.; Kyeong, S.-H.; Shin, Y.-B.; Kim, E.; Kim, J.-J. Neural Correlates of Distorted Self-concept in Individuals with Internet Gaming Disorder: A Functional MRI Study. Front. Psychol. 2018, 9. [Google Scholar] [CrossRef] [PubMed]
- Li, D.; Liau, A.; Khoo, A. Examining the Influence of Actual-Ideal Self-Discrepancies, Depression, and Escapism, on Pathological Gaming among Massively Multiplayer Online Adolescent Gamers. CyberPsychol. Behav. Soc. Netw. 2011, 14, 535–539. [Google Scholar] [CrossRef] [PubMed]
- Kwon, J.-H.; Chung, C.-S.; Lee, J. The Effects of Escape from Self and Interpersonal Relationship on the Pathological Use of Internet Games. Community Ment. Health J. 2009, 47, 113–121. [Google Scholar] [CrossRef] [PubMed]
- Martin, A.J.; Marsh, H.W. Academic resilience and its psychological and educational correlates: A construct validity approach. Psychol. Sch. 2006, 43, 267–281. [Google Scholar] [CrossRef]
- Tusaie, K.R.; Puskar, K.; Sereika, S.M. A predictive and moderating model of psychosocial resilience in adolescents. J. Nurs. Sch. 2007, 39, 54–60. [Google Scholar] [CrossRef]
- Nam, C.R.; Lee, D.H.; Lee, J.-Y.; Choi, A.; Chung, S.J.; Kim, D.J.; Bhang, S.-Y.; Kwon, J.-G.; Kweon, Y.-S.; Choi, J.-S. The Role of Resilience in Internet Addiction among Adolescents between Sexes: A Moderated Mediation Model. J. Clin. Med. 2018, 7, 222. [Google Scholar] [CrossRef] [Green Version]
- Gillespie, B.M.; Rn, W.C.; Wallis, M.; Grimbeek, P. Resilience in the operating room: Developing and testing of a resilience model. J. Adv. Nurs. 2007, 59, 427–438. [Google Scholar] [CrossRef]
- Hinz, A.; Schumacher, J.; Albani, C.; Schmid, G.; Brähler, E. Bevölkerungsrepräsentative Normierung der Skala zur Allgemeinen Selbstwirksamkeitserwartung. Diagnostica 2006, 52, 26–32. [Google Scholar] [CrossRef]
- Hamill, S.K. Resilience and self-efficacy: The importance of efficacy beliefs and coping mechanisms in resilient adolescents. Colgate Univ. J. Sci. 2003, 35, 115–146. [Google Scholar]
- Schwarzer, R.; Warner, L.M. Resilience in Children, Adolescents, and Adults; Springer: Berlin, Germany, 2013; pp. 139–150. [Google Scholar]
- Sagone, E.; De Caroli, M.E. Relationships between Resilience, Self-Efficacy, and Thinking Styles in Italian Middle Adolescents. Procedia Soc. Behav. Sci. 2013, 92, 838–845. [Google Scholar] [CrossRef] [Green Version]
- Liu, L.; Yao, Y.-W.; Li, C.-S.R.; Zhang, J.; Xia, C.-C.; Lan, J.; Ma, S.-S.; Zhou, N.; Fang, X.-Y. The Comorbidity between Internet Gaming Disorder and Depression: Interrelationship and Neural Mechanisms. Front. Psychol. 2018, 9, 154. [Google Scholar] [CrossRef] [PubMed]
- Lim, J.-A.; Lee, J.-Y.; Jung, H.Y.; Sohn, B.K.; Choi, S.-W.; Kim, Y.J.; Kim, D.-J.; Choi, J.-S. Changes of quality of life and cognitive function in individuals with Internet gaming disorder. Medicine 2016, 95, e5695. [Google Scholar] [CrossRef]
- Hyun, G.J.; Han, U.H.; Lee, Y.S.; Kang, K.D.; Yoo, S.K.; Chung, U.; Renshaw, P.F. Risk factors associated with online game addiction: A hierarchical model. Comput. Hum. Behav. 2015, 48, 706–713. [Google Scholar] [CrossRef]
- Park, S.M.; Park, Y.A.; Lee, H.W.; Jung, H.Y.; Lee, J.Y.; Choi, J.-S. The effects of behavioral inhibition/approach system as predictors of Internet addiction in adolescents. Pers. Individ. Differ. 2013, 54, 7–11. [Google Scholar] [CrossRef]
- Yen, J.-Y.; Liu, T.-L.; Wang, P.-W.; Chen, C.-S.; Yen, C.-F.; Ko, C.-H. Association between Internet gaming disorder and adult attention deficit and hyperactivity disorder and their correlates: Impulsivity and hostility. Addict. Behav. 2017, 64, 308–313. [Google Scholar] [CrossRef]
- Yen, J.-Y.; Ko, C.-H.; Yen, C.-F.; Chen, C.-S.; Chen, C.-C. The association between harmful alcohol use and Internet addiction among college students: Comparison of personality. Psychiatry Clin. Neurosci. 2009, 63, 218–224. [Google Scholar] [CrossRef]
- Yen, J.-Y.; Cheng-Fang, Y.; Chen, C.-S.; Chang, Y.-H.; Yeh, Y.-C.; Ko, C.-H. The bidirectional interactions between addiction, behaviour approach and behaviour inhibition systems among adolescents in a prospective study. Psychiatry Res. 2012, 200, 588–592. [Google Scholar] [CrossRef]
- Franken, I.H.A.; Muris, P. BIS/BAS personality characteristics and college students’ substance use. Pers. Individ. Differ. 2006, 40, 1497–1503. [Google Scholar] [CrossRef]
- Baker, D.F.; Larson, L.M.; Seipel, M.T. Relation of Reinforcement Sensitivity on Vocational Interest and Self-Efficacy. J. Career Assess. 2017, 27, 230–245. [Google Scholar] [CrossRef] [Green Version]
Variable | IGD (n = 71) | CG (n = 37) | NG (n = 50) | F/x2 | p | Bonferroni Correction | |
---|---|---|---|---|---|---|---|
Sex (M/%) | 66 (93.0) | 33 (89.2) | 34 (68.0) | 14.632 | 0.001 | - | |
Age (years) | 26.04 (6.28) | 24.57 (4.29) | 24.22 (3.07) | 2.238 | 0.114 a | - | |
Game (h) | Weekdays | 4.59 (3.97) | 1.73 (1.91) | 0.00 (0.00) | 39.062 | <0.001 | IGD > CG > NG |
Weekends | 6.30 (4.46) | 2.96 (2.33) | 0.00 (0.00) | 55.151 | <0.001 | IGD > CG > NG | |
Internet (h) | Weekdays | 2.89 (2.33) | 2.20 (1.90) | 1.87 (1.03) | 4.502 | 0.007 a | IGD > NG b |
Weekends | 3.44 (2.88) | 2.35 (2.06) | 2.14 (1.21) | 5.390 | 0.005 a | IGD > NG b | |
Smartphone (h) | Weekdays | 3.98 (3.61) | 3.82 (3.12) | 2.77 (1.70) | 2.516 | 0.025 a | - |
Weekends | 4.75 (4.02) | 4.10 (3.47) | 3.19 (2.01) | 2.931 | 0.023 a | IGD > NG b | |
Y-IAT | 59.82 (15.86) | 34.78 (11.89) | 30.90 (9.23) | 84.758 | <0.001 a | IGD > CG, NG b | |
SAS | 98.99 (32.69) | 69.81 (27.30) | 62.62 (20.31) | 28.139 | <0.001 a | IGD > CG, NG b |
1 | 2-1. | 2-2. | 3-1. | 3-2. | 4-1. | 4-2. | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | ||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1. SES | 1 | ||||||||||||||||
2. Game (h) | 2-1. Weekdays | −0.454 ** | 1 | ||||||||||||||
2-2. Weekends | −0.433 ** | 0.917 ** | 1 | ||||||||||||||
3. Internet (h) | 3-1. Weekdays | −0.188 * | 0.342 ** | 0.269 ** | 1 | ||||||||||||
3-2. Weekends | −0.280 ** | 0.324 ** | 0.266 ** | 0.784 ** | 1 | ||||||||||||
4. Smartphone (h) | 4-1. Weekdays | −0.257 ** | 0.234 ** | 0.215 ** | 0.329 ** | 0.284 ** | 1 | ||||||||||
4-2. Weekends | −0.248 ** | 0.226 ** | 0.277 ** | 0.288 ** | 0.323 ** | 0.904 ** | 1 | ||||||||||
5. YIAT | −0.525 ** | 0.589 ** | 0.606 ** | 0.359 ** | 0.456 ** | 0.198 * | 0.219 ** | 1 | |||||||||
6. SAS | −0.456 ** | 0.359 ** | 0.349 ** | 0.343 ** | 0.438 ** | 0.388 ** | 0.376 ** | 0.683 ** | 1 | ||||||||
7. AQ | −0.434 ** | 0.463 ** | 0.458 ** | 0.254 ** | 0.299 ** | 0.248 ** | 0.214 ** | 0.635 ** | 0.588 ** | 1 | |||||||
8. BAS | −0.075 | 0.283 ** | 0.240 ** | 0.224 ** | 0.185 * | 0.162 * | 0.141 | 0.282 ** | 0.329 ** | 0.403 ** | 1 | ||||||
9. BIS | −0.632 ** | 0.393 ** | 0.344 ** | 0.161 * | 0.254 ** | 0.203 * | 0.206 * | 0.555 ** | 0.473 ** | 0.530 ** | 0.378 ** | 1 | |||||
10. BIS-11 | −0.548 ** | 0.438 ** | 0.428 ** | 0.120 | 0.143 | 0.258 ** | 0.262 ** | 0.458 ** | 0.384 ** | 0.495 ** | 0.280 ** | 0.436 ** | 1 | ||||
11. BDI | −0.652 ** | 0.542 ** | 0.507 ** | 0.276 ** | 0.357 ** | 0.288 ** | 0.272 ** | 0.627 ** | 0.454 ** | 0.691 ** | 0.280 ** | 0.618 ** | .501 ** | 1 | |||
12. BAI | −0.576 ** | 0.444 ** | 0.442 ** | 0.357 ** | 0.383 ** | 0.316 ** | 0.292 ** | 0.578 ** | 0.532 ** | 0.634 ** | 0.314 ** | 0.582 ** | 0.495 ** | 0.794 ** | 1 | ||
13. PWI | −0.637 ** | 0.495 ** | 0.445 ** | 0.222 ** | 0.300 ** | 0.277 ** | 0.244 ** | 0.561 ** | 0.523 ** | 0.639 ** | 0.291 ** | 0.606 ** | 0.554 ** | 0.795 ** | 0.726 ** | 1 | |
M | 27.59 | 2.48 | 3.52 | 2.4 | 2.77 | 3.56 | 4.1 | 44.8 | 80.53 | 66.01 | 34.14 | 19.35 | 61.59 | 9.74 | 8.78 | 48.97 | |
SD | 5.12 | 3.46 | 4.2 | 1.94 | 2.35 | 3.03 | 3.42 | 18.93 | 32.51 | 19.46 | 5.92 | 4.13 | 9.73 | 10.32 | 10.63 | 28.42 |
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Chung, S.J.; Jang, J.H.; Lee, J.Y.; Choi, A.; Kim, B.M.; Park, M.K.; Jung, M.H.; Choi, J.-S. Self-Efficacy and Clinical Characteristics in Casual Gamers Compared to Excessive Gaming Users and Non-Gamers in Young Adults. J. Clin. Med. 2020, 9, 2720. https://doi.org/10.3390/jcm9092720
Chung SJ, Jang JH, Lee JY, Choi A, Kim BM, Park MK, Jung MH, Choi J-S. Self-Efficacy and Clinical Characteristics in Casual Gamers Compared to Excessive Gaming Users and Non-Gamers in Young Adults. Journal of Clinical Medicine. 2020; 9(9):2720. https://doi.org/10.3390/jcm9092720
Chicago/Turabian StyleChung, Sun Ju, Joon Hwan Jang, Ji Yoon Lee, Aruem Choi, Bo Mi Kim, Min Kyung Park, Myung Hun Jung, and Jung-Seok Choi. 2020. "Self-Efficacy and Clinical Characteristics in Casual Gamers Compared to Excessive Gaming Users and Non-Gamers in Young Adults" Journal of Clinical Medicine 9, no. 9: 2720. https://doi.org/10.3390/jcm9092720