Depression and Internet Gaming Disorder among Chinese Adolescents: A Longitudinal Moderated Mediation Model
Abstract
:1. Introduction
1.1. Relationship between Depression and IGD
1.2. Maladaptive Cognition as a Mediator
1.3. Mindfulness as a Moderator
1.4. The Present Study
2. Method
2.1. Participants and Procedure
2.2. Measurements
2.2.1. Depression
2.2.2. Internet Gaming Disorder
2.2.3. Maladaptive Cognition
2.2.4. Mindfulness
2.3. Statistical Analysis
3. Results
3.1. Preliminary Analyses
3.2. Testing for the Mediation Model
3.3. Testing for the Moderated Mediation Model
4. Discussion
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Liao, Z.; Huang, Q.; Huang, S.; Tan, L.; Shao, T.; Fang, T.; Chen, X.; Lin, S.; Qi, J.; Cai, Y.; et al. Prevalence of internet gaming disorder and its association with personality traits and gaming characteristics among Chinese adolescent gamers. Front. Psychiatry 2020, 11, 598585. [Google Scholar] [CrossRef] [PubMed]
- Wang, J.P.; Yu, C.F.; Li, Q.W. Peer victimization and Internet gaming disorder in adolescents: Psychological needs satisfaction as a mediator and emotional intelligence as a moderator. J. Cent. China Norm. Univ. (Humanit. Soc. Sci.) 2020, 59, 184–192. [Google Scholar]
- Gentile, D. Pathological video-game use among youth ages 8 to 18: A national study. Psychol. Sci. 2009, 20, 594–602. [Google Scholar] [CrossRef] [PubMed]
- Wan, C.S.; Chiou, W.B. Why are adolescents addicted to online gaming? An interview study in Taiwan. CyberPsychol. Behav. 2006, 9, 762–766. [Google Scholar] [CrossRef] [PubMed]
- Lin, Y.; Liu, Q.X.; Yu, S.; Zhou, Z. The relationship between parents neglect and online gaming addiction among adolescents: The mediating role of hope and gender difference. Psychol. Dev. Educ. 2021, 37, 109–119. [Google Scholar]
- Ostinelli, E.G.; Zangani, C.; Giordano, B.; Maestri, D.; Gambini, O.; D’Agostino, A.; Furukawa, T.A.; Purgato, M. Depressive symptoms and depression in individuals with internet gaming disorder: A systematic review and meta-analysis. J. Affect. Disord. 2021, 284, 136–142. [Google Scholar] [CrossRef]
- Bodi, G.; Maintenant, C.; Pennequin, V. The role of maladaptive cognitions in gaming disorder: Differences between online and offline gaming types. Addict. Behav. 2021, 112, 106595. [Google Scholar] [CrossRef]
- Zajac, K.; Ginley, M.K.; Chang, R. Treatments of internet gaming disorder: A systematic review of the evi-dence. Expert Rev. Neurother. 2020, 20, 85–93. [Google Scholar] [CrossRef]
- Li, W.; Garland, E.L.; Howard, M.O. Therapeutic mechanisms of Mindfulness-Oriented Recovery Enhancement for internet gaming disorder: Reducing craving and addictive behavior by targeting cognitive processes. J. Addict. Dis. 2018, 37, 5–13. [Google Scholar] [CrossRef]
- World Health Organization. International Statistical Classification of Diseases and Related Health Problems; 11th Revision; World Health Organization: Geneva, Switzerland, 2018. Available online: https://icd.who.int/browse11/l-m/en (accessed on 31 January 2023).
- Deng, L.Y.; Liu, L.; Xia, C.C.; Lan, J.; Zhang, J.T.; Fang, X.Y. Craving behavior intervention in ameliorating col-lege students’ internet game disorder: A longitudinal study. Front. Psychol. 2017, 8, 526. [Google Scholar] [CrossRef] [Green Version]
- Griffiths, M.; King, D.; Demetrovics, Z. DSM-5 internet gaming disorder needs a unified approach to assessment. Neuropsychiatry 2014, 4, 1–4. [Google Scholar] [CrossRef]
- Li, W.; O’Brien, J.E.; Snyder, S.M.; Howard, M.O. Diagnostic criteria for problematic internet use among US university students: A mixed-methods evaluation. PLoS ONE 2016, 11, e0145981. [Google Scholar] [CrossRef] [Green Version]
- Young, K.S. Internet addiction: The emergence of a new clinical disorder. CyberPsychol. Behav. 2009, 1, 237–244. [Google Scholar] [CrossRef] [Green Version]
- Kochuchakkalackal, G.; Reyes, M.E.S. Development and efficacy of acceptance and cognitive restructuring intervention program on the symptoms of internet gaming disorder and psychological well-being of adolescents: A pilot study. Int. J. Behav. Sci. 2019, 12, 141–145. [Google Scholar]
- Lopez-Fernandez, O. Generalised versus specific internet use-related addiction problems: A mixed methods study on internet, gaming, and social networking behaviours. Int. J. Environ. Res. Public Health 2018, 15, 2913. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Griffiths, M. A ‘components’ model of addiction within a biopsychosocial framework. J. Subst. Use 2005, 10, 191–197. [Google Scholar] [CrossRef]
- Cudo, A.; Szewczyk, M.; Błachnio, A.; Przepiórka, A.; Jarząbek-Cudo, A. The role of depression and self-esteem in Facebook intrusion and gaming disorder among young adult gamers. Psychiatr. Q. 2020, 91, 65–76. [Google Scholar] [CrossRef]
- Teng, Z.; Pontes, H.M.; Nie, Q.; Griffiths, M.D.; Guo, C. Depression and anxiety symptoms associated with internet gaming disorder before and during the COVID-19 pandemic: A longitudinal study. J. Behav. Addict. 2021, 10, 169–180. [Google Scholar] [CrossRef]
- Sharma, P.; Bharati, A.; De Sousa, A.; Shah, N. Internet addiction and its association with psychopathology: A study in school children from Mumbai, India. Natl. J. Community Med. 2016, 7, 1–4. [Google Scholar]
- Davis, R.A. A cognitive-behavioral model of pathological Internet use. Comput. Hum. Behav. 2001, 17, 187–195. [Google Scholar] [CrossRef]
- Gámez-Guadix, M. Depressive symptoms and problematic Internet use among adolescents: Analysis of the longitudi-nal relationships from the cognitive–behavioral model. CyberPsychol. Behav. Soc. Netw. 2014, 17, 714–719. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Moudiab, S.; Spada, M.M. The relative contribution of motives and maladaptive cognitions to levels of Internet Gaming Disorder. Addict. Behav. Rep. 2019, 9, 100160. [Google Scholar] [CrossRef] [PubMed]
- Peng, W.; Liu, M. Online gaming dependency: A preliminary study in China. Cyberpsychol. Behav. Soc. Netw. 2010, 13, 329–333. [Google Scholar] [CrossRef] [PubMed]
- Kirisci, L.; Tarter, R.E.; Vanyukov, M.; Reynolds, M.; Habeych, M. Relation between cognitive distortions and neu-robehavior disinhibition on the development of substance use during adolescence and substance use disorder by young adulthood: A prospective study. Drug Alcohol Depend. 2004, 76, 125–133. [Google Scholar] [CrossRef]
- Lu, X.; Yeo, K.J. Pathological Internet use among Malaysia university students: Risk factors and the role of cognitive distortion. Comput. Hum. Behav. 2015, 45, 235–242. [Google Scholar] [CrossRef]
- Zhang, Y.Z.; Su, P.; Ye, Y.X.; Zhen, S.J. Psychosocial factors influencing Internet game disorder in university students: The mediating effect of maladaptive cognition. J. South China Norm. Univ. (Soc. Sci. Ed.) 2017, 86–91. [Google Scholar]
- Bonnaire, C.; Baptista, D. Internet gaming disorder in male and female young adults: The role of alexithymia, depression, anxiety and gaming type. Psychiatry Res. 2019, 272, 521–530. [Google Scholar] [CrossRef]
- Mai, Y.; Hu, J.; Yan, Z.; Zhen, S.; Wang, S.; Zhang, W. Structure and function of maladaptive cognitions in pathological Internet use among Chinese adolescents. Comput. Hum. Behav. 2012, 28, 2376–2386. [Google Scholar] [CrossRef]
- King, D.; Delfabbro, P.; Griffiths, M. Video game structural characteristics: A new psychological taxonomy. Int. J. Ment. Health Addict. 2010, 8, 90–106. [Google Scholar] [CrossRef]
- Yee, N. Motivations for play in online games. CyberPsychol. Behav. 2006, 9, 772–775. [Google Scholar] [CrossRef]
- Wood RT, A.; Griffiths, M.D.; Chappell, D.; Davies, M.N.O. The structural characteristics of video games: A psycho-structural analysis. CyberPsychol. Behav. 2004, 7, 1–10. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Calvete, E.; Gámez-Guadix, M.; Cortazar, N. Mindfulness facets and problematic Internet use: A six-month longi-tudinal study. Addict. Behav. 2017, 72, 57–63. [Google Scholar] [CrossRef]
- Chen, J.Y.; Xiang, H. Mindfulness-based interventions and possible mecha-nism of Internet game disorder. J. Clin. Psychiatry 2021, 31, 82–84. [Google Scholar]
- Li, W.; Garland, E.L.; McGovern, P.; O’Brien, J.E.; Tronnier, C.; Howard, M.O. Mindfulness-oriented recovery enhancement for Internet gaming disorder in U.S. adults: A stage I randomized controlled trial. Psychol. Addict. Behav. 2017, 31, 393–402. [Google Scholar] [CrossRef] [PubMed]
- Marchica, L.A.; Mills, D.J.; Keough, M.T.; Derevensky, J.L. Exploring differences among video gamers with and without depression: Contrasting emotion regulation and mindfulness. Cyberpsychol. Behav. Soc. Netw. 2020, 23, 119–125. [Google Scholar] [CrossRef]
- Schwebel, F.J.; Korecki, J.R.; Witkiewitz, K. Addictive behavior change and mindfulness-based interventions: Cur-rent research and future directions. Curr. Addict. Rep. 2020, 7, 117–124. [Google Scholar] [CrossRef] [PubMed]
- Brown, K.W.; Ryan, R.M.; Creswell, J.D. Addressing fundamental questions about mindfulness. Psychol. Inq. 2007, 18, 272–281. [Google Scholar] [CrossRef]
- Tang, Y.Y.; Hölzel, B.K.; Posner, M.I. The neuroscience of mindfulness meditation. Nat. Rev. Neurosci. 2015, 16, 213–225. [Google Scholar] [CrossRef]
- Meiklejohn, J.; Phillips, C.; Freedman, M.L.; Griffin, M.L.; Biegel, G.; Roach, A.; Frank, J.; Burke, C.; Pinger, L.; Soloway, G.; et al. Integrating mindfulness training into K-12 education: Fostering the resilience of teachers and students. Mindfulness 2012, 3, 291–307. [Google Scholar] [CrossRef]
- Kiken, L.G.; Shook, N.J. Mindfulness and emotional distress: The role of negatively biased cognition. Personal. Individ. Differ. 2012, 52, 329–333. [Google Scholar] [CrossRef]
- Segal, Z.V.; Williams, J.M.; Teasdale, J.D. Mindfulness-Based Cognitive Therapy for Depression: A New Approach to Preventing Relapse; Guilford Press: New York, NY, USA, 2002. [Google Scholar]
- Brandtner, A.; Antons, S.; King, D.L.; Potenza, M.N.; Tang, Y.Y.; Blycker, G.R.; Brand, M.; Liebherr, M. A preregistered, systematic review considering mindfulness-based interventions and neurofeedback for targeting affective and cognitive processes in behavioral addictions. Clin. Psychol. Sci. Pract. 2022, 29, 379. [Google Scholar] [CrossRef]
- van der Velden, A.M.; Kuyken, W.; Wattar, U.; Crane, C.; Pallesen, K.J.; Dahlgaard, J.; Fjorback, L.O.; Piet, J. A systematic review of mechanisms of change in mindfulness-based cognitive therapy in the treatment of recurrent major depressive disor-der. Clin. Psychol. Rev. 2015, 37, 26–39. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Sun, X.; Duan, C.; Niu, G.; Tian, Y.; Zhang, Y. Mindfulness buffers the influence of stress on cue-induced craving for Internet among Chinese colleges with problematic Internet use. J. Behav. Addict. 2021, 10, 983–989. [Google Scholar] [CrossRef] [PubMed]
- Chi, X.; Liu, X.; Guo, T.; Wu, M.; Chen, X. Internet addiction and depression in Chinese adolescents: A moderated mediation model. Front. Psychiatry 2019, 10, 816. [Google Scholar] [CrossRef] [PubMed]
- Kroenke, K.; Spitzer, R.L.; Williams, J.B.W. The PHQ-9: Validity of a brief depression severity measure. J. Gen. Intern. Med. 2001, 16, 606–613. [Google Scholar] [CrossRef]
- Leung DY, P.; Mak, Y.W.; Leung, S.F.; Chiang, V.C.L.; Loke, A.Y. Measurement invariances of the PHQ-9 across gender and age groups in Chinese adolescents. Asia-Pac. Psychiatry 2020, 12, e12381. [Google Scholar] [CrossRef] [Green Version]
- Yu, C.; Li, X.; Zhang, W. Predicting adolescent problematic online game use from teacher autonomy support, basic psychological needs satisfaction, and school engagement: A 2-year longitudinal study. Cyberpsychol. Behav. Soc. Netw. 2015, 18, 228–233. [Google Scholar] [CrossRef]
- Liu, X.F.; Chi, X.L.; Zhang, J.T.; Duan, W.J.; Wen, Z.K. Validation of Child and Adolescent Mindfulness Measure (CAMM) in Chinese adolescents. Psychol. Explor. 2019, 39, 250–256. [Google Scholar]
- Greco, L.A.; Baer, R.A.; Smith, G.T. Assessing mindfulness in children and adolescents: Development and valida-tion of the Child and Adolescent Mindfulness Measure (CAMM). Psychol. Assess. 2011, 23, 606–614. [Google Scholar] [CrossRef]
- Podsakoff, P.M.; MacKenzie, S.B.; Lee, J.Y.; Podsakoff, N.P. Common method biases in behavioral research: A critical review of the literature and recommended remedies. J. Appl. Psychol. 2003, 88, 879–903. [Google Scholar] [CrossRef]
- Zhou, H.; Long, L.R. Statistical remedies for Common Method Biases. Adv. Psychol. Sci. 2004, 12, 942–950. [Google Scholar]
- Gong, Y.L.; Sheng, X.T.; Wang, X.; Yang, Y.P.; Wang, H.Q.; Zhang, X.C. The impact of mindfulness on job crafting: The mediating role of work engagement. J. Psychol. Sci. 2020, 43, 187–192. [Google Scholar]
- Hayes, A.F. Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach; Guilford Press: New York, NY, USA, 2013. [Google Scholar]
- Liu, M.; Wang, N.; Wang, P.; Wu, H.; Ding, X.; Zhao, F. Negative emotions and job burnout in news media workers: A moderated mediation model of rumination and empathy. J. Affect. Disord. 2021, 279, 75–82. [Google Scholar] [CrossRef] [PubMed]
- Li, Y.; Wang, P. Relationship between passive use on social network site and depression: A moderated mediation model. China J. Health Psychol. 2021, 29, 412–417. [Google Scholar]
- Ekinci, N.E.; Yalçin, I.; Özer, Ö.; Kara, T. An investigation of the digital game addiction between high school stu-dents. Online Submiss. 2017, 14, 4989–4994. [Google Scholar] [CrossRef] [Green Version]
- Wang, C.W.; Chan, C.L.; Mak, K.K.; Ho, S.Y.; Wong, P.W.; Ho, R.T. Prevalence and correlates of video and in-ternet gaming addiction among Hong Kong adolescents: A pilot study. Sci. World J. 2014, 2014, 874648. [Google Scholar] [CrossRef] [Green Version]
- Jeong, H.; Yim, H.W.; Lee, S.Y.; Lee, H.K.; Potenza, M.N.; Jo, S.J.; Son, H.J. Reciprocal relationship between de-pression and Internet gaming disorder in children: A 12-month follow-up of the iCURE study using cross-lagged path analysis. J. Behav. Addict. 2019, 8, 725–732. [Google Scholar] [CrossRef]
- Yuan, G.; Elhai, J.D.; Hall, B.J. The influence of depressive symptoms and fear of missing out on severity of prob-lematic smartphone use and Internet gaming disorder among Chinese young adults: A three-wave mediation model. Addict. Behav. 2021, 112, 106648. [Google Scholar] [CrossRef]
- Kim, D.J.; Kim, K.; Lee, H.W.; Hong, J.P.; Cho, M.J.; Fava, M.; Mischoulon, D.; Heo, J.Y.; Jeon, H.J. Internet game addiction, depression, and escape from negative emotions in adulthood: A nationwide community sample of Korea. J. Nerv. Ment. Dis. 2017, 205, 568–573. [Google Scholar] [CrossRef]
- Garland, E.L.; Farb, N.A.; Goldin, P.R.; Fredrickson, B.L. The Mindfulness-to-Meaning Theory: Extensions, applications, and challenges at the attention–appraisal-emotion interface. Psychol. Inq. 2015, 26, 377–387. [Google Scholar] [CrossRef]
- Loton, D.; Borkoles, E.; Lubman, D.; Polman, R. Video game addiction, engagement and symptoms of stress, depression and anxiety: The mediating role of coping. Int. J. Ment. Health Addict. 2016, 14, 565–578. [Google Scholar] [CrossRef]
- Lee, J.Y.; Ko, D.W.; Lee, H. Loneliness, regulatory focus, inter-personal competence, and online game addiction: A moderated mediation model. Internet Res. 2019, 29, 381–394. [Google Scholar] [CrossRef]
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | |
---|---|---|---|---|---|---|---|---|
1. Depression T1 | - | |||||||
2. Depression T2 | 0.51 *** | - | ||||||
3. IGD T1 | 0.36 *** | 0.29 *** | - | |||||
4. IGD T2 | 0.27 *** | 0.37 *** | 0.63 *** | - | ||||
5. Maladaptive cognition T1 | 0.43 *** | 0.33 *** | 0.42 *** | 0.34 *** | - | |||
6. Maladaptive cognition T2 | 0.31 *** | 0.41 *** | 0.27 *** | 0.45 *** | 0.58 *** | - | ||
7. Mindfulness T1 | −0.52 *** | −0.40 *** | −0.34 *** | −0.26 *** | −0.35 *** | −0.29 *** | - | |
8. Mindfulness T2 | −0.40 *** | −0.55 *** | −0.24 *** | −0.30 *** | −0.31 *** | −0.36 *** | 0.53 *** | - |
Range | 0–27 | 0–25 | 0–11 | 0–9.50 | 12–60 | 12–60 | 0–40 | 4–40 |
Mean | 5.64 | 5.63 | 2.04 | 2.04 | 28.85 | 29.31 | 21.86 | 23.26 |
SD | 5.74 | 4.84 | 1.97 | 1.98 | 9.12 | 8.61 | 6.76 | 6.92 |
Independent Variable | IGD T2 | Maladaptive Cognition T1 | IGD T2 | ||||||
---|---|---|---|---|---|---|---|---|---|
β | SE | t | β | SE | t | β | SE | t | |
Constant | −0.35 | 0.05 | −7.70 *** | −0.09 | 0.05 | −1.86 | −0.33 | 0.04 | −7.45 *** |
Gender | 0.91 | 0.07 | 12.35 *** | 0.23 | 0.08 | 2.99 ** | 0.86 | 0.07 | 11.88 *** |
Depression T1 | 0.30 | 0.04 | 8.43 *** | 0.44 | 0.04 | 11.74 *** | 0.21 | 0.04 | 5.30 *** |
Maladaptive cognition T1 | 0.22 | 0.04 | 5.62 *** | ||||||
R² | 0.27 | 0.20 | 0.30 | ||||||
F | 104.64 *** | 71.16 *** | 83.98 *** |
Variable | Maladaptive Cognition T1 | IGD T2 | ||||
---|---|---|---|---|---|---|
β | SE | t | β | SE | t | |
Constant | −0.09 | 0.05 | −1.86 | −0.35 | 0.05 | −7.71 *** |
Gender | 0.23 | 0.08 | 2.99 ** | 0.85 | 0.07 | 11.86 *** |
Depression T1 | 0.44 | 0.04 | 11.74 *** | 0.15 | 0.04 | 3.39 *** |
Maladaptive cognition T1 | 0.21 | 0.04 | 5.27 *** | |||
Mindfulness T1 | −0.10 | 0.04 | −2.55 * | |||
Maladaptive cognition T1 * Mindfulness T1 | −0.06 | 0.03 | −2.07 * | |||
R² | 0.20 | 0.32 | ||||
F | 71.16 *** | 53.00 *** |
Moderator: Mindfulness T1 | Value | SE | Confidence Interval | |
---|---|---|---|---|
LLCI | ULCI | |||
M−1SD | 0.12 | 0.02 | 0.07 | 0.16 |
M | 0.09 | 0.02 | 0.06 | 0.13 |
M+1SD | 0.06 | 0.02 | 0.03 | 0.11 |
(M) − (M−1SD) | −0.03 | 0.01 | −0.05 | −0.00 |
(M+1SD) − (M−1SD) | −0.05 | 0.02 | −0.10 | −0.01 |
(M+1SD) − (M) | −0.03 | 0.01 | −0.05 | −0.00 |
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
Yin, M.; Huang, S.; Yu, C. Depression and Internet Gaming Disorder among Chinese Adolescents: A Longitudinal Moderated Mediation Model. Int. J. Environ. Res. Public Health 2023, 20, 3633. https://doi.org/10.3390/ijerph20043633
Yin M, Huang S, Yu C. Depression and Internet Gaming Disorder among Chinese Adolescents: A Longitudinal Moderated Mediation Model. International Journal of Environmental Research and Public Health. 2023; 20(4):3633. https://doi.org/10.3390/ijerph20043633
Chicago/Turabian StyleYin, Mengyun, Shihua Huang, and Chengfu Yu. 2023. "Depression and Internet Gaming Disorder among Chinese Adolescents: A Longitudinal Moderated Mediation Model" International Journal of Environmental Research and Public Health 20, no. 4: 3633. https://doi.org/10.3390/ijerph20043633
APA StyleYin, M., Huang, S., & Yu, C. (2023). Depression and Internet Gaming Disorder among Chinese Adolescents: A Longitudinal Moderated Mediation Model. International Journal of Environmental Research and Public Health, 20(4), 3633. https://doi.org/10.3390/ijerph20043633