Counseling Psychology and Psychotherapy
2025. Vol. 33, no. 3, 32–63
doi:10.17759/cpp.2025330302
ISSN: 2075-3470 / 2311-9446 (online)
Predictors of spontaneous remission in school students with Internet use disorders: Systematic review and meta-analysis
Abstract
Context and relevance. Internet use disorders (IUDs), which include different types of behavioral addiction patterns related to inappropriate or excessive internet use, have become a major problem among children and adolescents. Objective. This study aims to explore which predictors favor spontaneous remission in school students with IUDs. Methods and materials. We systematically searched for relevant longitudinal cohort and case-control studies published in PubMed, ProQuest, and the Cochrane Library. Quantitative syntheses were performed. Results: The analysis includes 10 prospective studies published between 2007 and 2022. Overall, the spontaneous remission rate was 44,2%. A higher level of self-esteem predicted spontaneous IUD remission. Social and demographic predictors (age, sex, family relations, economic welfare, macrosocial adjustment, etc.), IUD score, social anxiety score, general anxiety score, and impulsiveness did not affect the probability of remission. Data on the significance of school performance, hostility and aggression, ADHD score, and frequency of daily internet use were conflicting. A lower depression score did not favor remission; however, a tendency was observed, and conflicting data on the role of severe depression should be noted. Conclusions. Interpersonal IUD remission predictors are less important compared to intrapersonal ones. Since intrapersonal (especially self-related) predictors are less well studied, further research is warranted to verify our findings. Lower self-esteem and more severe depressive symptoms (the nature of which is yet to be studied) may increase the likelihood of spontaneous remission and could be targeted to improve therapeutic programs. The importance of addressing family relations, economic welfare, anxiety, social anxiety, and impulsiveness should not be overstated.
General Information
Keywords: systematic review; meta-analysis; internet use disorders; internet addiction; spontaneous remission; predictors; children
Journal rubric: Research Reviews
Article type: scientific article
DOI: https://doi.org/10.17759/cpp.2025330302
Received 30.03.2025
Revised 30.07.2025
Accepted
Published
For citation: Malygin, Y.V., Zolotareva, L.S., Orlova, A.S., Mokienko, O.A., Malygin, V.L. (2025). Predictors of spontaneous remission in school students with Internet use disorders: Systematic review and meta-analysis. Counseling Psychology and Psychotherapy, 33(3), 32–63. (In Russ.). https://doi.org/10.17759/cpp.2025330302
© Malygin Y.V., Zolotareva L.S., Orlova A.S., Mokienko O.A., Malygin V.L., 2025
License: CC BY-NC 4.0
References
- Basenach, L., Renneberg, B., Salbach, H., Dreier, M., Wölfling, K. (2023). Systematic reviews and meta-analyses of treatment interventions for Internet use disorders: Critical analysis of the methodical quality according to the PRISMA guidelines. Journal of behavioral addictions, 12(1), 9—25. https://doi.org/10.1556/2006.2022.00087
- Belmans, E., Bastin, M., Raes, F., Bijttebier, P. (2019). Temporal associations between social anxiety and depressive symptoms and the role of interpersonal stress in adolescents. Depression and anxiety, 36(10), 960—967. https://doi.org/10.1002/da.22939
- Borenstein, M., Higgins, J.P., Hedges, L.V., Rothstein, H.R. (2017). Basics of meta-analysis: I2 is not an absolute measure of heterogeneity. Research synthesis methods, 8(1), 5—18. https://doi.org/10.1002/jrsm.1230
- Bu, H., Chi, X., Qu, D. (2021). Prevalence and predictors of the persistence and incidence of adolescent internet addiction in Mainland China: A two-year longitudinal study. Addictive behaviors, 122, article 107039. https://doi.org/10.1016/j.addbeh.2021.107039
- Chang, F.C., Chiu, C.H., Lee, C.M., Chen, P.H., Miao, N.F. (2014). Predictors of the initiation and persistence of internet addiction among adolescents in Taiwan. Addictive behaviors, 39(10), 1434—1440. https://doi.org/10.1016/j.addbeh.2014.05.010
- Chia, D.X.Y., Ng, C.W.L., Kandasami, G., Seow, M.Y.L., Choo, C.C., Chew, P.K.H., Lee, C., Zhang, M.W.B. (2020). Prevalence of Internet Addiction and Gaming Disorders in Southeast Asia: A Meta-Analysis. Int J Environ Res Public Health, 17(7), article 2582. https://doi.org/10.3390/ijerph17072582
- Choi, S.W., Kim, D.J., Choi, J.S., Ahn, H., Choi, E.J., Song, W.Y., Kim, S., Youn, H. (2015). Comparison of risk and protective factors associated with smartphone addiction and Internet addiction. Journal of behavioral addictions, 4(4), 308–314. https://doi.org/10.1556/2006.4.2015.043
- Endomba, F.T., Demina, A., Meille, V., Ndoadoumgue, A.L., Danwang, C., Petit, B., Trojak, B. (2022). Prevalence of internet addiction in Africa: A systematic review and meta-analysis. J Behav Addict, 11(3), 739—753. https://doi.org/10.1556/2006.2022.00052
- Frison, E., Eggermont, S. (2016). Exploring the relationships between different types of Facebook use, perceived online social support, and adolescents’ depressed mood. Social Science Computer Review, 34(2), 153—171. https://doi.org/10.1177/0894439314567449
- Gentile, D.A., Choo, H., Liau, A., Sim, T., Li, D., Fung, D., Khoo, A. (2011). Pathological video game use among youths: a two-year longitudinal study. Pediatrics, 127(2), e319e—329. https://doi.org/10.1542/peds.2010-1353
- Gøtzsche, P.C. (2022). Critical psychiatry textbook. Copenhagen: Institute for Scientific Freedom.
- Hayden, J.A., van der Windt, D.A., Cartwright, J.L., Côté, P., Bombardier, C. (2013). Assessing bias in studies of prognostic factors. Annals of internal medicine, 158(4), 280—286. https://doi.org/10.7326/0003-4819-158-4-201302190-00009
- Higgins, J.P., Thompson, S.G., Deeks, J.J., Altman, D.G. (2003). Measuring inconsistency in meta-analyses. BMJ (Clinical research ed.), 327, article 557. https://doi.org/10.1136/bmj.327.7414.557
- Hirota, T., Takahashi, M., Adachi, M., Sakamoto, Y., Nakamura, K. (2021). Neurodevelopmental Traits and Longitudinal Transition Patterns in Internet Addiction: A 2-year Prospective Study. Journal of autism and developmental disorders, 51(4), 1365—1374. https://doi.org/10.1007/s10803-020-04620-2
- Hsieh, K.Y., Hsiao, R.C., Yang, Y.H., Liu, T.L., Yen, C.F. (2018). Predictive Effects of Sex, Age, Depression, and Problematic Behaviors on the Incidence and Remission of Internet Addiction in College Students: A Prospective Study. International journal of environmental research health, 15(12), article 2861. https://doi.org/10.3390/ijerph15122861
- Islam, M.I., Biswas, R.K., Khanam, R. (2020). Effect of internet use and electronic game-play on academic performance of Australian children. Sci Rep, 10(1), article 21727. https://doi.org/10.1038/s41598-020-78916-9
- Jeong, H., Yim, H.W., Lee, S.Y., Lee, H.K., Potenza, M.N., Lee, H. (2021). Factors associated with severity, incidence or persistence of internet gaming disorder in children and adolescents: a 2-year longitudinal study. Addiction, 116(7), 1828—838. https://doi.org/10.1111/add.15366
- Kim, J., Lee, S., Lee, D., Shim, S., Balva, D., Choi, K.H., Chey, J., Shin, S.H., Ahn, W.Y. (2022). Psychological treatments for excessive gaming: a systematic review and meta-analysis. Scientific reports, 12(1), article 20485. https://doi.org/10.1038/s41598-022-24523-9
- Ko, C.H., Liu, T.L., Wang, P.W., Chen, C.S., Yen, C.F., Yen, J.Y. (2014). The exacerbation of depression, hostility, and social anxiety in the course of Internet addiction among adolescents: a prospective study. Comprehensive psychiatry, 55(6), 1377—1384. https://doi.org/10.1016/j.comppsych.2014.05.003
- Ko, C.H., Wang, P.W., Liu, T.L., Yen, C.F., Chen, C.S., Yen, J.Y. (2015). Bidirectional associations between family factors and Internet addiction among adolescents in a prospective investigation. Psychiatry and clinical neurosciences, 69(4), 192—200. https://doi.org/10.1111/pcn.12204
- Ko, C.H., Yen, J.Y., Yen, C.F., Lin, H.C., Yang, M.J. (2007). Factors predictive for incidence and remission of internet addiction in young adolescents: a prospective study. Cyberpsychology & behavior: the impact of the Internet, multimedia and virtual reality on behavior and society, 10(4), 545–551. https://doi.org/10.1089/cpb.2007.9992
- Lampropoulou, P., Siomos, K., Floros, G., Christodoulou, N. (2022). Effectiveness of Available Treatments for Gaming Disorders in Children and Adolescents: A Systematic Review. Cyberpsychol Behav Soc Netw, 25(1), 5—13. https://doi.org/10.1089/cyber.2021.0067
- Lau, J.T.F., Wu, A.M.S., Gross, D.L., Cheng, K.M., Lau, M.M.C. (2017). Is Internet addiction transitory or persistent? Incidence and prospective predictors of remission of Internet addiction among Chinese secondary school students. Addictive behaviors, 74, 55—62. https://doi.org/10.1016/j.addbeh.2017.05.034
- Männikkö, N., Ruotsalainen, H., Miettunen, J., Pontes, H.M., Kääriäinen, M. (2020). Problematic gaming behaviour and health-related outcomes: A systematic review and meta-analysis. J Health Psychol, 25(1), 67—81. https://doi.org/10.1177/1359105317740414
- Marchant, A., Hawton, K., Stewart, A., Montgomery, P., Singaravelu, V., Lloyd, K., Purdy, N., Daine, K., John, A. (2017). A systematic review of the relationship between internet use, self-harm and suicidal behaviour in young people: The good, the bad and the unknown. PLoS One, 12(8), article 0181722. https://doi.org/10.1371/journal.pone.0181722
- Marrero, R.J., Fumero, A., Voltes, D., González, M., Peñate, W. (2021). Individual and Interpersonal Factors Associated with the Incidence, Persistence, and Remission of Internet Gaming Disorders Symptoms in an Adolescents Sample. International journal of environmental research and public health, 18(21), article 11638. https://doi.org/10.3390/ijerph182111638
- Montag, C., Wegmann, E., Sariyska, R., Demetrovics, Z., Brand, M. (2021). How to overcome taxonomical problems in the study of Internet use disorders and what to do with "smartphone addiction"? J Behav Addict, 9(4), 908—914. https://doi.org/10.1556/2006.8.2019.59
- Number of internet and social media users worldwide as of February 2025. URL: https://www.statista.com/statistics/617136/digital-population-worldwide/ (accessed 13/08/2025).
- Page, M.J., McKenzie, J.E., Bossuyt, P.M., Boutron, I., Hoffmann, T.C., Mulrow, C.D., Shamseer, L., Tetzlaff, J.M., Akl, E.A., Brennan, S.E., Chou, R., Glanville, J., Grimshaw, J.M., Hróbjartsson, A., Lalu, M.M., Li, T., Loder, E.W., Mayo-Wilson, E., McDonald, S., McGuinness, L.A., … Moher, D. (2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ (Clinical research ed.), 372, article 71. https://doi.org/10.1136/bmj.n71
- Stevens, M.W.R., King, D.L., Dorstyn, D., Delfabbro, P.H. (2019). Cognitive-behavioral therapy for Internet gaming disorder: A systematic review and meta-analysis. Clin Psychol Psychother, 26(2), 191—203. https://doi.org/10.1002/cpp.2341
- World Health Organization (2019). ICD-11: International statistical classification of diseases and related health problems. 11th version.
Information About the Authors
Contribution of the authors
Yaroslav V. Malygin — conceptualization, methodology, investigation, data curation, formal analysis, writing (original draft), visualization, project administration.
Lyubov S. Zolotareva — data curation, investigation, formal analysis, methodology, visualization, writing (original draft).
Aleksanda S. Orlova — data curation, investigation, formal analysis, methodology, visualization, writing (original draft).
Olesya A. Mokienko — methodology, validation, writing (review & editing).
Vladimir L. Malygin — conceptualization, supervision.
All authors share responsibility for the final version of the work submitted and published
Conflict of interest
The authors declare no conflict of interest.
Metrics
Web Views
Whole time: 93
Previous month: 37
Current month: 56
PDF Downloads
Whole time: 21
Previous month: 6
Current month: 15
Total
Whole time: 114
Previous month: 43
Current month: 71