PURPOSE: This study examined (1) whether intense and problematic social media use (SMU) were independently associated with adolescent well-being; (2) whether these associations varied by the country-level prevalence of intense and problematic SMU; and (3) whether differences in the country-level prevalence of intense and problematic SMU were related to differences in mobile Internet access. METHODS: Individual-level data came from 154,981 adolescents (meanage = 13.5) from 29 countries that participated in the 2017/2018 Health Behaviour in School-aged Children (HBSC) survey. Intense SMU was measured by the time spent on social media, whereas problematic SMU was defined by symptoms of addiction to social media. Mental (life satisfaction and psychological complaints), school (school satisfaction and perceived school pressure), and social (family support and friend support) well-being were assessed. Country-level data came from aggregated individual-level data and data from the Organisation for Economic Co-operation and Development (OECD) on Internet access. RESULTS: Two-level regression analyses indicated that in countries with a lower prevalence of intense SMU, intense users reported lower levels of life satisfaction and family support and more psychological complaints than nonintense users. In contrast, in countries with a higher prevalence of intense SMU, intense users reported higher levels of family support and life satisfaction than nonintense users, and similar levels of psychological complaints. In all countries, intense users reported more friend support than nonintense users. The findings regarding problematic SMU were more consistent: In all countries, problematic users reported lower well-being on all domains than nonproblematic users. Observed differences in country-level prevalence rates of intense and problematic SMU could not be explained by mobile Internet access. CONCLUSIONS: Adolescents reporting problematic SMU are particularly at risk of lower well-being. In many countries, intense SMU may be a normative adolescent behavior that contributes positively to specific domains of their well-being.

Center for Study and Development of Health National Institute of Public Health Ljubljana Slovenia

Centre for Health Promotion Public Health Agency of Canada Ottawa Canada

Department of Interdisciplinary Social Science Utrecht University Utrecht The Netherlands

Department of Psychology Queen's University Kingston Canada

Department of Public Health and Epidemiology Institute of Public Health Riga Stradinš University Riga Latvia

Faculty of Physical Culture Palacký University Olomouc Czech Republic

Institute of Mother and Child Foundation Warsaw Poland

MRC CSO Social and Public Health Sciences Unit University of Glasgow Glasgow Scotland; School of Medicine University of St Andrews St Andrews Scotland

School of Social Sciences and Humanities Kinneret Academic College Sea of Galilee Israel

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Underwood M.K., Ehrenreich S.E. The power and the pain of adolescents’ digital communication: Cyber victimization and the perils of lurking. Am Psychol. 2017;72:144–158. PubMed PMC

Primack B.A., Escobar-Viera C.G. Social media as it interfaces with psychosocial development and mental illness in transitional age youth. Child Adolesc Psychiatr Clin N Am. 2017;26:217–233. PubMed

Anderson M., Jiang J. Pew Research Center; Washington (D.C.): 2018. Teens, social media & technology 2018.

Bányai F., Zsila Á., Király O. Problematic social media use: Results from a large-scale nationally representative adolescent sample. PLoS One. 2017;12:10–14. PubMed PMC

Mérelle S., Kleiboer A., Schotanus M. Which health-related problems are associated with problematic video-gaming or social media use in adolescents? A large-scale cross-sectional study. Clin Neuropsychiatry. 2017;14:11–19.

Griffiths M., Kuss D., Demetrovics Z. Social networking addiction: An overview of preliminary findings. In: Rosenberg K.P., Feder Laura C., editors. Behav. Addict. Academic Press; Waltham (MA): 2014. pp. 119–141.

Kelly Y., Zilanawala A., Booker C. Social media use and adolescent mental health: Findings from the UK Millennium Cohort Study. EClinicalMedicine. 2018;6:59–68. PubMed PMC

Twenge J., Joiner T., Rogers M. Increases in depressive symptoms, suicide-related outcomes, and suicide rates among U.S. adolescents after 2010 and links to increased new media screen time. Clin Psychol Sci. 2018;6:3–17.

Al-Menayes J.J. Social media use, engagement and addiction as predictors of academic performance. Int J Psychol Stud. 2015;7:86–94.

Marino C., Gini G., Vieno A. The associations between problematic Facebook use, psychological distress and well-being among adolescents and young adults: A systematic review and meta-analysis. J Affect Disord. 2018;226:274–281. PubMed

Van den Eijnden R.J.J.M., Lemmens J., Valkenburg P.M. The social media disorder scale: Validity and psychometric properties. Comput Hum Behav. 2016;61:478–487.

Van den Eijnden R.J.J.M., Koning I.M., Doornwaard S. The impact of heavy and disordered use of games and social media on adolescents’ psychological, social, and school functioning. J Behav Addict. 2018;7:697–706. PubMed PMC

Boer M, Stevens GWJM, Finkenauer C, et al ADHD-symptoms, social media use intensity, and social media use problems in adolescents: Investigating directionality. Child Dev; In Press. PubMed PMC

Pera A. Psychopathological processes involved in social comparison, depression, and envy on Facebook. Front Psychol. 2018;9:1–5. PubMed PMC

Salmela-Aro K., Upadyaya K., Hakkarainen K. The dark side of internet use: Two longitudinal studies of excessive internet use, depressive symptoms, school burnout and engagement among Finnish early and late adolescents. J Youth Adolesc. 2017;46:343–357. PubMed

Wallsten S. National Bureau of Economic Research; Cambridge: 2013. What we are not doing when we’re online.

Vannucci A., McCauley Ohannessian C. Social media use subgroups differentially predict psychosocial well-being during early adolescence. J Youth Adolesc. 2019;48:1469–1493. PubMed

Boyd D. Yale University Press; New Haven (CT): 2014. It’s complicated: The social lives of networked teens.

Andreassen C. Online social network site addiction: A comprehensive review. Curr Addict Rep. 2015;2:175–184.

Shensa A., Escobar-Viera C.G., Sidani J.E. Problematic social media use and depressive symptoms among U.S. Young adults: A nationally-representative study. Soc Sci Med. 2017;182:150–157. PubMed PMC

Sznitman S.R., Kolobov T., ter Bogt T. Investigating cannabis use normalization by distinguishing between experimental and regular use: A multilevel study in 31 countries. J Stud Alcohol Drugs. 2015;76:181–189. PubMed PMC

Haskuka M., Arenliu A., Kelmendi K. The relationship between substance use and suicidal behaviour among adolescents in selected European countries: A test of normalisation theory. Drugs Educ Prev Pol. 2018;25:413–421.

Pennay A.E., Measham F.C. The normalisation thesis – 20 years later. Drugs Educ Prev Pol. 2016;23:187–189.

Eurostat . Publications Office of the European Union; Luxembourg: 2015. Being young in Europe today.

Inchley J., Currie D., Cosma A. Child & Adolescent Health Research Unit; St. Andrews: 2018. Health behaviour in school-aged Children (HBSC) study protocol: Background, methodology and mandatory items for the 2017/18 survey.

Mascheroni G., Ólafsson K. 2nd ed. Educatt; Milano: 2014. Access and use. Net Child. Go Mob. Risks Oppor; pp. 11–23.

Bollen K., Lennox R. Conventional wisdom on measurement: A structural equation perspective. Psychol Bull. 1991;110:305–314.

Boer M, Stevens GWJM, Koning I, et al Validation of the social media disorder scale in adolescents: Findings from a large-scale nationally representative sample (under review) n.d.. PubMed PMC

Gadermann A.M., Guhn M., Zumbo B.D. Estimating ordinal reliability for Likert-type and ordinal item response data: A conceptual, empirical, and practical guide. Pract Assess Res Eval. 2012;17

Cantril H. Rutgers University Press; New Brunswick: 1965. The pattern of human concerns.

Levin K.A., Currie C. Reliability and validity of an adapted version of the Cantril ladder for use with adolescent samples. Soc Indic Res. 2014;119:1047–1063.

Gariepy G., McKinnon B., Sentenac M. Validity and reliability of a brief symptom checklist to measure psychological health in school-aged children. Child Indic Res. 2016;9:471–484.

Inchley J., Currie D., Young T. Kopenhagen; Denemarken: 2016. Growing up unequal: Gender and socioeconomic differences in young people’s health and well-being. Health Behaviour in School-aged Children (HBSC) study: International report from the 2013/2014 survey.

Klinger D.A., Freeman J.G., Bilz L. Cross-national trends in perceived school pressure by gender and age from 1994 to 2010. Eur J Public Health. 2015;25:51–56. PubMed

Torsheim T., Wold B. School-related stress, school support, and somatic complaints: A general population study. J Adolesc Res. 2001;16:293–303.

Zimet G.D., Dahlem N.W., Zimet S.G. The multidimensional scale of perceived social support. J Pers Assess. 1988;51:30–41.

Elgar F.J., Gariépy G., Torsheim T. Early-life income inequality and adolescent health and well-being. Soc Sci Med. 2017;174:197–208. PubMed

OECD OECD broadband portal. https://www.oecd.org/sti/broadband/broadband-statistics/ Available at:

Muthén L.K., Muthén B.O. Mplus user’s guide. 8th. Los Angeles (CA); Muthén & Muthén: 2017.

Reiter J.P., Raghunathan T.E., Kinney S.K. The importance of modeling the sampling design in multiple imputation for missing data. Surv Methodol. 2006;32:143149.

Burnham K.P., Anderson D.R. Multimodel inference. Sociol Methods Res. 2004;33:261–304.

Hox J. Routledge; New York, NY: 2010. The basic two-level regression model. Multilevel Anal. Tech. Appl. pp. 11–39.

Hox J. Routledge; New York, NY: 2010. Some important methodological and statistical issues. Multilevel Anal. Tech. Appl. pp. 54–78.

Best P., Manktelow R., Taylor B. Online communication, social media and adolescent wellbeing: A systematic narrative review. Child Youth Serv Rev. 2014;41:27–36.

Verduyn P., Ybarra O., Résibois M. Do social network sites enhance or undermine subjective well-being? A critical review. Soc Issues Policy Rev. 2017;11:274–302.

Arnarsson A., Bjarnason T. The problem with low-prevalence of bullying. Int J Environ Res Public Health. 2018;15 PubMed PMC

Raudsepp L., Kais K. Longitudinal associations between problematic social media use and depressive symptoms in adolescent girls. Prev Med Rep. 2019;15:100925. PubMed PMC

Li J., Mo P.K.H., Lau J.T.F. Online social networking addiction and depression: The results from a large-scale prospective cohort study in Chinese adolescents. J Behav Addict. 2018;7:686–696. PubMed PMC

Orben A., Przybylski A.K. Screens, teens, and psychological well-being: Evidence from three time-use-diary studies. Psychol Sci. 2019;30:682–696. PubMed PMC

Orben A., Przybylski A.K. The association between adolescent well-being and digital technology use. Nat Hum Behav. 2019;3:173–182. PubMed

Verduyn P., Lee D.S., Park J. Passive Facebook usage undermines affective well-being: Experimental and longitudinal evidence. J Exp Psychol Gen. 2015;144:480–488. PubMed

Wenninger H., Krasnova H., Buxmann P. Activity matters: Investigating the influence of Facebook on life satisfaction of teenage users. Pap Present Twenty Second Eur Conf Inf Syst Tel Aviv, Isr. 2014:0–18.

Internet addiction: the Czech and Slovak adolescent population

Cross-national validation of the social media disorder scale: findings from adolescents from 44 countries