Adolescents' online communication and well-being: Findings from the 2018 health behavior in school-aged children (HBSC) study.

Nelli Lyyra, Niina Junttila, Jasmine Gustafsson, Henri Lahti, Leena Paakkari
Author Information
  1. Nelli Lyyra: Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland.
  2. Niina Junttila: Department of Teacher Education, University of Turku, Turku, Finland.
  3. Jasmine Gustafsson: Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland.
  4. Henri Lahti: Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland.
  5. Leena Paakkari: Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland.

Abstract

Background: Digital transformation has influenced all areas of adolescents' lives, including the ways adolescents maintain friendships. Interpersonal communication is one of the most common activities while online. Online communication may provide adolescents with opportunities to expand their social contacts, but these encounters can be risky, especially when the communication is with unknown people on the internet. This study examined the associations between different forms of online communication behavior and well-being.
Materials and methods: Data were collected from Finnish adolescents as part of the Health Behavior in School-Aged Children (HBSC) study in 2018. The participants were 3,140 Finnish adolescents aged 11-15 years. Descriptive analyses were used to examine the frequency of different forms of online communication behaviors. The associations between online communications and individual factors were analyzed using the X test and 95% confidence intervals. Structural equation modeling (SEM) was used to analyze the extent to which adolescents' online communication behavior explained the variance in adolescents' well-being indicators.
Results: Overall, 60% of the adolescents reported communicating intensively with close friends, with higher rates of intensive communication reported by girls, higher age groups, and the high health literacy group. 22% of adolescents reported intensive communication with friends they got to know through the internet (online friends), while intensive online communication with unknown people was reported by 13% of adolescents. Overall, around one-fourth of adolescents preferred sharing personal matters online rather than in face-to-face encounters, and 10% of adolescents reported using the internet daily to get to know new people, and to look for like-minded company. The SEM analysis showed that keeping online contact with offline friends was linked to a positive outcome in all the measured well-being indicators; however, intensive communication with people contacted only online (online friends and unknown people) was negatively associated with well-being indicators (lower self-rated health, lower life satisfaction, higher loneliness, and problematic social media use).
Conclusion: Both positive and negative associations were observed between online communication and well-being, depending on the target and content of the communication. The results indicate that online communication has benefits for adolescents who have more offline social life. Overall, one should ensure that the impact of interventions is proportionately greater for adolescents at the bottom end of the health gradient.

Keywords

References

  1. Body Image. 2007 Dec;4(4):353-60 [PMID: 18089281]
  2. Cyberpsychol Behav Soc Netw. 2017 Jun;20(6):346-354 [PMID: 28622031]
  3. Lancet. 2021 Nov 6;398(10312):1727-1776 [PMID: 34706260]
  4. Eur J Public Health. 2015 Apr;25 Suppl 2:7-12 [PMID: 25805778]
  5. Sci Rep. 2020 Jul 1;10(1):10763 [PMID: 32612108]
  6. Int J Environ Res Public Health. 2022 Feb 19;19(4): [PMID: 35206593]
  7. Nat Hum Behav. 2021 Nov;5(11):1535-1547 [PMID: 34002052]
  8. Eur J Public Health. 2019 Jun 1;29(3):432-436 [PMID: 30412226]
  9. J Health Econ. 2020 Jan;69:102274 [PMID: 31887480]
  10. J Adolesc Health. 2020 Jun;66(6S):S89-S99 [PMID: 32446614]
  11. Assessment. 2022 Dec;29(8):1658-1675 [PMID: 34189943]
  12. Future Child. 2008 Spring;18(1):119-46 [PMID: 21338008]
  13. Am Psychol. 1998 Sep;53(9):1017-31 [PMID: 9841579]
  14. J Health Commun. 2016;21(sup2):61-68 [PMID: 27669363]
  15. Int J Environ Res Public Health. 2021 Feb 15;18(4): [PMID: 33672074]
  16. Am J Epidemiol. 1983 Mar;117(3):292-304 [PMID: 6829557]
  17. Lancet Child Adolesc Health. 2018 Feb;2(2):79 [PMID: 30169237]
  18. Int J Environ Res Public Health. 2020 May 19;17(10): [PMID: 32438595]
  19. Suicide Life Threat Behav. 2015 Apr;45(2):178-91 [PMID: 25255896]
  20. J Adolesc Health. 2005 Jan;36(1):9-18 [PMID: 15661591]
  21. J Youth Adolesc. 2010 Oct;39(10):1226-39 [PMID: 20177962]
  22. Am J Mens Health. 2010 Mar;4(1):77-85 [PMID: 20164062]
  23. Int J Public Health. 2019 Dec;64(9):1301-1311 [PMID: 31297559]
  24. BMC Public Health. 2018 Mar 20;18(1):321 [PMID: 29554883]
  25. Int J Psychiatry Clin Pract. 2019 Jun;23(2):160-162 [PMID: 30570343]
  26. Scand J Public Health. 2016 Dec;44(8):751-757 [PMID: 27655781]
  27. Lancet Child Adolesc Health. 2020 Aug;4(8):634-640 [PMID: 32540024]
  28. Int J Soc Psychiatry. 2022 Feb;68(1):12-33 [PMID: 33295241]
  29. J Gen Intern Med. 2006 Mar;21(3):267-75 [PMID: 16336622]
  30. Cyberpsychol Behav Soc Netw. 2010 Jun;13(3):279-85 [PMID: 20557247]
  31. Public Health. 2012 Sep;126 Suppl 1:S4-S10 [PMID: 22784581]
  32. Int J Environ Res Public Health. 2021 Jun 29;18(13): [PMID: 34209886]
  33. J Affect Disord. 2020 Oct 1;275:165-174 [PMID: 32734903]

Word Cloud

Created with Highcharts 10.0.0communicationonlineadolescentswell-beingpeoplereportedfriendshealthsocialintensiveadolescents'unknowninternetstudyassociationsbehaviorindicatorsOverallhigheroneencountersdifferentformsFinnishHBSC2018usedusingSEMknowofflinepositivelowerlifelonelinessmediaBackground:DigitaltransformationinfluencedareaslivesincludingwaysmaintainfriendshipsInterpersonalcommonactivitiesOnlinemayprovideopportunitiesexpandcontactscanriskyespeciallyexaminedMaterialsmethods:DatacollectedpartHealthBehaviorSchool-AgedChildrenparticipants3140aged11-15yearsDescriptiveanalysesexaminefrequencybehaviorscommunicationsindividualfactorsanalyzedXtest95%confidenceintervalsStructuralequationmodelinganalyzeextentexplainedvarianceResults:60%communicatingintensivelycloseratesgirlsagegroupshighliteracygroup22%got13%aroundone-fourthpreferredsharingpersonalmattersratherface-to-face10%dailygetnewlooklike-mindedcompanyanalysisshowedkeepingcontactlinkedoutcomemeasuredhowevercontactednegativelyassociatedself-ratedsatisfactionproblematicuseConclusion:negativeobserveddependingtargetcontentresultsindicatebenefitsensureimpactinterventionsproportionatelygreaterbottomendgradientAdolescents'well-being:Findingsschool-agedchildrenadolescence

Similar Articles

Cited By