Schermtijd van 1 tot 8 jaar en de daaropvolgende academische prestaties en het werkgeheugen

Samenvatting

Achtergrond

Schermtijd is geassocieerd met de academische en cognitieve resultaten van kinderen, maar longitudinale studies zijn schaars. Dit belemmert de identificatie van de meest gevoelige leeftijdsperioden. In dit onderzoek hebben we de associaties van zowel enkelvoudige als cumulatieve gemiddelde schermtijd met academische prestaties en het werkgeheugen beoordeeld.

Methoden

Binnen de geboortecohort Growing Up in Singapore Towards healthy Outcomes (GUSTO) rapporteerden ouders de schermtijd van hun kind op 1, 1,5, 2, 3, 6 en 8-jarige leeftijd. Op 9-jarige en 10,5-jarige leeftijd beoordeelden getrainde psychologen de academische prestaties (via de Wechsler Individual Achievement Test-Third Edition) en het werkgeheugen (via de Letter-Number Sequencing taak en de Wechsler Intelligence Scale for Children-Fifth Edition). De associaties tussen enkelvoudige en cumulatieve gemiddelde schermtijd en de psychologische uitkomsten werden onderzocht middels multivariabele lineaire regressie (N = 502 kinderen).

Resultaten

De gemiddelde schermtijd (standaarddeviatie) varieerde van 2,1 (2,0) uur per dag op 1-jarige leeftijd tot 3,0 (2,2) uur per dag op 8-jarige leeftijd.

In niet-gecorrigeerde modellen was een hogere schermtijd van 1 tot 8 jaar consistent geassocieerd met slechtere academische prestaties op 9-jarige leeftijd en een slechter werkgeheugen op 10,5-jarige leeftijd. Na correctie werden de effectgroottes verkleind, maar bleven er significante associaties bestaan tussen een hogere schermtijd op de volgende leeftijden en slechtere academische prestaties op 9-jarige leeftijd:

  • 1 jaar: $\beta$ = – 1,47 (95% betrouwbaarheidsinterval (BI): – 2,37 tot – 0,57 standaardpunten per extra uur per dag)
  • 1,5 jaar: $\beta$ = – 0,95 (95% BI: – 1,85 tot – 0,06)
  • 6 jaar: $\beta$ = – 0,88 (95% BI: – 1,55 tot – 0,21)

Daarnaast was een grotere schermtijd op 1-jarige leeftijd ($\beta$ = – 1,12, 95% BI: – 2,07 tot – 0,17) en 6-jarige leeftijd ($\beta$ = – 1,01, 95% BI: – 1,71 tot – 0,31) geassocieerd met een slechter werkgeheugen op 10,5-jarige leeftijd. Modellen voor cumulatieve gemiddelde blootstelling toonden aan dat schermtijd gedurende de kindertijd consistent geassocieerd was met slechtere academische prestaties, maar niet met het werkgeheugen.

Conclusie

In deze longitudinale studie was de cumulatieve gemiddelde schermtijd geassocieerd met lagere academische prestaties, maar niet met het werkgeheugen. De sterkste effectgroottes voor enkelvoudige schermtijd werden waargenomen in de vroege kinderjaren.

Beschikbaarheid van gegevens

Deze cohortstudie vereist ethische goedkeuring voor elke specifieke onderzoeksvraag voordat gegevens gedeeld kunnen worden. De gegevens die in deze cohort worden gebruikt, zijn beschreven op https://gustodatavault.sg/. Geanonimiseerde individuele deelnemergegevens (inclusief datacatalogi) worden beschikbaar gesteld, samen met studieprotocollen, het statistische analyseplan en het formulier voor geïnformeerde toestemming. De gegevens worden na publicatie beschikbaar gesteld aan onderzoekers die een methodologisch onderbouwd voorstel indienen om de goedgekeurde doelen te bereiken. Voorstellen kunnen worden ingediend via https://www.gusto.sg/request-to-collaborate/.

Financiering

De GUSTO-studie is gefinancierd door de Singapore National Research Foundation onder het Translational and Clinical Research Flagship Programme en wordt beheerd door de National Medical Research Council van het Singapore Ministerie van Volksgezondheid (Singapore NMRC/TCR/0004-NUS/2008 en NMRC/TCR/012-NUHS/2014). Aanvullende financiering is verstrekt door het Institute for Human Potential and Development, Agency for Science Technology and Research.

Auteur JYB werd ondersteund door een beurs van de Agence Nationale de la Recherche (ANR) (iSCAN-project, ANR-20-CE36-0001). Auteur SY werd ondersteund door een beurs van de Agence Nationale de la Recherche (ANR) (iSCAN-project, ANR-20-CE36-0001) en door mobiliteitsbeurzen van de Université Paris Cité en de National University of Singapore. Auteur KMG wordt ondersteund door de UK Medical Research Council (MCUU12011/4), het National Institute for Health and Care Research [NIHR Senior Investigator (NF-SI-0515-10042) en NIHR Southampton Biomedical Research Centre (NIHR203319)] en Alzheimer’s Research UK (ARUK-PG2022A-008).

De financiers waren niet betrokken bij het ontwerp en de uitvoering van de studie, de verzameling, het beheer, de analyse en de interpretatie van de gegevens, de voorbereiding, revisie of goedkeuring van het manuscript, noch bij de beslissing om het manuscript ter publicatie in te dienen.

Referenties

  • World Health Organization. New WHO guidelines on physical activity, sedentary behaviour and sleep for children under 5 years of age. 2019.
  • Brown A. Media use by children younger than 2 years. Pediatrics. 2011;128:1040–5.
  • Tremblay MS, et al. Systematic review of sedentary behaviour and health indicators in school-aged children and youth. Int J Behav Nutr Phys Act. 2011;8:98.
  • LeBlanc AG, et al. Systematic review of sedentary behaviour and health indicators in the early years (aged 0-4 years). Appl Physiol Nutr Metab. 2012;37:753–72.
  • Kostyrka-Allchorne K, Cooper NR, Simpson A. The relationship between television exposure and children’s cognition and behaviour: a systematic review. Dev Rev. 2017;44:19–58.
  • Poitras VJ, et al. Systematic review of the relationships between sedentary behaviour and health indicators in the early years (0–4years). BMC Public Health. 2017;17:868.
  • Stiglic N, Viner RM. Effects of screentime on the health and well-being of children and adolescents: a systematic review of reviews. BMJ Open. 2019;9:e023191.
  • Ferguson CJ, et al. Like this meta-analysis: screen media and mental health. Prof Psychol Res Pract. 2022;53:205–14.
  • Yang S, et al. Associations of screen use with cognitive development in early childhood: the ELFE birth cohort. J Child Psychol Psychiatry. 2024;65:680–93.
  • Sticca F, Brauchli V, Lannen P. Screen on = development off? A systematic scoping review and a developmental psychology perspective on the effects of screen time on early childhood development. Front Dev Psychol. 2025;2:1439040.
  • Madigan S, et al. Associations between screen use and child language skills: a systematic review and meta-analysis. JAMA Pediatr. 2020;174:665–75.
  • Duch H, et al. Association of screen time use and language development in Hispanic toddlers: a cross-sectional and longitudinal study. Clin Pediatr. 2013;52:857–65.
  • Martinot P, et al. Exposure to screens and children’s language development in the EDEN mother-child cohort. Sci Rep. 2021;11:11863.
  • Nichols DL. The context of background TV exposure and children’s executive functioning. Pediatr Res. 2022;92:1168–74.
  • Blankson AN, et al. Do hours spent viewing television at ages 3 and 4 predict vocabulary and executive functioning at age 5? Merrill Palmer Q. 2015;61:264–89.
  • Yang X, Chen Z, Wang Z, Zhu L. The relations between television exposure and executive function in Chinese preschoolers: the moderated role of parental mediation behaviors. Front Psychol. 2017;8:1833.
  • Duncan GJ, et al. School readiness and later achievement. Dev Psychol. 2007;43:1428–46.
  • Bücker S, et al. Subjective well-being and academic achievement: a meta-analysis. J Res Pers. 2018;74:83–94.
  • Roisman GI, et al. Salient and emerging developmental tasks in the transition to adulthood. Child Dev. 2004;75:123–33.
  • Lê-Scherban F, et al. Does academic achievement during childhood and adolescence benefit later health? Ann Epidemiol. 2014;24:344–55.
  • French MT, et al. What you do in high school matters: high school GPA, educational attainment, and labor market earnings as a young adult. East Econ J. 2015;41:370–86.
  • Adelantado-Renau M, et al. Association between screen media use and academic performance among children and adolescents: a systematic review and meta-analysis. JAMA Pediatr. 2019;173:1058–67.
  • Poulain T, et al. Cross-sectional and longitudinal associations of screen time and physical activity with school performance at different types of secondary school. BMC Public Health. 2018;18:563.
  • Howie EK, et al. Associations between meeting sleep, physical activity or screen time behaviour guidelines and academic performance in Australian school children. BMC Public Health. 2020;20:520.
  • Neophytou E, Manwell LA, Eikelboom R. Effects of excessive screen time on neurodevelopment, learning, memory, mental health, and neurodegeneration: a scoping review. Int J Ment Health Addict. 2021;19:724–44.
  • Morita N, et al. Relationships among fitness, obesity, screen time and academic achievement in Japanese adolescents. Physiol Behav. 2016;163:161–6.
  • Paulich KN, et al. Screen time and early adolescent mental health, academic, and social outcomes in 9- and 10- year old children: utilizing the Adolescent Brain Cognitive Development ℠ (ABCD) Study. PLoS ONE. 2021;16:e0256591.
  • Lien A, et al. Adherence to 24-hour movement guidelines and academic performance in adolescents. Public Health. 2020;183:8–14.
  • Ozmert E, Toyran M, Yurdakök K. Behavioral correlates of television viewing in primary school children evaluated by the Child Behavior Checklist. Arch Pediatr Adolesc Med. 2002;156:910–4.
  • Skoric MM, Teo LL, Neo RL. Children and video games: addiction, engagement, and scholastic achievement. Cyberpsychol Behav. 2009;12:567–72.
  • Drummond A, Sauer JD. Video-games do not negatively impact adolescent academic performance in science, mathematics or reading. PLoS ONE. 2014;9:e87943.
  • Regondola E, Barbado L. Media habits and academic performance of elementary pupils of the Camarines Norte State College Laboratory School. IJIR. 2017;3:216–24.
  • Bowers AJ, Berland M. Does recreational computer use affect high school achievement? Educ Technol Res Dev. 2013;61:51–69.
  • Houdé O, Borst G. The Cambridge handbook of cognitive development. Cambridge: Cambridge University Press; 2022.
  • Ponti M. Screen time and preschool children: promoting health and development in a digital world. Paediatr Child Health. 2023;28:184–202.
  • Marciano L, Camerini AL. Recommendations on screen time, sleep and physical activity: associations with academic achievement in Swiss adolescents. Public Health. 2021;198:211–7.
  • Soh SE, et al. Cohort profile: Growing Up in Singapore Towards Healthy Outcomes (GUSTO) birth cohort study. Int J Epidemiol. 2014;43:1401–9.
  • Aishworiya R, et al. Television viewing and child cognition in a longitudinal birth cohort in Singapore: the role of maternal factors. BMC Pediatr. 2019;19:286.
  • Dumont R, et al. Wechsler individual achievement test–third edition. In: Encyclopedia of special education. 2013.
  • Padmapriya N, et al. The prospective associations of 24-hour movement behaviors and domain-specific activities with executive function and academic achievement among school-aged children in Singapore. Front Public Health. 2024;12:1412634.
  • Watkins MW, et al. Reliability and factorial validity of the Canadian Wechsler intelligence scale for children–fifth edition. Int J Sch Educ Psychol. 2018;6:252–65.
  • Rifkin-Graboi A, et al. Maternal sensitivity, infant limbic structure volume and functional connectivity: a preliminary study. Transl Psychiatry. 2015;5:e668.
  • de Groot S, et al. Single and cumulative exposure to psychosocial work conditions and mental health among young adults. Eur J Public Health. 2023;33:257–63.
  • Brew BK, et al. Longitudinal depression or anxiety in mothers and offspring asthma: a Swedish population-based study. Int J Epidemiol. 2018;47:166–74.
  • Liu S, Jones RN, Glymour MM. Implications of lifecourse epidemiology for research on determinants of adult disease. Public Health Rev. 2010;32:489–511.
  • Shah AD, et al. Comparison of random forest and parametric imputation models for imputing missing data using MICE: a CALIBER study. Am J Epidemiol. 2014;179:764–74.
  • Stekhoven DJ, Bühlmann P. MissForest—non-parametric missing value imputation for mixed-type data. Bioinformatics. 2012;28:112–8.
  • Rothman KJ. No adjustments are needed for multiple comparisons. Philadelphia: Epidemiology. Lippincott Williams & Wilkins; 1990.
  • Greenland S. Null misinterpretation in statistical testing and its impact on health risk assessment. Prev Med. 2011;53:225–8.
  • Lash TL, et al. Modern epidemiology. 4th edition. Alphen aan den Rijn: Wolters Kluwer; 2021.
  • Zimmerman FJ, et al. Associations between media viewing and language development in children under age 2 years. J Pediatr. 2007;151:364–8.
  • Johnson JG, et al. Extensive television viewing and the development of attention and learning difficulties during adolescence. Arch Pediatr Adolesc Med. 2007;161:480–6.
  • Hancox RJ, Milne BJ, Poulton R. Association of television viewing during childhood with poor educational achievement. Arch Pediatr Adolesc Med. 2005;159:614–8.
  • Gaddy GD. Television’s impact on high school achievement. Public Opin Q. 1986;50:340–59.
  • Carson V, et al. Systematic review of sedentary behaviour and health indicators in school-aged children and youth: an update. Appl Physiol Nutr Metab. 2016;41:S240–65.
  • Keith TZ, et al. Parental involvement, homework, and TV time: direct and indirect effects on high school achievement. J Educ Psychol. 1986;78:373–80.
  • Christakis DA, et al. Early television exposure and subsequent attentional problems in children. Pediatrics. 2004;113:708–13.
  • Law EC, et al. Associations between infant screen use, electroencephalography markers, and cognitive outcomes. JAMA Pediatr. 2023;177:311.
  • Koolstra CM, et al. Television’s impact on children’s reading comprehension and decoding skills: a 3-year panel study. Read Res Q. 1997;32(2):128–52.
  • Chen W, Adler JL. Assessment of screen exposure in young children, 1997 to 2014. JAMA Pediatr. 2019;173:391.
  • Bernard JY, et al. Temps d’écran de 2 à 5 ans et demi chez les enfants de la cohorte nationale Elfe. Bull Épidémiol Hebd. 2023;6:98–105.

Auteurs en Affiliaties

Auteurs: Shuai Yang, Natarajan Padmapriya, Saw Seang-Mei, Chong Yap Seng, Lynette P. Shek, Peter D. Gluckman, Keith M. Godfrey, Johan G. Eriksson, Falk Müller-Riemenschneider, Evelyn C. Law, Jonathan Y. Bernard.

Affiliaties:

  • Centre for Research in Epidemiology and StatisticS (CRESS), Université Paris Cité en Université Sorbonne Paris Nord, Inserm, INRAE, Parijs, Frankrijk.
  • Department of Obstetrics & Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, National University Health System, Singapore.
  • Saw Swee Hock School of Public Health, National University of Singapore, Singapore.
  • Institute for Human Potential and Development (IHPD), Agency for Science, Technology and Research (A*STAR), Singapore.
  • Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
  • Khoo Teck Puat-National University Children’s Medical Institute, National University Health System, Singapore.
  • Medical Research Council Lifecourse Epidemiology Centre, University of Southampton, Verenigd Koninkrijk.
  • NIHR Southampton Biomedical Research Centre, University of Southampton en University Hospital Southampton NHS Foundation Trust, Verenigd Koninkrijk.
  • Department of General Practice and Primary Health Care, University of Helsinki en Helsinki University Hospital, en Folkhälsan Research Center, Helsinki, Finland.
  • Digital Health Center, Berlin Institute of Health, Charité-Universitätsmedizin Berlin, Berlijn, Duitsland.
  • Duke-National University of Singapore Medical School, Singapore.
  • Liggins Institute, University of Auckland, Auckland, Nieuw-Zeeland.