Type of screen time and academic achievement in children from Australia and New Zealand: interactions with socioeconomic status

References

• Barger, M. M., Kim, E. M., Kuncel, N. R., & Pomerantz, E. M. (2019). The relation between parents’ involvement in children’s schooling and children’s adjustment: A meta-analysis. Psychological Bulletin, 145(9), 855–890.
   Google Scholar
• Barry, J. (2006). The effect of socioeconomic status on academic achievement.
   Google Scholar
• Belmon, L. S., van Stralen, M. M., Busch, V., Harmsen, I. A., & Chinapaw, M. J. M. (2019). What are the determinants of children’s sleep behavior? A systematic review of longitudinal studies. Sleep Medicine Reviews, 43, 60–70.
   Google Scholar
• Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: Series B (Methodological), 57(1), 289–300.
   Google Scholar
• Busch, V., Loyen, A., Lodder, M., Schrijvers, A. J. P., van Yperen, T. A., & de Leeuw, J. R. J. (2014). The effects of adolescent health-related behavior on academic performance: A systematic review of the longitudinal evidence. Review of Educational Research, 84(2), 245–274.
   Google Scholar
• Carson, V., Hunter, S., Kuzik, N., Gray, C. E., Poitras, V. J., Chaput, J.-P., … Tremblay, M. S. (2016). Systematic review of sedentary behaviour and health indicators in school-aged children and youth: An update. Applied Physiology, Nutrition & Metabolism, 41, S240–S265.
   Google Scholar
• Dewald, J. F., Meijer, A. M., Oort, F. J., Kerkhof, G. A., & Bögels, S. M. (2010). The influence of sleep quality, sleep duration and sleepiness on school performance in children and adolescents: A meta-analytic review. Sleep Medicine Reviews, 14(3), 179–189.
   Google Scholar
• Domingues‐Montanari, S. (2017). Clinical and psychological effects of excessive screen time on children. Journal of Paediatrics and Child Health, 53(4), 333–338.
   Google Scholar
• Dumuid, D., Olds, T., Maher, C., Lewis, L. K., Martín-Fernández, J.-A., & Cassidy, L. (2017). Academic performance and lifestyle behaviors in Australian school children: A cluster analysis. Health Education & Behavior, 44(6), 918–927.
   Google Scholar
• Duncan, G. J., Magnuson, K., & Votruba-Drzal, E. (2017). Moving beyond correlations in assessing the consequences of poverty. Annual Review of Psychology, 68(1), 413–434.
   Google Scholar
• Duncan, G. J., Morris, P. A., & Rodrigues, C. (2011). Does money really matter? Estimating impacts of family income on young children’s achievement with data from random-assignment experiments. Developmental Psychology, 47(5), 1263–1279. https://doi-org.ezproxy-b.deakin.edu.au/10.1037/a0023875
   Google Scholar
• Ennemoser, M., & Schneider, W. (2007). Relations of television viewing and reading: Findings from a 4-year longitudinal study. Journal of Educational Psychology, 99(2), 349–368.
   Google Scholar
• Fiorella, L., & Mayer, R. E. (2016). Eight ways to promote generative learning. Educational Psychology Review, 28(4), 717–741.
   Google Scholar
• Hale, L., & Guan, S. (2015). Screen time and sleep among school-aged children and adolescents: A systematic literature review. Sleep Medicine Reviews, 21, 50–58.
   Google Scholar
• Hayes, A. F. (2017). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. New York: Guilford Publications.
   Google Scholar
• Hisler, G., Twenge, J., & Krizan, Z. (2019). Associations between screen time and short sleep duration among adolescents varies by media type: Evidence from a cohort study. Sleep Medicine. doi:https://doi.org/10.1016/j.sleep.2019.08.007
   Google Scholar
• IBM Corp. (2017). IBM SPSS statistics for windows, version 25.0. Armonk, NY: Author.
   Google Scholar
• Kalmus, V., Runnel, P., & Siibak, A. (2009). Opportunities and benefits online (pp.71–82).
   Google Scholar
• Kansky, J., Allen, J. P., & Diener, E. (2016). Early adolescent affect predicts later life outcomes. Applied Psychology: Health and Well‐Being, 99(2), 192–212.
   Google Scholar
• LeBourgeois, M. K., Hale, L., Chang, A.-M., Akacem, L. D., Montgomery-Downs, H. E., & Buxton, O. M. (2017). Digital media and sleep in childhood and adolescence. Pediatrics, 140(5, Supp 2), S92–S96.
   Google Scholar
• Mielke, G. I., Brown, W. J., Nunes, B. P., Silva, I. C. M., & Hallal, P. C. (2017). Socioeconomic correlates of sedentary behavior in adolescents: Systematic review and meta-analysis. Sports Medicine, 47(1), 61–75.
   Google Scholar
• Nelson, T. D., Lundahl, A., Molfese, D. L., Waford, R. N., Roman, A., Gozal, D., … Ferguson, M. C. (2014). Estimating child sleep from parent report of time in bed: Development and evaluation of adjustment approaches. Journal of Pediatric Psychology, 39(6), 624–632.
   Google Scholar
• O’Connell, M. (2019). Is the impact of SES on educational performance overestimated? Evidence from the PISA survey. Intelligence, 75, 41–47.
   Google Scholar
• Pabilonia, S. W. (2016). Children’s media use and homework time (pp. 91–107). New York: Palgrave Macmillan US.
   Google Scholar
• Pool, M. M., Koolstra, C. M., & van der Voort, T. H. A. (2006). The impact of background radio and television on high school students’ homework performance. Journal of Communication, 53(1), 74–87.
   Google Scholar
• Pearson Clinical (2016). WIAT III: Wechsler Individual Achievement Test. Third Edition Australia and New Zealand. Melbourne: Pearson Clinical Australia.
   Google Scholar
• R Core Team. (2019). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. Retrieved from https://www.R-project.org/
   Google Scholar
• Sharif, I., & Sargent, J. D. (2006). Association between television, movie, and video game exposure and school performance. Pediatrics, 118(4), e1061–e1070.
   Google Scholar
• Short, M. A., Gradisar, M., Lack, L. C., Wright, H. R., & Chatburn, A. (2013). Estimating adolescent sleep patterns: Parent reports versus adolescent self-report surveys, sleep diaries, and actigraphy. Nature and Science of Sleep, 5, 23–26.
   Google Scholar
• Siddiq, F., & Scherer, R. (2019). Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy. Educational research review, 27, 205–217.
   Google Scholar
• Sirin, S. R. (2005). Socioeconomic status and academic achievement: A meta-analytic review of research. Review of Educational Research, 75(3), 417–453.
   Google Scholar
• Sweetser, P., Johnson, D., Ozdowska, A., & Wyeth, P.(2012). Active versus passive screen time for young children. Australasian Journal of Early Childhood,37(4), 94–98.
   Google Scholar
• Tucker-Drob, E. M., & Bates, T. C. (2016). Large cross-national differences in gene× socioeconomic status interaction on intelligence. Psychological Science, 27(2), 138–149.
   Google Scholar
• Victorian Registration and Qualification Authority (VRQA). (2019). VRQA annual report 2018-19. Victorian Government. Retrieved from https://www.vrqa.vic.gov.au/aboutus/Pages/annual-reports.aspx
   Google Scholar
• White, K. R. (1982). The relation between socioeconomic status and academic achievement. Psychological Bulletin, 91(3), 461.
   Google Scholar
• Xie, H., Peng, J., Qin, M., Huang, X., Tian, F., & Zhou, Z. (2018). Can touchscreen devices be used to facilitate young children’s learning? A meta-analysis of touchscreen learning effect. Frontiers in Psychology, 9(2580). doi:https://doi.org/10.3389/fpsyg.2018.02580
   Google Scholar
• Yland, J., Guan, S., Emanuele, E., & Hale, L. (2015). Interactive vs passive screen time and nighttime sleep duration among school-aged children. Sleep Health, 1(3), 191–196.
   Google Scholar
• Yu, M., & Baxter, J. (2016). Chapter 5 - Australian children’s screen time and participation in extracurricular activities. In K. Day (Ed). The Longitudinal Study of Australian Children Annual Statistical Report 2015, (99–124). Melbourne: Australian Institute of Family Studies.
   Google Scholar