American Academy of Pediatrics (AAP). (2016). Council on Communications and Media. (2016). Media Use in School-Aged Children and Adolescents. Pediatrics, 138(5), e20162592.
Article
Google Scholar
Australian Bureau of Statistics. Census of population and housing: socio-economic index for areas (SEIFA), Australia, State Suburb, Indexes, SEIFA 2011. http://www.abs.gov.au. Accessed 02/15/18.
Balázs, J., Miklósi, M., KeresztényÁ., Hoven C. W., Carli V., WassermanC., & Cotter P. (2013). Adolescent subthreshold‐depression and anxiety: Psychopathology, functional impairment and increased suicide risk. Journal of Child Psychology and Psychiatry, 54(6), 670–677.
Article
Google Scholar
Bertha, E. A., & Balázs, J. (2013). Subthreshold depression in adolescence: a systematic review. European Child and Adolescent Psychiatry, 22(10), 589–603.
Article
Google Scholar
Chaiton, M., Contreras, G., Brunet, J., Sabiston, C. M., O’Loughlin, E., Low, N. C., & O’Loughlin, J. (2013). Heterogeneity of depressive symptom trajectories through adolescence: predicting outcomes in young adulthood. Journal of the Canadian Academy of Child and Adolescent Psychiatry, 22(2), 96–105.
PubMed
PubMed Central
Google Scholar
Costello, J. E., Erkanli, A., & Angold, A. (2006). Is there an epidemic of child or adolescent depression? Journal of Child Psychology and Psychiatry, 47(12), 1263–1271.
Google Scholar
Coyne, S. M., Padilla‐Walker, L. M., & Holmgren, H. G. (2018). A six‐year longitudinal study of texting trajectories during adolescence. Child Development, 89(1), 58–65.
Article
Google Scholar
Diamantopoulou, S., Verhulst, F. C., & Van Der Ende, J. (2011). Gender differences in the development and adult outcome of co-occurring depression and delinquency in adolescence. Journal of Abnormal Psychology, 120(3), 644.
Article
Google Scholar
Do, Y. K., Shin, E., Bautista, M. A., & Foo, K. (2013). The associations between self-reported sleep duration and adolescent health outcomes: what is the role of time spent on Internet use? Sleeping Medicine, 14(2), 195–200.
Article
Google Scholar
Durkin, K., & Barber, B. (2002). Not so doomed: Computer game play and positive adolescent development. Journal of Applied Developmental Psychology, 23(4), 373–392.
Article
Google Scholar
Ellis, R. E., Seal, M. L., Simmons, J. G., Whittle, S., Schwartz, O. S., Byrne, M. L., & Allen, N. B. (2017). Longitudinal trajectories of depression symptoms in adolescence: psychosocial risk factors and outcomes. Child Psychiatry & Human Development, 48(4), 554–571.
Article
Google Scholar
Frick, P. J., Barry, C. T., & Kamphaus, R. W. (2009). Parent and teacher rating scales. In P. J. Frick, C. T. Barry, R. W. Kamphaus Clinical assessment of child and adolescent personality and behavior (pp. 141–188). Springer US: Boston, MA
Chapter
Google Scholar
Garber, J., & Cole, D. A. (2010). Intergenerational transmission of depression: a launch and grow model of change across adolescence. Developmental Psychopathology, 22(4), 819–830.
Article
Google Scholar
George, M. J., Russell, M. A., Piontak, J. R., & Odgers, C. L. (2018). Concurrent and subsequent associations between daily digital technology use and high‐risk adolescents’ mental health symptoms. Child Development, 89(1), 78–88.
Article
Google Scholar
Giletta, M., Scholte, R. H. J., Burk, W. J., Engels, R. C. M. E., Larsen, J. K., Prinstein, M. J., & Ciairano, S. (2011). Similarity in depressive symptoms in adolescents friendship dyads: Selection or socialization? Developmental Psychology, 47(6), 1804–1814.
Article
Google Scholar
Goldfield, G. S., Murray, M., Maras, D., Wilson, A. L., Phillips, P., Kenny, G. P., & Sigal, R. J. (2016). Screen time is associated with depressive symptomatology among obese adolescents: a HEARTY study. European Journal of Pediatrics, 175(7), 909–919.
Article
Google Scholar
Gomez-Baya, D., Mendoza, R., Paino, S., & Gillham, J. E. (2017). A two-year longitudinal study of gender differences in responses to positive affect and depressive symptoms during middle adolescence. Journal of Adolescence, 56, 11–23.
Article
Google Scholar
Gunnell, K. E., Flament, M. F., Buchholz, A., Henderson, K. A., Obeid, N., Schubert, N., & Goldfield, G. S. (2016). Examining the bidirectional relationship between physical activity, screen time, and symptoms of anxiety and depression over time during adolescence. Preventive Medicine, 88, 147–152.
Article
Google Scholar
Hamaker, E. L., Kuiper, R. M., & Grasman, R. P. (2015). A critique of the cross-lagged panel model. Psychological Methods, 20(1), 102–116.
Article
Google Scholar
Hankin, B. L., Mermelstein, R., & Roesch, L. (2007). Sex differences in adolescent depression: Stress exposure and reactivity models. Child Development, 78(1), 279–295.
Article
Google Scholar
Hansen, B. E. (1999). Threshold effects in non-dynamic panels: estimation, testing, and inference. Journal of Econometrics, 93(2), 345–368.
Article
Google Scholar
Hoare, E., Millar, L., Fuller-Tyszkiewicz, M., Skouteris, H., Nichols, M., Malakellis, M., Swinburn, B., & Allender, S. (2016). Depressive symptomatology, weight status and obesogenic risk among Australian adolescents: a prospective cohort study. BMJ Open, 6(3), e010072.
Article
Google Scholar
Hodges, K. (1990). Depression and anxiety in children: a comparison of self-report questionnaires to clinical interview. Psychological Assessment: A Journal of Consulting and Clinical Psychology, 2(4), 376–381.
Article
Google Scholar
Houghton, S., Hunter, S. C., & Crow, J. (2013). Assessing callous unemotional traits in children aged 7-to 12-years: a confirmatory factor analysis of the inventory of callous unemotional traits. Journal of Psychopathology and Behavioral Assessment, 35(2), 215–222.
Article
Google Scholar
Houghton, S., Hunter, S. C., Rosenberg, M., Wood, L., Zadow, C., Martin, K., & Shilton, T. (2015). Virtually impossible: limiting Australian children and adolescents daily screen based media use. BMC Public Health, 15(1), 5.
Article
Google Scholar
Hunter, S. C., Houghton, S., Zadow, C., Rosenberg, M., Wood, L., Shilton, T., & Lawrence, D. (2017). Development of the adolescent preoccupation with screens scale. BMC Public Health, 17, 652.
Article
Google Scholar
Jelenchick, L. A., Eickhoff, J. C., & Moreno, M. A. (2013). “Facebook depression?” Social networking site use and depression in older adolescents. Journal of Adolescent Health, 52(1), 128–130.
Article
Google Scholar
Kim, J. Y. (2012). The nonlinear association between Internet using time for non-educational purposes and adolescent health. Journal of Preventive Medicine and Public Health, 45(1), 37.
Article
Google Scholar
Kovacs, M. (2004). Children’s depression inventory (CDI). Toronto: Multi-Health Systems Inc.
Google Scholar
Kraut, R., Patterson, M., Lundmark, V., Kiesler, S., Mukophadhyay, T., & Scherlis, W. (1998). Internet paradox: A social technology that reduces social involvement and psychological well-being? American Psychologist, 53(9), 1017–1031.
Article
Google Scholar
Little, R. J., & Rubin, D. B. (2014). Statistical analysis with missing data (Vol. 333). John Wiley & Sons. Hoboken. New Jersey.
Chapter
Google Scholar
Liu, M., Wu, L., & Yao, S. (2016). Dose–response association of screen time-based sedentary behaviour in children and adolescents and depression: a meta-analysis of observational studies. British Journal of Sports Medicine, 50, 1252–1258.
Article
Google Scholar
Lo, Y., Mendell, N. R., & Rubin, D. B. (2001). Testing the number of components in a normal mixture. Biometrika, 88(3), 767–778.
Article
Google Scholar
Maras, D., Flament, M. F., Murray, M., Buchholz, A., Henderson, K. A., Obeid, N., & Goldfield, G. S. (2015). Screen time is associated with depression and anxiety in Canadian youth. Preventive Medicine, 73, 133–138.
Article
Google Scholar
McLachlan, G. J., Ng, S. K., & Peel, D. (2003). On clustering by mixture models. In M. Schwaiger & O. Opitz (eds) Exploratory Data Analysis in EmpiricalResearch (pp. 141–148). Springer, Berlin, Heidelberg.
Google Scholar
Merikangas, K. R., & Avenevoli, S. (2002). Epidemiology of mood and anxiety disorders in children and adolescents. In: M. T. Tsuang, & M. Tohen, (Eds.), Textbook in psychiatric epidemiology. 2nd edition. Hoboken, NJ, USA: John Wiley & Sons, Inc. https://doi.org/10.1002/0471234311.ch24.
Merikangas, K. R., Nakamura, E. F., & Kessler, R. C. (2009). Prevalence rates of anxiety disorders in recent community surveys. Dialogues Clinical Neuroscience, 11(1), 7–20.
Google Scholar
Mezulis, A., Salk, R. H., Hyde, J. S., Priess-Groben, H. A., & Simonson, J. L. (2014). Affective, biological, and cognitive predictors of depressive symptom trajectories in adolescence. Journal of Abnormal Child Psychology, 42(4), 539–550.
Article
Google Scholar
Muthén, B., & Muthén, L. K. (2000). Integrating person-centred and variable-centered analyses: growth mixture modelling with latent trajectory classes. Alcoholism, 24, 882–891.
Article
Google Scholar
Muthén, L. K., & Muthén, B. O. (1998). Mplus User’s Guide. Seventh Edition Los Angeles, CA: Muthén & Muthén. 2012.
Google Scholar
Nowland, R., Necka, E. A., & Cacioppo, J. T. (2018). Loneliness and social internet use: Pathways to reconnection in a digital world? Perspectives on Psychological Science, 13(1), 70–87.
Article
Google Scholar
O’Hara, K. (2008). Understanding geocaching practices and motivations. In Proceedings of the SIGCHI conference on human factors in computing systems (pp. 1177–1186). ACM.
Patel, V. (2017). Talking sensibly about depression. PLoS Medicine, 14(4), e1002257.
Article
Google Scholar
Przybylski, A. K., & Weinstein, N. (2017). A large-scale test of the Goldilocks hypothesis: quantifying the relations between digital-screen use and the mental well-being of adolescents. Psychological Science, 28(2), 204–215.
Article
Google Scholar
Reinke, W. M., Eddy, J. M., Dishion, T. J., & Reid, J. B. (2012). Joint trajectories of symptoms of disruptive behavior problems and depressive symptoms during early adolescence and adjustment problems during emerging adulthood. Journal of Abnormal Child Psychology, 40(7), 1123–1136.
Article
Google Scholar
Rice, F., Harold, G. T., & Thapar, A. (2003). Negative life events as an account of age-related differences in the genetic aetiology of depression in childhood and adolescence. Journal of Child Psychology and Psychiatry, 44(7), 977–987.
Article
Google Scholar
Rideout, V. J., Foehr, U. G., & Roberts, D. F. (2010). Generation M: media in the lives of 8- to 18-year olds. CA, USA: The Henry J. Kaiser Family Foundation.
Sampasa-Kanyinga, H., & Chaput, J.-P. (2016). Use of social networking sites and adherence to physical activity and screen time recommendations in adolescents. Journal of Physical Activity & Health, 13(5), 474–480.
Article
Google Scholar
Selfhout, M. H., Branje, S. J., Delsing, M., ter Bogt, T. F., & Meeus, W. H. (2009). Different types of Internet use, depression, and social anxiety: The role of perceived friendship quality. Journal of Adolescence, 32(4), 819–833.
Article
Google Scholar
Sonuga-Barke, E. J. S. (2010). Editorial: ‘It’s the environment stupid!’ On epigenetics, programming and plasticity in child mental health. Journal of Child Psychology & Psychiatry, 51(2), 113–115.
Article
Google Scholar
Stoolmiller, M., Kim, H. K., & Capaldi, D. M. (2005). The course of depressive symptoms in men from early adolescence to young adulthood: identifying latent trajectories and early predictors. Journal of Abnormal Psychology, 114(3), 331.
Article
Google Scholar
Suchert, V., Hanewinkel, R., & Isensee, B. (2015). Sedentary behavior and indicators of mental health in school-aged children and adolescents: a systematic review. Preventive Medicine, 76, 48–57.
Article
Google Scholar
Touitou, Y., Touitou, D., & Reinberg, A. (2016). Disruption of adolescents’ circadian clock: The vicious circle of media use, exposure to light at night, sleep loss and risk behaviors. Journal of Physiology-Paris, 110(4), 467–479.
Article
Google Scholar
Twenge, J. M., Joiner, T. E., Rogers, M. L., & Martin, G. N. (2018). Increases in depressive symptoms, suicide-related outcomes, and suicide rates among US adolescents after 2010 and links to increased new media screen time. Clinical Psychological Science, 6(1), 3–17.
Article
Google Scholar
Vannucci, A., & Ohannessian, C. M. (2017). Self-competence and depressive symptom trajectories during adolescence. Journal of Abnormal Child Psychology, 46, 1089–1109.
Article
Google Scholar
Werner-Seidler, A., Perry, Y., Calear, A. L., Newby, J. M., & Christensen, H. (2017). School-based depression and anxiety prevention programs for young people: A systematic review and meta-analysis. Clinical Psychology Review, 51, 30–47.
Article
Google Scholar
Wickrama, K. A. S., Conger, R. D., Lorenz, F. O., & Jung, T. (2008). Family antecedents and consequences of trajectories of depressive symptoms from adolescence to young adulthood: A life course investigation. Journal of Health and Social Behavior, 49(4), 468–483.
Article
Google Scholar
Woods, H. C., & Scott, H. (2016). # Sleepyteens: social media use in adolescence is associated with poor sleep quality, anxiety, depression and low self-esteem. Journal of adolescence, 51, 41–49.
Article
Google Scholar
World Health Organisation (WHO). (2014). Mental health: a state of well-being. Geneva: WHO. (WHO factfile, August, p. 1).
Yaroslavsky, I., Pettit, J. W., Lewinsohn, P. M., Seeley, J. R., & Roberts, R. E. (2013). Heterogeneous trajectories of depressive symptoms: Adolescent predictors and adult outcomes. Journal of Affective Disorders, 148(2), 391–399.
Article
Google Scholar