Social Media and Depressive Symptoms in Childhood and Adolescence: A Systematic Review

Concerns are increasingly raised in academic and lay literature about the impact of the internet on young people’s well-being. This systematic review examined empirical research on the relationship between social media use and depressive symptoms in the child and adolescent population. A systematic search of Medline, PsycInfo and Embase databases yielded eleven eligible studies. Relevant results were extracted from each study, with a total sample of 12,646. Analysis revealed a small but statistically significant correlation between social media use and depressive symptoms in young people. However, studies varied widely in methods, sample size and results, making the clinical significance of these findings nuanced. Over half of the studies were cross-sectional, while those of longitudinal design were of limited duration. This review justifies further investigation of this phenomenon, with a need for consensus on variables and measurement

Reciprocal relationships between trajectories of depressive symptoms and screen media use during adolescence

Adolescents are constantly connected with each other and the digital landscape through a myriad of screen media devices. Unprecedented access to the wider world and hence a variety of activities, particularly since the introduction of mobile technology, has given rise to questions regarding the impact of this changing media environment on the mental health of young people. Depressive symptoms are one of the most common disabling health issues in adolescence and although research has examined associations between screen use and symptoms of depression, longitudinal investigations are rare and fewer still consider trajectories of change in symptoms. Given the plethora of devices and normalisation of their use, understanding potential longitudinal associations with mental health is crucial. A sample of 1,749 (47% female) adolescents (10-17 years) participated in six waves of data collection over two years. Symptoms of depression, time spent on screens, and on separate screen activities (social networking, gaming, web browsing, TV/passive) were self-reported. Latent growth curve modelling revealed three trajectories of depressive symptoms (Low-Stable, High-Decreasing, and Low-Increasing) and there were important differences across these groups on screen use. Some small, positive associations were evident between depressive symptoms and later screen use, and between screen use and later depressive symptoms. However, a Random Intercept Cross Lagged Panel Model revealed no consistent support for a longitudinal association. The study highlights the importance of considering differential trajectories of depressive symptoms and specific forms of screen activity to understand these relationships

Sleeping hours: what is the ideal number and how does age impact this?

Jean-Philippe Chaput,1–4 Caroline Dutil,1,3 Hugues Sampasa-Kanyinga1,4 1Healthy Active Living and Obesity Research Group, Children’s Hospital of Eastern Ontario Research Institute, Ottawa, ON, Canada; 2Department of Pediatrics, University of Ottawa, Ottawa, ON, Canada; 3School of Human Kinetics, University of Ottawa, Ottawa, ON, Canada; 4School of Epidemiology and Public Health, University of Ottawa, Ottawa, ON, Canada Abstract: The objective of this narrative review paper is to discuss about sleep duration needed across the lifespan. Sleep duration varies widely across the lifespan and shows an inverse relationship with age. Sleep duration recommendations issued by public health authorities are important for surveillance and help to inform the population of interventions, policies, and healthy sleep behaviors. However, the ideal amount of sleep required each night can vary between different individuals due to genetic factors and other reasons, and it is important to adapt our recommendations on a case-by-case basis. Sleep duration recommendations (public health approach) are well suited to provide guidance at the population-level standpoint, while advice at the individual level (eg, in clinic) should be individualized to the reality of each person. A generally valid assumption is that individuals obtain the right amount of sleep if they wake up feeling well rested and perform well during the day. Beyond sleep quantity, other important sleep characteristics should be considered such as sleep quality and sleep timing (bedtime and wake-up time). In conclusion, the important inter-individual variability in sleep needs across the life cycle implies that there is no “magic number” for the ideal duration of sleep. However, it is important to continue to promote sleep health for all. Sleep is not a waste of time and should receive the same level of attention as nutrition and exercise in the package for good health. Keywords: sleep, recommendations, guidelines, population heath, public health, life cycl

Bidirectional associations of sleep and discretionary screen time in adults: Longitudinal analysis of the UK biobank.

The direction of the association between discretionary screen time (DST) and sleep in the adult population is largely unknown. We examined the bidirectional associations of DST and sleep patterns in a longitudinal sample of adults in the general population. A total of 31,361 UK Biobank study participants (52% female, 56.1 ± 7.5 years) had two repeated measurements of discretionary screen time (TV viewing and leisure-time computer use) and self-reported sleep patterns (five sleep health characteristics) between 2012 and 2018 (follow-up period of 6.9 ± 2.2 years). We categorised daily DST into three groups (low, 4 h/day), and calculated a sleep pattern composite score comprising morning chronotype, adequate sleep duration (7-8 h/day), never or rare insomnia, never or rare snoring, and infrequent daytime sleepiness. The overall sleep pattern was categorised into three groups (healthy: ≥ 4; intermediate: 2-3; and poor: ≤ 1 healthy sleep characteristic). Multiple logistic regression analyses were applied to assess associations between DST and sleep with adjustments for potential confounders. Participants with either an intermediate (OR: 1.40; 95% CI: 1.15, 1.71) or a poor (OR: 1.16; 95% CI: 1.10, 1.24) sleep pattern at baseline showed higher odds for high DST at follow-up, compared with those with a healthy baseline sleep pattern. Participants with medium (OR: 1.40; 95% CI: 1.14, 1.71) or high DST (OR: 1.62; 95% CI: 1.30, 2.00) at baseline showed higher odds for poor sleep at follow-up, compared with participants with a low DST. In conclusion, our findings provide consistent evidence that a high DST at baseline is associated with poor sleep over a nearly 7 year follow-up period, and vice versa

Energy drink consumption and substance use among middle and high school students

This study examined the association between energy drink consumption and substance use among adolescents and tested whether sex and/or grade level (i.e., middle vs. high school) moderate the association. Data were derived from the 2017 Ontario Student Drug Use and Health Survey, a representative survey of students in 7th to 12th grade. Analyses included 10,662 students who self-reported information on energy drink consumption and substance use. Poisson regression models were used with adjustments for important covariates. Energy drink consumption was associated with tobacco cigarette smoking (incidence rate ratio (IRR): 3.74; 95% confidence interval (CI): 3.22–4.35), cannabis use (IRR: 2.90; 95% CI: 2.53–3.32), binge drinking (IRR: 2.46; 95% CI: 2.05–2.96), opioid use (IRR: 2.23; 95% CI: 1.85–2.68), and alcohol use (IRR: 1.31; 95% CI: 1.26–1.36). The associations of energy drink consumption with tobacco cigarette smoking, cannabis use, and alcohol consumption were modified by grade level (two-way interaction terms p < 0.05). The association between energy drink consumption and substance use was generally much stronger among middle school students compared with high school students. The findings suggest that middle school students may be more vulnerable to the negative effects of energy drinks in relation with substance use