Technology Use and Sleep Quality in Preadolescence and Adolescence

Bruni, Oliviero; Sette, Stefania; Fontanesi, Lilybeth; Baiocco, Roberto; Laghi, Fiorenzo; Baumgartner, Emma

doi:10.5664/jcsm.5282

Cited by 173 publications

(129 citation statements)

References 49 publications

Supporting

Mentioning

107

Contrasting

Unclassified

Order By: Relevance

“…The authors concluded that evening circadian preference, mobile phone and Internet use, the number of other activities engaged in after 9:00 PM, later media turning-off time, and the number of devices in the bedroom have different, but significant, negative influences on sleep quality in preadolescents and adolescents. 90 Similarly, Lemola et al 99 reported associations between electronic media use in bed before sleep, sleep difficulties, and symptoms of depression in teenagers.…”

Section: How Does Media Use Affect Sleep?mentioning

confidence: 99%

“…90 Increased duration of media exposure and the presence of a TV, computer, or mobile device in the bedroom in early childhood have been associated with fewer minutes of sleep per night, especially among children of racial/ethnic minority groups. 91 Later bedtimes after evening media use and violent content in the media also may be contributing factors, 92 and suppression of endogenous melatonin by blue light emitted from screens is another possible cause.…”

Section: How Does Media Use Affect Sleep?mentioning

confidence: 99%

See 1 more Smart Citation

Children and Adolescents and Digital Media

Chassiakos¹,

Radesky²,

Christakis³

et al. 2016

Pediatrics

881

530

View full text Add to dashboard Cite

Today's children and adolescents are immersed in both traditional and new forms of digital media. Research on traditional media, such as television, has identifi ed health concerns and negative outcomes that correlate with the duration and content of viewing. Over the past decade, the use of digital media, including interactive and social media, has grown, and research evidence suggests that these newer media offer both benefi ts and risks to the health of children and teenagers. Evidence-based benefi ts identifi ed from the use of digital and social media include early learning, exposure to new ideas and knowledge, increased opportunities for social contact and support, and new opportunities to access health promotion messages and information. Risks of such media include negative health effects on sleep, attention, and learning; a higher incidence of obesity and depression; exposure to inaccurate, inappropriate, or unsafe content and contacts; and compromised privacy and confi dentiality. This technical report reviews the literature regarding these opportunities and risks, framed around clinical questions, for children from birth to adulthood. To promote health and wellness in children and adolescents, it is important to maintain adequate physical activity, healthy nutrition, good sleep hygiene, and a nurturing social environment. A healthy Family Media Use Plan (www. healthychildren. org/ MediaUsePlan) that is individualized for a specifi c child, teenager, or family can identify an appropriate balance between screen time/online time and other activities, set boundaries for accessing content, guide displays of personal information, encourage age-appropriate critical thinking and digital literacy, and support open family communication and implementation of consistent rules about media use.

show abstract

Section: How Does Media Use Affect Sleep?mentioning

confidence: 99%

Section: How Does Media Use Affect Sleep?mentioning

confidence: 99%

Children and Adolescents and Digital Media

Chassiakos¹,

Radesky²,

Christakis³

et al. 2016

Pediatrics

881

530

View full text Add to dashboard Cite

show abstract

“…4), including poor sleep quality Arora et al, 2012;Bruni et al, 2015;Hysing et al, 2015;Lemola et al, 2014;Liu et al, 2017;Mak et al, 2014;Sami et al, 2018;Hawi et al, 2018), early awakenings (Arora et al, 2014;Fatih et al, 2013;Choi et al, 2009;Shochat et al, 2010), difficulty falling asleep (Arora et al, 2014;Fatih et al, 2013;Choi et al, 2009;Shochat et al, 2010), night awakenings (Arora et al, 2014;Fatih et al, 2013;Choi et al, 2009), less sleep quantity ( Van den Bulck, 2004;Nuutinen et al, 2014;Park, 2014;Park & Lee, 2017;Punama-ki et al, 2006;Shochat et al, 2010;Kim et al, 2018) and insomnia (Cheung & Wong, 2011;Tan et al, 2016;Tamura et al, 2017). Three subgroups were classified by country.…”

Section: Sleep Problemsmentioning

confidence: 99%

“…There were data from 22 studies Arora et al, 2012;Arora et al, 2014;Bruni et al, 2015;Fatih et al, 2013;Cheung & Wong, 2011;Choi et al, 2009;Hysing et al, 2015;Van den Bulck, 2004;Lemola et al, 2014;Liu et al, 2017;Mak et al, 2014;Nuutinen et al, 2014;Park, 2014;Park & Lee, 2017;Punama-ki et al, 2006;Shochat et al, 2010;Tan et al, 2016;Sami et al, 2018;Tamura et al, 2017;Hawi et al, 2018;Kim et al, 2018) that investigated association between the technology use and sleep problems (Fig. 4), including poor sleep quality Arora et al, 2012;Bruni et al, 2015;Hysing et al, 2015;Lemola et al, 2014;Liu et al, 2017;Mak et al, 2014;Sami et al, 2018;Hawi et al, 2018), early awakenings (Arora et al, 2014;Fatih et al, 2013;Choi et al, 2009;Shochat et al, 2010), difficulty falling asleep (Arora et al, 2014;Fatih et al, 2013;Choi et al, 2009;Shochat et al, 2010), night awakenings (Arora et al, 2014;Fatih et al, 2013;…”

Section: Sleep Problemsmentioning

confidence: 99%

“…Included studies were conducted in Europe (n = 9) (Arora et al, 2012;Arora et al, 2013;Arora et al, 2014;Bruni et al, 2015;Hysing et al, 2015;Van den Bulck, 2004;Lemola et al, 2014;Nuutinen et al, 2014;Punama-ki et al, 2006), East Asia (n = 10) Cheung & Wong, 2011;Choi et al, 2009;Liu et al, 2017;Mak et al, 2014;Park, 2014;Park & Lee, 2017;Tan et al, 2016;Tamura et al, 2017;Kim et al, 2018), and West Asia (n = 4) (Fatih et al, 2013;Shochat et al, 2010;Sami et al, 2018;Hawi et al, 2018). Eight studies assessed the sleep duration of ETU and no excessive technology use (Arora et al, 2013;Arora et al, 2014;Fatih et al, 2013;Cheung & Wong, 2011;Choi et al, 2009;Lemola et al, 2014;Shochat et al, 2010;Hawi et al, 2018).…”

Section: Study Characteristicsmentioning

confidence: 99%

See 1 more Smart Citation

Sleep problems in excessive technology use among adolescent: a systemic review and meta-analysis

Mei

Zhou

et al. 2018

Sleep Science Practice

View full text Add to dashboard Cite

Background: Inadequate sleep quantity and quality is a public health concern with an array of detrimental health outcomes. Portable technological devices have become a ubiquitous part of adolescents' lives and may affect their sleep duration and quality. The purpose of this study was to summarize published analyses of various technology uses and sleep outcomes and to examine whether there is an association between excessive technology use (ETU) and poor sleep outcomes in adolescents. Method: We conduct a systematic review and meta-analysis. Pubmed, Embase, Science Direct, Google Scholar, Cochrane Library were used. Inclusion and exclusion criteria were performed. Only original research papers published from 1999 to 2018 and offcially reviewed by peers were included for analysis. We used the Review Manager 5.3 software for statistical analysis.

show abstract

Chronotype, Social Jet Lag, and Cardiometabolic Risk Factors in Early Adolescence

et al. 2019

View full text Add to dashboard Cite

and quality increase the risk of obesity. Sleep timing, while less studied, is important in adolescents because increasing evening preferences (chronotypes), early school start times, and irregular sleep schedules may cause circadian misalignment. OBJECTIVE To investigate associations of chronotype and social jet lag with adiposity and cardiometabolic risk in young adolescents. DESIGN, SETTING, AND PARTICIPANTS Starting in 1999, Project Viva recruited pregnant women from eastern Massachusetts. Mother-child in-person visits occurred throughout childhood. From January 23, 2012, to October 16, 2016, 804 adolescents aged 12 to 17 years completed 5 days or more of wrist actigraphy, questionnaires, and anthropometric measurements. A cross-sectional analysis using these data was conducted from April 31, 2018, to May 1, 2019. EXPOSURES Chronotype, measured via a continuous scale with higher scores indicating greater evening preferences, and social jet lag, measured as the continuous difference in actigraphy sleep midpoint in hours from midnight on weekends vs weekdays, with higher values representing more delayed sleep timing on weekends. MAIN OUTCOMES AND MEASURES Adiposity, measured via anthropometry and dual-energy x-ray absorptiometry. For a subset of 479 adolescents with blood samples, cardiometabolic risk scores were computed as the mean of 5 sex-and cohort-specific z scores for waist circumference, systolic blood pressure, inversely scaled high-density lipoprotein cholesterol, and log-transformed triglycerides and homeostatic model of insulin resistance. RESULTS Among the 804 adolescents in the study, 418 were girls and 386 were boys, with a mean (SD) age of 13.2 (0.9) years. In multivariable models adjusted for age, puberty, season, and sociodemographics, associations of chronotype and social jet lag with adiposity varied by sex. For girls, greater evening preference was associated with a 0.58-cm (95% CI, 0.12-1.03 cm; P = .04 for interaction) higher waist circumference and 0.16 kg/m 2 (95% CI, 0.01-0.31 kg/m 2 ; P = .03 for interaction) higher fat mass index as measured by dual-energy x-ray absorptiometry; each hour of social jet lag was associated with a 1.19-cm (95% CI, 0.04-2.35 cm; P = .21 for interaction) higher waist circumference and 0.45 kg/m 2 (95% CI, 0.09-0.82 kg/m 2 ; P = .01 for interaction) higher fat mass index as measured by dual-energy x-ray absorptiometry. Associations of social jet lag and evening chronotypes persisted for many measures of adiposity after adjustment for sleep duration and other lifestyle behaviors. By contrast, no associations were observed in boys. There were no associations with the cardiometabolic risk score for either sex, although statistical power was low for this outcome. CONCLUSIONS AND RELEVANCE Evening chronotypes and social jet lag were associated with greater adiposity in adolescent girls but not adolescent boys. Interventions aimed at improving sleep schedules may be useful for obesity prevention, especially in girls.

show abstract

Technology Use and Sleep Quality in Preadolescence and Adolescence

Cited by 173 publications

References 49 publications

Children and Adolescents and Digital Media

Children and Adolescents and Digital Media

Sleep problems in excessive technology use among adolescent: a systemic review and meta-analysis

Chronotype, Social Jet Lag, and Cardiometabolic Risk Factors in Early Adolescence

Contact Info

Product

Resources

About