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Adolescent sleep needs range from 8.5–10 hours per night, with older adolescents requiring less sleep than younger adolescents. On average, however, American adolescents receive between 7.5–8.5 hours of sleep per night, with many sleeping fewer than 6.5 hours on school nights. Cellular phone use is emerging as an important factor that interferes with both sleep quality and quantity, particularly as smartphones become more widely available to teens. This review paper has three objectives. First, we will describe adolescent sleep patterns and the effects of sleep deprivation on adolescent physical and mental health. Second, we will describe current trends in technology use among adolescents, making associations to how technology impacts sleep. Lastly, we will discuss some of the methodological barriers of conducting sleep and technology research with adolescents and young adults and offer suggestions for overcoming those barriers. We will also discuss implications for healthcare providers.

Objective Prior research identified peer use as a salient risk factor of adolescent electronic cigarette (e-cigarette) use, but has not expanded on the mechanisms of this association. Methods Participants were 562 adolescents recruited from rural and suburban public high schools and an adolescent medicine clinic in the mid-Atlantic United States. Participants completed a packet of questionnaires that assessed demographics, substance use, expectations about the consequences of e-cigarette use, and perceptions of their own self-efficacy to resist using e-cigarettes. We estimated a series of mediation models using the MODEL INDIRECT command in MPLUS statistical software. In all models, significance of indirect effects from peer e-cigarette use to self-reported e-cigarette use were tested via two variables: (a) expected costs, (b) benefits of e-cigarette use, and (c) the perceived self-efficacy of the individual to refrain from e-cigarette use. Results Adolescents with more peers using e-cigarettes were more likely to have ever used an e-cigarette and perceived greater benefits and fewer costs, which was associated with a reduced self-efficacy to refrain from e-cigarette smoking (Model 1). Those with more peers using e-cigarettes were more likely to be currently using e-cigarettes themselves because they perceived greater benefits and fewer costs, which was associated with a reduced self-efficacy to refrain from e-cigarette smoking (Model 2). Conclusion Peer use, self-efficacy to resist use, and expectations of cost and benefits of e-cigarette use should be considered as possible targets when devising tailored interventions and policies to prevent or reduce negative health consequences of long-term e-cigarette use.

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