Adolescents Living the 24/7 Lifestyle: Effects of
Caffeine and Technology on Sleep Duration and
Christina J. Calamaro, PhD, CRNP
, Thornton B. A. Mason, MD, PhD, MSCE
, Sarah J. Ratcliffe, PhD
College of Nursing and Allied Professions, Drexel University, Philadelphia, Pennsylvania;
School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania;
Division of Neurology and Center for Sleep, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
The authors have indicated they have no ﬁnancial relationships relevant to this article to disclose.
What’s Known on This Subject
Aspects of adolescent lifestyle, such as academic stress or social pursuits, can interact
and lead to irregular sleep patterns. Poor sleep quality and shortened sleep duration
have been associated with mental and physical comorbidities and decreased quality of
life in adolescents.
What This Study Adds
No studies to date have quantiﬁed nighttime technology use and caffeine consumption
to assess their potential effects on sleep duration and daytime behaviors in a group of
middle school and high school adolescents aged 12 to 18 years.
Adolescents may not receive the sleep they need. New media technology
and new, popular energy drinks may be implicated in sleep deﬁcits. In this pilot study
we quantiﬁed nighttime technology use and caffeine consumption to determine
effects on sleep duration and daytime behaviors in adolescents. We hypothesized that
with increased technology use, adolescents increase caffeine consumption, resulting
in insufﬁcient sleep duration.
PATIENTS AND METHODS.
Subjects were recruited from a pediatric ofﬁce in a proximal
suburb of Philadelphia, Pennsylvania. Inclusion criteria for this study were middle
and high school subjects aged 12 to 18 years old. The questionnaire, Adolescent
Sleep, Caffeine Intake, and Technology Use, was developed by the investigators to
measure adolescents’ intake of caffeinated drinks, use of nighttime media-related
technology, and sleep behaviors. Descriptive statistics characterized the subjects,
their caffeine and technology use, and sleep variables. Regression models assessed