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Effects of the SMART Classroom Curriculum to Reduce Child and Family Screen Time

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Evidence for adverse effects of screen media exposure has led to recommendations to limit children's screen time. This paper describes a randomized controlled trial of SMART (Student Media Awareness to Reduce Television), an 18-lesson, theory-based classroom curriculum to reduce screen time among third and fourth grade children in two matched public elementary schools (n = 181). Intervention school children significantly reduced their weekday television viewing and weekday and Saturday video game playing compared to controls. Greater effects were found among boys and more adult-supervised children. Mothers, fathers, and siblings and other children in intervention school households also reduced their television viewing. The findings demonstrate the efficacy of a classroom intervention to reduce screen time among elementary school children and their family/household members.
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RESEARCH ARTICLE
Effects of the SMART Classroom Curriculum
to Reduce Child and Family Screen Time
Thomas N. Robinson
1
& Dina L. G. Borzekowski
2
1 Division of General Pediatrics, Department of Pediatrics, and Stanford Prevention Research Center,
Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305-5705
2 Department of Population and Family Health Sciences, Johns Hopkins Bloomberg School of Public Health,
Baltimore, MD 21205
Evidence for adverse effects of screen media exposure has led to recommendations to
limit children’s screen time. This paper describes a randomized controlled trial of
SMART (Student Media Awareness to Reduce Television), an 18-lesson, theory-based
classroom curriculum to reduce screen time among third and fourth grade children in
two matched public elementary schools (n = 181). Intervention school children signifi-
cantly reduced their weekday television viewing and weekday and Saturday video game
playing compared to controls. Greater effects were found among boys and more adult-
supervised children. Mothers, fathers, and siblings and other children in intervention
school households also reduced their television viewing. The findings demonstrate the
efficacy of a classroom intervention to reduce screen time among elementary school chil-
dren and their family/household members.
doi:10.1111/j.1460-2466.2006.00001.x
The homes of U.S. children have an average of 2.9 TV sets, 1.8 video cassette recorders
(VCR), and 1.4 video game players. One can find TV sets in half (53%) of children’s
bedrooms; one third (32%) of 2–7 year olds and two thirds (65%) of 8–18 year olds
(Roberts, Foehr, Rideout, & Brodie, 2003). Children watch television and videotapes
around 3 hours and play video games about a half-hour per day (Roberts et al., 2003;
Woodard, 2000). On average, U.S. children spend more than a quarter of their waking
lives in front of a television or other electronic media screen (Robinson, 2001).
Children’s media use has been associated with a number of adverse effects. True
experiments, cross-sectional studies, and longitudinal fieldwork consistently show
that exposure to media violence is associated with more aggressive behaviors, de-
sensitization to violence, and the belief that aggressive behavior is an appropriate
reaction to conflict (Bandura, Ross, & Ross, 1963; Bushman & Huesmann, 2001;
Johnson, Cohen, Smailes, Kasen, & Brook, 2002; Paik & Comstock, 1994). Excessive
Corresponding author: Thomas N. Robinson; e-mail: tom.robinson@stanford.edu
Journal of Communication ISSN 0021-9916
Journal of Communication 56 (2006) 1–26 ª2006 International Communication Association 1
screen time leads to increased obesity (Dietz & Gortmaker, 1985; Robinson, 2001),
consuming more fast foods (French, Story, Neumark-Sztainer, Fulkerson, &
Hannan, 2001), eating fewer fruits and vegetables (Boynton-Jarrett et al., 2003),
and being less physically active and fit (Robinson, 2001). Furthermore, reducing
children’s screen time results in less weight gain and obesity (Gortmaker et al.,
1999; Robinson, 1999). A large body of evidence also suggests that television adver-
tising can be harmful to children’s health and development (Kunkel et al., 2004).
Evidence for the effects of media use on academic performance and social devel-
opment has been less conclusive, though some studies have found associations
between more television viewing and/or video game use and worse academic
achievement, less time spent reading and doing homework, and greater risk for later
attentional problems (Anderson & Collins, 1988; Christakis, Zimmerman, DiGiu-
seppe, & McCarty, 2004; Comstock & Paik, 1991; Hornik, 1981; Madden, Bruekman,
& Littlejohn, 1997; Potter, 1987; Wiecha, Sobol, Peterson, & Gortmaker, 2001;
Williams, Haertel, Haertel, & Wahlberg, 1982).
Parents report trying to mediate their children’s media use. Some employ
‘‘restrictive mediation’’; that is, parents forbid their children from watching certain
programs, control viewing to certain times and limit the length of their children’s TV
viewing (Nathanson, 2002). In two recent national surveys, half to more than two
thirds of parents report having household rules governing their children’s media use
(Annenberg Public Policy Center, 1997; Roberts, Foehr, Rideout, & Brodie, 1999).
Parents’ negative attitudes about television predicts the use of restrictive mediation,
along with child’s age and parents’ level of involvement with the child (Nathanson;
Warren, Gerke, & Kelly, 2002).
To decrease the negative effects associated with children’s media use, some social,
health, and political advocacy groups try to change the structure and content of media
(Strasburger & Wilson, 2002). Others argue for reducing or eliminating children’s
screen time altogether (Trotta, 2001). The American Academy of Pediatrics advises
that children aged 2 years and younger watch no television and that children older
than 2 years limit television watching to a total of no more than 1–2 hours per day, and
only educational, nonviolent programming (American Academy of Pediatrics Com-
mittee on Public Education, 2001). Other recommendations to limit children’s screen
time come from the American Psychological Association (1995), the American Acad-
emy of Child and Adolescent Psychiatry (2001), the American Medical Association
(1996), the National Parent Teachers Association (2001), the National Education
Association (1999), and the U.S. Surgeon General (2000), among many others. Since
1995, there also has been a national grassroots movement to encourage families to turn
off their televisions for a week (The TV Turnoff, www.tvturnoff.org). Despite these
widespread calls for parents to limit their children’s screen time, little work has been
conducted to discover the means to successfully do so. The question remains, how do
we decrease use when these media activities are so central in the lives of U.S. children?
Surprisingly, few scientific studies directly focus on reducing children’s televi-
sion viewing. Rather, most research interventions try to teach children media
Curriculum to Reduce Child and Family Screen Time T. N. Robinson & D. L. G. Borzekowski
2Journal of Communication 56 (2006) 1–26 ª2006 International Communication Association
education and critical viewing skills (Corder-Bolz, 1982; Dorr, Graves, & Phelps,
1980; Huesmann, Eron, Klein, Brice, & Fischer, 1983; Roberts, Christenson, Gibson,
Mooser, & Goldberg, 1980; Singer, Zuckerman, & Singer, 1980). Several recent
studies, however, have attempted to reduce children’s media use in order to reduce
obesity. In one study, a 2-year, middle school curriculum was designed to reduce
students’ television and video viewing to less than 2 hours per day, increase physical
activity and fruit and vegetable consumption, and decrease high fat food con-
sumption (Gortmaker et al., 1999). Following treatment, students in the intervention
schools reported reducing their television viewing more than controls. Another
obesity prevention trial conducted with 77 preschool children included a TV viewing
reduction component that emphasized a weeklong TV Turnoff coupled with in-
creased book reading. At the end of the treatment period, children in the interven-
tion group reported watching significantly less television than their peers in the
control group (Dennison, Russo, Burdick, & Jenkins, 2004).
Prior to these intervention studies and our own television reduction study, the
only studies to examine media reduction interventions were small and did not
employ randomized controlled designs. Conducted around 20 years ago, these
studies did demonstrate the potential efficacy of using behavioral strategies of self-
monitoring, reinforcing reduced viewing, and budgeting television viewing time, at
least among children who were excessive television viewers (Jason, 1983, 1985, 1987;
Jason & Rooney-Rebeck, 1984; Wolfe, Mendes, & Factor, 1984). Contrasting the
more recent work, media reduction was the primary objective of the earlier studies.
This paper reports the results of an experimental school-based intervention to
reduce screen time among third- and fourth- grade elementary school children. The
intervention addressed only reducing television, videotape, and video game use and did
not specify any replacement activities to occupy time that was spent in front of the
electronic video screen. This intervention, if successful, could have widespread practical
and research applications. It could provide both a population-based approach to reduce
children’s television, videotape, and video game use, as well as an experimental model
to study the effects of reduced media exposure on cognitive, behavioral, and physiolog-
ical outcomes in real-world settings. In prior publications, we documented the impact
of this intervention on body weight and fatness, physical activity, diet (Robinson, 1999),
aggressive behavior (Robinson, Wilde, Navratil, Haydel, & Varady, 2001), and
consumeristic behavior (Robinson, Saphir, Kraemer, Varady, & Haydel, 2001).
Bandura’s (1986) social cognitive model provided the conceptual foundation for
our intervention because the model is well grounded in experimental research,
provides directives for the production of behavior-change interventions, and has
demonstrated efficacy in previous school-based behavior-change research (Bandura,
1986, 1997; Killen et al., 1988). In social cognitive theory, behavior develops and is
maintained through the reciprocal interplay of personal, behavioral, and environ-
mental factors (Bandura, 1986). Within this context, the social cognitive model
offers four processes that influence learning and adopting new behaviors, and are
particularly helpful for designing behavior-change interventions: attention, retention,
T. N. Robinson & D. L. G. Borzekowski Curriculum to Reduce Child and Family Screen Time
Journal of Communication 56 (2006) 1–26 ª2006 International Communication Association 3
production, and motivation (Bandura, 1986). To reliably apply the principles of
social cognitive theory in our intervention, we were careful to focus specifically on
these four processes in the design of all elements of the intervention.
The purpose of this paper is to (a) fully describe our intervention and its con-
ceptual origin and design, (b) examine the effects of the intervention on reduc-
ing children’s time with individual screen media and potential substitute activities,
(c) examine the effects of the intervention on television viewing among parents
and other household members, and (d) explore the role of baseline characteristics
as potential moderators and of postrandomization intervention-related factors as
potential mediators of the intervention’s effects (Kraemer, Stice, Kazdin, Offord, &
Kupfer, 2001; Kraemer, Wilson, Fairburn, & Agras, 2002).
Subjects and methods
All third- and fourth- grade students in two public elementary schools in one school
district in San Jose, CA, were eligible to participate. Schools were sociodemographically
and scholastically matched by school district personnel. All third and fourth grade
teachers and their school principals agreed to participate in the study prior to random-
ization. Parents or guardians provided written informed consent for their children to
participate in the school-based study, and for their own participation in telephone inter-
views. Children provided assent for their own participation. One school was randomly
assigned to implement the SMART (Student Media Awareness to Reduce Television)
curriculum to reduce television, videotape, and video game use. The other school was
assigned to be an assessments-only control. All assessments were performed by trained
staff, blinded to the experimental design and school assignment, at baseline (September
1996) and after the intervention (April 1997). Children, parents/guardians, and school
personnel, including classroom teachers, were informed of the nature of the intervention
and assessments prior to participation. The study was approved by the Stanford Uni-
versity Panel on Human Subjects in Research.
The intervention
The intervention’s design was drawn primarily from Bandura’s (1986) social cognitive
model. In social cognitive theory, behavior develops and is maintained through the
interplay of personal, behavioral, and environmental factors. Because our goal was to
reduce children’s screen time, we focused on personal factors that included the children’s,
parents’ and teachers’ value systems that determine the nature of the incentives that
sustain media-use behaviors, expectations derived from observation and experience
about the consequences of different behaviors (outcome expectancies), and expectations
about personal abilities to perform behaviors that will secure desired outcomes (efficacy
expectancies). Behavioral factors included the skills available in the behavioral repertoire
of the child, parent, or teacher, and the degree of competence attained in using these
skills. Environmental factors consisted of the ways in which peers, family members,
teachers, supervisors, and even media characters and actors model various attitudes
Curriculum to Reduce Child and Family Screen Time T. N. Robinson & D. L. G. Borzekowski
4Journal of Communication 56 (2006) 1–26 ª2006 International Communication Association
and behaviors regarding television viewing, videotape viewing, and video game playing.
Such individuals are positioned, through their own actions, judgments, or social posi-
tions, to influence the development of children’s value systems and standards of conduct
regarding those attitudes and behaviors. In addition, environmental factors include
household or community factors such as media ownership or the availability of safe
places to play in the neighborhood.
Prior to the intervention, we identified three primary approaches for reducing
children’s screen time. They were (a) nonselectively decreasing total television and
videotape viewing and video game use, regardless of content or context; (b) selec-
tively decreasing television and videotape viewing and video game use, by becoming
more selective about content or context; and (c) displacing television and videotape
viewing and video game use with other activities. Although the third mechanism,
displacement of screen time with other activities, may hold great potential for reduc-
ing screen time, we chose not to use it in this study because we wished to investigate
the hypothesized causal association between reduced television, videotape, and video
game use and associated outcomes (e.g., school performance, obesity, physical activ-
ity, diet, aggression, consumeristic attitudes and behaviors, body dissatisfaction) in
an authentic setting. To keep the experimental model ‘‘clean,’’ it was important that
the intervention targeted only reducing screen media use and did not include ‘‘con-
taminating’’ elements that could influence these related outcomes (e.g., alternative
physical or academic activities).
Our intervention targeted nonselective and selective reduction of television view-
ing, videotape viewing, and video game use, without providing specific alternative or
substitute activities. Nonselective approaches include (a) budgeting total weekly
screen time and (b) limiting physical access to screen media (e.g., removing TV sets
from the home, especially from kitchens and bedrooms; placing VCRs and video
game players in cabinets; and/or hiding remote controls). Selective approaches to
decreasing screen time include (a) limiting viewing of screen media to certain days of
the week or times of day (e.g., not until after dinner and/or homework is completed,
not on school nights), (b) restricting screen media use to only specified content (e.g.,
prohibiting media that has been rated as violent or sexually explicit, only watch
shows broadcast on public television), and (c) limiting screen media use only to
particular circumstances (e.g., playing video games only with a parent present, not
watching television during meals).
Why target television, videotapes, and video games instead of television alone?
From an etiological research perspective, an intervention targeting only reduced televi-
sion viewing might seem more pure than an intervention that tries to simultaneously
reduce several types of screen media use. Of course, media may differ in how they impact
children’s health. For example, television programming that is regularly interrupted with
commercials for sugary cereals and high-fat snack foods may have greater impact on
dietary behaviors than videotapes that have no advertising (Gorn & Goldberg, 1982;
Jeffrey, McLellarn, & Fox, 1982) and playing some video games can result in greater
T. N. Robinson & D. L. G. Borzekowski Curriculum to Reduce Child and Family Screen Time
Journal of Communication 56 (2006) 1–26 ª2006 International Communication Association 5
energy expenditure than watching television or videotapes (Segal & Dietz, 1991). However,
we decided to target television, videotapes, and video games for both conceptual and
practical reasons.
In concept, time spent watching television resembles time spent watching video-
tapes and playing video games. To begin, different screen media can look very
similar. Characters and storylines cross media frequently; children may be just as
likely to see Rugrats or Muppets on television programs as they are to see them on
videotapes or video games. In observing children using different media, one might
have a difficult time distinguishing what type of screen media they were using. For
most, use of these different media almost always involves being sedentary in an
indoor setting. Even the child who is playing video games is sitting, manipulating
a joystick that might be on his or her lap. And children come to the couch for similar
reasons, whether they are watching television or videotapes or playing video games.
Time spent using each of these media is also time that is not used for potentially
more constructive activities, such as reading, doing homework, or playing outside.
Displacement of other activities is frequently cited as a negative effect of media use.
In our formative research, children also reported that they use all types of media
either to be entertained or when they were bored. As well, parents and teachers may
not consistently discriminate between these three media. Parents’ and teachers’
beliefs about the roles of these three media on, for example, time for homework
and reading, socialization with other children, physical activity, or exposure to
violence, adult language, and sexually explicit content may be linked to all these
media. In focus groups with parents, we have heard individual preferences voiced for
(and against) certain media, but most seem to differentiate according to media
content. Therefore, targeting television alone, as a medium, may be inconsistent
with a parent’s own belief systems (e.g., ‘‘TV is not so bad but video games are much
too violent, why aren’t you focusing video games?’’). Targeting all screen time but
incorporating selective viewing intervention approaches allows parents to exert their
own beliefs and preferences about individual media and/or content. Targeting all
screen time, therefore, was expected to produce the greatest parent and teacher ‘‘buy-
in’’ for the intervention, and providing this element of parental choice and control
was designed to increase self-motivation for their participation in screen-time-
reducing behaviors (Bandura, 1986, 1997).
The decision to target all three of these screen media was also guided by practical
reasons. First, all three media are typically delivered via a TV set. We would be
simplifying the intervention and reducing all screen media use if we instructed
turning off or using electronic time managers connected to the households’ TV sets.
Second, we believed that addressing all three media would make for easier delivery of
the intervention, for this study and for future work and dissemination. Pediatricians
and educators can recommend reducing all screen time, rather than justifying why
children need to reduce use of one medium more than another. A more inclusive
intervention helps minimize situations where exceptions are made for particular
programs, games, or individual children. This is also consistent with cognitive
Curriculum to Reduce Child and Family Screen Time T. N. Robinson & D. L. G. Borzekowski
6Journal of Communication 56 (2006) 1–26 ª2006 International Communication Association
social learning principles of setting explicit, nonambiguous, and measurable goals
(Bandura, 1986).
Last, we wanted our intervention to operate in a real-world setting, so that our
results might have the greatest clinical, practical, and policy relevance. Although it
would be possible, despite the constraints already mentioned, to design a study to
evaluate the overall and relative effects of an intervention targeting a single medium,
such ‘‘component’’ studies seem premature given the current state of experimental
research on media effects in real-world settings. Furthermore, many epidemiological
studies examining the health and behavioral correlates of excessive viewing do not
differentiate among these media. Without prior evidence of large differential effects, it
was most appropriate to test the efficacy of a more comprehensive intervention before
moving to more complicated component studies (Agras, Kazdin, & Wilson, 1979).
What about computer use?
Recent national data indicate that 67% of households with children aged 6–17 years have
a personal computer, and average 6–11 year olds spend about 50 minutes per day using
a computer (U.S. Census, 2001; Woodard, 2000). However, reducing time spent using
computers may be more complex than reducing time spent watching television and
videotapes and playing video games. In particular, many parents and teachers believe
that using computers, unlike other screen time, is educational and prepares children to
be competitive in future job markets, especially near Silicon Valley where we conducted
this research. Therefore, we did not indiscriminately combine all computer use with
other screen media use. As part of the intervention, we explicitly recommended that
parents include computer ‘‘games’’ and ‘‘playing on the computer’’ in the total weekly
screen time budget. We suggested that parents try to discern between playing games
versus educational or school work done on the computer. Our formative research sug-
gested that excessive computer use would be a significant problem for few children, and
that this approach would be satisfactory to both parents and teachers. This was also
consistent with our emphasis on including opportunities for choice and control for both
parents and children, to enhance motivation for reducing screen time (Bandura, 1986).
The SMART classroom curriculum
We delivered a classroom curriculum in all four third and fourth grade classrooms in
the intervention school over a 6-month period (October 1996 to April 1997). The curric-
ulum consisted of eighteen, 30- to 50-minute classroom lessons plus weekly 5- to 10-
minute boosters over the course of the last 4 months. Social cognitive theory suggests that
‘‘induction,’’ ‘‘generalization,’’ and ‘‘maintenance’’ of effects are conceptually distinct pro-
cesses in behavior change, with each phase at least partly determined by different factors
(Bandura, 1986). Classroom lessons were designed and scheduled accordingly, with more
frequent and intensive activities focusing on maximizing attention and motivation for
participating in early mastery experiences in the months of October through December
to promote enhanced self-efficacy for initial adoption and generalization of behavior
changes. These lessons were followed by a combination of brief, regularly scheduled
T. N. Robinson & D. L. G. Borzekowski Curriculum to Reduce Child and Family Screen Time
Journal of Communication 56 (2006) 1–26 ª2006 International Communication Association 7
reinforcing activities and moderately intensive, intermittently scheduled activities over
the rest of the school year to promote self-efficacy for maintaining changes or reinstitut-
ing lapsed behaviors. Teacher preparation consisted of a 3-hour group curriculum ori-
entation session with all classroom teachers, led by the principal investigator and
a research assistant. The goal was to provide teachers with sufficient familiarity with the
curriculum and briefmastery experiences to boost perceived efficacy for implementing the
curriculum with success (Bandura). Orientation to the entire curriculum and mastery
experiences were also intended to have a positive impact on other variables important to
program implementation, such as teacher enthusiasm, reduced anxiety, and perceived
preparedness to deliver the curriculum (Parcel, Perry, & Taylor, 1990). Four regular
classroom teachers taught all classroom lessons, but the research assistant prepared mate-
rials and provided ongoing advice and feedback to facilitate implementation. Ready access
to the research assistant, as a resource person, was also designed to enhance classroom
teachers’ efficacy expectancies for curriculum delivery.
As noted above, social cognitive theory specifies four processes that influence
learning and adopting new behaviors, and are particularly helpful for designing
behavior-change interventions: attention, retention, production, and motivation
(Bandura, 1986). Attention regulates exploration and perception; it is highly influ-
enced by factors such as salience, conspicuousness, functional value, affective
valence, and attractiveness. Retention is influenced by the processes of symbolic
coding, information organization, cognitive or imagined rehearsal, and enactive
rehearsal. Production is the conversion of conceptual representations into actions,
is influenced by immediate intrinsic and extrinsic feedback, and is the process most
closely linked to efficacy expectancies. Motivation is linked to both outcome expec-
tancies and perceived self-efficacy and is strongly influenced by external, vicarious,
and internal incentives. These four processes guided the macro- and microdevelop-
ment and implementation of specific intervention components. Therefore, all ele-
ments of the curriculum were subjected to particular scrutiny to ensure that they
included (a) stimulus material and specific lesson activities that would engage and
direct the attention of the children, (b) intervention formats and content (i.e.,
language and skill demands, information level, activity complexity) that matched
the cognitive and behavioral skill levels of third and fourth grade children,
(c) sufficient cognitive and behavioral performance opportunities to provide mastery
experiences, and (d) incentives and incentive systems that were relevant and attractive
to the children, and thus more likely to serve as prompts for action. For example, we
attempted to maximize attentional processes with techniques such as using boldly
colored materials that differed in form and style from the rest of their curricula,
including music and art in lessons, making lessons highly interactive and participa-
tory, using content that emphasized meaningful short-term consequences of behav-
iors that were meaningful to third and fourth grade children instead of future
long-term outcomes, and specifying incentives prior to the learning activities. We
aimed to maximize retention by using methods like presenting explicit instruction
for new skills along with linked visual demonstrations and using simple stories and
Curriculum to Reduce Child and Family Screen Time T. N. Robinson & D. L. G. Borzekowski
8Journal of Communication 56 (2006) 1–26 ª2006 International Communication Association
simulation activities that allowed children to infer the intended messages. Produc-
tion processes were maximized by including many opportunities for practicing skills
and mastery through role-playing and simulations, with feedback to highlight suc-
cesses and correct deficiencies, and including activities such as self-monitoring
screen time, calendar planning, inventing strategies to overcome common barriers
to reducing screen time, and making persuasive appeals to reduce television viewing
to peers and younger students. Finally, motivational processes were maximized for
both reducing screen time and participating in the intervention activities themselves
by creating opportunities to achieve peer, parent, or teacher approval for successfully
performing the targeted behaviors; providing some material extrinsic rewards such
as ribbons, stickers, and classroom honors; using stories and simulations for children
to observe modeled behaviors linked to desirable outcomes; and emphasizing per-
ceived choice and control, as well as personalization, contextualization, challenge,
curiosity, and mastery, factors that have been demonstrated to enhance intrinsic
motivation, greater persistence, better performance, and higher satisfaction in chil-
dren (Cordova & Lepper, 1996; Lepper, 1985; Parker & Lepper, 1992).
The curriculum consisted of four sections, which were delivered in the following
order:
1. TV awareness. Five lessons focusing on TV awareness were intended to
(a) increase children’s awareness of the roles television, videotapes, and video games
play in their lives; (b) inform children about the potential short- and long-term
consequences of watching a lot of television and videotapes and playing a lot of video
games; and (c) promote positive attitudes and motivation to reduce television,
videotape, and video game use. These lessons included self-monitoring exercises
(and homework to self-monitor television, videotape, and video game use for
a week), in-class reporting and self-identifying activities they liked to do when not
watching television, reading a story about TV taking over a child’s life, and inven-
ting individualized endings to model potential outcomes and stimulate children
to form their own outcome expectations for reducing screen time, and a lesson
‘‘The world really wants to know: Are American kids addicted to TV?’’ to excite
the students about participating in their own scientific ‘‘experiment’’ and the
challenge of the upcoming TV Turnoff to boost intrinsic motivation. In sum, these
lessons were designed to provide opportunities for greater behavioral awareness,
elicit social support for watching less TV, and heighten the perceived incentive value
of the TV Turnoff and reducing screen time. These lessons helped children form
expectations regarding anticipated positive and negative outcomes of either main-
taining current levels of screen time or reducing their screen time.
2. The TV Turnoff. These five lessons occurred during a 10-day TV Turnoff
(Winn, 1987; The TV Turnoff, www.tvturnoff.org). During the TV Turnoff, children
attempted to watch no television or videotapes and play no video games for 10 days.
The TV Turnoff and the accompanying lessons were intended to provide an ‘‘inoc-
ulation’’ experience (McGuire, 1964) to help children (a) learn new strategies to resist
watching television and videotapes and playing video games; (b) invent and practice
T. N. Robinson & D. L. G. Borzekowski Curriculum to Reduce Child and Family Screen Time
Journal of Communication 56 (2006) 1–26 ª2006 International Communication Association 9
skills to reduce television, videotape, and video game use; (c) experience positive
outcomes from reducing television, videotape, and video game use, enhancing
outcome expectations; and (d) experience mastery in controlling screen time, in-
crease their perceived self-efficacy for reducing television, videotape, and video game
use. As part of this phase, we included an excitement-filled ‘‘kick-off ceremony,’’ in
which children assembled and committed to take the challenge of the 10-day TV
Turnoff. The challenge aspect was highlighted to enhance motivation. The highlight
of the kick-off ceremony was arrival of a research staff member in a gorilla suit, who
taught the children a parody of the then- popular song and dance ‘‘the Macarena,’’
called ‘‘the No-Watcherena,’’ to promote greater attention to and retention of the
TV-Turnoff tasks. Subsequent lessons included role-plays of specific tough situations
to build perceived self-efficacy, drawing their own ‘‘portrait of a TV Junkie’’ to
reinforce negative expected outcomes of excessive screen time, and a ‘‘closing cere-
mony’’ where school officials and community leaders acknowledged the students for
trying and/or succeeding in meeting the 10-day TV-Turnoff challenge. The classroom
with the greatest proportion of turnoff participants was awarded a trophy. Although
tangible rewards were included during the turnoff, a particular emphasis was placed
on building self-satisfaction for accomplishing goals, as self-evaluative outcomes are
often stronger influences on behavior than tangible rewards (Bandura, 1986).
3. Staying in control. Following the TV Turnoff, the next four lessons helped
children set and adhere to a more modest goal of 7 hours per week of media use. We
used this goal because our prior research suggested that this would be a substantial
decrease for most children, as well as a challenging yet realistic objective. Broad
evidence indicates that explicit challenging goals increase motivation (Bandura,
1986; Locke & Latham, 1990). To promote perceived choice and control among
children, we recommended that teachers guide their students into coming up with
the 7 hours per week budget, ‘‘by themselves.’’ All classrooms did choose 7 hours for
their goal budget. The Staying in Control lessons helped children (a) build additional
skills to resist social and environmental influences promoting excessive television,
videotape, and video game use; (b) develop high levels of perceived self-efficacy for
performing the skills learned; and (c) remain motivated to maintain reduced media
use. As a result, these lessons highlighted opportunities for skills mastery and
included brief role-playing exercises for dealing with difficult situations, problem
solving for long weekends and vacations, and ‘‘planning ahead’’ exercises to help
them stay within their budgets by being more selective about what they watch or
play. These lessons set the stage for the subsequent 4–5 months.
During this section, students also learned about and received the TV Allowance.
The TV Allowance (TV Allowance, Miami, FL) is a set-top electronic television time
manager that monitors and controls television use with a personal identification
number (PIN) for each member of the family. The TV Allowance allows parents
to set weekly time budgets for their children, and also can block use during certain
times of the day or week. Because it controls electrical power to the TV set, it
also controls VCR and video game use. When a child’s weekly budget expires, the
Curriculum to Reduce Child and Family Screen Time T. N. Robinson & D. L. G. Borzekowski
10 Journal of Communication 56 (2006) 1–26 ª2006 International Communication Association
television set turns off and cannot be turned on again with his/her PIN until the
budget replenishes at the beginning of the following week. Children practiced select-
ing a ‘‘secret code’’ PIN during a classroom lesson, creating additional motivation to
use the TV Allowance at home. We gave each student a TV Allowance to take home
and informed parents that they could request additional units, at no cost, for all the
television sets in their home. We customized an easy-to-read instruction manual to
help simplify set up of the TV Allowance and suggested methods to account for
budgeting over multiple TV sets and multiple children in a household. We also
provided a toll-free ‘‘SMART Hotline’’ to help parents over the telephone or for
parents to request additional TV Allowances. In a few cases when parents were
unable to solve their problems over the Hotline, a research assistant went to the
participants’ homes to help them set up the TV Allowance in person. Because
feedback on performance heightens motivation to achieve goals and the accompa-
nying personal satisfaction (Bandura, 1986; Bandura & Cervone, 1983), the TV time
manager also was intended to partially reduce the burden on parents to monitor and
enforce children’s screen time and to help provide children with ongoing feedback
on their performance (i.e., staying under budget goals).
This section of the curriculum also introduced an incentive system for children
who maintained their weekly media-use budget. Every Friday during the interven-
tion, there was a 5- to 10-minute ‘‘SMART Talk,’’ when children reported their
successes and received peer recognition for turning in a ‘‘SMART Slip.’’ The SMART
Slip was a form signed by parents, confirming that the child adhered to his or her
budget over the past week. Thus, the weekly SMART Slips produced opportunities
for parental awareness and reinforcement of goals and achievements by their chil-
dren. The SMART Talks created a classroom environment of teacher and peer
recognition and social support for achievement of goals. Red, bronze, silver, and
gold desk ribbons and ‘‘certificates of accomplishment’’ were awarded for cumulative
counts of 5, 10, 15, and 20 weeks within budget, respectively, also providing grad-
uated levels of challenge and mastery to enhance intrinsic motivation. This design
feature drew upon prior research and theory that self-motivation is generally best
sustained by a series of proximal subgoals that are hierarchically arranged to lead to
longer-term goals (Bandura, 1986; Locke & Latham, 1990).
4. Helping others: After several months of using the TV Allowance and engaging
in ‘‘SMART Talks,’’ four more lessons occurred in Spring 1997. These lessons were
intended to (a) support children’s positive attitudes about reducing time spent using
media, (b) reinforce children’s perceived self-efficacy for the skills they were engag-
ing in, and (c) help motivate children to maintain their behavior changes. Our
experience is that advocacy to help peers is a highly motivating activity for school-
age children. It also provides opportunities and reinforcement for repeated cognitive
and enactive rehearsal of arguments for reducing screen time and the skills used to
influence both outcome expectancies and self-efficacy. Students were enlisted to help
third- graders at another school overcome their ‘‘addictions’’ to television, videotapes,
and video games. Children wrote two-paragraph letters to the other students to
T. N. Robinson & D. L. G. Borzekowski Curriculum to Reduce Child and Family Screen Time
Journal of Communication 56 (2006) 1–26 ª2006 International Communication Association 11
persuade them to reduce their screen time and tell them which methods work best.
Children then read out the letters to their own classmates before they were mailed.
Children also painted a mural to publicly display all the fun things they found them-
selves doing (and planned to do) because of their reduced screen time. These advocacy
activities were designed to alert students to discrepancies between their behavioral
goals to reduce screen time and their own screen-use behaviors and then to nominate
and cognitively rehearse the strategies they considered most effective to reduce these
discrepancies to achieve their goals as well as the positive outcomes expected to
accompany their goal behaviors. Reducing perceived discrepancies between goals
and performance is considered central to self-motivation (Bandura, 1986).
Parent newsletters
In a review of parent intervention research for school-based health promotion, Perry and
colleagues concluded that (a) children are able to influence the attitudes and behaviors of
their parents, (b) poor parent participation rates are a substantial barrier to implement-
ing parent/family-based interventions, and (c) parents prefer interventions involving
their children that can be completed at home (Perry, Crockett, & Pirie, 1987). Our
experience has been consistent with these conclusions. Because most families are unlikely
to accept face-to-face interventions, given their inherent intrusiveness and time com-
mitment, we created an engaging, informative, and noninvasive parent newsletter. Four-
teen SMART Kids, SMART Families parent newsletters were sent to parents of students
in the intervention school. We designed the newsletters to (a) inform parents of the
potential benefits of reducing their children’s television, videotape, and video game use;
(b) motivate parents to help their children reduce their media use; (c) suggest strategies
to help their child and the entire family; (d) offer ideas for implementing selective
viewing policies; (e) teach contingency management skills to help them support their
children’s behavior changes; (f) provide public recognition for children staying under
their budgets; and (g) create a stronger connection with their children’s school and
classroom by updating parents on the SMART classroom activities.
Child measures
At baseline and post-test, on the same days in both schools, children completed self-report
questionnaires during 40-minute class periods on two separate days. A research staff
member read each question aloud and students followed along and marked their responses
in the survey booklets. Teachers did not participate in the assessments.
Demographics and household media environment
Children reported their date of birth; age in years; sex; number of TV sets, VCRs, and
video game players in their home; and whether there was a television in their bedroom
(Robinson, 1999).
Media use and other activities
After a series of participatory time-estimating exercises, repeated on each day, children
reported the time they spent ‘‘Watching television (not including videos on a VCR),’’
‘‘Watching movies or videos on a VCR,’’ ‘‘Playing video games (like Nintendo or Sega, not
Curriculum to Reduce Child and Family Screen Time T. N. Robinson & D. L. G. Borzekowski
12 Journal of Communication 56 (2006) 1–26 ª2006 International Communication Association
including games on a computer),’’ ‘‘Playing on a computer (not including homework),’’
‘‘Doing homework (including reading a book or magazine for school or working on
a computer),’’ ‘‘Reading a book or magazine NOT for school,’’ ‘‘Listening to music on
the radio, tapes, or CDs,’’ ‘‘Playing a musical instrument,’’ ‘‘Doing artwork or crafts (like
drawing, painting, and making things),’’ ‘‘Talking with your parents,’’ ‘‘Playing quiet
games indoors (like playing with toys, puzzles, or board games),’’ and ‘‘At classes or clubs
(like Brownies, Cub Scouts, religious school, or Judo classes).’’ Children completed the list
first for ‘‘Yesterday before school, from when you woke up until the start of school’’ and
then for ‘‘Yesterday after school, from the end of school until you went to bed,’’ on an 8-
item scale: none, 15 minutes or less, 30 minutes, 1 hour, 2 hours, .6 hours or more. On
the first assessment day, children similarly reported time spent watching television, mov-
ies, or videos in a VCR; playing video games; and playing on a computer, for ‘‘Last
Saturday in the morning (from when you woke up until noon)’’ and ‘‘Last Saturday in
the afternoon and evening (from noon until the time you went to bed).’’ This instrument
was adapted from a similar instrument previously used with young adolescents with high
test-retest reliability (r= .94) (Robinson & Killen, 1995) and piloted with direct video
observation in children in this age group (Borzekowski & Robinson, 1999).
Parent measures
Trained research staff interviewed parents by telephone at baseline and posttest. At least
10 call attempts were made at various times of day and different days of the week, and up
to three messages were left on answering machines, before classifying a parent as a non-
respondent. Mothers or female guardians were requested for interviews, but fathers or
male guardians were interviewed if mothers were not available. We completed all the
parent interviews within a 23-day period at baseline and a 36-day period at posttest, with
more than 85% of interviews performed during the first 16 days of each assessment period.
Demographics
Parents reported the ethnicity of their child, the highest education level completed for all
parents or guardians living in the household, and their marital status (Robinson, 1999).
Household composition and television viewing
For themselves and every member of the participating child’s household, parents
reported specific relationship to the participating child, sex, age (for minors only),
and ‘‘hours of television viewing in a typical week.’’
Intervention participation
After completing the posttest parent phone interview, experimental assignment was
unblinded to interviewers, and parents of children in the intervention school were asked
how often they read the parent newsletters (7-point Likert scale ranging from never to all
of the time), if they used the TV Allowance, and, if yes, whether they were still using the
TV Allowance.
Statistical analysis
We assessed baseline comparability of treatment and control groups using nonparametric
Wilcoxon rank sum tests for scaled variables and chi-square tests for categorical variables.
T. N. Robinson & D. L. G. Borzekowski Curriculum to Reduce Child and Family Screen Time
Journal of Communication 56 (2006) 1–26 ª2006 International Communication Association 13
To test the hypothesis that the intervention reduced television, videotape, and video game
use, we used analysis of covariance (ANCOVA) with the posttest measure as the dependent
variable, the intervention group (intervention vs. control) as the independent variable,
and the baseline value of the same measure as a covariate. This analysis assumes that
there is no nonzero correlation between the subjects’ responses within a school. Because
randomization was by school, and students within a school may have correlated
responses, we also checked this assumption by repeating the analysis using a mixed-
model ANCOVA (SAS MIXED procedure, SAS version 8.0, SAS Institute, Inc., Cary,
NC), which adjusts for observed between-subjects correlations within schools (Murray,
1998). As expected, this analysis produced the same results. In no single case did the
mixed-model ANCOVA result differ in statistical significance from the standard
ANCOVA, suggesting intraclass correlations approximating zero. Therefore, all reported
effect sizes, confidence intervals, and pvalues are derived from the simpler, standard
ANCOVA. Consistent with intention-to-treat principles, all students were analyzed in
their schools as randomized, regardless of their participation or compliance with the
intervention or whether they transferred between schools between baseline and posttest,
and all available data were included in the analyses. Tests of statistical significance were
two-tailed with a= 0.05. With this analysis and an anticipated sample size of approx-
imately 100 participants per group, the study was designed to have 80% power to detect
an effect size as small as 0.2 standard deviation units (Kraemer & Thiemann, 1987).
Results
At baseline, 105 third and fourth graders were enrolled in the intervention school and
120 third and fourth graders were enrolled in the control school. Ten students from the
intervention school (9.5%) and 18 students from the control school (15%) did not have
parental consent to participate in the study. We also excluded self-report survey data
a priori for two students from the intervention school and nine from the control school,
because their teachers classified them as having a significant learning disability or limited
English proficiency and were concerned about their ability to complete the surveys,
resulting in baseline samples of 93 students in each school. Posttest surveys were com-
pleted by 92 children in the intervention school and 89 children in the control school
(baseline to posttest retention rates of 99% and 96%, respectively), making up the analysis
sample for this study. The children lost to follow-up included three control school
children who moved and one student in each school who was absent during data collec-
tion. Intervention and control children were comparable in age (mean [SD] 8.9 [0.6] vs. 8.9
[0.7] years, p= .51), sex (44.6% vs. 47.2% girls, p= .72), mean [SD] number of TV sets in
the home (2.7 [1.3] vs. 2.7 [1.1], p= .80), mean [SD] number of VCR’s in the home (1.7
[0.9] vs. 1.8 [0.9], p= .76), mean [SD] number of video game players (0.7 [0.5] vs. 0.6 [0.5],
p= .32), and percentage of children with a bedroom TV (43.5% vs. 42.7%, p= .92).
In the intervention and control schools, 68 (73.9%) and 67 (75.3%) of the parents
or guardians of participating children, respectively, completed both baseline and
posttest telephone interviews. Participating intervention school parents reported
Curriculum to Reduce Child and Family Screen Time T. N. Robinson & D. L. G. Borzekowski
14 Journal of Communication 56 (2006) 1–26 ª2006 International Communication Association
greater maximum household education levels than control school parents (87.5% vs.
70.9% with at least some education beyond high school, p= .01) but did not differ
significantly in ethnicity (80.6% vs. 77.2% White, p= .62), sex of respondent (81.9%
vs. 87.2% female, p= .37), or marital status (76.4% vs. 67.1% married, p= .21).
Intervention implementation and participation
Teachers reported teaching all lessons although we did not collect student attendance
data to estimate the classroom intervention dose for individual students. Ninety-five
percent of students in the intervention school sample participated in at least some of the
TV Turnoff (i.e., submitted at least one signed parent confirmation slip), and 71%
completed the entire 10 days without watching television and videotapes or playing
video games (mean [SD] = 7.9 [3.6] days). Forty-two percent of parents returned slips
reporting they had installed the TV Allowance, and 20% requested one or more addi-
tional TV Allowances (range = 1–3 additional). However, among the subgroup of inter-
vention school parents participating in post-test telephone interviews, 70% reported
using the TV Allowance, and 72% of them (therefore at least 50% of the entire inter-
vention school sample) reported they were still using the TV Allowance at posttest.
Almost all interviewed parents (92%) reported reading at least one SMART Kids, SMART
Families newsletter, 55% reported reading more than half of the newsletters, and 37%
reported reading all 14 newsletters. Over the budgeting phase of the intervention, 58% of
students turned in at least one parent-signed SMART Slip indicating they had stayed
under their weekly budget (mean [SD] = 8.0 [9.0] weeks; range = 0–29 weeks).
Effects of the intervention on children’s screen media use
We report baseline and posttest estimates of students’ screen media use in Table 1. At
baseline, students from the intervention and control samples were similar with respect to
Table 1 Weekday and Saturday Hours Per Day of Television, Videotape, and Video Game Use
Mean Hours (SD) Per Day Adjusted Difference
(95% CI)
a
Baseline Posttest
Intervention Control Intervention Control
Television viewing
Weekday 1.78 (1.67) 1.86 (2.07) 1.14 (1.38) 1.96 (1.95) 20.79 (21.22, 20.35)***
Saturday 3.17 (3.22) 3.03 (3.36) 1.76 (2.41) 2.42 (2.74) 20.70 (21.42, 0.03)
Videotape/video cassette recorder viewing
Weekday 0.51 (0.88) 0.71 (1.58) 0.36 (0.63) 0.62 (1.21) 20.18 (20.42, 0.06)
Saturday 1.14 (1.79) 0.98 (1.78) 0.81 (1.36) 1.04 (1.71) 20.23 (20.69, 0.23)
Video games
Weekday 0.27 (0.67) 0.48 (1.47) 0.19 (0.59) 0.52 (1.23) 20.24 (20.48, 20.01)*
Saturday 0.56 (1.25) 0.72 (1.68) 0.31 (0.76) 0.90 (2.49) 20.53 (21.04, 20.01)*
a
Adjusted differences are intervention minus control group mean differences at post-test,
adjusted for pretest values with analysis of covariance.
*p,.05. *** p,.001.
T. N. Robinson & D. L. G. Borzekowski Curriculum to Reduce Child and Family Screen Time
Journal of Communication 56 (2006) 1–26 ª2006 International Communication Association 15
their screen time (all p..24). Effects of the intervention are presented as adjusted post-
test differences and 95% confidence intervals with accompanying pvalues. Intervention
school children significantly reduced their weekday television viewing and weekday and
Saturday video game playing compared to children in the control school. The results did
not change when we repeated this same analysis for separate morning and afternoon/
evening estimates of media use. Therefore, all results are presented as full-day estimates.
There were no significant differences between groups in changes in self-reported
weekday time spent playing on a computer (adjusted difference [95% CI] = 2.23
[2.48, .03], p= .08), Saturday time spent playing on a computer (2.07 [2.39, .25],
p= .66), time spent doing homework (p= .23), reading (p= .64), listening to music
(p= .39), or doing artwork or crafts (p= .77). Reported occurrences of playing
musical instruments, talking with parents, playing quiet indoor games, and attending
classes or clubs were too small to allow for valid analysis.
Effects of the intervention on parents and other household members’
television viewing
To assess the effects of the intervention on household television viewing, we analyzed
data provided by the interviewed parent or guardian regarding weekly hours of television
viewing for (a) mothers, including biological, step, and adoptive mothers, and female
guardians (n= 64 in the intervention sample and n= 62 in the control sample);
(b) fathers, including biological, step, and adoptive fathers, and male guardians (n=
56 in the intervention sample and n= 47 in the control sample); and (c) each sibling
and/or other minor living in the same household at the time of the interview. In this
analysis of viewing changes, we averaged viewing estimates across all siblings and other
children in each household (n= 55 and n= 58 for siblings and other children in the
intervention and control samples, respectively). Intervention and control samples were
comparable on the number of siblings and other children per household (1.3 vs. 1.5,
respectively, p= .31), the mean ages of siblings and other children (9.1 vs. 9.0 years,
respectively, p= .90), and total household size (4.3 vs. 4.3 people per household, respec-
tively, p= .78). We show the baseline and post-test estimates of household members’
weekly television viewing in Table 2. We observed no significant baseline differences
between the intervention and control samples for hours of television viewing by the
mother or female guardian (p= .11), the father or male guardian (p= .11), and siblings
and other children (p= .34). At posttest, however, all intervention sample household
members significantly reduced their television viewing compared to control school
household members.
Moderators of changes in children’s television, videotape, and video game use
To identify subgroups of the intervention school sample that had greater or lesser
responses to the intervention, we examined a number of baseline factors in a moderator
analysis. Awareness of potential moderators can be useful for appropriate targeting
of interventions, identifying particular inclusion/exclusion criteria in future studies, or
determining factors on which studies may be stratified to amplify power (Kraemer et al.,
Curriculum to Reduce Child and Family Screen Time T. N. Robinson & D. L. G. Borzekowski
16 Journal of Communication 56 (2006) 1–26 ª2006 International Communication Association
2002). For this, we combined weekday and Saturday estimates into a summed weekly
estimate, multiplying the weekday estimate by 5 and the Saturday estimate by 2. We then
used the same ANCOVA approach used above but also adding in each potential mod-
erator variable and the treatment by potential moderator interaction term as additional
covariates. A significant interaction term indicates that that variable acts as a moderator
of the intervention effect. This analysis was also done separately for each of the three
outcomes of children’s reported television viewing, videotape viewing, and video game
use. Potential moderators tested in this manner included baseline screen media use, sex,
number of siblings and other children living in the household, total number of persons
living in the household, number of television sets in the home, number of VCRs in the
home, presence of a television set in the child’s bedroom, number of video game
machines in the home, ownership of a handheld video game machine, presence of
a computer that the child was allowed to use in the home, baseline levels of household
television use, parent attitudes about television, parent policies about television, family
rules about television, whether the child spent any time in child care, and whether the
child spent any time alone unsupervised by an adult.
We found several baseline factors to be statistically significant moderators of the
intervention effect. Reductions in television viewing in response to the intervention
were greater among boys than among girls (p= .05), among children who spent no
time alone, unsupervised by an adult (p= .03), and among children who watched more
television prior to the intervention (p= .05). In addition, we observed the intervention
to be most effective at limiting videotape viewing and video game playing among
children who reported no videotape or video game use prior to the intervention
(p= .04 and p= .05, respectively). In other words, the intervention effects were most
pronounced for preventing subsequent onset or increases in videotape and video game
use among baseline nonusers. There were no other statistically significant moderators.
Mediators of changes in children’s media use
To better understand intervention-related factors related to individual response to the
intervention, we used a similar ANCOVA approach to identify potential mediators of
Table 2 Other Household Members’ Hours Per Week of Television Viewing
Mean Hours (SD) Per Week Adjusted Difference
(95% CI)
a
Baseline Post-test
Intervention Control Intervention Control
Mothers or female
guardians
10.46 (10.76) 11.48 (8.40) 8.80 (8.97) 12.49 (9.92) 23.09 (25.74, 20.44)*
Fathers or male
guardians
11.14 (8.66) 15.67 (12.45) 10.21 (7.42) 16.16 (11.33) 23.93 (27.17, 20.69)*
Siblings and other
children
11.76 (8.41) 12.59 (8.69) 8.38 (5.96) 12.51 (7.80) 23.79 (26.02, 21.56)***
a
Adjusted differences are intervention minus control group mean differences at post-test, adjusted for
pretest values with analysis of covariance.
*p,.05. *** p,.001.
T. N. Robinson & D. L. G. Borzekowski Curriculum to Reduce Child and Family Screen Time
Journal of Communication 56 (2006) 1–26 ª2006 International Communication Association 17
changes in children’s reported television, videotape, and video game use. Knowing
mediators can inform and advance the investigation of causal mechanisms (Kraemer
et al., 2002), including shedding light on the relative importance of various elements of
the intervention model. Potential mediators tested included the number of days reported
with no television, videotapes, or video games during the TV Turnoff, whether or not the
TV Allowance was reported to have ever been hooked-up, the number of additional TV
Allowances requested, whether the TV Allowance was still being used at the posttest
interview, the proportion of newsletters the parent reported reading, and the number of
underbudget SMART Slips the child turned in during the budgeting phase of the cur-
riculum. In these analyses, none of these factors were found to be statistically significant
mediators of changes in television viewing, videotape viewing, or video game playing.
Discussion
This study demonstrates the efficacy of a social cognitive theory–based classroom inter-
vention to reduce children’s screen time, as well as to decrease television watching among
their parents, siblings, and other household children. At the end of the intervention, third
and fourth graders in the intervention school were spending about 14 hours a week using
electronic media, while students from the matched control school were spending about
24 hours per week. Statistically significant differences were seen for weekday television
viewing and weekday and weekend video game use with substantial, but nonsignificant,
trends in Saturday television viewing and weekday and Saturday videotape viewing. The
results provide additional support for the validity of social cognitive theory as a concep-
tual model for interventions to influence complex behaviors, such as screen media use.
Although effects were seen across all students, moderator analyses revealed
a number of subgroups that responded more or less to the intervention. First, differ-
ences between boys in the intervention and control schools were greater than differ-
ences between girls; boys in the intervention school decreased their television
watching by about 6 hours per week compared to boys in the control school, who
increased their television watching by about 1 hour per week during the course of the
study. Girls in the intervention and control schools reported decreases in their
television watching of about 7 hours and 2 hours per week, respectively. Our inter-
vention was designed to apply social cognitive theory principles for both boys and
girls, and thus we do not have an explanation for these differential effects of the
intervention. Because substantial decreases were seen in both sexes, we do not think
the curriculum is necessarily suited more to boys than to girls. It is possible that these
differences reflect sex differences in normal trajectories of television viewing from fall
to spring at these ages.
Baseline media use also moderated some intervention effects. The intervention
produced greater magnitude effects on television watching among children who
started as the heaviest TV viewers. In contrast, the intervention had a bigger effect
on videotape and video game use for students who reported the least videotape or
video game use at baseline. Although these results seem contradictory on the surface,
Curriculum to Reduce Child and Family Screen Time T. N. Robinson & D. L. G. Borzekowski
18 Journal of Communication 56 (2006) 1–26 ª2006 International Communication Association
they all may indicate that the greatest effects are observed among those students
with the most room to change (children who watch the most TV at baseline and
children who are not yet playing video games and watching videotapes). Because the
goal was to keep total screen time to 7 hours per week or less, successful budgeting
would create greater magnitude differences among heavy baseline viewers. Heavy
baseline television watchers might also be more responsive to the intervention
because we designed the curriculum to influence children’s outcome expectancies
through establishment of perceived social norms. Lessons were designed to help
children associate negative outcomes with greater screen time and positive outcomes
with reducing screen time. Activities such as reporting one’s baseline TV hours viewed
and seeing them graphed with the rest of one’s classmates would be expected to create
greater perceived social pressure for change on those who were heavy viewers. In
addition, intrinsic motivation to change might be greater for those whose behavior
was more discrepant from the standard (Bandura, 1986; Locke & Latham, 1990).
Finally, children who were rarely left alone without adult supervision responded
the most to the intervention compared to those with less adult supervision. This
result may suggest that children who experience more adult supervision receive more
help from household adults in limiting their television watching and/or that adult
supervision is a proxy for greater child behavioral change skills or environments that
are more supportive of changes in media use. Social cognitive theory would predict
that children whose parents or guardians are more supportive of their attempts to
reduce their screen viewing time would develop more positive outcome expectations
and greater perceived self-efficacy for decreasing screen time by seeing their parents
model screen-limiting behaviors, receiving more immediate feedback about their
screen-viewing behaviors from their parents, and receiving more reinforcement
for successful behavior change. More adult supervision allows for more opportuni-
ties to model desired behaviors, observe children’s behaviors and provide immediate
feedback, and provide rewards for successful behavior change. Although a number of
other home environmental characteristics also would be expected to either facilitate or
deter behavioral changes, variations in other household factors were not statistically
significant moderators of intervention effects, including household composition and
size, existing parent attitudes, policies and rules about television watching, and the
screen media present in the household. Because statistical power was limited to detect
interactions, however, statistical significance is a conservative standard and cannot
fully rule out that some of these factors might also moderate intervention effects.
None of our measures of intervention participation proved to be statistically
significant mediators of individual intervention responsiveness. This included whether
or how long the family used the TV Allowance television time manager. This small
study, therefore, does not allow us to conclude whether individual components of
intervention participation were more or less important in reducing children’s screen
time. Again, because statistical power was limited to detect interactions, we cannot
rule out that some of intervention components might be more likely than others to be
in the causal pathway for reducing screen time. Our findings also do not support
T. N. Robinson & D. L. G. Borzekowski Curriculum to Reduce Child and Family Screen Time
Journal of Communication 56 (2006) 1–26 ª2006 International Communication Association 19
claims that screen time displaces homework, recreational reading, listening to music,
or doing arts or crafts, as children in the intervention school did not report increased
time spent in these other activities, compared to controls. Like all null results, con-
clusions drawn from these findings must be made cautiously because children’s
self-reports of time use may suffer from substantial measurement errors, reducing
statistical power to detect differences. These results also leave it unclear what students
from the intervention school did when they reduced their screen time. As reported,
the prevalences of many measured activities were too small to satisfactorily test for
differences between groups. This may also suggest that there is a large variety of
activities with which individual children replace their screen time. Larger studies
with more objective measures of time use may be necessary to answer this question.
This is the first study to report that a classroom curriculum targeting students’
media use can also reduce television watching by other members of their households.
Among intervention school households, students’ mothers, fathers, siblings, and
other children living in the home watched about 3–4 hours per week less television
than control school household members. This result supports the potential of inter-
vening with children in schools to influence parent and sibling behaviors at home.
This finding is consistent with the experiences of some other school-based health
promotion interventions that have impacted the home environment (Perry et al.,
1987). In our formative research leading to the present study, we were impressed that
targeting children directly for television reduction was more successful than targeting
their parents directly. Based on interviews with individual families, our impression
was that parents, even apparently motivated parents who had volunteered to par-
ticipate in a study because they wanted to reduce their children’s television viewing,
had too many other competing priorities to balance, resulting in less follow-through
with intervention activities. In contrast, when children became motivated by the
intervention activities, they were able to draw their parents into the process, making
it a higher family priority. These qualitative observations helped reinforce our deci-
sion to target children directly with the intervention through a classroom curricu-
lum. They also highlight the importance of paying special attention to motivational
processes in designing behavior-change interventions (Bandura, 1986).
We are confident in our findings, even though the study only involved two
elementary schools. Although it is possible that the results were due to differences
in the intervention and control groups that were unrelated to the intervention, this is
not very likely because the schools were drawn from a single school district, the
schools were matched by school district administrators prior to randomization, and
participants were comparable at baseline on almost all measured variables, including
all baseline screen media use variables, and household media ownership. Another
potential limitation is that we relied on self-reports and parent reports of screen time.
To try to minimize this limitation, we used very detailed measures that have face
validity and have proven to be highly reliable in prior studies (Robinson & Killen,
1995). Some studies suggest that self- and parent reports of television viewing are
valid (Anderson, Field, Collins, Lorch, & Nathan, 1985), though we acknowledge
Curriculum to Reduce Child and Family Screen Time T. N. Robinson & D. L. G. Borzekowski
20 Journal of Communication 56 (2006) 1–26 ª2006 International Communication Association
that self-reports have many weaknesses (Borzekowski & Robinson, 1999). In addition,
we employed a randomized controlled trial design where data collectors were blinded
to intervention assignment. Students, parents, and teachers were blind to the specific
study hypotheses although it was impossible, of course, to blind them to the fact that
they were receiving a curriculum to reduce screen time. Last, if participants were
trying to impress our data collectors, we presume that they would have reported that
they were adhering to the 7-hour per week screen time budget, rather than exceeding
it by an average of twice that amount, and they would have reported increased time
doing publicly sanctioned activities such as reading and doing homework.
The intervention’s success may be a consequence of its strong theoretical foun-
dation. We put great attention into creating a feasible curriculum that engages and
motivates children, teachers, school administrators, and family members to comply
with the intervention’s objectives and components. As described above, the social
cognitive model (Bandura, 1986) served as the conceptual foundation for interven-
tion design and implementation. We designed curriculum activities to account for
a wide variety of personal, behavioral, and environmental factors that were consid-
ered to influence screen media use among children. We took great care to make all
elements of the curriculum consistent with the cognitive social learning model,
particularly concentrating on the four key processes of attention, retention, pro-
duction, and motivation. As a result, the successful behavior change observed in
this study is further evidence of the applicability of social cognitive theory to devel-
oping interventions to promote individual and group behavior change (Bandura,
1986, 1997). However, although this study was a successful test of applying social
cognitive theory to change a complex behavior in a real-world setting, and thus
adds support to the usefulness of this model to explain human behavior, the study
was not designed to test a specific part of the model, or contrast the relative im-
portance of different inputs or processes specified by the model. Instead, we have
provided a description of how we applied the principles of social cognitive theory
to the specific behavior-change activities that comprised the curriculum and their
implementation. These can now serve as examples for developing other theory-based
interventions to influence screen media–related behaviors, either in the laboratory
setting, to further delineate the processes involved in changing these behaviors, or in
naturalistic studies, such as ours, to alter or examine the effects of related behaviors.
We concur with Agras et al. (1979) about the need to begin with simple, straight-
forward efficacy trials before moving to more complicated component studies.
Another strength of this intervention was that it encouraged the child to take
control of his or her media use, without dictating specific content or context rules.
With the nonspecific 7-hour per week limit, the intervention attempted to help
children (and their family members) learn to be ‘‘smart’’ consumers of screen media,
by budgeting and regulating their use of television, videotapes, and video games. This
focus was selected because of research on perceived choice and control as factors that
increase intrinsic motivation for learning and behavior change (Bandura, 1986;
Lepper, 1985).
T. N. Robinson & D. L. G. Borzekowski Curriculum to Reduce Child and Family Screen Time
Journal of Communication 56 (2006) 1–26 ª2006 International Communication Association 21
If the effects of this intervention can be replicated in additional samples and
settings, further research might examine which specific aspects of the intervention
are necessary to produce effects. Future component studies may also be useful in
clarifying how specific elements of the intervention affected outcome expectancies
and perceived self-efficacy for each of the specific behaviors targeted. This inter-
vention involved only a small sample of northern California third- and fourth-
graders. It is unknown whether this intervention would produce similar effects in
schools in other geographic and sociodemographic settings. We designed the inter-
vention and curriculum components to be ‘‘age appropriate,’’ and because some of
the specific factors influencing attention, retention, production, and motivation
processes would differ across age groups, we believe that modifications would be
necessary before this intervention could be used effectively with other age groups.
Last, we delivered this intervention through schools. Other researchers may wish to
test whether comparable effects are observed if a similar intervention is delivered
through parents.
From clinical, practical, and policy perspectives, this study has produced an
efficacious and potentially generalizable, classroom-based curriculum to reduce
third and fourth grade children’s screen time. The curriculum also reduces televi-
sion viewing among other household members. Because the intervention was tested
in a naturalistic, public elementary school setting and sample, and delivered by the
existing classroom teachers, this may be the first feasible and effective response to
the many calls from health, education, and child and family advocacy groups to
limit children’s television viewing. For other investigators, this study provides
a model for an ethical and practical experimental method to study the hypothesized
impacts of media exposure on children’s and families’ health, behaviors, and well-
being. Instead of studying increased media exposure as a cause of adverse out-
comes, the standard approach under the current ‘‘problem-oriented’’ or ‘‘disease-
oriented’’ research paradigm, this new experimental model is more consistent with
a ‘‘solution-oriented’’ research paradigm, in which one tests the effects of reducing
the putative risk factor of media exposure as a cause of improved outcomes
(Robinson & Sirard, 2005). This approach avoids ethical concerns regarding expos-
ing children to potentially harmful media (e.g., violent, commercial, or obesogenic
media content), supports causal inferences because of its experimental design, and
also can result in identifying a ‘‘solution’’ that is not possible from the standard
approach to etiological research.
Acknowledgments
This study was supported in part by a grant from the American Heart Association,
California Affiliate and a Robert Wood Johnson Foundation Generalist Physician Faculty
Scholar Award. We thank Marta L. Wilde, M.A., who was invaluable in the development
and implementation of this intervention, K. Farish Haydel and Ann Varady, M.S., for
coordinating data collection and database management and data analysis, and the
Curriculum to Reduce Child and Family Screen Time T. N. Robinson & D. L. G. Borzekowski
22 Journal of Communication 56 (2006) 1–26 ª2006 International Communication Association
participating students, families, teachers and administrators for their contributions to
this study. The SMART curriculum may be obtained at http://NoTV.stanford.edu.
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... Pela negativa, e de acordo com a hipótese da redução, há uma grande quantidade de estudos que evidencia correlatos desenvolvimentais negativos do tempo a ver televisão (Robinson & Borzekowski, 2006). ...
... Parece claro que uma intervenção nas rotinas das crianças deverá ter como objectivo limitar o tempo a ver televisão Robinson & Borzekowski, 2006). Estratégias para reduzir o tempo de televisão devem ser incluídas entre as estratégias mais amplas para reduzir a obesidade infantil (Gable & Lutz, 2000;Zutphen et al., 2007) e, para reduzir ou ajustar o visionamento da televisão, é essencial intervir junto dos pais (Yalçin et al., 2002). ...
Thesis
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Children's screen time is increasing and has devastating effects on various aspects of their development and health. This systematic review study was conducted to investigate the role of family and shortcomings in interventions to reduce children's use of digital media. PsycNet, ScienceDirect, Medline, Pub- Med, Scopus, Web of Science, ISC, SID and IranDoc were searched from 2000 to 2019. All research studies that were RCT with children under age 12 and aimed to reduce ST in children were eligible to study. 18 of them were eligible and were included in the review. Most of the strategies used were behavioral and cogn- itive, and family factors, including communication between family members and child-parent relationship as an impor- tant and influential factors in managing child behavior were largely neglected across the articles reviewed. Awareness of parents about the negative consequences of children's over- use of digital devices and training them to perform alternative and joint activities as two main elements can make interventions be more effective than when they focus only on teaching skills to children. In addition, involving parents in interventions is more effective when other influential factors such as child and parent characteristics, quality of parent-child interaction, patterns of pare- nting behaviors, parenting styles and influencing factors in home environment should also be considered. Keywords: Child, Digital Devices, Fam- ily, Interaction, Intervention, Parents, Pa- rent- Child, Screen Time.
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