Screen Time and Learner Well-being

Screen Time and Learner Well-being:
The Debate, the Evidence and Directions for Future
Research and Policy
A Research Brief by
UNESCO MGIEP
Anantha DURAIAPPAH
Yoko MOCHIZUKI
Robin SHARMA
Kriti SINGH (Research Support)
Introduction: Growing up in a Digital Environment
In many parts of the world, children are growing up surrounded by digitally mediated
communication, gaming and a plethora of information and entertainment on screens. Children
today live in a digitally connected world. Irrespective of the type of digital device used, the
screen is the key portal that connects the user with the digital world.
The screen has become the gateway to entertainment, social interaction, information and
education. In the recent context of social distancing in the face of the COVID-19 pandemic,
screens have become even more embedded in our everyday lives for both adults and children.
While we cannot overstate the need to address the digital divide within and across countries,
the children and young people of today—the digital natives—are practically born with a screen
in their hands. For example, over 75% of 450 French parents of infants (ages 5-40 months) have
reported that their young children use some touch-screen technology (Cristia and Seidl 2015),
1
Screen Time and Learner Well-being:
The Debate, the Evidence and Directions for Future Research and Policy
A Research Brief by UNESCO MGIEP

while over 66% of children aged 3-8 years have been reported to use their parents’ mobile
touch-screen devices in five Southeast Asian countries (Unantenne 2014). 1
Figure 1: Percentage of young people (15-24 year olds) who are internet users by region
Source: Adopted from UNICEF (2017), p. 46, Figure 2.2.
Unsurprisingly, the overwhelming majority of young people are internet users across the world,
with a notable exception of the African continent (see Figure 1). There is no denying that the
increasingly mobile and connected digital devices are becoming an integral part of the daily lives
of the younger generation. Just as the book and the printed medium was an integral part of the
20 th century, the digital media is the preferred choice in the 21 st century especially among the
younger generation.
In fact, there is a generational divide when it comes to the use of digital technology. In a recent
study on the use of digital technology during the COVID-19 pandemic, it was found that the
users with the maximum time spent on digital devices were the GEN Z followed by the
Millennials (see Figure 2 below).
1
In these studies, ‘touch-screen technology’ and ‘mobile touch-screen devices’ refer to tablets and smartphones.
2
Screen Time and Learner Well-being:
The Debate, the Evidence and Directions for Future Research and Policy
A Research Brief by UNESCO MGIEP

Figure 2: Mobile and PC/laptop usage increase on lockdown. Source: Adopted from GlobalWebMiIndex
(2020), p.28 2
In recent years, young children’s and adolescents’ time spent on screens has attracted
considerable public and policy attention, with concerns around the effects of screen time on
physical and mental health and educational outcomes. What is the impact of the increased use
of digital devices on the well-being of learners and in particular young children and adolescents
is a key question on the minds of parents and many decision makers. However, we must
acknowledge that these questions are generally posed by policymakers who belong to the Baby
Boomer generation who incidentally have the lowest time usage of digital technology as
indicated in Figure 2.
With the COVID-19 crisis, the use of digital technology for teaching and learning has taken on a
new alignment, which has a completely new meaning and imperative for policymakers,
researchers and educators alike across the globe. The annual total internet usage worldwide
jumped from a 2.6 % average over the past 14 years to a growth of 5.4% just in 2020 (ITU
2020) 3 . The average daily time spent on the internet for all age groups (16-64) was around 7
hours a day (GWI 2020).
In the face of a paramount need to address continuous learning and learner well-being at the
times of social distancing and uncertainty, this paper aims at providing a ‘state of the art’ review
of the knowledge on the use of screen-based media devices 4 and learner well-being, drawn
primarily from peer-reviewed literature on the topic.
2
https://blog.gwi.com/chart-of-the-week/device-trends-shaping-2020/
3
https://www.itu.int/en/ITU-D/Statistics/Pages/ff2020interactive.aspx
4
Screen-based media devices (SBMD) include mobile phone, tablet, laptop, television etc. (Mireku et al. 2019).
3
Screen Time and Learner Well-being:
The Debate, the Evidence and Directions for Future Research and Policy
A Research Brief by UNESCO MGIEP

Reframing the Debate: Screen Time and Learner Well-being
There are always hypes and concerns surrounding new technology. While changing technologies
certainly have some effects on us, these effects—both negative and positive—can often be
exaggerated during the early stages of diffusion of a new technology. Even before the COVID-19
pandemic hit the world, there were concerns about screen time as related to ‘learner wellbeing’
(See Box 1) that includes social skills deficits, deteriorating physical and mental health,
and aggression of young children and adolescents.
Box 1: Defining ‘screen time’ and ‘learner well-being’
Definition of screen time: Screen time refers to time spent on screen-based media devices,
including TV and both mobile and stationary digital devices of different sizes, such as smart
phones, tablets and computers.
Definition of learner well-being: The notion of learner well-being in this paper entails both
learning outcomes (cognitive) and health outcomes (mental such as social and emotional
development and physical health).
The American Academy of Pediatrics (AAP) revised its screen time guidelines in 2016 to
recommend no use of screen media except for video-chatting for children under 18 months,
and ‘high-quality’ programming for children of 18-24 months of age and 1 hour daily screen
limit for 2 to 5 year olds, with parental co-viewing. Similarly, regarding pre-school exposure to
screens, the Canadian Paediatric Society (2017) recommends no screen time for children under
2 years old, a 1-hour daily limit for 2-5-year olds and avoiding screens for an hour before bed.
It has been pointed out that screen time guidelines are not always evidence-based, and that it is
not possible to give limits or thresholds on screen time given that the effects of screen time
depend so much on context (Viner, Davie and Firth 2019; Stiglic and Viner 2019).
There are general tendencies in the media and paediatric communities to overstate the risks of
prolonged screen time. It is important to bring to the fore what we know and do not know
about the use of digital media devices and learner wellbeing and the gaps in research and
practice we need to address.
With social distancing restricting our ability to have face-to-face interaction, for many of us,
screens are our lifelines and our window into the outside world. Both the negative and positive
effects of using screen devices need to be considered in reframing the overgeneralized and
oversimplified screen-time debate and advancing public debate and evidence-informed
policymaking on the use of screen-based digital media devices for young children and
adolescents.
4
Screen Time and Learner Well-being:
The Debate, the Evidence and Directions for Future Research and Policy
A Research Brief by UNESCO MGIEP

Approach
This paper provides a rapid scoping review of recent systematic reviews (including a review of
reviews and meta-analyses) and research studies on the effects of the use of screen-based
digital media devices on learner well-being (including learning gains). The purpose is to scope a
body of health literature on screen time, clarify definitions and conceptual boundaries of screen
time, and identify gaps in the research.
This scoping review draws primarily on a core set of 22 articles on screen time recently
published in peer-reviewed journals as its main source of information (see Appendix I). Aside
from two articles, they were all published within the last 10 years, and the majority of them
were published within the last 5 years. While the majority of these 22 studies cover North
American and European countries, they include focused studies undertaken in Australia,
Thailand, Turkey, Iran, and China.
The core set of articles includes five systematic reviews (one Review of Reviews and two metaanalyses)
which together cover 377 studies in total. The total number of participants in the 22
studies covered in the present review amounts to 3.77 million (see Appendix I). Rubrics were
designed and used to highlight analytical foci and key messages and draw key recommendations
from these articles (see Appendix II).
In addition, the paper draws on peer-reviewed literature which does not explicitly focus on
screen time but on relevant topics such as learning through different media and instructional
effectiveness of computer games. It also covers reports by international organizations that
might not have been peer reviewed, taking into account their influence in national and
international policymaking.
Methodological limitations of the current review
Due to the rapid nature of this scoping review, this paper is not based on a comprehensive
literature search but draws on a selection of studies that have explored the topic of screen time,
and only studies in English were included. Although Carson’s (2016) systematic review of
sedentary behaviour and health indicators covered 235 studies from 71 countries, most
literature reviewed for this paper focuses on data from North America and Europe (see
Appendix I), and thus generalizability of research findings and their applicability to the rest of
the world might need to be cautiously evaluated.
As a result of the prevalence of remote working and distance learning in the context of the
COVID-19 pandemic, it is speculated that averages of daily screen time have drastically
increased. For example, a newspaper reported that screen time for children doubled after the
first lockdown was introduced in India based on a survey conducted with parents of children
5
Screen Time and Learner Well-being:
The Debate, the Evidence and Directions for Future Research and Policy
A Research Brief by UNESCO MGIEP

aged 5 - 15 years. 5 Given the importance of observing social distancing measures, it may not be
practical to follow the screen time guidelines developed in the pre-COVID-19 times. This paper
however was not able to cover research on screen time in the context of COVID-19, as few
studies have been published by the time the paper was completed.
What is the current ‘state of the art’ of the knowledge on screen time?
While there is an emerging body of high-quality studies, research on screen time suffers from
conceptual, theoretical and methodological limitations that make the evidence collected so far
inadequate in terms of guiding policy. As will be discussed below in Key Insights 2 and 3, ‘screen
time’ is not a sensible construct as an object of study. Consequently, studies that take it at face
value are likely misleading because of the confounding of more important variables (Key Insight
4).
Not only is the geographic coverage of screen-time literature largely restricted to North America
and Europe, most studies are limited in terms of deriving causal relationships, as they are
correlational or associational in nature. Many studies use cross-sectional data, which is helpful
for hypothesis generation, but not suitable for hypothesis testing and for capturing the longterm
outcomes. Furthermore, most studies control and account for a limited set of background
variables, with insufficient consideration of children’s broader life context, which risks
overestimating the effect of screen time (‘positive confounding’) or observing association
between screen time and well-being outcomes when in fact there might be none.
As UNICEF’s literature review covering research conducted between 2005 and 2017 on the
impact of digital technology use on children’s well-being (Kardefelt-Winther 2017) has pointed
out, research in this area tends to focus on screen harm and the hypothetical idea of addiction
to technology, rather than investigating why some children spend more time on screen-based
media devices than others and when more screen time under what conditions might have an
effect—positively or negatively—on their well-being.
Perhaps more fundamentally, not only is there insufficient evidence base to determine when
screen time becomes excessive, determining ‘excessive use’ itself depends on the context in
which screen-based media devices are used and is shaped by what is perceived to be ‘normal’
or ‘moderate’ use of such devices. Furthermore, in addition to generational differences on what
is considered ‘normal’ use, views and opinions on ‘how much screen time is too much’ and
‘which use is appropriate’ will change over time and according to changing contexts. In this
respect, it is telling that WHO supported video games as a healthy means of physical distancing
5
COVID-19 Impact: Screen time up by 100% for children, 15 June 2020, The Economic Times
https://economictimes.indiatimes.com/industry/services/education/covid-19-impact-screen-time-up-by-100-forchildren/articleshow/76383951.cms?from=mdr
6
Screen Time and Learner Well-being:
The Debate, the Evidence and Directions for Future Research and Policy
A Research Brief by UNESCO MGIEP

and social connection in the COVID-19 context, while it added “gaming disorder” as a
classification in alongside others related to addictive behaviour. 6
“…not only is there insufficient evidence base to determine when screen time
becomes excessive, determining ‘excessive use’ itself depends on the context
in which screen-based media devices are used and is shaped by what is
perceived to be ‘normal’ or ‘moderate’ use of such devices.
Key insights and recommendations from the review
This section presents key insights that we highlight from the literature review, followed by some
key recommendations. The key recommendations are a combination of recommendations
emerging directly from the literature and recommendations we propose based on the key
insights.
Key Insights
1. Digital technology will continue to grow and advance and its use in education will continue
to increase.
The advances made in digital technology over the past two decades within the educational
sector have been phenomenal, including the development and use of artificial intelligence.
There is no doubt that digital technology will have significant impacts on the lives of the current
and future generations and its use in education will continue to increase. The recent COVID-19
pandemic has given a renewed significance to digital learning tools.
6
The WHO is recommending video games as an effective way to stop the spread of COVID-19, one year after adding 'gaming
disorder' to its list of addictive behaviours, 2 April 2020, Business Insider Australia,.
https://www.businessinsider.com.au/who-video-games-coronavirus-pandemic-mental-health-disorder-2020-4?r=US&IR=T;
Gaming fosters social connection at a time of physical distance, 14 April 2020, The Conversation,
https://theconversation.com/gaming-fosters-social-connection-at-a-time-of-physical-distance-135809
7
Screen Time and Learner Well-being:
The Debate, the Evidence and Directions for Future Research and Policy
A Research Brief by UNESCO MGIEP

Figure 3: Increase in use of internet by school going children Source: Adopted from OECD (2018), p.6,
In 2017, more than 98% of homes in the United States (US) with young children had a mobilescreen
device, as compared to 52% six years earlier; similar trends have been observed in
France, Australia and in many parts of Asia (Straker et al. 2018; Rideout 2017). The use of
internet by school going children is rapidly increasing year by year (see Figure 3), and young
children and adolescents are using digital media at ever-increasing rates. For instance, in 2016,
about 75% of teenagers in the US owned a smartphone and 76% were connected to at least one
social media site (AAP 2016).
Adapting to the increased use of digital devices at home, at school, at work and in society at
large will certainly require changes not only in parenting but also in how education and learning
are organized. The current situation is rather uncommon as children are often more
comfortable in using digital devices and applications than adults. To foster constructive
dialogues around screen time, especially in the current context of social distancing, it is crucial
to listen to and take into account children’s voices.
2. A high level of policy incoherence exists between the health and education sectors on the
impacts of screen time
Education authorities encourage the use of digital technology by children to prepare them for
the digital world, although it is not uncontested within the education sector itself. 7 In contrast,
health authorities discourage young children from using these devices based on concerns for
7
For example, in China, the Ministry of Education in 2018 together with seven other government departments launched an action
plan to address the problem of nearsightedness in primary and secondary school students. This plan forbids students from bringing
electronic devices to class, and requests teachers not to depend on electronic devices in teaching and giving homework (Ministry
of Education of the People’s Republic of China 2018). The Republic of Korea announced its intention of going fully digital in school
education, but in spite of a well-planned schedule put forward in the 1990s, Korea held back its plan to roll out the fully digital
learning environment. Reasons for postponing the plan included the harmful effects of students’ overexposure to digital devices
(Harlan 2012, as cited by Smart and Jagannathan 2018, p.59).
8
Screen Time and Learner Well-being:
The Debate, the Evidence and Directions for Future Research and Policy
A Research Brief by UNESCO MGIEP

their cognitive, emotional and social wellbeing (Straker et al. 2018). This has led to policy
incoherence between education and health guidelines and recommendations regarding
children’s use of digital technology.
Health officials and professionals often seek to minimize screen time with an assumption that
screen time is sedentary, passive and displacing beneficial activities that are important for wellbeing
outcomes. On the other hand, digital education guidelines often look at active screen time
that involves interactive activities linked to learning outcomes.
Given the digital imperative especially in the face of COVID-19, there is a need for cross-sector
coordination and alignment of different goals and preoccupations of different sectors, with the
notion of learner well-being at the heart of the screen time debate. Caution must be exercised
when interpreting research on the negative effects of screen time as well as the positive effects
of digital learning.
More evidence disentangling prolonged screen time from other factors affecting health and
educational outcomes in young children and adolescents is clearly required. It is however
important to note that a whole child approach emphasizing the sensible balance across good
sleep, face-to-face social interaction, digital use, and physical exercises should remain a core
component of recommendations for promoting learner well-being.
3. Quality Content is more important than screen time. Many studies do not distinguish
between the entertainment use of screen-based media devices (primarily television
viewing time) and educational use of digital media devices such as computers, game
consoles and smart phones.
Traditionally, studies on screen time have focused on television, and many studies do not make a
distinction between time spent on watching TV for pure entertainment and time spent on
education related content. The same observation is valid for mobile digital screen devices for
education such as computers, game consoles and smart phones versus these being used for
entertainment. Given the elusive notion of ‘screen time’, one of the problems is overgeneralization
of harmful effects of screen time without taking into account the enormously
diverse use of screen-based media devices.
The term ‘screen time’ is itself misleading and overly simplistic. Distinguishing between passively
absorbing what is on the screen and actively engaging with it is critical to understanding the
overall impacts of screen time. For example, a seminal 3-year ethnographic investigation of
informal learning through digital media use following over 800 youth in the US (Ito et al. 2009)
identified three major ways they engage actively with digital technology and captured them in
what came to be known as HOMAGO (Hanging Out, Messing Around, Geeking Out) framework
(see Box 2).
Box 2: HOMAGO framework on digital media and learning
HOMAGO is a concept that emerged out of the findings of the Digital Youth Project, a 3-year
ethnographic investigation of informal learning of over 800 youth in the US, funded by
MacArthur Foundation as part of the Digital Media and Learning Initiative (Ito et al. 2009).
HOMAGO refers to:
9
Screen Time and Learner Well-being:
The Debate, the Evidence and Directions for Future Research and Policy
A Research Brief by UNESCO MGIEP

• Hanging out (friendship-driven, primarily social media);
• Messing around (more intensive engagement with digital media and technology, e.g.
searching for information online, gaming, digital media production); and
• Geeking out (interest-driven learning, learning how to navigate specialized domains of
knowledge and practice and participating in online communities).
In screen time research, the non-differentiation across television and digital devices screen time
is problematic (Straker et al. 2018). For example, in a study focusing on 6-15 year-old children in
the US, a negative association was found between physical and functional strength and television
viewing but not with computer or video game use (Edelson et al. 2016; van den Heuvel et al. 2019;
Christakis et al. 2009). These results demonstrate a need for a deeper and more nuanced
understanding of screen time.
Literature on screen time and impacts has tended to focus on health outcomes and primarily with
screen time associated with entertainment use. For example, a meta-analysis on screen time and
Attention Deficit Hyperactivity Disorder (ADHD) symptoms found that television viewing or
gaming among children of 4–17 years of age was modestly associated with later ADHD symptoms
(Nikkelen et al. 2014, Tanama et.al 2019, Christakis et.al 2004). However, there have an equal
number of studies which have questioned the validity of many of these studies and have
demonstrated that no correlation has been found between screen time and ADHD (McBee et.al
2021, Camerer et.al 2018, Foster et.al 2010, Huber et.al 2018, Kostyrka-Allchorne et.al 2017)
Relationship between screen time and cognitive outcomes has been less investigated. According
to Anderson and Subrahmanyam (2017), studies show that for children less than 2 years, TV has
negative impacts on language and executive functions, while for preschool children it is found to
have both positive and negative outcomes. A large pool of research shows that educational TV
programs could have positive impact on cognitive development, with examples such as Sesame
Street. Beyond preschool, research tends to look at only entertainment program consumption
and therefore cognitive outcomes have not been well explored.
4. The cognitive, health and socio-emotional outcomes are influenced by the age and other
individual characteristics of users as well as the content and the context of media device
use.
There are studies that report negative impacts of screen time on cognitive development such as
language learning (see Key Insight 3), but there are also many studies that show positive or null
associations (Drummond and Sauer 2014; Regondola and Barbado 2017). A recent meta-analysis
of studies on the association between screen media use and academic performance among young
children and adolescents found no association between the two (Adelantado-Renau et al. 2019).
This could be partially the result of several aspects of the overall screen media time measure that
are not captured.
Different studies give support to impact of screen time on children’s wellbeing based on different
hypotheses of the potential relationship (see Box 3).
Box 3: Four hypotheses of the impact of screen time on children’s well-being
10
Screen Time and Learner Well-being:
The Debate, the Evidence and Directions for Future Research and Policy
A Research Brief by UNESCO MGIEP

UNICEF’s literature review on the impact of digital technology on children’s well-being
identified four main hypotheses explored in research on digital technology use and user wellbeing
(Kardefelt Winther 2017). This typology is useful in terms of examining research on the
impact of screen time on learner well-being.
1. The displacement hypothesis suggests that screen time is replacing or displacing
opportunities for positive activities such as face-to-face interaction, exercise, sleep
which are important for well-being.
2. The rich-get-richer hypothesis suggests that those who already have strong in-person
social networks and social skills will benefit more from digital media use in terms of
social interaction than those who have weaker social connections.
3. The social compensation hypothesis suggests that digital media use will be beneficial
to those who are socially anxious and isolated as it compensates for lacked social skills
and allows them to feel more at ease in interacting with others.
4. The stimulation hypothesis suggests that digital media use stimulates communication
with existing friends, leading to mostly positive outcomes.
We must keep in mind that both positive and negative outcomes of screen time tend to be highly
contextual and dependent on the design of activities children engage in through screen devices.
A 2015 study on cognition and media concludes that there is no clear consensus and that effects
likely depend on the age, type of content and other contextual factors (Anderson and Kirkorian
2015). Focusing on screen time without adequately considering the internal and external
attributes may severely limit the value of the conclusions drawn.
The lack of association between screen media use and well-being outcomes, as well as the lack of
agreement among studies, could be partially attributed to the measure of screen time which fail
to take into account: (i) internal attributes of children that include: (a) age of children; and (b)
gender; and (ii) external attributes such as (a) purpose and content of programming (e.g.
educational versus entertainment); (b) the context in which young children and adolescents use
screen media; and (c) active versus passive media (e.g. interactive media versus the older oneway
media). As illustrated below, there is an ostensibly contradictory body of evidence on the
associations between these factors and well-being outcomes.
Internal Attributes:
Age of children: For children less than 2 years, TV has negative impacts on language and executive
functions. In preschool children it is found to have both positive and negative outcomes. A 2020
meta-analysis study found positive association across screen use and stronger language skills for
older children (Madigan et al. 2020). However, children (average age 12) who watch mainly
entertainment programs tend to have reduced reading achievements and executive functions like
focus and attention regulation (Ibid.).
Gender: A meta-analysis on media use and ADHD-related behaviours in young children and
adolescents found no significant interactions between screen time and gender (Nikkelen et al.
2014). According to the evidence-focused literature review by Kardefelt Winther (2017) for
11
Screen Time and Learner Well-being:
The Debate, the Evidence and Directions for Future Research and Policy
A Research Brief by UNESCO MGIEP

UNICEF, few significant gender differences were found in relation to the impact of children’s
digital technology use on their mental well-being.
However, more recently, studies looking at newer uses of digital screen devices such as social
media showed gendered impact of screen time on mental health outcomes. One study that has
received much media attention suggested that adolescents were 13% more likely to experience
high levels of depression symptoms if they used social media at least once per day, and 34% more
likely to have at least one “suicide-related outcome” 8 if they used an electronic device three or
more hours per day, compared to two or fewer hours per day (Twenge et al. 2018). The
correlation between time spent on social media and depression symptoms was only evident for
female participants. Also important to note is that the time spent on social media was only related
to higher depression symptoms for adolescents who did not engage much in face-to-face
socializing. This would seem to be aligned with the “rich get richer” hypothesis elaborated in Box3.
External Attributes
Content: A recent systematic review and meta-analysis of associations between screen use and
child language skills found that ‘better-quality’ screen use (defined by ‘educational programs’ and
‘co-viewing’) was correlated with stronger child language skills (Madigan et al. 2020), which
suggests that content (as well as the social context of viewing—see below) does matter in
improving learning outcomes. One of the studies reviewed by Anderson and Subrahmanyam
(2017), albeit a small-scale experiment involving a group of 18 children and a comparison group
of 11 children (4 years of age), revealed after 3 months a literacy skill gain of 11 standard score
points for the experimental group exposed to educational software while only 4 points for the
comparison group exposed to entertainment software and a mathematics skill gain of 8 points
for the education group while only 1 point for the entertainment group.
“…content (as well as the social context of viewing) does matter in
improving learning outcomes.
There is an ongoing effort to demonstrate educational benefits of computer games, in addition
to visionary work by pioneers who highlighted the potential of gaming to revolutionize education
such as Paul Gee (2007) and Jane McGonical (2011). For example, a recent report highlighted that
more than a third of 4,626 respondents (ages 11-16) reported that playing games made them
better readers (Picton et al. 2020). A cross-sectional study based on data from the School Children
Mental Health Europe project conducted in six European Union countries (youth ages 6–11, n =
3,195) found video gaming beneficial for cognitive functioning (Kovess-Masfety et al. 2017). A
recent review of experimental studies of instructional effectiveness of computer games found
that games can increase student learning of academic material in science, mathematics and
second-language learning (Mayer 2019; see Table 1). These results indicate that content and
pedagogy play an important role in ensuring screen time be maximised for learning outcomes.
8
Suicide-related outcomes include a) significant sadness or hopelessness; b) seriously considering suicide; c) having a suicide
plan; and d) making a suicide attempt.
12
Screen Time and Learner Well-being:
The Debate, the Evidence and Directions for Future Research and Policy
A Research Brief by UNESCO MGIEP

Table 1: Effect of computer games on cognitive skills
Discipline Experiments in which effects were observed Effect size
Science 12 out of 16 experiments 0.7
Mathematics 4 out of 6 experiments 0.5
Language 4 out of 5 experiments 1.0
Source: Adopted from Mayer 2019, Table 4.
Note: An effect size greater than 0.4 is considered significant.
Social context of viewing: A 2019 study showed how increased TV viewing was associated with
language delays in early childhood (Madigan et al. 2019). However, one study observed that this
could be attributed to the reduced child-parent interaction and play which is critical for early
development (Christakis et al. 2009). A 2017 national study by Common Sense Media covering a
representative sample of over 1,400 parents across the US revealed that on average 46% of
children under 2 years of age had used a mobile media device at least once, but the average time
spent watching TV or videos on a mobile device amounted only to five minutes per day (Rideout
2017). In another study, with a sample size of 350 children from low-income urban population in
the US, it was found that 96.6% of children were found to use mobile devices (Kabali et.al 2015).
The same study reported that 70% of parents were giving children devices to keep them occupied
while doing household chores while 65% used these devices to keep the children calm. These
findings might suggest that increased screen time on mobile devices by young children can be
linked to reduced time interacting with parents and negative well-being outcomes (see below).
Active vs passive: Studies which have shown language impairments caused by increased screen
time and in particular to children below the age of two have primarily used television screen
time—a passive one way process—as the key explanatory variable. However, studies which
looked at computers and other educational digital media—an active two way interactive
process—found mixed effects on cognition.
As Kardefelt-Winther (2017) summarizes in UNICEF’s literature review on the impact of digital
technology use on children’s well-being, many studies show the use of digital media devices
brings benefits to children, by opening new opportunities for social interaction and active creative
expression. This points to the benefits of active screen time, but not all active screen time may
lead to positive outcomes; content and educational outcomes are key if digital devices are to be
beneficial for wellbeing.
Computer games with content developed with educational outcomes as the objective can provide
promising examples of active screen time. While there is an emerging body of literature that
suggests computer games can be as effective as or more effective than conventional media for
particular instructional domains, more research is needed in which the control group is exposed
to exactly the same academic material as the game group (Mayer 2019). It is important to keep
in mind that positive education outcomes of active screen time are highly contextual and depend
on the design of digital games and other activities children can engage in through screen devices
(see Schrier 2018 for discussion of the use and design of game-based learning).
13
Screen Time and Learner Well-being:
The Debate, the Evidence and Directions for Future Research and Policy
A Research Brief by UNESCO MGIEP

Key Recommendations
1. Addressing the holistic development and wellbeing of the whole child
Policy should address the holistic development and wellbeing of the whole child and support
informed decision making by parents, caregivers and professionals. This requires a reexamination
of the diverse perspectives derived from health and education literature, with a view
to provide consistent, neutral and evidence-informed messages to parents and school
administrators (Straker et al. 2018). Many of the apparent connections between screen time and
screen harm may be mediated by lost opportunities for positive activities (socialising, exercise,
sleep) due to displacement by screen time. 9
Recommendations addressing the holistic development and wellbeing of the whole child include
the following:
a. Screen time guidelines should address the importance of adequate physical activity,
healthy nutrition, good sleep hygiene, and nurturing social environment in promoting
children’s well-being outcomes. These factors would contribute together with
activities related to screen time to produce overall health effects (Ashton and Beattie
2019). Positive activities such as socializing and physical exercise can also be
conducted via screen devices, for example through the use of social media, playing
active video games, or taking online exercise classes. 10 Careful attention also needs to
be paid to areas where screen time seems to have direct negative impact on physical
health. Obesity and myopia (near-sightedness), which were already major public
health concerns prior to the COVID-19 pandemic, are cases in point. For example, the
increase in the consumption of high-density foods while using screen media appears
to be related to being distracted from feelings of satiety or fullness (Robinson et al.
2017). While current evidence is not conclusive, increased digital screen time appears
to be associated with myopia onset and progression in children (Wai WONG et al.
2020).
b. Interventions on screen-based media use should include curtailed use within an hour
before bedtime and particularly in darkness. Parents, teachers, health professionals
and adolescents should be made aware of the associations between night-time
screen-based media devise use (including TV watching) and sleep outcomes, as these
may impact on cognitive function and educational attainment (Mireku et al. 2019).
c. Health and education professionals as well as parents and caregivers should encourage
screen-based activities that are beneficial to individual children based on their
developmental stages and individual characteristics and needs, rather than
categorically limiting screen time. Children can benefit from spending time in the
9
Kardefelt Winther’s (2017) literature review found little support for the displacement hypothesis, when it is understood as a
hypothesis that screen harm is proportional to exposure (also see Box 2).
10
In the midst of the COVID-19 pandemic, WHO tweeted that active video games and online exercise classes can be means to
stay active and healthy at home. See https://twitter.com/WHO/status/1242738384772239360?s=20
14
Screen Time and Learner Well-being:
The Debate, the Evidence and Directions for Future Research and Policy
A Research Brief by UNESCO MGIEP

digital space. For digital natives whose identity, existence, and reality are almost
unimaginable without digital devices, a forced reduction in screen time may lead to
curtailment of positive activities such as interacting with friends during school closures
or engaging in creative play that are important for their well-being. Instead, focus on
finding a menu of different activities with children that they like to do, or guide them
to make choices as to how they spend their time online or otherwise. If there are
underlying problems which prompt excessive screen time, it is critical to address those
problems rather than imposing a reduction in screen time.
2. Improving the quality of screen-based activities
Research shows that the quality of the content and for parents or caregivers to be there to help
children process what is on screen are important factors that can lead to positive well-being
outcomes, especially for young children.
a. Policy should support the development of high-quality educational content for digital
devices. For example, there is evidence to support a hybrid form of learning, such as
the introduction of touch-screen devices while reading traditional books in early
childhood education (Anderson and Subrahmanyam 2017). However, clear
information on appropriate digital technology use for educational purposes is still
limited.
b. Parents are encouraged to participate in screen time activities for children from early
childhood to at least the early years in school. Online interaction is a valid form of
interaction, and positive relationships can be formed and encouraged online.
However, for children to develop the skills and resilience to cope with the world,
they need regular interaction in the physical world. This is especially true for young
children who need regular offline play and interaction with other people. Family
involvement can play an important role in having children engage with technology in
positive ways to ensure development process of children growing up in a digital age
(Madigan et al. 2019). Parental involvement is also important in terms of facilitating
home-based learning during school closures and also at normal times. Authorities
should consider measures to enable parents to make a living and take care of and
educate their children during lockdowns, such as reduced work hours for the same
wages and online support to parents.
3. Encouraging further research and strengthening research-policy-practice nexus
Given the rapid increase in the use of digital screen devices by young children and adolescents
internationally, notably for new content areas such as social media, there is a need for more and
better research as well as for strengthening the research-policy-practice nexus. The following
recommendations are suggested to strengthen the literature to guide policymaking in the use of
digital media.
15
Screen Time and Learner Well-being:
The Debate, the Evidence and Directions for Future Research and Policy
A Research Brief by UNESCO MGIEP

a. Promote further research to disaggregate the notion of ‘screen time’ and deepen the
understanding of the impact of the contexts and content of digital devices on learner
well-being, particularly in relationship to mobile digital devices. With its reliance on
self-reporting of the total daily or weekly time spent on screen and the ensuing low
quality of measurement available in current data sources, there is limited high-quality
(robust and transparent) evidence for harmful impacts of screen time. Aggregate
measures of ‘screen time’ are conceptually problematic and need to be reconsidered,
as they ignore the different screen devices used by children and how they engage with
what is on the screen. This might lead to ending the use of the construct ‘screen time’,
except in the restricted sense of its impact on vision or sleep quality.
b. Conduct a long-term follow up while controlling for confounding variables, and produce
longitudinal data to gain a better understanding of screen time and its positive and
negative impacts (Ashton and Beattie 2019; Straker et al. 2018; Anderson and
Subrahmanyam 2017). Little is known about the cumulative effects of spending much
time on digital screen media from a young age, and it is particularly important to study
the long-term consequences of digital media use. This requires more longitudinal
studies for confirmatory (hypothesis-testing) research. It also requires including more
control variables so as not to exclude variables that have established effects on wellbeing
outcomes. Fully taking into consideration that children’s experiences with
screen media cannot be studied in vacuum in isolation from their life contexts,
researchers should tighten research design to control and account for sociodemographic
and other variables and increase the likelihood of having true (unconfounded)
results. 11 At the same time, it is important to be mindful that the rapid
evolution of digital technology is still ongoing and even accelerating, and that there is
a risk that longitudinal studies become obsolete by the time they conclude due to
dramatic changes in the context of media use. One cannot easily gather evidence of
long-term effects when the constructs keep changing as the research is conducted.
c. Support research studies by a team of multi-disciplinary experts and where possible
multi-stakeholder groups to provide a more holistic understanding of the multidimensional
impacts that might emerge from digital media use by young children and
adolescents. Not only quantitative studies but also qualitative studies should be
encouraged, as qualitative data can generate more nuanced and context-specific
insights based on children’s voices, which in turn can contribute to generating
hypotheses and building theories along with cross-sectional studies. Multi-disciplinary
collaboration and close partnerships between health and education ministries, schools
and parents are necessary to strengthen the research-policy-practice nexus.
11
Kardefelt-Winther (2017) also recommends strengthening reproducibility of research and the reliability of findings by
encouraging researchers to register their hypotheses prior to data collection and then share the raw data and analysis code
with each publication, following an ‘Open Science’ approach (for example through the Open Science framework—see
https://osf.io/ ).
16
Screen Time and Learner Well-being:
The Debate, the Evidence and Directions for Future Research and Policy
A Research Brief by UNESCO MGIEP

Conclusion
Time spent on screens—from social media to computers and television—is a major part of
everyday life and a necessary part of education today and into the foreseeable future. One of the
problems is over-generalization of harmful effects of screen time without taking into account the
enormously diverse use of screen-based media devices. Different uses have different effects. On
the same media platform (for example on YouTube and/or Instagram), different content will have
different effects. Furthermore, the same content could have different effects on different people
or on the same person in different time frames or in different environments or under different
conditions of usage. Technology is used in varied ways, with wide-ranging motivations, to access
an enormous amount of diverse content. Certain uses affect certain people in a negative way,
while certain uses affect certain people in a positive way.
The risks from screen exposure should not be overstated. The evidence is relatively weak overall,
and the magnitude of impact of screens is small on key health outcomes. The existing screen time
guidelines tend to focus on risks, without recognizing the potential benefits of digital screen use
in education. Currently the literature takes little account of the increasing demands for homework
to be undertaken on computers nor the needs for school lessons to be delivered online, although
these will likely be taken up as important research topics given the COVID-19.
Collaboration across the health and education sectors, inter-disciplinary research, and schoolfamily
partnerships will be the key to advancing policy and practice around screen time in a digital
age. Another key point we must take into consideration is the role of the younger generation.
We now know for sure that the Generation Z, Millennials and to a smaller extent Generation X
are all primarily digital natives. They thrive in the digital world and therefore any policy referring
to use of digital media must involve the voices of youth and their concerns and wants in the wideranging
use of digital technology in their lives—for entertainment, socialising, learning and more.
“Collaboration across the health and education sectors, inter-disciplinary
research, and school-family partnerships will be the key to advancing policy
and practice around screen time in a digital age.
Acknowledgements and Disclaimer
We would like to thank Karen (Kat) Schrier and John Sabatini for their insightful comments on an
earlier version of this research brief. We also thank Kriti Singh for finding post-2020 data on
digital device use.
The analysis, conclusions, and recommendations contained in this paper are solely a product of
the individual authors and are not the policy or opinions of, nor do they represent an
endorsement by UNESCO or UNESCO MGIEP.
17
Screen Time and Learner Well-being:
The Debate, the Evidence and Directions for Future Research and Policy
A Research Brief by UNESCO MGIEP

Bibliography
AAP (American Association of Pediatrics) Council on Communications and Media (2016) ‘Media use in schoolaged
children and adolescents’, Pediatrics, 138(5), e2016259.
Abramson, M.J., Benke, G.P., Dimitriadis, C., Inyang, I.O. and Sim, M.R. (2009) ‘Mobile telephone use is
associated with changes in cognitive function in young adolescents’, Bioelectromagnetics, 30, pp. 678-686.
Adelantado-Renau, M., Urdiales, D.M., Redonodo, I.C., Valls, M.R.B., Vizcaino, V.M. and Bueno, C.A. (2019)
‘Association between screen media use and academic performance among children and adolescents: a
systematic review and meta-analysis’, JAMA Pediatrics, 173(11), pp. 1058–67.
Anderson, D.R. and Kirkorian, H.L. (2015) ‘Media and cognitive development’, in Liben, L.S., Müller, U. and
Lerner, R.M. (eds.) Handbook of child psychology and developmental science - Cognitive processes. John Wiley
& Sons Inc., pp. 949–994.
Anderson, D.R. and Subrahmanyam, K. (on behalf of the Cognitive Impacts of Digital Media Workgroup)
(2017) ‘Digital screen media and cognitive development’, Pediatrics (Official Journal of the American Academy
of Pediatrics), 140 (Supplement 2), pp. S57-S61. doi: 10.1542/peds.2016-1758C.
Ashton, J.J. and Beattie, R.M. (2019) ‘Screen time in children and adolescents: is there evidence to guide parents
and policy?’, Lancet Child Adolescent Health, 3(5), pp. 292-294. doi: 10.1016/S2352-4642(19)30062-8.
Bowers, A.J. and Matthew, B. (2013) ‘Does recreational computer use affect high school achievement?’,
Educational Technology Research & Development, 61(1), pp. 51-69. doi:10.1007/s11423-012-9274-1.
Camerer, C. F., Dreber, A., Holzmeister, F., Ho, T.-H., Huber, J., Johannesson, M., Kirchler, M., Nave, G., Nosek,
B. A., Pfeiffer, T., Altmejd, A., Buttrick, N., Chan, T., Chen, Y., Forsell, E., Gampa, A., Heikensten, E., Hummer,
L., Imai, T., . . . Wu, H. (2018). Evaluating the replicability of social science experiments in Nature and Science
between 2010 and 2015. Nature Human Behaviour, 2, 637–644. https:// doi.org/10.1038/s41562-018-0399-z
Canadian Paediatric Society, Digital Health Task Force (2017) ‘Screen time and young children: promoting
health and development in a digital world’, Paediatrics and Child Health, 22(8), pp. 461-468.
Canadian Paediatric Society, Digital Health Task Force (2019) ‘Digital media: promoting healthy screen use in
school-aged children and adolescents’, Paediatrics and Child Health, 24(6), pp. 402–408.
doi: 10.1093/pch/pxz095
Carson V, Hunter S, Kuzik N, et al. (2016) ‘Systematic review of sedentary behaviour and health indicators in
school-aged children and youth: an update’, Applied Physiology, Nutrition, and Metabolism, 41(6 Suppl 3): pp.
S240-S265. doi:10.1139/apnm-2015-0630.
Carter, B., Rees, P., Hale, L., Bhattacharjee, D. and Paradkar, M.S. (2016) ‘Association between portable
screen-based media device access or use and sleep outcomes: a systematic review and meta-analysis’, JAMA
Pediatrics 170(12), pp. 1202-1208.
18
Screen Time and Learner Well-being:
The Debate, the Evidence and Directions for Future Research and Policy
A Research Brief by UNESCO MGIEP

Christakis, D.A., Gilkerson J., Richards J.A., Zimmerman, F.J., Garrison, M.M., Xu, D., Gray, S. and Yapanel, U.
(2009) ‘Audible television and decreased adult words, infant vocalizations, and conversational turns: a
population-based study’, Archives of Pediatrics & Adolescent Medicin, 163(6), pp. 554-558.
Cristia, A. and Seidl A. (2015) ‘Parental reports on touch screen use in early childhood’, PLoS One, 10(6),
e0128338. doi: 10.1371/journal.pone.0128338.
Drummond, A. and Sauer, J.D. (2014) ‘Video-games do not negatively impact adolescent academic performance
in science, mathematics or reading’, PLoS ONE 9(4), e87943.
Edelson, L.R., Mathias, K.C., Fulgoni, V.L. 3 rd and Karagounis, L.G. (2016) ‘Screen-based sedentary behavior and
associations with functional strength in 6–15 year-old children in the United States’, BMC Public Health,16,
Article 116. doi: 10.1186/s12889-016-2791-9.
Esmaeilzadeh, S. and Kalantari, H. (2013) ‘Physical fitness, physical activity, sedentary behavior and academic
performance among adolescent boys in different weight statuses’, Mediterranean Journal of Nutrition and
Metabolism, 6, pp. 207–216. doi: 10.1007/s12349-013-0133-3.
Foerster, M. and Rsli, M. (2017) ‘A latent class analysis on adolescents media use and associations with health
related quality of life’, Computers in Human Behavior, 71, pp. 266-274. doi: 10.1016/j.chb.2017.02.015.
Foster, E. M., & Watkins, S. (2010). The value of reanalysis: TV viewing and attention problems. Child
Development, 81(1), 368–375. https://doi.org/10.1111/j.1467-8624 .2009.01400.x
Gee, J.P. (2007) Good video games and good learning. New York: Peter Lang.
GlobalWebIndex (GWI). (2020). Coronavirus Research | March 2020 Series 3: Multi-market research. Retrieved
from:https://www.globalwebindex.com/hubfs/1.%20Coronavirus%20Research%20PDFs/GWI%20coronavirus
%20findings%20March%202020%20-%20Multi-Market%20data%20(Release%203).pdf
Hale L. and Guan S. (2015) ‘Screen time and sleep among school-aged children and adolescents: a systematic
literature review’, Sleep Medicine Reviews, 21, pp. 50-58. doi:10.1016/j.smrv.2014.07.007.
Huber, B., Yeates, M., Meyer, D., Fleckhammer, L., & Kaufman, J. (2018). The effects of screen media content
on young children’s executive functioning. Journal of Experimental Child Psychology, 170, 72–85. https://doi
.org/10.1016/j.jecp.2018.01.006
International Telecommunication Union (ITU). (2020). Measuring Digital Development: Facts and Figures 2020.
Retrieved from: https://www.itu.int/en/ITU-D/Statistics/Pages/facts/default.aspx
Ito, M., Baumer, S., Bittanti, M., boyd, d., Cody, R., Herr Stephenson, B., Horst, H.A., Lange, P.G., Mahendran,
D., Martínez, K.Z., Pascoe, C.J., Perkel, D., Robinson, L., Sims, C. and Tripp, L. (2009) Hanging Out, Messing
Around, and Geeking Out: kids living and learning with new media. Cambridge, Massachusetts: MIT Press.
Jackson, L.A., von Eye, A., Fitzgerald, H.E., Witt, E.A. and Zhao, Y. (2011) ‘Internet use, videogame playing and
cell phone use as predictors of children’s body mass index (BMI), body weight, academic performance, and
social and overall self-esteem’, Computers in Human Behavior, 27 (1), pp. 599-604. doi:
10.1016/j.chb.2010.10.019.
19
Screen Time and Learner Well-being:
The Debate, the Evidence and Directions for Future Research and Policy
A Research Brief by UNESCO MGIEP

Kabali, H.K., Irigoyen, M.M., Nunez-Davis, R., Budacki, J.G., Mohanty, S.H., Leister, K.P. and Bonner, R.L. (2015)
‘Exposure and use of mobile media devices by young children’, Pediatrics, 136(6), pp. 1044–1050.
doi: 10.1542/peds.2015-2151.
Kardefelt-Winther, D. (2017) How does the time children spend using digital technology impact their mental
well-being, social relationships and physical activity? An evidence-focused literature review. Innocenti
Discussion Paper no. 2017-02. Florence: UNICEF Office of Research - Innocenti. Available at:
https://www.unicef-irc.org/publications/925-how-does-the-time-children-spend-using-digital-technologyimpact-their-mental-well.html
Kiatrungrit, K. and Hongsanguansri, S. (2014) ‘Cross-sectional study of use of electronic media by secondary
school students in Bangkok, Thailand’, Shanghai Archives of Psychiatry, 26(4), pp. 216–226. doi:
10.3969/j.issn.1002-0829.2014.04.005.
Kostyrka-Allchorne, K., Cooper, N. R., & Simpson, A. (2017). The relationship between television exposure and
chil- dren’s cognition and behavior: A systematic review. Developmental Review, 44, 19–58. https://doi.org/10
.1016/j.dr.2016.12.002
Kovess-Masfety, V., Keyes, K., Hamilton, A., Hanson, G., Bitfoi, A., Golitz, D., Koç, C., Kuijpers, R., Lesinskiene,
S., Mihova, Z., Otten, R., Fermanian, C. and Pez, O. (2016) ‘Is time spent playing video games associated with
mental health, cognitive and social skills in young children?’, Social Psychiatry and Psychiatric Epidemiology,
51(3), pp. 349–357. doi: 10.1007/s00127-016-1179-6.
Li S, Jin X, Wu S, Jiang F, Yan C, Shen X. (2007) ‘The impact of media use on sleep patterns and sleep disorders
among school-aged children in China’, Sleep, 30(3), pp. 361-367. doi:10.1093/sleep/30.3.361.
Madigan, S., Browne, D., Racine, N., Mori, C. and Tough, S. (2019) ‘Association between screen time and
children’s performance on a developmental screening test’, JAMA Pediatrics, 173(3), pp. 244-250. doi:
10.1001/jamapediatrics.2018.5056.
Madigan, S., McArthur, B.A., Anhorn, C., Eirich, R., Christakis, D.A. (2020) ‘Associations between screen use
and child language skills: a systematic review and meta-analysis. JAMA Pediatrics, 174(7), pp. 665-675. doi:
10.1001/jamapediatrics.2020.0327.
Mayer, R. (2019) ‘Computer games in education’, Annual Review of Psychology, 70, pp 531–49.
McBee,M.T., Brand,R.J. and Dixon,W.E., (2021). ‘Challenging the Link Between Early Childhood Television
Exposure and Later Attention Problems: A Multiverse Approach’, Psychological Science. 1-23. DOI:
10.1177/0956797620971650.
McGonigal, J. (2011) Reality is broken: why games make us better and how they can change the world. New
York: Penguin Press.
Ministry of Education of the People’s Republic of China (2018) Implementation plan on prevention and control
of near-sightedness in students in primary and secondary school. Beijing, China: People’s Education Press.
20
Screen Time and Learner Well-being:
The Debate, the Evidence and Directions for Future Research and Policy
A Research Brief by UNESCO MGIEP

Mireku, M.O., Barker, M.M., Mutz, J., Dumontheil, I., Thomas, M.S.C., Röösli, M., Elliott, P. and Toledano, M.B.
(2019) ‘Night-time screen-based media device use and adolescents' sleep and health related quality of life’,
Environment International, 124, pp 66–78. doi: 10.1016/j.envint.2018.11.069.
Muñoz-Miralles, R., Ortega-González, R., López-Morón, M.R., et al. (2016) ‘The problematic use of Information
and Communication Technologies (ICT) in adolescents by the cross sectional JOITIC study’, BMC Pediatrics,
16(1), Article 140. doi:10.1186/s12887-016-0674-y.
Nikkelen, S.W.C., Valkenburg, P.M., Huizinga, M. and Bushman, B. (2014) ‘Media use and ADHD-related
behaviors in children and adolescents: a meta-analysis’, Developmental Psychology, 50(9), pp. 2228–2241.
OECD (2018) Children and young people’s mental health in the digital age: shaping the future. Available at:
https://www.oecd.org/els/health-systems/Children-and-Young-People-Mental-Health-in-the-Digital-Age.pdf
Orben, A. and Przybylski, A.K. (2019a) ‘The association between adolescent well-being and digital technology
use’, Nature Human Behaviour, 3, pp. 173–182. doi: 10.1038/s41562-018-0506-1.
Orben, A. and Przybylski, A.K. (2019b) ‘Screens, teens, and psychological well-being: evidence from three
time-use-diary studies’, Psychological Science, 30(5), pp. 682-696. doi: 10.1177/0956797619830329.
Ozmert EN, Ince T, Pektas A, Ozdemir R, Uckardes Y. (2011) ‘Behavioral correlates of television viewing in
young adolescents in Turkey’, Indian Pediatrics, 48(3), pp. 229-231. doi:10.1007/s13312-011-0048-3.
Picton, I., Clark, C. and Judge, T. (2020) Video game playing and literacy: a survey of young people aged 11 to
16. A National Literacy Trust research report. Available at:
https://cdn.literacytrust.org.uk/media/documents/Video_game_playing_and_literacy_report_final_updated.
pdf
Przybylski, A. and Weinstein, N. (2017) ‘A large-scale test of the Goldilocks Hypothesis: quantifying the relations
between digital-screen use and the mental well-being of adolescents’, Psychological Science, 28(2), pp. 204–
215. doi: 10.1177/0956797616678438.
Regondola, E.N. and Barbado, L.N. (2017) ‘Media habits and academic performance of elementary pupils of the
Camarines Norte State College Laboratory School’, Imperial Journal of Interdisciplinary Research, 3(11), pp. 216-
24.
Rideout, V. (2017). The Common Sense census: media use by kids age zero to eight. San Francisco, CA:
Common Sense Media. Available at:
https://www.commonsensemedia.org/sites/default/files/uploads/research/csm_zerotoeight_fullreport_relea
se_2.pdf
Robinson, T.N., Banda, J.A., Hale, L., Lu, A.S., Fleming-Milici, F., Calvert, S.L. and Wartella, E. (2017) ‘Screen
media exposure and obesity in children and adolescents’, Pediatrics, 140 (Suppl 2), pp. S97–S101. doi:
10.1542/peds.2016-1758K.
Rosen, B. (2019) How to utilize the research about children and screen time. Clinical Science Insights, January
2019. The Family Institute at Northwestern University.
21
Screen Time and Learner Well-being:
The Debate, the Evidence and Directions for Future Research and Policy
A Research Brief by UNESCO MGIEP

Schoeni, A., Roser, K., Röösli, M. (2015). ‘Symptoms and cognitive functions in adolescents in relation to mobile
phone use during night’, PLoS One, 10(7), e0133528. doi: 10.1371/journal.pone.0133528.
Schrier, K. (2018) ‘Guiding questions for game-based learning’, in Voogt, J., Knezek, G., Christensen, R., Lai, K.W.
(eds.) Second Handbook of Information Technology in Primary and Secondary Education. Springer International
Handbooks of Education. Springer, Cham. doi: 10.1007/978-3-319-71054-9_59.
Smart, A. and Jagannathan, S. (2018) Textbook policies in Asia: development, publishing, printing, distribution,
and future implications. Manila: Asian Development Bank.
Stiglic, N. and Viner, R.M. (2019). ‘Effects of screentime on the health and well-being of children and
adolescents: a systematic review of reviews’, BMJ Open, 9, e023191. doi: 10.1136/bmjopen-2018-023191.
Straker, L., Zabatiero, J., Danby, S., Thorpe, K. and Edwards, S. (2018) ‘Conflicting guidelines on young children's
screen time and use of digital technology create policy and practice dilemmas’, The Journal of Pediatrics, 202,
pp. 300-303. doi: 10.1016/j.jpeds.2018.07.019.
Tamana, S. K., Ezeugwu, V., Chikuma, J., Lefebvre, D. L., Azad, M. B., Moraes, T. J., Subbarao, P., Becker, A. B.,
Turvey, S. E., Sears, M. R., Dick, B. D., Carson, V., Rasmussen, C., CHILD study Investigators, Pei, J., & Mandhane,
P. J. (2019). ‘Screen-time is associated with inattention problems in preschoolers: Results from the CHILD birth
cohort study’, PloS one, 14(4), e0213995. https://doi.org/10.1371/journal.pone.0213995
Twenge, J.M., Joiner, T.E., Rogers, M.L. and Martin, G.N. (2018). ‘Increases in depressive symptoms, suiciderelated
outcomes, and suicide rates among U.S. adolescents after 2010 and links to increased new media screen
time’, Clinical Psychological Science, 6(1), 3-27.
Unantenne, N. (2014). Mobile device usage among young kids: a Southeast Asia study. Report commissioned
by Samsung Kidstime. Singapore: theAsianparent Insights.
Available at: https://s3-ap-southeast-1.amazonaws.com/tap-sgmedia/theAsianparent+Insights+Device+Usage+A+Southeast+Asia+Study+November+2014.pdf
UNICEF (2017) Children in digital world: the state of world’s children 2017 report. Available at:
https://www.unicef.org/publications/files/SOWC_2017_ENG_WEB.pdf
van den Heuvel, M., Ma, J., Borkhoff, C.M., Koroshegyi, C., Dai, D.W.H., Parkin, P.C., Maguire, J.L. and Birken,
C.S., TARGet Kids! Collaboration (2019) ‘Mobile media device use is associated with expressive language
delay in 18-month-old children’, Journal of Developmental and Behavioral Pediatrics, 40(2), pp. 99-104. doi:
10.1097/DBP.0000000000000630.
Viner, R., Davie, M. and Firth, A. (2019) The health impacts of screen time: a guide for clinicians and parents.
Royal College of Paediatrics and Child Health. Available at: https://www.rcpch.ac.uk/sites/default/files/2018-
12/rcpch_screen_time_guide_-_final.pdf
Wai WONG, C., TSAI, A., Jonas, J.B., Ohno-Matsui, K., CHEN, J., ANG, M. and Wei TING, D.S. (2020) ‘Digital
screen time during COVID-19 pandemic: risk for a further myopia boom?’, American Journal of
Ophthalmology, doi: 10.1016/j.ajo.2020.07.034.
22
Screen Time and Learner Well-being:
The Debate, the Evidence and Directions for Future Research and Policy
A Research Brief by UNESCO MGIEP

Wouters, P., van Nimwegen, C., van Oostendorp, H. and van der Spek, E. D. (2013) ‘A meta-analysis of the
cognitive and motivational effects of serious games’, Journal of Educational Psychology, 105(2), 249.
23
Screen Time and Learner Well-being:
The Debate, the Evidence and Directions for Future Research and Policy
A Research Brief by UNESCO MGIEP

Appendix I: Types and designs of study, geographic coverage, and participants of the studies covered in the present review
Title of the Study Type Study Design Region Participants Age
Screen time and sleep among school-aged children
and adolescents: a systematic literature review (Hale
and Guan 2014)
Systematic review of sedentary behaviour and health
indicators in school-aged children and youth: an
update (Carson et al. 2016)
Effects of screen time on health and wellbeing of
children and adolescents : a systematic review of
reviews (Stiglic and Viner 2019)
Associations between screen use and child language
skills: A systematic review and meta-analysis
(Madigan et al. 2020)
A meta-analysis of the effect of media devices on
sleep outcomes (Carter et al. 2016)
Cross-sectional study of use of electronic media by
secondary school students in Bangkok, Thailand
(Kiatrungrit and Hongsanguansri 2014)
Mobile telephone use is associated with changes in
cognitive function in young adolescents (Abramson
et al. 2009)
Symptoms and cognitive functions in adolescents in
relation to mobile phone use during night (Schoeni et
al. 2015)
The problematic use of Information and
Communication Technologies (ICT) in adolescents by
the cross sectional JOITIC study (Muñoz-Miralles et
al. 2016)
A latent class analysis on adolescents media use and
associations with health-related quality of life
(Foerster and Rsli 2017)
Behavioral correlates of television viewing in young
adolescents in Turkey (Ozmert et al. 2011)
Does recreational computer use affect high school
achievement (Bowers and Matthew 2013)
Systematic
Review
Systematic
Review
Systematic
Review
Meta Analysis;
Systematic
Review
Meta Analysis
Investigatory (identify
associations)
Literature Review
Review of Reviews (RoR)
Investigatory (identify
associations)
Investigatory (identify
associations)
Focussed Paper Cross sectional
Studies from several
countries included in
review
Studies from 71
countries included in
review
Majority studies
under review
undertaken in United
States
US
North America,
Europe, Asia, and
Australasia
Thailand
Number of
Studies
covered
Total Number
of Participants
(N)
5-17 year olds 67 401,869
5-17 year olds 235 1,657,064
0-18 year olds 13 1,046,165
Average age of
participants was 12
years
42 18905
6 - 19 year olds 20 125198
Adolescents
(secondary grade
students)
1 768
Focussed Paper Cross sectional Australia 7th Grade students 1 317
Focussed Paper Cross Sectional Switzerland 12-17 year olds 1 439
Focussed Paper Cross sectional Spain 12 - 20 years olds 1 5,538
Focussed Paper
Focussed Paper
Focussed Paper
Investigatory (identify
associations)
Investigatory (identify
associations)
Investigatory (identify
associations)
Switzerland
Turkey
Adolescents (7th - 9th
Graders)
Adolescents (7th - 8th
grade students)
1 895
1 581
US 10th Grade students 1 13,960
Comments
Covered in Stiglic and Viner
2019 but numbers not
included
Covered in Stiglic and Viner
2019 but numbers not
included
N is sum of only 4 reviews
where it was reported.
Other 9 do not report total
number of subjects.
Included in Carson et al.
2016
Included in Carson et al.
2016
24
A Research Brief by UNESCO MGIEP

Internet use, videogame playing and cell phone use
as predictors of children’s body mass index (BMI),
body weight, academic performance, and social and
overall self-esteem (Jackson et al. 2011)
Night-time screen-based media device use and
adolescents' sleep and health-related quality of life
(Mireku et al. 2019)
Physical fitness, physical activity, sedentary behavior
and academic performance among adolescent boys
in different weight statuses (Esmaeilzadeh and
Kalantari 2013)
The impact of media use on sleep patterns and sleep
disorders among school aged children in China (Li et
al. 2007)
Association between screen time and children's
performance on a development screening test
(Madigan et al. 2019)
A large-scale test of the Goldilocks Hypothesis:
quantifying the relations between digital-screen use
and the mental well-being of adolescents (Przybylski
and Weinsten 2017)
Association between adolescent well-being and
digital tech use (Orben and Przybylski 2019)
Screens, teens and psychological wellbeing: evidence
from three time use diary studies (Orben and
Przybylski 2019)
Screen time in children and adolescents - is there
evidence to guide parents and policy (Ashton and
Beattie 2019)
Digital screen media and cognitive development
(Anderson and Subrahmanyam 2017)
Focussed Paper
Focussed Paper
Focussed Paper
Focussed Paper
Investigatory (identify
associations)
Investigatory (identify
associations)
Investigatory (identify
associations)
Investigatory (identify
associations)
Focussed Paper Longitudinal Study
Focussed Paper
Focussed Paper
Focussed Paper
Two part study: exploratory and
confirmatory
Specification Curve Analysis
(identify associations) on data
from 3 large scale social datasets
Two part study: exploratory and
confirmatory
US
Average age of
participants was 12
years
UK 11-12 year olds 1 6,616
1 482 Included in Carson 2016
Iran 15 - 17 year olds 1 538 Included in Carson 2016
China
Canada
Elementary Grade
Children, Mean age =
9 years
Data collected at 2, 3
and 5 years of age for
each participant
1 19,299
1 2,441
UK 15 year olds 1 120,115
US and UK 12 - 18 year olds 1 355,358
Ireland, United
States, United
Kingdom
9 year olds 1 17,247
Comment Comment Article NA NA NA NA
Comment
Comment Article/Literature
Review
Mainly US
Mainly infants and
toddlers
NA
NA
Included in Hale and Guan
2014
Covered in Stiglic and Viner
2019 but numbers not
included
Total 392 3,793,795
Adjusted Total after excluding double counts 385 3,772,127
25
A Research Brief by UNESCO MGIEP

Appendix II: Analytical foci and key conclusions of the studies covered in the present review
Factor→
Study↓
Evidence
/Data
Sample
Devices
Timing of
Usage
Environment
of Usage
Purpose of
Usage
Content of
Media
Impact on Health
Impact on Learning
Conclusion/
Message
Screen time and sleep
among school-aged
children and
adolescents: a
systematic literature
review (Hale and Guan
2014)
Yes
5-17 year
olds
All digital
devices (TV,
computer,
smart phones,
tablets,
gaming
consoles)
Night time
Not
discussed
Not discussed
Not
discussed
Screen time across
different devices and on
a consistent basis
adversely associated
with sleep outcomes but
causal association not
confirmed
Not considered
More studies necessary
Systematic review of
sedentary behaviour
and health indicators in
school-aged children
and youth: an update
(Carson et al. 2016)
Yes
5-17 year
olds
All digital
devices (TV,
computer,
smart phones,
tablets,
gaming
consoles)
Not
discussed
Not
discussed
Not discussed
Not
discussed
Higher durations of
screen time associated
with unfavourable body
composition,
cardiometabolic risk,
unfavourable social
behavior, low fitness
and low self esteem.
Higher duration of TV viewing
associated with lower
academic achievement but
quality of evidence marked as
'very low'.
Overall quality of evidence in
this review: low to moderate.
Higher quality and strong
studies required to confirm
primarily observational
evidence.
Effects of screen time
on health and wellbeing
of children and
adolescents : a
systematic review of
reviews (Stiglic and
Viner 2019)
Yes
0-18 year
olds
TV, Computers
and
Smartphones
(but non TV
data very
sparse)
Not
discussed
Not
discussed
Not discussed
Not
discussed
Strong indication of
negative effects of
screen time on health.
Low quality/poor evidence
that greater screen time was
associated with poorer
educational attainment.
Moderate quality evidence for
harmful effects of screen time
on cognition among infants.
Strong evidence for correlation
between screen time adiposity,
unhealthy diet, depressive
symptoms and quality of life.
Weak evidence that small
amounts of daily screen time
may have some benefits.
Associations between
screen use and child
language skills: A
systematic review and
meta-analysis (Madigan
et al. 2020)
Yes
Average
age of
participant
s was 12
years
All Screen
Based Devices
primarily TV
and Mobile
Phones
Not
discussed
Co-viewing
with
Parents
considered
For
Educational
and
Entertainment
Purposes
Educational
and Non
Educational
(both)
Impact on Language
Skills
Greater Quantity of screen
use associated with lower
language skills but
educational programs and coviewing
associated with
stronger language skills
Limit exposure to screen time,
select high quality programmes
for viewing and co-view with
parents when possible
A meta-analysis of the
effect of media devices
on sleep outcomes
(Carter et al. 2016)
Yes
6 - 19 year
olds
All Screen
Based Devices
primarily TV
and Mobile
Phones
Discussion
on nighttime
usage
Not
discussed
Not discussed
Not
discussed
Bedtime media device
usage associated with
inadequate sleep
quantity, poor sleep
quality, and daytime
sleepiness
Not considered
Age specific guidance for
screen based media device
usage and parent led initiatives
to reduce access and use in
collaboration with health
providers and teachers.
Cross-sectional study of
use of electronic media
by secondary school
students in Bangkok,
Yes
Adolescents
(secondary
grade
students)
All digital
devices (TV,
computer,
smart phones,
Not
discussed
Not
discussed
Not discussed
Not
discussed
Not discussed
Use of devices not related to
academic performance. As
they age adolescents tend to
spend more time engaged in
Longitudinal studies with
precise time logs of device
usage and description of type
of content required to
26
A Research Brief by UNESCO MGIEP

Thailand (Kiatrungrit
and Hongsanguansri
2014)
tablets,
gaming
consoles)
interpersonal communication
through digital devices. Boys
more interested in
competitive games, girls more
in passive recreation and
communication.
determine the extent of effects
in social and psychological
development of adolescents.
Mobile telephone use is
associated with changes
in cognitive function in
young adolescents
(Abramson et al. 2009)
Yes
7th Grade
students
Mobile
Not
discussed
Not
discussed
Not discussed
Not
discussed
Not discussed
Mobile phone use associated
with faster but less accurate
response to cognitive tasks.
Greater mobile phone use
related to poorer accuracy on
working memory and
associative learning tasks.
Symptoms and cognitive
functions in adolescents
in relation to mobile
phone use during night
(Schoeni et al. 2015)
Yes
12-17 year
olds
Mobile Phone
Night time
Not
discussed
Not discussed
Not
discussed
Increase in health
symptom reports such
as tiredness, rapid
exhaustibility, headache
and physical ill-being
No indications of impact on
memory and concentration
capacity
More studies necessary
The problematic use of
Information and
Communication
Technologies (ICT) in
adolescents by the cross
sectional JOITIC study
(Muñoz-Miralles et al.
2016)
Yes
12 - 20
years olds
All ICTs
Not
discussed
Not
discussed
Not discussed
Not
discussed
Problematic use of
mobile phones
associated with drug
consumption. Video
game use among male
students associated with
consumption of drugs,
poor academic
performance and poor
family relationships.
Problematic use of ICT and
Internet greatest risk for poor
academic performance.
Number of hours of use is a risk
factor. Causality cannot be
established.
A latent class analysis on
adolescents media use
and associations with
health-related quality of
life (Foerster and Rsli
2017)
Yes
Adolescents
(7th - 9th
Graders)
All digital
devices (TV,
computer,
smart phones,
tablets,
gaming
consoles)
Not
discussed
Not
discussed
5 classes of
usage
identified:
Low Use,
Medium Use,
Gaming, Call
Preference
and High
Social Use
Not
discussed
High Social Use class
showed less well being
but best connection
with peers; low selfperception;
least
satisfaction at home;
less connectedness to
school and teachers
Not considered
Direction of associations
cannot be clarified but class
analysis important to identify
effects of media use
Behavioral correlates of
television viewing in
young adolescents in
Turkey (Ozmert et al.
2011)
Yes
Adolescents
(7th - 8th
grade
students)
TV
Not
discussed
Not
discussed
Not discussed
Not
discussed
Parent reported
durations were found to
be correlated with
aggressive behaviour.
Not considered
27
A Research Brief by UNESCO MGIEP

Does recreational
computer use affect
high school
achievement (Bowers
and Matthew 2013)
Yes
10th
Grade
students
Computer
Not
discussed
Not
discussed
Not discussed
Not
discussed
Not discussed
Use of computers for fun and
gaming were positive and
significant on reading and
mathematics achievement
assessments in high school.
Causality is difficult to ascertain
but effects of using computers
for fun and games for 1-2 hours
a day are +ve.
Internet use, videogame
playing and cell phone
use as predictors of
children’s body mass
index (BMI), body
weight, academic
performance, and social
and overall self-esteem
(Jackson et al. 2011)
Yes
Average age
of
participants
was 12
years.
Computers
and Mobile
phones
Not
discussed
Not
discussed
Not discussed
Not
discussed
Use of IT did not predict
BMI.
Videogame play predicted
positive visual-spatial skills
but lower GPAs. Use of
internet associated with
better reading scores among
females. More videogame
time associated with low self
esteem.
More research needed to
investigate the causes and
consequences of IT use and to
incorporate individual
differences in effects of IT use.
Night-time screen-based
media device use and
adolescents' sleep and
health-related quality of
life (Mireku et al. 2019)
Yes
11-12 year
olds
All digital
devices (TV,
computer,
smart phones,
tablets,
gaming
consoles)
Night time
(within one
hour before
sleep SBMD
usage)
Lit and dark
rooms
Not discussed
Not
discussed
Night time use
associated with higher
odds of insufficient
sleep; Magnitude of
association higher when
night time usage
occurred in darkness.
Not considered
Screen-based media device
(SBMD) usage should be
curtailed within an hour before
bedtime and particularly in
darkness.
Physical fitness, physical
activity, sedentary
behavior and academic
performance among
adolescent boys in
different weight
statuses (Esmaeilzadeh
and Kalantari 2013)
Yes
15 - 17
year olds
All sedentary
behaviour
through usage
of all digital
devices (TV,
computer,
smart phones,
tablets,
gaming
consoles)
Not
discussed
Not
discussed
Not discussed
Not
discussed
Positive relationship
between sedentary
behaviour and BMI.
No relationship between
weight classes and academic
performance
Longitudinal studies needed to
determine the directionality.
The impact of media use
on sleep patterns and
sleep disorders among
school aged children in
China (Li et al. 2007)
Yes
Elementar
y Grade
Children,
Mean age
= 9 years
TV and
Computer
Not
discussed
Device in
bedroom of
children
Not discussed
Not
discussed
TV viewing of more than
2 hours was a risk factor
for sleep disorders.
Computer use, however,
had NO correlation with
any sleep disorder.
Not considered
Presence of media in child's
bedroom and media use had a
negative impact on sleep
patterns duration and sleep
disorders.
Association between
screen time and
children's performance
on a development
screening test (Madigan
et al. 2019)
Yes
Data
collected
at 2, 3 and
5 years of
age for
each
participant
TV, Computers
and
Smartphones
(but non TV
data very
sparse)
Not
discussed
Not
discussed
Not discussed
Not
discussed
Development Screening
Test measured:
communication, gross
motor, fine-motor,
problem solving and
personal-social. Higher
levels of screen time
significantly associated
NA
Evidence of directional
association between screen
time and poor performance on
development screening
28
A Research Brief by UNESCO MGIEP

with poorer
performance on
development screening
tests.
A large-scale test of the
Goldilocks Hypothesis:
quantifying the relations
between digital-screen
use and the mental wellbeing
of adolescents
(Przybylski and
Weinsten 2017)
Yes
15 year
olds
All digital
devices (TV,
computer,
smart phones,
tablets,
gaming
consoles)
Compares
weekday vs
weekend
usage
Not
discussed
4 classes of
usage identified:
Watching films,
TV programs,
etc.; Playing
games; Using
computers for
internet, email,
etc.; Using
smartphone for
social
networking,
chatting, etc.
Not
discussed
The categories of digital
activity examined in this
study are unlikely to
present risk to mental
well-being at moderate
levels.
Not considered
Moderate engagement in
digital activities is not harmful.
Association between
adolescent well-being
and digital tech use
(Orben and Przybylski
2019a)
Yes
12 - 18
year olds
All digital
devices (TV,
computer,
smart phones,
tablets,
gaming
consoles)
Not
discussed
Not
discussed
Not discussed
Not
discussed
Association between
Digital Technology use
and adolescent
wellbeing is negative but
small
Not considered
Effects too small to warrant
policy change
Screens, teens and
psychological wellbeing:
evidence from three
time use diary studies
(Orben and Przybylski
2019b)
Yes
9 year olds
TV, Computers
and
Smartphones
(but non TV
data very
sparse)
Not
discussed
Not
discussed
Not discussed
Not
discussed
Little substantive
statistically significant
and negative association
between screen time
and wellbeing.
Not considered
Highlights need for robust and
reliable data, analysis and
research to support claims.
Screen time in children
and adolescents - is
there evidence to guide
parents and policy
(Ashton and Beattie
2019)
NA
NA
TV, Computers
and
Smartphones
Not
discussed
Not
discussed
Not discussed
Not
discussed
Overall negative but lack
of evidence; correlation
but no causation.
Not discussed
Highlights need for more
evidence; caution when
interpreting research on the
negative effects of screen
time.
Digital screen media and
cognitive development
(Anderson and
Subrahmanyam 2017)
NA
Mainly
infants
and
toddlers
TV, computers
and touch
screen devices
Not
discussed
Co-viewing
with
parents
considered
Entertainment
and
educational
Entertainme
nt and
educational
Not discussed
Impact on cognitive
development is the main
focus of the article.
Educational television found
to have positive impact on
early cognitive development.
Violent content found to
influence antisocial and
aggressive behaviour.
The greatest impact on
cognitive development likely
via content. A paucity of
research on the differential
effects of content as regards
interactive digital media.
29
A Research Brief by UNESCO MGIEP