literature review on screen time

• Open access
• Published: 19 April 2023

Screen time among school-aged children of aged 6–14: a systematic review

• Jingbo Qi 1 ,
• Yujie Yan 2 &
• Hui Yin 1  

Global Health Research and Policy volume  8 , Article number:  12 ( 2023 ) Cite this article

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Screen time refers to the time an individual spends using electronic or digital media devices such as televisions, smart phones, tablets or computers. The purpose of this study was to conduct systematic review to analyze the relevant studies on the length and use of screen time of school-aged children, in order to provide scientific basis for designing screen time interventions and perfecting the screen use guidelines for school-aged children.

Screen time related studies were searched on PubMed, EMBASE, Clinical Trials, Controlled Trials, The WHO International Clinical Trials Registry Platform, the Cochrane Central Register of Controlled Trials, CNKI, and Whipple Journal databases from January 1, 2016 to October 31, 2021. Two researchers independently screened the literature and extracted the data, and adopted a qualitative analysis method to evaluate the research status of the length and usage of screen time of school-aged students.

Fifty-three articles were included. Sixteen articles studied screen time length in the form of continuous variables. Thirty-seven articles studied screen time in the form of grouped variables. The average screen time of schoolchildren aged 6 to 14 was 2.77 h per day, and 46.4% of them had an average screen time ≥ 2 h per day. A growth trend could be roughly seen by comparing studies in the same countries and regions before and after the COVID-19 outbreak. The average rates of school-aged children who had screen time within the range of ≥ 2 h per day, were 41.3% and 59.4% respectively before and after January 2020. The main types of screen time before January 2020 were watching TV (20 literatures), using computers (16 literature), using mobile phones/tablets (4 literatures). The mainly uses of screens before January 2020 were entertainment (15 literatures), learning (5 literatures) and socializing (3 literatures). The types and mainly uses of screen time after January 2020 remained the same as the results before January 2020.

Conclusions

Excessive screen time has become a common behavior among children and adolescents around the world. Intervention measures to control children's screen use should be explored in combination with different uses to reduce the proportion of non-essential uses.

Screen time refers to the time an individual spends using electronic or digital media devices such as televisions, smart phones, tablets or computers [ 1 ]. With the development of science and technology integrated into social life, smart devices such as mobile phones, computers and tablets are more and more widely used in work, study and daily life. Children are exposed to electronic products at a younger age and their screen time is increasing. Too much screen time can have negative effects on children's physical and mental health. First, the negative effect of screen time on eyesight has been confirmed in many countries’ studies [ 2 , 3 ]. For example, the study by Hu Jia et al. showed that screen time ≥ 3 h per day (OR = 2.026, 95%CI:1.235 ~ 3.325) was a myopia risk factor for primary and middle school students [ 4 ]. Second, excessive screen time will also bring obesity, depression, sleep disorders and other health problems to children and adolescents [ 4 , 5 , 6 ].

The COVID-19 pandemic is still spreading across the globe, affecting the lives of billions of residents around the world. Various public institutions, including schools, have adopted a range of lockdown measures. More primary and middle schools have conducted online teaching, and the time for school-aged children to use electronic products for online learning has further increased. Diane Seguin et al. found that during the pandemic, the average daily screen time of Canadian children increased from over 2 h (2.6 h on average) to nearly 6 h (5.9 h on average)(t(73) = 9.04, p  = 0.001). Screen time increased by a total of more than 3 h, and children's screen time increased further during the pandemic compared to pre-pandemic [ 7 ].

Due to the physical development stage of school-aged children, the effect of prolonged screen time on their physical and mental health is more obvious and irreversible than that of adults. The Physical Activity Guidelines for Chinese Children and Adolescents [ 8 ] released in 2017 states that, the screen time of Chinese children and adolescents should be limited to 2 h per day. Referring to the guidelines of the American Academy of Pediatrics [ 9 ], children under the age of 2 should not use electronic media, while the time of using it for children over 2 years old should be limited to 2 h per day. However, empirical studies on the actual length and use of current screen time of school-aged children are relatively scattered and insufficient. This study used the qualitative systematic review method to analyze the relevant studies on the length and use of screen time of school-aged children, in order to provide scientific basis for designing screen time interventions and perfecting the screen use guidelines for school-aged children.

Inclusion criteria

The types of literature include cross-sectional studies, cohort studies and case–control studies published in the form of peer-reviewed journal articles. The research subjects of the literature should include primary and secondary school students aged 6 to 14, including male and female. The literature published includes raw data, screen time values, age distribution, time distribution, and the screen use.

Exclusion criteria

Unpublished, unoriginal and non-peer reviewed articles, case reports, letters or comments; the research subjects do not meet the age requirements (under 6 years old, over 14 years old); the literature does not describe screen use time in detail, lacks quantitative data and correlation verification, and is only empirical conclusion.

The strategy of literature search

Search the literature in the public databases on PubMed, Clinical Trials, Controlled Trials, the WHO International Clinical Trials Registry Platform, EMBASE, the Cochrane Central Register of Controlled Trials, CNKI, and Whipple Journal. According to the phrases included the age group, and the screen use, "school-age child"/"primary school"/"junior high school student"/"primary and secondary school student"; "screen time"/" video time "/" electronic equipment "/" electronic products "/" multimedia equipment "/" digital equipment "are searched in the database. At the same time, search the references of the literature for other literature. The search time limit is from January 1, 2016 to October 31, 2021. The types of literature searched include cross-sectional studies, cohort studies and case–control studies. The search was limited to human studies reported either in English or in Chinese. All search phrases were modified according to MeSH terms.

Literature screening and data extraction

According to the search strategy and inclusion and exclusion criteria, two researchers independently conduct literature screening. After the screening, the two researchers discuss the screening process and the inconsistent parts of the results to form a unified result. If no agreement were to reach, a third party should be consulted. The contents of the research extraction include: author, publishing time, research region, research type, sample characteristics, screen time length, use and influencing factors, research content and main results and conclusions.

Risk evaluation and systematic evaluation of literature bias

The Cochrane risk assessment tool [ 10 ] is used to evaluate the literature quality of the included cross-sectional studies from the following aspects: random sequence generation, allocation hiding, blinding method, result data integrity, selective reporting and other biases. The bias risk has three possibilities: low risk, high risk and unknown bias risk. For observational studies, Newcastle–Ottawa Scale (NOS) [ 11 ] is used for quality assessment, which is scored from three parts: the selection of study population, comparability, exposure evaluation or result evaluation, and uses the semi-quantitative principle of star level system to evaluate literature quality. Studies with a score of 6 stars or more are defined as high quality and are included in this study. The quality assessment is conducted independently by the above-mentioned three researchers. In case of any dispute, a consensus shall be reached through discussion. In this study, Excel 2016 software was used to count the published literature, and qualitative analysis was performed on the included studies.

Basic information and bias risk evaluation of included research

The preliminary search obtained 1275 relevant literatures. After removing the duplicates and reading the literature titles and abstracts, through rounds of screening, two hundred and twenty-six literatures were excluded due to the lack of screen use data. Seventy-nine literatures were excluded due to inconsistent characteristics such as age and gender of the subjects. Thirty-six literatures were excluded due to inconsistent research types. Eight literatures were excluded due to incomplete content of the full text. Thirteen literatures were excluded because the research data source time was more than five years. Finally, fifty-three literatures [ 4 , 5 , 6 , 7 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 ] were included. Their basic information was shown in Table 1 . The literature screening process and results are shown in Fig.  1 . Considering the representativeness of the sample population, we made unified screening regulations on the age of the study population, the difficulty in obtaining electronic devices, the family's economic ability, and the parents' education level of the study population. There were 19 Chinese literatures and 34 English literatures. In terms of research time, there were two literatures in 2016, eight literatures in 2017, ten literatures in 2018, seven literatures in 2019, thirteen literatures in 2020 and thirteen literatures in 2021. Nineteen literatures were from China (including Taiwan Province), 6 literatures from other Asian countries, 17 literatures from European countries, 9 literatures from American countries, 1 literature from African countries and 1 literature from Oceania countries. The screen time data in the literature were collected by questionnaire and database. There were 16 literatures with continuous screen time and 37 literatures with classified screen time. The evaluation results of the bias risk of different included studies are shown in Fig.  2 .

Flow chart of literature screening

Bias risk evaluation results of different included studies (red indicators high risk, green indicators low risk)

Average daily length of screen time among schoolchildren aged 6–14 (continuous variable)

In 55 literatures, sixteen of them studied screen time length in the form of continuous variables. Sixteen literatures investigated the average daily length and standard deviation of the group by screen time and other health behavior factors. A total of 105,209 primary and middle school students aged 6 to 14 years were included in the study. Taking the international recommended length of screen time—2 h per day as the control parameter, the average length and standard deviation of the screen time of each literature were entered. Meta-analysis carried out by RevMan software showed that the average screen time of the included literature was + 0.77 h higher than the control parameter and the average screen time was 2.77 h per day (95% CI: 0.32 ~ 1.22).The analysis results are shown in Fig.  3 .

Forest plot for screen time of 6–14 year old school children (continuous variable)

Average daily length of screen time for Schoolchildren aged 6–14 (Classification variable)

Among the 55 literatures, thirty-seven expressed screen time in the form of grouped variables. Screen time < 2 h per day and ≥ 2 h per day were defined as screen time in 35 of the 37 classification variable literatures. Two literatures that only provided data on screen time use were not included in the bar chart. Among the included literatures published in 2021, there were four papers whose actual data collection took place in 2021, while the rest of the literatures published in 2021 reported data was collected in 2020 and before. A total of 472,042 primary and middle school students aged 6 to 14 years were included in the study. With the included literatures presented in chronological order, the bar chart showed the proportion of groups with average screen time ≥ 2 h per day in the whole study population. The results showed that 46.4% of primary and middle school students aged 6 to 14 years had screen time within the range of ≥ 2 h per day. A growth trend could be roughly seen by comparing studies in the same countries and regions before and after the COVID-19 outbreak. The average rates of school-aged children, who had screen time within the range of ≥ 2 h per day, were 41.3% and 59.4% respectively before and after January 2020. The statistical results are shown in Fig.  4 .

Screen time of 6–14 year old school children (classification variable)

Main uses of screen time for school-aged children

In the included literatures, twenty-five analyzed the types and uses of screen time among schoolchildren aged 6 to 14. The full text of the literature were read to get the classification of the screen devices, including televisions, mobile phones, tablets and computers. The classification of screen use were put into three categories, namely, learning, entertainment (including watching video and video games) and social interaction. The number of literatures and samples for each kind of use were counted. A total of 330,119 schoolchildren aged 6 to 14 were included in this indicator. Calculated according to the statistical sequence of the sample size of the literature study, the results showed that the main types of screen time before January 2020 were watching TV (20 literatures), using computers (16 literature), using mobile phones/tablets (4 literatures). The mainly uses of screens before January 2020 were entertainment (15 literatures), learning (5 literatures) and socializing (3 literatures). The types and mainly uses of screen time after January 2020 remained the same as the results before January 2020, as shown in Table 2 .

From smartphones and social media to TV and tablet-based online courses, today’s school-aged children are constantly inundated by technology. The primary purpose of this review was to summarize the current situation of length and use of screen time of school-aged children. Our findings show that excessive screen time among schoolchildren aged 6–14 is very common and has become a serious public health problem in high—and middle-income countries. Excessive screen time has a variety of effects on the health of school-aged children, including emotional, sleep, behavioral problems, and affects the growth and cognitive development of school-aged children. Some high-income countries, such as the United States [ 61 ] and Germany [ 62 ], have developed guidelines for restrictions on digital media overuse across age groups, while some low—and middle-income countries have not developed such screen time guidelines. In 2021, the National Health Commission issued Appropriate Technical Guidelines for Prevention and control of Myopia in Children and Adolescents (updated version) [ 63 ], which suggested that families should "not put TV and other video products in children's bedrooms", but did not put forward suggestions on screen duration. This review might be useful for the policymakers in formulating or refining guidelines for limiting the excessive digital-media usage for school-aged groups in these countries.

Instead of school settings, home-based television viewing and home-based computers are two primary types of screen viewing of school-aged children. The home setting, especially parents, plays a vital role in deciding the type and length of screen viewing. Parents’ attitudes, beliefs, norms, and behaviors shape and create a shared social and physical environment in the home setting, and this environment affects children’s possibilities for different types of behaviors [ 64 ]. Higher parental self-efficacy to limit screen time is associated with less children’s screen time, whereas availability of media equipment is associated with increased children’s screen time [ 65 ]. Therefore, health promotion programs are needed to help raise parents' awareness and ability to help reduce children’s excessive screen time. Among different purposes of screen time for school-aged children, the main purpose is spent on entertainment rather than learning, which offers the possibility of reducing long screen time. Parents could set time limits on the use of entertainment software on electronic devices, or replace screen use with outdoor activities. It is also relevant to study further the screen use preferences of students of different ages, and to distinguish the use time of different screen media such as TV, computer and mobile phone. This knowledge would be valuable for the development of effective interventions aiming to diminish the school-aged children’s screen time.

During disease pandemic such as COVID-19, screen usage may become more prevalent through periods of school closures, lockdowns, social isolation, and online learning classes. Public health policies and health promotion strategies targeting parents are needed to raise awareness of the adverse health effects associated with excessive screen time [ 66 ]. From our findings, comparing the literature data before 2020 with those after 2020, the increase in screen time of primary and middle school students in the same countries and regions is obvious. There are also relevant studies [ 67 ] that due to the impact of the epidemic, the proportion of children whose screen time of electronic products was longer than 3 h per day rose from 9.16% before the epidemic to 19.20% after the epidemic. When literatures were searched, the publication years of literature included the time of epidemic. Compared with those before 2019, there has been a significant increase in screen time reported in the literature since 2020, which is related to the fact that the children have been forced to stay at home longer, and online teaching has led to increased average exposure to electronic devices during the pandemic. Since the online learning is “required” by schools, it raises a triple dilemma among maintaining school-learning, prevention of communicable diseases, and reducing excessive screen time, which needs further discussion. In addition, healthcare workers could provide health education and health consulting service on appropriate screen use behavior, how to improve digital media environment at home, and raise awareness of adverse health effects of screen time. Fitness and entertainment facilities shall be provided at the community level to reduce screen time, and enhance the physical activity level of children and adolescents. An integration of family, community, school, and health systems should be considered to design for intervention model of screen time behaviors.

This study has some limitations. First, according to the research types included in the literature, this study selected the international mainstream methodological quality scale for quality evaluation, but the quality of the relevant original research methodology was limited and not rigorous. It may have reduced the credibility of the conclusions. Second, in the included studies, national conditions and medical systems vary from country to country. The included literatures mainly focus on the health effects of screen time. The standards of screen time data collection and classification were not uniform among studies, which made the statistical results may deviate from the actual situation. In addition, the age range of some study subject included in the literature is not completely in the age range of 6–14 years old. Although only the data of the study subjects in accordance with the age group were selected in the data analysis, there were cases where a single data represented the level of the entire age group, and the sample size of the study subjects of each age group was not balanced, which may cause some bias to the conclusion. Only published literatures were searched, which may lead to incomplete data acquisition and potential publication bias. Third, because of the exclusion of literature published in languages other than English and Chinese, the research results were not representative in these language regions. Last, seventeen of the included literature were published after January 2020, but their data was collected before January 2020. New papers investigating screen time during COVID-19 pandemic have been published after our target date. Those latest data collection could be continued in the future to fully reflect the impact of the pandemic on screen time.

Focusing on school-aged children, this study systematically assessed the specific length and main uses of screen time in school-aged children aged 6–14, providing a baseline reference level for excessive screen time in school-aged children. It also provides ideas for interventions to reduce long screen time. However, the quality of the existing research is uneven, and the research types and quantity are relatively scarce. Further empirical research is needed to confirm the above conclusions.

Availability of data and materials

The datasets during and/or analysed during the current study available from the corresponding author on reasonable request.

Abbreviations

Screen time: time spent using the computer, watching TV, playing video games and other multimedia screens

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Qi, J., Yan, Y. & Yin, H. Screen time among school-aged children of aged 6–14: a systematic review. glob health res policy 8 , 12 (2023). https://doi.org/10.1186/s41256-023-00297-z

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DOI : https://doi.org/10.1186/s41256-023-00297-z

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Effect sizes for all screen types are presented in eFigure 1 in Appendix 1 .

The x-axis represents the observed outcome in log odds ratios. Filled and hollow diamonds represent the results of the meta-analysis before and after trim-and-fill correction, respectively. The diamond centers and corresponding vertical lines represent the value of the summary result. The diamond width represents the 95% CI of the summary result. The white area within the dashed diagonal lines indicates P  > .05 to P  > .99; the light gray area outside these lines indicates P  > 0 to P  = .05.

eAppendix. Formulas Used for Conversion of the Various Effect Sizes Into Log Odds Ratios

eFigure 1. Forest Plot of All 66 Effect Sizes by Screen Type

eFigure 2. Forest Plot by Age Groups of the 28 Effect Sizes of General Screen Use

eFigure 3. Forest Plot by the Type of Autism Spectrum Disorder (ASD) Measure of 28 Effect Sizes of General Screen Use

eFigure 4. Forest Plot of the 6 Longitudinal Studies

eFigure 5. Forest Plot by Type of Screen of 66 Effect Sizes Using Fisher z Scores

eFigure 6. Forest Plot by Age Groups of the 28 Effect Sizes of General Screen Use Based on Fisher z Scores

eFigure 7. Forest Plot by Type of Autism Spectrum Disorder (ASD) Measure of the 28 Effect Sizes of General Screen Use Based on Fisher z Scores

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Ophir Y , Rosenberg H , Tikochinski R , Dalyot S , Lipshits-Braziler Y. Screen Time and Autism Spectrum Disorder : A Systematic Review and Meta-Analysis . JAMA Netw Open. 2023;6(12):e2346775. doi:10.1001/jamanetworkopen.2023.46775

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Screen Time and Autism Spectrum Disorder : A Systematic Review and Meta-Analysis

• 1 Department of Education, Ariel University, Ariel, Israel
• 2 Centre for Human Inspired Artificial Intelligence, University of Cambridge, Cambridge, United Kingdom
• 3 School of Communication, Ariel University, Ariel, Israel
• 4 Faculty of Data and Decision Sciences, Technion–Israel Institute of Technology, Haifa, Israel
• 5 Communications Department, Sapir Academic College, Hof Ashkelon, Israel
• 6 Seymour Fox School of Education, Hebrew University of Jerusalem, Jerusalem, Israel

Question   Is there an association between screen time and autism spectrum disorder (ASD)?

Findings   In this systematic review and meta-analysis of 46 of 4682 observational studies, a statistically significant association was found between screen time and ASD, in particular among studies that examined general screen use among children. However, when accounting for publication bias, the findings were no longer statistically significant.

Meaning   These findings suggest that excessive screen time may be associated with negative developmental outcomes; however, the observational nature and publication bias of the included studies render these findings inconclusive.

Importance   Contemporary studies raise concerns regarding the implications of excessive screen time on the development of autism spectrum disorder (ASD). However, the existing literature consists of mixed and unquantified findings.

Objective   To conduct a systematic review and meta-analyis of the association between screen time and ASD.

Data Sources   A search was conducted in the PubMed, PsycNET, and ProQuest Dissertation & Theses Global databases for studies published up to May 1, 2023.

Study Selection   The search was conducted independently by 2 authors. Included studies comprised empirical, peer-reviewed articles or dissertations published in English with statistics from which relevant effect sizes could be calculated. Discrepancies were resolved by consensus.

Data Extraction and Synthesis   This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guideline. Two authors independently coded all titles and abstracts, reviewed full-text articles against the inclusion and exclusion criteria, and resolved all discrepancies by consensus. Effect sizes were transformed into log odds ratios (ORs) and analyzed using a random-effects meta-analysis and mixed-effects meta-regression. Study quality was assessed using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) approach. Publication bias was tested via the Egger z test for funnel plot asymmetry. Data analysis was performed in June 2023.

Main Outcomes and Measures   The 2 main variables of interest in this study were screen time and ASD. Screen time was defined as hours of screen use per day or per week, and ASD was defined as an ASD clinical diagnosis (yes or no) or ASD symptoms. The meta-regression considered screen type (ie, general use of screens, television, video games, computers, smartphones, and social media), age group (children vs adults or heterogenous age groups), and type of ASD measure (clinical diagnosis vs ASD symptoms).

Results   Of the 4682 records identified, 46 studies with a total of 562 131 participants met the inclusion criteria. The studies were observational (5 were longitudinal and 41 were cross-sectional) and included 66 relevant effect sizes. The meta-analysis resulted in a positive summary effect size (log OR, 0.54 [95% CI, 0.34 to 0.74]). A trim-and-fill correction for a significant publication bias (Egger z  = 2.15; P  = .03) resulted in a substantially decreased and nonsignificant effect size (log OR, 0.22 [95% CI, −0.004 to 0.44]). The meta-regression results suggested that the positive summary effect size was only significant in studies targeting general screen use (β [SE] = 0.73 [0.34]; t 58  = 2.10; P  = .03). This effect size was most dominant in studies of children (log OR, 0.98 [95% CI, 0.66 to 1.29]). Interestingly, a negative summary effect size was observed in studies investigating associations between social media and ASD (log OR, −1.24 [95% CI, −1.51 to −0.96]).

Conclusions and Relevance   The findings of this systematic review and meta-analysis suggest that the proclaimed association between screen use and ASD is not sufficiently supported in the existing literature. Although excessive screen use may pose developmental risks, the mixed findings, the small effect sizes (especially when considering the observed publication bias), and the correlational nature of the available research require further scientific investigation. These findings also do not rule out the complementary hypothesis that children with ASD may prioritize screen activities to avoid social challenges.

The ever-increasing rates of autism spectrum disorder (ASD), 1 , 2 a neurodevelopmental condition characterized by difficulties in interpersonal interactions and communication, as well as restricted and repetitive behaviors, are a major concern in pediatrics. Several explanations have been proposed for this increased prevalence, 3 , 4 including the global emergence of screen-based devices (eg, smartphones, tablets) and their ubiquitous use among young children, including infants. 5 Corresponding to a longstanding concern in media psychology termed the displacement hypothesis , 6 contemporary scholars warn that excessive screen use may come at the expense of positive and vital real-life experiences, such as interpersonal interactions, outdoor and sporting events, and educational activities. 7 , 8 According to this hypothesis, screen use contributes to young children being less active, less verbal, and less social than children of previous generations, essentially increasing their risk of experiencing developmental delays, behavioral problems, and ASD symptoms. 9 - 13

Although this concern, along with multiple other screen-related risks, 14 warrants the periodic formulation of screen use guidelines for parents (such as the recent recommendations issued by the World Health Organization 15 ), its empirical foundations remain unclear. To date, very few longitudinal studies have been conducted on this topic, and the picture arising from the existing, mostly cross-sectional literature is ambiguous and requires further examination. 16 - 18

Before undertaking the current study, we identified 2 systematic reviews that addressed the association between screen time and ASD. 17 , 18 Indeed, these reviews focused on the opposite direction of this association—that is, they explored the hypothesis that children with ASD would be more attracted than their peers to screen activities because these activities allow them to avoid real-life communication challenges. However, the results of these reviews also may be relevant to our research question, because they relied mostly on bidirectional correlational studies.

A 2018 systematic review by Stiller and Mößle 17 that included 47 studies was inconclusive. Some studies indicated that children with ASD have increased screen time, whereas other studies suggested that children without ASD have increased screen time. 17 The 2019 systematic review by Slobodin et al 18 implemented a more rigid inclusion criterion and included only studies that compared participants with diagnosed ASD with nondiagnosed participants. That review yielded 16 relevant studies, of which 14 pointed to a consistent trend whereby children with ASD indeed had increased screen time. 18 Nevertheless, Slobodin et al emphasized that the wide variability in the populations and methodologies in the included studies limited their finding, and they stated that “there are no data to confirm or refute a causal relationship between ASD and screen use.” 18 (p309)

Apart from these limitations and the mixed findings of Stiller and Mößle, 17 we identified 3 additional gaps in the literature. First, the latest search of the literature ended in April 2018, while screen use has only become more popular over the years, especially during the COVID-19 pandemic that shifted peoples’ activity to screen-based platforms. 19 Second, none of the available reviews included a quantitative evaluation of the association between screen time and ASD using a meta-analysis procedure. Finally, although several moderating factors were suggested in these reviews (eg, to explain mixed findings), none included a designated analysis that could shed light on the moderating role of these factors in the association between screen time and ASD.

Considering these gaps, we performed an updated systematic review and, to our knowledge, the first meta-analysis of the literature accumulated on the bidirectional association between screen time and ASD. In addition, this study also implemented meta-regression analyses to explore potential moderating factors that may be involved in this association. Specifically, the following 3 salient variables that distinguished the collected studies from one another were examined: (1) the type of screen device or screen activity (eg, smartphones, social media), (2) the age of screen users, and (3) the type of ASD measure, whether it reflected an ASD clinical diagnosis or symptoms or behaviors typical to ASD. Although these procedures cannot compensate for the absence of experimental studies, their results may shed light on this concerning association between screen time and ASD.

This systematic review and meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses ( PRISMA ) guideline. The 2 main variables of interest were screen time (ie, hours of screen use per day or per week) and ASD. The ASD variable consisted of 2 measures: (1) a binary variable (yes or no) that indicated the presence of a clinical diagnosis of ASD and (2) a continuous variable that indicated the existence of symptoms or behaviors typical to ASD (but may not necessarily indicate the existence of a clinical diagnosis).

A systematic search of relevant studies published up to May 1, 2023, was conducted in the 2 prominent databases in medicine and psychology: PubMed and PsycNET. A complementary search for unpublished work was conducted in the ProQuest Dissertation & Theses Global database. The search did not contain restrictions on publication type or language. Terms related to screen time and ASD were searched in all available database search fields, except in PubMed, which allowed a narrowed search within the study title and abstract (assuming that relevant articles mentioned the search terms in these sections).

For ASD, the search terms used were autism and ASD . For screen time, the search terms used were computer , media , mobile media , mobile phone , phone , screen time , smartphone , social media , television , and video games . This list was discussed among and consolidated by all authors, and it includes and extends the list used in the most recent systematic review on this topic. 18 During the search, each term for screen time was coupled with the terms for ASD; that is, the screen time terms were searched twice, once with ASD and once with autism spectrum disorder . Two authors (R.T. and S.D.) independently coded all titles and abstracts, reviewed full-text articles against the inclusion and exclusion criteria, and resolved all discrepancies by consensus.

After duplicate records were removed, the PubMed and PsycNET searches yielded 4677 articles. These articles examined the association between ASD and the following: computers (2884 articles), media (922 articles), mobile media (7 articles), mobile phones (17 articles), phone (121 articles), screen time (164 articles), smartphones (60 articles), social media (309 articles), television (105 articles), and video games (88 articles). The complementary search in ProQuest yielded 5 additional records of doctoral dissertations, thus creating an initial pool of 4682 studies.

In the first filtering step, we read the titles and abstracts of the 4682 articles and determined whether they (1) presented an empirical study, (2) were written in English, (3) were published in a peer-reviewed journal (or were a thesis or dissertation), and (4) specifically examined screen time and ASD (as multiple studies were conducted among ASD populations but addressed other negative outcomes, such as sleep problems). In the second filtering step, we read the remaining articles thoroughly and excluded those that did not meet the aforementioned inclusion criteria. In the second step, we also excluded studies that (1) did not report any statistics or reported a single case study, (2) presented a literature review and did not include an empirical study, and (3) had no comparison group, provided that they had a group of participants with ASD (studies without a comparison group were only included if they measured ASD symptoms). Research quality was assessed using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) approach. 20

Upon review of the final set, we collected all effect sizes (eg, Cohen’s d , Pearson r , odds ratio [OR], and log OR values) that represented the associations between screen time and ASD. In cases in which no effect size was reported, we calculated the effect size manually using the reported data or available statistics. We calculated Cohen’s d using means and SDs or t or F scores. We calculated log ORs using either reported frequency tables, reported χ 2 values, or β coefficients of logistic regression models. In cases in which a linear (not logistic) regression analysis was conducted, we transformed the standardized β coefficients to Pearson r values using the following conventional formula: r  = β + 0.5γ, where γ equals 1 when β is positive and 0 when β is negative. 21

When different effect sizes were reported for different age groups or for different screen types, they were all entered into the meta-analysis. When more than a single effect size was reported within a given age group or screen device type (eg, for different time points or for different assessment tools), we collected the largest effect size available.

Because ASD is typically perceived as a binary variable indicating whether an individual has this diagnosis, we transformed all collected effect sizes into log OR effect sizes. These log OR scores were then used to calculate the meta-analysis and meta-regression of this study. Because nearly half of the collected studies treated ASD as a continuous variable (measuring ASD symptoms), we conducted complementary analyses using continuous effect sizes (ie, Fisher z scores instead of log OR scores). These analyses yielded equivalent results (eFigures 5-7 in Supplement 1 ) that replicated the main results reported in the following meta-analysis and meta-regression results.

Effect sizes were calculated using the R psych package, version 1.9.1 (R Project for Statistical Computing). 22 Conversion of effect sizes to log ORs was conducted using the R effect size package, version 0.8.6.1 (R Project for Statistical Computing). 23 The eAppendix in Supplement 1 presents the exact formulas used in this process.

The univariate meta-analysis was conducted using a random-effects model and the meta-regression analyses were conducted using a mixed-effects model, both via the restricted maximum likelihood estimator for heterogeneity (τ 2 ). The meta-regression analysis addressed 3 independent variables, representing the 3 salient features that differentiated the collected studies from one another and thus allowed us to allocate them to distinct clusters. These variables were as follows: (1) screen type (general use of screens, television, video games, computer, smartphones, or social media), (2) age group (children vs adults or heterogenous age groups), and (3) type of ASD measure (clinical diagnosis vs ASD symptoms). The level of statistical significance in all analyses was P < .05 (2-tailed), meaning there were no prior assumptions regarding the direction of the results. Publication bias was tested via the Egger z test for funnel plot asymmetry. 24

The age variable comprised a wide range of ages across the various studies, which made the categorization process difficult. However, we observed that approximately half of the studies comprised children aged younger than 12 years, whereas the others included older or heterogenous age groups; we therefore coded age as a binary variable (children vs adults or heterogenous age groups). All analyses were conducted using the R metafor package, version 2.1-0 (R Project for Statistical Computing). 25 Data analysis was performed in June 2023.

The initial systematic literature search yielded 4682 records ( Figure 1 ). The first filtering step resulted in 145 studies, and the second filtering step resulted in a final collection of 46 studies 9 - 13 , 26 - 66 that examined the association between screen time and ASD ( Figure 1 and Table 1 ).

The 46 included studies were published between 2011 and 2023, with a total of 562 131 participants. Thirteen studies reported on data collected since the COVID-19 pandemic ( Table 1 ). 13 , 26 - 28 , 33 , 34 , 36 , 39 , 49 , 59 , 60 , 65 , 66 Notably, the research design of all 46 studies was observational: 41 were cross-sectional 9 , 13 , 26 - 30 , 32 - 44 , 46 - 66 and 5 were longitudinal. 10 - 12 , 31 , 45 Accordingly, the overall research quality of these studies was determined to be relatively low (according to the GRADE approach). 20

Altogether, the 46 studies reported on 66 effect sizes relevant to the association between screen time and ASD. There were 3 effect sizes for social media (n = 784), 3 for smartphones (n = 10 344), 5 for computers (n = 48 836), 13 for video games (n = 2137), 14 for television (n = 207 972), and 28 for unspecified screen devices or screen activity (n = 343 047; coded as “general use of screens” in this review). Regarding the age of the researched populations, 37 effect sizes were observed among children aged younger than 12 years (n = 266 474) and 29 effect sizes were observed among adults or heterogenous age groups (n = 346 646).

The meta-analysis of all 66 effect sizes resulted in a significant positive summary effect size (log OR, 0.54 [95% CI, 0.34 to 0.74]; SE = 0.10; P  < .001; τ 2  = 0.58; Q 65  = 6222.68; P  < .001; I 2  = 99.7%) ( Figure 2 and eFigure 1 in Supplement 1 ). A separate meta-analysis of the 6 longitudinal effect sizes only yielded an equivalent summary effect (log OR, 0.65 [95% CI, 0.26 to 1.05]) (eFigure 4 in Supplement 1 ) that did not differ significantly from the aforementioned summary effect size ( Q m  = 0.23; P  = .63).

An Egger Z test for funnel plot asymmetry 24 suggested a significant publication bias (2.15; P  = .03). A trim-and-fill correction for this bias 67 resulted in a substantially decreased and nonsignificant summary effect (log OR, 0.22 [95% CI, −0.004 to 0.44]; P  = .05) ( Figure 3 ).

A further meta-regression indicated that all 3 independent variables entered into the model (ie, screen type, age group, and type of ASD measure) contributed significantly to the overall explained variance ( R 2  = 0.29; τ 2  = 0.03; Q e58  = 2656.55; P  < .001). However, in terms of β coefficients, only screen type had a significant effect size. That is, the β coefficients for general use of screens (β [SE] = 0.73 [0.34]; t 58  = 2.10; P  = .03) and social media use (β [SE] = −1.29 [0.51]; t 58  = −2.50; P  = .01) were significantly different from 0, whereas the effect sizes of television, video games, computers, and smartphones were not statistically significant ( Table 2 ). The association between social media and ASD was negative (log OR, −1.24 [95% CI, −1.51 to −0.96]; Q 2  = 1.76; P  = .41), whereas the association between general use of screens and ASD was positive (log OR, 0.79 [95% CI, 0.55 to 1.03]; Q 27  = 2980.44; P  < .001).

The most prominent cluster in our review comprised studies addressing general screen use ( k  = 28), which also had the largest heterogeneity ( Q 27  = 2980.44; P  < .001; I 2  = 99.67%). To further examine the positive association evidenced only in this cluster, we conducted a second meta-regression analysis that targeted only the 28 effect sizes reported in the general screen use cluster. Results from the mixed-effects model suggested that both remaining moderators contributed significantly to model variance for age group (β [SE] = 0.67 [0.25]; t 25  = 2.69; P  = .001) and ASD measure (β [SE] = 0.79 [0.25]; t 25  = 3.23; P  = .007) ( Table 2 ). Specifically, the effect size for children (log OR, 0.98 [95% CI, 0.66 to 1.29]) was significantly larger than that for adults or heterogenous age groups (log OR, 0.49 [95% CI, 0.19 to 0.79]; Q m  = 3.94; P  = .047) (eFigure 2 in Supplement 1 ). The effect size for the group with an ASD clinical diagnosis (log OR, 0.9 [95% CI, 0.55 to 1.25]) was slightly larger than that for the group with ASD symptoms (log OR, 0.57 [95% CI, 0.32 to 0.82]), but this difference was not significant ( Q m  = 1.14; P  = .29) (eFigure 3 in Supplement 1 ).

The goal of this study was to provide an updated systematic review and, to our knowledge, the first meta-analysis of the literature accumulated on the association between screen time and ASD. This review yielded 46 observational studies (5 longitudinal and 41 cross-sectional) with 66 relevant effect sizes. The first meta-analysis of these effect sizes resulted in a statistically significant, although small, summary effect size suggesting that screen time is indeed associated with ASD. This association seemed to be most dominant within studies addressing general screen use among children aged younger than 12 years.

The primary findings of this study may serve as a preliminary warning that supports existing medical recommendations to limit screen use among young children. 15 This preliminary conclusion corresponds with the few longitudinal studies conducted on this topic to date. 11 , 12 According to these studies and the displacement hypothesis described earlier, infancy and early childhood are highly sensitive developmental stages. Therefore, adult caregivers are advised to monitor their children’s screen time and ensure that it does not come at the expense of positive, real-life experiences and relationships, which are essential for the development of communication and emotional skills.

Nevertheless, our primary findings restrict this preliminary conclusion. First, the observational nature of the available studies limits our ability to determine the direction of the association between screen time and ASD. Second, the literature seems to be characterized by a substantial publication bias that challenges the reliability of the observed summary effect size. In fact, when this bias was considered in the analysis, the summary effect size became negligible and insignificant. These findings suggest that the potential negative outcomes associated with screen use may be less severe than commonly believed, 68 , 69 especially when they are balanced against other factors such as the specific type of screen use.

As our meta-regression results suggest, the observed effect size for screens disappeared in the separate analyses of studies dedicated to the specific effect sizes of television, video games, computers, and smartphones. Moreover, the association between social media and ASD was negative, thus suggesting that some types of screen use may either protect against ASD or be avoided by users with ASD (depending on the direction of the association). This distinction between various types of screen devices and activities is important because it may offer an explanation for the mixed findings in the existing literature, 17 and it might facilitate the development of more nuanced guidelines for parents. 68

Screen use may have both negative and positive outcomes, as described in previous studies. 70 , 71 For example, social media use may have some benefits for children with ASD or ASD symptoms, owing to the engagement in interpersonal associations that typically occurs on these media. 14 This observation replicates, to a certain extent, findings from a related meta-analysis that targeted the association between screen time and language skills. 7 Although so-called background television had negative effect sizes in this meta-analysis, educational programs and co-viewing had positive effect sizes. 7 Correspondingly, some video games may be positively associated with intellectual functioning and school performance 72 - 74 ; some were even developed specifically for children with ASD to provide emotional support and joyful experiences. 75

This research has several limitations. First, the heterogeneity in the methodologies and measurements of the studies introduces inconsistencies into the analysis. Second, the correlational nature of the included studies limits our ability to determine the direction of the association, as mentioned earlier. Third, despite our attempt to control for key moderating variables, multiple other potentially confounding variables, such as socioeconomic factors or parental attitudes, limit our interpretation of the findings. Future, high-quality studies are therefore crucially recommended, preferably using objective screen time measurements, longitudinal and experimental designs (eg, through interventions aimed at reducing screen time and examining its implications on ASD symptoms), and comprehensive control of confounding variables. These studies may help determine whether screen use precedes ASD symptom onset or vice versa, and they may generally contribute to more robust understanding of the complex associations between screen use and ASD.

The results of this systematic review and meta-analysis, including a notable indication for publication bias as well as small and sometimes nonsignificant effect sizes, and the limitations just described suggest that the issue of screen time and ASD is far from being resolved. In fact, the slight superiority (although not statistically significant) of the clinical diagnosis variable over the ASD symptom variable we observed in the meta-regression brings forth the basic obstacle in this field, which relates to the directionality of the association, as discussed at the start of this work. Alongside the displacement hypothesis focused on the potential negative outcomes associated with screens, a large portion of the literature is dedicated to the opposite direction—that is, to the characteristics that draw children with ASD to engage in screen activities. 16 - 18 As concluded in a previous literature review on this topic, children with ASD seem to “show increased interest in screen viewing… [which] begins at a very young age.” 18 (p308) It is also reasonable to assume that parents of children with clinically diagnosed ASD adopt a relatively permissive position regarding their children’s screen use. It is possible, then, that the observed (bidirectional) association of the current meta-analysis reflects this tendency of children with diagnosed ASD, at least to a certain extent, thus requiring us to continue searching for other explanations for the increasing global rates of ASD. Excessive screen time may indeed come at the expense of positive real-life activities and close familial relationships that could increase ASD risk. However, further research is needed to support this concern, as the increase in ASD prevalence may be attributable to a range of medical, environmental, and societal factors. 1 , 3 , 4 , 76 , 77

Accepted for Publication: October 26, 2023.

Published: December 8, 2023. doi:10.1001/jamanetworkopen.2023.46775

Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2023 Ophir Y et al. JAMA Network Open .

Corresponding Author: Yaakov Ophir, PhD, Department of Education, Ariel University, 3 Kiryat Hamada St, Ariel 4070000, Israel ( [email protected] ).

Author Contributions: Dr Ophir and Mr Tikochinski had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Ophir, Rosenberg, Dalyot, Lipshits-Braziler.

Acquisition, analysis, or interpretation of data: Rosenberg, Tikochinski, Dalyot.

Drafting of the manuscript: Ophir, Rosenberg, Tikochinski, Dalyot.

Critical review of the manuscript for important intellectual content: Ophir, Rosenberg, Dalyot, Lipshits-Braziler.

Statistical analysis: Tikochinski.

Administrative, technical, or material support: Rosenberg.

Supervision: Ophir, Rosenberg, Lipshits-Braziler.

Conflict of Interest Disclosures: None reported.

Data Sharing Statement: See Supplement 2 .

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Adverse physiological and psychological effects of screen time on children and adolescents: Literature review and case study

Affiliation.

• 1 Meuhedet Health Services, Jerusalem, Israel. Electronic address: [email protected].
• PMID: 29499467
• DOI: 10.1016/j.envres.2018.01.015

A growing body of literature is associating excessive and addictive use of digital media with physical, psychological, social and neurological adverse consequences. Research is focusing more on mobile devices use, and studies suggest that duration, content, after-dark-use, media type and the number of devices are key components determining screen time effects. Physical health effects: excessive screen time is associated with poor sleep and risk factors for cardiovascular diseases such as high blood pressure, obesity, low HDL cholesterol, poor stress regulation (high sympathetic arousal and cortisol dysregulation), and Insulin Resistance. Other physical health consequences include impaired vision and reduced bone density. Psychological effects: internalizing and externalizing behavior is related to poor sleep. Depressive symptoms and suicidal are associated to screen time induced poor sleep, digital device night use, and mobile phone dependency. ADHD-related behavior was linked to sleep problems, overall screen time, and violent and fast-paced content which activates dopamine and the reward pathways. Early and prolonged exposure to violent content is also linked to risk for antisocial behavior and decreased prosocial behavior. Psychoneurological effects: addictive screen time use decreases social coping and involves craving behavior which resembles substance dependence behavior. Brain structural changes related to cognitive control and emotional regulation are associated with digital media addictive behavior. A case study of a treatment of an ADHD diagnosed 9-year-old boy suggests screen time induced ADHD-related behavior could be inaccurately diagnosed as ADHD. Screen time reduction is effective in decreasing ADHD-related behavior.

Conclusions: Components crucial for psychophysiological resilience are none-wandering mind (typical of ADHD-related behavior), good social coping and attachment, and good physical health. Excessive digital media use by children and adolescents appears as a major factor which may hamper the formation of sound psychophysiological resilience.

Keywords: ADHD; Addiction; Adiposity; Adolescents; Children; Depression; Gaming; Hypertension; Internet; Screen time; Sedentary behavior; Sleep deprivation; Stress.

Copyright © 2018 Elsevier Inc. All rights reserved.

Publication types

• Adolescent Behavior*
• Depression / epidemiology
• Internet / trends
• Screen Time*
• Sleep / physiology

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Screen Time and Youth Health Issues: A Literature Review

• Luis Santos ,
• Richard Reeve

Author Biography

Luis Santos is a secondary Technological Education teacher in the Toronto District School Board. He has a Master of Education from Queen’s University. Luis’ research focuses on Technological Education and teacher collaboration in the classroom. His thesis examined teacher collaboration while implementing an integrated program of mathematics and technology education. 

Richard Reeve is an Associate Professor in  Educational Technology in Teaching and Learning  in the Faculty of Education, Queen’s University in Kingston, Ontario. Dr. Reeve’s research examines the designing of classroom-based uses for technology. In 2016 he co-edited the book  Design as Scholarship: Case Studies from the Learning Sciences . 

Published 2020-10-30

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Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution 3.0 Unported License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access ).

This literature review was undertaken in 2019 with the goal of examining the health effects of screen time exposure on school-aged youth. With the COVID-19 outbreak in early 2020, and the subsequent requirement for many students to learn online, concerns about youth exposure to screens only became more pronounced. Now, more than ever, it is vital that educators—both new and old—consider the effects of screen time exposure. Three databases were accessed for the literature review including EBSCO Education Source, APA (American Psychological Association) PsycNet, and Ovid MEDLINE. The final set of 22 studies were compiled using systematic searches conducted in January 2019 using search terms associated with screen time use among adolescents. The categories of effects that emerged were: (a) physical, (b) behavioural, and (c) psychological. While some of the results of these studies demonstrate small but significant negative correlations between screen time exposure and health effects, and are potentially helpful in understanding screen time associations with the identified factors, in their conclusions authors point out that it is difficult to establish causal connections. Discussion of the results focuses on the potential that familial influences may have in terms of supporting youth in establishing positive screen time behaviours.

Keywords : screen time; well-being; technology; social media; cell phone; digital citizenship   Résumé

Cette revue de la littérature a été entreprise en 2019 dans le but d'examiner les effets sur la santé de l'exposition à l'écran sur les jeunes d'âge scolaire. Avec l'épidémie de COVID-19 au début de 2020 et l'obligation subséquente pour de nombreux étudiants d'apprendre en ligne, les préoccupations concernant l'exposition des jeunes aux écrans ne font que devenir plus prononcées. Aujourd'hui plus que jamais, il est essentiel que les éducateurs, qu'ils soient nouveaux ou anciens, tiennent compte des effets de l'exposition à l'écran. Trois bases de données ont été consultées pour la revue de la littérature, notamment EBSCO Education Source, APA (American Psychological Association) PsycNet, et Ovid MEDLINE. L'ensemble final de 22 études a été compilé à l'aide de recherches systématiques menées en janvier 2019 à l'aide de termes de recherche associés à l'utilisation du temps d'écran chez les adolescents. Les catégories d'effets qui ont émergé étaient: (a) physiques; (b) comportemental; et (c) psychologique. Bien que certains des résultats de ces études démontrent des corrélations négatives faibles mais significatives entre l'exposition au temps d'écran et les effets sur la santé, et sont potentiellement utiles pour comprendre les associations du temps d'écran avec les facteurs identifiés, dans leurs conclusions, les auteurs soulignent qu'il est difficile d'établir des liens de causalité. La discussion des résultats se concentre sur le potentiel que les influences familiales peuvent avoir pour ce qui est d'aider les jeunes à adopter des comportements positifs à l'écran. 

Mots-clés : temps d'écran; bien-être; technologie; médias sociaux; téléphone mobile; citoyenneté numérique 

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The health effects of screen time on children: A research roundup

This research roundup looks at the effects of screen time on children’s health.

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This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License .

by Chloe Reichel, The Journalist's Resource May 14, 2019

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This research roundup, originally published in May 2019, has been updated to include a recent systematic review and meta-analysis looking at the effects of screen time on academic performance.

Gone are visions of idyllic childhoods spent frolicking in fields and playing in pastures; for many kids, green grass has been replaced with smartphone screens.

In fact, recent research finds that 63% of kids in the U.S. spend over two hours a day on recreational screen time .

This is in spite of official guidelines from the American Academy of Pediatrics, which recommends less than one hour per day of screen time for children between the ages of 2 and 5, and, for older children, “consistent limits” on screen time and prioritization of sleep, physical activity and other healthy behaviors over media use. Just last month the World Health Organization issued guidelines on the subject, stressing that children between the ages of 2 and 4 should have no more than one hour of screen time per day.

The ubiquity of screens and their prominence in everyday life has drawn criticism and concerns, with Microsoft veteran and philanthropist Melinda Gates writing about not being “prepared for smartphones and social media” as a parent and news headlines questioning whether smartphones have “ destroyed a generation .”

But what does the research say? This roundup looks at the effects of screen time on children’s health. Studies range from childhood to adolescence and focus on topics including sleep, developmental progress, depression and successful interventions to reduce screen time.

Screen-Time is Associated with Inattention Problems in Preschoolers: Results from the CHILD Birth Cohort Study Tamana, Sukhpreet K.; et al. PLOS ONE , April 2019.

This study analyzes parent-reported data about screen time and behavioral issues such as inattention and aggressiveness for a sample of 2,322 Canadian preschool-age children. Researchers found that over 13% of kids in the sample were exposed to over two hours of screen time each day including watching TV and DVDs, playing video games or using a computer, tablet or mobile device. The effects: Kids who were exposed to more screen time “showed significantly increased behavior problems at five-years,” the authors write. “Briefly, children who watched more than 2 hours of screen time/day had increased externalizing [e.g., attention and behavior], internalizing [e.g., anxiety and depression], and total behavior problems scores compared to children who watched less than 20 minutes.” Attention problems in particular were apparent in children who had over two hours of screen time each day.

Mobile Media Device Use is Associated with Expressive Language Delay in 18-Month-Old Children van den Heuvel, Meta; et al. Journal of Developmental & Behavioral Pediatrics , 2019.

Toddlers who use mobile devices daily are more likely to experience speech delays, according to an analysis of parent-reported data on 893 children in the greater Toronto area of Canada. While 78% of parents said their kids spent no time on mobile devices, the other 22% reported a range of 1.4 to 300 minutes daily, with a median of 15.7 minutes.

In total, 6.6% of parents reported expressive speech delays (i.e., late to begin talking). The prevalence of other communication delays, such as lack of use of gestures and eye gaze, was 8.8%. The researchers found a positive association between mobile device use and expressive speech delays. “An increase in 30 minutes per day in mobile media device use was associated with a 2.3 times increased risk of parent-reported expressive speech delay,” the authors write. Other communication delays were not linked to device use. The researchers suggest the connection between device use and expressive speech delays might be explained by the fact that past research has shown infants “have difficulty applying what they learn across different contexts.” An alternate explanation is that these children who spend more time with devices might have less exposure to speech from caregivers.

Association Between Screen Time and Children’s Performance on a Developmental Screening Test Madigan, Sheri; et al. JAMA Pediatrics , March 2019.

Is screen time detrimental to child development? This study looks at data collected from 2,441 mothers and children in Canada at three different time points – when the children were 2, 3 and 5 years old. The researchers were interested in the total number of hours the children spent looking at screens each week as well as their progress in various developmental areas such as fine motor skills, communication and problem solving. The average amount of screen time for the age groups in the study: 17, 25 and 11 hours of television per week for 2-, 3-, and 5-year olds, respectively.

The researchers found that kids who spent more time watching screens at ages 2 and 3 did worse on developmental tests at the subsequent time points of 3 and 5 years. “To our knowledge, the present study is the first to provide evidence of a directional association between screen time and poor performance on development screening tests among very young children,” the authors write.

The researchers suggest that excessive screen time leads to developmental delays, rather than the other way around – negating the notion that children with developmental delays might receive more screen time to manage their behavior.

The three phase data capture supports this explanation because children with greater screen time at one time point go on at the next time point to have poorer developmental progress, but children with poor developmental performance at an earlier time point do not receive increased screen time at later time points.

Association Between Screen Media Use and Academic Performance Among Children and Adolescents Adelantado-Renau, Mireia; et al. JAMA Pediatrics , September 2019.

This publication consists of both a systematic review and meta-analysis of research on the relationship between screen time and academic performance. The authors identified 58 studies to include in the systematic review, which provides a summary of the qualitative effects of screen time; 30 of these studies were included in the subsequent meta-analysis, which the authors used to calculate the effect size of screen time on academic performance.

The 58 studies in the systematic review included 480,479 participants ranging from four to 18 years of age. The articles were published between 1958 and 2018 and represent the efforts of researchers around the world. The studies looked at computer, internet, mobile phone, television and video game use individually, as well as overall screen time. Outcomes of interest included school grades, performance on academic achievement tests, academic failure data, or self-reported academic achievement or school performance.

The key finding from the systematic review was that in most of the papers reviewed, as time spent watching television increased, academic performance suffered. Relationships were less clear-cut for other types of screen use.

The meta-analysis, which focused on a subset of 106,653 participants from the larger sample, did not find an association between overall screen time and academic performance. When the authors analyzed the data by type of activity, they found television watching was linked to poorer overall academic performance as well as poorer language and mathematics performance, separately. Time spent playing video games was negatively linked with composite academic performance scores, too. Analyzing the data further by age, the authors found that time spent with screens had a larger negative association with academic performance for adolescents than children.

“The findings from this systematic review and meta-analysis suggest that each screen-based activity should be analyzed individually because of its specific association with academic performance,” the authors conclude. “This study highlights the need for further research into the association of internet, computer, and mobile phone use with academic performance in children and adolescents. These associations seem to be complex and may be moderated and/or mediated by potential factors, such as purpose, content, and context of screen media use.”

The authors suggest that educators and health professionals should focus screen time reduction efforts on television and video games for their negative connections to academic performance and potential health risks due to their sedentary nature.

Screen Time Is Associated with Adiposity and Insulin Resistance in Children Nightingale, Claire M.; et al. Archives of Disease in Childhood , July 2017.

This study looks at the relationship between screen time and Type 2 diabetes risk factors, like being severely overweight, among 4,495 schoolchildren in the United Kingdom between the ages of 9 and 10. The short of it: Kids who spent over three hours daily on screen time were less lean and more likely to show signs of insulin resistance, which can contribute to the development of Type 2 diabetes, compared with their peers who reported one hour or less of screen time each day. Black children were more likely to spend over three hours daily on devices compared with their white and south Asian peers – 23% of black children fell into that group, compared with 16% of white children and 16% of south Asian children.

Digital Media and Sleep in Childhood and Adolescence LeBourgeois, Monique K.; et al. Pediatrics , November 2017.

This report summarizes 67 studies looking at associations between screen time and sleep health – adequate sleep length and quality — in children and adolescents. The main takeaways: A majority (90%) of the studies included in a systematic review of research on screen time in children and teenagers found adverse associations between screen time and sleep health – primarily because of later bedtimes and less time spent sleeping. Delving deeper, underlying mechanisms include “time displacement” (think scrolling Instagram for an hour that might otherwise be spent sleeping), psychological stimulation from content consumed and impacts of screen light on sleep patterns. The upshot? These kids are tired. The previously cited research review also indicates that a majority of studies saw a relationship between tiredness and screen time.

Prevalence and Likelihood of Meeting Sleep, Physical Activity, and Screen-Time Guidelines Among US Youth Knell, Gregory; et al. JAMA Pediatrics , April 2019.

This study analyzes data from the 2011, 2013, 2015 and 2017 cycles of a nationally-administered, school-based survey on various health-related behaviors related to the leading causes of death and disability in the U.S. The researchers were interested in whether respondents met the recommendations for time spent on sleep, physical activity and screen time in a given day. A total of 59,397 adolescents were included in the data set.

The findings indicate that only 5% of adolescents surveyed met all three guidelines – that is, getting the recommended amount of sleep and physical activity and limiting screen time to less than two hours per day. There were disparities among the sample in terms of the odds of meeting all of the recommendations: 16- and 17-year-olds were less likely than those aged 14 and younger to meet all the guidelines; black, Hispanic/Latino and Asian participants were less likely to meet the three guidelines than white participants; overweight and obese participants were less likely to meet the guidelines than normal weight participants; participants who reported marijuana use were less likely to meet the guidelines than those who did not. Participants who reported depressive symptoms were also less likely to meet all the guidelines.

Associations Between 24 Hour Movement Behaviors and Global Cognition in US Children: A Cross-Sectional Observational Study Walsh, Jeremy J.; et al. The Lancet Child & Adolescent Health , November 2018.

This study looks at the same three outcomes examined above, but adds another component – “global cognition.” This is an overall cognition score assessed by the National Institutes of Health Toolbox – an iPad-based neuro-behavioral screening tool. The assessment measures various cognitive functions including memory, attention, vocabulary and processing speed. The sample included 4,520 participants between the ages of 8 and 11. Only 5% of participants met all three recommendations – and they were the better for it. “Compared with meeting none of the recommendations, associations with superior global cognition were found in participants who met all three recommendations, the screen time recommendation only, and both the screen time and the sleep recommendations,” the authors write.

Increases in Depressive Symptoms, Suicide-Related Outcomes, and Suicide Rates Among U.S. Adolescents After 2010 and Links to Increased New Media Screen Time Twenge, Jean M.; et al. Clinical Psychological Science , January 2018.

This study looks at the relationship between screen time and depression and suicide rates in 506,820 adolescents in the U.S. between 2010 and 2015. The data on screen time use and mental health issues came from two nationally representative surveys of students in grades 8 through 12. Suicide rates were calculated from national statistics collected by the Centers for Disease Control and Prevention’s Fatal Injury Reports.

The analysis finds a “clear pattern linking screen activities with higher levels of depressive symptoms/suicide-related outcomes [suicidal ideation — that is, thinking about suicide — and attempts] and nonscreen activities with lower levels.” Among participants who used devices for over five hours each day, nearly half – 48% — reported at least one suicide-related outcome. In comparison, 29% of those who used devices for just an hour per day had at least one suicide-related outcome.

Overall, during the time studied, suicide rates, depressive symptoms and suicide-related outcomes increased. Girls accounted for most of the rise – they were more likely to experience depressive symptoms and suicide-related outcomes than boys; they also experienced stronger effects of screen time on mental health. In particular, girls, but not boys, had a significant correlation between social media use and depressive symptoms.

Interventions Designed to Reduce Sedentary Behaviors in Young People: A Review of Reviews Biddle, Stuart J.H.; Petrolini, Irene; Pearson, Natalie. British Journal of Sports Medicine , 2014.

This review looks at 10 systematic reviews and meta-analyses of research on interventions to reduce sedentary behaviors such as screen time among children and adolescents. The authors found that all of the included reviews determined “some level of effectiveness in reducing time spent in sedentary behavior.” Effects, however, were small. Interventions tended to be more successful among children younger than 6 years old. Strategies that were effective included restricting access to television through TV monitors, systems that use TV as a reward for physical activity and behavioral interventions such as setting goals and developing schedules for screen time.

For more research on the effects of screen time, check out our write ups of research that shows how smartphones make people unhappy and how they’re distracting even when they aren’t in use .

About The Author

Chloe Reichel

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Adolescents' screen time, sleep and mental health: literature review

Systematic review summarising the published experimental and longitudinal evidence on adolescent screen time, sleep and mental health.

This document is part of a collection

• Mental health social research reports

The objective of this systematic review was to summarise the published experimental and longitudinal evidence on adolescent mobile device screen time or use, and the association with sleep and mental health and wellbeing. Five research questions guided this review which included evidence from quantitative and qualitative studies conducted in Western countries classified as high-income by the World Bank.

Key findings

• The body of evidence based on longitudinal or experimental studies is very small: nine quantitative studies and two qualitative studies.
• The quality of individual studies was low and they lacked detailed descriptions of methodology, limiting assessment of risk of bias. This means findings and conclusions should be interpreted with caution.
• The body of evidence is incomplete. There were various types of mobile device screen use ( e.g. time spent using a mobile device, social media use) and various outcomes ( e.g. sleep duration, sleep quality), and only one or two studies that assessed each exposure/outcome relationship, making it difficult to draw conclusions beyond these individual studies.

1. To what extent does adolescents' mobile device screen time impact on sleep outcomes?

• Mobile phone use around bedtime and cybervictimisation, but not the overall time spent engaging in mobile phone activities per se (at any time of the day), was linked to lower sleep duration.
• Sleep quality was negatively influenced by mobile phone use in general and social media use in particular.
• Experiencing pressure to engage socially using a mobile phone was associated with poor bedtime behaviours that might promote poor sleep quality ( i.e. sleep hygiene).
• Stopping phone use one hour before bedtime was not linked to earlier sleep.
• One pilot study (a small scale, preliminary study) showed that use of a smartphone app (under development) that teaches about the importance of consistent sleep and wake times, and recommended bedtimes was associated with a potential improvement in sleep duration, sleep quality and earlier sleep onset.

2. What are the potential causal mechanisms through which mobile device screen time affects sleep outcomes amongst adolescents?

• Experiences of cybervictimisation were indirectly associated with sleeping less than the recommended 8 hours per night. The factor linking cybervictimisation with shorter sleep was repetitively thinking and obsessing about distressing thoughts, emotions, and memories
• Other potential mechanisms through which mobile device screen time or use affect sleep outcomes are: sleep displacement ( i.e. using the phone instead of sleeping), delaying sleep time, increased alertness through blue light exposure, psychological arousal which can result in bodily responses ( e.g. faster heart beat) through binge watching and/or watching violent or upsetting content.

3. What are the implications of the potential impact of mobile device screen time on sleep for adolescents' mental health and wellbeing?

• Night-time mobile use and problematic social media use were linked to depressed mood through experiences of poor-quality sleep. Poor sleep quality also played a role in the link between night-time mobile phone use and low self-esteem, poor coping skills and higher externalising behaviour ( e.g. disobeying rules, physical aggression).
• One pilot study showed that use of a smartphone app (under development) that teaches healthy sleep habits was associated with potentially lower depressive symptoms and reduced anxiety.

4. To what extent might girls' and boys' differential mobile device screen time, and its relationship with sleep, contribute to inequalities in mental health and wellbeing by gender?

• None of the included quantitative studies reported separate data for boys' and girls' mobile device screen time or use and its relationship with sleep that in turn might contribute to inequalities in mental health and wellbeing for boys and girls.
• In August 2019, a new eligible study was published which we did not include in our evidence synthesis because of its availability after we had completed our literature search.
• The study found that using social media multiple times daily when aged 13-15 predicted lower life satisfaction, lower happiness, and higher anxiety among girls 1- to 2-years later but not among boys.
• It also found that sleeping less than 8 hours per night, not being physically active most days, and experiencing cyberbullying play a detrimental role in the association between social media use and lower wellbeing in girls only.

5. What existing evidence is there on adolescents' views of how mobile device screen time affects their sleep, and following on from this, their mental health and wellbeing?

• In the qualitative studies both adolescent boys and girls reported using smartphones in bed and recognised that it may negatively affect their sleep.
• Adolescents felt that sleep issues were connected to the content in video games rather than their use.
• Boys were more likely to report trying to follow guidelines ( e.g. putting electronics away one-hour pre-bedtime) whilst girls suggested they specifically used their mobile screen devices as a tool to aid sleep ( e.g. listening to music).
• No study asked young people directly about their view of the relationship between sleep and mental health. However, when young people thought about the importance of sleep they mentioned the 'energising, relaxing, stress-reducing and restorative qualities of sleep'.
• No study asked young people explicitly about the connections between screen use, sleep and mental health and wellbeing.

Recommendations

Policy and practice initiatives could target all or a combination of the identified modifiable factors within the causal pathway between mobile device screen exposures and impaired sleep, but the current evidence severely limits the recommendations that can be made. Only one study provided suitable data to explore potential causal mechanisms through which mobile device exposure influences sleep outcomes. It suggests:

• Young people should be protected from cybervictimisation and mandatory requirements of social media platforms to develop algorithms that block aggressive and upsetting content could be put in place. Education around the impact of cybervictimisation and how to avoid it ( e.g. adequate privacy settings) could be embedded in the school curriculum.
• Repetitively thinking and obsessing about distressing thoughts, emotions, and memories as a consequence of cybervictimisation could potentially be targeted by initiatives that strengthen resilience in adolescents, in particular teaching young people and their parents healthy coping strategies ( e.g. help seeking and sharing thoughts/emotions, mindfulness).

Further research investigating the causal relationship between mobile device screen use, impaired sleep and mental health and wellbeing is needed. Therefore, future research studies should use multiple time points of mobile device screen use, sleep and mental health data.

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Screen Time: What and How Much is Too Much?

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We are on screens on all the time, as faculty members in Computer Science and as human beings in a technologically developed society. Screens come in all form factors, from the mobile phone that has us wrapped around it continually, to multiple monitors at work, to surrounding gigantic screens for consuming our entertainment. This large amount of screen time has raised alarm bells — from our ability to focus and think deep thoughts to our mental health. I got to thinking about this in a navel-gazing exercise after recently having to sit down and read about 20 papers and 5 proposals for reviewing, in an intense contiguous period of five days because I was running up against deadlines. It stretched my ability to keep screen distractions away. So I will contemplate on two questions here.

• What constitutes screen time? This is not obvious — my layers of monitors at work where I use them to look at visualization do not constitute screen time, my Kindle reading of a magazine arguably does not, and then there are obvious ones that do like scrolling through the unending social media messages.
• How much screen time is too much? This is not obvious — different folks have different tolerances and the tolerance varies depending on other factors going on in our lives, like what time pressures we have, how we are multi-tasking as we are getting such screen time.

Spoiler alert: I give no definitive answers based on a scientific study with many people. I give my subjective take based on a small sample set.

What is screen time?

Here I am not using the term “screen time” in the obvious physical sense of looking at a screen, but rather for the kind of activity that we should limit. One obvious way to demarcate this is to say anything that we do for work is not screen time. But this is a little too convenient. We look through Twitter at work ostensibly for keeping up with our professional networks. We look at YouTube videos on work topics. Much of that to me is screen time.

Where I come down is that we look at screen for work-related activities, broadly defined, that does not count as screen time. As I read some technology article say on BBC or MIT Tech Review, which is only tangentially related to work, I am folding all that in to this category, a little too conveniently. And taking the converse, screen time is what I do that is completely optional for my work.

Then there is a subtle classification, both of which is screen time. One is individual and the other is communal, or more relevantly, family screen time. Purists would scowl but I think the latter is a pragmatic reality and needs to be tolerated, if not embraced. I think back to my childhood days crowding around our television as a family for some memorable programs, all on the government-run Doordarshan, the single channel available to us. The fact that I remember the pleasantness, even joy, of some of those shared moments is a good argument for the family screen time.

What’s the screen time allowance?

First let us look at what the experts tell us. The American Academy of Pediatrics recommends two hours per day for teens and adults — yes they may be pediatricians but they are still medical professionals and know what to tell us adults. The more nuanced message is that it is not just the time, but the content we are consuming that also matters [ WWW ]. This kind of message I can get behind.

The ill effects of excessive screen time are enough to strike terror into the hearts of even those workaholics who go about bragging how they are always working on their screens. To quote from a Time magazine article aptly titled “Experts Can’t Agree on How Much Screen Time Is Too Much for Adults” (May 2022):

“Excessive screen time has been shown to have negative effects on children and adolescents. It’s been linked to psychological problems, such as higher rates of depression and anxiety, as well as health issues like poor sleep and higher rates of obesity . Many researchers believe that excessive screen use may not be as damaging to adults, but the impact hasn’t been studied as extensively. Recent research has found that it can still have damaging consequences, such as digital eye strain , impaired sleep , and worsened mental health. “

OK, with all the bad news out of the way in this succinct summary, let us get back to the question of what type of screen time is really bad, what is bad, and what may be OK, in moderation or as Buddha would have it “The Middle Path” (in Sanskrit, “मध्यमप्रतिपादः”).

The OK Type of Screen Time

I find that reading an article, one not related to work, if it calls for me to read for some length of time, say more than 5 minutes, without being drawn into a warren of hyperlinks is the OK type. This takes various forms—reading a New York Times or a Wall Street Journal article, reading a post on Medium or The Conversation, or at the longest end of the spectrum, reading a book on Kindle. Well, I have never read one end-to-end in one sitting; reading a chapter or two at a stretch counts toward that.

The Bad Type of Screen Time

As much of a fan of BBC News I am, I have to say reading the news snippets on BBC’s News site, and going from one to the next, in manifestation of a voracious reading appetite is the Bad Type. Now BBC has many long form articles, in sections such as BBC Innovation and BBC Culture, which take me on surprising journeys and make me think. They definitely fall in the OK kind. So back to the Bad Type, in general scrolling through news article one after another, and face it, much of it is bad news, falls in this category.

The Really Bad Type of Screen Time

No suspense here. Scrolling through social media posts, filled with an alluring mishmash of text, images, video, sounds, a veritable assault on the senses, is the worst kind of screen time. I wish my scrolling through Twitter did not fall in this category, as that is supposedly for finding what my professional colleagues are cooking up in terms of latest discoveries. But sadly it does. Don’t we feel counter-intuitively that after a few tens of minutes of scrolling through social media content that we are drained of energy. So while many billions of dollars worth of market valuation depends on our compulsive urge to meander through miles of rabbit holes like possessed souls, that is the really bad kind of screen time.

The Bottom Line

I know I am doing the right kind of screen time when I give myself the freedom to switch off and ponder over what I have consumed and when that pondering generates some train of thought. So wandering in rabbit holes may not be bad after all, if we do not go too deep and the wandering is done as we are thinking rather than when we are consuming screen content. And even that right kind of screen time needs to be moderated, so we are leaving enough time for our professional development and for stepping outside in this balmy 70 degree February afternoon in the mid west. The clear blue sky with specks of clouds in fantastical shapes is a screen of a kind, just of cosmic proportions.

Saurabh Bagchi is a professor of Electrical and Computer Engineering and Computer Science at Purdue University, where he leads a university-wide center on resilience called CRISP. His research interests are in distributed systems and dependable computing, while he and his group have the most fun making and breaking large-scale usable software systems for the greater good.

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Once Upon a Time, the World of Picture Books Came to Life

The tale behind a new museum of children’s literature is equal parts imagination, chutzpah and “The Little Engine That Could.”

By Elisabeth Egan

Photographs and Video by Chase Castor

Elisabeth Egan followed the Rabbit Hole as it was nearing completion. She has written about several of its inhabitants for The Times.

On a crisp Saturday morning that screamed for adventure, a former tin can factory in North Kansas City, Mo., thrummed with the sound of young people climbing, sliding, spinning, jumping, exploring and reading.

Yes, reading.

If you think this is a silent activity, you haven’t spent time in a first grade classroom. And if you think all indoor destinations for young people are sticky, smelly, depressing hellholes, check your assumptions at the unmarked front door.

Welcome to the Rabbit Hole, a brand-new, decade-in-the-making museum of children’s literature founded by the only people with the stamina for such a feat: former bookstore owners. Pete Cowdin and Deb Pettid are long-married artists who share the bullish determination of the Little Red Hen. They’ve transformed the hulking old building into a series of settings lifted straight from the pages of beloved picture books.

Before we get into what the Rabbit Hole is, here’s what it isn’t: a place with touch screens, a ball pit, inscrutable plaques, velvet ropes, a cloying soundtrack or adults in costumes. It doesn’t smell like graham crackers, apple juice or worse (yet). At $16 per person over 2 years old, it also isn’t cheap.

During opening weekend on March 16, the museum was a hive of freckles and gap toothed grins, with visitors ranging in age from newborn to well seasoned. Cries of “Look up here!,” “There’s a path we need to take!” and “There’s Good Dog Carl !” created a pleasant pandemonium. For every child galloping into the 30,000 square foot space, there was an adult hellbent on documenting the moment.

Did you ever have to make a shoe box diorama about your favorite book? If so, you might remember classmates who constructed move-in ready mini kingdoms kitted out with gingham curtains, clothespin people and actual pieces of spaghetti.

Cowdin, Pettid and their team are those students, all grown up.

The main floor of the Rabbit Hole consists of 40 book-themed dioramas blown up to life-size and arranged, Ikea showroom-style, in a space the size of two hockey rinks. The one inspired by John Steptoe’s “ Uptown ” features a pressed tin ceiling, a faux stained-glass window and a jukebox. In the great green room from “ Goodnight Moon ,” you can pick up an old-fashioned phone and hear the illustrator’s son reading the story.

One fictional world blends into the next, allowing characters to rub shoulders in real life just as they do on a shelf. Visitors slid down the pole in “The Fire Cat,” slithered into the gullet of the boa constrictor in “ Where the Sidewalk Ends ” and lounged in a faux bubble bath in “ Harry the Dirty Dog .” There are plenty of familiar faces — Madeline , Strega Nona , Babar — but just as many areas dedicated to worthy titles that don’t feature household names, including “ Crow Boy ,” “ Sam and the Tigers ,” “ Gladiola Garden ” and “ The Zabajaba Jungle .”

Emma Miller, a first-grade teacher, said, “So many of these are books I use in my classroom. It’s immersive and beautiful. I’m overwhelmed.”

As her toddler bolted toward “ Frog and Toad ,” Taylar Brown said, “We love opportunities to explore different sensory things for Mason. He has autism so this is a perfect place for him to find little hiding holes.”

A gaggle of boys reclined on a bean bag in “ Caps for Sale ,” passing around a copy of the book. Identical twins sounded out “ Bread and Jam for Frances ” on the pink rug in the badger’s house. A 3-year-old visiting for the second time listened to her grandfather reading “The Tawny Scrawny Lion.”

Tomy Tran, a father of three from Oklahoma, said, “I’ve been to some of these indoor places and it’s more like a jungle gym. Here, my kids will go into the area, pick up the book and actually start reading it as if they’re in the story.”

All the titles scattered around the museum are available for purchase at the Lucky Rabbit, a bookstore arranged around a cozy amphitheater. Pettid and Cowdin estimate that they’ve sold one book per visitor, with around 650 guests per day following the pink bunny tracks from the parking lot.

Once upon a time, Cowdin and Pettid owned the Reading Reptile, a Kansas City institution known not just for its children’s books but also for its literary installations. When Dav Pilkey came to town, Pettid and Cowdin welcomed him by making a three-and-a-half foot papier-mâché Captain Underpants. Young customers pitched in to build Tooth-Gnasher Superflash or the bread airplane from “In the Night Kitchen.”

One of the store’s devotees was Meg McMath, who continued to visit through college, long after she’d outgrown its offerings (and its chairs). Now 36, McMath traveled from Austin, Texas with her husband and six-month-old son to see the Rabbit Hole. “I’ve cried a few times,” she said.

The Reading Reptile weathered Barnes & Noble superstores and Amazon. Then came “the Harry Potter effect,” Pettid said, “where all of a sudden adults wanted kids to go from picture books to thick chapter books. They skipped from here to there; there was so much they were missing.”

As parents fell under the sway of reading lists for “gifted” kids, story time became yet another proving ground.

“It totally deformed the reading experience,” Cowdin said. Not to mention the scourge of every bookstore: surreptitious photo-snappers who later shopped online.

In 2016, Cowdin and Pettid closed the Reptile to focus on the Rabbit Hole, an idea they’d been percolating for years. They hoped it would be a way to spread the organic bookworm spirit they’d instilled in their five children while dialing up representation for readers who had trouble finding characters who looked like them. The museum would celebrate classics, forgotten gems and quality newcomers. How hard could it be?

Cowdin and Pettid had no experience in the nonprofit world. They knew nothing about fund-raising or construction. They’re ideas people, glass half full types, idealists but also stubborn visionaries. They didn’t want to hand their “dream” — a word they say in quotes — to consultants who knew little about children’s books. Along the way, board members resigned. Their kids grew up. Covid descended. A tree fell on their house and they had to live elsewhere for a year. “I literally have told Pete I quit 20 times,” Pettid said.

“It has not always been pleasant,” Cowdin said. “But it was just like, OK, we’re going to do this and then we’re going to figure out how to do it. And then we just kept figuring it out.”

Little by little, chugging along like “ The Little Engine That Could ,” they raised $15 million and assembled a board who embraced their vision and commitment to Kansas City. They made a wish list of books — “Every ethnicity. Every gender. Every publisher,” Pettid said — and met with rights departments and authors’ estates about acquiring permissions. Most were receptive; some weren’t. (They now have rights to more than 70 titles.)

“A lot of people think a children’s bookstore is very cute,” Pettid said. “They have a small mind for children’s culture. That’s why we had to buy this building.”

For $2 million, they bought the factory from Robert Riccardi, an architect whose family operated a beverage distribution business there for two decades. His firm, Multistudio, worked with Cowdin and Pettid to reimagine the space, which sits on an industrial corner bordered by train tracks, highways and skyline views.

Cowdin and Pettid started experimenting with layouts. Eventually they hired 39 staff members, including 21 full-time artists and fabricators who made everything in the museum from some combination of steel, wood, foam, concrete and papier-mâché.

“My parents are movers and shakers,” Gloria Cowdin said. She’s the middle of the five siblings, named after Frances the badger’s sister — and, yes, that’s her voice reading inside the exhibit. “There’s never been something they’ve wanted to achieve that they haven’t made happen, no matter how crazy.”

During a sneak peek in December, it was hard to imagine how this semi-construction zone would coalesce into a museum. The 22,000 square foot fabrication section was abuzz with drills and saws. A whiteboard showed assembly diagrams and punch lists. (Under “Random jobs,” someone had jotted, “Write Christmas songs.”) The entryway and lower level — known as the grotto and the burrow — were warrens of scaffolding and machinery.

But there were pockets of calm. Kelli Harrod worked on a fresco of trees outside the “ Blueberries for Sal ” kitchen, unfazed by the hubbub. In two years as lead painter, she’d witnessed the Rabbit Hole’s steady growth.

“I remember painting the ‘ Pérez and Martina ’ house before there was insulation,” Harrod said. “I was bundled up in hats, gloves and coats, making sure my hands didn’t shake.”

Leigh Rosser was similarly nonplused while describing his biggest challenge as design fabrication lead. Problem: How to get a dragon and a cloud to fly above a grand staircase in “ My Father’s Dragon .” Solution: “It’s really simple, conceptually” — it didn’t sound simple — “but we’re dealing with weight in the thousands of pounds, mounted up high. We make up things that haven’t been done before, or at least that I’m not aware of.”

Attention to detail extends to floor-bound exhibits. The utensil drawer in “Blueberries for Sal” holds Pete Cowdin’s mother’s egg whisk alongside a jar containing a baby tooth that belonged to Cowdin and Pettid’s oldest daughter, Sally. The tooth is a wink at “ One Morning in Maine ,” an earlier Robert McCloskey book involving a wiggly bicuspid — or was it a molar? If dental records are available, Cowdin and Pettid have consulted them for accuracy.

“With Pete and Deb, it’s about trying to picture what they’re seeing in their minds,” said Brian Selznick , a longtime friend who helped stock the shelves in the Lucky Rabbit. He’s the author of “ The Invention of Hugo Cabret ,” among many other books.

Three months ago, the grotto looked like a desert rock formation studded with pink Chiclets. The burrow, home of Fox Rabbit, the museum’s eponymous mascot, was dark except for sparks blasting from a soldering iron. The floor was covered with tiny metal letters reclaimed from a newly-renovated donor wall at a local museum.

Cowdin and Pettid proudly explained their works-in-progress; these were the parts of the museum that blossomed from seed in their imaginations. But to the naked eye, they had the charm of a bulkhead door leading to a scary basement.

When the museum opened to the public, the grotto and the burrow suddenly made sense. The pink Chiclets are books, more than 3000 of them — molded in silicone, cast in resin — incorporated into the walls, the stairs and the floor. They vary from an inch-and-a-half to three inches thick. As visitors descend into the Rabbit Hole, they can run their fingers over the edges of petrified volumes. They can clamber over rock formations that include layers of books. Or they can curl up and read.

Dennis Butt, another longtime Rabbit Hole employee, molded 92 donated books into the mix, including his own copies of “ The Hobbit ” and “ The Lord of the Rings .” He said, “They’re a little piece of me.”

As for the metal letters, they’re pressed into the walls of a blue-lit tunnel leading up a ramp to the first floor. They spell the first lines of 141 books, including “ Charlotte’s Web ,” “Devil in the Drain” and “ Martha Speaks .” Some were easier to decipher than others, but “Mashed potatoes are to give everybody enough” jumped out. It called to mind another line from “A Hole is to Dig,” Ruth Krauss’s book of first definitions (illustrated by a young Maurice Sendak ): “The world is so you have something to stand on.”

At the Rabbit Hole, books are so you have something to stand on. They’re the bedrock and the foundation; they’re the solid ground.

Cowdin and Pettid have plans to expand into three more floors, adding exhibit space, a print shop, a story lab, a resource library and discovery galleries. An Automat-style cafeteria and George and Martha -themed party and craft room will open soon. A rooftop bar is also in the works.

Of course, museum life isn’t all happily ever after. Certain visitors whined, whinged and wept, especially as they approached the exit. One weary adult said, “Charlie, we did it all.”

Then, “Charlie, it’s time to go.”

And finally, “Fine, Charlie, we’re leaving you here.” Cue hysteria.

But the moral of this story — and the point of the museum, and maybe the point of reading, depending on who you share books with — crystallized in a quiet moment in the great green room. A boy in a Chiefs Super Bowl T-shirt pretended to fall asleep beneath a fleecy blanket. Before closing his eyes, he said, “Goodnight, Grandma. Love you to the moon.”

Elisabeth Egan is a writer and editor at the Times Book Review. She has worked in the world of publishing for 30 years. More about Elisabeth Egan

The Great Read

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The Pants Pendulum: Around 2020, the “right” pants began to swing from skinny to wide. But is there even a consensus around trends anymore ?

The Psychic Peril of Mars: NASA is conducting tests on what might be the greatest challenge of a human mission to the red planet: the trauma of isolation .

Saved by a Rescue Dog: He spent 13 years addicted to cocaine. Running a shelter for abused and neglected dogs in New York has kept him sober, but it hasn’t been easy .

An Art Mogul's Fall: After a dramatic rise in business and society, Louise Blouin finds herself unloading a Hamptons dream home in bankruptcy court .

Rancho Santa Fe resident helps people manage screen time to prevent adverse effects

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After leaving her teaching job with the San Diego Unified School District about six years ago, Rancho Santa Fe resident Nicole Rawson launched Screen Time Clinic, which helps address the adverse effects of all the time people are spending staring at their phones and other devices.

Rawson was one of the speakers and co-hosts of an April 11 workshop at BioLabs in Sorrento Valley.

“Everything is very self-taught and easy to use, but if we’re not careful it can really overtake us,” she said.

As a teacher, Rawson said she had a firsthand look at the mental health impacts students are prone to experiencing as a result of excessive screen time.

Apps and other tools and techniques have become increasingly popular to help smartphone users regulate their screen time, and to help parents monitor their childrens’ usage.

But, Rawson said, “Overall, we’re in the do it yourself era of tech regulation.”

Some families have also resorted to filing lawsuits against some of the social media giants, such as Facebook parent company Meta, TikTok and Snapchat, over allegations that they caused conditions ranging from anxiety and depression to eating disorders in children.

One of Rawson’s first efforts in addressing screen time was authoring a book, “Screen Smart Sam,” based in part on her own experiences trying to manage her son’s screen time. Since then, Screen Time Clinic has been working to create “digital wellness educators” who can help their friends, family, co-workers and other parts of their communities manage the challenges that come with screen time.

A growing amount of media attention and research is being devoted to the side effects of screen time and how it rewires the human brain.

“There are tons of brain-body connections to what you’re seeing online,” Rawson said, “and it’s being reinforced over and over and over by the content that you’re viewing, and the algorithms continue to feed them that because that kind of content is engaging.”

For more information, visit screentimeclinic.com

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After the solar eclipse: Eyesight blurry? What are the symptoms of eclipse blindness? What to look for

The 2024 solar eclipse brings a rare event to ohio, but safe viewing is essential to avoid "eclipse blindness" and what could become permanent eye damage..

Ohio will witness a unique and spectacular event when the solar eclipse darkens skies around the state. A large swath of the state will be shrouded in total darkness as it falls in the path of totality (even if data suggests that path might now be smaller ).

Hopefully you're prepared with the best glasses or have supplies to construct a viewer at home . If not, you'll want to forget about watching this eclipse. Here's why.

Looking at the sun during an eclipse without protection can permanently damage your eyes

Fast forward to the hours after the solar eclipse :

You witnessed an amazing celestial sight that reminded you of our place in the cosmos. Or you stepped outside long enough to check it out, post a pic to Facebook and call it a day. But now  your eyesight is a bit blurry , and straight things look a little curved. Did you damage your eyes?

Even a short glance at the sun  without proper protection  can cause temporary or permanent damage to your eyes. Sunglasses aren't enough, you need  ISO-certified solar eclipse glasses  which block  about 1,000 times  more sunlight.

So make sure your glasses are approved, undamaged and within arm's reach today. The solar spectacle will last most of the afternoon in Ohio, but the path of totality will last just a few minutes.

When does the solar eclipse start in Ohio?

Have your eclipse glasses ready after lunch, Buckeye State stargazers. According to National Eclipse , Ohio residents can first see the moon overtake the sun at 1:53 p.m. before it fully reappears at 4:30 p.m.

The eclipse totality will last from 3:08 to 3:19 p.m. as it cuts a swath from southwest to northeast Ohio. Cincinnati and Columbus lie just south of the path of totality (northern suburbs of both cities will experience total darkness), but Akron, Cleveland, Kent and portions of North Canton lie in the path of totality.

Here's when some Ohio cities along its path can expect the total eclipse, and how long totality will last:

• Hamilton – Begins at 3:09:09 p.m., will last 1 minute, 42 seconds.
• Dayton – 3:09:29 p.m., will last 2 minutes, 43 seconds.
• Springfield – 3:10:15 p.m., will last 2 minutes, 34 seconds.
• Marion – 3:11:14 p.m., duration 3 minutes, 34 seconds.
• Delaware – 3:11:36 p.m., will last 2 minutes, 35 seconds.
• Fremont – 3:11:46 p.m., duration 2 minutes, 38 seconds.
• Dublin – 3:11:59 p.m., will last 1 minute, 23 seconds.
• Port Clinton – 3:12:12 p.m., duration 3 minutes, 30 seconds.
• Toledo – 3:12:17 p.m., duration 1 minute, 53 seconds.
• Mansfield -- 3:12:23 p.m., will last 3 minutes, 16 seconds.
• Ashland – 3:12:43 p.m., duration 3 minutes, 19 seconds.
• Wooster – 3:13:39 p.m., duration 2 minutes, 25 seconds.
• Akron – 3:14:14 p.m., will last 2 minutes, 46 seconds.
• Cuyahoga Falls – 3:14:15 p.m., will last 2 minutes, 56 seconds.
• Cleveland – 3:13:46 p.m., will last 3 minutes, 49 seconds.
• Kent – 3:14:31 p.m., will last 2 minutes, 47 seconds.

What was the last solar eclipse in Ohio? When is the next one?

Congress voted to welcome the Ohio to the United States in 1803. The Buckeye State was still a toddler the last time it experienced a solar eclipse in 1806. Eclipse glasses were decades away from being invented.

Ohio's next solar eclipse comes a little sooner than 281 years, but the 2024 event is still a once-in-a-lifetime show for many viewers – the next one won't happen until 2099.

Let's be clear: If you're in Cincinnati or Columbus on April 8, you won't see a total solar eclipse

How do I know if I damaged my eyes during the April eclipse? What are the symptoms of eclipse blindness?

So you watched the eclipse with glasses, but maybe they slipped off, were damaged, or were never ISO certified. How do you know if you damaged your eyes?

The retinas of your eyes have no nerve endings, so even if they are damaged, you may not feel any pain. But according to the  American Academy of Ophthalmology , you should go see your ophthalmologist if you experience any of these symptoms a few hours or even days after the eclipse:

• Blurry vision.
• Headache and/or eye pain.
• Vision loss or a black spot at the center of a patient’s sight in one or both eyes.
• Increased sensitivity to light.
• Distorted vision (a straight line may look bent or curvy).
• Changes in the way you see color, known as "dyschromatopsia."

How long can I look at the sun if I'm using eclipse glasses?

According to the American Astronomical Society, while some glasses and viewers include warnings about looking through them at the sun for more than 3 minutes at a time, as long as your glasses are compliant with the ISO 12312-2 safety standard and are undamaged, "you may look at the uneclipsed or partially eclipsed sun through them for as long as you wish."

What does looking at the sun do to your eyes?

Ever started a fire by using a magnifying glass to focus sunlight onto a point?

The lens of your eye does essentially the same thing when it focuses the light you see onto the retinas at the back of your eye, the  American Academy of Ophthalmology  explained. The retina is the light-detecting part of your eye that transmits those signals to the brain. Direct, intense light can burn a hole in them or destroy retinal cells almost immediately.

Normally it hurts to look at the sun and humans naturally squint or look away. Even a few seconds can be too much. But during an eclipse, the visible sunlight is reduced and it becomes possible to look directly at it without discomfort for longer periods of time. You may not even know you've damaged your eyes until the next day.

The result is solar retinopathy or retinal burns. It can happen from looking at the sun or at too-bright reflections of sunlight off snow or water. The most common cause of solar retinopathy is viewing a solar eclipse, also called eclipse blindness.

It's rare, but it can be permanent. The  2017 eclipse , which passed from Oregon to South Carolina, is thought to have caused about 100 cases, according to the  American Astronomical Society , out of the estimated 150 million people who witnessed it. But since solar retinopathy doesn't cause complete blindness, many people with minor cases may have never reported it or even known they had it.

How long will damage from looking at an eclipse last?

Researchers have found that some patients "may see symptoms ease over time," according to  David Hutton  for Ophthalmology Times. The cones in the retina are resilient and resist damage, experts say.

In a 1976 study, some patients saw their symptoms clear over time, and researchers found that some cases saw an "excellent recovery" in the first three months.

However, others have suffered permanent damage resulting in impaired vision in the form of a small blind spot in one or both eyes and distortion.

Is damage from looking at a solar eclipse treatable?

No. There is no treatment.

You should have an ophthalmologist scan your eyes to see how much damage has been done and they can monitor them over the next few months to chart any recovery, but the only thing you can do is wait and hope for it to go away.

And avoid looking at the sun.

‘Challengers’ Review: Zendaya and Company Smash the Sports-Movie Mold in Luca Guadagnino’s Tennis Scorcher

Josh O’Connor and Mike Faist compete for a fellow player’s heart in a steamy and stylish love triangle from the director of 'Call Me by Your Name.'

By Peter Debruge

Peter Debruge

Chief Film Critic

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Anyone who’s ever played tennis knows the game starts with love and escalates fast. In Luca Guadagnino ’s hip, sexy and ridiculously overheated “ Challengers ,” the rivals are former doubles partners Art Donaldson ( Mike Faist ) and Patrick Zweig (Josh O’Connor), best friends since the age of 12, who went their separate ways after both players fell for the same woman. Patrick got there first, but Art wound up marrying her — and their sense of competition has only intensified since.

Popular on Variety

“I’m no homewrecker,” Tashi teases Art and Patrick the night they meet her, 13 years earlier. Constructed like a tennis competition, Justin Kuritzkes’ screenplay ricochets back and forth through time, asking us to pivot our brains the way audiences do at the movie’s opening challenger match. (In pro tennis, challenger events are like the minor leagues, where second-tier talents prove themselves.) This one frames the film, as Tashi seems torn between her husband and his old partner.

Watching from the stands, their legs splayed indecently wide, the pair ogle Tashi as the wind whips her short skirt up in the air. None of this is accidental: not the way Jonathan Anderson (as in J.W. Anderson, switching from catwalks to costume design in his first feature credit) showcases Zendaya’s gazelle-like legs, not the way DP Sayombhu Mukdeeprom frames the boys’ crotches, and certainly not the moment Patrick squeezes his pal’s leg as Tashi shows them how, at its most beautiful, the game can be an ecstatic experience.

Later that night, at an Adidas-sponsored party for Tashi, the guys take turns trying to get her number. They’re motivated by hormones. She’s more strategic (the sheer control involved in Zendaya’s performance is astonishing, transforming this would-be trophy into the one who sets the rules). “You don’t know what tennis is,” Tashi challenges Patrick, going on to explain, “It’s a relationship.” Lines like this, which spell everything out in blinking neon lights, run throughout Kuritzkes’ script. But Guadagnino’s execution is all about subtext, calibrating things such that body language speaks volumes.

The same goes for what promises to be the year’s hottest scene, back in the boys’ hotel room, as Tashi sits on the bed between the two and coaxes — or coaches — them to make out. “Challengers” is not a gay film per se, but it leaves things ambiguous enough that one could read it like Lukas Dhont’s recent “Close,” about a friendship so tight, the boys’ peers tease them for it.

Over the course of 131 minutes, “Challengers” volleys between what amounts to a romantic rematch and intimate earlier vignettes. At all times, even off-screen, Tashi remains the fulcrum. In the present, Art — whose torso shows signs of multiple surgeries — has been on a cold streak, which betrays a loss of passion for the game. Passion’s no problem for Patrick, who’s more confident in both his swing and his sexuality.

The film calls for intensely physical performances from the two male actors, who both appear wobbly and exhausted by the end. Faist (a Broadway star whom “West Side Story” introduced to moviegoers) has a relatively traditional character arc, patiently waiting his turn and evolving as the timeline progresses. O’Connor (whose smoldering turn in gay indie “God’s Own Country” got him cast on “The Crown”) comes across as animalistic and immature by comparison, as his bad-boy character refuses to grow up or give up.

Another filmmaker might have subtracted himself in order to foreground the story, whereas Guadagnino goes big, leading with style (and a trendy score from Trent Reznor and Atticus Ross). In keeping with the athletic theme, he does all kinds of wild things with the camera, including a composition framed from the umpire’s perspective mid-court that zooms along the net to find Tashi in the crowd. Occasionally, she and other characters smack the fluorescent yellow balls directly at the screen, making us flinch in our seats. By the end, “Challengers” has assumed the ball’s POV — or maybe it’s the racket’s — as Guadagnino immerses audiences in the film’s climactic match.

Far from your typical sports movie, “Challengers” is less concerned with the final score than with the ever-shifting dynamic between the players. The pressure mounts and the perspiration pours, as the pair once known as “Fire and Ice” face off again. Whether audiences identify as Team Patrick or Team Art, Guadagnino pulls a risky yet effective trick, essentially scoring the winning shot himself.

Reviewed at AMC Century City 15, Los Angeles, April 9, 2024. MPA Rating: R. Running time: 131 MIN.

• Production: Amazon MGM presentation of a Why Are You Acting?, Frenesy Films, Pascal Pictures production. Producers: Amy Pascal, Luca Guadagnino, Zendaya, Rachel O’Connor. Executive producers: Bernard Bellew, Lorenzo Mieli, Kevin Ulrich.
• Crew: Director: Luca Guadagnino. Camera: Sayonbhu Mukdeeprom. Editor: Marco Costa. Music: Trent Reznor, Atticus Ross. Music supervisor: Robin Urdang.
• With: Zendaya, Josh O’Connor, Mike Faist.

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Screen Rant

Abigail review: scream 6 directors reinvent vampire movies in highly entertaining, gory horror.

In what may become one of the greatest vampire movies of all time, Abigail provides an extremely bloody, fun, humorous & fresh take on the subgenre.

• Radio Silence's Abigail reinvigorates the vampire subgenre with its unique gore and humor.
• The film features compelling characters and family-centric themes.
• Abigail delivers an effective ending with incredible performances by leads Alisha Weir and Melissa Barrera.

Abigail is a terrifying, hilarious, gory, and highly entertaining ride that rejuvenates the vampire flick with an inventive touch and concept. Directed by Ready or Not and Scream VI's Matt Bettinelli-Olpin and Tyler Gillett , collectively known as Radio Silence , Abigail sees them masterfully tackle a new horror subgenre, putting a twist on a classic Universal Monsters vampire story. The gory chaos kicks off as a group of strangers is hired to kidnap and "babysit" the daughter of a mysterious man, only for the team to find out that Abigail – and her father – are more dangerous than they thought.

Abigail (2024)

Abigail is a 2024 horror thriller directed by Matt Bettinelli-Olpin and Tyler Gillett. The plot follows a group of people who kidnap the daughter of a dangerous crime lord only to discover that the little girl is actually a vicious vampire out for blood. Alisha Weir stars as the titular character alongside Kathryn Newton, Melissa Barrera, and Dan Stevens.

• Abigail is an inventive, exciting vampire horror entry
• The film's cast is top-notch, with Alisha Weir being a standout
• Abigail has connective, compelling themes
• The vampire horror equally funny and scary

The story establishes that the 12-year-old is no normal girl, and Abigail is no normal vampire movie. Many have tried to update Dracula and vampire lore, one that still carries meaning and novelty, but none have done so as masterfully as Radio Silence. What's accomplished with Abigail is a marvel, and Radio Silence recruits some of the greatest horror actors of their generation to bring to life a reluctant, eccentric team of soon-to-be vampire fighters. The film balances scares and laughs with pitch-perfect timing, creating one of the smartest, most inventive vampire movies in decades.

Radio Silence... has created one of the smartest, most inventive vampire movies in decades

Abigail Is A Gory & Joke-Filled Crowd-Pleaser

Radio silence reinvigorates the vampire subgenre with plenty of blood & laughs.

From giving audiences compelling new heroes to root for, to using gallons of blood for gory kill scenes, and crafting horrifyingly hilarious villains, Radio Silence brings not just one of the most fun movies of the year, but also one of the best crowd-pleasing horror entries in recent memory . Abigail is the perfect example of why we go to the movies: Jaw-dropping gore and effects, thrilling and unexpected performances, moments that make us jump, shocking twists, and an unforgettable ending are all present and tick the boxes of what makes an incredible popcorn flick.

Abigail is the perfect example of why we go to the movies...

Abigail successfully distinguishes itself from the genre fare that preceded it. Our knowledge of a typical horror movie doesn't give us a leg up in the characters’ efforts to survive being prey. Rather, we’re also in the dark about how to take on Abigail as they are. While the influence of movies like The Lost Boys and From Dusk Till Dawn is apparent, Abigail expertly honors what came before while simultaneously flipping vampire subgenre tropes and audience expectations on their heads . In doing so, Abigail effectively cements itself as the most inventive Universal Monsters movie since 2020's The Invisible Man .

"Ready Or Not On Steroids": Abigail Stars Detail How Much Fake Blood Was Used

Abigail has compelling characters & performances in its "horror breakfast club", cast performances, character building, and family-centric themes give abigail an effective story.

Of course, while certain figures could have used more exposition as the events unfolded, Abigail doesn’t work without the captivating chemistry of the actors and characters in what has been described as “The Horror Breakfast Club .” Melissa Barrera and Dan Stevens give knockout performances as they further solidify their status as a beloved Scream Queen and King.

Lisa Frankenstein 's Kathryn Newton earned some of the greatest laughs in a standout role that may be unexpected after her past outings in the genre. Meanwhile, Kevin Durand and the late Angus Cloud are hilarious in every scene they appear in as they play with classic character tropes, and William Catlett commands the screen as a necessary complement to Barrera’s Abigail character.

Remember the name Alisha Weir, whose performance shows horror range and versatility. Weir is not only incredibly terrifying and sincere in Abigail ’s more frightening moments, but she also has a unique physical presence that harmonizes with her outstanding comedic timing and wit – whether it be ballet dances, charged attacks on potential victims, or biting insults. It’s easy to forget that Abigail is a 12-year-old girl when Weir proves to have the most commanding presence in a room filled with alleged criminal masterminds, which is a testament to her undeniable talent.

Weir is not only incredibly terrifying and sincere in Abigail’s more frightening moments, but she also has a unique physical presence that harmonizes with her outstanding comedic timing and wit.

Abigail Sticks The Landing With Its Family Themes & Final Shocks

The movie earns its ending with an effective overarching message.

Only a few characters are given deeper backstories and emotional arcs throughout the film, with Weir’s Abigail having the most rich, complex history and motivations of the bunch. Radio Silence effectively utilizes Weir’s Abigail and Barrera’s Joey to tell a timeless familial story that packs a punch throughout the movie’s various expository beats. Though certain twists and character choices have more merit than others , Abigail takes the time to earn its satisfying ending in a way that honors its messages about family and accountability, staying true to the main characters while leaving us wanting more.

Abigail solidifies Radio Silence as a powerful force in reinvigorating the horror genre with smart, fun, and incredibly comedic stories and concepts. By the movie’s final act, Abigail makes her case as a contender for the horror genre’s Mt. Rushmore of Evil Children alongside the likes of Damien, M3GAN, Regan, Esther, and Isaac. With such a fresh take on the monster class after already making waves with black comedy survival horrors and slashers, Abigail stamps Radio Silence – and three-time collaborator Melissa Barrera – as staples of the genre.

Abigail premiered at the 2024 Overlook Film Festival. It will release in theaters on April 19.

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Association Between Screen Media Use and Academic Performance Among Children and Adolescents

Mireia adelantado-renau.

1 LIFE Research Group, University Jaume I, Castellon, Spain

Diego Moliner-Urdiales

Iván cavero-redondo.

2 Universidad Politécnica y Artística del Paraguay, Asunción, Paraguay

3 Universidad de Castilla-La Mancha, Health and Social Research Center, Cuenca, Spain

Maria Reyes Beltran-Valls

Vicente martínez-vizcaíno.

4 Universidad Autónoma de Chile, Facultad de Ciencias de la Salud, Talca, Chile

Celia Álvarez-Bueno

Accepted for Publication: May 29, 2019.

Published Online: September 23, 2019. doi:10.1001/jamapediatrics.2019.3176

Author Contributions: Ms Adelantado-Renau and Dr Álvarez-Bueno had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Adelantado-Renau, Moliner-Urdiales, Beltran-Valls, Martínez-Vizcaíno, Álvarez-Bueno.

Acquisition, analysis, or interpretation of data: Adelantado-Renau, Moliner-Urdiales, Cavero-Redondo, Martínez-Vizcaíno, Álvarez-Bueno.

Drafting of the manuscript: Adelantado-Renau, Martínez-Vizcaíno, Álvarez-Bueno.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Adelantado-Renau, Cavero-Redondo, Martínez-Vizcaíno, Álvarez-Bueno.

Obtained funding: Moliner-Urdiales.

Administrative, technical, or material support: Moliner-Urdiales, Beltran-Valls.

Supervision: Moliner-Urdiales, Beltran-Valls, Martínez-Vizcaíno, Álvarez-Bueno.

Conflict of Interest Disclosures: None reported.

Funding/Support: Ms Adelantado-Renau was funded by predoctoral research grant PREDOC/2015/13 from the University Jaume I.

Role of the Funder/Sponsor: The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Associated Data

eTable 2. Data from Included Studies Examining the Linear Associations or Mean Differences Between Duration of Screen-based Activities and Academic Performance in Children and Adolescents

eTable 3. Study Quality Assessed by the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies

eTable 4. Random-Effects Meta-Regression Model to Examine Whether the Associations Between Screen-based Activities and Composite Scores Are Associated With the Children’s and Adolescents’ Age (in Years)

eTable 5. Sensitivity Analysis by Removing the Studies One by One

eFigure. Funnel Plots Assessing Publication Bias for Studies Analyzing the Association of A) Overall Screen Media, B) Television Viewing, and C) Video Game Playing, With Academic Performance Areas

What is the association between screen-based activities and academic performance areas among children and adolescents?

In this systematic review and meta-analysis of 58 cross-sectional studies, television viewing and video game playing (but not overall screen media) were inversely associated with the academic performance of children and adolescents. In addition, the negative association between these screen-based activities and academic performance seemed greater for adolescents than for children.

This study suggests that education and public health professionals should consider screen media use supervision and reduction as strategies to improve the academic success of children and adolescents.

This systematic review and meta-analysis of 58 cross-sectional studies examines the association between cognitive and academic performance and exposure to sedentary screen-based behavior among children aged 4 to 18 years.

The health consequences of excessive screen media use in children and adolescents are increasingly being recognized; however, the association between screen media use and academic performance remains to be elucidated.

To estimate the association of time spent on screen-based activities with specific academic performance areas in children and adolescents and to examine this association separately in these populations.

Data Sources

MEDLINE, Scopus, Web of Science, Cochrane Database of Systematic Reviews, and ERIC were searched from database inception through September 2018.

Study Selection

Cross-sectional studies of the association between time or frequency of screen media use and academic performance in children and adolescents were independently screened by 2 researchers. A total of 5599 studies, published between 1958 and 2018 from 23 countries, were identified.

Data Extraction and Synthesis

Data were processed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses ( PRISMA ). Random-effects models were used to estimate the pooled effect size (ES).

Main Outcomes and Measures

Academic performance areas included composite scores, language, and mathematics. Screen media measurements included time or frequency of computer, internet, mobile phone, television, video game, and overall screen media use.

In total, 58 cross-sectional studies (1.0%) of 5599 articles were included in the systematic review, of which 30 (52%) were included in the meta-analysis. The systematic review studies involved 480 479 participants aged 4 to 18 years, ranging from 30 to 192 000 people per study, and the meta-analysis studies involved 106 653 total participants, ranging from 70 to 42 041 people per study. Across studies, the amount of time spent on overall screen media use was not associated with academic performance (ES = −0.29; 95% CI, −0.65 to 0.08). Individually, television viewing was inversely associated with composite academic performance scores (ES = −0.19; 95% CI, −0.29 to −0.09), language (ES = −0.18; 95% CI, −0.36 to −0.01), and mathematics (ES = −0.25; 95% CI, −0.33 to −0.16). Video game playing was inversely associated with composite scores (ES = −0.15; 95% CI, −0.22 to −0.08). Subgroup analyses found that television viewing was inversely associated with language only in children (ES = −0.20; 95% CI, −0.26 to −0.15), whereas both television viewing (ES = −0.19; 95% CI, −0.30 to −0.07) and video game playing (ES = −0.16; 95% CI, −0.24 to −0.09) were inversely associated with composite scores only in adolescents.

Conclusions and Relevance

Findings from this study suggest that each screen-based activity should be analyzed individually for its association with academic performance, particularly television viewing and video game playing, which appeared to be the activities most negatively associated with academic outcomes. Education and public health professionals should consider supervision and reduction to improve the academic performance of children and adolescents exposed to these activities.

Introduction

Sedentary behaviors, defined as sitting or lying-down activities involving an energy expenditure of 1.0 to 1.5 basal metabolic equivalents, 1 are considered the fourth greatest risk factor of mortality worldwide. 2 Specifically, screen media use is the most popular leisure-time sedentary behavior among children and adolescents. Screen media use includes screen-based activities such as internet surfing, computer use, mobile phone use, television viewing, and video game playing. 3 On average, during their free time, children and adolescents watch television between 1.8 and 2.8 hours, play video games for 40 minutes, and use a computer 34 minutes per day. 3 Overall, 28% of children and adolescents are engaged in these screen-based activities more than 4 hours per day, with higher prevalence among boys than girls (30% vs 25%). 3 Along with screen media’s advantages of access to a wide variety of resources and fast communication, use of screen media has been associated with adverse physical, psychological, and social health consequences. 4 , 5

A growing body of evidence suggests that screen media use could play a key role in cognition (ie, brain processes involved in knowledge, intellect, and action) and academic performance (ie, academic achievement and abilities) in children and adolescents. 6 , 7 For instance, recent empirical research has reported that screen media use may reduce functional connectivity between cognitive areas. 7 However, studies into the association between screen media use and academic performance have shown controversial results, reporting not only negative 6 , 7 , 8 , 9 but also positive 10 , 11 and null associations. 12 , 13

Previous systematic reviews in children and adolescents have focused on the association of television viewing and video game playing with academic performance, showing a negative association. 14 , 15 More than 2 hours per day of television viewing has been associated with lower academic performance in children and adolescents. 14 However, to our knowledge, no previous systematic review and meta-analysis has examined the association of several screen-based activities with different academic performance areas in these age populations.

Given the increasing time spent on screen-based activities among children and adolescents, elucidating the association between sedentary behaviors and academic performance, which has been shown as a factor in future health 16 and work opportunities, is important. 17 Thus, the aim of this systematic review and meta-analysis was 2-fold: (1) to estimate the association of time spent on screen-based activities with specific academic performance areas in children and adolescents and (2) to examine this association separately in children and adolescents.

This systematic review and meta-analysis was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses ( PRISMA ) 18 and the Cochrane handbook. 19 The study protocol was registered on the International Prospective Register of Systematic Reviews (PROSPERO reference number CRD42018090388).

Search Strategy and Inclusion Criteria

We systematically searched MEDLINE (via PubMed), Scopus, Web of Science, Cochrane Database of Systematic Reviews, and ERIC databases from their inception through September 2018. The search strategy included the following relevant terms: screen time , screen media , electronic media , internet use , computer use , mobile phone use , television watching , TV watching , television viewing , TV viewing , television programs , video game , and video viewing ; scholastic , academic performance , academic achievement , school grades , mathematics , language , reading , and writing ; and children , childhood , preschooler , schoolchildren , preadolescent , adolescent , and youth . In addition, the reference lists of the articles included in this review and the references from previous systematic reviews and meta-analyses were reviewed to identify other relevant studies.

Primary source articles published in peer-reviewed journals were eligible for inclusion if the data were in regard to the association between screen media use time or frequency and academic performance in children and adolescents. Specific inclusion criteria were as follows: (1) participants: children and adolescents aged 4 to 18 years or primary, elementary, and secondary school students; (2) exposure: usage time or frequency of screen-based activities; (3) outcomes analyzed: academic performance assessed by school grades, standardized tests, or other measurements, such as school performance or academic failure; (4) study design: cross-sectional studies; and (5) language: articles published in English or Spanish.

Studies were excluded if they did not meet the inclusion criteria or did not report findings concerning the association between time or frequency of screen media use and academic performance (ie, measurements of screen media use time or frequency and academic performance were included, but their association was not analyzed). Inclusion of toddlers or participants with disorders that could limit the generalization of the data was also a reason for exclusion.

Data Extraction and Quality Assessment

Two of us (M.A-R., C.A-B.) independently screened the full texts of selected studies. One of us (M.A-R.) extracted data from the selected studies, and another (C.A-B.) checked the data for accuracy. A standardized data extraction table was created (eTable 1 in the Supplement ) and included the following data from all eligible articles: author, year of publication, country of the study, sample size (with percentage of girls), age of participants, main exposures (screen-based activities), main outcomes (academic performance indicators), and control variables.

After concealing information about authors, affiliations, date, and source of each article included in the review, 2 of us (M.A-R., C.A-B.) independently evaluated their methodological quality. Discrepancies were settled by consensus.

The Quality Assessment Tool for Observational Cohort and Cross-sectional Studies was used to evaluate the risk of bias. 20 The checklist comprised 14 items for longitudinal research, of which only 11 could be applied to cross-sectional studies. Each item of methodological quality was classified as yes, no, or not reported.

Statistical Analysis

Detailed statistical procedures used in this meta-analysis followed the recommendations of previous protocols. 21 Academic performance indicators were classified according to 3 main areas: composite scores, language, and mathematics. In addition, screen-based activities were classified as computer use, internet surfing, mobile phone use, television viewing, video game playing, and overall screen media (a composite measure of 2 or more screen-based activities). At least 3 observations in each academic performance area or in each screen-based activity were requested for conducting the meta-analysis, and only unadjusted correlations and regression coefficients were considered for these analyses.

The effect size was calculated with Cohen d index 22 by using random-effects models based on the Der Simonian and Laird method, considering each screen-based activity and academic performance area. Heterogeneity was assessed with the I 2 statistic, and its values were classified as not important (0%-40%), moderate (30%-60%), substantial (50%-90%), or considerable (75%-100%) 23 ; the corresponding P values were also considered. When studies included 2 or more cohorts or groups, their data were analyzed as independent samples.

Analyses of the association between screen-based activities and academic performance areas were performed by subgroups of age: children were between 4 and 11.9 years of age, and adolescents were between 12 and 18 years of age. In addition, random-effects meta-regression analyses were conducted to examine whether age (in years) was a factor in these associations. At least 10 observations for each association were required to conduct random-effects meta-regression analyses. Sensitivity analyses were performed to estimate the association of each study with the pooled effect size. The Egger regression asymmetry test was conducted to assess publication bias, considering P  < .10 to be statistically significant. 24

Statistical analyses used StataSE software, version 14 (StataCorp LLC). A 2-sided P  < .05 indicated statistical significance.

A total of 5599 records were identified after literature search ( Figure 1 ). Fifty-eight cross-sectional studies (1%) 8 , 9 , 10 , 11 , 12 , 13 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 were selected from these records for inclusion in this systematic review, of which 30 (52%) were included in the meta-analysis.

A summary of the cross-sectional studies included in this review is provided in eTable 1 in the Supplement . Articles were published between 1958 and 2018, and the studies involved participants aged 4 to 18 years from 23 countries. Eighteen studies originated from 10 European countries, 14 from 8 Asian countries, 23 from 2 North American countries, 2 from 2 South American countries, and 1 from a country in Oceania. Studies included in the systematic review involved a total of 480 479 participants, ranging from 30 to 192 000 people per study, whereas the studies included in the meta-analysis involved 106 653 total participants, ranging from 70 to 42 041 people per study.

Of the 58 studies in the systematic review, 4 studies (7%) reported data on computer use, 9 (15.5%) on internet surfing, 5 (9%) on mobile phone use, 36 (62%) on television viewing, 23 (40%) on video game playing, and 10 (17%) on overall screen media time or frequency. Regarding the outcomes analyzed, most studies used school grades (n = 25 [43%]) or standardized academic achievement tests (n = 21 [36%]), whereas other studies reported academic failure data (n = 4 [7%]) or self-reported academic achievement (n = 6 [10%]) or school performance (n = 6 [10%]).

Study Quality

Studies met from 27.3% to 81.8% of the quality criteria, with 36 studies (62%) meeting more than 50% of the quality criteria as assessed by the Quality Assessment Tool for Observational Cohort and Cross-sectional Studies 20 (eTable 3 in the Supplement ). Most studies clearly stated the main aim and plainly defined the exposure variables. However, 23 studies (40%) did not include objectively measured outcomes, and 23 (39%) did not use key potential confounders in the analyses. For instance, 30 (52%) of the 58 included studies did not consider potential confounders associated with home environment and parental characteristics.

Systematic Review

Among the 58 included studies, 47 (81%) examined the linear associations or mean differences between time spent on screen-based activities and academic performance in children and adolescents (eTable 2 in the Supplement ). Cross-sectional data from these studies showed that time spent on overall screen media, specifically television viewing, was inversely associated with academic performance in most unadjusted and adjusted analyses.

Regarding video game playing, results were controversial because studies mainly reported an inverse association or a lack of association with composite scores. Lack of association also predominated in those studies analyzing the association of video game playing with language and mathematics.

Studies of the association between internet surfing and academic performance reported an inverse association with composite scores and mathematics and divergent results regarding language. Regarding computer use, only 2 studies analyzed this screen-based activity and showed divergent results: no association 44 and positive association. 56 Overall, mobile phone use was not associated with academic performance indicators. 40 , 44

In addition, other studies included in this systematic review reported odds ratios (n = 8) and difference of proportions (n = 3). Among these studies, 2 assessed the association between time spent on overall screen media and academic performance. 32 , 74 Wang et al 74 showed an inverse association, whereas Faught et al 32 reported a positive association of screen media with academic performance when adolescents spent from 2 to 4 hours on screen-based activities, but a negative association was found when they spent 7 or more hours per day. Four studies investigating whether time or frequency of television viewing was associated with academic performance showed divergent results: a lack of association 52 , 65 or a negative association. 69 , 76 Three studies analyzed the association between video game playing and academic performance 41 , 47 , 53 : Jaruratanasirikul et al 41 and Muñoz-Miralles et al 53 reported an inverse association, whereas Kovess-Masfety et al 47 found that high use was associated with 1.88 times the odds of high overall school competence. Two studies examined the association between internet use time and academic performance. 45 , 61 Kim et al 45 found a negative association between internet surfing for entertainment purposes and academic performance, but a positive association was found when the internet was used for educational activities. Sánchez-Martínez and Otero Puime 61 showed that high internet surfing frequency and no internet use were both associated with academic failure.

Meta-analysis

The pooled effect size estimation for the association between overall screen media time or frequency and composite scores was −0.29 (95% CI, −0.65 to 0.08). This estimate showed a considerable heterogeneity among studies ( I 2  = 96.4%; P  < .001) ( Figure 2 ).

Positive ES values indicate direct association, whereas negative ES values indicate inverse association.

In the analysis of the association between duration of television viewing and academic performance areas, the pooled effect sizes were −0.19 (95% CI, −0.29 to −0.09) for composite scores, −0.18 (95% CI, −0.36 to −0.01) for language, and −0.25 (95% CI, −0.33 to −0.16) for mathematics ( Figure 3 ). Considerable heterogeneity was found among the included studies for the association of duration of television viewing with composite scores ( I 2  = 97.5%; P  < .001) and language ( I 2  = 95.5%; P  < .001), whereas substantial heterogeneity was observed for mathematics ( I 2  = 70.7%; P  = .002).

Data for the association between duration of video game playing and composite scores showed a pooled effect size of −0.15 (95% CI, −0.22 to −0.08). A large heterogeneity was found among studies ( I 2  = 63.0%; P  = .004) ( Figure 4 ).

Subgroup analyses conducted separately in children and adolescents ( Table ) showed that, in children, the duration of television viewing was inversely associated with language (effect size = −0.20; 95% CI, −0.26 to −0.15) and mathematics (effect size = −0.36; 95% CI, −0.66 to −0.07). However, in adolescents, the duration of television viewing was inversely associated with composite scores (effect size = −0.19; 95% CI, −0.30 to −0.07) and mathematics (effect size = −0.21; 95% CI, −0.26 to −0.15). In addition, the duration of video game playing was inversely associated with the composite scores of adolescents (effect size = −0.16; 95% CI, −0.24 to −0.09).

The random-effects meta-regression model showed that the associations of overall screen media (β, −0.0005; 95% CI, −0.131 to 0.130; P  > .99), television viewing (β, −0.056; 95% CI, −0.117 to 0.006; P  = .07), and video game playing (β, −0.009; 95% CI, −0.121 to 0.104; P  = .82) with composite scores were not associated with the age of children and adolescents (as a continuous variable) (eTable 4 in the Supplement ).

Sensitivity analyses suggested that the pooled effect size estimation for the association between television viewing and language was slightly modified when data from several studies were removed, with effect size ranging from −0.21 to −0.13. 25 , 34 , 55 , 57 , 59 , 60 , 67 The pooled effect sizes for the remaining associations were not modified by the one-by-one removal of the included cohorts (eTable 5 in the Supplement ).

Funnel plots and the Egger asymmetry test indicated statistically significant publication bias only for the pooled subgroup analyses of the association between overall screen media and composite scores (effect size = 0.80; 95% CI, 0.16-1.43; P  = .02; eFigure in the Supplement ).

To our knowledge, this systematic review and meta-analysis is the first to synthesize the evidence on the cross-sectional associations between time spent on overall screen media, different screen-based activities, and specific academic performance areas in children and adolescents. The meta-analysis indicates a lack of association between the amount of time spent on overall screen media use and the academic performance of children and adolescents. However, when the association between each screen-based activity and academic performance was analyzed, television viewing was inversely associated with composite scores, language, and mathematics, whereas video game playing was inversely associated with composite scores. In addition, subgroup analyses conducted separately in children and adolescents showed that the duration of these screen-based activities may have a greater association with the academic performance of adolescents than children.

The lack of association between the overall time spent on screen-based activities and academic performance does not concur with previous research reporting a negative association between overall screen media time and academic performance. 7 , 8 , 9 , 30 , 56 One study found that adolescents who spent more than 7 hours per day on overall screen media were 40% less likely to achieve high academic performance, whereas those who spent 2 to 4 hours per day had 1.23 times the odds of achieving excellent grades compared with those who spent fewer than 2 hours per day. 32 We speculate that the lack of association between overall screen media use and academic performance found in this meta-analysis as well as the lack of agreement among studies could be partially the result of several aspects of the overall screen media time measure that are not captured, such as the specific device used, the purpose of the task, the content, and the context in which children and adolescents use screen media.

Regarding the association between the duration of individual screen-based activities and academic performance, our results concur with previous research showing an inverse association of television viewing with composite scores, 29 , 64 , 66 , 71 language, 59 , 67 and mathematics. 59 , 77 Previous research has suggested that television viewing replaces other activities such as physical activity, verbal interaction, studying, or sleeping (ie, the time-displacement hypothesis) 6 and reduces mental effort (ie, the passivity hypothesis), which might affect school performance. 67 In addition, excessive television viewing time among children has been shown to decrease attention and cognitive functioning 78 and to increase behavioral problems and unhealthy eating habits, 67 which may also impair academic outcomes.

The analysis of video game revealed an inverse association between the duration of video game playing and composite scores, in consonance with previous research. 42 , 44 , 50 , 63 Previous studies have shown that playing video games is inversely associated with emotional and social health, triggering psychological and behavioral problems 15 , 79 that may have implications for overall academic outcomes. Conversely, because playing video games requires interaction with the task, it could also be positively associated with academic outcomes depending on the game content. Evidence has indicated that playing video games requires players to successfully understand the language 70 and might increase their engagement with text online. 80

Regarding internet surfing, few studies have analyzed its association with academic performance in children and adolescents. Most studies showed an inverse association between internet overuse and academic performance, although they did not consider the device used (ie, computer, smartphone, or tablet) or the purpose of internet use. 25 , 26 , 31 , 61 Kim et al 45 showed that internet use time was inversely associated with academic performance when used for leisure activities but was positively associated when used for educational purposes. With regard to the device used, the association between time of computer use and academic performance in children and adolescents remains equivocal, with both negative 53 and positive 39 associations found, whereas the duration of mobile phone use has been poorly investigated, suggesting a lack of association with academic performance. 39 , 40 , 44 Overall, this systematic review and meta-analysis highlights the need for further research into individual types of screen-based activities given their varying associations with the academic performance of children and adolescents.

Subgroup analyses conducted separately in children and adolescents indicated an inverse association between the duration of television viewing and language only in children, showing that time spent on screen-based activities was mostly associated with negative implications for academic performance in adolescents. These findings agree with those in previous studies, suggesting that only young children (aged 2-3 years) may gain an advantage from watching educational programs because they learn from repetitions. 6 However, this method is not efficient for developing more complex academic abilities during late childhood, when high exposure to television viewing has been shown to increase the risk of language-derived problems. 81 Among adolescents, the facilitated and simultaneous access to different screen-based activities for different purposes (eg, social communication, online networking, and playing games), which is a signature of contemporary society, could explain the greater negative association of these activities with academic performance.

Although the data show that the association between screen media use and academic performance seems to depend on the age of children and adolescents and the type of device they used, the exact nature of these associations still needs a more nuanced consideration. In addition to these 2 factors, screen media use content, context, and task should be analyzed given that each sedentary screen-based activity (eg, talking to someone, looking at magazines, or playing) might have a different implication for academic performance. 82 , 83 Moreover, previous studies have suggested that the home environment and parental characteristics (eg, socioeconomic status and parental support) may be stronger factors in academic performance compared with the amount of screen media use per se. 28 A restricted budget likely does not allow children and adolescents to buy books or to participate in out-of-school educational activities. At the same time, parents with high educational level and knowledge of pediatric media guidelines as well as parents who support and have high expectations for their children’s future might discourage activities with low educational value, 6 such as television viewing or video game playing. However, these factors were considered in only 48% of included studies in the present systematic review. Thus, further investigations of these potential aspects are needed to clarify the association between screen media use and academic performance in children and adolescents.

These findings have public health implications for the prevention of academic failure in children and adolescents as well as support the need for designing interventions to reduce screen media use beginning in early childhood. Given that previous systematic reviews and meta-analyses have shown that the effectiveness of interventions to reduce screen time is higher when including health promotion curricula or counseling, 84 teachers and public health professionals should collaborate to achieve better results. Thus, in addition to controlling access to screen media and reducing the exposure to screen-based activities, particularly to television and video games, interventions should include the promotion of active and healthy lifestyles. More in-depth studies of the consequences of excessive screen media use and its association with health and cognition are warranted, which will inform the advice provided to families, educators, and health policymakers.

Limitations and Strengths

This systematic review and meta-analysis have some limitations. First, the cross-sectional design of the included studies prevents causal inferences. Second, the questionnaires to assess screen media use and the variety of tools to measure academic performance, as well as the inclusion of articles published only in English or Spanish, could have altered the results. Third, subgroup analyses could not be conducted for some of the screen-based activities and/or academic performance areas. Fourth, the purpose, content, and context of screen media use; socioeconomic status; and/or parental support were not taken into account in the analyses.

Nonetheless, this systematic review and meta-analysis have several strengths, including the inclusion of a wide range of screen-based activities and different academic performance areas. In addition, only 22 studies met less than 50% of quality criteria, and subgroup analyses were conducted to examine the implication of age for the studied associations.

Conclusions

The findings from this systematic review and meta-analysis suggest that each screen-based activity should be analyzed individually because of its specific association with academic performance. Television viewing and video game playing seem to be the activities most negatively associated with academic performance, particularly among adolescents. Moreover, this study highlights the need for further research into the association of internet, computer, and mobile phone use with academic performance in children and adolescents. These associations seem to be complex and may be moderated and/or mediated by potential factors, such as purpose, content, and context of screen media use. Given that both academic performance and sedentary behaviors can be factors in future health, education and public health professionals should consider supervision and reduction as strategies for television viewing and video game playing to improve both the health status and academic performance of children and adolescents exposed to these activities.

Supplement.

eTable 1. Summary of Characteristics of Included Cross-Sectional Studies