Global Prevalence of Meeting Screen Time Guidelines Among Children 5 Years and Younger: A Systematic Review and Meta-analysis

Brae Anne McArthur; Valeriya Volkova; Suzy Tomopoulos; Sheri Madigan

doi:10.1001/jamapediatrics.2021.6386

. 2022 Feb 14;176(4):373–383. doi: 10.1001/jamapediatrics.2021.6386

Global Prevalence of Meeting Screen Time Guidelines Among Children 5 Years and Younger

A Systematic Review and Meta-analysis

Brae Anne McArthur ^1,², Valeriya Volkova ³, Suzy Tomopoulos ⁴, Sheri Madigan ^1,^2,^✉

¹Department of Psychology, University of Calgary, Calgary, Alberta, Canada

²Alberta Children’s Hospital Research Institute, Calgary, Alberta, Canada

³Faculty of Kinesiology, University of Calgary, Calgary, Alberta, Canada

⁴Department of Pediatrics, New York University School of Medicine–Bellevue Hospital Center, New York

Accepted for Publication: November 11, 2021.

Published Online: February 14, 2022. doi:10.1001/jamapediatrics.2021.6386

^✉

Corresponding Author: Sheri Madigan, PhD, RPsych, Department of Psychology, University of Calgary, Calgary, AB T2N 1N4, Canada (sheri.madigan@ucalgary.ca).

Author Contributions: Drs McArthur and Madigan 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: McArthur, Madigan.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: McArthur, Volkova, Madigan.

Critical revision of the manuscript for important intellectual content: Tomopoulos, Madigan.

Statistical analysis: McArthur, Madigan.

Obtained funding: Madigan.

Administrative, technical, or material support: Madigan.

Supervision: Madigan.

Conflict of Interest Disclosures: None reported.

Funding/Support: This work was supported by the Alberta Children’s Hospital Foundation and the Canada Research Chairs Program.

Role of the Funder/Sponsor: The funders 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.

Additional Contributions: We acknowledge Cheri Nickel, MLIS, for her assistance with the search strategy, and the members of the Determinants of Child Development Laboratory at the University of Calgary, in particular, Ciana Anhorn, Katarina Padilla, and Claire McGuinness, for their contributions to data screening. All received compensation for their work.

^✉

Corresponding author.

PMCID: PMC8845032 PMID: 35157028

This meta-analysis examines population samples from 63 studies to determine whether young children (aged 2-5 years) are meeting guidelines about their daily screen time.

Key Points

Question

What proportion of young children are meeting the guidelines about daily amounts of screen time?

Findings

This meta-analysis of 95 samples (89 163 children) revealed that 24.7% of children younger than 2 years met the guideline to avoid screen use, and 35.6% of children aged 2 to 5 years met the guideline of no more than 1 hour a day of screen time. Moderator analyses suggest the prevalence of meeting guidelines has increased in recent years.

Meaning

One in 4 children younger than 2 years and 1 in 3 children aged 2 to 5 years are meeting screen time guidelines, highlighting the need for additional public health initiatives aimed at promoting healthy device use.

Abstract

Importance

Pediatric guidelines suggest that infants younger than 2 years avoid screen time altogether, while children aged 2 to 5 years receive no more than 1 hour per day. Although these guidelines have been adopted around the world, substantial variability exists in adherence to the guidelines, and precise estimates are needed to inform public health and policy initiatives.

Objective

To derive the pooled prevalence via meta-analytic methods of children younger than 2 years and children aged 2 to 5 years who are meeting guidelines about screen time.

Data Sources

Searches were conducted in MEDLINE, PsycINFO, and Embase up to March 2020.

Study Selection

Studies were included if participants were 5 years and younger and the prevalence of meeting (or exceeding) screen time guidelines was reported.

Data Extraction and Synthesis

Data extraction followed Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. Two independent reviewers extracted all relevant data. Random-effects meta-analyses were used to derive the mean prevalence rates.

Main Outcomes and Measures

Prevalence of meeting screen time guidelines.

Results

From 63 studies, 95 nonoverlapping samples with a total of 89 163 participants were included. For children younger than 2 years, the pooled prevalence of meeting the screen time guideline (0 h/d) was 24.7% (95% CI, 19.0%-31.5%). Moderator analyses revealed that prevalence of meeting screen time guidelines varied as a function of year of data collection (increased over time), measurement method (higher when questionnaires compared with interview), and type of device use (higher when a combination of screen use activities compared with television/movies only). For children aged 2 to 5 years, the mean prevalence of meeting the screen time guideline (1 h/d) was 35.6% (95% CI, 30.6%-40.9%). Moderator analyses revealed that the prevalence of meeting screen time guidelines varied as a function of type of device use (higher when screen time was television/movies only compared with a combination of screen use activities).

Conclusions and Relevance

The findings of this meta-analysis indicate that only a minority of children 5 years and younger are meeting screen time guidelines. This highlights the need to provide support and resources to families to best fit evidence-based recommendations into their lives.

Introduction

Children 5 years and younger are the fastest-growing users of digital media (content transmitted over tablets, television [TV], etc).^1,2 Before the COVID-19 pandemic, children 5 years and younger used screens for an average of approximately 25% of their waking hours.³ This value is potentially concerning, because high levels of screen use in young children can be associated with negative consequences for their development.^{1,4,5,6,7,8,9,10} The American Academy of Pediatrics first developed screen time guidelines in 1999, recommending that pediatricians advise parents to avoid TV viewing for children younger than 2 years.¹¹ Adding to the policy in 2001, they recommended no more than 1 to 2 hours per day for children aged 2 to 5 years. In 2016, the American Academy of Pediatrics recommended avoiding screen time for children younger than 2 years (outside of video chatting), and limiting screen use to 1 hour per day for children aged 2 to 5 years.¹² The World Health Organization,¹³ as well as pediatric societies worldwide (eg, Canadian 24-Hour Movement Guidelines,¹⁴ Australian 24-Hour Movement Guidelines¹⁵), have adopted similar guidelines.

Although many parents express concern about screen time,¹⁶ few children appear to be meeting the screen time guidelines.¹⁷ However, there is variability in adherence across the globe, with rates of meeting the screen time guidelines ranging from 2% to 83%.^9,18,19 Thus, there is a need to establish precise estimates of the proportion of children 5 years or younger who are meeting screen time guidelines. Given the existing variability, it is important determine at what age and for whom screen time guidelines are being met. For example, some studies show younger infants and girls are more likely to meet the guidelines.^20,21 Other studies have mixed findings when examining guideline uptake over time.^20,22 This information can inform future public health initiatives aimed at promoting healthy device use. This is especially important given that screen use in young children has been identified as a concern by parents, health professionals, and policymakers alike.^23,24

To our knowledge, no meta-analysis to date has examined the prevalence of children aged 5 years or younger meeting screen time guidelines. To advance knowledge and inform policy and practice, the aim of this study was to derive pooled estimates of the global prevalence of meeting the screen time guidelines for (1) children younger than 2 years (ie, no screen time) and (2) children aged 2 to 5 years (ie, meeting the <1 h/d or <2 h/d guideline). To explain between-study heterogeneity in the prevalence of meeting the guidelines, a secondary aim was to determine if prevalence rates varied as a function of demographic (ie, sex, age), geographical (ie, continent), and methodological moderators (eg, screen type, assessment method).

Methods

Search Strategy

This study was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guidelines.²⁵ Systematic searches were conducted in MEDLINE, PsycINFO, and Embase up to March 11, 2020, by a health sciences librarian (eTable 1 in the Supplement). All studies include data collected during or after 1999, when screen time guidelines originated. Given that screen use during the COVID-19 pandemic has increased,²⁶ we did not include pandemic-related research. Key search terms included the following: (guideline* or recommendation*), and (Screen - time*, media, usage, view*, or watch*), or (digital - media, or technolog*), or (screentime*), or (“screen use”), or (mobile device* or media device*), or (sedentary behavior), or (sedentary). The concept of children (<18 y) was searched using the Age Limits function and a text word search. No language limits were applied in the search. The search revealed 7159 nonduplicate abstracts. References of included studies and review articles were manually searched for further studies, yielding 14 additional studies, 3 of which met inclusion criteria.

Study Inclusion and Exclusion Criteria

Inclusion criteria were 3-fold: (1) proportion of children meeting or exceeding an established screen time guideline was reported, (2) children were 5 years and younger, and (3) reports were written in English. Studies were excluded if they were qualitative, and included an intervention targeted at screen time and reported only postintervention data. The PRISMA flow diagram is shown in the Figure. Four reviewers assessed titles and abstracts for inclusion. All titles and abstracts were reviewed by 2 coders, and disagreements were resolved via consensus.

Data Extraction

Along with prevalence data and sample size, moderator variables extracted included the following: child age (in months), child sex (percentage of boys), year of data collection, screen time measurement (ie, screen time diary vs questionnaire vs interview), guidelines used (ie, 0, 1, or 2 hours), type of device use (eg, computer, TV, tablet), and geographical study location (ie, continent). We extracted and analyzed prevalence data based on the screen time guideline referenced in the original article (ie, 0, 1 or 2 hours). All screen time measurement methods were included, but only studies using screen time diaries, questionnaires, interviews, or some combination of these methods were identified. When prevalence data were reported separately for week and weekend use, a daily average was calculated ([week*5 +weekend*2]/7). When a study included longitudinal data on the same children over time, we extracted data from the most recent time point. When prevalence rates were reported separately by device (eg, TV vs video game vs computer), we extracted TV prevalence rates as a proxy for overall use. Watching or streaming TV is the primary modality for this age range,² and averaging across different modalities would overestimate or underestimate true rates of compliance. Prevalence data were available for all included studies. To retrieve missing moderator data from study publications, 7 authors were contacted, and 4 (57%) responded. If prevalence estimates from nonoverlapping cohorts were provided within a study, they were entered into the meta-analysis separately. All studies were extracted by 2 coders, and discrepancies were resolved through consensus. Intercoder agreement was 0.86.

Study Quality

To assess study quality, a 7-item tool adapted from the National Institutes of Health Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies²⁷ was used (eTable 2 in the Supplement). All studies were coded as 0 (no) or 1 (yes) for each item, with a maximum score of 7. A primary coder assessed all articles for methodological quality, and a second coder verified a proportion of the studies (20%). The intercoder agreement was 0.81, and discrepancies were resolved through consensus.

Data Analysis

All extracted data were entered into Comprehensive Meta-analysis Version 3.0 (CMA²⁸), and 3 separate meta-analyses were conducted: (1) children younger than 2 years, (2) children aged 2 to 5 years following the guideline about 1 hour a day, and (3) children aged 2 to 5 years following the guideline about 2 hours a day. All studies were from independent samples. Pooled prevalence estimates with associated 95% CIs were computed. Pooled prevalence estimates were weighted by the inverse of their variance, which gives greater weight to large sample sizes.

Random-effects models were used to assess variations observed across studies, and the Q and I² statistics were used to assess between-study heterogeneity of effects. Pooled prevalence is reported as an event rate (ie, 0.10), but is interpreted as prevalence (ie, 10.0%). A significant Q statistic suggests moderator analyses should be explored.²⁹ The I² statistic provides an estimate of the variability across studies (ie, values >75% indicate moderators should be explored).³⁰ As recommended by Bornstein et al,²⁹ categorical moderators were examined when k ≥ 10 and a minimum of 3 samples (ie, ≥3 cells) were available. A P value of .05 was considered statistically significant. Random-effect meta-regression analyses with restricted maximum likelihood estimation was used for continuous moderators. When meta-regressions were significant, we calculated odds ratios from the log odds coefficient (ie, odds ratio = e^LogOdds). Inspection of funnel plots of symmetry and Egger tests³¹ were used to estimate publication bias.

Results

Our search yielded 7173 nonduplicate records (Figure). A total of 620 full-text articles were examined, and 63 studies with 95 nonoverlapping samples (89 163 participants) met full inclusion criteria.

Study Characteristics

For the included studies (Table 1), the sample size ranged from 5 to 11 490, and the year of data collection ranged from 1999 to 2018. For the studies including children younger than 2 years, the mean age was 12.4 months; for those aged 2 to 5 years, the mean age was 46.1 months; and 50.9% of the samples were male. A majority of samples were from North America (47.6%) with fewer studies from Australia/New Zealand (20.6%), Europe (17.5%), Asia (11.1%), Africa (1.6%), and the Middle East (1.6%). Measurement of screen use included questionnaires (71.4%), with fewer studies using interviews (20.6%), screen time diaries (3.2%), or mixed methods (eg, questionnaire and interview; 4.8%). For children younger than 2 years, a large portion of studies examined screen use via watching TV/movies exclusively (55.6%) or a composite of TV/movies and/or computers, mobile use, and video games (37.0%). A minority examined tablet or computer use exclusively (3.7%, respectively). For children aged 2 to 5 years, a large portion of studies examined screen use via watching TV/movies exclusively (29.0%), and a majority of studies used a composite of TV/movies, and/or computers, tablets, and video games (68.2%). A minority examined tablet or computer use exclusively (1.4%, respectively). The mean study quality score was 4.6 for children younger than 2 years and 4.8 for children aged 2 to 5 years (range, 2.0-7.00; eTable 3 in the Supplement).

Table 1. Study Characteristics of Studies Included in the Meta-analyses.

Source	No. of children	Age, mean, mo	% Male	Data collection date	Assessment method	Age, y	Screen time guideline, h	Screen type	Geography
Adams et al,³² 2018
Cohort 1	114	18	49.6	2013	Q	<2	0	Mixed	NA
Cohort 2	106	30	49.6	2013	Q	2-5	2	Mixed	NA
Anderson and Whitaker,³³ 2010	8550	52.3	51	2005	I	2-5	2	TV/movies	NA
Asplund et al,³⁴ 2015
Cohort 1	120	10.4	55	2013	Q	<2	0	Mixed	NA
Cohort 2	177	41.5	55	2013	Q	2-5	2	Mixed	NA
Baker et al,³⁵ 2020
Cohort 1	113	11.5	51.8	2017	Q	<2	0	Computer	AU/NZ
Cohort 2	302	42	51.8	2017	Q	2-5	1	Computer	AU/NZ
Barber et al,³⁶ 2017
Cohort 1	812	12.7	48.6	2009	I	<2	0	TV/movies	EU
Cohort 2	812	37	48.6	2009	I	2-5	1	TV/movies	EU
Barr et al,³⁷ 2010a	308	12.2	54.2	2002	C	<2	0	TV/movies	NA
Barr et al,³⁸ 2010b	53	15.8	46.7	2001	D	<2	0	TV/movies	NA
Berglind et al,³⁹ 2018	830	51.6	55.3	2008	Q	2-5	1	Mixed	EU
Briefel et al,⁴⁰ 2015
Cohort 1	925	18	53	2008	I	<2	0	TV/movies	NA
Cohort 2	1461	36	53	2008	I	2-5	2	TV/movies	NA
Carson et al,⁴¹ 2013
Cohort 1	124	15.6	46.3	2011	Q	<2	0	TV/movies	NA
Cohort 2	533	42	53.7	2011	Q	2-5	1	TV/movies	NA
Carson et al,⁴² 2019	539	36	52.1	2011	Q	2-5	1	Mixed	NA
Certain and Kahn,⁴³ 2002
Cohort 1	2338	11.9	49.8	ND	Q	<2	0	TV/movies	NA
Cohort 2	1247	29.5	51.6	ND	Q	2-5	2	TV/movies	NA
Chaput et al,¹⁸ 2017	803	42	49.8	ND	I	2-5	1	Mixed	NA
Chia et al,⁴⁴ 2019	2346	36	50	2018	Q	2-5	1	Mixed	Asia
Chuang et al,⁴⁵ 2013	623	48	49.9	2008	Q	2-5	2	TV/movies	NA
Cliff et al,⁹ 2017	248	50.4	57	2015	Q	2-5	1	Mixed	AU/NZ
De Craemer et al,⁴⁶ 2018	595	50.4	53.3	2012	Q	2-5	1	Mixed	EU
Dennison et al,⁴⁷ 2002
Cohort 1	790	12	50.9	1999	Q	<2	0	TV/movies	NA
Cohort 2	1937	34.7	50.9	1999	Q	2-5	2	TV/movies	NA
Goh et al,⁴⁸ 2016	725	7	55.3	2014	I	<2	0	Mixed	Asia
Guan et al,⁴⁹ 2020	254	61.3	53.1	2018	Q	2-5	1	Mixed	Asia
Hardy et al,⁵⁰ 2018
Cohort 1	1141	64.2	51.7	2010	Q	2-5	2	Mixed	AU/NZ
Cohort 2	1150	64.7	49.8	2015	Q	2-5	2	Mixed	AU/NZ
Harrison and Liechty,⁵¹ 2012	354	37.4	49.9	2009	Q	2-5	2	Mixed	NA
Hesketh et al,⁵² 2017	455	3.6	54.1	2008	Q	<2	0	TV/movies	AU/NZ
Hinkley et al,⁵³ 2012	935	54	54	2008	Q	2-5	1	Mixed	AU/NZ
Hinkley et al,⁵⁴ 2018	575	45	54	2013	Q	2-5	1	Mixed	AU/NZ
Huber et al,²⁰ 2018
Cohort 1	10	12	55.4	2014	Q	<2	0	Mixed	AU/NZ
Cohort 2	96	36	55.4	2014	Q	2-5	1	Mixed	AU/NZ
Cohort 3	13	12	55.4	2015	Q	<2	0	Mixed	AU/NZ
Cohort 4	44	36	55.4	2015	Q	2-5	1	Mixed	AU/NZ
Cohort 5	12	12	55.4	2016	Q	<2	0	Mixed	AU/NZ
Cohort 6	101	36	55.4	2016	Q	2-5	1	Mixed	AU/NZ
Cohort 7	5	12	55.4	2017	Q	<2	0	Mixed	AU/NZ
Cohort 8	59	36	55.4	2017	Q	2-5	1	Mixed	AU/NZ
Hudson et al,⁵⁵ 2009	89	42.1	44.8	ND	Q	2-5	2	Mixed	NA
Khalsa et al,⁵⁶ 2017	379	51.6	49	2009	C	2-5	2	Mixed	NA
Kovacs et al,²¹ 2014
Cohort 1	822	47.5	50.4	2007	Q	2-5	1	TV/movies	EU
Cohort 2	830	47.5	50.4	2007	Q	2-5	1	TV/movies	EU
Cohort 3	763	47.5	50.4	2007	Q	2-5	1	TV/movies	EU
Cohort 4	924	47.5	50.4	2007	Q	2-5	1	TV/movies	EU
Cohort 5	1069	47.5	50.4	2007	Q	2-5	1	TV/movies	EU
Cohort 6	842	47.5	50.4	2007	Q	2-5	1	TV/movies	EU
Cohort 7	638	47.5	50.4	2007	Q	2-5	1	TV/movies	EU
Cohort 8	713	47.5	50.4	2007	Q	2-5	1	TV/movies	EU
Kracht et al,⁵⁷ 2019	107	41.1	50.4	2016	Q	2-5	1	Mixed	NA
Lampard et al,⁵⁸ 2013	146	44.4	45	2010	Q	2-5	2	Mixed	NA
Lee et al,⁵⁹ 2017	908	41.4	48.7	2008	I	2-5	1	TV/movies	Asia
Leppanen et al,⁶⁰ 2019	778	56.4	51	2015	D	2-5	1	Mixed	EU
Liu,⁶¹ 2014
Cohort 1	1000	42.2	51	2006	Q	2-5	2	Mixed	NA
Cohort 2	2029	42.1	51.4	2007	Q	2-5	2	Mixed	NA
Loprinzi et al,⁶² 2013	164	48	44.5	2011	Q	2-5	2	Mixed	NA
Madigan et al,⁶³ 2020	1994	36	51.8	2011	Q	2-5	1	Mixed	NA
McClure et al,⁶⁴ 2015	183	13	49	2014	Q	<2	0	TV/movies	NA
Meredith-Jones et al,⁶⁵ 2019
Cohort 1	615	17	51.4	2009	I	<2	0	TV/movies	AU/NZ
Cohort 2	372	59.8	50.5	2009	I	2-5	1	Mixed	AU/NZ
Miguel-Berges et al,⁶⁶ 2019	4961	56.9	51.8	2012	Q	2-5	1		EU
Myers et al,⁶⁷ 2015
Cohort 1	160	12	53.9	2010	I	<2	0	TV/movies	AU/NZ
Cohort 2	252	36	53.9	2010	I	2-5	1	TV/movies	AU/NZ
Natsiopoulou and Melissa-Halikiopoulou,⁶⁸ 2009	355	48	50.4	2005	Q	2-5	2	TV/movies	EU
Nejadsadeghi et al,⁶⁹ 2018	82	54	55	2016	Q	2-5	2	Mixed	M.East
Okely et al,⁷⁰ 2009	266	47.5	52.6	2004	Q	2-5	2	Mixed	AU/NZ
Pempek and McDaniel,⁷¹ 2016
Cohort 1	164	18	50	ND	Q	<2	0	Tablet	NA
Cohort 2	192	36.5	50	ND	Q	2-5	1	Tablet	NA
Peralta et al,⁷² 2018	817	48	51.2	2003	Q	2-5	1	TV/movies	EU
Perrin et al,⁷³ 2014	861	2.1	48.7	ND	Q	<2	0	TV/movies	NA
Prioreschi et al,⁷⁴ 2017	140	11.8	52.9	2016	Q	<2	0	TV/movies	Africa
Pujadas Botey et al,⁷⁵ 2016	177	36.7	52	2013	I	2-5	1	Mixed	NA
Ruangdaraganon et al,⁷⁶ 2009
Cohort 1	203	12	53.2	2001	I	<2	0	TV/movies	Asia
Cohort 2	203	24	53.2	2002	I	2-5	2	TV/movies	Asia
Saldanha-Gomes et al,⁷⁷ 2017	883	24	53.6	2005	Q	2-5	1	Mixed	EU
Sanders et al,⁷⁸ 2015	4983	50.4	50.9	2004	Q	2-5	2	TV/movies	AU/NZ
Shah et al,⁷⁹ 2019	379	51.8	54.9	2013	Q	2-5	1	Mixed	Asia
Shook et al,⁸⁰ 2018	11490	42	51.2	2013	I	2-5	2	Mixed	NA
Stough et al,⁸¹ 2018	148	55.2	43.1	2012	Q	2-5	2	Mixed	NA
Tomopoulos et al,⁸² 2010	259	6	47.1	2005	C	<2	0	TV/movies	NA
Tooth et al,⁸³ 2019
Cohort 1	316	9.56	50	2015	Q	<2	0	Mixed	AU/NZ
Cohort 2	1007	37.5	50	2015	Q	2-5	1	Mixed	AU/NZ
Turer et al,⁸⁴ 2013	400	42	56	2007	Q	2-5	2	Mixed	NA
Vanderloo and Tucker,⁸⁵ 2015
Cohort 1	40	12	45	2013	Q	<2	0	Mixed	NA
Cohort 2	40	25.7	45	2013	Q	2-5	1	Mixed	NA
Vandewater et al,⁸⁶ 2007
Cohort 1	412	15	50	2005	I	<2	0	Mixed	NA
Cohort 2	303	42	50	2005	I	2-5	2	Mixed	NA
Venetsanou et al,²² 2020
Cohort 1	182	52.6	39.5	2009	Q	2-5	1	Mixed	EU
Cohort 2	161	52.5	38.5	2012	Q	2-5	1	Mixed	EU
Cohort 3	165	53	39	2015	Q	2-5	1	Mixed	EU
Cohort 4	144	52.8	42	2018	Q	2-5	1	Mixed	EU
Wu et al,⁸⁷ 2017	8900	52.4	52.9	2015	Q	2-5	2	Mixed	Asia
Xu et al,⁸⁸ 2016	369	60	50.4	2013	I	2-5	1	Mixed	AU/NZ
Yang-Huang et al,⁸⁹ 2018	4833	48.9	51.1	2006	Q	2-5	1	TV/movies	EU

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Abbreviations: AU/NZ, Australia/New Zealand; C, combined; D, diary; EU, Europe; I, interview; M.East, Middle East; NA, North America; ND, no dates provided; Q, questionnaire.

Pooled Prevalence of Children Younger Than 2 Years Meeting the Screen Time Guideline

A meta-analysis of 26 studies revealed a pooled prevalence rate of 0.24 (95% CI, 0.19-0.32; eFigure 1 in the Supplement). Thus, 24.7% (95% CI, 19.0%-31.5%) of children younger than 2 years are meeting and 75.3% are exceeding the screen use guideline. The funnel plot was symmetrical (eFigure 2 in the Supplement); however, the Egger test was statistically significant (P = .03). There was significant between-study heterogeneity (Q = 859.88, P < .001, I² = 97.09). Significant moderators are reported below and presented in Table 2.

Table 2. Moderator Analyses for the Prevalence of Children Younger Than 2 Years Meeting the Screen Time Guidelines.

	k	Rate or coefficient (95% CI)^a	Q or z score^b	P value
Categorical moderators
Screen time assessment			4.24	.04
Interview	7	0.181 (0.103 to 0.299)^d
Questionnaire	16	0.335 (0.248 to 0.435)^e
Screen type^c			11.70	.001
Mixed screens	10	0.360 (0.279 to 0.449)^e
TV/movies only	14	0.164 (0.109 to 0.240)^d
Geographical location			2.52	.11
Australia	9	0.344 (0.253 to 0.448)^e
North America	13	0.225 (0.140 to 0.342)^d
Continuous moderators
Child age	26	−0.031 (−0.150 to 0.089)	−0.50	.62
% Male	26	3.44 (−12.43 to 19.32)	0.42	.68
Year of data collection	24	0.089 (0.009 to 0.170)	2.18	.03
Study quality	26	−0.319 (−0.707 to 0.069)	−1.61	.11

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^{^a}

Rate reported for categorical moderators, and coefficient (indicating log odds for event rate) reported for continuous moderators.

^{^b}

Q statistic reported for categorical moderators, and z score reported for continuous moderators.

^{^c}

There were too few studies examining computer and tablet only to include in this moderator analysis.

^{^d}

P < .01.

^{^e}

P < .05.

For categorical moderators, screen time assessment method and screen type were significant (Q = 4.24, P = .04, and Q = 11.70, P = .001, respectively). Prevalence of meeting the screen time guideline was higher in studies where screen time was assessed via questionnaires (event rate: 0.34; 95% CI, 0.25-0.44) vs interview methods (event rate: 0.18; 95% CI, 0.10-0.30), and in studies where screen time was a combination of screen use activities (eg, TV/movies, tablets, and computers; event rate: 0.36; 95% CI, 0.28-0.45) vs TV/movies only (event rate: 0.16; 95% CI, 0.11-0.24). Meta-regression analyses indicated that prevalence of meeting screen time guidelines increased as year of data collection increased (b = 0.09; 95% CI, 0.01-0.17). Specifically, meeting the screen time guidelines was 2.43 times more likely in studies where data collection was more recent (range: 1999-2017).

Pooled Prevalence of Children Aged 2 to 5 Years Meeting the 1-Hour-Daily Screen Time Guideline

A meta-analysis of 44 studies revealed a pooled prevalence rate of 0.36 (95% CI, 0.31-0.41; eFigure 3 in the Supplement). Thus, 35.6% (95% CI, 30.6%-40.9%) of children aged 2 to 5 years are meeting and 64.4% are exceeding the 1-hour-daily screen use guideline. The funnel plot was symmetrical (eFigure 4 in the Supplement), and the Egger test was not significant (P = .07). There was significant between-study heterogeneity (Q = 3711.83, P < .001, I² = 98.84). Significant moderators are reported below and in Table 3.

Table 3. Moderator Analyses for the Prevalence of Children Aged 2 to 5 Years Meeting the 1-Hour-Daily Screen Time Guidelines.

	k	Rate or coefficient (95% CI)^a	Q or z score^b	P value
Categorical moderators
Screen time assessment			3.00	.09
Interview	7	0.255 (0.287 to 0.222)^d
Questionnaire	36	0.371 (0.312 to 0.434)^d
Screen type^c			11.70	.02
Mixed screens	28	0.310 (0.250 to 0.373)^e
TV/movies only	14	0.424 (0.355 to 0.496)^f
Geographical location			1.03	.79
Asia	4	0.430 (0.248 to 0.633)
Australia	12	0.327 (0.246 to 0.419)^d
Europe	20	0.351 (0.286 to 0.421)^d
North America	8	0.386 (0.211 to 0.597)
Continuous moderators
Child age	44	−0.033 (−0.068 to 0.003)	−1.79	.08
% Male	44	6.67 (−0.765 to 14.11)	1.76	.08
Year of data collection	24	0.087 (0.032 to 0.145)	−1.12	.27
Study quality	42	−0.042 (−0.115 to 0.031)	0.16	.88

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^{^a}

Rate reported for categorical moderators, and coefficient (indicating log odds for event rate) reported for continuous moderators.

^{^b}

Q statistic reported for categorical moderators, and z score reported for continuous moderators.

^{^c}

There were too few studies examining computer and tablet only to include in this moderator analysis.

^{^d}

P < .001.

^{^e}

P < .01.

^{^f}

P < .05.

Categorical moderator analyses revealed that screen type was significant (Q = 11.70, P = .02). Prevalence of meeting the guideline was higher in studies where screen time was TV/movies only (event rate: 0.42; 95% CI, 0.36-0.50) vs a combination of screen use activities (event rate: 0.31; 95% CI, 0.25-0.37).

Pooled Prevalence of Children Aged 2 to 5 Years Meeting the 2-Hours-Daily Screen Time Guideline

A meta-analysis of 25 studies revealed a pooled prevalence rate of 0.56 (95% CI, 0.50-0.62; eFigure 5 in the Supplement). Thus, 56.0% of children aged 2 to 5 years are meeting and 44.0% are exceeding the 2-hours-daily guideline. The funnel plot was symmetrical (eFigure 6 in the Supplement), and the Egger test was not significant (P = .44). There was significant between-study heterogeneity (Q = 3229.87, P < .001, I² = 99.26). Moderators were tested, but none was significant (Table 4).

Table 4. Moderator Analyses for the Prevalence of Children Aged 2 to 5 Years Meeting the 2-Hours-Daily Screen Time Guidelines.

	k	Rate or coefficient (95% CI)^a	Q or z score^b	P value
Categorical moderators
Screen time assessment			1.02	.32
Interview	5	0.623 (0.440 to 0.776)
Questionnaire	19	0.525 (0.468 to 0.581)
Screen type^c			0.23	.63
Mixed screens	18	0.550 (0.480 to 0.618)
TV/movies only	7	0.583 (0.466 to 0.693)
Geographical location			0.36	.55
Australia	4	0.562 (0.509 to 0.613)^d
North America	17	0.528 (0.431 to 0.623)
Continuous moderators
Child age	25	−0.003 (−0.034 to 0.039)	0.15	.89
% Male	25	−4.79 (−15.61 to 6.03)	−0.87	.39
Year of data collection	24	0.026 (−0.070 to 0.121)	0.53	.60
Study quality	25	0.023 (−0.421 to 0.047)	0.10	.92

Open in a new tab

^{^a}

Rate reported for categorical moderators, and coefficient (indicating log odds for event rate) reported for continuous moderators.

^{^b}

Q statistic reported for categorical moderators, and z score reported for continuous moderators.

^{^c}

There were too few studies examining computer and tablet only to include in this moderator analysis.

^{^d}

P < .05.

Discussion

To our knowledge, this is the first meta-analysis of the prevalence of meeting screen time guidelines in children aged 5 years or younger. We demonstrated that a minority of children are meeting guidelines^12,13,14,15; specifically, 1 in 4 (24.7%) children younger than 2 years and 1 in 3 (35.6%) children aged 2 to 5 years. For children aged 2 to 5 years, the prevalence of meeting the guideline was significantly higher when screen use limits were designated as 2 hours daily (56.0%) vs 1 hour daily (35.6%). Research has shown that the threshold or digital tipping point for this age range is 1 hour a day. For example, young children using screens 2 hours daily or 3 hours or more, when compared with 1 hour a day, show an increased likelihood of reported behavioral problems and poor developmental outcomes.⁹⁰ The finding that a higher proportion of children are meeting the 2-hours-daily guideline is important for public health initiatives because it suggests that for many families only minor adjustments may be needed to meet the evidence-based recommendation of 1 hour a day.

When examining year of data collection, for children younger than 2 years the prevalence of meeting the guidelines was higher when data collection occurred more recently. This finding may suggest that public awareness of the guidelines over the last decade has increased. However, this time trend was not observed for children aged 2 to 5 years, suggesting that adherence to screen use guidelines has not substantially changed over time for this age group. This is also an inherently more difficult age group to monitor given known fluxes in media usage (eg, use of tablets in addition to TV). It is also possible that the method of measuring adherence to guidelines is changing, as are the type and context of screen use (eg, more mobile use was often not measured in earlier studies), making it difficult to identify the true time effect.

Interestingly, the prevalence of meeting the guidelines differed across age groups based on how screen time was measured. Children younger than 2 years were more likely to meet the screen time guideline when measured as a combination of screen use activities, compared with TV/movies only. Alternatively, children 2 to 5 years of age were more likely to meet the 1-hour-daily guideline when screen time was measured as TV/movies only, vs a combination of screen use activities. This pattern of results may suggest that there is a change in screen use patterns with age, where younger children tend to consume more TV/movies, whereas older children may be more likely to engage in a variety of screen use activities (eg, TV/movies, tablets, computer, video games). This finding also suggests that policy and practice recommendations may need to include specific examples based on the target age range. For example, clearly explaining to families that children younger than 2 years often exceed screen time limits through viewing TV/movies may help draw awareness to a specific screen time activity.

The meta-analysis for children younger than 2 years revealed that more children were meeting the screen time guideline when questionnaire methods were used vs when interviews were used. With greater methodological challenges associated with measuring screen use in young children,⁹¹ specifically measurement tools (eg, lack of psychometric properties for current measures), this is not surprising. Interview methods tended to reveal higher-quality data and are considered a more rigorous methodology, which is likely to capture a more accurate assessment of screen use activities. Questionnaire methods can be influenced by social desirability and difficulties with accurate recall.^91,92 One promising tool to improve measurement accuracy of screen use is mobile output sampling, which is using the mobile device to track media duration, time of day, and program content.⁹³ While this type of measurement could improve screen time methodology, mobile sampling is also limited by difficulties differentiating between screen users and tracking data from multiple devices (eg, TV). Nonetheless, there is a clear need for advances in the field of media research to more accurately measure screen use in children.

Our results demonstrate that the majority of children 5 years and younger are not meeting screen time guidelines. Given that a universal touchpoint for families is pediatric primary care, pediatricians should ask about family media use and talk about the importance of growth-enhancing offline activities such as reading, play, physical activity, movement, and social interaction.¹¹ Starting these conversations early in the child’s care is important because poor screen use habits formed in young children are likely to be maintained over time.⁹⁴ Resources such as the American Academy of Pediatrics Family Media Use Plan⁹⁵ can help families self-assess use and set media goals. Since the introduction of smartphones in the early 2000s and tablets in 2010, children have more access to mobile devices, making it more difficult for parents to co-view and monitor screens.⁹³ Rapid changes in mobile digital accessibility and content targeted at children,² as well as the reported increases in screen use during the COVID-19 pandemic,²⁶ have placed additional pressures on families. More studies are needed to assess the effect that device access during the pandemic has had on child outcomes. Guidelines may need to be contextualized within the changing digital landscape.

Limitations

First, many studies reported a screen time composite where it was unclear what proportion of screen time each device contributed. Second, the majority of research to date on the proportion of children meeting the screen time guidelines is focused on screen time duration; however, content (eg, educational) and context (eg, co-viewing) are other important aspects of the screen use guidelines that should be evaluated in future research. Third, only studies with the search terms in the titles, abstracts, keywords, or database indexing fields can be identified in the systematic search. Thus, it is possible that some studies were missed if key search terms appeared only in the body of the article. We tried to circumvent this issue by reviewing the references of all included studies as an added search method. Fourth, the current study did not examine how the proportion of children meeting the screen time guidelines varies by sociodemographic factors (eg, family income, race/ethnicity), as there were insufficient data in individual studies to examine this moderator, so the results from this study may not be reflective of all children 5 years and younger.

Conclusions

Young children are the fastest-growing users of digital media,² and parents often report that their child’s screen use is a top parenting concern.⁹⁶ This meta-analysis demonstrates that the majority of children 5 years and younger are not meeting screen time guidelines. Pediatricians play a major role in helping support and provide resources to families. Policy changes directed at industry, such as easier and more transparent device settings, could help families better set limits. Given how many children exceed screen time guidelines, industry elimination of ads from programming and apps directed at children⁹⁷ would support healthier outcomes. Digital media are now a regular part of young children’s lives, and supporting families to best fit evidence-based recommendations into their daily routines needs to be a priority.

Supplement.

eTable 1. Example Search Strategy From PsycINFO.

eTable 2. Study Quality Evaluation Criteria

eTable 3. Quality Assessment of Studies Included

eFigure 1. Forest Plot of Studies Examining the Prevalence of Meeting the Screen Time Guideline (0hrs/day) for Children Under the Age of 2 Years

eFigure 2. Funnel Plot for Studies Included in the Meta-analysis on the Prevalence of Children under Age 2 Meeting Screen Time Guidelines

eFigure 3. Forest Plot of Studies Examining the Prevalence of Meeting the Screen Time Guideline of ≤ 1hr/day for Children 2 to 5 Years of Age

eFigure 4. Funnel Plot for Studies Included in the Meta-analysis on the Prevalence of Children between Ages 2 to 5 Meeting the 1/hr Screen Time Guidelines

eFigure 5. Forest Plot of Studies Examining the Prevalence of Meeting the Screen Time Guideline of 2hrs/day for Children 2 to 5 Years of Age

eFigure 6. Funnel Plot for Studies Included in the Meta-analysis on the Prevalence of Children between Ages 2 to 5 Meeting the 2/hr Screen Time Guidelines

Click here for additional data file.^{(1.8MB, pdf)}

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement.

eTable 1. Example Search Strategy From PsycINFO.

eTable 2. Study Quality Evaluation Criteria

eTable 3. Quality Assessment of Studies Included

eFigure 1. Forest Plot of Studies Examining the Prevalence of Meeting the Screen Time Guideline (0hrs/day) for Children Under the Age of 2 Years

eFigure 2. Funnel Plot for Studies Included in the Meta-analysis on the Prevalence of Children under Age 2 Meeting Screen Time Guidelines

eFigure 3. Forest Plot of Studies Examining the Prevalence of Meeting the Screen Time Guideline of ≤ 1hr/day for Children 2 to 5 Years of Age

eFigure 4. Funnel Plot for Studies Included in the Meta-analysis on the Prevalence of Children between Ages 2 to 5 Meeting the 1/hr Screen Time Guidelines

eFigure 5. Forest Plot of Studies Examining the Prevalence of Meeting the Screen Time Guideline of 2hrs/day for Children 2 to 5 Years of Age

eFigure 6. Funnel Plot for Studies Included in the Meta-analysis on the Prevalence of Children between Ages 2 to 5 Meeting the 2/hr Screen Time Guidelines

Click here for additional data file.^{(1.8MB, pdf)}

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PERMALINK

Global Prevalence of Meeting Screen Time Guidelines Among Children 5 Years and Younger

Brae Anne McArthur, PhD, RPsych

Valeriya Volkova, BSc

Suzy Tomopoulos, MD

Sheri Madigan, PhD, RPsych

Key Points

Question

Findings

Meaning

Abstract

Importance

Objective

Data Sources

Study Selection

Data Extraction and Synthesis

Main Outcomes and Measures

Results

Conclusions and Relevance

Introduction

Methods

Search Strategy

Study Inclusion and Exclusion Criteria

Figure. Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) Flow Diagram Detailing the Search Strategy.

Data Extraction

Study Quality

Data Analysis

Results

Study Characteristics

Table 1. Study Characteristics of Studies Included in the Meta-analyses.

Pooled Prevalence of Children Younger Than 2 Years Meeting the Screen Time Guideline

Table 2. Moderator Analyses for the Prevalence of Children Younger Than 2 Years Meeting the Screen Time Guidelines.

Pooled Prevalence of Children Aged 2 to 5 Years Meeting the 1-Hour-Daily Screen Time Guideline

Table 3. Moderator Analyses for the Prevalence of Children Aged 2 to 5 Years Meeting the 1-Hour-Daily Screen Time Guidelines.

Pooled Prevalence of Children Aged 2 to 5 Years Meeting the 2-Hours-Daily Screen Time Guideline

Table 4. Moderator Analyses for the Prevalence of Children Aged 2 to 5 Years Meeting the 2-Hours-Daily Screen Time Guidelines.

Discussion

Limitations

Conclusions

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

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