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Table 1.  Summary of Adolescent-Reported Screen Time Use During the COVID-19 Pandemic by Sociodemographic Characteristics Among 5412 Participants in the Adolescent Brain Cognitive Development Study, May 2020a
Summary of Adolescent-Reported Screen Time Use During the COVID-19 Pandemic by Sociodemographic Characteristics Among 5412 Participants in the Adolescent Brain Cognitive Development Study, May 2020a
Table 2.  Mental Health and Resiliency Factors Associated With Total Screen Time Use During the COVID-19 Pandemic Among 5412 Participants in the Adolescent Brain Cognitive Development Study, May 2020a
Mental Health and Resiliency Factors Associated With Total Screen Time Use During the COVID-19 Pandemic Among 5412 Participants in the Adolescent Brain Cognitive Development Study, May 2020a
1.
Stiglic  N, Viner  RM.  Effects of screentime on the health and well-being of children and adolescents: a systematic review of reviews.   BMJ Open. 2019;9(1):e023191. doi:10.1136/bmjopen-2018-023191 PubMedGoogle Scholar
2.
Anderson  SE, Economos  CD, Must  A.  Active play and screen time in US children aged 4 to 11 years in relation to sociodemographic and weight status characteristics: a nationally representative cross-sectional analysis.   BMC Public Health. 2008;8(1):366. doi:10.1186/1471-2458-8-366 PubMedGoogle ScholarCrossref
3.
Guo  YF, Liao  MQ, Cai  WL,  et al.  Physical activity, screen exposure and sleep among students during the pandemic of COVID-19.   Sci Rep. 2021;11(1):8529. doi:10.1038/s41598-021-88071-4 PubMedGoogle ScholarCrossref
4.
Werling  AM, Walitza  S, Drechsler  R.  Impact of the COVID-19 lockdown on screen media use in patients referred for ADHD to child and adolescent psychiatry: an introduction to problematic use of the internet in ADHD and results of a survey.   J Neural Transm (Vienna). 2021;128(7):1033-1043. doi:10.1007/s00702-021-02332-0 PubMedGoogle ScholarCrossref
5.
Bagot  KS, Matthews  SA, Mason  M,  et al.  Current, future and potential use of mobile and wearable technologies and social media data in the ABCD study to increase understanding of contributors to child health.   Dev Cogn Neurosci. 2018;32:121-129. doi:10.1016/j.dcn.2018.03.008 PubMedGoogle ScholarCrossref
6.
Nagata  JM, Iyer  P, Chu  J,  et al.  Contemporary screen time modalities among children 9-10 years old and binge-eating disorder at one-year follow-up: a prospective cohort study.   Int J Eat Disord. 2021;54(5):887-892. doi:10.1002/eat.23489 PubMedGoogle ScholarCrossref
1 Comment for this article
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Screen time usage in Children in this pandemic
Harikrishnan Pandurangan, MDS, FDSRCS(England), PhD | Teeth "N" Jaws Center, Lake Area, Chennai-600034, India
This nice study by Nagata et al. reveals the effect of pandemic on children's screen time with sociodemographic factors. We don't have similar data from our Indian sub-continent, but I would share some observations on screen time usage by children/adolescents of age 10-15 years in this pandemic.

During the complete lockdown in the beginning of this pandemic, in the rural areas the kids where involved in outdoor games and less with screen devices. Whereas in the urban and sub-urban areas kids remained more indoors due to strict police monitoring and were more with screen devices. As the lockdown eased
out partially, even the urban kids did more of outdoor activities and less of screen time.

As the schools opened up, all the kids were forced to spend 2-4 hours of online education according to their class levels and had more screen time along with their entertainment activities on the devices. They spent additional screen time on their class assignments which totalled to an average of 6-8 hours of screen time or even more each day.

Lower socioeconomic kids had lesser screen time due to the less availability of the devices and the internet connections and affordability compared to higher socioeconomic kids.

It will be interesting to know the positive and negative consequences of more screen time in the children/adolescents regionwise, which will vary globally due to the cultural and varying tolerance limits in children of different regions.
CONFLICT OF INTEREST: None Reported
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Research Letter
November 1, 2021

Screen Time Use Among US Adolescents During the COVID-19 Pandemic: Findings From the Adolescent Brain Cognitive Development (ABCD) Study

Author Affiliations
  • 1Department of Pediatrics, University of California, San Francisco
  • 2Fielding School of Public Health, University of California, Los Angeles
  • 3Factor-Inwentash Faculty of Social Work, University of Toronto, Toronto, Ontario, Canada
  • 4Department of Epidemiology and Biostatistics, University of California, San Francisco
  • 5Center for Health Sciences, SRI International, Menlo Park, California
JAMA Pediatr. 2022;176(1):94-96. doi:10.1001/jamapediatrics.2021.4334

Excessive screen use in adolescents has been associated with physical and mental health risks,1 and there are known disparities in screen use across sex, race and ethnicity, and income in adolescents.2 The COVID-19 pandemic and subsequent stay-at-home mandates, online learning, and social distancing requirements have led to an increasing reliance on digital media (ie, screens) for nearly all facets of adolescents’ lives (eg, entertainment, socialization, education). Although studies conducted worldwide have suggested an increase in screen time among children and teens during the pandemic,3,4 this has not yet been explored using national US data. The aims of this study were to evaluate adolescents’ self-reported screen use during the pandemic across 7 modalities by sociodemographic categories and to assess mental health and resiliency factors associated with screen use among a demographically diverse, national sample of children and adolescents aged 10 to 14 years.

Methods

Cross-sectional data from the May 2020 COVID-19 survey (COVID-19 Rapid Response Research Release) from the Adolescent Brain Cognitive Development (ABCD) Study were analyzed. The sample consisted of 5412 adolescents predominantly aged 12 to 13 years. Centralized institutional review board approval was obtained from the University of California, San Diego. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline. Written informed consent and assent were obtained from a parent or guardian and the child, respectively, to participate in the ABCD study.

Screen use for the following modalities was determined using adolescents’ self-reported hours of use on a typical day, excluding hours spent on school-related work: multiple-player gaming, single-player gaming, texting, social media, video chatting, browsing the internet, and watching or streaming movies, videos, or television shows.5 Total typical daily screen use, excluding schoolwork, was calculated as the sum. Multiple linear regression analyses estimated associations between mental health and resiliency factors (eMethods in the Supplement provides the measures) and total screen use, after adjustment for potential confounders including sex, race and ethnicity (as self-reported from a list of categories), annual household income, parent educational level, and study site. Analyses were conducted in 2021 using Stata 15.1, weighting data to approximate the American Community Survey by the US Census. Testing was 2-sided, and P < .05 was considered statistically significant.

Results

Among the 5412 adolescents included in our sample, 50.7% were female and 49.3% were male. The sample was racially and ethnically diverse (7.2% Asian; 11.1% Black; 17.2% Hispanic, Latina, and Latino; 2.5% Native American; 60.6% White; and 1.4% self-reported as other). Adolescents reported a mean (SD) of 7.70 (5.74) h/d of screen use, mostly spent on watching or streaming videos, movies, or television shows (2.42 [2.45] h/d), multiple-player gaming (1.44 [2.21] h/d), and single-player gaming (1.17 [1.82] h/d). The mean and SD screen use time for each modality by sociodemographic characteristics are given in Table 1. In adjusted models (Table 2), poorer mental health (B, 0.29; 95% CI, 0.06-0.52; P = .01) and greater perceived stress (B, 0.67; 95% CI, 0.43-0.91; P < .001) were associated with higher total screen use, while more social support (B, −0.32; 95% CI, −0.59 to −0.04; P = .02) and coping behaviors (B, −0.17; 95% CI, −0.26 to −0.09; P < .001) were associated with lower total screen use.

Discussion

In this cross-sectional study of a large, national sample of adolescents surveyed early in the COVID-19 pandemic, we found that the mean total daily screen use was 7.70 h/d. This is higher than prepandemic estimates (3.8 h/d) from the same cohort at baseline, although younger age and slightly different screen time categories could also account for differences.6 Despite the gradual reversal of quarantine restrictions, studies have suggested that screen use may remain persistently elevated.4 Screen time disparities across racial, ethnic, and income groups in adolescents have been reported previously and may be due to structural and systemic racism–driven factors (eg, built environment, access to financial resources, and digital media education)—all of which have been amplified in the COVID-19 pandemic.2 Different screen use modalities may have differential positive or negative consequences for adolescents’ well-being during the COVID-19 pandemic. Adolescents experiencing stress and poor mental health may use screens to manage negative feelings or withdraw from stressors. Although some screen modalities may be used to promote social connection, higher coping behaviors and social support in this sample were associated with lower total screen usage. Limitations of this study include the use of self-reported data. Furthermore, adolescents often multitask on screens; thus, the computed total could be an overestimate. Future studies should examine screen use trends as pandemic restrictions are lifted and also explore mechanisms to prevent sociodemographic disparities.

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Article Information

Accepted for Publication: August 30, 2021.

Published Online: November 1, 2021. doi:10.1001/jamapediatrics.2021.4334

Corresponding Author: Jason M. Nagata, MD, MSc, Department of Pediatrics, University of California, San Francisco, 550 16th St, Fourth Floor, Box 0110, San Francisco, CA 94158 (jason.nagata@ucsf.edu)

Author Contributions: Dr Nagata and Ms Cortez had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Nagata, Cortez, Cattle, Ganson.

Acquisition, analysis, or interpretation of data: Nagata, Cortez, Ganson, Iyer, Bibbins-Domingo, Baker.

Drafting of the manuscript: Nagata, Cortez, Cattle, Iyer.

Critical revision of the manuscript for important intellectual content: Nagata, Cortez, Ganson, Iyer, Bibbins-Domingo, Baker.

Statistical analysis: Nagata, Cortez.

Administrative, technical, or material support: Ganson.

Supervision: Nagata.

Conflict of Interest Disclosures: Dr Baker reported receiving grants from the NIH during the conduct of the study.

Funding/Support: This study was supported in part by grant K08HL159350 from the National Institutes of Health (NIH) (Dr Nagata). Dr Nagata was also funded by Career Development Award CDA34760281 from the American Heart Association.

Role of the Funder/Sponsor: The funding organizations 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 Information: The Adolescent Brain Cognitive Development (ABCD) Study was supported by the National Institutes of Health and additional federal partners under award numbers U01DA041022, U01DA041025, U01DA041028, U01DA041048, U01DA041089, U01DA041093, U01DA041106, U01DA041117, U01DA041120, U01DA041134, U01DA041148, U01DA041156, U01DA041174, U24DA041123, and U24DA041147. A full list of supporters is available at https://abcdstudy.org/?s=nIH+collaborators. A listing of participating sites and a complete listing of the study investigators can be found at https://abcdstudy.org/principal-investigators.html. The ABCD consortium investigators designed and implemented the study and/or provided data but did not necessarily participate in the analysis or writing of this report.

References
1.
Stiglic  N, Viner  RM.  Effects of screentime on the health and well-being of children and adolescents: a systematic review of reviews.   BMJ Open. 2019;9(1):e023191. doi:10.1136/bmjopen-2018-023191 PubMedGoogle Scholar
2.
Anderson  SE, Economos  CD, Must  A.  Active play and screen time in US children aged 4 to 11 years in relation to sociodemographic and weight status characteristics: a nationally representative cross-sectional analysis.   BMC Public Health. 2008;8(1):366. doi:10.1186/1471-2458-8-366 PubMedGoogle ScholarCrossref
3.
Guo  YF, Liao  MQ, Cai  WL,  et al.  Physical activity, screen exposure and sleep among students during the pandemic of COVID-19.   Sci Rep. 2021;11(1):8529. doi:10.1038/s41598-021-88071-4 PubMedGoogle ScholarCrossref
4.
Werling  AM, Walitza  S, Drechsler  R.  Impact of the COVID-19 lockdown on screen media use in patients referred for ADHD to child and adolescent psychiatry: an introduction to problematic use of the internet in ADHD and results of a survey.   J Neural Transm (Vienna). 2021;128(7):1033-1043. doi:10.1007/s00702-021-02332-0 PubMedGoogle ScholarCrossref
5.
Bagot  KS, Matthews  SA, Mason  M,  et al.  Current, future and potential use of mobile and wearable technologies and social media data in the ABCD study to increase understanding of contributors to child health.   Dev Cogn Neurosci. 2018;32:121-129. doi:10.1016/j.dcn.2018.03.008 PubMedGoogle ScholarCrossref
6.
Nagata  JM, Iyer  P, Chu  J,  et al.  Contemporary screen time modalities among children 9-10 years old and binge-eating disorder at one-year follow-up: a prospective cohort study.   Int J Eat Disord. 2021;54(5):887-892. doi:10.1002/eat.23489 PubMedGoogle ScholarCrossref
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