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Guo Y, Dhaliwal J, Rights JD. Disaggregating level-specific effects in cross-classified multilevel models. Behav Res Methods 2024; 56:3023-3057. [PMID: 37993674 DOI: 10.3758/s13428-023-02238-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/06/2023] [Indexed: 11/24/2023]
Abstract
In psychology and other fields, data often have a cross-classified structure, whereby observations are nested within multiple types of non-hierarchical clusters (e.g., repeated measures cross-classified by persons and stimuli). This paper discusses ways that, in cross-classified multilevel models, slopes of lower-level predictors can implicitly reflect an ambiguous blend of multiple effects (for instance, a purely observation-level effect as well as a unique between-cluster effect for each type of cluster). The possibility of conflating multiple effects of lower-level predictors is well recognized for non-cross-classified multilevel models, but has not been fully discussed or clarified for cross-classified contexts. Consequently, in published cross-classified modeling applications, this possibility is almost always ignored, and researchers routinely specify models that conflate multiple effects. In this paper, we show why this common practice can be problematic, and show how to disaggregate level-specific effects in cross-classified models. We provide a novel suite of options that include fully cluster-mean-centered, partially cluster-mean-centered, and contextual effect models, each of which provides a unique interpretation of model parameters. We further clarify how to avoid both fixed and random conflation, the latter of which is widely misunderstood even in non-cross-classified models. We provide simulation results showing the possible deleterious impact of such conflation in cross-classified models, and walk through pedagogical examples to illustrate the disaggregation of level-specific effects. We conclude by considering additional model complexities that can arise with cross-classification, providing guidance for researchers in choosing among model specifications, and describing newly available software to aid researchers who wish to disaggregate effects in practice.
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Affiliation(s)
- Yingchi Guo
- Department of Psychology, University of British Columbia, 2136 West Mall, Vancouver, BC, V6T1Z4, Canada.
| | - Jeneesha Dhaliwal
- Department of Psychology, University of British Columbia, 2136 West Mall, Vancouver, BC, V6T1Z4, Canada
| | - Jason D Rights
- Department of Psychology, University of British Columbia, 2136 West Mall, Vancouver, BC, V6T1Z4, Canada
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2
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Yamada M, Sekine M, Tatsuse T. Association between excessive screen time and school-level proportion of no family rules among elementary school children in Japan: a multilevel analysis. Environ Health Prev Med 2024; 29:16. [PMID: 38494706 PMCID: PMC10957336 DOI: 10.1265/ehpm.23-00268] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Accepted: 02/24/2024] [Indexed: 03/19/2024] Open
Abstract
BACKGROUND Excessive screen time (ST) in children is a global concern. We assessed the association between individual- and school-level factors and excessive ST in Japanese children using a multilevel analysis. METHODS A school-based cross-sectional study was conducted in Toyama, Japan in 2018. From 110 elementary schools in Toyama Prefecture, 13,413 children in the 4th-6th grades (boys, 50.9%; mean, 10.5 years old) participated. We assessed lifestyle, recreational ST (not for study use), psychological status, and school and family environment including family rules. We defined ≥3 hours ST as excessive. We calculated the school-level proportions of no family rules and divided them into four categories (<20%, 20% to <30%, 30% to <40%, and ≥40%). A modified multilevel Poisson regression analysis was performed. RESULTS In total, 12,611 children were included in the analysis (94.0%). The average school-level proportion of those with no family rules was 32.1% (SD = 9.6). The prevalence of excessive ST was 29.9% (34.9% in boys; 24.8% in girls). The regression analysis showed that excessive ST was significantly associated with both individual-level factors, such as boys (adjusted prevalence ratio (aPR); 1.39), older grades (aPR; 1.18 for 5th grades and 1.28 for 6th grades), late wakeup (aPR; 1.13), physical inactivity (aPR; 1.18 for not so much and 1.31 for rarely), late bedtime (aPR; 1.43 for 10 to 11 p.m. and 1.76 for ≥11 p.m.), frequent irritability (aPR; 1.24 for sometimes and 1.46 for often), feelings of school avoidance (aPR; 1.17 for sometimes and 1.22 for often), infrequent child-parental interaction (aPR; 1.16 for rare and 1.21 for none), no family rules (aPR; 1.56), smartphone ownership (aPR; 1.18), and the school-level proportion of no family rules (aPR; 1.20 for 20% to <30%, 1.29 for 30% to <40%, and 1.43 for ≥40%, setting <20% as reference). CONCLUSION Besides individual factors, a higher school-level proportion of no family rules seemed influential on excessive ST. Increasing the number of households with family rules and addressing individual factors, could be deterrents against excessive ST in children.
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Affiliation(s)
- Masaaki Yamada
- Department of Epidemiology and Health Policy, School of Medicine, University of Toyama, Toyama, Japan
| | - Michikazu Sekine
- Department of Epidemiology and Health Policy, School of Medicine, University of Toyama, Toyama, Japan
| | - Takashi Tatsuse
- Department of Epidemiology and Health Policy, School of Medicine, University of Toyama, Toyama, Japan
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3
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Mackey AW, Ralston PA, Young-Clark I, Coccia CC. Life Satisfaction and Emerging Health Behaviors in Underserved Adolescents: A Narrative Review. Am J Health Behav 2023; 47:479-488. [PMID: 37596754 DOI: 10.5993/ajhb.47.3.5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/20/2023]
Abstract
Objectives: Obesity rates continue to rise in underserved adolescents. Obesity is linked to poor mental health outcomes. The purpose of this narrative review is to examine existing literature on life satisfaction and obesity-related emerging health behaviors (sugar-sweetened beverage consumption, sleeping patterns, and screen time) in underserved adolescents. Methods: We conducted a review of articles published in English between January 1995 and November 2021 to develop a narrative summary. Results: In general, few studies have been conducted investigating life satisfaction and the emerging behaviors of sugar-sweetened beverage consumption, sleeping patterns, and screen time use with adolescents, especially underserved adolescents. In the studies reviewed, we noted links between lower life satisfaction and more than once-a-day sugar consumption, including sugar-sweetened beverages, lower life satisfaction and lower sleep duration, and life satisfaction and screen-time, with both positive and negative relationships shown. Conclusions: Given the limitations in the number of studies, recommendations are provided for future research.
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Affiliation(s)
- Alexandria W Mackey
- College of Medicine, Florida State University, Tallahassee, FL, United States
| | - Penny A Ralston
- Center on Better Health and Life for Underserved Populations, Florida State University, Tallahassee, FL, United States
| | - Iris Young-Clark
- Center on Better Health and Life for Underserved Populations, Florida State University, Tallahassee, FL, United States
| | - Catherine C Coccia
- Department of Dietetics & Nutrition, Florida International University, Miami, FL, United States
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4
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Uddin H, Hasan MK. Family resilience and neighborhood factors affect the association between digital media use and mental health among children: does sleep mediate the association? Eur J Pediatr 2023:10.1007/s00431-023-04898-1. [PMID: 36922452 PMCID: PMC10257603 DOI: 10.1007/s00431-023-04898-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Revised: 02/21/2023] [Accepted: 02/22/2023] [Indexed: 03/18/2023]
Abstract
The associations between digital media use and mental well-being among children and adolescents have been inconclusive. We examined (i) the associations between digital media use and mental health outcomes, anxiety, depression, and ADHD, (ii) whether family resilience and neighborhood factors attenuate the associations, and (iii) whether sleep mediates these associations. We used the National Survey of Children's Health data from 2019 to 2020. A total of 45,989 children's (6-17 years) data were analyzed in this study. Multivariate logistic regression was used to assess the associations between digital media use and anxiety, depression, and ADHD. Path models and Paramed command in STATA were used to test the role of sleep as a mediator of these associations. The prevalence of heavy digital media users (who spent 4 or more hours per day) among the analytic sample was 30.52%, whereas anxiety was 13.81%, depression was 5.93%, and ADHD was 12.41%. Children in the heavy media user group had 63% increased odds of anxiety (95% CI: 1.32-2.01) and 99% increased odds of depression (95% CI: 1.35-2.94) after adjusting for sociodemographic factors, compared to the children in light media user group (who spent < 2 h per day), and these relations were significant at 0.01 level. However, family resilience and community factors significantly attenuated the effect of digital media use on anxiety and depression. Sleep did not mediate the associations between digital media use and anxiety or depression. Conclusions: Family resilience and neighborhood factors protect against the harmful effects of digital media use. Further research is needed to examine the relationships of media contents, the presence of electronic devices in bedrooms, and sleep quality with mental health. What is Known: • Spending long hours on digital media may adversely affect children and adolescents' health and development. However, the mediating role of sleep in the association between digital media use and mental health outcomes is inconclusive. What is New: • Digital media use has detrimental effects on anxiety and depression. However, family resilience and neighborhood factors attenuated the association. The study highlights the importance of positive family functioning and neighborhood conditions reducing the harmful effects of digital media use.
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Affiliation(s)
- Helal Uddin
- Department of Global Public Health, Karolinska Institutet, Solna, 17177, Sweden. .,Department of Sociology, East West University, Dhaka, 1212, Bangladesh. .,Unit for Research in Emergency and Disaster, Faculty of Medicine and Health Sciences, University of Oviedo, Oviedo, 33006, Spain.
| | - Md Khalid Hasan
- Institute of Disaster Management and Vulnerability Studies, University of Dhaka, Dhaka 1000, Dhaka, Bangladesh.
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5
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Nagata JM, Cortez CA, Iyer P, Ganson KT, Chu J, Conroy AA. Parent-Adolescent Discrepancies in Adolescent Recreational Screen Time Reporting During the Coronavirus Disease 2019 Pandemic. Acad Pediatr 2022; 22:413-421. [PMID: 34923146 PMCID: PMC8675144 DOI: 10.1016/j.acap.2021.12.008] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Revised: 12/09/2021] [Accepted: 12/09/2021] [Indexed: 01/02/2023]
Abstract
OBJECTIVE To describe the relationship between parent and adolescent reports of adolescent recreational screen time and to determine sociodemographic predictors of recreational screen time reporting differences during the coronavirus disease 2019 pandemic. METHODS We analyzed data from the Adolescent Brain Cognitive Development Study (N = 5335, ages 10-14) a national prospective cohort study in the United States collected in May 2020. We compared parent-reported, adolescent-reported, and a parent-adolescent differences in recreational screen time hours per day across 5 screen categories. RESULTS Adolescents' total recreational screen time per day was reported as 4.46 hours by parents and 3.87 hours by adolescents. Parents reported higher levels of their child's texting, video chatting, and total recreational screen time, while adolescents reported higher multiplayer gaming and social media use. Larger discrepancies in total recreational screen time were found in older, Black, and Latino/Hispanic adolescents. Larger discrepancies in total recreational screen time were also found among unmarried/unpartnered parents. CONCLUSIONS Given discrepancies in parent-adolescent recreational screen time reporting during the pandemic, a period of high screen use, pediatricians should encourage family discussions about adolescent media use through the development of a Family Media Use Plan. The digital media industry could provide more opportunities for parental monitoring of recreational screen time within product designs.
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Affiliation(s)
- Jason M Nagata
- Department of Pediatrics, University of California, San Francisco (JM Nagata, P Iyer, and J Chu).
| | - Catherine A Cortez
- Fielding School of Public Health, University of California (CA Cortez), Los Angeles, Calif
| | - Puja Iyer
- Department of Pediatrics, University of California, San Francisco (JM Nagata, P Iyer, and J Chu)
| | - Kyle T Ganson
- Factor-Inwentash Faculty of Social Work, University of Toronto (KT Ganson), Toronto, Ontario, Canada
| | - Jonathan Chu
- Department of Pediatrics, University of California, San Francisco (JM Nagata, P Iyer, and J Chu)
| | - Amy A Conroy
- Department of Medicine, Division of Preventive Sciences, University of California, San Francisco (AA Conroy)
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6
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Effect of screen time intervention on obesity among children and adolescent: A meta-analysis of randomized controlled studies. Prev Med 2022; 157:107014. [PMID: 35248682 DOI: 10.1016/j.ypmed.2022.107014] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2021] [Revised: 01/04/2022] [Accepted: 02/28/2022] [Indexed: 11/23/2022]
Abstract
Several studies have investigated the effect of screen time interventions on obesity in children and adolescents, but the existing results were controversial. This study aimed to analyze the effect of screen time intervention on obesity in children and adolescents. PubMed, Cochrane, Web of Science, Embase databases were searched through December 2020 to identify publications meeting a priori inclusion criteria and references in the published articles were also reviewed. Finally, 14 randomized controlled trials and 1894 subjects were included in this meta-analysis. The results showed that interventions targeting screen time are effective in reducing total screen time (MD: -6.90 h/week, 95% CI: [-9.19 to -4.60], p < 0.001) and television time (MD: -6.17 h/week, 95% CI: [-10.70 to -1.65], p < 0.001) in children and adolescents. However, there was no significant difference between the intervention and control groups in body mass index and body mass index-z score. In conclusion, there is no evidence that screen time interventions alone can decrease obesity risk in children and adolescents, though they can effectively reduce screen time.
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7
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Sun L, Li K, Zhang L, Zhang Y. Distinguishing the Associations Between Evening Screen Time and Sleep Quality Among Different Age Groups: A Population-Based Cross-Sectional Study. Front Psychiatry 2022; 13:865688. [PMID: 35815054 PMCID: PMC9263078 DOI: 10.3389/fpsyt.2022.865688] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Accepted: 05/30/2022] [Indexed: 11/13/2022] Open
Abstract
OBJECTIVE The age differences in the association between screen time and sleep problems have been implied in many studies, and this study aims to distinguish the associations between evening screen time and sleep quality among different age groups. METHODS This is a population-based, cross-sectional study among community residents aged ≥18 years in China. A total of 21,376 valid questionnaires were analyzed. Sleep quality was measured by the Pittsburgh Sleep Quality Index. Averaged evening screen time (AEST), sociodemographic information, and health-related behaviors were also evaluated in this study. RESULTS In the 18-to-34-year age group, compared with people without AEST, ≤1 h/day (β = 0.34, p < 0.05) and >3 h/day (β = 1.05, p < 0.001) of AEST were significantly associated with poor sleep quality, and a reverse S-shaped relationship for this association was shown. In the 35-to-49-year and 50-to-64-year age groups, ≤1 h/day (β = 0.43 and 0.36, both p < 0.001), ≤2 h/day (β = 0.43 and 0.31, p < 0.001 and p < 0.01), ≤3 h/day (β = 0.62 and 0.61, both p < 0.001), and >3 h/day (β = 1.55 and 1.88, both p < 0.001) of AEST were positively associated with poor sleep quality. In the 65-year-and-older age group, a J-shaped relationship was found, and ≤3 h/day (β = 0.82, p < 0.001) and >3 h/day (β = 1.84, p < 0.001) of AEST were associated with poor sleep quality. CONCLUSION Associations between AEST and sleep quality among different age groups are different. In the 18-to-34-year and 65-year-and-older age groups, acceptable AEST is not related to sleep quality. In the 35-to-49-year and 50-to-64-year age groups, AEST was harmful to sleep quality.
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Affiliation(s)
- Long Sun
- Centre for Health Management and Policy Research, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China.,Key Laboratory of Health Economics and Policy Research, National Health Commission of China, Shandong University, Jinan, China
| | - Keqing Li
- Hebei Provincial Mental Health Center, Baoding, China
| | - Lili Zhang
- Hebei Provincial Mental Health Center, Baoding, China
| | - Yunshu Zhang
- Hebei Provincial Mental Health Center, Baoding, China
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8
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Nagata JM, Singh G, Sajjad OM, Ganson KT, Testa A, Jackson DB, Assari S, Murray SB, Bibbins-Domingo K, Baker FC. Social epidemiology of early adolescent problematic screen use in the United States. Pediatr Res 2022; 92:1443-1449. [PMID: 35768491 PMCID: PMC9243697 DOI: 10.1038/s41390-022-02176-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Accepted: 06/07/2022] [Indexed: 12/25/2022]
Abstract
OBJECTIVE To determine sociodemographic correlates of problematic screen use (social media, video games, mobile phones) among a racially/ethnically and socioeconomically diverse population-based sample of 10-14-year-old early adolescents. STUDY DESIGN We analyzed cross-sectional data from the Adolescent Brain Cognitive Development Study (Year 2, 2018-2020; N = 8753). Multiple linear regression analyses were used to estimate associations between sociodemographic factors (age, sex, race/ethnicity, primary language, household income, parental education) and adolescent-reported problematic video game (Video Game Addiction Questionnaire), social media (Social Media Addiction Questionnaire), and mobile phone use (Mobile Phone Involvement Questionnaire). RESULTS Boys reported higher problematic video game use while girls reported higher problematic social media and mobile phone use. Native American, black, and Latinx adolescents reported higher scores across all problematic screen measures compared to non-Latinx white adolescents. Having unmarried/unpartnered parents was associated with higher problematic social media use. Although higher household income was generally protective against problematic video game use, these associations were weaker for black than white adolescents (p for interaction <0.05). CONCLUSIONS Given the sociodemographic differences in problematic screen use, digital literacy education strategies can focus on at-risk populations, encourage targeted counseling by pediatricians, and adapt family media use plans for diverse backgrounds. IMPACT While sociodemographic differences in screen time are documented, we examined sociodemographic differences in problematic screen use in a large, diverse sample of early adolescents in the US. Boys reported higher problematic video game use while girls reported higher problematic social media and mobile phone use. Native American, black, and Latinx adolescents reported higher scores across all problematic screen measures compared to non-Latinx white adolescents. Although higher household income was generally protective against problematic video game use, these associations were weaker for black than white adolescents. Beyond time spent on screens, pediatricians, parents, and educators should be aware of sociodemographic differences in problematic screen use.
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Affiliation(s)
- Jason M. Nagata
- grid.266102.10000 0001 2297 6811Division of Adolescent and Young Adult Medicine, Department of Pediatrics, University of California, San Francisco, San Francisco, CA USA
| | - Gurbinder Singh
- grid.266102.10000 0001 2297 6811Division of Adolescent and Young Adult Medicine, Department of Pediatrics, University of California, San Francisco, San Francisco, CA USA
| | - Omar M. Sajjad
- grid.254880.30000 0001 2179 2404Geisel School of Medicine, Dartmouth College, Hanover, NH USA
| | - Kyle T. Ganson
- grid.17063.330000 0001 2157 2938Factor-Inwentash Faculty of Social Work, University of Toronto, Toronto, ON Canada
| | - Alexander Testa
- grid.267308.80000 0000 9206 2401Department of Management, Policy and Community Health, University of Texas Health Science Center at Houston, Houston, TX USA
| | - Dylan B. Jackson
- grid.21107.350000 0001 2171 9311Department of Population, Family, and Reproductive Health, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD USA
| | - Shervin Assari
- grid.254041.60000 0001 2323 2312Department of Family Medicine, College of Medicine, Charles R. Drew University of Medicine and Science, Los Angeles, CA USA ,grid.254041.60000 0001 2323 2312Department of Urban Public Health, Charles R. Drew University of Medicine and Science, Los Angeles, CA USA ,grid.254041.60000 0001 2323 2312Marginalization-related Diminished Returns (MDRs) Research Center, Charles R. Drew University of Medicine and Science, Los Angeles, CA USA
| | - Stuart B. Murray
- grid.42505.360000 0001 2156 6853Department of Psychiatry and Behavioral Sciences, University of Southern California, Los Angeles, CA USA
| | - Kirsten Bibbins-Domingo
- grid.266102.10000 0001 2297 6811Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA USA
| | - Fiona C. Baker
- grid.98913.3a0000 0004 0433 0314Center for Health Sciences, SRI International, Menlo Park, CA USA ,grid.11951.3d0000 0004 1937 1135School of Physiology, University of the Witwatersrand, Johannesburg, South Africa
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Nagata JM, Ganson KT, Iyer P, Chu J, Baker FC, Gabriel KP, Garber AK, Murray SB, Bibbins-Domingo K. Sociodemographic Correlates of Contemporary Screen Time Use among 9- and 10-Year-Old Children. J Pediatr 2022; 240:213-220.e2. [PMID: 34481807 PMCID: PMC9107378 DOI: 10.1016/j.jpeds.2021.08.077] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 08/20/2021] [Accepted: 08/26/2021] [Indexed: 01/03/2023]
Abstract
OBJECTIVE To determine sociodemographic correlates of contemporary screen time use among a diverse population-based sample of 9- and 10-year-old children. STUDY DESIGN In 2021, we analyzed cross-sectional baseline (2016-2018) data from the Adolescent Brain Cognitive Development study (n = 10 755). Multiple linear regression analyses were conducted to estimate associations between sociodemographic factors (sex, race/ethnicity, country of birth, household income, parental education) and 6 contemporary forms of screen time (television, videos [eg, YouTube], video games, social networking, texting, and video chat). RESULTS On average, children reported 3.99 hours of screen time per day across 6 modalities, with the most time spent watching/streaming television shows/movies (1.31 hours), playing video games (1.06 hours), and watching/streaming videos (1.05 hours). On average, Black children reported 1.58 more hours of screen time per day and Asian children reported 0.35 less hours of screen time per day compared with White children (mean 3.46 hours per day), and these trends persisted across most modalities. Boys reported higher overall screen time (0.75 hours more) than girls, which was primarily attributed to video games and videos. Girls reported more time texting, social networking, and video chatting than boys. Higher income was associated with lower screen time usage across all modalities except video chat. However, in high-income households, Latinx children reported 0.65 more hours of screen time per day than White children. CONCLUSIONS Given the sociodemographic differences in child screen use, guideline implementation strategies can focus on key populations, encourage targeted counseling by pediatricians, and adapt Family Media Use Plans for diverse backgrounds.
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Affiliation(s)
- Jason M. Nagata
- Division of Adolescent and Young Adult Medicine, Department of Pediatrics, University of California, San Francisco, San Francisco, California, USA
| | - Kyle T. Ganson
- Factor-Inwentash Faculty of Social Work, University of Toronto, Toronto, Ontario, Canada
| | - Puja Iyer
- Division of Adolescent and Young Adult Medicine, Department of Pediatrics, University of California, San Francisco, San Francisco, California, USA
| | - Jonathan Chu
- Division of Adolescent and Young Adult Medicine, Department of Pediatrics, University of California, San Francisco, San Francisco, California, USA
| | - Fiona C. Baker
- Center for Health Sciences, SRI International, Menlo Park, California, USA,Department of Physiology, School of Physiology, University of the Witwatersrand, Johannesburg, South Africa
| | - Kelley Pettee Gabriel
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Andrea K. Garber
- Division of Adolescent and Young Adult Medicine, Department of Pediatrics, University of California, San Francisco, San Francisco, California, USA
| | - Stuart B. Murray
- Department of Psychiatry and Behavioral Sciences, University of Southern California, Los Angeles, California, USA
| | - Kirsten Bibbins-Domingo
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California, USA
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10
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Aulbach MB, Konttinen H, Gardner B, Kujala E, Araujo-Soares V, Sniehotta FF, Lintunen T, Haukkala A, Hankonen N. A dual process model to predict adolescents' screen time and physical activity. Psychol Health 2021:1-20. [PMID: 34662259 DOI: 10.1080/08870446.2021.1988598] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
OBJECTIVE Many adolescents report a lack of physical activity (PA) and excess screen time (ST). Psychological theories aiming to understand these behaviours typically focus on predictors of only one behaviour. Yet, behaviour enactment is often a choice between options. This study sought to examine predictors of PA and ST in a single model. Variables were drawn from dual process models, which portray behaviour as the outcome of deliberative and automatic processes. DESIGN 411 Finnish vocational school students (age 17-19) completed a survey, comprising variables from the Reasoned Action Approach (RAA) and automaticity pertaining to PA and ST, and self-reported PA and ST four weeks later. MAIN OUTCOME MEASURES Self-reported time spent on PA and ST and their predictors. RESULTS PA and ST correlated negatively (r = -.17, p = .03). Structural equation modelling revealed that intentions and habit for PA predicted PA while ST was predicted by intentions and habit for ST and negatively by PA intentions. RAA-cognitions predicted intentions. CONCLUSION PA and ST and their psychological predictors seem to be weakly interlinked. Future studies should assess more behaviours and related psychological influences to get a better picture of connections between different behaviours. HighlightsPhysical activity and screen time are largely mutually exclusive classes of behaviours and might therefore be related in terms of their psychological predictors.411 adolescent vocational school students self-reported variables from the Reasoned Action Approach and behavioural automaticity related to physical activity and leisure time screen time behaviours as well as those behaviours.Structural equation modelling revealed expected within-behaviour predictions but, against expectations, no strong connections between the two behaviour classes in terms of their predictors. Only intentions to engage in physical activity negatively predicted screen time.Future research should aim to measure a wider range of mutually exclusive classes of behaviours that cover a large share of the day to uncover relations between behaviours and their respective predictors.
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Affiliation(s)
| | - Hanna Konttinen
- Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
| | | | - Emilia Kujala
- Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
| | - Vera Araujo-Soares
- Population Health Science Institute, Medical Faculty, Newcastle University, Newcastle, U.K.,Health Technology and Services Research, Technical Medical Centre, BMS, University of Twente, The Netherlands
| | - Falko F Sniehotta
- Population Health Science Institute, Medical Faculty, Newcastle University, Newcastle, U.K.,Faculty of Behavioural, Management and Social sciences, University of Twente, The Netherlands
| | - Taru Lintunen
- Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Ari Haukkala
- Faculty of Social Sciences, University of Helsinki, Helsinki, Finland.,Helsinki Collegium for Advanced Studies, University of Helsinki, Helsinki, Finland
| | - Nelli Hankonen
- Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
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11
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Nagata JM, Iyer P, Chu J, Baker FC, Pettee Gabriel K, Garber AK, Murray SB, Bibbins-Domingo K, Ganson KT. 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; 54:887-892. [PMID: 33646623 PMCID: PMC9714253 DOI: 10.1002/eat.23489] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Revised: 01/29/2021] [Accepted: 02/08/2021] [Indexed: 12/15/2022]
Abstract
OBJECTIVE To determine the prospective associations between contemporary screen time modalities in a nationally representative cohort of 9-10-year-old children and binge-eating disorder at one-year follow-up. METHOD We analyzed prospective cohort data from the Adolescent Brain Cognitive Development (ABCD) Study (N = 11,025). Logistic regression analyses were conducted to estimate associations between baseline child-reported screen time (exposure) and parent-reported binge-eating disorder based on the Kiddie Schedule for Affective Disorders and Schizophrenia (KSADS-5, outcome) at one-year follow-up, adjusting for race/ethnicity, sex, household income, parent education, BMI percentile, site, and baseline binge-eating disorder. RESULTS Each additional hour of total screen time per day was prospectively associated with 1.11 higher odds of binge-eating disorder at 1-year follow-up (95% CI 1.05-1.18) after adjusting for covariates. In particular, each additional hour of social networking (aOR 1.62, 95% CI 1.18-2.22), texting (aOR 1.40, 95% CI 1.08-1.82), and watching/streaming television shows/movies (aOR 1.39, 95% CI 1.14-1.69) was significantly associated with binge-eating disorder. DISCUSSION Clinicians should assess screen time usage and binge eating in children and adolescents and advise parents about the potential risks associated with excessive screen time.
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Affiliation(s)
- Jason M. Nagata
- Division of Adolescent and Young Adult Medicine, Department of Pediatrics, University of California, San Francisco, San Francisco, California, USA
| | - Puja Iyer
- Division of Adolescent and Young Adult Medicine, Department of Pediatrics, University of California, San Francisco, San Francisco, California, USA
| | - Jonathan Chu
- Division of Adolescent and Young Adult Medicine, Department of Pediatrics, University of California, San Francisco, San Francisco, California, USA
| | - Fiona C. Baker
- Biosciences Division, Center for Health Sciences, SRI International, Menlo Park, California, USA,Department of Physiology, School of Physiology, University of the Witwatersrand, Johannesburg, South Africa
| | - Kelley Pettee Gabriel
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Andrea K. Garber
- Division of Adolescent and Young Adult Medicine, Department of Pediatrics, University of California, San Francisco, San Francisco, California, USA
| | - Stuart B. Murray
- Department of Psychiatry and Behavioral Sciences, University of Southern California, Los Angeles, California, USA
| | - Kirsten Bibbins-Domingo
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California, USA
| | - Kyle T. Ganson
- Factor-Inwentash Faculty of Social Work, University of Toronto, Toronto, Ontario, Canada
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Wärnberg J, Pérez-Farinós N, Benavente-Marín JC, Gómez SF, Labayen I, G. Zapico A, Gusi N, Aznar S, Alcaraz PE, González-Valeiro M, Serra-Majem L, Terrados N, Tur JA, Segú M, Lassale C, Homs C, Oses M, González-Gross M, Sánchez-Gómez J, Jiménez-Zazo F, Marín-Cascales E, Sevilla-Sánchez M, Herrera-Ramos E, Pulgar S, Bibiloni MDM, Sancho-Moron O, Schröder H, Barón-López FJ. Screen Time and Parents' Education Level Are Associated with Poor Adherence to the Mediterranean Diet in Spanish Children and Adolescents: The PASOS Study. J Clin Med 2021; 10:795. [PMID: 33669366 PMCID: PMC7920265 DOI: 10.3390/jcm10040795] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Revised: 01/31/2021] [Accepted: 02/07/2021] [Indexed: 02/07/2023] Open
Abstract
The aim of this study is to evaluate if screen time and parents' education levels are associated with adherence to a Mediterranean dietary pattern. This cross-sectional study analyzed a representative sample of 3333 children and adolescents (8 to 16 years) included in the Physical Activity, Sedentarism, lifestyles and Obesity in Spanish youth (PASOS) study in Spain (which ran from March 2019 to February 2020). Data on screen time (television, computer, video games, and mobile phone) per day, Mediterranean diet adherence, daily moderate or vigorous physical activity, and parents' education levels were gathered using questionnaires. A descriptive study of the variables according to sex and parents' education level was performed. Logistic regression models (adjusted by sex and weight status) were fitted to evaluate the independent association between screen time and Kids' level of adherence to the Mediterranean diet (KIDMED) index, as well as some of its items. A greater amount of screen time was associated with worse adherence to the Mediterranean diet; a lower consumption of fruit, vegetables, fish, legumes, and nuts; and a greater consumption of fast food, sweets, and candies. A lower parents' education level was associated with worse adherence to the Mediterranean diet. It is necessary to promote the responsible, limited use of screen time, especially in children with parents with a lower education level.
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Affiliation(s)
- Julia Wärnberg
- Epi-Phaan Research Group, School of Health Sciences, Universidad de Málaga, Instituto de Investigación Biomédica de Málaga (IBIMA), 29071 Málaga, Spain; (J.W.); (J.C.B.-M.); (F.J.B.-L.)
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28029 Madrid, Spain; (L.S.-M.); (J.A.T.); (C.L.); (M.G.-G.); (M.d.M.B.)
| | - Napoleón Pérez-Farinós
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28029 Madrid, Spain; (L.S.-M.); (J.A.T.); (C.L.); (M.G.-G.); (M.d.M.B.)
- Epi-Phaan Research Group, School of Medicine, Universidad de Málaga, Instituto de Investigación Biomédica de Málaga (IBIMA), 29071 Málaga, Spain
| | - Juan Carlos Benavente-Marín
- Epi-Phaan Research Group, School of Health Sciences, Universidad de Málaga, Instituto de Investigación Biomédica de Málaga (IBIMA), 29071 Málaga, Spain; (J.W.); (J.C.B.-M.); (F.J.B.-L.)
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28029 Madrid, Spain; (L.S.-M.); (J.A.T.); (C.L.); (M.G.-G.); (M.d.M.B.)
| | - Santiago Felipe Gómez
- Programs, Gasol Foundation, Sant Boi de Llobregat, 08830 Barcelona, Spain; (S.F.G.); (C.H.)
- GREpS, Health Education Research Group, Nursing and Physiotherapy Department, University of Lleida, 25198 Lleida, Spain
| | - Idoia Labayen
- ELIKOS Group, Institute for Innovation and Sustainable Development in Food Chain (IS-FOOD), Instituto de Investigación Sanitaria de Navarra, Public University of Navarre, 31006 Pamplona, Spain; (I.L.); (M.O.)
| | - Augusto G. Zapico
- ImFINE Research Group, Department of Health and Human Performance, Universidad Politecnica de Madrid, 28040 Madrid, Spain;
- Department of Didactics of Language, Arts and Physical Education, Universidad Complutense de Madrid, 28040 Madrid, Spain
| | - Narcis Gusi
- Physical Activity and Quality of Life Research Group (AFYCAV), Faculty of Sport Sciences, University of Extremadura, 10003 Caceres, Spain; (N.G.); (J.S.-G.)
| | - Susana Aznar
- PAFS Research Group, Faculty of Sports Sciences, University of Castilla-La Mancha-Toledo Campus, 45071 Toledo, Spain; (S.A.); (F.J.-Z.)
| | - Pedro Emilio Alcaraz
- Research Center for High Performance Sport, San Antonio Catholic University of Murcia, 30830 Murcia, Spain; (P.E.A.); (E.M.-C.)
- Faculty of Sport Sciences, San Antonio Catholic University of Murcia, 30107 Murcia, Spain
| | - Miguel González-Valeiro
- Faculty of Sports Sciences and Physical Education, Universidade da Coruña, 15179 A Coruña, Spain; (M.G.-V.); (M.S.-S.)
| | - Lluís Serra-Majem
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28029 Madrid, Spain; (L.S.-M.); (J.A.T.); (C.L.); (M.G.-G.); (M.d.M.B.)
- Research Institute of Biomedical and Health Sciences (IUIBS), University of Las Palmas de Gran Canaria, 35016 Las Palmas, Spain;
| | - Nicolás Terrados
- Regional Unit of Sports Medicine–Municipal Sports Foundation of Avilés and Health Research Institute of the Principality of Asturias (ISPA), 33401 Avilés, Spain; (N.T.); (S.P.)
| | - Josep A. Tur
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28029 Madrid, Spain; (L.S.-M.); (J.A.T.); (C.L.); (M.G.-G.); (M.d.M.B.)
- Research Group of Community Nutrition and Oxidative Stress, University of the Balearic Islands and IDISBA, 07122 Palma de Mallorca, Spain
| | - Marta Segú
- Probitas Foundation, 08022 Barcelona, Spain; (M.S.); (O.S.-M.)
| | - Camille Lassale
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28029 Madrid, Spain; (L.S.-M.); (J.A.T.); (C.L.); (M.G.-G.); (M.d.M.B.)
- Cardiovascular Risk and Nutrition Research Group, Hospital del Mar Institute for Medical Research (IMIM), 08003 Barcelona, Spain;
| | - Clara Homs
- Programs, Gasol Foundation, Sant Boi de Llobregat, 08830 Barcelona, Spain; (S.F.G.); (C.H.)
- Global Research on Wellbeing (GRoW), Blanquerna Ramon Llull University Faculty of Health Sciences, 08025 Barcelona, Spain
| | - Maddi Oses
- ELIKOS Group, Institute for Innovation and Sustainable Development in Food Chain (IS-FOOD), Instituto de Investigación Sanitaria de Navarra, Public University of Navarre, 31006 Pamplona, Spain; (I.L.); (M.O.)
| | - Marcela González-Gross
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28029 Madrid, Spain; (L.S.-M.); (J.A.T.); (C.L.); (M.G.-G.); (M.d.M.B.)
- ImFINE Research Group, Department of Health and Human Performance, Universidad Politecnica de Madrid, 28040 Madrid, Spain;
| | - Jesús Sánchez-Gómez
- Physical Activity and Quality of Life Research Group (AFYCAV), Faculty of Sport Sciences, University of Extremadura, 10003 Caceres, Spain; (N.G.); (J.S.-G.)
| | - Fabio Jiménez-Zazo
- PAFS Research Group, Faculty of Sports Sciences, University of Castilla-La Mancha-Toledo Campus, 45071 Toledo, Spain; (S.A.); (F.J.-Z.)
| | - Elena Marín-Cascales
- Research Center for High Performance Sport, San Antonio Catholic University of Murcia, 30830 Murcia, Spain; (P.E.A.); (E.M.-C.)
| | - Marta Sevilla-Sánchez
- Faculty of Sports Sciences and Physical Education, Universidade da Coruña, 15179 A Coruña, Spain; (M.G.-V.); (M.S.-S.)
| | - Estefanía Herrera-Ramos
- Research Institute of Biomedical and Health Sciences (IUIBS), University of Las Palmas de Gran Canaria, 35016 Las Palmas, Spain;
| | - Susana Pulgar
- Regional Unit of Sports Medicine–Municipal Sports Foundation of Avilés and Health Research Institute of the Principality of Asturias (ISPA), 33401 Avilés, Spain; (N.T.); (S.P.)
| | - María del Mar Bibiloni
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28029 Madrid, Spain; (L.S.-M.); (J.A.T.); (C.L.); (M.G.-G.); (M.d.M.B.)
- Research Group of Community Nutrition and Oxidative Stress, University of the Balearic Islands and IDISBA, 07122 Palma de Mallorca, Spain
| | | | - Helmut Schröder
- Cardiovascular Risk and Nutrition Research Group, Hospital del Mar Institute for Medical Research (IMIM), 08003 Barcelona, Spain;
- Centro de Investigación Biomédica en Red Fisiopatología de Epidemiología y Salud Pública (CIBERESP), Institute of Health Carlos III, 28029 Madrid, Spain
| | - F. Javier Barón-López
- Epi-Phaan Research Group, School of Health Sciences, Universidad de Málaga, Instituto de Investigación Biomédica de Málaga (IBIMA), 29071 Málaga, Spain; (J.W.); (J.C.B.-M.); (F.J.B.-L.)
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28029 Madrid, Spain; (L.S.-M.); (J.A.T.); (C.L.); (M.G.-G.); (M.d.M.B.)
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