Jacob T. Borodovsky Ph.D. , Lindsay M. Squeglia Ph.D. , Louise Mewton Ph.D. , Lisa A. Marsch Ph.D.
{"title":"进入青春期初期技术亚型的纵向使用模式:青少年大脑认知发展研究的结果。","authors":"Jacob T. Borodovsky Ph.D. , Lindsay M. Squeglia Ph.D. , Louise Mewton Ph.D. , Lisa A. Marsch Ph.D.","doi":"10.1016/j.jadohealth.2024.06.020","DOIUrl":null,"url":null,"abstract":"<div><h3>Purpose</h3><div>Adolescents encounter a complex digital environment, yet existing data on youth technology use rarely differentiates technology subtypes. This study maps the evolution and intricacies of youth engagement with technology subtypes.</div></div><div><h3>Methods</h3><div>N = 11,868 participants in the Adolescent Brain Cognitive Development study followed from ages ∼9/10 to ∼13/14. We examined youths' self-reported hours per day (hr/day) of technology subtypes: TV/Movies, video games, YouTube, social media, video chat, and texting. We used descriptive statistics and multilevel logistic regression to assess cross-sectional and longitudinal use patterns of technology subtypes, agreement between child and parent reports on the child's technology use, and associations between each technology subtype and sociodemographics (child's biological sex, parent education, income, and marital status).</div></div><div><h3>Results</h3><div>At age 9/10, ∼75% of youth reported minimal (<30 min/day) social technology use (social media, video chat, texting) and up to ∼1.5 hr/day of TV, video games, and YouTube. By age 13/14, TV trajectories were converging to >2 hr/day, but social technology trajectories “fanned out” into a wide range of usage rates. Child and parent reports were weakly correlated (r<sub>s</sub> range: 0.13–0.29). Using child-reported hours of technology use, increases in the subject-specific odds of using a technology >2 hr/day ranged from 25% (YouTube; 95% CI: 1.16–1.35) to 234% (social media; 95% CI: 3.14–3.55). Compared with males, females had ∼100–200% greater odds of >2 hr/day of social technologies, but ∼40–80% reduced odds of >2 hr/day of video games and YouTube. Higher parent education and income predicted significantly lower odds of >2 hr/day of use – regardless of technology subtype.</div></div><div><h3>Discussion</h3><div>Distributions of youths' self-reported technology engagement are highly contingent on technology subtype, age, and biological sex. Future research on youth development and technology may benefit from considering youths' varied digital experiences.</div></div>","PeriodicalId":56278,"journal":{"name":"Journal of Adolescent Health","volume":"75 5","pages":"Pages 809-818"},"PeriodicalIF":5.5000,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Longitudinal Use Patterns of Technology Subtypes During the Transition Into Early Adolescence: Results From the Adolescent Brain Cognitive Development Study\",\"authors\":\"Jacob T. Borodovsky Ph.D. , Lindsay M. Squeglia Ph.D. , Louise Mewton Ph.D. , Lisa A. Marsch Ph.D.\",\"doi\":\"10.1016/j.jadohealth.2024.06.020\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Purpose</h3><div>Adolescents encounter a complex digital environment, yet existing data on youth technology use rarely differentiates technology subtypes. This study maps the evolution and intricacies of youth engagement with technology subtypes.</div></div><div><h3>Methods</h3><div>N = 11,868 participants in the Adolescent Brain Cognitive Development study followed from ages ∼9/10 to ∼13/14. We examined youths' self-reported hours per day (hr/day) of technology subtypes: TV/Movies, video games, YouTube, social media, video chat, and texting. We used descriptive statistics and multilevel logistic regression to assess cross-sectional and longitudinal use patterns of technology subtypes, agreement between child and parent reports on the child's technology use, and associations between each technology subtype and sociodemographics (child's biological sex, parent education, income, and marital status).</div></div><div><h3>Results</h3><div>At age 9/10, ∼75% of youth reported minimal (<30 min/day) social technology use (social media, video chat, texting) and up to ∼1.5 hr/day of TV, video games, and YouTube. By age 13/14, TV trajectories were converging to >2 hr/day, but social technology trajectories “fanned out” into a wide range of usage rates. Child and parent reports were weakly correlated (r<sub>s</sub> range: 0.13–0.29). Using child-reported hours of technology use, increases in the subject-specific odds of using a technology >2 hr/day ranged from 25% (YouTube; 95% CI: 1.16–1.35) to 234% (social media; 95% CI: 3.14–3.55). Compared with males, females had ∼100–200% greater odds of >2 hr/day of social technologies, but ∼40–80% reduced odds of >2 hr/day of video games and YouTube. Higher parent education and income predicted significantly lower odds of >2 hr/day of use – regardless of technology subtype.</div></div><div><h3>Discussion</h3><div>Distributions of youths' self-reported technology engagement are highly contingent on technology subtype, age, and biological sex. Future research on youth development and technology may benefit from considering youths' varied digital experiences.</div></div>\",\"PeriodicalId\":56278,\"journal\":{\"name\":\"Journal of Adolescent Health\",\"volume\":\"75 5\",\"pages\":\"Pages 809-818\"},\"PeriodicalIF\":5.5000,\"publicationDate\":\"2024-08-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Adolescent Health\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1054139X24003045\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PEDIATRICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Adolescent Health","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1054139X24003045","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PEDIATRICS","Score":null,"Total":0}
Longitudinal Use Patterns of Technology Subtypes During the Transition Into Early Adolescence: Results From the Adolescent Brain Cognitive Development Study
Purpose
Adolescents encounter a complex digital environment, yet existing data on youth technology use rarely differentiates technology subtypes. This study maps the evolution and intricacies of youth engagement with technology subtypes.
Methods
N = 11,868 participants in the Adolescent Brain Cognitive Development study followed from ages ∼9/10 to ∼13/14. We examined youths' self-reported hours per day (hr/day) of technology subtypes: TV/Movies, video games, YouTube, social media, video chat, and texting. We used descriptive statistics and multilevel logistic regression to assess cross-sectional and longitudinal use patterns of technology subtypes, agreement between child and parent reports on the child's technology use, and associations between each technology subtype and sociodemographics (child's biological sex, parent education, income, and marital status).
Results
At age 9/10, ∼75% of youth reported minimal (<30 min/day) social technology use (social media, video chat, texting) and up to ∼1.5 hr/day of TV, video games, and YouTube. By age 13/14, TV trajectories were converging to >2 hr/day, but social technology trajectories “fanned out” into a wide range of usage rates. Child and parent reports were weakly correlated (rs range: 0.13–0.29). Using child-reported hours of technology use, increases in the subject-specific odds of using a technology >2 hr/day ranged from 25% (YouTube; 95% CI: 1.16–1.35) to 234% (social media; 95% CI: 3.14–3.55). Compared with males, females had ∼100–200% greater odds of >2 hr/day of social technologies, but ∼40–80% reduced odds of >2 hr/day of video games and YouTube. Higher parent education and income predicted significantly lower odds of >2 hr/day of use – regardless of technology subtype.
Discussion
Distributions of youths' self-reported technology engagement are highly contingent on technology subtype, age, and biological sex. Future research on youth development and technology may benefit from considering youths' varied digital experiences.
期刊介绍:
The Journal of Adolescent Health is a scientific publication dedicated to enhancing the health and well-being of adolescents and young adults. Our Journal covers a broad range of research topics, spanning from the basic biological and behavioral sciences to public health and policy. We welcome a variety of contributions, including original research papers, concise reports, literature reviews, clinical case reports, opinion pieces, and letters to the editor. We encourage professionals from diverse disciplines such as Anthropology, Education, Ethics, Global Health, Health Services Research, Law, Medicine, Mental and Behavioral Health, Nursing, Nutrition, Psychology, Public Health and Policy, Social Work, Sociology, and Youth Development to share their expertise and contribute to our mission of promoting adolescent health. Moreover, we value the voices of young individuals, family and community members, and healthcare professionals, and encourage them to submit poetry, personal narratives, images, and other creative works that provide unique insights into the experiences of adolescents and young adults. By combining scientific peer-reviewed research with creative expressions, our Journal aims to create a comprehensive understanding of the challenges and opportunities in adolescent and young adult health.