Center for Technology and Behavioral Health, Dartmouth Geisel School of Medicine, Lebanon, New Hampshire.
Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, South Carolina.
J Adolesc Health. 2024 Nov;75(5):809-818. doi: 10.1016/j.jadohealth.2024.06.020. Epub 2024 Aug 14.
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.
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).
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 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.
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.
青少年身处复杂的数字环境中，但现有关于青少年技术使用的数据很少区分技术类型。本研究旨在描绘青少年与各种技术类型互动的演变和复杂性。
我们对青少年大脑认知发展研究中的 11868 名参与者进行了研究，这些参与者的年龄从 9/10 岁到 13/14 岁不等。我们检查了青少年每天报告的技术类型（电视/电影、视频游戏、YouTube、社交媒体、视频聊天和短信）的时间（小时/天，hr/day）。我们使用描述性统计和多层次逻辑回归来评估技术类型的横断面和纵向使用模式、儿童和父母报告之间在儿童技术使用方面的一致性，以及每种技术类型与社会人口统计学因素（儿童的生物学性别、父母教育程度、收入和婚姻状况）之间的关联。
在 9/10 岁时，约 75%的青少年报告称他们很少使用（<30 分钟/天）社交媒体（社交媒体、视频聊天、短信），每天使用电视、视频游戏和 YouTube 的时间不到 1.5 小时。到 13/14 岁时，电视的轨迹趋于集中在 2 小时/天以上，但社交媒体的轨迹“扩散”到了各种使用率。儿童和父母的报告相关性较弱（r 范围：0.13-0.29）。使用儿童报告的技术使用时间，特定于主题的使用>2 小时/天的几率从 25%（YouTube；95%置信区间：1.16-1.35）到 234%（社交媒体；95%置信区间：3.14-3.55）不等。与男性相比，女性使用>2 小时/天的社交媒体的几率增加了 100-200%，但使用>2 小时/天的视频游戏和 YouTube 的几率降低了 40-80%。较高的父母教育程度和收入显著降低了使用>2 小时/天的几率——无论技术类型如何。
青少年自我报告的技术参与分布高度依赖于技术类型、年龄和性别。未来关于青少年发展和技术的研究可能受益于考虑青少年多样化的数字体验。
