家庭媒体使用的新特征:潜在特征分析。

IF 2.1 Q2 PEDIATRICS
Nicole Hamp, Jenny Radesky, Heidi M Weeks, Alison L Miller, Niko Kaciroti
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引用次数: 0

摘要

背景:在过去的30年里,数字和屏幕媒体已经从广播、固定的平台发展到一个互动、无所不在、移动媒体的复杂环境。因此,以“屏幕时间”等单向度概念为中心的临床指导必须现代化,以帮助家庭驾驭随时可用的娱乐和信息的复杂数字生态系统。目的:本研究旨在识别和检查有幼儿的家庭中媒体使用的不同潜在特征。我们假设潜在特征分析(LPA)将识别出不同的媒体使用特征,其特征是更重的、反应性的、个人的和允许的媒体使用,以及更有意的、受管制的或共享的媒体使用。方法:对398名学龄前儿童的资料进行分析。说英语的父母是通过社区环境招募的。参与者完成了关于家庭媒体使用的几个方面的调查,如儿童设备使用或活动,父母的担忧和态度,限制设置和调解,父母媒体使用和技术干扰,在LPA中进行了检查。使用贝叶斯信息准则确定潜在媒体概况的数量。父母还完成了育儿压力、抑郁症状、育儿方式、孩子行为、孩子睡眠和家庭混乱的有效量表。使用多变量逻辑回归来检验父母、子女和家庭的群体成员预测因子。结果:LPA结果显示,家长和孩子在镇静或帮助孩子入睡的媒介使用时间上存在明显差异。两组之间具有统计学意义的差异包括:第一组(n=236,我们称之为社会情绪驱动者)的父母更喜欢通过短信或电子邮件进行互动,而不是面对面(P= 0.01),并且更有可能使用媒体来安抚孩子(P= 0.03);相比之下,第2组(n=162,有意媒体)的家庭更多地使用任务导向媒体,如音频和非游戏应用程序(P= 0.01),更关注媒体对儿童语言发展的影响(P= 0.04),并使用更多的媒体限制(P= 0.01)。在回归模型中,被调查者父母的性别、兄弟姐妹的数量和较晚的儿童睡眠中点独立地预测了第一组的成员资格。结论:研究结果表明,不同的家庭媒体使用模式可以分为两个主要的媒体用户群体:那些使用媒体来缓冲社交情况或调节情绪的人,以及那些围绕功能目的和媒体暴露问题规划移动设备使用的人。档案与家庭规模和儿童睡眠有关。需要更多的研究来检验媒体的社会和情感使用对儿童结局的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Novel Profiles of Family Media Use: Latent Profile Analysis.

Background: Over the past 3 decades, digital and screen media have evolved from broadcast, stationary platforms to a complex environment of interactive, omnipresent, mobile media. Thus, clinical guidance centered around unidimensional concepts such as "screen time" must be modernized to help families navigate the intricate digital ecosystems of readily available entertainment and information.

Objective: This study aimed to identify and examine distinct latent profiles of media use in families with young children. We hypothesized that latent profile analysis (LPA) would identify different media use profiles characterized by more heavy, reactive, individual, and permissive media use and more intentional, regulated, or shared uses of media.

Methods: We analyzed data from 398 preschool-aged children. English-speaking parents were recruited through community settings. Participants completed surveys regarding several aspects of family media use, such as child device use or activities, parent concerns and attitudes, limit setting and mediation, parent media use, and technology interference, examined in an LPA. The number of latent media profiles was determined using Bayesian Information Criteria. Parents also completed validated scales of parenting stress, depression symptoms, parenting style, child behavior, child sleep, and household disorganization. Multivariable logistic regression was used to examine parent, child, and household predictors of group membership.

Results: The LPA yielded 2 distinct groups that differed in the duration of media used by parents and children, to calm children or help them fall asleep. Statistically significant differences between groups included: families in group 1 (n=236, which we termed social-emotional drivers) had parents who preferred interactions via text or email to in-person (P=.01) and were more likely to use media to calm their children (P=.03); in contrast, families in group 2 (n=162, intentional media) used more task-oriented media, like audio and nongame apps (P=.01), had more concerns about effects of media on child language development (P=.04), and used more media restrictions (P=.01). In regression models, female sex of the parent respondent, greater number of siblings, and later child sleep midpoint independently predicted group 1 membership.

Conclusions: Findings suggest divergent family media use patterns that can be categorized into 2 main media user groups: those using media to buffer social situations or regulate emotions and those planning mobile device use around functional purposes and concerns around media exposure. Profiles were associated with household size and child sleep. More research is needed to examine the impact of social and emotional uses of media on child outcomes.

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来源期刊
JMIR Pediatrics and Parenting
JMIR Pediatrics and Parenting Medicine-Pediatrics, Perinatology and Child Health
CiteScore
5.00
自引率
5.40%
发文量
62
审稿时长
12 weeks
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