College of Nursing, Jeju National University, Jeju, Republic of Korea; Health and Nursing Research Institute, Jeju National University, Jeju, Republic of Korea.
Graduate School, College of Nursing, Seoul National University, Seoul 03080, Republic of Korea.
J Pediatr Nurs. 2023 Nov-Dec;73:44-52. doi: 10.1016/j.pedn.2023.08.013. Epub 2023 Aug 26.
With widespread use of smartphones, side effects of smartphone dependency among adolescents are emerging as a social problem. Screening high-risk groups is important for appropriate interventions to prevent smartphone dependency in early adolescence. This study thus aimed to identify latent classes of smartphone dependency trajectories and predictors of classes among South Korea's middle school students.
We used data from 2164 middle school students from the Korean Children and Youth Panel Survey (2018-2020). Latent growth curve modeling (LGCM) was performed to confirm the longitudinal trajectory, and latent class growth modeling (LCGM) was performed to identify latent classes of middle school students' smartphone dependency. Then, multinomial logistic regression analysis was conducted to explore predictors of the classes.
The LGCM showed that the trajectory of all middle school students' smartphone dependency increased (intercept 30.65, slope = 1.09). However, the LCGM identified three latent classes: (1) low-stable (intercept 23.01, nonsignificant slope), (2) medium-increasing (intercept 30.37, significant increasing slope), and (3) high-increasing (intercept 37.79, significant increasing slope). Predictors of each latent class included gender, aggressive behavior, self-esteem, parental smartphone dependency, parenting attitude, and negative peer relationships.
The results indicate that the smartphone dependency trajectory of all adolescents is not the same, and there are latent classes with different trajectory patterns.
These findings may contribute to the development of nursing interventions for the smartphone dependency of adolescents. Such interventions should encourage positive factors and eliminate negative factors and, especially, involve parents.
随着智能手机的广泛使用,青少年对智能手机的依赖所产生的副作用正在成为一个社会问题。筛查高危人群对于在青少年早期预防智能手机依赖的适当干预措施很重要。因此,本研究旨在确定韩国中学生智能手机依赖轨迹的潜在类别以及各轨迹类别的预测因素。
我们使用了韩国儿童与青年纵向调查(2018-2020 年)中 2164 名中学生的数据。采用潜在增长曲线模型(LGCM)来确认纵向轨迹,采用潜在类别增长模型(LCGM)来确定中学生智能手机依赖的潜在类别。然后,进行多项逻辑回归分析以探索类别的预测因素。
LGCM 显示,所有中学生的智能手机依赖轨迹均呈上升趋势(截距 30.65,斜率=1.09)。然而,LCGM 确定了三个潜在类别:(1)低稳定(截距 23.01,斜率无显著意义),(2)中升高(截距 30.37,显著升高斜率)和(3)高升高(截距 37.79,显著升高斜率)。每个潜在类别的预测因素包括性别、攻击行为、自尊、父母对智能手机的依赖、养育态度和消极同伴关系。
研究结果表明,所有青少年的智能手机依赖轨迹并不相同,存在不同轨迹模式的潜在类别。
这些发现可能有助于为青少年的智能手机依赖制定护理干预措施。这些干预措施应鼓励积极因素,消除消极因素,特别是要让父母参与其中。