Latent classes of smartphone dependency trajectories and predictors of classes among middle school students in South Korea.

Purpose: 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.

Design And Methods: 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.

Results: 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.

Conclusion: The results indicate that the smartphone dependency trajectory of all adolescents is not the same, and there are latent classes with different trajectory patterns.

Practical Implications: 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.