Trajectory of problematic smartphone use among adolescents aged 10–18 years: The roles of childhood family environment and concurrent parent–child relationships

Abstract

Background and aims Adolescence is a period of high incidence of problematic smartphone use. Understanding the developmental trajectory of problematic smartphone use in adolescence and its influencing factors could guide the choice of timing for prevention and intervention. This study fitted the growth trajectory of problematic smartphone use among adolescents and examined its associations with the childhood family environment and concurrent parent–child relationships. Methods Using a cohort sequential design, we investigated 2,548 Chinese adolescents and their parents three times in three years. Multiple group multiple cohort growth models were used to fit the growth trajectory. Results The quadratic growth trajectory of problematic smartphone use in adolescents aged 10–18 years showed a clear increasing trend, with a possible decreasing trend in late adolescence or early adulthood. Early life socioeconomic status, childhood family unpredictability, and the concurrent parent–child relationship had unique impacts on the development of problematic smartphone use during adolescence. Discussion and conclusions Early adolescence is a favorable time for problematic smartphone use prevention and intervention. A supportive family environment should be maintained throughout the different developmental stages of children and adolescents.

The more academic burnout students got, the more problematic mobile phone use they suffered? A meta-analysis of mainland Chinese adolescents and young adults

“…Supposing that students have PMPU, their self-esteem, psychological capital and family intimacy will be reduced, and alexithymia, family conflict and life pressure etc. will be increased ( Kim and Lee, 2012a ; Mei et al, 2018 ; You et al, 2019 ; Chen H. et al, 2022 ; Lai et al, 2022 ). Students with higher psychological symptoms, interpersonal barriers and life pressure are more likely to produce AB ( Kim and Lee, 2012b ; Lin and Huang, 2014 ; Romano et al, 2019 ; Luo et al, 2020 ; Wang et al, 2021a ).…”

Protective and risk factors associated with problem behaviors among disadvantaged children and adolescents in rural China during the COVID-19 pandemic

“…Finally, the findings also observed age differences; specifically, older (relative to younger) children had fewer increases in self-injury behaviors; they also demonstrated greater increases in excessive screen time amid the pandemic. Prior findings observed heterogenous changing trajectories of self-injury behaviors (Hasking et al, 2021; Wang et al, 2017), smartphone addiction (Lai et al, 2022; Sahu et al, 2019), and screen time (Eales et al, 2021; Guimarães et al, 2021; Trott et al, 2022). Our findings add novelty to the extant literature, which primarily focused on problem behaviors among younger participants during the pandemic in comparison to their older (e.g., middle-aged, elderly) counterparts (Fernández et al, 2020; Lahav, 2020) by elucidating indicator-specific changes under pandemic conditions across children and adolescents of different ages.…”

“…In particular, adolescents are more likely than young children to engage in non-suicidal self-injury behaviors (Hasking et al, 2021), but heterogeneity in changing patterns of self-injury behaviors was also observed in adolescence (Wang et al, 2017). Older children report greater smartphone addiction (Sahu et al, 2019) than younger children, and there is an increasing trend of smartphone addiction during adolescence (Lai et al, 2022). For screen time, distinct changing trajectories from childhood to adolescence were observed and most children (approximately 89%) reported stable levels of screen time over time (Guimarães et al, 2021).…”

“…Child age. We included participants' ages (T1) as a predictor in analysis, given that children and adolescents exhibited various changing patterns of self-injury behaviors (Hasking et al, 2021;Wang et al, 2017), smartphone addiction (Lai et al, 2022;Sahu et al, 2019), and screen time (Eales et al, 2021;Guimarães et al, 2021), and that their behavioral responses to the pandemic may vary by their ages (Trott et al, 2022). The sample consists of a wide range of ages, including ages 9 (4.1%), 10 (21.9%), 11 (22.8%), 12 (12.4%), 13 (16.7%), 14 (14.9%), 15 (5.7%), and 16 (.5%).…”

“…We also hypothesized that prior adversities and pandemic-related stress experiences would be associated with more problem behaviors (Hypothesis 2), whereas resources would be linked to fewer problem behaviors during the pandemic (Hypothesis 3). Finally, given the mixed findings with regards to changes in self-injury behaviors, smartphone addiction, and screen time across time (Eales et al, 2021; Guimarães et al, 2021; Lai et al, 2022; Sahu et al, 2019; Trott et al, 2022; Wang et al, 2017), analyses examining group differences by child age were largely exploratory.…”