A study published in the Journal of Interpersonal Violence found that adolescents who faced cybervictimization had increased risk of sleep problems, anxiety, and depression than adolescents who were not victimized.
The 3-wave, 1-year longitudinal study used emotional distress as a mediator in the process of demonstrating cybervictimization as a risk factor for sleep problems. Autoregressive-cross-lagged models were used to test the longitudinal interactions between cybervictimization, depression, anxiety, and sleep problems. Multivariate latent growth approach was used to determine whether each factor was influenced by the other rather than changes over time.
There were 3 waves of data (T1, T2, and T3) that were collected 6 months apart in November 2018, May 2016, and November 2019. All participants were Chinese adolescents. The baseline assessment at T1 was 1987 adolescents in 7th grade (56.1% male; mean age 12.32 [SD, 0.53]); T2 was 1818 adolescents with 8.51% attrition (56.0% male; mean age 12.82 [0.53] years); T3 had 1820 adolescents with 8.40% attrition (56.0% male; mean age 13.33 [0.53] years). The final sample was 1987 students who had available data in at least 1 of the 3 waves of the assessment.
Depressive symptoms were assessed using a 20-item version of the Center for Epidemiologic Studies Depression Scale for Children, anxiety symptoms were assed with a 7-item anxiety subscale from the Depression Anxiety Stress Scales, and sleep problems were assed using the 18-item Pittsburgh Sleep Quality Index.
A cross-lagged model between cybervictimization and sleep problems fit the data (χ2/df, 1.20; CFI, 1.00; TLI, 1.00; RMSEA, 0.01) and autoregressive paths were significant. Cybervictimization at T1/T2 predicted sleep problems at T2/T3 with gender, age, and peer victimization at baseline as covariates.
Anxiety was demonstrated as having a relationship between cybervictimization and adolescent sleep problems (χ2/df, 1.91; CFI, 1.00; TLI, 0.99; RMSEA, 0.02; SRMR, 0.01) and cybervictimization at T1 predicted anxiety symptoms at T2 which predicted sleep problems at T3.
Depression also had a relationship between cybervictimization and adolescent sleep problems (χ2/df, 3.22; CFI 1.00; TLI, 0.98; RMSEA, 0.03; SRMR, 0.01) where depressive symptoms at T3 had a positive indirect effect in the associaton between cybervictimization at T1 and sleep problems at T3 (indirect effect, 0.005; 95% CI, 0.001, 0.012).
A linear regression model was used, which demonstrated a linear decrease in cybervictimization and linear increase in anxiety symptoms, depressive symptoms, and sleep problems. The direct associations between developmental trajectories in cybervictimization and sleep problems were positively associated but did not predict changes in sleep problems over time whereas there was an association between increase in cybervictimization and increase in sleep problems.
Cybervictimization was also linked with the intercept of anxiety symptoms, which was associated with the intercept of sleep problems. The slope of cybervictimization was associated with the slope of anxiety symptoms which was also associated with the slope of sleep problems.
The developmental trajectory of anxiety had significant indirect effects on the association between developmental trajectories of cybervictimization and sleep problems.
Elevated levels of cybervictimization were associated with elevated levels of depressive symptoms, which predicted elevated levels of sleep problems. Developmental trajectory of depressive symptoms had positive indirect effects in the association between the developmental trajectory of cybervictimization and sleep problems.
There were some limitations in this study. Self-reports were used to measure all study variables which may have a bias toward socially desirable responses. The community sample was not at risk for psychopathological levels of anxiety, depression, or sleep problems which may account for the relationship between them. The study sample may also not generalize to other countries and populations. The current study also did not consider genetic influence of these factors.
The researchers concluded that the longitudinal risk of cybervictimization on unique variance in sleep problems over time was highlighted in this study. The study also demonstrated the mediating effects of anxiety and depression on developmental trajectories.
“The findings have implications for the development of future prevention and intervention strategies to reduce maladaptive outcomes associated with cybervictimization during adolescence,” the authors wrote.
Chen Y, Zhu J. Longitudinal associations between cybervictimization and adolescent sleep problems: the role of anxiety and depressive symptoms. J Interpers Violence. 2022;0(0): 1-22. doi:10.1177/08862605221102485