Fatigue as a central bridge: temporal dynamics between problematic smartphone use and depressive symptoms in Chinese adolescents

Abstract

Background: The prevalence of problematic smartphone use (PSU) has been increasing among adolescents in recent years, often co-occurring with depressive symptoms, which poses additional challenges to adolescent mental health. Despite growing concern, the mechanisms underlying the co-occurrence of PSU and depression remain poorly understood. To address this gap, the current study employed cross-lagged panel network analysis to investigate the temporal relationships between specific symptoms of PSU and depressive symptoms over time.

Methods: Data were collected at three time points (T1, T2, and T3), with six-month intervals between each wave. Participants self-reported their levels of depressive symptoms and PSU. A total of 558 participants (52.5% male; mean age at T1 = 13.83, SD = 0.78) were included in the final analysis. Two cross-lagged panel networks were constructed to examine the bidirectional relationships between depressive symptoms and PSU from T1 to T2 and from T2 to T3.

Results: In the T1-T2 network, Withdrawal from PSU and Fatigue from depressive symptoms not only emerged as the most influential symptoms but also acted as bridge symptoms linking the co-occurrence of these two mental health issues. In the T2-T3 network, the structure of network became denser, with the most influential symptoms primarily stemming from depressive symptoms, such as Sleep Disturbance and Feeling of Failure. Negative Life Consequences from PSU and Fatigue from depressive symptoms served as key bridge symptoms.

Conclusions: The findings provide valuable insights into the temporal dynamics underlying the co-occurrence of PSU and depressive symptoms during adolescence, with Fatigue appearing to play a significant role in linking these two mental health issues over time. Future studies should account for individual differences in how symptoms evolve over time and explore how these symptoms develop and persist at the individual level.

Keywords: Adolescents; Cross-lagged panel network analysis; Depressive symptoms; Problematic smartphone use.

Fig. 1

Stability of centrality indices by case dropping subset bootstrap. The x-axis shows the percentage of cases from the original sample used at each step, while the y-axis displays the average correlations between centrality indices from the original network and those from networks re-estimated after progressively dropping cases. Each line represents correlations for BEI, In-EI and Out-EI, with shaded areas indicating the 95% confidence intervals

Fig. 2

The cross-lagged panel networks for T1-T2 and T2-T3 (Thresholds = 0.05). Arrows represent the directional relationships. Blue edges indicate positive relationships (i.e., odds ratios greater than 1), and red edges indicate negative relationships (i.e., odds ratios less than 1). Edge thickness represents the weight of the odds ratios such that thicker edges represent stronger relations. To simplify visual interpretation, autoregressive edges, weaker edges (i.e., odds ratios within 1 ± 0.05), and covariates were excluded from the plot

Fig. 3

Centrality estimates and BEI in the T1-T2 CLPN. Larger values reflect greater centrality

Fig. 4

Centrality estimates and BEI in the T2-T3 CLPN. Larger values reflect greater centrality