Evidence indicates that smartphone addiction is associated with a series of psychological problems. However, there is still a lack of sufficient understanding regarding smartphone addiction that occurs in both negative and positive mental health conditions in youths. We aimed to map the network linking smartphone addiction (SMA) with negative (depression, anxiety, stress, loneliness) and positive (life satisfaction, social support, resilience, and self-efficacy) mental health factors in youths. In a cross-sectional sample of 701 youths (aged 18.27 ± 1.57 years, 16–20 years old, 47.6% male, Chinese), participants completed validated self-report scales. A regularized Gaussian graphical model was estimated to identify conditional associations and central nodes. Bootstrapped exploratory graph analysis was used to detect communities, and a PC-algorithm-based directed acyclic graph (DAG) was used to explore potential directional associations. Compared with non-SMA individuals, youths with SMA reported higher depression, anxiety, stress, and loneliness, and lower life satisfaction, social support, resilience, and self-efficacy (p < 0.05). The strongest edges were self-efficacy–resilience (weight = 0.47) and depression–anxiety (weight = 0.42), SMA was most strongly linked to stress (0.23). Anxiety (Expected Influence = 0.80) and depression (EI = 0.77) showed the highest centrality with good stability. The DAG suggested potential directional pathways from SMA to stress and depression, stress was statistically associated with subsequent nodes of depression and loneliness. SMA is embedded within a tightly connected cluster of negative mental health factors and diminished positive resources. Stress and depression appear to be key pathways from SMA to broader psychopathology, highlighting intervention targets (stress regulation and depression management) alongside strengthening mental health promotion in SMA youths in the future.
Zhang et al. (2026) studied this question.