ArticleEuropean archives of psychiatry and clinical neuroscience2026
The interplay between mental health, ecological factors, and problematic smartphone use: a network analysis in adolescents with major depressive disorder.
Article in European archives of psychiatry and clinical neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Adolescence is a critical period for the onset of major depressive disorder (MDD), during which emotional symptoms frequently co-occur with environmental adversity and maladaptive behavioral coping. In China, these processes may be further shaped by left-behind experience (LBE) - a prevalent structural vulnerability in which children grow up separated from migrating parents. To clarify these relationships, we applied network analysis in a clinical sample of 2341 adolescents (Mage = 14.99 years,77.92% female) with MDD. Participants were recruited from 14 psychiatric outpatient clinics across China. The networks examined associations among mental health symptoms (depression, anxiety, stress, sleep problems, self-esteem, loneliness), ecological factors (childhood trauma, peer victimization, social support), and problematic smartphone use (PSU). We further examined whether network topology differed by LBE (19.99% of the sample). In the full sample network, depression and loneliness demonstrated the highest strength centrality, while sleep exhibited the lowest. Loneliness and PSU acted as bridges between mental health symptoms and ecological factors. Network comparison tests revealed no significant between-group global structural differences. Although childhood trauma and PSU appeared more centrally positioned in the left-behind group and social support showed slightly higher centrality in the non-left-behind network, these subtle trends need further confirmation. These findings underscore critical psychological-ecological-behavioral interaction pathways in adolescents with MDD, and suggest loneliness and PSU as promising targets for bridge-informed clinical intervention.
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