Frontiers in public health · 2026
Mobile phone addiction and depression among adolescents: the moderation effect of family environment.
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Bai Yanlin, Xu Xia, Jiang Weijie, Yang Yuting, Li Qixi, Li Xiaoli, Zhu Qian, Meng Yajing, Qiu Changjian
Аннотация
BACKGROUND: Mobile phone addiction (MPA) is positively associated with adolescent depressive symptoms, yet the moderating role of multidimensional family environments in this relationship remains poorly understood. This study aimed to identify distinct family environment typologies and examine their moderating effects on the MPA-depression association among Chinese adolescents.
METHODS: A cross-sectional, school-based survey was conducted among middle and high school students in China. MPA and depressive symptoms were assessed using the Mobile Phone Addiction Index (MPAI) and the Patient Health Questionnaire-9 (PHQ-9), respectively. Latent class analysis (LCA) was employed to identify family environment typologies based on seven socioeconomic and structural indicators. Moderated regression analyses tested interaction effects, adjusting for age and gender.
RESULTS: A total of 103,874 students (mean age 15.58 ± 1.74; 50.4% female) participated. LCA revealed three family clusters: "High-Resource Stable Family," "Low-Resource Cohesive Family," and "Low-Resource Fragmented Family." Adolescents in Low-Resource Fragmented family had significantly higher MPA and depression scores (p < 0.001). MPA was positively correlated with depression across all groups (p < 0.001). Family type significantly moderated this relationship, with stronger associations in both Low-Resource clusters (p < 0.05). Subgroup analyses showed specific moderation effects by gender and school level.
CONCLUSION: Multidimensional family environments not only shape levels of MPA and depression but also amplify their association in socioeconomically disadvantaged and structurally fragmented contexts. Employing LCA to identify family typologies provides a nuanced, person-centered framework for targeting prevention efforts and identifying adolescents at elevated digital mental health risk.
METHODS: A cross-sectional, school-based survey was conducted among middle and high school students in China. MPA and depressive symptoms were assessed using the Mobile Phone Addiction Index (MPAI) and the Patient Health Questionnaire-9 (PHQ-9), respectively. Latent class analysis (LCA) was employed to identify family environment typologies based on seven socioeconomic and structural indicators. Moderated regression analyses tested interaction effects, adjusting for age and gender.
RESULTS: A total of 103,874 students (mean age 15.58 ± 1.74; 50.4% female) participated. LCA revealed three family clusters: "High-Resource Stable Family," "Low-Resource Cohesive Family," and "Low-Resource Fragmented Family." Adolescents in Low-Resource Fragmented family had significantly higher MPA and depression scores (p < 0.001). MPA was positively correlated with depression across all groups (p < 0.001). Family type significantly moderated this relationship, with stronger associations in both Low-Resource clusters (p < 0.05). Subgroup analyses showed specific moderation effects by gender and school level.
CONCLUSION: Multidimensional family environments not only shape levels of MPA and depression but also amplify their association in socioeconomically disadvantaged and structurally fragmented contexts. Employing LCA to identify family typologies provides a nuanced, person-centered framework for targeting prevention efforts and identifying adolescents at elevated digital mental health risk.