ArticleFrontiers in psychiatry2024
Sleep patterns and smartphone use among left-behind children: a latent class analysis and its association with depressive symptoms.
Article in Frontiers in psychiatry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Depression in left-behind adolescents from single-parent families: a nomogram based on multidimensional risk factors.Child and adolescent psychiatry and mental health · 2025Article
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Authors and funding
6 authors.
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Abstract
Background: Left-behind children in China face challenges in sleep patterns, technology use, and mental health. This study uses an individual-centered approach to derive behavioral profiles associated with depressive symptoms. Methods: Data from 131,586 left-behind children aged 8 to 18 years from the Chinese Psychological Health Guard for Children and Adolescents Project were analyzed. Participants were recruited from 569 centers across schools, community institutes, orphanages, and children's hospitals throughout China. Latent class analysis was conducted using weekday and weekend sleep duration and smartphone use as indicators. Depressive symptoms were assessed using the Center for Epidemiologic Studies Depression Scale (CES-D). Results: Four distinct classes emerged: Sufficient Sleep Low Users (23.6%), Moderate Sleep Medium Users (25.2%), Limited Sleep High Users (22.1%), and Healthy Sleep Low Users (29.2%). Significant differences in CES-D scores were found between classes (F(3, 131579) = 4929, Conclusions: This study reveals complex associations between sleep patterns, smartphone use, and depressive symptoms among left-behind children. The identified behavioral profiles provide insights into population heterogeneity and inform targeted intervention strategies. Findings emphasize the importance of addressing both sleep and technology use in mental health initiatives for this vulnerable population.
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