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Artificial intelligence-based technologies are gradually being applied to psych-iatric research and practice. This paper reviews the primary literature concerning artificial intelligence-assisted psychosis risk screening in adolescents. In terms of the practice of psychosis risk screening, the application of two artificial intelligence-assisted screening methods, chatbot and large-scale social media data analysis, is summarized in detail. Regarding the challenges of psychiatric risk screening, ethical issues constitute the first challenge of psychiatric risk screening through artificial intelligence, which must comply with the four biomedical ethical principles of respect for autonomy, nonmaleficence, beneficence and impartiality such that the development of artificial intelligence can meet the moral and ethical requirements of human beings. By reviewing the pertinent literature concerning current artificial intelligence-assisted adolescent psychosis risk screens, we propose that assuming they meet ethical requirements, there are three directions worth considering in the future development of artificial intelligence-assisted psychosis risk screening in adolescents as follows: nonperceptual real-time artificial intelligence-assisted screening, further reducing the cost of artificial intelligence-assisted screening, and improving the ease of use of artificial intelligence-assisted screening techniques and tools.

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Sleep time and depression symptoms are important factors affecting cognitive development in adolescents. Based on the China Education Panel Survey (CEPS) database, this study used a two-wave cross-lagged model to examine the bidirectional relationship between sleep time, depression symptoms, and cognitive development. Descriptive statistics showed that Chinese adolescents’ cognitive development increased significantly from 7th to 8th grade in junior high school, but unfortunately, their depression level and average sleep time per night demonstrated a slightly deteriorating trend. Correlation analysis showed that there was a relatively stable negative correlation between cognitive development, sleep time, and depression symptoms. Moreover, the cross-lagged model revealed that there was a bidirectional relationship between cognitive development and sleep time, a bidirectional relationship between depression symptoms and sleep time, and a unidirectional relationship between depression symptoms and cognitive development. Male adolescents in the subgroup were consistent with the total sample. Among female adolescents, only cognitive development and sleep time have a bidirectional relationship, while depression symptoms and cognitive development, and depression symptoms and sleep time have a unidirectional relationship. Therefore, it is of significance to take targeted action to promote cognitive development and healthy growth in adolescents worldwide.

Everyone’s time is limited, and there is competition between different aspects of time use; this requires comprehensive consideration of the effects of different aspects of time use on cognitive achievement in adolescents. This study uses a dataset of 11,717 students from a nationally representative large-scale survey project conducted in 2013 to 2014 to clarify the relationship between time use (including working on homework, playing sports, surfing the Internet, watching TV, and sleeping) and cognitive achievement among Chinese adolescents, and explores the mediating role of depression symptoms in the relationship between time use and cognitive achievement. The results of the correlation analysis show that the average daily time spent on homework, playing sports, and sleeping is significantly positively correlated with cognitive achievement (p < 0.01), while time spent surfing the Internet and watching TV are significantly negatively correlated with cognitive achievement (p < 0.01). The results of the mediating effect model show that depression symptoms play a mediating role in the relationship between time use and cognitive achievement among Chinese adolescents. Specifically, time spent playing sports (indirect effect = 0.008, p < 0.001) and sleeping (indirect effect = 0.015, p < 0.001) have a positive effect on cognitive achievement when using depression symptoms as mediators; time spent on homework (indirect effect = −0.004, p < 0.001), surfing the Internet (indirect effect = −0.002, p = 0.046), and watching TV (indirect effect = −0.005, p < 0.001) have a negative effect on cognitive achievement when using depression symptoms as mediators. This study contributes to the understanding of the relationship between time use and cognitive achievement among Chinese adolescents.