Background: Internet addiction and depression frequently co‐occur among university students, resulting in amplified functional deterioration and treatment resistance. Despite established bidirectional relationships, existing research has predominantly examined linear associations and treated these conditions as single global constructs. This study integrated person‐centered and network‐based approaches to identify distinct symptom profiles of Internet addiction and depressive symptoms, examine sociodemographic predictors of profile membership, and uncover interconnected symptom networks within high‐risk populations among Chinese university students. Methods: A multicenter cross‐sectional study was conducted from April to July 2024. Data were collected through a web‐based survey incorporating validated instruments for Internet addiction, depression, and suicide risk assessment. Latent profile analysis was employed to identify distinct symptom profiles, followed by multivariate logistic regression to examine sociodemographic predictors. Network analysis was performed within the high‐risk profile to unveil symptom interactions, central symptoms, bridge symptoms, and symptomatic pathways to suicide risk. Results: Among 30,992 participants, latent profile analysis identified three distinct groups: Healthy profile (59.31%), at‐risk profile (35.06%), and comorbidity profile (5.63%). Students who were female, ethnic minorities, in higher grade levels, and had prolonged Internet use showed increased risks of problematic profiles. Conversely, enrollment in bachelor’s programs, science and medical majors, higher household income, and regular physical activity demonstrated protective effects. Network analysis revealed Internet preoccupation and fatigue as central symptoms, identified key bridge symptoms (e.g., offline negative affect, difficulty concentrating) linking the symptom clusters, and highlighted Internet withdrawal symptoms and depressed mood as critical pathways to suicide risk within the comorbidity profile. Conclusion: This study identified distinct profiles of Internet addiction and depression comorbidity, with specific sociodemographic and lifestyle predictors informing targeted screening strategies. Network analysis revealed central symptoms and specific bridge symptoms connecting the conditions, while also identifying critical pathways to suicide risk in the Comorbidity profile, providing empirical evidence for developing precise and effective interventions.

Background: Adolescence is a formative period of social development. Adolescents have experienced considerable changes in their lives due to the COVID-19 pandemic. We conducted a longitudinal study to examine the effects of the COVID-19 pandemic on adolescents’ prosocial attributes and empathy, as well as their longitudinal bilateral relationships. Methods: A total of 2,510 students from five junior schools in Sichuan Province were recruited via random cluster sampling. Data were collected in December 2019 (Wave 1, before the outbreak of the pandemic) and July 2020 (Wave 2, during the pandemic) in Chengdu, Sichuan, China. Prosocial attributes and empathy were measured with the Positive Youth Development Scale (GPYDS) subscale and Chinese Empathy Scale, respectively. Results: During the pandemic, both empathy and prosocial attributes decreased significantly from 49.89 (9.12) and 49.89 (8.80) before to 48.29 (8.72) and 49.39 (9.26) (p < 0.001), respectively. A higher level of empathy at Wave 1 significantly predicted higher prosocial attributes at Wave 2 (β = 0.173, SE = 0.021, t = 8.430, p < 0.001). A lower prosocial attributes score predicted a significantly lower empathy score from Wave 1 to Wave 2 (β = 0.100, SE = 0.021, t = 4,884, p < 0.001). Conclusions: The COVID-19 pandemic has had detrimental effects on adolescents’ empathy and prosocial attributes. Special attention should be given to these two longitudinally associated factors in any social crisis, such as the COVID-19 pandemic, considering their importance for adolescents’ physical, mental, and social development.

(1) Background: Female body composition undergoes significant changes to support fetal growth and development during pregnancy. This study investigated the association of maternal body composition in the second trimester and macrosomia and explored whether body-composition-related indicators could be used to predict macrosomia. (2) Methods: This study was conducted in China from December 2016 to December 2021. Women with singleton pregnancies, gestational ages between 37 and 42 weeks, and an absence of pregnancy complications were included. In the second trimester, bioelectric impedance analysis (BIA) was used to measure body-composition-related indicators. Logistic regression analysis was performed to explore the risk factors for macrosomia. The predictive performance of maternal body composition and clinical indicators for macrosomia were assessed using the area under the receiver-operating-characteristics curve (AUC). (3) Results: This retrospective study involved 43,020 pregnant women; we collected 2008 cases of macrosomia. Gravidity, gestational age, body mass index (BMI), gestational weight gain (GWG), total body water, fat mass, fat-free mass (FFM), skeletal muscle mass, and visceral fat level were risk factors for macrosomia (p < 0.05 for all). In the prediction model, the AUC of FFM for predicting macrosomia was the largest (0.742). (4) Conclusions: Body-composition-related indicators associated with macrosomia and body composition measurements in the second trimester can predict the risk of macrosomia, enabling clinicians to implement interventions earlier to reduce adverse perinatal outcomes.

Tai Chi, a mindfulness-based aerobic exercise, may alleviate depressive symptoms and improve physiological markers in older adults. However, its distinct effects compared with general aerobic exercise remain unclear. To compare the effects of Tai Chi and general aerobic exercise on depressive symptoms and serum lipid levels in community-dwelling older adults with mild to moderate depression, a randomized controlled trial was conducted. Participants were randomly assigned to Tai Chi (n = 120) or general aerobic exercise (n = 120) for 3 months. Depressive symptoms and serum lipid levels were measured at baseline and postintervention. A generalized estimating equation was used to assess group differences over time. The Tai Chi group exhibited significantly greater reductions in depressive symptoms and improvements in serum lipid profiles compared with the general aerobic exercise group. Tai Chi’s mind–body synergy may enhance its antidepressant effects, offering a promising approach to mental health and healthy aging.