Rebuilding well-being from daily lifestyle habits: Understanding the problematic social media use and its relationship with sleep, physical activity, and well-being

Study 1: The current study focuses on the association between PSMU and happiness, exploring a mediating effect of healthy habits among Italian adolescents. A total of 58976 Italian adolescents (mean age = 13.55, SD = 1.63; age range = 10.54 -16.46; 49.40% females;) were included. The pattern of relationships specified by the theoretical model was examined through path analysis. Difficulties in getting to sleep and frequency of physical activity as mediators of the relationship between PSMU and happiness, while the chain mediating effect of frequency of physical activity on difficulties in getting to sleep wasn’t significant for female group. Furthermore, females and older ages were sensitive to the whole model. Along with difficulties in getting to sleep and frequency of physical activity, healthy habits may contribute to the association between PSMU and happiness. Study 2: This study aimed to test the factorial structure, internal consistency, and external validity of the Chinese version of the PSMUS in a sample of 672 adults (31% males) aged between 18 and 58. A series of confirmatory factor analyses supported the bifactor structure of the PSMUS, including a general factor and five specific independent components, namely preference for online social interactions, mood regulation, cognitive preoccupation, compulsive use, and negative outcomes. Hierarchical Omega supported the presence of a general factor, and also ancillary indexes suggested that the questionnaire is not strictly unidimensional. Subsequent structural equation modeling testing the incremental contribution of each PSMUS facet in predicting negative emotional states showed that, above and beyond the general factor, only one of the five dimensions (i.e., negative outcomes) significantly links to our criterion measure further support the use of an overall PSMU score. Moreover, results support the external validity of the questionnaire, given its positive association with depression, anxiety, and stress scores. The Chinese version of the PSMUS is a psychometric sound instrument to assess the level of PSMU in adults. Future research may evaluate the cross-cultural validity of the bifactor model and its associations with other assessment methods. Study 3: The present study aims to conceptualize the associations between PSMU, sleep disturbance, and well-being as interacting between nodes to identify the most influential central and bridge domains that come into play. The analysis included a total of 564 Chinese emerging adults (Mean = 24.59, SD = 3.25, ranging from 18 to 30 years old). Network analysis was employed by using EBICglasso model. “Cognitive preoccupation” demonstrated a consistent central role in all the networks. Following by the central symptom of “compulsive use” in the relationship between PSMU and sleep disturbance. While “positive emotions” took on a central role both between the networks of PSMU and well-being, and among PSMU, BSMU, sleep disturbance, and well-being. Furthermore, the “negative outcomes” symptom of PSMU served as bridging factor connecting PSMU and sleep disturbance communities. However, in this context, when BSMU was added, BSMU played the primary bridging role, and then “compulsive use” and “negative outcomes between PSMU, BSMU, and sleep disturbance. Moving on, within the networks depicting the relationships with well-being, the well-being symptoms “negative emotions” and “loneliness” played crucial bridging roles. This study reveals a strong network connection among PSMU, BSMU, sleep disturbance, and well-being. The PSMU symptom “cognitive preoccupation” and "positive emotions" in well-being are pivotal, offering key targets for addressing maladaptive thinking and fostering positive emotions at the same time. We also emphasize the role of BSMU symptoms and compulsive social media use, contributing to sleep disturbance in problematic users.