Dimension-level network structure linking depression, anxiety, stress, sleep problems, and problematic smartphone use among chinese medical students - Summary - MDSpire
To characterize associations among emotional distress, sleep problems, and problematic smartphone use (PSU) among medical students.
Approach:
Statistical Methods: Examined strength, bridge strength, node predictability, bootstrapped stability, and gender-based network differences using regularized Gaussian graphical models.
Key Findings:
Anxiety (39.89%) was the most prevalent emotional distress dimension, followed by depression (34.60%) and stress (15.58%).
Sleep problems were detected in 23.42% of participants, while problematic smartphone use was found in 64.71%.
Nodes clustered into differentiated emotional distress, sleep, and PSU modules, with stronger within-domain than cross-domain edges.
In the DASS-MPAI network, stress and withdrawal had the highest strength; in the PSQI-MPAI network, withdrawal and inefficiency were the strongest nodes.
Bridge strength identified sleep disturbance, daytime dysfunction, and anxiety as prominent cross-domain bridge nodes.
No significant gender differences in global strength, but the omnibus network structure test was significant.
Interpretation:
Findings provide a dimension-level map of associations among emotional distress, sleep problems, and PSU.
Limitations:
Cross-sectional design limits causal inference.
Findings are based on a single-institution sample, which may not be generalizable.
Conclusion:
The study offers insights into the associations among emotional distress, sleep issues, and PSU.
