Objective:

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.