Examining stable and dynamic factors associated with daily problematic mobile phone use: Evidence from a 14-day diary...

Area of Science:

• Psychology
• Computer Science
• Public Health

Background:

• Problematic mobile phone use (PMPU) is a growing concern among university students.
• Identifying key psychological predictors of PMPU is crucial for developing effective interventions.

Purpose of the Study:

• To identify key predictors of daily PMPU using machine learning and SHAP.
• To examine the associations between these predictors and PMPU at different levels (between-person, within-day, across-day).

Main Methods:

• Machine learning (Random Forest) and SHAP analysis were employed.
• A 14-day daily diary study was conducted with 279 Chinese undergraduate students.
• Network analysis was used to explore relationships between PMPU and psychological factors.

Main Results:

• Day-level factors like boredom, stress, and loneliness were significant predictors of next-day PMPU.
• Boredom and stress were central nodes in between-person and contemporaneous networks.
• Prior-day stress, rumination, and boredom predicted next-day PMPU, with reciprocal effects observed.

Conclusions:

• Daily PMPU is significantly influenced by proximal psychological experiences.
• Boredom and stress are core processes maintaining PMPU in university students.
• Findings support targeted interventions for stress management and boredom regulation.