Fluctuations in behavior and affect in college students measured using deep phenotyping

Area of Science:

• Psychology
• Digital Health
• Student Mental Health

Background:

• College students frequently experience psychological distress due to academic and social pressures.
• Understanding the dynamics of student affective and behavioral experiences is crucial for characterizing psychological distress.

Purpose of the Study:

• To investigate the relationship between academic, social, and affective behaviors and psychological distress in first-year college students.
• To identify distinct student clusters based on behavioral and affective patterns and their association with distress.

Main Methods:

• Utilized wearables and smartphones for continuous monitoring of 49 first-year college students throughout an academic year.
• Analyzed changes in affect, sleep, academic, and social behaviors across academic semesters, breaks, weekdays, and weekends.
• Identified student clusters exhibiting behavioral-affective dissociations and varying distress levels.

Main Results:

• Significant changes in affect and behavior were observed between academic semesters and breaks, and weekdays versus weekends.
• Three distinct student clusters emerged, characterized by behavioral-affective dissociations and differential distress levels.
• Social stress, more than academic stress, predicted subsequent clinical symptoms and was prominent in the highest distress cluster, even during the COVID-19 pandemic.

Conclusions:

• Sustained social stress, rather than academic stress, may be a key indicator for identifying students at higher risk for psychopathology.
• Digital health tools can provide continuous, real-world data on student well-being.
• Interventions targeting social stressors may be more effective in mitigating psychological distress among college students.