Person-Specific Analyses of Smartphone Use and Mental Health: Intensive Longitudinal Study

Area of Science:

• Digital media psychology
• Mental health research
• Behavioral informatics

Background:

• Research on media use and mental health is inconclusive, often due to cross-sectional designs and imprecise measurement.
• Null or small associations between media and mental health hinder theoretical and practical advancements.

Purpose of the Study:

• To investigate person-specific associations between granular media use experiences and mental health over one year.
• To develop new metrics for fragmented media use to advance individualized theories in media psychology.
• To identify unique combinations of media behaviors and mental health symptoms for more effective study.

Main Methods:

• Intensive longitudinal data collection: 6.7 million smartphone screenshots and 123 surveys over 1 year from 5 adults.
• Derived six media use metrics from smartphone metadata and captured symptoms of depression, ADHD, anxiety, and positive affect via surveys.
• Applied idiographic filter models (p-technique canonical correlation analyses) to explore person-specific relationships.

Main Results:

• Discovered substantial, person-specific associations between media use and mental health (r=0.82 to 0.92).
• Demonstrated significant individual variability, with unique combinations of media behaviors and mental health dimensions for each participant.
• Highlighted how specific patterns, like app-switching or prolonged screen time, correlated with distinct mental health outcomes (e.g., anxiety, depression).

Conclusions:

• Media use and mental health relationships are highly individualized, supporting personalized models and interventions.
• Granular, longitudinal data can uncover person-specific patterns crucial for theory, screening, diagnosis, and mental health interventions.
• Emphasized the value of idiographic approaches in understanding complex media-mental health dynamics.