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Smartphone Screen Time Characteristics in People With Suicidal Thoughts: Retrospective Observational Data Analysis

Marta Karas¹, Debbie Huang¹, Zachary Clement¹

¹Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, United States.

JMIR Mhealth and Uhealth

|October 11, 2024

Summary

This summary is machine-generated.

This study shows that passively collected smartphone data can accurately measure screen time in individuals with suicidal thoughts, offering a reliable alternative to self-reports for mental health research.

Keywords:

app data analysis study feasibility mental health mobile apps mobile health mobile phone monitor observational data psychiatric screen screen time smartphone suicidal suicidal ideation suicidal thoughts and behavior survey

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Area of Science:

Digital Phenotyping
Mental Health Technology
Psychiatric Research

Background:

Smartphone monitoring offers novel ways to track mental health behaviors, including suicidal ideation.
Traditional research relies on self-reported data, which can be unreliable.
Passive data collection from smartphone sensors provides objective behavioral insights, such as screen time.

Purpose of the Study:

To develop methods for identifying screen-on bouts and screen time characteristics from passive smartphone logs.
To estimate daily smartphone screen time in individuals experiencing suicidal thinking.
To offer a more reliable alternative to self-report measures for assessing screen time in this population.

Main Methods:

Utilized the Beiwe app to passively collect phone state logs from 126 participants for up to 6 months.
Derived daily screen time metrics: screen-on time, screen-on/off bout durations, and screen-on bout count.
Analyzed data across age subgroups, operating systems, and monitoring periods, including sensitivity analyses and daylight saving time impact.

Main Results:

Mean daily screen-on time was approximately 255-271 minutes for adolescents and adults, with no significant differences by operating system.
Most daily screen time measures did not significantly differ between the first 4 weeks and later monitoring periods.
Sensitivity analysis revealed the significant impact of bout identification parameters on screen time measures; daylight saving time showed a statistically significant effect on screen-on time.

Conclusions:

Passively collected smartphone logs provide a viable alternative to self-report measures for studying screen time in individuals with suicidal thinking.
This approach demonstrates feasibility for future research on the links between daily screen time, mental health, and other factors.
Further research can leverage passive data collection for a deeper understanding of mental health conditions.