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Accepted for/Published in: JMIR Mental Health

Date Submitted: Jul 18, 2023
Date Accepted: Feb 26, 2024

The final, peer-reviewed published version of this preprint can be found here:

Digital Phenotypes for Early Detection of Internet Gaming Disorder in Adolescent Students: Explorative Data-Driven Study

Cho K, Kim M, Cho Y, Hur JW, Kim DH, Park S, Park S, Jang M, Lee CG, Kwon JS

Digital Phenotypes for Early Detection of Internet Gaming Disorder in Adolescent Students: Explorative Data-Driven Study

JMIR Ment Health 2024;11:e50259

DOI: 10.2196/50259

PMID: 38683658

PMCID: 11091800

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

The Identification of Digital Phenotypes Associated with Internet Gaming Disorder in Adolescents

  • Kwangsu Cho; 
  • Minah Kim; 
  • Youngeun Cho; 
  • Ji-Won Hur; 
  • Do Hyung Kim; 
  • Seonghyeon Park; 
  • Sunghyun Park; 
  • Moonyoung Jang; 
  • Chang-Gun Lee; 
  • Jun Soo Kwon

ABSTRACT

Background:

Adolescents diagnosed with Internet gaming disorder (IGD) often experience difficulties in their learning abilities and daily functioning. Early identification and intervention for IGD in adolescents are crucial, but seeking treatment at psychiatric hospitals is uncommon among this population. Thus, there is a need for the development of an assessment tool that can be seamlessly integrated into their daily routines.

Objective:

The aim of this study was to uncover digital markers of Internet Gaming Disorder (IGD) among adolescent students while they were engaged in learning activities.

Methods:

This study collected passive sensor data on tablet computers from 927 adolescents, with 59 in the IGD group and 868 in the control group. Analysis included 77 keyboarding-related and stroking behaviors, such as the number of key presses, speed, acceleration, length, duration time, path, and pressure. Multiple regressions were conducted using bootstrapping and stratified sampling methods, followed by MANOVAs and univariate ANOVAs.

Results:

The study identified five digital indicators for IGD: Stroke acceleration, stroke speed, vertical distance, number of blank spaces, and time interval. The MANOVAs and univariate ANOVAs showed that these five digital markers effectively distinguished behavioral differences between the IGD and non-IGD groups.

Conclusions:

The findings suggest that adolescents with IGD display a stronger impulsive tendency, prioritizing speed over accuracy in their digital interactions. Overall, the digital phenotypes for IGD demonstrate reliability and hold promise in providing valuable insights into how IGD manifests in a learning environment.


 Citation

Please cite as:

Cho K, Kim M, Cho Y, Hur JW, Kim DH, Park S, Park S, Jang M, Lee CG, Kwon JS

Digital Phenotypes for Early Detection of Internet Gaming Disorder in Adolescent Students: Explorative Data-Driven Study

JMIR Ment Health 2024;11:e50259

DOI: 10.2196/50259

PMID: 38683658

PMCID: 11091800

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