Identifying Potentially Effective Preventive Measures of Game Addiction on Children and Adolescents: A Literature-Based Discovery (LBD) Approach

Authors

Ananya S. Choudhury, Lingnan UniversityFollow
Wendy Hui, Singapore Institute of TechnologyFollow
Eric See-To, Lingnan UniversityFollow

Paper Number

1877

Abstract

To help us go through the vast, multidisciplinary literature on game addiction, this study makes use of a knowledge extraction technique called Literature-Based Discovery (LBD) to identify potentially effective but under-studied measures that help prevent the negative effects of online game addiction among children and adolescents. LBD was implemented using association rule mining to generate a list of preventive measure-negative effect pairs (rules), which are then evaluated using the ‘support’ metric. This helped us identify preventive measures that have received relatively less research attention, and one such preventive measure is peer education. Using meta-analysis, we computed the average effect size of peer education and showed that it is comparable to other popular preventive measures in terms of effectiveness. This study which involves a total of 876 articles demonstrates generally that LBD can be a useful research method to discover promising but under-studied research topics in the existing literature.

Comments

Paper Number 1877

Recommended Citation

Choudhury, Ananya S.; Hui, Wendy; and See-To, Eric, "Identifying Potentially Effective Preventive Measures of Game Addiction on Children and Adolescents: A Literature-Based Discovery (LBD) Approach" (2022). PACIS 2022 Proceedings. 274.
https://aisel.aisnet.org/pacis2022/274