## 5 Discussion
The prevention approach by stimulating user awareness as suggested in study A is One of the psychological approaches in addiction prevention. However, it is still limited in that it only uses the time dimension as a basis for providing prevention feedback to users. Future research may enhance the advantage of this approach by involving some other dimensions. The second study found in prevention proposed the utilization of AI to suggest the appropriate prevention program for users. However, in this study, AI only plays a role in selecting the proper prevention program based on the individual's addiction risk level. AI has the potential to be explored as an essential part of the prevention program itself. For instance, using the approach applied in study A, the process of stimulating user awareness can be implemented by utilizing AI. All studies found on the intervention propose frameworks to develop IT-based intervention programs. Because the results of these studies are still in the conceptual stage, future research may focus on the implementation of these frameworks and the measurement of the intervention strategy's effectiveness for combating digital addiction. Second, the utilization of human physiological parameters and AI technology may still be further explored for developing an effective, reliable, and real-time system for combating digital addiction. The IT found in this study can be classified into four categories, i.e., application, application framework, AI, and biosignal recording system. The two most used IT in the selected studies are AI and biosignal recording system (Figure 8). The biosignal recording system has strength in recording real-time human physiological data. The real-time detection system may be used further by users to assist them in using digital technology or may be used by any specialists in the user rehabilitation effort. One consideration in developing a physiological-based detection system is how it can be implemented as a personal device that can be used practically by users at an affordable cost. Future research may explore the development of such technology. The strength of AI lies in its capability to intelligently process the input data. The intelligent system can be developed to assist users to prevent or intervene in excessive behavior of using digital technology. This intelligent system may exploit various AI technologies as its processing system. The potential capabilities of AI have also been studied and implemented in the other addiction domain, i.e., substance addiction domain. Various AI technologies have been implemented in the prevention and intervention of substance addiction [66]. One example of AI applications that help those suffering from substance addiction is Addicaid. Addicaid combines machine learning, adaptive AI, and clinical research to predict when a person may be at risk for relapse and generate treatment suggestions [67]. The other app called Triggr was developed to provide moral support during someone's recovery. Triggr has capabilities to track how long a person has been sober and to connect him via text message or chatting apps with his recovery coaches [66]. Considering each of the advantages of biosignal recording systems and AI, future research may wish to focus on combining the strength of those IT to develop a reliable and real-time system for detecting and combating digital addiction.