Is it possible to cure Internet addiction with the Internet?

Smartphone addiction and phubbing behavior among university students: A moderated mediation model by fear of missing out, social comparison, and loneliness

Introduction

This article examines mediators and moderators that may explain the link between smartphone addiction and phubbing behavior using a sample of 794 university students.

Methods

A mediation model was tested to test the hypothesis that social comparison orientation and fear of missing out would mediate the link between smartphone addiction and phubbing behavior. Additionally, a moderated mediation model was leveraged to examine loneliness as a moderator within the hypothesized model. The data collected were analyzed using SPSS.

Results and Discussion

The findings show a significant positive relationship between smartphone addiction and phubbing behavior. The findings confirm the hypothesized associations and reveal that smartphone addiction is positively linked to phubbing behavior. The link, on the other hand, is partially and sequentially mediated by the fear of missing out and social comparison orientation. As a result, both mediators might be regarded as proximal variables of phubbing behavior. Moreover, the associations between both smart addiction and phubbing behaviors as well as social comparison orientation and phubbing behaviors are moderated by loneliness. These two effects were stronger for university students with high loneliness than for those with low loneliness. This study addresses a major gap in the clinical psychology literature through the attempt to explore the relationship between smartphone addiction and increased phubbing behavior among university students.

Research Trend on the Use of IT in Digital Addiction: An Investigation Using a Systematic Literature Review

Despite the negative role of IT in digital addiction development, IT may have a positive role in dealing with digital addiction. The present study undertakes a systematic literature review to explore the state of play and the trend regarding the use of IT in digital addiction research. Using predefined keywords, the Scopus database was searched for relevant literature published from 2017 to 2020. The initial search found 1655 papers. Six stages of study selection were completed using a set of inclusion and exclusion criteria. The study selection and quality assessment process were applied, then 15 papers were selected for further review. The results show that addiction detection using IT is the most researched topic in digital addiction research. The most commonly used IT in the selected studies are AI methods and biosignal recording systems. Various approaches in detection, prevention, and intervention are suggested in the selected studies. The advantages and limitations of each approach are discussed. Based on these results, some future research directions are suggested.