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Abstract:
Internet addiction may arise from multiple factors and personality tendencies have been previously implicated. Prior studies have found that extraversion may be a protective factor mitigating against internet addiction, yielding a "rich-get-richer" effect. However, few studies have explored how extraversion may influence internet addiction from the perspective of online-offline integration. Drawing on a sample of 428 college students, the current study examined a serial mediation model exploring the underlying mechanisms of how extraversion may statistically predict internet addiction through online-offline integration and antecedent factors. The serial mediation model analyses indicated that extraverted internet users exhibited a weaker preference for online anonymity and less online extraversion compensation, thus formulating a higher level of online-offline integration than introverted individuals, which, in turn, appeared to reduce the risk of internet addiction. In contrast, with regard to specific components of online-offline integration, introverted internet users preferred online anonymity, which reduced their relationship integration and increased their likelihood of internet addiction; similarly, the introverted individuals were also more likely to exhibit an extraversion compensation effect. That is, they were more extraverted on the internet than in general; hence, they had a lower level of self-identity integration, resulting in a greater likelihood of experiencing internet addiction. These results highlight the importance of online-offline integration that may account for personality variations in social and psychological outcomes related to internet use, and suggest a role for online anonymity preference and extraversion compensation in influencing specific components of integration.
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BEHAVIORAL SCIENCES
ISSN: 2076-328X
Year: 2022
Issue: 6
Volume: 12
2 . 6
JCR@2022
2 . 5 0 0
JCR@2023
ESI Discipline: PSYCHIATRY/PSYCHOLOGY;
ESI HC Threshold:35
JCR Journal Grade:2
CAS Journal Grade:4
Cited Count:
WoS CC Cited Count: 6
SCOPUS Cited Count: 6
ESI Highly Cited Papers on the List: 0 Unfold All
WanFang Cited Count:
Chinese Cited Count:
30 Days PV: 3
Affiliated Colleges: