ArticleBMC psychology2026
From self to screen: a person-centered analysis of self-identity and internet addiction among Chinese college students.
Article in BMC psychology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundThe internet has become a crucial space for college students to explore and construct their self-identity. However, discrepancies between self-identity in real versus virtual environments can generate psychological dissonance and identity confusion, which in turn heighten vulnerability to maladaptive coping strategies such as internet addiction (IA). This study aims to identify the latent profiles of self-identity among Chinese college students and examine how these profiles relate to their susceptibility to IA.
methodA total of 1,022 Chinese college students (44.91% male; mean age = 20.38 years, SD = 2.94) completed the Self-Identity Scale and the Internet Addiction Scale. Latent profile analysis was used to classify participants based on their patterns of self-identity development. Multinomial logistic regression was conducted to examine how demographic variables predicted latent profile membership, and the Bolck-Croon-Hagenaars (BCH) method was employed to compare differences in internet addiction and its dimensions across the identified profiles.
resultsThree distinct self-identity profiles were identified: the self-identity acceptance group, the self-identity moratorium group, and the self-identity achievement group. These profiles revealed distinct internet addiction patterns: individuals classified as moratorium reported the most severe addiction, contrasting with the achievement group, which showed minimal levels.
conclusionsThe findings indicate that distinct patterns of self-identity are closely associated with variations in Chinese college students' vulnerability to internet addiction. Students undergoing identity moratorium appear particularly at risk for excessive internet use. Supporting identity development may therefore represent an effective focus for targeted interventions aimed at reducing IA risk.
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