Profiles and transitions of non-suicidal self-injury with addictive features in adolescents: Predictive role of maladaptive cognitive schemas.

Authors

Quan Zhou, Yiting Liang, Xia Liu

Published in

Journal of behavioral addictions. Aug 16, 2025. Epub Aug 16, 2025.

Abstract

Non-suicidal self-injury (NSSI) with addictive features is prevalent among adolescents and linked to various detrimental outcomes. However, little is known about the heterogeneity of these features and the factors influencing their progression. This study examined profiles and transitions of NSSI addictive features (NSSI-AF) in adolescents and the role of maladaptive cognitive schemas in profile memberships and transitions.
This longitudinal study involved 2,951 adolescents (42.9% female; Mage = 13.79; SD = 0.73) assessed at two time points over a nine-month interval. Questionnaires assessed NSSI-AF and maladaptive schemas. Latent profile analysis identified profiles at each time point, while latent transition analysis examined profile transitions. Logistic regression assessed associations between maladaptive schemas and profile memberships and transitions.
Three profiles emerged: no, low, and high NSSI-AF. The no profile exhibited high stability, with 98% remaining in this group. The low profile was the least stable, with only 22% remaining, 67% transitioning to the no profile, and 11% shifting to the high profile. The high profile showed moderate stability, with 36% remaining at high risk. Adolescents with elevated maladaptive schemas, especially in the disconnection & rejection and impaired autonomy & performance domains, were more likely to belong to or transition into at-risk profiles.
Findings reveal distinct profiles and transition patterns in NSSI-AF and suggest that maladaptive schemas-particularly disconnection & rejection and impaired autonomy & performance-serve as important predictors. These insights may inform the development of schema-focused interventions tailored to the unique characteristics and risks within each profile.

PMID:
40818054
Bibliographic data and abstract were imported from PubMed on 17 Aug 2025.

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