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ORIGINAL RESEARCH article

Front. Psychiatry
Sec. Adolescent and Young Adult Psychiatry
Volume 16 - 2025 | doi: 10.3389/fpsyt.2025.1513685

Subgroups of Nonsuicidal Self-injury in a Large Diverse Sample of Online Help-seekers

Provisionally accepted
  • 1 Feinberg School of Medicine, Northwestern University, Chicago, United States
  • 2 Mental Health America, Alexandria, United States

The final, formatted version of the article will be published soon.

    Introduction: Many young people access information and resources for nonsuicidal self-injury (NSSI) online; yet our understanding of who accesses such information is limited. NSSI is a behavior with varied presentations. Understanding heterogeneity can help guide person-centered intervention. The present study aimed to (1) empirically identify classes of individuals with NSSI and (2) compare the classes according to demographic and clinical characteristics.Methods: Data were collected from a survey posted to a national advocacy group website. Latent class analysis was used to derive classes based on characteristics associated with NSSI severity.Relationships between the latent classes and variables along five dimensions (behavior change, consequences or life interference, expectancies, functions, and NSSI across lifetime) were explored via logistic regression models.: 11,262 individuals reporting past month NSSI were included in analyses. The 4-class model provided the most clinically interpretable groups. Class 1 was the smallest (16.8%), scored highest on all items and reported the youngest age of onset. Class 3 was the largest (31.8%), scored lowest on all items and reported the latest age of onset. Classes 2 (29.3%) and 4 (22.2%) had moderate scores on most items and differed in levels of suicidal ideation. Conclusion: Classes presented with more severe symptoms than what is typical in samples in extant literature underscoring the importance of tailoring interventions for dissemination in online contexts.

    Keywords: nonsuicidal self-injury, subgroups, latent class analysis, heterogeneity, subtypes

    Received: 18 Oct 2024; Accepted: 05 Feb 2025.

    Copyright: © 2025 Kruzan, Washburn, Aaby, Nguyen and Mohr. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Kaylee P Kruzan, Feinberg School of Medicine, Northwestern University, Chicago, United States

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.