JOURNAL ARTICLE

Cyberbullying and Bullying Reports Among Youth in a Behavioral Health Inpatient Unit: Insights From Youth and Parent Intake Surveys.

  • Published In: Journal of the American Psychiatric Nurses Association, 2025, v. 31, n. 3. P. 250 1 of 3

  • Database: Psychology Source 2 of 3

  • Authored By: Drouin, Michelle; Kardys, Kelley; Flanagan, Mindy; Pater, Jessica; Kerrigan, Connie 3 of 3

Abstract

This article focuses on the implementation and analysis of a novel intake form assessing offline bullying and cyberbullying among youth admitted to a behavioral health inpatient facility in the Midwestern United States. Among 622 youth aged 10 and older, 21.5% reported cyberbullying victimization, 6.1% reported offline bullying victimization, and 8% reported mixed bullying, with bullied youth feeling significantly less safe in various environments than non-bullied peers. The study found only fair to moderate agreement between youth and parent reports of bullying, with many parents unaware of their child's victimization or its contribution to hospitalization. Results suggest that feelings of safety and negative emotional impact from bullying, rather than bullying frequency or type, are significant factors related to inpatient admission, highlighting the need for behavioral health units to adapt intake procedures and develop educational programming addressing both offline and online bullying.

Additional Information

  • Source:Journal of the American Psychiatric Nurses Association. 2025/06, Vol. 31, Issue 3, p250
  • Document Type:Article
  • Subject Area:Psychology
  • Publication Date:2025
  • ISSN:1078-3903
  • DOI:10.1177/10783903241265888
  • Accession Number:185255871
  • Copyright Statement:Copyright of Journal of the American Psychiatric Nurses Association is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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