JOURNAL ARTICLE

Social Workers' Perceptions of the Stigmatization Process for Individuals with Mental Health Needs within the Criminal Justice System in Türkiye: An Intersectional Analysis.

  • Published In: International Journal of Forensic Mental Health, 2025, v. 24, n. 4. P. 336 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Afyonoğlu, Meliha Funda; Pak Güre, Merve Deniz; Erükçü Akbaş, Gamze; Uğurlu, Zilan 3 of 3

Abstract

This article examines social workers' perceptions of the stigmatization process experienced by individuals with mental health needs involved in the criminal justice system in Türkiye, using an intersectional framework. The study identifies three forms of stigma—self, public, and structural—that affect these individuals, with stigma intensifying after criminal justice involvement and varying according to intersecting social categories such as gender, sexual orientation, class, ethnicity, and type of crime. Women, LGBTQI+ individuals, immigrants, and those convicted of sexual offenses face distinct and heightened stigmatization, which impedes access to services and social reintegration. The research highlights systemic barriers within Türkiye's criminal justice and health institutions, emphasizing the need for increased, specialized mental health services and targeted anti-stigma interventions informed by intersectional awareness. Future research is recommended to include longitudinal and quantitative studies and to incorporate the perspectives of affected individuals to better tailor support services.

Additional Information

  • Source:International Journal of Forensic Mental Health. 2025/11, Vol. 24, Issue 4, p336
  • Document Type:Article
  • Subject Area:Science
  • Publication Date:2025
  • ISSN:1499-9013
  • DOI:10.1177/14999013251346499
  • Accession Number:188053930
  • Copyright Statement:Copyright of International Journal of Forensic Mental Health 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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