Relational work with distressing voices mirroring experiences of discrimination and marginalisation: Three illustrative cases of an extended form of AVATAR therapy ( AV ‐ EXT )
Year: 2025
Type: article
Study design: Case Report
Abstract: BACKGROUND: For voice-hearers from minoritised communities, voices may reflect interpersonal and societal discrimination, including experiences of feeling silenced or 'voiceless'. AVATAR therapy is a relational approach involving facilitated dialogues between a voice-hearer and a digital embodiment of their main distressing voice (the avatar). The aim is for the voice hearer to gain understanding, acceptance and empowerment. AIMS: This paper illustrates an extended form of AVATAR therapy (AV-EXT), which seeks to understand a person's voices within their developmental and relational context. METHODS: We present three therapy narratives in which voices mirrored experiences of discrimination and marginalisation based on aspects of the person's identity. Personalised avatars were used during dialogues to re-enact the lived experience of voice-hearing. RESULTS: Avatar dialogues offered opportunities to rescript disempowering experiences, target associated meanings and connect individuals with the power of their own identity. CONCLUSIONS: Implications for the continued refinement of AVATAR therapy and other relational approaches are considered. This paper aims to support wider reflection on the impact of discrimination on distressing voices.
DOI: 10.1111/papt.70027
Institutions: King's College London, South London and Maudsley NHS Foundation Trust, Greater Manchester Mental Health NHS Foundation Trust, Manchester Academic Health Science Centre, University of Manchester, North East London NHS Foundation Trust, University College London, NHS Greater Glasgow and Clyde, University of Glasgow, Ruhr University Bochum
Language: English
Subfield: Psychiatry and Mental health
Field: Medicine
Domain: Health Sciences
SDG: Reduced inequalities
Open Access status: hybrid
Estimated APC paid: $4,070
OpenAlex ID: W4417100717
