GOBLIN: Prototype Architecture and Prospective Validation Roadmap for Clinician-Supervised Management of Auditory Verbal Hallucinations

Auditory verbal hallucinations are one of the most common symptoms in schizophrenia, contributing substantially to distress, functional impairment, and relapse risk. Existing therapeutic approaches, including pharmacological treatment and structured psychotherapies such as cognitive behavioral therapy for psychosis and AVATAR therapy, show promising clinical outcomes. However, scalability remains limited due to resource intensity and reliance on specialized personnel. Against this background, we describe the rationale, prototype architecture, and prospective validation roadmap for GOBLIN—a digital platform prototype combining personalized voice conversion, webcam-based eye-tracking, and large-language-model-assisted clinical documentation and decision support. The platform is intended to support clinician-supervised therapeutic workflows and between-visit monitoring following prospective validation. GOBLIN is intended to investigate whether an integrated digital workflow could address key limitations of current care models in schizophrenia and psychotic disorders, including fragmented follow-up, limited responsiveness to rapid symptom changes, and lack of scalable intervention tools. Our conceptual prototype is the first step toward leveraging the potential of digital, AI-driven platforms to complement existing treatment modalities and improve long-term management of psychosis-related symptoms. The system’s modules are intended for clinician-supervised research workflows and remain investigational. This manuscript does not report completed clinical validation, therapeutic efficacy, diagnostic performance, relapse-prediction performance, or validated safety outcomes. Such capabilities remain to be evaluated prospectively through staged technical, usability, safety, and clinical studies before clinical implementation can be considered.

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Publication Details

Journal
Informatics
Published
2026-10-27
DOI
https://doi.org/10.3390/informatics13110180
Primary Topic
Schizophrenia research and treatment
Type
article
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article

GOBLIN: Prototype Architecture and Prospective Validation Roadmap for Clinician-Supervised Management of Auditory Verbal Hallucinations

Maria-Luiza Vladarean, Zaki Milhem, Roland Stretea, Alexandru Constantin Stan et al.
1 links
Informatics
Schizophrenia research and treatment
article

GOBLIN: Prototype Architecture and Prospective Validation Roadmap for Clinician-Supervised Management of Auditory Verbal Hallucinations

Maria-Luiza Vladarean, Zaki Milhem, Roland Stretea, Alexandru Constantin Stan, Mara-Simina Olinic, Radu-George Bolborici, Alexandru-Florin Ene, Ana-Antonia Nicolae, Ioan-Andrei Bârsan, Rareș-Codrin Lache, Emanuela-Gabriela Hărăguș-Hațegan
article en

Abstract

Auditory verbal hallucinations are one of the most common symptoms in schizophrenia, contributing substantially to distress, functional impairment, and relapse risk. Existing therapeutic approaches, including pharmacological treatment and structured psychotherapies such as cognitive behavioral therapy for psychosis and AVATAR therapy, show promising clinical outcomes. However, scalability remains limited due to resource intensity and reliance on specialized personnel. Against this background, we describe the rationale, prototype architecture, and prospective validation roadmap for GOBLIN—a digital platform prototype combining personalized voice conversion, webcam-based eye-tracking, and large-language-model-assisted clinical documentation and decision support. The platform is intended to support clinician-supervised therapeutic workflows and between-visit monitoring following prospective validation. GOBLIN is intended to investigate whether an integrated digital workflow could address key limitations of current care models in schizophrenia and psychotic disorders, including fragmented follow-up, limited responsiveness to rapid symptom changes, and lack of scalable intervention tools. Our conceptual prototype is the first step toward leveraging the potential of digital, AI-driven platforms to complement existing treatment modalities and improve long-term management of psychosis-related symptoms. The system’s modules are intended for clinician-supervised research workflows and remain investigational. This manuscript does not report completed clinical validation, therapeutic efficacy, diagnostic performance, relapse-prediction performance, or validated safety outcomes. Such capabilities remain to be evaluated prospectively through staged technical, usability, safety, and clinical studies before clinical implementation can be considered.

InformaticsVol. 13(11)
University of Toronto (CA), Iuliu Hațieganu University of Medicine and Pharmacy (RO), Universitatea Națională de Știință și Tehnologie Politehnica București (RO), Technical University of Munich (DE)
Good health and well-being
Openalex Percentile: Top 12%
Schizophrenia research and treatment
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