The voice characterisation checklist: psychometric properties of a brief clinical assessment of voices as social agents
Year: 2023
Type: article
Abstract: Aim There is growing interest in tailoring psychological interventions for distressing voices and a need for reliable tools to assess phenomenological features which might influence treatment response. This study examines the reliability and internal consistency of the Voice Characterisation Checklist (VoCC), a novel 10-item tool which assesses degree of voice characterisation, identified as relevant to a new wave of relational approaches. Methods The sample comprised participants experiencing distressing voices, recruited at baseline on the AVATAR2 trial between January 2021 and July 2022 (n = 170). Inter-rater reliability (IRR) and internal consistency analyses (Cronbach’s alpha) were conducted. Results The majority of participants reported some degree of voice personification (94%) with high endorsement of voices as distinct auditory experiences (87%) with basic attributes of gender and age (82%). While most identified a voice intention (75%) and personality (76%), attribution of mental states (35%) to the voice (‘What are they thinking?’) and a known historical relationship (36%) were less common. The internal consistency of the VoCC was acceptable (10 items, α = 0.71). IRR analysis indicated acceptable to excellent reliability at the item-level for 9/10 items and moderate agreement between raters’ global (binary) classification of more vs. less highly characterised voices, κ = 0.549 (95% CI, 0.240–0.859), p < 0.05. Conclusion The VoCC is a reliable and internally consistent tool for assessing voice characterisation and will be used to test whether voice characterisation moderates treatment outcome to AVATAR therapy. There is potential wider utility within clinical trials of other relational therapies as well as routine clinical practice.
Source: Frontiers in Psychiatry
Institutions: King's College London, South London and Maudsley NHS Foundation Trust, Ruhr University Bochum, NHS Greater Glasgow and Clyde, University of Glasgow, North East London NHS Foundation Trust, University College London, Greater Manchester Mental Health NHS Foundation Trust, Manchester Academic Health Science Centre, University of Manchester
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,295
Awards: G1412918328, Optimising AVATAR therapy for distressing voices: a multi-centre randomised controlled trial, Optimising AVATAR therapy for distressing voices: a multi-centre randomised controlled trial, Digital solutions for people with severe mental health problems, Design and analysis of efficient randomised trials in mental health, NIHR Senior Investigator Award
OpenAlex ID: W4385069025
