A principle‐based framework for disclosing a psychosis risk diagnosis. (9th November 2022)

• Record Type: Journal Article
• Authors: Zhang, Oliver Y.; McConnell, Doug; Carter, Adrian; Pugh, Jonathan
• Is Part Of: Bioethics. Volume 37:Number 2(2023)
• Page Start: 171
• Page End: 182
• Publication Date: 2022-11-09
• Subjects: at‐risk mental state -- autonomy -- diagnosis -- disclosure -- psychosis risk -- ultra‐high risk; Bioethics -- Periodicals; 174.957
• DOI: 10.1111/bioe.13106
• Languages: English
• ISSNs: 0269-9702

Abstract

Abstract: In recent decades, researchers have attempted to prospectively identify individuals at high risk of developing psychosis in the hope of delaying or preventing psychosis onset. These psychosis risk individuals are identified as being in an 'At‐Risk Mental State' (ARMS) through a standardised psychometric interview. However, disclosure of ARMS status has attracted criticism due to concerns about the risk–benefit ratio of disclosure to patients. Only approximately one quarter of ARMS patients develop psychosis after three years, raising concerns about the unnecessary harm associated with such 'false‐positive' results. These harms are especially pertinent when identifying psychosis risk individuals due to potential stigma and discrimination in a young clinical population. A dearth of high‐quality evidence supporting interventions for ARMS patients raises further doubts about the benefit accompanying an ARMS disclosure. Despite ongoing discussion in the bioethical literature, these concerns over the ethical justification of disclosure to ARMS patients are not directly addressed in clinical guidelines. In this paper, we aim to provide a unified disclosure strategy grounded in principle‐based analysis for ARMS clinicians. After considering the ethical values at stake in ARMS disclosure, and their normative significance, we argue that full disclosure of the ARMS label is favoured in the vast majority of clinical situations due to the strong normative significance of enhancing patients' understanding. We then compare our framework with other approaches to ARMS disclosure and outline its limitations.