Measuring Voluntary Control Over Hallucinations: The Yale Control Over Perceptual Experiences (COPE) Scales

Auditory verbal hallucinations (AVH) frequently cause significant distress and dysfunction, and may be unresponsive to conventional treatments. Some voice-hearers report an ability to fully control the onset and offset of their AVH, making them significantly less disruptive. Measuring and understanding these abilities may lead to novel interventions to enhance control over AVH. 52 voice-hearers participated in the pilot study. 318 participants with frequent AVH participated in the validation study. A pool of 59 items was developed by a diverse team including voice-hearers and clinicians. After the pilot study, 35 items were retained. Factorial structure was assessed with exploratory (EFA, n = 148) and confirmatory (CFA, n = 170) factor analyses. Reliability and convergent validity were assessed using a comprehensive battery of validated phenomenological and clinical scales. CFA supported two factors for a Methods of Control Scale (5 items each, average ω = .87), and one factor for a Degree of Control Scale (8 items, average ω = .95). Correlation with clinical measures supported convergent validity. Degree of control was associated with positive clinical outcomes in voice-hearers both with and without a psychosis-spectrum diagnosis. Degree of control also varied with quality of life independently of symptom severity and AVH content. The Yale COPE Scales are the first measure of voice-hearers’ control over AVH and exhibit sound psychometric properties. Results demonstrate that the capacity to voluntarily control AVH is independently associated with positive clinical outcomes. Reliable measurement of control over AVH will enable future development of interventions meant to bolster that control

Measuring Voluntary Control Over Hallucinations: The Yale Control Over Perceptual Experiences (COPE) Scales

Auditory verbal hallucinations (AVH) frequently cause significant distress and dysfunction, and may be unresponsive to conventional treatments. Some voice-hearers report an ability to fully control the onset and offset of their AVH, making them significantly less disruptive. Measuring and understanding these abilities may lead to novel interventions to enhance control over AVH. Fifty-two voice-hearers participated in the pilot study. 318 participants with frequent AVH participated in the validation study. A pool of 59 items was developed by a diverse team including voice-hearers and clinicians. After the pilot study, 35 items were retained. Factorial structure was assessed with exploratory (EFA, n = 148) and confirmatory (CFA, n = 170) factor analyses. Reliability and convergent validity were assessed using a comprehensive battery of validated phenomenological and clinical scales. CFA on the final 18 items supported two factors for a Methods of Control Scale (5 items each, average omega = .87), and one factor for a Degree of Control Scale (8 items, average omega = .95). Correlation with clinical measures supported convergent validity. Degree of control was associated with positive clinical outcomes in voice-hearers both with and without a psychosis-spectrum diagnosis. Degree of control also varied with quality of life independently of symptom severity and AVH content. The Yale control over perceptual experiences (COPE) Scales robustly measure voice-hearers' control over AVH and exhibit sound psychometric properties. Results demonstrate that the capacity to voluntarily control AVH is independently associated with positive clinical outcomes. Reliable measurement of control over AVH will enable future development of interventions meant to bolster that control

Conditioned Hallucinations and Prior Overweighting Are State-Sensitive Markers of Hallucination Susceptibility

Background Recent advances in computational psychiatry have identified latent cognitive and perceptual states that predispose to psychotic symptoms. Behavioral data fit to Bayesian models have demonstrated an overreliance on priors (i.e., prior overweighting) during perception in select samples of individuals with hallucinations, corresponding to increased precision of prior expectations over incoming sensory evidence. However, the clinical utility of this observation depends on the extent to which it reflects static symptom risk or current symptom state. Methods To determine whether task performance and estimated prior weighting relate to specific elements of symptom expression, a large, heterogeneous, and deeply phenotyped sample of hallucinators (n = 249) and nonhallucinators (n = 209) performed the conditioned hallucination (CH) task. Results We found that CH rates predicted stable measures of hallucination status (i.e., peak frequency). However, CH rates were more sensitive to hallucination state (i.e., recent frequency), significantly correlating with recent hallucination severity and driven by heightened reliance on past experiences (priors). To further test the sensitivity of CH rate and prior weighting to symptom severity, a subset of participants with hallucinations (n = 40) performed a repeated-measures version of the CH task. Changes in both CH frequency and prior weighting varied with changes in auditory hallucination frequency on follow-up. Conclusions These results indicate that CH rate and prior overweighting are state markers of hallucination status, potentially useful in tracking disease development and treatment response

Structural and functional brain patterns predict formal thought disorder’s severity and its persistence in recent-onset psychosis:Results from the PRONIA Study

Background: Formal thought disorder (FThD) is a core feature of psychosis, and its severity and long-term persistence relates to poor clinical outcomes. However, advances in developing early recognition and management tools for FThD are hindered by a lack of insight into the brain-level predictors of FThD states and progression at the individual level. Methods: 233 individuals with recent-onset psychosis were drawn from the multi-site European Prognostic Tools for Early Psychosis Management study. Support vector machine classifiers were trained within a cross-validation framework to separate two FThD symptom-based subgroups (high vs. low FThD severity), using cross-sectional whole-brain multi-band fractional amplitude of low frequency fluctuations (fALFF), gray-matter volume (GMV) and white-matter volume (WMV) data. Moreover, we trained machine learning models on these neuroimaging readouts to predict the persistence of high FThD subgroup membership from baseline to 1-year follow-up. Results: Cross-sectionally, multivariate patterns of GMV within the salience, dorsal attention, visual and ventral attention networks separated the FThD severity subgroups (BAC=60.8%). Longitudinally, distributed activations/deactivations within all fALFF sub-bands (BACslow-5=73.2%, BACslow-4=72.9%, BACslow-3=68.0), GMV patterns overlapping with the cross-sectional ones (BAC=62.7%) and smaller frontal WMV (BAC=73.1%) predicted the persistence of high FThD severity from baseline to follow-up, with a combined multi-modal balanced accuracy of BAC=77%. Conclusions: We report first evidence of brain structural and functional patterns predictive of FThD severity and persistence in early psychosis. These findings open the avenue for the development of neuroimaging-based diagnostic, prognostic and treatment options for the early recognition and management of FThD and associated poor outcomes