Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
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Journal of psychiatric research
Predicting treatment response in psychosis using fMRI: A comprehensive review
In recent years, the use of functional Magnetic Resonance Imaging (fMRI) methods to predict treatment response in schizophrenia (SCZ) through statistical and machine learning (ML) algorithms has increased. We conducted a comprehensive literature review to assess the role of various fMRI measures in predicting pharmacological treatment response in psychosis. Literature available on PubMed from January 1990 to December 2023 was reviewed, and 21 fMRI studies were included. The results suggest that many studies have employed ML techniques, which may enhance the accuracy of treatment outcome predictions. Additionally, several studies utilizing resting-state fMRI have identified potential associations of functional connectivity patterns across multiple large-scale networks, including the default mode network (DMN), the salience network (SN), the central executive network (CEN), and sensory-motor circuits. These findings suggest that altered connectivity within and between these networks may be relevant for personalized treatment strategies in patients with psychosis, although further investigation is needed to confirm their predictive value. Future research should focus on developing robust and generalizable models to more reliably optimize treatment outcomes in psychosis.
5 May 2026
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Treatment effect modifiers of virtual reality-based versus standard cognitive behavioral therapy for paranoia in schizophrenia spectrum disorders: an exploratory moderator analysis of clinical and demographic characteristics in the FaceYourFears trial
BACKGROUND: This exploratory study examined baseline characteristics modifying treatment effects on paranoia in individuals diagnosed with schizophrenia spectrum disorders following a 10-session virtual reality-based cognitive behavioral therapy for psychosis (VR-CBTp) or standard CBTp. METHODS: All participants in the FaceYourFears trial were included (n=254; CBTp n=128; VR-CBTp n=126). General linear and logistic regression models examined baseline variables associated with end-of-treatment paranoia. In covariate analyses, regression coefficients quantified associations across treatments. In moderation analyses, interaction terms (randomization x moderator) were tested, with corresponding regression coefficients estimated and assessed at the 25th (low), 50th (medium), and 75th (high) percentiles of continuous variables. RESULTS: Across treatments, higher baseline avolition, safety behavior, delusion severity, and cognitive biases were associated with end-of-treatment paranoia. Moderation analyses revealed interactions for avolition, delusion severity, and negative other-beliefs. Although avolition and delusion severity were associated with poorer outcomes overall, individuals with high avolition and those with moderate-to-high delusion severity improved more in VR-CBTp than CBTp, whereas participants with lower delusion severity showed better outcomes in CBTp. No demographic (age, gender, education, and occupation) or other clinical characteristics (diagnosis, paranoia, social anxiety, depression, anhedonia, total negative symptoms, functioning, core beliefs, or interpersonal trauma) were significantly associated with outcome. CONCLUSIONS: This exploratory study generates hypotheses for future research, including VR-CBTp's potential to engage individuals with high avolition. Given the modest effects and largely nonsignificant findings, both CBTp and VR-CBTp appear suitable for a wide range of individuals with paranoia, highlighting the importance of considering patient preferences.
2 May 2026
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