The role of control groups in non-pharmacological randomised controlled trials of treatment-resistant schizophrenia: A systematic review and meta-analysis.

Control groups used in randomised controlled trials investigating psychological interventions for depression and anxiety disorders have effects of their own. This has never been investigated for schizophrenia, in particular treatment-resistant schizophrenia. This systematic review and meta-analysis aimed to examine how control groups in randomised controlled trials on psychological interventions for treatment-resistant schizophrenia behave in their effects on general symptomatology. In a search of various databases until July 2023, 31 eligible studies with 3125 participants were found whose control groups were assigned to four categories: active, inactive, treatment as usual and waitlist. The analyses showed that psychological interventions had a greater effect on symptom reduction to all control groups combined. When separating the control groups, only compared to TAU and waitlist controls the psychological interventions were superior. The difference was larger when less active control groups (e.g. waitlist - or treatment as usual control groups) were used. All control groups were associated with an improvement in symptoms from pre- to post-measurement point, with the greatest improvement observed in the inactive control group. The results are preliminary, but they suggest that the choice of the control group has a considerable impact on study effects as it has been shown in other psychiatric diagnoses.

Pilot study to test the feasibility and clinical efficacy of a psychosocial care programme for patients with psychosis in low-resource settings.

BACKGROUND: Home-based psychosocial care has the potential to improving outcomes in patients with schizophrenia and related disorders (SCZ). There is lack of India data for such care in early psychosis. We developed the "Saksham" programme, a bespoke self-managed home-based psychosocial care model, available in two formats: manual-based and mobile-application based. With the anticipated success of recruitment of early psychosis cases in our setting, we plan to test the such intervention in this population in future trials. AIM: To assess the feasibility of the Saksham programme intervention in people with SCZ and its clinical efficacy as an adjunct to treatment as usual. METHODS: Seventy-five patient-caregiver pairs (total n=150) were recruited. Patients received either: treatment-as-usual (TAU) (n=25), manual-based Saksham intervention+TAU (n=25), or app-based Saksham intervention+TAU (n=25). Feasibility (i.e. acceptability, practicality, demand, implementation and integration) was assessed at three-months. Participants were assessed for psychopathology, illness-severity, cognition, functioning, disability, and caregiver-coping at baseline, one-month, and three-month. The percentage changes over time were compared across three groups. RESULTS: More found the mobile application-based intervention acceptable and easy-to-use than the manual-based intervention (92 % vs 68 %, and 76 % vs 68 %, respectively). Psychopathology and caregiver-burden improved significantly in all three groups (p<0.05). Cognition, disability, functioning, and caregiver burden improved significantly in the two Saksham intervention groups, with greater improvement in the Saksham app group (p<0.05). CONCLUSION: Home-based intervention is feasible and acceptable in a low-resource setting, with preliminary evidence for effectiveness. These findings need corroboration with randomised controlled trials in early psychosis to ameliorate course of illness.

Association between the oral microbiome and brain resting state connectivity in schizophrenia.

Recent microbiome-brain axis findings have shown evidence of the modulation of microbiome community as an environmental mediator in brain function and psychiatric illness. This work is focused on the role of the microbiome in understanding a rarely investigated environmental involvement in schizophrenia (SZ), especially in relation to brain circuit dysfunction. We leveraged high throughput microbial 16s rRNA sequencing and functional neuroimaging techniques to enable the delineation of microbiome-brain network links in SZ. N = 213 SZ and healthy control subjects were assessed for the oral microbiome. Among them, 139 subjects were scanned by resting-state functional magnetic resonance imaging (rsfMRI) to derive brain functional connectivity. We found a significant microbiome compositional shift in SZ beta diversity (weighted UniFrac distance, p = 6 × 10-3; Bray-Curtis distance p = 0.021). Fourteen microbial species involving pro-inflammatory and neurotransmitter signaling and H2S production, showed significant abundance alterations in SZ. Multivariate analysis revealed one pair of microbial and functional connectivity components showing a significant correlation of 0.46. Thirty five percent of microbial species and 87.8 % of brain functional network connectivity from each component also showed significant differences between SZ and healthy controls with strong performance in classifying SZ from healthy controls, with an area under curve (AUC) = 0.84 and 0.87, respectively. The results suggest a potential link between oral microbiome dysbiosis and brain functional connectivity alteration in relation to SZ, possibly through immunological and neurotransmitter signaling pathways and the hypothalamic-pituitary-adrenal axis, supporting for future work in characterizing the role of oral microbiome in mediating effects on SZ brain functional activity.

Identifying differential predictors for treatment response to amisulpride and olanzapine combination treatment versus each monotherapy in acutely ill patients with schizophrenia: Results of the COMBINE-study.

BACKGROUND: Extensive research has been undertaken to predict treatment response (TR) to antipsychotics. Most studies address TR to antipsychotics in general and as monotherapy, however, it is unknown whether patients might respond favourably to a combination of antipsychotics. AIMS: This study aimed to identify differential predictors for TR to monotherapy with amisulpride or olanzapine compared to a combination of antipsychotics. METHODS: Post-hoc analysis was conducted of data collected from the COMBINE-study, a double-blind, randomized, controlled trial. Demographic and disease-related measures were gathered at baseline to predict TR after eight weeks defined by the Positive and Negative Syndrome Scale. Missing values were accounted for by a random replacement procedure. Attrition effects and multicollinearity were analysed and sets of logistic regression models were calculated for different treatment groups. RESULTS: Of the 321 randomized patients, 201 completed procedures until week eight and 197 were included in the analyses. For all treatment groups, early TR after two weeks and high subjective well-being under antipsychotics at baseline were robust predictors for TR. The propensity for early side effects also indicated a higher risk of later non-response. Specific parameter estimates were rather similar between treatment groups. CONCLUSION: Early TR, drug-related subjective well-being, and early side effect propensity evolved as predictors for later TR whether to monotherapy or combination strategy. Accordingly, due to a lack of differential predictors, early and close monitoring of targeted and unwanted effects is indicated to guide respective treatment decisions.

Trustworthiness judgments and pupil-size in individuals with schizophrenia.

Individuals with schizophrenia show aberrant processing of social cues. In the current study, we (1) compared trustworthiness ratings of faces between patients with schizophrenia and healthy controls, (2) compared pupillary reactivity between patients and controls (3) examined whether trustworthiness judgments in schizophrenia are related to pupil reactivity, (4) and examined associations between trustworthiness judgements and symptom severity, specifically paranoia. Patients with schizophrenia spectrum disorders (N = 48) and healthy controls (N = 33) completed a Trustworthiness Task, during which their pupil size was measured via an eye-tracking device. The mean baseline-corrected pupil size was calculated from 24 pictures of real neutral faces, each presented for 2500ms. Self-reported psychotic experiences were measured by Community Assessment of Psychic Functioning (CAPE-42), and symptom severity was rated by Brief Psychiatric Rating Scale (BPRS). No group differences were found in trustworthiness ratings or pupil reactivity parameters during trustworthiness judgments. Separately, among patients, absolute difference in pupil-size change and dilation after reaching minimum size were related to more severe positive symptoms and self-reported paranoia. Our results did not show social cognitive biases in the stable outpatients with schizophrenia, or the role of pupil reactivity in trustworthiness judgments. Future studies should use longer stimuli for pupillary reactivity and control the type and dosage of utilized antipsychotic medication. Further studies are required to explore relationships in larger and more symptomatic groups of patients.

A cognitive-behavioral treatment for suicide prevention among adults with schizophrenia spectrum disorders in community mental health: Study protocol for a pilot feasibility and acceptability randomized clinical trial.

BACKGROUND: Suicide is among the leading causes of death for adults with schizophrenia spectrum disorders (SSDs), and there is a paucity of evidence-based suicide prevention-focused interventions tailored for this vulnerable population. Cognitive-Behavioral Suicide Prevention for psychosis (CBSPp) is a promising intervention developed in the UK that required modifications for delivery in community mental health (CMH) settings in the United States of American. This pilot trial evaluates the feasibility, acceptability, and preliminary effectiveness of our modified CBSPp intervention in comparison to services as usual (SAU) within a CMH setting in a Midwestern state of the USA. METHODS: This is a single-site randomized pilot trial with a planned enrollment of 60 adults meeting criteria for both SSD and SI/A. Eligible participants will be randomized 1:1 to either 10 sessions of CBSPp or SAU. Clinical and cognitive assessments will be conducted within a 4-waive design at baseline (prior to randomization and treatment) and approximately 1 month (mid-treatment), 3 months (post-treatment), and 5 months (follow-up) after baseline assessment. Qualitative interviews will also be conducted at post-treatment. The primary objective is to determine whether CBSPp is feasible and acceptable, involving examinations of recruitment rate, treatment engagement and adherence, retention and completion rates, and experiences in the CBSPp treatment and overall study. The secondary objective is to preliminarily evaluate whether modified CBSPp is associated with reductions in clinical (suicide ideation, suicide attempt, symptoms of psychosis, depression, and emergency/hospital service, hopelessness, defeat, and entrapment) and cognitive (information processing biases, appraisals, and schemas) outcomes in comparison to SAU from baseline to post-treatment assessment. DISCUSSION: This randomized pilot trial will provide clinically relevant information about whether CBSPp can improve SI/A, depression, and psychosis among adults with SSDs. Testing this modified cognitive-behavioral suicide prevention-focused intervention has the potential for a large public health impact by increasing the intervention's utility and usability in CMH where many individuals with SSDs receive care, and ultimately working towards reductions in premature suicide death. TRIAL REGISTRATION: ClinicalTrials.gov NCT#05345184. Registered on April 12, 2022.

Wavelet Transform, Reconstructed Phase Space, and Deep Learning Neural Networks for EEG-Based Schizophrenia Detection.

This study proposes an innovative expert system that uses exclusively EEG signals to diagnose schizophrenia in its early stages. For diagnosing psychiatric/neurological disorders, electroencephalogram (EEG) testing is considered a financially viable, safe, and reliable alternative. Using the reconstructed phase space (RPS) and the continuous wavelet transform, the researchers maximized the differences between the EEG nonstationary signals of normal and schizophrenia individuals, which cannot be observed in the time, frequency, or time-frequency domains. This reveals significant information, highlighting more distinguishable features. Then, a deep learning network was trained to enhance the accuracy of the resulting image classification. The algorithm's efficacy was confirmed through three distinct methods: employing 70% of the dataset for training, 15% for validation, and the remaining 15% for testing. This was followed by a 5-fold cross-validation technique and a leave-one-out classification approach. Each method was iterated 100 times to ascertain the algorithm's robustness. The performance metrics derived from these tests - accuracy, precision, sensitivity, F1 score, Matthews correlation coefficient, and Kappa - indicated remarkable outcomes. The algorithm demonstrated steady performance across all evaluation strategies, underscoring its relevance and reliability. The outcomes validate the system's accuracy, precision, sensitivity, and robustness by showcasing its capability to autonomously differentiate individuals diagnosed with schizophrenia from those in a state of normal health.

The longitudinal course of psychological distress and resilience in patients with serious mental illnesses during the first two years of the Covid-19 pandemic.

The positive effects of resilience on psychological distress has been found in previous studies in samples not including the seriously mentally ill. The present study aimed to investigate the course of psychological distress and resilience in the first two years of the Covid-19 pandemic in patients with severe mental illness (SMI) and major depressive disorder without psychotic features (MDD) compared to healthy control subjects. 141 patients with SMI or MDD who had been admitted to a psychiatric ward in Tyrol (Austria) or South Tyrol (Italy) in 2019 and 584 community controls participated in a longitudinal online survey. Next to collecting sociodemographic data, psychological distress was evaluated using the Brief Symptom Checklist (BSCL) and resilience by the 13-Item Resilience Scale (RS-13). Psychological distress was consistently significantly higher while resilience was consistently significantly lower among both patient groups compared to healthy controls. In the patient samples, those with MDD consistently exhibited a significantly higher prevalence and level of psychological distress and significantly lower resilience. Resilience had a moderating effect on psychological distress especially in the MDD group. Our results suggest that MDD patients represent a particularly vulnerable group and findings imply that these patients would profit the most from trainings fostering resilience.

Media Use and Its Associations With Paranoia in Schizophrenia and Bipolar Disorder: Ecological Momentary Assessment.

Background: Paranoia is a spectrum of fear-related experiences that spans diagnostic categories and is influenced by social and cognitive factors. The extent to which social media and other types of media use are associated with paranoia remains unclear. Objective: We aimed to examine associations between media use and paranoia at the within- and between-person levels. Methods: Participants were 409 individuals diagnosed with schizophrenia spectrum or bipolar disorder. Measures included sociodemographic and clinical characteristics at baseline, followed by ecological momentary assessments (EMAs) collected 3 times daily over 30 days. EMA evaluated paranoia and 5 types of media use: social media, television, music, reading or writing, and other internet or computer use. Generalized linear mixed models were used to examine paranoia as a function of each type of media use and vice versa at the within- and between-person levels. Results: Of the 409 participants, the following subgroups reported at least 1 instance of media use: 261 (63.8%) for using social media, 385 (94.1%) for watching TV, 292 (71.4%) for listening to music, 191 (46.7%) for reading or writing, and 280 (68.5%) for other internet or computer use. Gender, ethnoracial groups, educational attainment, and diagnosis of schizophrenia versus bipolar disorder were differentially associated with the likelihood of media use. There was a within-person association between social media use and paranoia: using social media was associated with a subsequent decrease of 5.5% (fold-change 0.945, 95% CI 0.904-0.987) in paranoia. The reverse association, from paranoia to subsequent changes in social media use, was not statistically significant. Other types of media use were not significantly associated with paranoia. Conclusions: This study shows that social media use was associated with a modest decrease in paranoia, perhaps reflecting the clinical benefits of social connection. However, structural disadvantage and individual factors may hamper the accessibility of media activities, and the mental health correlates of media use may further vary as a function of contents and contexts of use.

Computer modeling of the peculiarities in the interaction of IL-1 with its receptors in schizophrenia.

One of the primary theories regarding the development of schizophrenia revolves around genetics, indicating the involvement of hereditary factors in various processes, including inflammation. Research has demonstrated that inflammatory reactions occurring in microglia can impact the progression of the disease. It has also been established that genetically determined changes in IL-1 can contribute to schizophrenia, thereby confirming the role of the IL-1 gene cluster in disease susceptibility. The aim of this study is a computer-based assessment of the structural interactions of IL-1 proteins with their receptors in schizophrenia. The study utilized the DisGeNET database, enabling the assessment of the reliability of identified IL-1 polymorphisms. Polymorphisms were also sought using NCBI PubMed. The NCBI Protein service was employed to search for and analyze the position of the identified polymorphisms on the chromosome. Structures for modeling were extracted from the Protein Data Bank database. Protein modeling was conducted using the SWISS-MODEL server, and protein interaction modeling was performed using PRISM. Notably, this study represents the first prediction of the interactions of IL-1α, IL-1ß, and IL- 1RA proteins, taking into account the presence of single-nucleotide polymorphisms associated with schizophrenia in the sequence of the corresponding genes. The results indicate that the presence of SNP rs315952 in the IL-1RA protein gene, associated with schizophrenia, may lead to a weakening of the IL-1RA binding to receptors, potentially triggering the initiation of the IL-1 signaling pathway by disrupting or weakening the IL-1RA binding to receptors and facilitating the binding of IL-1 to them. Such alterations could potentially lead to a change in the immune response. The data obtained contribute theoretically to the development of ideas about the molecular mechanisms through which hereditary factors in schizophrenia influence the interactions of proteins of the IL-1 family, which play an important role in the processes of the immune system.

Psychosis and help-seeking behaviour-A systematic review of the literature.

PURPOSE: Many people with psychosis do not seek help which delays access to recommended treatments. Duration of untreated psychosis is associated with poor healthcare outcomes and increased risk of relapse. The reasons why people delay accessing treatment remain unclear. This is the first systematic review to synthesise the literature examining professional and non-professional help-seeking in psychosis across clinical and subclinical populations. METHODS: We searched four databases (APA PsycINFO, APA PsycArticles, Medline and British Library EThOS) to generate a comprehensive account of the quantitative literature. Heterogeneity of measures precluded a meta-analysis. RESULTS: We identified 19 articles (including 9686 participants) that met criteria for the review. Help-seeking in psychosis is associated with being female, having a higher level of education, and experiencing more than one symptom. People with psychosis report stigma, poor mental health literacy and lack of family support as key barriers. Clinicians report childhood physical abuse, insecure attachment and severity of psychosis as additional barriers. We also found differences in preferred sources of help across cultures. There is currently no consensus on reliable help-seeking measures. CONCLUSIONS: This is the first systematic review to examine help-seeking behaviour in psychosis. Assertive and culturally sensitive engagement efforts should be targeted towards people with a history of early adversity, poor mental health literacy, limited social support and more severe psychosis.

Therapeutic potential of transient receptor potential (TRP) channels in psychiatric disorders.

Psychiatric disorders such as Bipolar disorder, Anxiety, Major depressive disorder, Schizophrenia, Attention-deficit/hyperactivity disorder, as well as neurological disorders such as Migraine, are linked by the evidence of altered calcium homeostasis. The disturbance of intra-cellular calcium homeostasis disrupts the activity of numerous ion channels including transient receptor potential (TRP) channels. TRP channel families comprise non-selective calcium-permeable channels that have been implicated in variety of physiological processes in the brain, as well as in the pathogenesis of psychiatric disorders. Through a comprehensive review of current research and experimentation, this investigation elucidates the role of TRP channels in psychiatric disorders. Furthermore, this review discusses about the exploration of epigenetics and TRP channels in psychiatric disorders.

Association between reduced plasma BDNF concentration and MMSE scores in both chronic schizophrenia and mild cognitive impairment.

Reduced brain derived neurotrophic factor (BDNF) concentration is reported to be associated with a cognitive decline in schizophrenia, depending on the stage of the disease. Aim of the study was to examine the possible association between plasma BDNF and cognitive decline in chronic stable schizophrenia and mild cognitive impairment (MCI). The study included 123 inpatients of both sexes with schizophrenia, 123 patients with MCI and 208 healthy control subjects. Cognitive abilities were assessed using mini mental state examination (MMSE), Clock Drawing test (CDT) and cognitive subscale of the Positive and Negative Syndrome Scale (PANSS). Plasma BDNF concentration was determined using ELISA. BDNF concentration was lower in patients with schizophrenia and MCI compared to age-matched healthy controls and was similar in carriers of different BDNF Val/66Met genotypes. The MMSE and CDT scores were lower in patients with schizophrenia compared to healthy controls and subjects with MCI. Reduced plasma BDNF was significantly associated with lower MMSE scores in all subjects. BDNF concentration in patients with schizophrenia was not affected by clinical and demographic factors. BDNF Val66Met polymorphism was not associated with the MMSE scores in all participants. Further studies should include longitudinal follow-up and other cognitive scales to confirm these results and offer cognition-improving strategies to prevent cognitive decline in chronic schizophrenia.

Role of different omics data in the diagnosis of schizophrenia disorder: A machine learning study.

Schizophrenia is a serious mental disorder that affects millions of people worldwide. This disorder slowly disintegrates thinking ability and changes behaviours of patients. These patients will show some psychotic symptoms such as hallucinations, delusions, thought disorder and movement disorder. These symptoms are in common with some other psychiatric disorders such as bipolar disorder, major depressive disorder and mood spectrum disorder. As patients would require immediate treatment, an on-time diagnosis is critical. This study explores the use of omics data in diagnosis of schizophrenia. Transcriptome, miRNA and epigenome data are used in diagnosis of patients with schizophrenia with the aid of machine learning algorithms. As the data is in high dimension, mutual information and feature importance are independently used for selecting relevant features for the study. Selected sets of features (biomarkers) are individually used with different machine learning algorithms and their performances are compared to select the best-performing model. This study shows that the top 140 miRNA features selected using mutual information along with support vector machines give the highest accuracy (0.86 ± 0.07) in the diagnosis of schizophrenia. All reported accuracies are validated using 5-fold cross validation. They are further validated using leave one out cross validation and the accuracies are reported in the supplementary material.

Aberrant brain functional connectivity mediates the effects of negative symptoms on cognitive function in schizophrenia: A structural equation model.

BACKGROUND: Schizophrenia is a severe psychiatric disorder, characterized by positive symptoms, negative symptoms, and cognitive deficits. Elucidating the mechanism of negative symptom and cognitive deficits could contribute to the treatment and prognosis of schizophrenia. We hypothesized that abnormal functional connectivity would be involved in the indirect effects of negative symptoms on cognitive function. METHODS: A total of 150 schizophrenia male patients and 108 healthy controls matched for age, education and gender were enrolled in the study. The scores of Brief Negative Symptom Scale were divided into two factors: motivation and pleasure deficits (MAP) and diminished expression (EXP). Subsequently, a series of classic neurocognitive tests were used to evaluate cognitive functions. Resting-state fMRI data was collected from all participants. The Anatomical Automatic Labeling template was employed to establish regions of interest, thereby constructing the functional connectivity network across the entire brain. Eventually, scores of patients' negative symptoms scale, cognitive function, and strengths of abnormal functional connectivity were incorporated into a structural equation model to explore the interactions among variables. RESULTS: MAP exhibited a distinctly and significantly negative impact on cognitive function. The functional connectivity between the left insula and left precuneus, along with that between the left precuneus and right angular gyrus, collectively served as intermediaries, contributing to the indirect effects of MAP and EXP on cognitive function. CONCLUSIONS: Our findings demonstrated the moderating role of aberrant brain functional connectivity between negative symptoms and cognitive function, providing clues about the neural correlates of negative symptoms and cognitive deficits in schizophrenia.

Molecular evidence of altered stress responsivity related to neuroinflammation in the schizophrenia midbrain.

Stress and inflammation are risk factors for schizophrenia. Chronic psychosocial stress is associated with subcortical hyperdopaminergia, a core feature of schizophrenia. Hyperdopaminergia arises from midbrain neurons, leading us to hypothesise that changes in stress response pathways may occur in this region. To identify whether transcriptional changes in glucocorticoid and mineralocorticoid receptors (NR3C1/GR, NR3C2/MR) or other stress signalling molecules (FKBP4, FKBP5) exist in schizophrenia midbrain, we measured gene expression in the human brain (N = 56) using qRT-PCR. We assessed whether alterations in these mRNAs were related to previously identified high/low inflammatory status. We investigated relationships between stress-related transcripts themselves, and between FKBP5 mRNA, dopaminergic, and glial cell transcripts in diagnostic and inflammatory subgroups. Though unchanged by diagnosis, GR mRNA levels were reduced in high inflammatory compared to low inflammatory schizophrenia cases (p = 0.026). We found no effect of diagnosis or inflammation on MR mRNA. FKBP4 mRNA was decreased and FKBP5 mRNA was increased in schizophrenia (p < 0.05). FKBP5 changes occurred in high inflammatory (p < 0.001), whereas FKBP4 changes occurred in low inflammatory schizophrenia cases (p < 0.05). The decrease in mRNA encoding the main stress receptor (GR), as well as increased transcript levels of the stress-responsive negative regulator (FKBP5), may combine to blunt the midbrain response to stress in schizophrenia when neuroinflammation is present. Negative correlations between FKBP5 mRNA and dopaminergic transcripts in the low inflammatory subgroup suggest higher levels of FKBP5 mRNA may also attenuate dopaminergic neurotransmission in schizophrenia even when inflammation is absent. We report alterations in GR-mediated stress signalling in the midbrain in schizophrenia.

Detecting outliers in case-control cohorts for improving deep learning networks on Schizophrenia prediction.

This study delves into the intricate genetic and clinical aspects of Schizophrenia, a complex mental disorder with uncertain etiology. Deep Learning (DL) holds promise for analyzing large genomic datasets to uncover new risk factors. However, based on reports of non-negligible misdiagnosis rates for SCZ, case-control cohorts may contain outlying genetic profiles, hindering compelling performances of classification models. The research employed a case-control dataset sourced from the Swedish populace. A gene-annotation-based DL architecture was developed and employed in two stages. First, the model was trained on the entire dataset to highlight differences between cases and controls. Then, samples likely to be misclassified were excluded, and the model was retrained on the refined dataset for performance evaluation. The results indicate that SCZ prevalence and misdiagnosis rates can affect case-control cohorts, potentially compromising future studies reliant on such datasets. However, by detecting and filtering outliers, the study demonstrates the feasibility of adapting DL methodologies to large-scale biological problems, producing results more aligned with existing heritability estimates for SCZ. This approach not only advances the comprehension of the genetic background of SCZ but also opens doors for adapting DL techniques in complex research for precision medicine in mental health.

Cognitive Behavioral Psychotherapy as an Add-on in Comprehensive Outpatient Care of Non-affective Psychoses: A Multicenter Randomized-Controlled Effectiveness Trial in a Naturalistic Setting.

BACKGROUND AND HYPOTHESIS: Non-affective psychoses (NAP) are associated with severe consequences with regard to social functioning, physical health, employment, and suicidality. Treatment guidelines recommend cognitive behavioral therapy for psychosis (CBTp) as an effective additional treatment strategy to psychopharmacology. We hypothesized that outpatient CBTp has an add-on effect in individuals with NAP who already receive comprehensive outpatient care (COC) in Germany. STUDY DESIGN: In a randomized-controlled effectiveness trial, 6 months of COC + CBTp were compared to COC. The primary outcomes were change of symptom severity as assessed by the Positive and Negative Symptom Scale (pre-/post-treatment and 6-month follow-up). Mixed linear models and effect sizes were used to compare changes across treatment groups. Additionally, the number of readmissions was compared. STUDY RESULTS: N = 130 individuals with chronic NAP were recruited (COC + CBTp: n = 64, COC: n = 66). COC + CBTp participants significantly improved more regarding positive symptom severity (estimated mean difference at follow-up: -2.33, 95% CI: -4.04 to -0.61, P = .0083, d = 0.32) and general psychopathology (estimated mean difference at follow-up: -4.55, 95% CI: -7.30 to -1.81, P = .0013, d = 0.44) than the COC group. In both groups, negative symptom severity did not change significantly over time nor did groups differ regarding readmissions. CONCLUSION: The results underline an add-on benefit of CBTp in chronically ill individuals with NAP. Superiority of CBTp was demonstrated in comparison with high-quality comprehensive care and may also be true in different comprehensive care settings. CLINICAL TRIALS REGISTRATION: DRKS00015627.