Qatar's National Mental Health Study-The World Mental Health Qatar.

BACKGROUND: We provide an overview of Qatar's first epidemiological study on prevalence, predictors, and treatment contact for mood and anxiety disorders. AIMS: We highlight the importance of the three-pronged study, its aims, and its key components. MATERIALS & METHODS: The first component comprised a probability-based representative survey of Qatari and non-Qatari (Arab) adult males and females recruited from the general population and interviewed using the International Diagnostic Interview (CIDI version 3.3). The second component, a clinical reappraisal study, assessed concordance between diagnoses based on the CIDI and independent clinical assessments conducted by trained clinical interviewers. The third component comprised a resting-state functional magnetic resonance imaging study of healthy survey respondents who were matched to patients with psychosis. RESULTS: 5000 survey interviews provided data on prevalence and treatment of common mental disorders. Clinical re-interviews (N = 485) provided important diagnostic validity data. Finally, state-of-the art structural and functional brain markers for psychosis were also collected (N = 100). DISCUSSION: Descriptive epidemiological data were collected to inform future mental health priorities in Qatar and situates these within a global context. CONCLUSION: The study fills important gaps in regional and global estimates and establish necessary baseline to develop comprehensive risk estimates for mental health in Qatar's young population.

ZO-1 Serum Levels as a Potential Biomarker for Psychotic Disorder.

OBJECTIVE: There are limited studies in the literature on the relationship between intestinal and blood-brain barrier permeability and the etiology of schizophrenia. We hypothesized that the difference in serum ZO-1 levels in patients with schizophrenia may affect the severity of the disease. The aim of this study was to investigate the role of changes in serum ZO-1 concentrations in the etiopathogenesis of patients with schizophrenia. METHODS: A total of 46 patients, 34 with schizophrenia, 12 with a first psychotic attack, and 37 healthy controls, were included in the study. Symptom severity was determined by applying the Positive and Negative Syndrome Scale and the Clinical Global Impression-Severity Scale. Serum ZO-1 levels were measured from venous blood samples. RESULTS: Serum ZO-1 levels were higher in patients with psychotic disorder compared to healthy controls. There was no statistically significant difference between the groups in the first psychotic attack group and the schizophrenia patients. There was a statistically significant positive correlation between serum ZO-1 levels and Positive and Negative Syndrome Scale positive symptom score. CONCLUSIONS: These findings regarding ZO-1 levels suggest that dysregulation of the blood-brain barrier in psychotic disorder may play a role in the etiology of the disorder.

Acceptability and experience of a smartphone symptom monitoring app for people with psychosis in China (YouXin): a qualitative study.

BACKGROUND: Access to high-quality mental healthcare remains challenging for people with psychosis globally, including China. Smartphone-based symptom monitoring has the potential to support scalable mental healthcare. However, no such tool, until now, has been developed and evaluated for people with psychosis in China. This study investigated the acceptability and the experience of using a symptom self-monitoring smartphone app (YouXin) specifically developed for people with psychosis in China. METHODS: Semi-structured interviews were conducted with 10 participants with psychosis to explore the acceptability of YouXin. Participants were recruited from the non-randomised feasibility study that tested the validity, feasibility, acceptability and safety of the YouXin app. Data analysis was guided by the theoretical framework of acceptability. RESULTS: Most participants felt the app was acceptable and easy to use, and no unbearable burdens or opportunity costs were reported. Participants found completing the self-monitoring app rewarding and experienced a sense of achievement. Privacy and data security were not major concerns for participants, largely due to trust in their treating hospital around data protection. Participants found the app easy to use and attributed this to the training provided at the beginning of the study. A few participants said they had built some form of relationship with the app and would miss the app when the study finished. CONCLUSIONS: The YouXin app is acceptable for symptom self-monitoring in people with experience of psychosis in China. Participants gained greater insights about their symptoms by using the YouXin app. As we only collected retrospective acceptability in this study, future studies are warranted to assess hypothetical acceptability before the commencement of study to provide a more comprehensive understanding of implementation.

An Open Conversation About Postpartum Psychosis: An Interview with Jessie Hunt: Communications Lead, Advocate, and Expert by Experience.

Postpartum psychosis is a mental illness that is often misunderstood and stigmatized and can have a devastating impact on the women affected and their families, particularly when not identified and treated early on. The first-person perspective of experiencing a mental illness such as postpartum psychosis is remarkably powerful and can shed light on some of the hidden or misunderstood aspects of diagnosis, treatment, recovery, and getting support. With this in mind, we have prepared this interview from both an academic and lived experience perspective of postpartum psychosis, for clinicians, academics, mental health professionals, and members of the public.

Beyond imagination: Sorting out and treating psychosis in the context of autism spectrum disorder.

In the last decades, growing caseness for Autism Spectrum Disorder (ASD) has been observed, owing to the diagnostic accretion of low-impairment forms, over and above other possible causes. Unrecognized ASD is likely to be mislabeled as a psychotic disorder (PD), as people in the spectrum may show 'pseudopsychotic' symptoms, resembling both negative and positive symptoms. On the other hand, PDs are likely to be overlooked when they arise in people with ASD, due to the 'diagnostic overshadowing' of new-onset conditions by lifelong core autistic symptoms. The three available metanalyses on the occurrence of psychosis in adults with ASD convergently reported a rate of PDs that is at least ten times higher than in the general population. Therefore, the lack of literature addressing risk factors, outcomes, and treatment options for psychosis in the context of ASD is utterly concerning. The present review aims to summarize up-to-date knowledge of PDs with comorbid ASD in terms of clinical features, course, and treatment.

A Novel Blended Transdiagnostic Intervention (eOrygen) for Youth Psychosis and Borderline Personality Disorder: Uncontrolled Single-Group Pilot Study.

BACKGROUND: Integrating innovative digital mental health interventions within specialist services is a promising strategy to address the shortcomings of both face-to-face and web-based mental health services. However, despite young people's preferences and calls for integration of these services, current mental health services rarely offer blended models of care. OBJECTIVE: This pilot study tested an integrated digital and face-to-face transdiagnostic intervention (eOrygen) as a blended model of care for youth psychosis and borderline personality disorder. The primary aim was to evaluate the feasibility, acceptability, and safety of eOrygen. The secondary aim was to assess pre-post changes in key clinical and psychosocial outcomes. An exploratory aim was to explore the barriers and facilitators identified by young people and clinicians in implementing a blended model of care into practice. METHODS: A total of 33 young people (aged 15-25 years) and 18 clinicians were recruited over 4 months from two youth mental health services in Melbourne, Victoria, Australia: (1) the Early Psychosis Prevention and Intervention Centre, an early intervention service for first-episode psychosis; and (2) the Helping Young People Early Clinic, an early intervention service for borderline personality disorder. The feasibility, acceptability, and safety of eOrygen were evaluated via an uncontrolled single-group study. Repeated measures 2-tailed t tests assessed changes in clinical and psychosocial outcomes between before and after the intervention (3 months). Eight semistructured qualitative interviews were conducted with the young people, and 3 focus groups, attended by 15 (83%) of the 18 clinicians, were conducted after the intervention. RESULTS: eOrygen was found to be feasible, acceptable, and safe. Feasibility was established owing to a low refusal rate of 25% (15/59) and by exceeding our goal of young people recruited to the study per clinician. Acceptability was established because 93% (22/24) of the young people reported that they would recommend eOrygen to others, and safety was established because no adverse events or unlawful entries were recorded and there were no worsening of clinical and social outcome measures. Interviews with the young people identified facilitators to engagement such as peer support and personalized therapy content, as well as barriers such as low motivation, social anxiety, and privacy concerns. The clinician focus groups identified evidence-based content as an implementation facilitator, whereas a lack of familiarity with the platform was identified as a barrier owing to clinicians' competing priorities, such as concerns related to risk and handling acute presentations, as well as the challenge of being understaffed. CONCLUSIONS: eOrygen as a blended transdiagnostic intervention has the potential to increase therapeutic continuity, engagement, alliance, and intensity. Future research will need to establish the effectiveness of blended models of care for young people with complex mental health conditions and determine how to optimize the implementation of such models into specialized services.

Developing a prediction model to identify people with severe mental illness without regular contact to their GP - a study based on data from the Danish national registers.

INTRODUCTION: People with severe mental illness (SMI) face a higher risk of premature mortality due to physical morbidity compared to the general population. Establishing regular contact with a general practitioner (GP) can mitigate this risk, yet barriers to healthcare access persist. Population initiatives to overcome these barriers require efficient identification of those persons in need. OBJECTIVE: To develop a predictive model to identify persons with SMI not attending a GP regularly. METHOD: For individuals with psychotic disorder, bipolar disorder, or severe depression between 2011 and 2016 (n = 48,804), GP contacts from 2016 to 2018 were retrieved. Two logistic regression models using demographic and clinical data from Danish national registers predicted severe mental illness without GP contact. Model 1 retained significant main effect variables, while Model 2 included significant bivariate interactions. Goodness-of-fit and discriminating ability were evaluated using Hosmer-Lemeshow (HL) test and area under the receiver operating characteristic curve (AUC), respectively, via cross-validation. RESULTS: The simple model retained 11 main effects, while the expanded model included 13 main effects and 10 bivariate interactions after backward elimination. HL tests were non-significant for both models (p = 0.50 for the simple model and p = 0.68 for the extended model). Their respective AUC values were 0.789 and 0.790. CONCLUSION: Leveraging Danish national register data, we developed two predictive models to identify SMI individuals without GP contact. The extended model had slightly better model performance than the simple model. Our study may help to identify persons with SMI not engaging with primary care which could enhance health and treatment outcomes in this group.

[Clinical and psychopathological characteristics of patients with late-onset schizophrenia and schizophrenia-like psychoses in clusters identified by biological parameters]. / Kliniko-psikhopatologicheskie kharakteristiki bol'nykh s pozdno manifestiruyushchimi shizofreniei i shizofrenopodobnymi psikhozami v klasterakh, vydelennykh po biologicheskim parametram.

OBJECTIVE: To assess clinical and psychopathological characteristics of late-aged female patients with late-onset psychoses in clusters formed on the basis of biochemical and immunological blood parameters. MATERIAL AND METHODS: We examined 59 women with schizophrenia and schizophrenia-like psychoses with onset after 40 years (ICD-10 F20, F22.8, F25, F23, F06.2), including 34 women with late-onset (40-60 years) and 25 with very late onset psychoses (after 60 years). At the time of hospitalization, a clinical/ psychopathological study was carried out using CGI-S, PANSS, CDSS, and HAMD-17, as well as the activities of glutathione reductase (GR) and glutathione-S-transferase (GT) have been determined in erythrocyte hemolysates, and the activities of leukocyte elastase (LE) and α1-proteinase inhibitor (α1-PI) have been assessed in blood plasma. Biochemical and immunological parameters have been also determined in 34 age-matched mentally healthy women. RESULTS: Clustering by signs such as GR, GT, LE and α1-PI has yielded two clusters of objects (patients) significantly different in GT (p<0.0001), LE (p<0.0001), and α1-PI (p<0.001) activities. Relatively to the controls, in the cluster 1 patients, the activities of GST and α1-PI are increased, the activity of LE is decreased, whereas, in the cluster 2 patients, the activity of GR is decreased, and the activities of LE and α1-PI are increased. Cluster 1 patients differ from cluster 2 patients in greater severity of the condition (CGI-S, p=0.04) and higher total scores on PANSS subscales' items. Cluster 1 includes 76% of patients with very late onset. Different correlations between clinical and biological signs are found in two clusters. CONCLUSION: The identified clusters have different clinical and psychopathological characteristics. Dividing patients into subgroups according to biochemical and immunological parameters is promising for the search for differentiated therapeutic approaches.

Development and initial validation of the cannabis-related psychosis risk literacy scale (CPRL): a multinational psychometric study.

BACKGROUND: Public education efforts to address and reduce potential harms from cannabis use in Arab countries are either slow or inexistent, and do not follow the steadily increasing trends of cannabis use in Arab youth. Several decades of research on substance use, it can be suggested that being aware of, and knowing about, psychosis risk related to cannabis can at least limit the consumption of the substance. Motivated by a lack of measures specifically designed to measure literacy about cannabis-related psychosis risk in younger populations, and based on an extensive literature review, we aimed to create and validate a new self-report scale to assess the construct, the Cannabis-related Psychosis Risk Literacy Scale (CPRL), in the Arabic language. METHOD: A cross-sectional study was carried-out during the period from September 2022 to June 2023, enrolling 1855 university students (mean age of 23.26 ± 4.96, 75.6% females) from three Arab countries (Egypt, Kuwait and Tunisia). RESULTS: Starting from an initial pool of 20 items, both Exploratory Factor Analysis and Confirmatory Factor Analysis suggested that the remaining 8 items loaded into a single factor. The scale demonstrated good internal consistency, with both McDonald omega and Cronbach's alpha values exceeding 0.7 (omega = 0.85 / alpha = 0.85). The CPRL showed measurement invariance across gender and country at the configural, metric, and scalar levels. Concurrent validity of the CPRL was established by correlations with less favourable attitudes towards cannabis (r = -.14; p <.001). In addition, higher literacy levels were found in students who never used cannabis compared to lifetime users (4.18 ± 1.55 vs. 3.44 ± 1.20, t(1853) = 8.152, p <.001). CONCLUSION: The newly developed CPRL scale offers a valid and reliable instrument for assessing and better understanding literacy about cannabis-related psychosis risk among Arabic-speaking young adults. We believe that this new scale is suitable as a screening tool of literacy, as an instrument for measuring the effect of public education interventions aimed at promoting cannabis-related psychosis risk literacy among young people, and as a research tool to facilitate future studies on the topic with a wider application.

Psychosis in Neurodegenerative Dementias: A Systematic Comparative Review.

Background: Psychosis, characterized by delusions and/or hallucinations, is frequently observed during the progression of Alzheimer's disease (AD) and other neurodegenerative dementias (ND) (i.e., dementia with Lewy bodies (DLB), and frontotemporal dementia (FTD)) and cause diagnostic and management difficulties. Objective: This review aims at presenting a concise and up-to-date overview of psychotic symptoms that occur in patients with ND with a comparative approach. Methods: A systematic review was conducted following the PRISMA guidelines. 98 original studies investigating psychosis phenotypes in neurodegenerative dementias were identified (40 cohort studies, 57 case reports). Results: Psychosis is a frequently observed phenomenon during the course of ND, with reported prevalence ranging from 22.5% to 54.1% in AD, 55.9% to 73.9% in DLB, and 18% to 42% in FTD. Throughout all stages of these diseases, noticeable patterns emerge depending on their underlying causes. Misidentification delusions (16.6-78.3%) and visual hallucinations (50-69.6%) are frequently observed in DLB, while paranoid ideas and somatic preoccupations seem to be particularly common in AD and FTD, (respectively 9.1-60.3% and 3.10-41.5%). Limited data were found regarding psychosis in the early stages of these disorders. Conclusions: Literature data suggest that different ND are associated with noticeable variations in psychotic phenotypes, reflecting disease-specific tendencies. Further studies focusing on the early stages of these disorders are necessary to enhance our understanding of early psychotic manifestations associated with ND and help in differential diagnosis issues.

Plasma neurofilament light chain is not elevated in people with first-episode psychosis or those at ultra-high risk for psychosis.

INTRODUCTION: Neurofilament light chain (NfL), a blood biomarker of neuronal injury, shows promise in distinguishing neurodegenerative disorders from psychiatric conditions. This is especially relevant in psychosis, given neurological conditions such as autoimmune encephalitis and Niemann Pick Type C disease (NPC) may initially present with psychotic symptoms. Whilst NfL levels have been studied in established schizophrenia cases, their levels in first-episode psychosis (FEP) and ultra-high risk (UHR) for psychosis individuals remain largely unexplored. This study aimed to compare plasma NfL in people with FEP or UHR with healthy controls, as well as explore its associations with clinical data. METHOD: We retrospectively analysed plasma NfL in 63 participants, consisting of 29 individuals with FEP, 10 individuals with UHR, and 24 healthy controls. We used general linear models (GLM), which were bootstrapped, to compute bias-corrected and accelerated (BCa) 95 % confidence intervals (CIs). RESULTS: Mean NfL levels were 5.2 pg/mL in FEP, 4.9 pg/mL in UHR, and 5.9 pg/mL in healthy controls. Compared to healthy controls, there were no significant differences in NfL levels in the FEP group (ß = -0.22, 95 % CI [-0.86, 0.39], p = 0.516) nor UHR group (ß = -0.37, 95 % CI [-0.90, 0.19], p = 0.182). There were no significant associations between NfL levels and clinical variables in the FEP group. DISCUSSION: Our study is the first to demonstrate that plasma NfL levels are not significantly elevated in individuals at UHR for psychosis compared to healthy controls, a finding also observed in the FEP cohort. These findings bolster the potential diagnostic utility of NfL in differentiating between psychiatric and neurodegenerative disorders.

Predicting the onset of psychotic experiences in daily life with the use of ambulatory sensor data - A proof-of-concept study.

INTRODUCTION: Predictive models of psychotic symptoms could improve ecological momentary interventions by dynamically providing help when it is needed. Wearable sensors measuring autonomic arousal constitute a feasible base for predictive models since they passively collect physiological data linked to the onset of psychotic experiences. To explore this potential, we investigated whether changes in autonomic arousal predict the onset of hallucination spectrum experiences (HSE) and paranoia in individuals with an increased likelihood of experiencing psychotic symptoms. METHOD: For 24 h of ambulatory assessment, 62 participants wore electrodermal activity and heart rate sensors and were provided with an Android smartphone to answer questions about their HSE-, and paranoia-levels every 20 min. We calculated random forests to detect the onset of HSEs and paranoia. The generalizability of our models was tested using leave-one-assessment-out and leave-one-person-out cross-validation. RESULTS: Leave-one-assessment-out models that relied on physiological data and participant ID yielded balanced accuracy scores of 80 % for HSE and 66 % for paranoia. Adding baseline information about lifetime experiences of psychotic symptoms increased balanced accuracy to 82 % (HSE) and 70 % (paranoia). Leave-one-person-out models yielded lower balanced accuracy scores (51 % to 58 %). DISCUSSION: Using passively collectible variables to predict the onset of psychotic experiences is possible and prediction models improve with additional information about lifetime experiences of psychotic symptoms. Generalizing to new individuals showed poor performance, so including personal data from a recipient may be necessary for symptom prediction. Completely individualized prediction models built solely with the data of the person to be predicted might increase accuracy further.