Support vector machines (SVMs) based on brain-wise functional connectivity (FC) have been widely adopted for single-subject prediction of patients with schizophrenia, but most of them had small sample size. This study aimed to evaluate the performance of SVMs based on a large single-site dataset and investigate the effects of demographic homogeneity and training sample size on classification accuracy.

The resting functional Magnetic Resonance Imaging (fMRI) dataset comprised 220 patients with schizophrenia and 220 healthy controls. Brain-wise FCs was calculated for each participant and linear SVMs were developed for automatic classification of patients and controls. First, we evaluated the SVMs based on all participants and homogeneous subsamples of men, women, younger (18–30 years), and older (31–50 years) participants by 10-fold nested cross-validation. Then, we hold out a fixed test set of 40 participants (20 patients and 20 controls) and evaluated the SVMs based on incremental training sample sizes (N = 40, 80, …, 400).

We found that the SVMs based on all participants had accuracy of 85.05%. The SVMs based on male, female, young, and older participants yielded accuracy of 84.66, 81.56, 80.50, and 86.13%, respectively. Although the SVMs based on older subsamples had better performance than those based on all participants, they generalized poorly to younger participants (77.24%). For incremental training sizes, the classification accuracy increased stepwise from 72.6 to 83.3%, with >80% accuracy achieved with sample size >240.

The findings indicate that SVMs based on a large dataset yield high classification accuracy and establish models using a large sample size with heterogeneous properties are recommended for single subject prediction of schizophrenia.

Early intervention in psychosis (EIP) services target the early manifestation of psychosis and provide multidisciplinary care. They demonstrate effectiveness and cost-effectiveness. Implementation of EIP services is inconsistent and piecemeal. This systematic review and narrative synthesis aims to identify barriers and facilitators to EIP service implementation.

We conducted an electronic search of databases (EMBASE, Medline, Web of Science, and PsychINFO) to detect papers reporting EIP service implementation findings and associated barriers and facilitators. The search occurred between June to August 2020, and again in January 2021. Articles meeting inclusion criteria were extracted and narratively synthesized. A quality assessment was conducted using the Mixed Methods Appraisal Tool.

Twenty-three studies were selected. The most common study design was descriptive accounts of implementation. Patient age ranged varied from 14 to 35 years. We identified three barrier and facilitator domains: (a) system; (b) services; and (c) staff, and a range of subdomains. The most frequent subdomains were “funding” and “strength of collaboration and communication between EIP and outside groups and services”. Associations between domains and subdomains were evident, particularly between systems and services.

A range of barriers and facilitators to EIP implementation exist. Some of these are generic factors germane across health systems and services, while others are specific to EIP services. A thorough prior understanding of these challenges and enablers are necessary before implementation is attempted. Accounting for these issues within local and national contexts may help predict and increase the likelihood of services’ success, stability, and longevity.

Previous research has indicated that attention-deficit/hyperactivity disorder (ADHD) is associated with an increased risk for dementia, but studies are scarce and inconclusive. We aimed to investigate the association between ADHD, and dementia and mild cognitive impairment (MCI). Additionally, we aimed to investigate the impact of comorbid conditions, educational attainment, head injuries, other developmental disorders, and sex on the association.

The study population consisted of 3,591,689 individuals born between 1932 and 1963, identified from Swedish population-based registers. Cases of ADHD, dementia and MCI were defined according to ICD diagnostic codes and ATC codes for medication prescriptions. A Cox proportional hazards model was used to test the associations between ADHD, and dementia and MCI.

Individuals with ADHD had an increased risk for dementia and MCI. After adjusting for sex and birth year, a hazard ratio (HR) was 2.92 (95% confidence interval 2.40–3.57) for dementia, and 6.21 (5.25–7.35) for MCI. Additional adjustment for psychiatric disorders (depression, anxiety, substance use disorder, and bipolar disorder) substantially attenuated the associations, HR = 1.62 (1.32–1.98) for dementia, and 2.54 (2.14–3.01) for MCI. Common metabolic disorders (hypertension, type 2 diabetes, and obesity), sleep disorders, head injuries, educational attainment, and other developmental disorders, had a limited impact on the association. The association between ADHD and dementia was stronger in men.

ADHD is a potential risk factor for dementia and MCI, although the risk significantly attenuates after controlling for psychiatric disorders. Further research is needed to confirm these findings and to explore underlying mechanisms of the associations.

Catatonic features can appear in autism spectrum disorders (ASDs). There can be overlap in symptoms across catatonia and ASD. The overall aim of this review is to provide evidence for the presence of catatonic features in subjects with ASD.

A systematic literature search using the Web of Science database from inception to July 10, 2021 was conducted following PRISMA, MOOSE guidelines and the PROSPERO protocol. (CRD42021248615). Twelve studies with information about catatonia and ASD were reviewed. Data from a subset was used to conduct meta-analyses of the presence of catatonia in ASD.

The systematic review included 12 studies, seven of which were used for the meta-analysis, comprising 969 individuals. The mean age was 21.25 (7.5) years. Two studies (16.6%) included only children and adolescents. A total of 70–100% were males. Our meta-analysis showed that 10.4% (5.8–18.0 95%CI) of individuals with ASD have catatonia. Motor disturbances were common in ASD subjects with catatonia. No differences were found in comorbidity. Several treatments have been used in ASD with catatonic features, including benzodiazepines, antipsychotics, and electroconvulsive therapy (ECT). The findings of the systematic review showed that ECT might help manage catatonic symptoms.

Different features of catatonia can exist in individuals with ASD and core symptoms of catatonia are reported in ASD. Longitudinal and longer-term studies are required to understand the relationship between catatonia and ASD, and the response of catatonic symptoms to treatment.

Long-acting injectable (LAI) antipsychotics improve medication adherence in patients with schizophrenia and extend the duration of therapeutic drug levels but with administration of an increased dose. Real-world mortality data in patients prescribed LAIs are lacking. We conducted a population-based cohort study to estimate and compare the incidence rates of all-cause death and completed suicide in patients with schizophrenia/schizoaffective disorder exposed to LAIs and oral antipsychotics.

Patients with a diagnosis of schizophrenia/schizoaffective disorder between January 1, 2015 and November 30, 2019 were enrolled from the Taiwan National Health Insurance Research Database and linked to Death Registry records. Eligible patients were new antipsychotic users. Relative risks of death for each antipsychotic compared with oral paliperidone were evaluated using a Cox proportional hazard model adjusted for age, sex, Charlson Comorbidity Index, index year, bipolar or major depressive or other mood disorders, mental disorders due to drug use, and baseline hospitalization frequency.

There were 228,791.08 person-years of follow-up (mean 2.48 years). The incidence rates of all-cause death in users of LAI paliperidone administered monthly (PP1M) and every 3 months (PP3M) were 7.40/1,000 person-years (95% confidence interval 5.94–9.11) and 9.93 (5.88–15.79), respectively. The incidences of completed suicide were 2.03/1,000 person-years (1.32–2.99) and 3.10 (1.14–6.88), respectively. No significant associations were observed between PP1M and PP3M compared to oral paliperidone in incidences of all-cause death or for completed suicide.

No increased risk of all-cause death or completed suicide was observed in users of antipsychotic LAIs, including PP1M and PP3M.

Despite multiple ethical issues and little evidence of their efficacy, compulsory admission and treatment are still common psychiatric practice. Therefore, we aimed to assess potential differences in treatment and outcome between voluntarily and compulsorily admitted patients.

We extracted clinical data from inpatients treated in an academic hospital in Zurich, Switzerland between January 1, 2013 and December 31, 2019. Observation time started upon the first admission and ended after a one-year follow-up after the last discharge. Several sociodemographic and clinical characteristics, including Health of the Nation Outcome Scales (HoNOS) scores, were retrospectively obtained. We then identified risk factors of compulsory admission using logistic regression in order to perform a widely balanced propensity score matching. Altogether, we compared 4,570 compulsorily and 4,570 voluntarily admitted propensity score-matched patients. Multiple differences between these groups concerning received treatment, coercive measures, clinical parameters, and service use outcomes were detected.

Upon discharge, compulsorily admitted patients reached a similar HoNOS sum score in a significantly shorter duration of treatment. They were more often admitted for crisis interventions, were prescribed less pharmacologic treatment, and received fewer therapies. During the follow-up, voluntarily admitted patients were readmitted more often, while the time to readmission did not differ.

Under narrowly set circumstances, compulsory admissions might be helpful to avert and relieve exacerbations of severe psychiatric disorders.

Studies of COVID-19 pandemic biopsychosocial exposure and schizophrenia risk showed contradictory results, were undertaken early in the pandemic, and did not consider lockdowns or COVID-19 infection. Hence, we examined the association between COVID-19 biopsychosocial exposure and incident schizophrenia.

An interrupted time-series study design was implemented based on Israeli electronic health records from 2013 to 2021 with national coverage. The period coinciding with the COVID-19 pandemic biopsychosocial exposures from March 2020 to February 2021 was classified as exposed, otherwise unexposed. The effect of the COVID-19 pandemic on incident schizophrenia was quantified by fitting a Poisson regression and modeling the relative risk (RR) and corresponding 95% confidence intervals (CI). Three scenarios were projected from the third lockdown to 10 months to forecast incident schizophrenia rates and their associated 95% prediction intervals (PI).

The total population (N = 736,356) yielded 4,310 cases of incident schizophrenia over time. The primary analysis showed that the period exposed to the COVID-19 pandemic was associated with a reduced RR (RR = 0.81, 95% CI = 0.73, 0.91, p < 0.001). This conclusion was supported in 12 sensitivity analyses, including scrutinizing lockdowns and COVID-19 infection status. Two of three forecast scenarios projected an incident increase (6.74, 95% PI = 5.80, 7.84; 7.40, 95% PI = 6.36, 8.60).

The reduced risk of schizophrenia during the pandemic suggests no immediate triggering of new onsets either by the virus or the pandemic-induced psychosocial adversities. Once restrictions are lifted, the increased projected presentations have implications for clinicians and healthcare policy.

Bipolar disorder (BD) is recognized to be at high risk for developing negative psychopathological sequelae to potentially traumatic events. Nevertheless, scant data are still available about the effects of the COVID-19 emergency on the clinical course of BD. The present study examined prospectively the development and trajectories of post-traumatic stress, depressive, and anxiety symptoms among subjects with BD that were followed in an outpatient psychiatric clinic at the time of pandemic onset.

A cohort of 89 subjects with BD was enrolled during the first wave of the COVID-19 pandemic, and assessed at baseline (T0), 2-months (T1), and 6-months (T2) follow-up. A K-means cluster analysis was used to identify distinct trajectories of depressive, anxiety, and post-traumatic stress symptoms during the three time points.

We identified three trajectories: the Acute reaction (13.5%); the Increasing severity (23.6%); and the Low symptoms (62.9%) groups, respectively. In the Acute reaction group a significant prevalence of female gender was reported with respect to the Low symptoms one. Subjects in the Increasing severity group reported significantly lower employment rate, and higher rate of relatives at risk for COVID-19 medical complications. Subjects in the Increasing Severity group reported higher rates of previous hospitalization and manic symptoms at baseline than those included in the Low symptoms one.

Our results describe three distinct symptom trajectories during the COVID-19 emergency in a cohort of subjects suffering from BD, suggesting the need of a long-term follow-up for detecting the impact of the COVID-19 pandemic in this vulnerable population.

Healthcare workers (HCWs) exposed to coronavirus 19 (COVID-19) are at high risk of developing mental health concerns across several domains. The aim of this study is to determine the updated, global frequency of these outcomes.

A multistep literature search was performed from database inception until March 1, 2021. PRISMA/MOOSE-compliant systematic review and PROSPERO protocol were used to identify studies reporting on depression, anxiety, acute stress, post-traumatic symptoms, insomnia, and burnout in HCWs exposed to COVID-19. A quantitative meta-analysis with random effects was conducted to analyze the proportion rate of the mental health disorders. Sensitivity analyses were performed to investigate the effect of the different continents and scales. Meta-regression analyses were conducted to examine the effect of gender, age, and work position.

239 articles were included (n = 271,319 HCWs, mean age = 36.08 ± 8.33 (66.99% female). 33% HCWs exposed to COVID-19 reported depressive symptoms (95% confidence intervals [CI] = 28–38%), 42% anxiety features (95% CI = 35–48), 40% acute stress (95% CI = 32–47), 32% post-traumatic symptoms (95% CI = 26–37%), 42% insomnia (95% CI = 36–48), 37% burnout (95% CI = 31–42). Sensitivity analyses did not show statistically significant differences. Meta-regressions found a statistically significant lower prevalence of post-traumatic symptoms in Asia.

HCWs exposed to COVID-19 were found to have a significant prevalence of mental health concerns in all domains analyzed. The effects of COVID-19 on HCWs’ mental health could be underestimated and the future consequences dismissed.

The experience of time, or the temporal order of external and internal events, is essential for humans. In psychiatric disorders such as depression and schizophrenia, impairment of time processing has been discussed for a long time.

In this explorative pilot study, therefore, the subjective time feeling as well as objective time perception were determined in patients with depression and schizophrenia, along with possible neurobiological correlates.

Depressed (n = 34; 32.4 ± 9.8 years; 21 men) and schizophrenic patients (n = 31; 35.1 ± 10.7 years; 22 men) and healthy subjects (n = 33; 32.8 ± 14.3 years; 16 men) were tested using time feeling questionnaires, time perception tasks and critical flicker-fusion frequency (CFF) and loudness dependence of auditory evoked potentials (LDAEP) to determine serotonergic neurotransmission.

There were significant differences between the three groups regarding time feeling and also in time perception tasks (estimation of given time duration) and CFF (the “DOWN” condition). Regarding the LDAEP, patients with schizophrenia showed a significant negative correlation to time experience in terms of a pathologically increased serotonergic neurotransmission with disturbed time feeling.

Impairment of time experience seems to play an important role in depression and schizophrenia, both subjectively and objectively, and novel neurobiological correlates have been uncovered. It is suggested, therefore, that alteration of experience of time should be increasingly included in the current psychopathological findings.

One of the challenges in human neuroscience is to uncover associations between brain organization and psychopathology in order to better understand the biological underpinnings of mental disorders. Here, we aimed to characterize the neural correlates of psychopathology dimensions obtained using two conceptually different data-driven approaches.

Dimensions of psychopathology that were either maximally dissociable or correlated were respectively extracted by independent component analysis (ICA) and exploratory factor analysis (EFA) applied to the Childhood Behavior Checklist items from 9- to 10-year-olds (n = 9983; 47.8% female, 50.8% white) participating in the Adolescent Brain Cognitive Development study. The patterns of brain morphometry, white matter integrity and resting-state connectivity associated with each dimension were identified using kernel-based regularized least squares and compared between dimensions using Spearman’s correlation coefficient.

ICA identified three psychopathology dimensions, representing opposition–disinhibition, cognitive dyscontrol, and negative affect, with distinct brain correlates. Opposition–disinhibition was negatively associated with cortical surface area, cognitive dyscontrol was negatively associated with anatomical and functional dysconnectivity while negative affect did not show discernable associations with any neuroimaging measure. EFA identified three dimensions representing broad externalizing, neurodevelopmental, and broad Internalizing problems with partially overlapping brain correlates. All EFA-derived dimensions were negatively associated with cortical surface area, whereas measures of functional and structural connectivity were associated only with the neurodevelopmental dimension.

This study highlights the importance of cortical surface area and global connectivity for psychopathology in preadolescents and provides evidence for dissociable psychopathology dimensions with distinct brain correlates.

Psychiatric comorbidities and suicide attempts are highly prevalent in Bipolar Disorders (BD). We examined the associations between childhood maltreatment, psychiatric comorbidities, and suicide attempts, in terms of lifetime prevalence, sequence of onset, and current symptoms.

We assessed 3,047 individuals with BD for suicide attempts, anxiety disorders, substance use disorders, and eating disorders. Participants completed a self-report for the assessment of childhood maltreatment. Associations between childhood maltreatment and characteristics of comorbidities (lifetime prevalence, current symptoms, and age at onset) were examined using logistic regressions and network analyses.

Psychiatric comorbidities were frequent with a mean number per individual of 1.23 (SD = 1.4). Most comorbidities occurred prior to the onset of BD. Participants who reported higher levels of childhood maltreatment had more frequent and multiple comorbidities, which were also more currently active at inclusion. Childhood maltreatment did not decrease the age of onset of comorbidities, but was associated with a faster accumulation of comorbidities prior to the onset of BD. Logistic regression and network analyses showed that emotional abuse and sexual abuse might play a prominent role in the lifetime prevalence of psychiatric comorbidities and suicide attempts.

Childhood maltreatment was associated with suicide attempts, and with frequent, multiple, and persistent psychiatric comorbidities that accumulated more rapidly prior to the onset of BD. Hence, childhood maltreatment should be systematically assessed in individuals with BD, in particular when the course of the disorder is characterized by a high comorbid profile or by a high suicidality.

Guidance in England recommends psychosocial assessment when presenting to hospital following self-harm but adherence is variable. There is some evidence suggesting that psychosocial assessment is associated with lower risk of subsequent presentation to hospital for self-harm, but the potential cost-effectiveness of psychosocial assessment for hospital-presenting self-harm is unknown.

A three-state four-cycle Markov model was used to assess cost-effectiveness of psychosocial assessment after self-harm compared with no assessment over 2 years. Data on risk of subsequent self-harm and hospital costs of treating self-harm were drawn from the Multicentre Study of Self-Harm in England, while estimates of effectiveness of psychosocial assessment on risk of self-harm, quality of life, and other costs were drawn from literature. Incremental cost-effectiveness ratios (ICERs) for cost per Quality Adjusted Life Year (QALY) gained were estimated. Parameter uncertainty was addressed in univariate and probabilistic sensitivity analyses.

Cost per QALY gained from psychosocial assessment was £10,962 (95% uncertainty interval [UI] £15,538–£9,219) from the National Health Service (NHS) perspective and £9,980 (95% UI £14,538–£6,938) from the societal perspective. Results were generally robust to changes in model assumptions. The probability of the ICER being below £20,000 per QALY gained was 78%, rising to 91% with a £30,000 threshold.

Psychosocial assessment as implemented in the English NHS is likely to be cost-effective. This evidence could support adherence to NICE guidelines. However, further evidence is needed about the precise impacts of psychosocial assessment on self-harm repetition and costs to individuals and their families beyond immediate hospital stay.

The Positive and Negative Syndrome Scale (PANSS) is widely used in schizophrenia and has been divided into distinct factors (5-factor models) and subfactors. Network analyses are newer in psychiatry and can help to better understand the relationships and interactions between the symptoms of a psychiatric disorder. The aim of this study was threefold: (a) to evaluate connections between schizophrenia symptoms in two populations of patients (patients in the acutely exacerbated phase of schizophrenia and patients with predominant negative symptoms [PNS]), (b) to test whether network analyses support the Mohr 5 factor model of the PANSS and the Kahn 2 factor model of negative symptoms, and finally (c) to identify the most central symptoms in the two populations.

Using pooled baseline data from four cariprazine clinical trials in patients with acute exacerbation of schizophrenia (n = 2193) and the cariprazine–risperidone study in patients with PNS (n = 460), separate network analyses were performed. Network structures were estimated for all 30 items of the PANSS.

While negative symptoms in patients with an acute exacerbation of schizophrenia are correlated with other PANSS symptoms, these negative symptoms are not correlated with other PANSS symptoms in patients with PNS. The Mohr factors were partially reflected in the network analyses. The two most central symptoms (largest node strength) were delusions and uncooperativeness in acute phase patients and hostility and delusions in patients with PNS.

This network analysis suggests that symptoms of schizophrenia are differently structured in acute and PNS patients. While in the former, negative symptoms are mainly secondary, in patients with PNS, they are mainly primary. Further, primary negative symptoms are better conceptualized as distinct negative symptom dimensions of the PANSS.

Suicide is one of the main preventable causes of death. Artificial intelligence (AI) could improve methods for assessing suicide risk. The objective of this review is to assess the potential of AI in identifying patients who are at risk of attempting suicide.

A systematic review of the literature was conducted on PubMed, EMBASE, and SCOPUS databases, using relevant keywords.

Thanks to this research, 296 studies were identified. Seventeen studies, published between 2014 and 2020 and matching inclusion criteria, were selected as relevant. Included studies aimed at predicting individual suicide risk or identifying at-risk individuals in a specific population. The AI performance was overall good, although variable across different algorithms and application settings.

AI appears to have a high potential for identifying patients at risk of suicide. The precise use of these algorithms in clinical situations, as well as the ethical issues it raises, remain to be clarified.

Psychopathological network model has received attention recently in the traditional debate about the continuity of depression. However, there is little evidence for comparing the network structure of depressive symptoms in several depressive states at different clinical stages. Through this study of a broad sample of patients with nonclinical to clinical depression, we examined differences in the network structure of depressive symptoms.

Four groups of participants, including cohorts of clinical depression (current depression, n = 294; remitted depression, n = 118) and nonclinical depression (subthreshold depression, N = 184; healthy control, n = 257), responded to Beck Depression Inventory-II (BDI-II). After adjusting for age and sex, the residual scores of the 21 BDI-II items were input into a regularized partial correlation network for each group. Then, the estimated edge strengths/densities and node characteristics were compared.

Current depression has a discontinuous structure with a stronger and denser network of symptoms compared with nonclinical groups. Interestingly, remitted depression had improved to the level in healthy controls; however, it retained the same network structure as current depression, which indicates a trace of depression.

We found the traces of depression that remained even after the symptoms disappeared. This study might provide a novel framework for elucidating the development and formation of depression.