To enhance indicated prevention in patients with a clinical high risk (CHR) for psychosis, recent research efforts have been increasingly directed towards estimating the risk of developing psychosis on an individual level using multivariable clinical prediction models. The aim of this study was to systematically review the methodological quality and reporting of studies developing or validating such models.

A systematic literature search was carried out (up to 14 March 2016) to find all studies that developed or validated a clinical prediction model predicting the transition to psychosis in CHR patients. Data were extracted using a comprehensive item list which was based on current methodological recommendations.

A total of 91 studies met the inclusion criteria. None of the retrieved studies performed a true external validation of an existing model. Only three studies (3.5%) had an event per variable ratio of at least 10, which is the recommended minimum to avoid overfitting. Internal validation was performed in only 14 studies (15%) and seven of these used biased internal validation strategies. Other frequently observed modeling approaches not recommended by methodologists included univariable screening of candidate predictors, stepwise variable selection, categorization of continuous variables, and poor handling and reporting of missing data.

Our systematic review revealed that poor methods and reporting are widespread in prediction of psychosis research. Since most studies relied on small sample sizes, did not perform internal or external cross-validation, and used poor model development strategies, most published models are probably overfitted and their reported predictive accuracy is likely to be overoptimistic.

The public health, public safety and clinical implications of violent events among adults with mental illness are significant; however, the causes and consequences of violence and victimization among adults with mental illness are complex and not well understood, which limits the effectiveness of clinical interventions and risk management strategies. This study examined interrelationships between violence, victimization, psychiatric symptoms, substance use, homelessness and in-patient treatment over time.

Available data were integrated from four longitudinal studies of adults with mental illness. Assessments took place at baseline, and at 1, 3, 6, 9, 12, 15, 18, 24, 30 and 36 months, depending on the parent studies’ protocol. Data were analysed with the autoregressive cross-lag model.

Violence and victimization were leading indicators of each other and affective symptoms were a leading indicator of both. Drug and alcohol use were leading indicators of violence and victimization, respectively. All psychiatric symptom clusters – affective, positive, negative, disorganized cognitive processing – increased the likelihood of experiencing at least one subsequent symptom cluster. Sensitivity analyses identified few group-based differences in the magnitude of effects in this heterogeneous sample.

Violent events demonstrated unique and shared indicators and consequences over time. Findings indicate mechanisms for reducing violent events, including trauma-informed therapy, targeting internalizing and externalizing affective symptoms with cognitive–behavioral and psychopharmacological interventions, and integrating substance use and psychiatric care. Finally, mental illness and violence and victimization research should move beyond demonstrating concomitant relationships and instead focus on lagged effects with improved spatio-temporal contiguity.

Functional decline among patients with mental illness is not unique to individuals with psychotic disorders. Despite this, research on early predictors of functional outcome mainly focused on individuals thought to have an ‘at risk mental state’ (ARMS) for psychosis. There is evidence suggesting that certain early vulnerability markers, such as neurological soft signs (NSS), may explain variability in functional outcomes independent of the level of psychosis risk and the traditional diagnostic classification.

Structural equation modeling was applied to baseline data from a prospective longitudinal study of 138 young individuals in treatment with secondary services for non-psychotic disorders. We evaluated theoretically based models of pathways to functional outcome starting from NSS. The intervening variables were established according to previous evidence and drawn from two general categories: cognition (neuro- and social-) and negative symptoms (expressive and experiential).

A final trimmed model was a single path running from NSS to neurocognition to experiential negative symptoms to outcome. It could not be improved by adding or dropping connections that would change the single path to multiple paths. The indirect effect from NSS to outcome was significant. The validity of the model was independent of the ARMS status and the psychiatric diagnosis.

Our results provide evidence for a single pathway model in which the starting and intervening variables represent modifiable trans-diagnostic therapeutic targets to improve functional trajectories in young individuals with a recent-onset psychiatric diagnosis and different levels of psychosis risk.

Obsessive–compulsive disorder (OCD) is often co-morbid with depression. Using the methods of network analysis, we computed two networks that disclose the potentially causal relationships among symptoms of these two disorders in 408 adult patients with primary OCD and co-morbid depression symptoms.

We examined the relationship between the symptoms constituting these syndromes by computing a (regularized) partial correlation network via the graphical LASSO procedure, and a directed acyclic graph (DAG) via a Bayesian hill-climbing algorithm.

The results suggest that the degree of interference and distress associated with obsessions, and the degree of interference associated with compulsions, are the chief drivers of co-morbidity. Moreover, activation of the depression cluster appears to occur solely through distress associated with obsessions activating sadness – a key symptom that ‘bridges’ the two syndromic clusters in the DAG.

Bayesian analysis can expand the repertoire of network analytic approaches to psychopathology. We discuss clinical implications and limitations of our findings.

This study aimed to extend the current understanding of dissociative symptoms experienced by patients with dissociative (psychogenic, non-epileptic) seizures (DS), including psychological and somatoform types of symptomatology. An additional aim was to assess possible relationships between dissociation, traumatic experiences, post-traumatic symptoms and seizure manifestations in this group.

A total of 40 patients with DS were compared with a healthy control group (n = 43), matched on relevant demographic characteristics. Participants completed several self-report questionnaires, including the Multiscale Dissociation Inventory (MDI), Somatoform Dissociation Questionnaire-20, Traumatic Experiences Checklist and the Post-Traumatic Diagnostic Scale. Measures of seizure symptoms and current emotional distress (Hospital Anxiety and Depression Scale) were also administered.

The clinical group reported significantly more psychological and somatoform dissociative symptoms, trauma, perceived impact of trauma, and post-traumatic symptoms than controls. Some dissociative symptoms (i.e. MDI disengagement, MDI depersonalization, MDI derealization, MDI memory disturbance, and somatoform dissociation scores) were elevated even after controlling for emotional distress; MDI depersonalization scores correlated positively with trauma scores while seizure symptoms correlated with MDI depersonalization, derealization and identity dissociation scores. Exploratory analyses indicated that somatoform dissociation specifically mediated the relationship between reported sexual abuse and DS diagnosis, along with depressive symptoms.

A range of psychological and somatoform dissociative symptoms, traumatic experiences and post-traumatic symptoms are elevated in patients with DS relative to healthy controls, and seem related to seizure manifestations. Further studies are needed to explore peri-ictal dissociative experiences in more detail.

Although there is robust evidence linking childhood adversities (CAs) and an increased risk for psychotic experiences (PEs), little is known about whether these associations vary across the life-course and whether mental disorders that emerge prior to PEs explain these associations.

We assessed CAs, PEs and DSM-IV mental disorders in 23 998 adults in the WHO World Mental Health Surveys. Discrete-time survival analysis was used to investigate the associations between CAs and PEs, and the influence of mental disorders on these associations using multivariate logistic models.

Exposure to CAs was common, and those who experienced any CAs had increased odds of later PEs [odds ratio (OR) 2.3, 95% confidence interval (CI) 1.9–2.6]. CAs reflecting maladaptive family functioning (MFF), including abuse, neglect, and parent maladjustment, exhibited the strongest associations with PE onset in all life-course stages. Sexual abuse exhibited a strong association with PE onset during childhood (OR 8.5, 95% CI 3.6–20.2), whereas Other CA types were associated with PE onset in adolescence. Associations of other CAs with PEs disappeared in adolescence after adjustment for prior-onset mental disorders. The population attributable risk proportion (PARP) for PEs associated with all CAs was 31% (24% for MFF).

Exposure to CAs is associated with PE onset throughout the life-course, although sexual abuse is most strongly associated with childhood-onset PEs. The presence of mental disorders prior to the onset of PEs does not fully explain these associations. The large PARPs suggest that preventing CAs could lead to a meaningful reduction in PEs in the population.

Obsessive–compulsive disorder (OCD) has been linked to functional abnormalities in fronto-striatal networks as well as impairments in decision making and learning. Little is known about the neurocognitive mechanisms causing these decision-making and learning deficits in OCD, and how they relate to dysfunction in fronto-striatal networks.

We investigated neural mechanisms of decision making in OCD patients, including early and late onset of disorder, in terms of reward prediction errors (RPEs) using functional magnetic resonance imaging. RPEs index a mismatch between expected and received outcomes, encoded by the dopaminergic system, and are known to drive learning and decision making in humans and animals. We used reinforcement learning models and RPE signals to infer the learning mechanisms and to compare behavioural parameters and neural RPE responses of the OCD patients with those of healthy matched controls.

Patients with OCD showed significantly increased RPE responses in the anterior cingulate cortex (ACC) and the putamen compared with controls. OCD patients also had a significantly lower perseveration parameter than controls.

Enhanced RPE signals in the ACC and putamen extend previous findings of fronto-striatal deficits in OCD. These abnormally strong RPEs suggest a hyper-responsive learning network in patients with OCD, which might explain their indecisiveness and intolerance of uncertainty.

A previous small study suggested that Brain Network Activation (BNA), a novel ERP-based brain network analysis, may have diagnostic utility in attention deficit hyperactivity disorder (ADHD). In this study we examined the diagnostic capability of a new advanced version of the BNA methodology on a larger population of adults with and without ADHD.

Subjects were unmedicated right-handed 18- to 55-year-old adults of both sexes with and without a DSM-IV diagnosis of ADHD. We collected EEG while the subjects were performing a response inhibition task (Go/NoGo) and then applied a spatio-temporal Brain Network Activation (BNA) analysis of the EEG data. This analysis produced a display of qualitative measures of brain states (BNA scores) providing information on cortical connectivity. This complex set of scores was then fed into a machine learning algorithm.

The BNA analysis of the EEG data recorded during the Go/NoGo task demonstrated a high discriminative capacity between ADHD patients and controls (AUC = 0.92, specificity = 0.95, sensitivity = 0.86 for the Go condition; AUC = 0.84, specificity = 0.91, sensitivity = 0.76 for the NoGo condition).

BNA methodology can help differentiate between ADHD and healthy controls based on functional brain connectivity. The data support the utility of the tool to augment clinical examinations by objective evaluation of electrophysiological changes associated with ADHD. Results also support a network-based approach to the study of ADHD.

Various sources indicate that mental disorders are the leading contributor to the burden of disease among youth. An important determinant of functioning is current mental health status. This study investigated whether psychiatric history has additional predictive power when predicting individual differences in functional outcomes.

We used data from the Dutch TRAILS study in which 1778 youths were followed from pre-adolescence into young adulthood (retention 80%). Of those, 1584 youths were successfully interviewed, at age 19, using the World Health Organization Composite International Diagnostic Interview (CIDI 3.0) to assess current and past CIDI-DSM-IV mental disorders. Four outcome domains were assessed at the same time: economic (e.g. academic achievement, social benefits, financial difficulties), social (early motherhood, interpersonal conflicts, antisocial behavior), psychological (e.g. suicidality, subjective well-being, loneliness), and health behavior (e.g. smoking, problematic alcohol, cannabis use).

Out of the 19 outcomes, 14 were predicted by both current and past disorders, three only by past disorders (receiving social benefits, psychiatric hospitalization, adolescent motherhood), and two only by current disorder (absenteeism, obesity). Which type of disorders was most important depended on the outcome. Adjusted for current disorder, past internalizing disorders predicted in particular psychological outcomes while externalizing disorders predicted in particular health behavior outcomes. Economic and social outcomes were predicted by a history of co-morbidity of internalizing and externalizing disorder. The risk of problematic cannabis use and alcohol consumption dropped with a history of internalizing disorder.

To understand current functioning, it is necessary to examine both current and past psychiatric status.

The conceptualization of post-traumatic stress disorder (PTSD) in the upcoming International Classification of Diseases (ICD)-11 differs in many respects from the diagnostic criteria in the Diagnostic and Statistical Manual for Mental Disorders, fifth edition (DSM-5). The consequences of these differences for individuals and for estimation of prevalence rates are largely unknown. This study investigated the concordance of the two diagnostic systems in two separate samples at two separate waves.

Young survivors of the 2011 Norway attacks (n = 325) and their parents (n = 451) were interviewed at 4–6 months (wave 1) and 15–18 months (wave 2) after the shooting. PTSD was assessed with the UCLA PTSD Reaction Index for DSM-IV adapted for DSM-5, and a subset was used as diagnostic criteria for ICD-11.

In survivors, PTSD prevalence did not differ significantly at any time point, but in parents, the DSM-5 algorithm produced significantly higher prevalence rates than the ICD-11 criteria. The overlap was fair for survivors, but amongst parents a large proportion of individuals met the criteria for only one of the diagnostic systems. No systematic differences were found between ICD-11 and DSM-5 in predictive validity.

The proposed ICD-11 criteria and the DSM-5 criteria performed equally well when identifying individuals in distress. Nevertheless, the overlap between those meeting the PTSD diagnosis for both ICD-11 and DSM-5 was disturbingly low, with the ICD-11 criteria identifying fewer people than the DSM-5. This represents a major challenge in identifying individuals suffering from PTSD worldwide, possibly resulting in overtreatment or unmet needs for trauma-specific treatment, depending on the area of the world in which patients are being diagnosed.

Patients with bipolar disorder (BD) frequently exhibit impulsive behaviors independent of their mood state, and trait impulsivity is increasingly recognized as a crucial BD biomarker. This study aimed to investigate structural correlates of trait impulsivity measured using the Barratt Impulsiveness Scale (BIS) in healthy controls (HCs) and patients with BD.

We recruited 59 patients diagnosed with BD I or BD II (35.3 ± 8.5 years) and 56 age- and sex-matched HCs (33.9 ± 7.4 years). Participants underwent structural magnetic resonance imaging and clinical evaluations, and their BIS scores were evaluated. An automated surface-based method (FreeSurfer) was used to measure cortical thickness and generate thickness maps for each participant. Brain-wise regression analysis of the association between cortical thickness and BIS scores was performed separately for BD and HC groups by using a general linear model.

Patients with BD obtained significantly higher BIS scores than HCs. In HCs, higher BIS scores were associated with a thinner cortex in the left inferior, middle and medial frontal cortices. By contrast, in BD patients, higher BIS scores were associated with a thicker cortex in the right insula. Patients with BD showed a thinner cortex than HCs in all these four structures.

The findings indicate that the left prefrontal cortex plays a cardinal role in trait impulsivity of healthy individuals. Patients with BD have a different structural correlate of trait impulsivity in the right insula. However, the use of various psychotropics in patients with BD may limit our interpretation of BD findings.

Sensory-processing deficits appear crucial to the clinical expression of symptoms of schizophrenia. The visual cortex displays both dysconnectivity and aberrant spontaneous activity in patients with persistent symptoms and cognitive deficits. In this paper, we examine visual cortex in the context of the remerging notion of thalamic dysfunction in schizophrenia. We examined specific regional and longer-range abnormalities in sensory and thalamic circuits in schizophrenia, and whether these patterns are strong enough to discriminate symptomatic patients from controls.

Using publicly available resting fMRI data of 71 controls and 62 schizophrenia patients, we derived conjunction maps of regional homogeneity (ReHo) and fractional amplitude of low-frequency fluctuations (fALFF) to inform further seed-based Granger causality analysis (GCA) to study effective connectivity patterns. ReHo, fALFF and GCA maps were entered into a multiple kernel learning classifier, to determine whether patterns of local and effective connectivity can differentiate controls from patients.

Visual cortex shows both ReHo and fALFF reductions in patients. Visuothalamic effective connectivity in patients was significantly reduced. Local connectivity (ReHo) patterns discriminated patients from controls with the highest level of accuracy of 80.32%.

Both the inflow and outflow of Granger causal information between visual cortex and thalamus is affected in schizophrenia; this occurs in conjunction with highly discriminatory but localized dysconnectivity and reduced neural activity within the visual cortex. This may explain the visual-processing deficits that are present despite symptomatic remission in schizophrenia.

Blunted facial affect is a common negative symptom of schizophrenia. Additionally, assessing the trustworthiness of faces is a social cognitive ability that is impaired in schizophrenia. Currently available pharmacological agents are ineffective at improving either of these symptoms, despite their clinical significance. The hypothalamic neuropeptide oxytocin has multiple prosocial effects when administered intranasally to healthy individuals and shows promise in decreasing negative symptoms and enhancing social cognition in schizophrenia. Although two small studies have investigated oxytocin's effects on ratings of facial trustworthiness in schizophrenia, its effects on facial expressivity have not been investigated in any population.

We investigated the effects of oxytocin on facial emotional expressivity while participants performed a facial trustworthiness rating task in 33 individuals with schizophrenia and 35 age-matched healthy controls using a double-blind, placebo-controlled, cross-over design. Participants rated the trustworthiness of presented faces interspersed with emotionally evocative photographs while being video-recorded. Participants’ facial expressivity in these videos was quantified by blind raters using a well-validated manualized approach (i.e. the Facial Expression Coding System; FACES).

While oxytocin administration did not affect ratings of facial trustworthiness, it significantly increased facial expressivity in individuals with schizophrenia (Z = −2.33, p = 0.02) and at trend level in healthy controls (Z = −1.87, p = 0.06).

These results demonstrate that oxytocin administration can increase facial expressivity in response to emotional stimuli and suggest that oxytocin may have the potential to serve as a treatment for blunted facial affect in schizophrenia.

Autism spectrum disorders (ASDs) are pervasive and multifactorial neurodevelopmental conditions, characterized by impairments in social communication and interaction, and restricted, repetitive patterns of behaviour, interests or activities. Treatment options to ameliorate symptoms of ASDs are limited. Heterogeneity complicates the quest for personalized medicine in this population. Our aim was to investigate if there are baseline characteristics of patients that moderate response or trial design features that impede the identification of efficacious interventions for ASDs.

Literature searches of EMBASE, MEDLINE and PsycINFO identified 43 studies for qualitative assessment of baseline characterization of participants and 37 studies for quantitative analysis of moderators of treatment response. Criteria included blinded randomized controlled trials (RCTs) in paediatric ASD, with at least 10 participants per arm or 20 overall, of oral treatments, including pharmacological interventions and dietary supplements.

Random-effects meta-analysis of 1997 participants (81% male) identified three moderators associated with an increase in treatment response: trials located in Europe and the Middle-East; outcome measures designated primary status; and the type of outcome measure. Inconsistent reporting of baseline symptom severity and intellectual functioning prevented analysis of these variables. Qualitative synthesis of baseline characteristics identified at least 31 variables, with only age and gender reported in all trials. Biological markers were included in six RCTs.

Few trials reported adequate baseline characteristics to permit detailed analysis of response to treatment. Consideration of geographical location, baseline severity and intellectual function is required to ensure generalizability of results. The use of biological markers and correlates in ASD trials remains in its infancy. There is great need to improve the application of baseline characterization and incorporation of biological markers and correlates to permit selection of participants into homogeneous subgroups and to inform response to treatment in ASD.