There is growing evidence that smoking increases the risk of developing psychiatric disorders, but the underlying mechanisms are largely unknown. We examine brain structure as a potential pathway between smoking and psychiatric disease liability.

We test associations between smoking (initiation, cigarettes per day, cessation, lifetime use) and depression, bipolar disorder, and schizophrenia, with and without correcting for volume of the amygdala, hippocampus, lateral and medial orbitofrontal cortex, superior frontal context, and cortical thickness and surface area. We use three methods that use summary statistics of genome-wide association studies to investigate genome-wide and local genetic overlap (genomic structural equation modeling, local analysis of (co)variant association), as well as causal associations (Mendelian randomization).

While we find causal effects of smoking on brain volume in different brain areas, and with psychiatric disorders, brain volume did not seem to mediate the effect of smoking on psychiatric disorders.

While these findings are limited by characteristics of the included summary statistics (e.g. sample size), we conclude that brain volume of these areas is unlikely to explain a substantial part of any effect of smoking on psychiatric disorders. Nevertheless, genetic methods are valuable tools for exploring other potential mechanisms, such as brain functional connectivity, foregoing the need to collect all phenotypes in one dataset.

It remains unclear which individuals with subthreshold depression benefit most from psychological intervention, and what long-term effects this has on symptom deterioration, response and remission.

To synthesise psychological intervention benefits in adults with subthreshold depression up to 2 years, and explore participant-level effect-modifiers.

Randomised trials comparing psychological intervention with inactive control were identified via systematic search. Authors were contacted to obtain individual participant data (IPD), analysed using Bayesian one-stage meta-analysis. Treatment–covariate interactions were added to examine moderators. Hierarchical-additive models were used to explore treatment benefits conditional on baseline Patient Health Questionnaire 9 (PHQ-9) values.

IPD of 10 671 individuals (50 studies) could be included. We found significant effects on depressive symptom severity up to 12 months (standardised mean-difference [s.m.d.] = −0.48 to −0.27). Effects could not be ascertained up to 24 months (s.m.d. = −0.18). Similar findings emerged for 50% symptom reduction (relative risk = 1.27–2.79), reliable improvement (relative risk = 1.38–3.17), deterioration (relative risk = 0.67–0.54) and close-to-symptom-free status (relative risk = 1.41–2.80). Among participant-level moderators, only initial depression and anxiety severity were highly credible (P > 0.99). Predicted treatment benefits decreased with lower symptom severity but remained minimally important even for very mild symptoms (s.m.d. = −0.33 for PHQ-9 = 5).

Psychological intervention reduces the symptom burden in individuals with subthreshold depression up to 1 year, and protects against symptom deterioration. Benefits up to 2 years are less certain. We find strong support for intervention in subthreshold depression, particularly with PHQ-9 scores ≥ 10. For very mild symptoms, scalable treatments could be an attractive option.

Cognitive deficits may be characteristic for only a subgroup of first-episode psychosis (FEP) and the link with clinical and functional outcomes is less profound than previously thought. This study aimed to identify cognitive subgroups in a large sample of FEP using a clustering approach with healthy controls as a reference group, subsequently linking cognitive subgroups to clinical and functional outcomes.

204 FEP patients were included. Hierarchical cluster analysis was performed using baseline brief assessment of cognition in schizophrenia (BACS). Cognitive subgroups were compared to 40 controls and linked to longitudinal clinical and functional outcomes (PANSS, GAF, self-reported WHODAS 2.0) up to 12-month follow-up.

Three distinct cognitive clusters emerged: relative to controls, we found one cluster with preserved cognition (n = 76), one moderately impaired cluster (n = 74) and one severely impaired cluster (n = 54). Patients with severely impaired cognition had more severe clinical symptoms at baseline, 6- and 12-month follow-up as compared to patients with preserved cognition. General functioning (GAF) in the severely impaired cluster was significantly lower than in those with preserved cognition at baseline and showed trend-level effects at 6- and 12-month follow-up. No significant differences in self-reported functional outcome (WHODAS 2.0) were present.

Current results demonstrate the existence of three distinct cognitive subgroups, corresponding with clinical outcome at baseline, 6- and 12-month follow-up. Importantly, the cognitively preserved subgroup was larger than the severely impaired group. Early identification of discrete cognitive profiles can offer valuable information about the clinical outcome but may not be relevant in predicting self-reported functional outcomes.

Autism spectrum disorder (ASD) symptoms and attention deficit/ hyperactivity disorder (ADHD) symptoms are frequently comorbid with obsessive-compulsive disorder (OCD). However, limited research exists with respect to the relations between these symptoms, and their impact on OC symptom severity.

109 outpatients with primary OCD and 87 healthy controls were administered OCD, ADHD, and ASD questionnaires. Univariate analyses, correlations, and stepwise regression analyses were conducted.

OCD, ADHD, and autism symptoms were highly correlated, with OCD patients showing elevated ADHD as well as autism scores when compared with healthy controls. OCD patients with comorbid ADHD presented with higher autism symptoms and OCD symptoms, yet similar OCD severity scores as OCD without ADHD patients. the attention switching and lack of social skills subscales of the Autism Questionnaire (AQ) were particularly correlated with ADHD and OCD symptoms in the patient group. the AQ subscale attention switching proved to be the most significant predictor of OCD severity and symptoms (with the exception of hoarding). Contrary to expectations, the AQ subscale attention to detail did not predict OCD symptoms, nor did any of the AQ subscale scores predict hoarding symptoms.

OCD patients present with elevated scores of ADHD and ASD symptoms, and these symptoms (particularly attention switching) are important in predicting OC symptoms and severity. It is suggested that problems in attention may be related to the uncertainty about one's own memory as demonstrated by OCDs patients, as well as a common factor underlying comorbid ADHD and ASD symptoms.

Two types of mentalisation-based treatment (MBT) have been developed and empirically evaluated for borderline personality disorder (BPD): day hospital MBT (MBT-DH) and intensive out-patient MBT (MBT-IOP). No trial has yet compared their efficacy.

To compare the efficacy of MBT-DH and MBT-IOP 18 months after start of treatment. MBT-DH was hypothesised to be superior to MBT-IOP because of its higher treatment intensity.

In a multicentre randomised controlled trial (Nederlands Trial Register: NTR2292) conducted at three sites in the Netherlands, patients with BPD were randomly assigned to MBT-DH (n = 70) or MBT-IOP (n = 44). The primary outcome was symptom severity (Brief Symptom Inventory). Secondary outcome measures included borderline symptomatology, personality functioning, interpersonal functioning, quality of life and self-harm. Patients were assessed every 6 months from baseline to 18 months after start of treatment. Data were analysed using multilevel modelling based on intention-to-treat principles.

Significant improvements were found on all outcome measures, with moderate to very large effect sizes for both groups. MBT-DH was not superior to MBT-IOP on the primary outcome measure, but MBT-DH showed a clear tendency towards superiority on secondary outcomes.

Although MBT-DH was not superior to MBT-IOP on the primary outcome measure despite its greater treatment intensity, MBT-DH showed a tendency to be more effective on secondary outcomes, particularly in terms of relational functioning. Patients receiving MBT-DH and MBT-IOP, thus, seem to follow different trajectories of change, which may have important implications for clinical decision-making. Longer-term follow-up and cost-effectiveness considerations may ultimately determine the optimal intensity of specialised treatments such as MBT for patients with BPD.

Current ultra-high-risk (UHR) criteria appear insufficient to predict imminent onset of first-episode psychosis, as a meta-analysis showed that about 20% of patients have a psychotic outcome after 2 years. Therefore, we aimed to develop a stage-dependent predictive model in UHR individuals who were seeking help for co-morbid disorders.

Baseline data on symptomatology, and environmental and psychological factors of 185 UHR patients (aged 14–35 years) participating in the Dutch Early Detection and Intervention Evaluation study were analysed with Cox proportional hazard analyses.

At 18 months, the overall transition rate was 17.3%. The final predictor model included five variables: observed blunted affect [hazard ratio (HR) 3.39, 95% confidence interval (CI) 1.56–7.35, p < 0.001], subjective complaints of impaired motor function (HR 5.88, 95% CI 1.21–6.10, p = 0.02), beliefs about social marginalization (HR 2.76, 95% CI 1.14–6.72, p = 0.03), decline in social functioning (HR 1.10, 95% CI 1.01–1.17, p = 0.03), and distress associated with suspiciousness (HR 1.02, 95% CI 1.00–1.03, p = 0.01). The positive predictive value of the model was 80.0%. The resulting prognostic index stratified the general risk into three risk classes with significantly different survival curves. In the highest risk class, transition to psychosis emerged on average ⩾8 months earlier than in the lowest risk class.

Predicting a first-episode psychosis in help-seeking UHR patients was improved using a stage-dependent prognostic model including negative psychotic symptoms (observed flattened affect, subjective impaired motor functioning), impaired social functioning and distress associated with suspiciousness. Treatment intensity may be stratified and personalized using the risk stratification.

Minimal efficacy differences have been found between cognitive behavioral therapy (CBT) and psychodynamic therapies for depression, but little is known about patient characteristics that might moderate differential treatment effects. We aimed to generate hypotheses regarding such potential prescriptive factors.

We conducted post-hoc model-based recursive partitioning analyses alongside a randomized clinical trial comparing the efficacy of CBT and short-term psychodynamic supportive psychotherapy (SPSP). Severely depressed patients received additional antidepressant medication. We included 233 adults seeking treatment for a major depressive episode in psychiatric outpatient clinics, who completed post-treatment assessment. Post-treatment mean Hamilton Depression Rating Scale scores constituted the main outcome measure.

While treatment differences (CBT v. SPSP) were minimal in the total sample of patients (d = 0.04), model-based recursive partitioning indicated differential treatment efficacy in certain subgroups of patients. SPSP was found more efficacious among moderately depressed patients receiving psychotherapy only who showed low baseline co-morbid anxiety levels (d = −0.40) and among severely depressed patients receiving psychotherapy and antidepressant medication who reported a duration of the depressive episode of ⩾1 year (d = −0.31), while CBT was found more efficacious for such patients reporting a duration <1 year (d = 0.83).

Our findings are observational and need validation before they can be used to guide treatment selection, but suggest that knowledge of prescriptive factors can help improve the efficacy of psychotherapy for depression. Depressive episode duration and co-morbid anxiety level should be included as stratification variables in future randomized clinical trials comparing CBT and psychodynamic therapy.

It is well known that web-based interventions can be effective treatments for depression. However, dropout rates in web-based interventions are typically high, especially in self-guided web-based interventions. Rigorous empirical evidence regarding factors influencing dropout in self-guided web-based interventions is lacking due to small study sample sizes. In this paper we examined predictors of dropout in an individual patient data meta-analysis to gain a better understanding of who may benefit from these interventions.

A comprehensive literature search for all randomized controlled trials (RCTs) of psychotherapy for adults with depression from 2006 to January 2013 was conducted. Next, we approached authors to collect the primary data of the selected studies. Predictors of dropout, such as socio-demographic, clinical, and intervention characteristics were examined.

Data from 2705 participants across ten RCTs of self-guided web-based interventions for depression were analysed. The multivariate analysis indicated that male gender [relative risk (RR) 1.08], lower educational level (primary education, RR 1.26) and co-morbid anxiety symptoms (RR 1.18) significantly increased the risk of dropping out, while for every additional 4 years of age, the risk of dropping out significantly decreased (RR 0.94).

Dropout can be predicted by several variables and is not randomly distributed. This knowledge may inform tailoring of online self-help interventions to prevent dropout in identified groups at risk.

Although there is evidence for the effectiveness of interventions for psychosis among ultra-high-risk (UHR) groups, health economic evaluations are lacking. This study aimed to determine the cost effectiveness and cost–utility of cognitive–behavioural therapy (CBT) to prevent first-episode psychosis.

The Dutch Early Detection and Intervention Evaluation study was a randomized controlled trial of 196 UHR patients with an 18-month follow-up. All participants were treated with routine care (RC) for non-psychotic disorders. The experimental group (n = 95) received add-on CBT to prevent first-episode psychosis. We report the intervention, medical and travel costs, as well as costs arising from loss of productivity. Treatment response was defined as psychosis-free survival and quality-adjusted life years (QALYs) gained.

In the cost-effectiveness analysis, the proportion of averted psychoses was significantly higher in the CBT condition (89.5% v. 76.2%). CBT showed a 63.7% probability of being more cost effective, because it was less costly than RC by US$844 (£551) per prevented psychosis. In the cost–utility analysis, QALY health gains were slightly higher for CBT than for RC (0.60 v. 0.57) and the CBT intervention had a 52.3% probability of being the superior treatment because, for equal or better QALY gains, the costs of CBT were lower than those of RC.

Add-on preventive CBT for UHR resulted in a significant reduction in the incidence of first psychosis. QALY gains show little difference between the two conditions. The CBT intervention proved to be cost saving.

There is an increasing interest in cognitive–behavioural therapy (CBT) interventions targeting negative symptoms in schizophrenia. To date, CBT trials primarily focused on positive symptoms and investigated change in negative symptoms only as a secondary outcome. To enhance insight into factors contributing to improvement of negative symptoms, and to identify subgroups of patients that may benefit most from CBT directed at ameliorating negative symptoms, we reviewed all available evidence on these outcomes.

A systematic search of the literature was conducted in PsychInfo, PubMed and the Cochrane register to identify randomized controlled trials reporting on the impact of CBT interventions on negative symptoms in schizophrenia. Random-effects meta-analyses were performed on end-of-treatment, short-term and long-term changes in negative symptoms.

A total of 35 publications covering 30 trials in 2312 patients, published between 1993 and 2013, were included. Our results showed studies’ pooled effect on symptom alleviation to be small [Hedges’ g = 0.093, 95% confidence interval (CI) −0.028 to 0.214, p = 0.130] and heterogeneous (Q = 73.067, degrees of freedom = 29, p < 0.001, τ2 = 0.081, I2 = 60.31) in studies with negative symptoms as a secondary outcome. Similar results were found for studies focused on negative symptom reduction (Hedges’ g = 0.157, 95% CI −0.10 to 0.409, p = 0.225). Meta-regression revealed that stronger treatment effects were associated with earlier year of publication, lower study quality and with CBT provided individually (as compared with group-based).

The co-occurring beneficial effect of conventional CBT on negative symptoms found in older studies was not supported by more recent studies. It is now necessary to further disentangle effective treatment ingredients of older studies in order to guide the development of future CBT interventions aimed at negative symptom reduction.

Research into age of onset in obsessive–compulsive disorder (OCD) has indicated significant differences between patients with early and late onset of the disorder. However, multiple criteria have been used arbitrarily for differentiating between early- and late-onset OCD, rendering inconsistent results that are difficult to interpret.

In the current study, admixture analysis was conducted in a sample of 377 OC patients to determine the number of underlying populations of age of onset and associated demographic and clinical characteristics. Various measures of anxiety, depression, co-morbidity, autism, OCD, tics and attention deficit hyperactivity disorder (ADHD) symptoms were administered.

A bimodal age of onset was established and the best-fitting cut-off score between early and late age of onset was 20 years (early age of onset ⩽19 years). Patients with early age of onset were more likely to be single. Early age of onset patients demonstrated higher levels of OCD severity and increased symptoms on all OCD dimensions along with increased ADHD symptoms and higher rates of bipolar disorder.

It is suggested that 20 years is the recommended cut-off age for the determination of early versus late age of onset in OCD. Early age of onset is associated with a generally graver OCD clinical picture and increased ADHD symptoms and bipolar disorder rates, which may be related to greater functional implications of the disorder. We propose that age of onset could be an important marker for the subtyping of OCD.