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.

There is increasing interest in day-to-day affect fluctuations of patients with depressive and anxiety disorders. Few studies have compared repeated assessments of positive affect (PA) and negative affect (NA) across diagnostic groups, and fluctuation patterns were not uniformly defined. The aim of this study is to compare affect fluctuations in patients with a current episode of depressive or anxiety disorder, in remitted patients and in controls, using affect instability as a core concept but also describing other measures of variability and adjusting for possible confounders.

Ecological momentary assessment (EMA) data were obtained from 365 participants of the Netherlands Study of Depression and Anxiety with current (n = 95), remitted (n = 178) or no (n = 92) DSM-IV defined depression/anxiety disorder. For 2 weeks, five times per day, participants filled-out items on PA and NA. Affect instability was calculated as the root mean square of successive differences (RMSSD). Tests on group differences in RMSSD, within-person variance, and autocorrelation were performed, controlling for mean affect levels.

Current depression/anxiety patients had the highest affect instability in both PA and NA, followed by remitters and then controls. Instability differences between groups remained significant when controlling for mean affect levels, but differences between current and remitted were no longer significant.

Patients with a current disorder have higher instability of NA and PA than remitted patients and controls. Especially with regard to NA, this could be interpreted as patients with a current disorder being more sensitive to internal and external stressors and having suboptimal affect regulation.

Genetic–epidemiological studies that estimate the contributions of genetic factors to variation in tic symptoms are scarce. We estimated the extent to which genetic and environmental influences contribute to tics, employing various phenotypic definitions ranging between mild and severe symptomatology, in a large population-based adult twin-family sample.

In an extended twin-family design, we analysed lifetime tic data reported by adult mono- and dizygotic twins (n = 8323) and their family members (n = 7164; parents and siblings) from 7311 families in the Netherlands Twin Register. We measured tics by the abbreviated version of the Schedule for Tourette and Other Behavioral Syndromes. Heritability was estimated by genetic structural equation modeling for four tic disorder definitions: three dichotomous and one trichotomous phenotype, characterized by increasingly strictly defined criteria.

Prevalence rates of the different tic disorders in our sample varied between 0.3 and 4.5% depending on tic disorder definition. Tic frequencies decreased with increasing age. Heritability estimates varied between 0.25 and 0.37, depending on phenotypic definitions. None of the phenotypes showed evidence of assortative mating, effects of shared environment or non-additive genetic effects.

Heritabilities of mild and severe tic phenotypes were estimated to be moderate. Overlapping confidence intervals of the heritability estimates suggest overlapping genetic liabilities between the various tic phenotypes. The most lenient phenotype (defined only by tic characteristics, excluding criteria B, C and D of DSM-IV) rendered sufficiently reliable heritability estimates. These findings have implications in phenotypic definitions for future genetic studies.

There is a paucity of valid, brief instruments for the assessment of lifetime major depressive disorder (MDD) that can be used in, for example, large-scale genomics, imaging or biomarker studies on depression. We developed the LIfetime Depression Assessment Self-report (LIDAS), which assesses lifetime MDD diagnosis according to DSM criteria, and is largely based on the widely used Composite International Diagnostic Interview (CIDI). Here, we tested the feasibility and determined the sensitivity and specificity for measuring lifetime MDD with this new questionnaire, with a regular CIDI as reference.

Sensitivity and specificity analyses of the online lifetime MDD questionnaire were performed in adults with (n = 177) and without (n = 87) lifetime MDD according to regular index CIDIs, selected from the Netherlands Study of Depression and Anxiety (NESDA) and Netherlands Twin Register (NTR). Feasibility was tested in an additional non-selective, population-based sample of NTR participants (n = 245).

Of the 753 invited persons, 509 (68%) completed the LIDAS, of which 419 (82%) did this online. User-friendliness of the instrument was rated high. Median completion time was 6.2 min. Sensitivity and specificity for lifetime MDD were 85% [95% confidence interval (CI) 80–91%] and 80% (95% CI 72–89%), respectively. This LIDAS instrument gave a lifetime MDD prevalence of 20.8% in the population-based sample.

Measuring lifetime MDD with an online instrument was feasible. Sensitivity and specificity were adequate. The instrument gave a prevalence of lifetime MDD in line with reported population prevalences. LIDAS is a promising tool for rapid determination of lifetime MDD status in large samples, such as needed for genomics studies.

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.

To investigate trajectories of cognitive decline in patients with different types of dementia compared to controls in a longitudinal study.

In 199 patients with Alzheimer's disease (AD), 10 with vascular dementia (VaD), 26 with dementia with Lewy bodies (DLB), 20 with behavioural variant frontotemporal dementia (bvFTD), 15 with language variant frontotemporal dementia (lvFTD) and 112 controls we assessed five cognitive domains: memory, language, attention, executive and visuospatial functioning, and global cognition (Mini-Mental State Examination, MMSE). All subjects had at least two neuropsychological assessments (median 2, range 2–7). Neuropsychological data were standardized into z scores using baseline performance of controls as reference. Linear mixed models (LMMs) were used to estimate baseline cognitive functioning and cognitive decline over time for each group, adjusted for age, gender and education.

At baseline, patients with dementia performed worse than controls in all cognitive domains (p < 0.05) except visuospatial functioning, which was only impaired in patients with AD and DLB (p < 0.001). During follow-up, patients with AD declined in all cognitive domains (p < 0.001). DLB showed decline in every cognitive domain except language and global cognition. bvFTD showed rapid decline in memory, language, attention and executive functioning (all p < 0.01) whereas visuospatial functioning remained fairly stable. lvFTD declined mostly in attention and executive functioning (p < 0.01). VaD showed decline in attention and executive functioning.

We show cognitive trajectories of different types of dementia. These estimations of natural disease course have important value for the design of clinical trials as neuropsychological measures are increasingly being used as outcome measures.

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, τ 2 = 0.081, I 2 = 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.

Over the past few decades, new care models that are more resident-oriented and directed toward small-scale and homelike environments have been developed worldwide. The impact of these care models on the quality of life of residents has been studied. However, little research has been conducted to gain insight into how these new care models influence healthcare staff's work environment. This study focuses on the consequences of small-scale care on staff's perceived job characteristics.

Data were derived from a sample of 136 Dutch living arrangements providing nursing home care for people with dementia (2008/2009), in which 1,327 residents and 1,147 staff participated. The relationship between two indicators of small-scale care (small-scale care characteristics and total number of residents with dementia in facility) and staff's job characteristics (job demands, decision authority, coworker and supervisor support) were studied with multilevel regression analyses. All analyses were adjusted for staff, resident, and living arrangement characteristics when needed.

Both indicators of small-scale care were associated with job demands; staff perceived less time and work pressure as more characteristics of small-scale care were integrated and the facility had less residents with dementia in total. Only one indicator was associated with decision authority. As more characteristics of small-scale care were integrated, staff's perceived decision authority was higher. No relationship was found with coworker and supervisor social support.

Knowing that job demands and decision authority are important predictors of job appraisal and well-being, our findings show that small-scale care could have a beneficial impact on healthcare staff's work environment.