Aims were to assess the efficacy of metacognitive training (MCT) in people with a recent onset of psychosis in terms of symptoms as a primary outcome and metacognitive variables as a secondary outcome.

A multicenter, randomized, controlled clinical trial was performed. A total of 126 patients were randomized to an MCT or a psycho-educational intervention with cognitive-behavioral elements. The sample was composed of people with a recent onset of psychosis, recruited from nine public centers in Spain. The treatment consisted of eight weekly sessions for both groups. Patients were assessed at three time-points: baseline, post-treatment, and at 6 months follow-up. The evaluator was blinded to the condition of the patient. Symptoms were assessed with the PANSS and metacognition was assessed with a battery of questionnaires of cognitive biases and social cognition.

Both MCT and psycho-educational groups had improved symptoms post-treatment and at follow-up, with greater improvements in the MCT group. The MCT group was superior to the psycho-educational group on the Beck Cognitive Insight Scale (BCIS) total (p = 0.026) and self-certainty (p = 0.035) and dependence self-subscale of irrational beliefs, comparing baseline and post-treatment. Moreover, comparing baseline and follow-up, the MCT group was better than the psycho-educational group in self-reflectiveness on the BCIS (p = 0.047), total BCIS (p = 0.045), and intolerance to frustration (p = 0.014). Jumping to Conclusions (JTC) improved more in the MCT group than the psycho-educational group (p = 0.021). Regarding the comparison within each group, Theory of Mind (ToM), Personalizing Bias, and other subscales of irrational beliefs improved in the MCT group but not the psycho-educational group (p < 0.001–0.032).

MCT could be an effective psychological intervention for people with recent onset of psychosis in order to improve cognitive insight, JTC, and tolerance to frustration. It seems that MCT could be useful to improve symptoms, ToM, and personalizing bias.

Patients with psychosis display the so-called ‘Jumping to Conclusions’ bias (JTC) – a tendency for hasty decision-making in probabilistic reasoning tasks. So far, only a few studies have evaluated the JTC bias in ‘at-risk mental state’ (ARMS) patients, specifically in ARMS samples fulfilling ‘ultra-high risk’ (UHR) criteria, thus not allowing for comparisons between different ARMS subgroups.

In the framework of the PREVENT (secondary prevention of schizophrenia) study, a JTC task was applied to 188 patients either fulfilling UHR criteria or presenting with cognitive basic symptoms (BS). Similar data were available for 30 healthy control participants matched for age, gender, education and premorbid verbal intelligence. ARMS patients were identified by the Structured Interview for Prodromal Symptoms (SIPS) and the Schizophrenia Proneness Instrument – Adult Version (SPI-A).

The mean number of draws to decision (DTD) significantly differed between ARM -subgroups: UHR patients made significantly less draws to make a decision than ARMS patients with only cognitive BS. Furthermore, UHR patients tended to fulfil behavioural criteria for JTC more often than BS patients. In a secondary analysis, ARMS patients were much hastier in their decision-making than controls. In patients, DTD was moderately associated with positive and negative symptoms as well as disorganization and excitement.

Our data indicate an enhanced JTC bias in the UHR group compared to ARMS patients with only cognitive BS. This underscores the importance of reasoning deficits within cognitive theories of the developing psychosis. Interactions with the liability to psychotic transitions and therapeutic interventions should be unravelled in longitudinal studies.

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.