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IntroductionThe Global Platform for the Prevention of Autoimmune Diabetes-SINT1A Study is designed as a randomised, placebo-controlled, double-blind, multicentre, multinational, primary prevention study aiming to assess whether daily administration of Bifidobacterium infantis from age 7 days to 6 weeks until age 12 months to children with elevated genetic risk for type 1 diabetes reduces the cumulative incidence of beta-cell autoantibodies in childhood.Methods and analysisInfants aged 7 days to 6 weeks from Germany, Poland, Belgium, UK and Sweden are eligible for study participation if they have a >10.0% expected risk for developing multiple beta-cell autoantibodies by age 6 years as determined by genetic risk score or family history and HLA genotype. Infants are randomised 1:1 to daily administration of B. infantis EVC001 or placebo until age 12 months and followed for a maximum of 5.5 years thereafter. The primary outcome is the development of persistent confirmed multiple beta-cell autoantibodies. Secondary outcomes are (1) Any persistent confirmed beta-cell autoantibody, defined as at least one confirmed autoantibody in two consecutive samples, including insulin autoantibodies, glutamic acid decarboxylase, islet tyrosine phosphatase 2 or zinc transporter 8, (2) Diabetes, (3) Transglutaminase autoantibodies associated with coeliac disease, (4) Respiratory infection rate in first year of life during supplementation and (5) Safety. Exploratory outcomes include allergy, antibody response to vaccines, alterations of the gut microbiome or blood metabolome, stool pH and calprotectin.Ethics and disseminationThe study was approved by the local ethical committees of the Technical University Munich, Medical Faculty, the Technische Universität Dresden, the Medizinische Hochschule Hannover, the Medical University of Warsaw, EC Research UZ Leuven and the Swedish ethical review authority. The results will be disseminated through peer-reviewed journals and conference presentations and will be openly shared after completion of the study.Trial registration numberNCT04769037.

A variety of effective psychotherapies for depression are available, but patients who suffer from depression vary in their treatment response. Combining face-to-face therapies with internet-based elements in the sense of blended treatment is a new approach to treatment for depression. The goal of this study was to answer the following research questions: (1) What are the most important predictors determining optimal treatment allocation to treatment as usual or blended treatment? and (2) Would model-determined treatment allocation using this predictive information and the personalized advantage index (PAI)-approach result in better treatment outcomes? Bayesian model averaging (BMA) was applied to the data of a randomized controlled trial (RCT) comparing the efficacy of treatment as usual and blended treatment in depressive outpatients. Pre-treatment symptomatology and treatment expectancy predicted outcomes irrespective of treatment condition, whereas different prescriptive predictors were found. A PAI of 2.33 PHQ-9 points was found, meaning that patients who would have received the treatment that is optimal for them would have had a post-treatment PHQ-9 score that is two points lower than if they had received the treatment that is suboptimal for them. For 29% of the sample, the PAI was five or greater, which means that a substantial difference between the two treatments was predicted. The use of the PAI approach for clinical practice must be further confirmed in prospective research; the current study supports the identification of specific interventions favorable for specific patients.

Publisher's version (útgefin grein), Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder that is associated with risk-taking behaviors, poor self-control, and interpersonal difficulties. Affected individuals have an increased probability of involvement with the criminal justice system, contributing to a higher rate of arrest, and imprisonment compared with the general population; they are also inadequately treated once sentenced. Because prison staff play a central role in the identification of inmates with mental disorders, they could well be key to improving provision of care. There is however little knowledge of the conceptions, perceptions, and attitudes of prison staff toward ADHD. Such information could help to identify starting points for awareness training and further implementation of specific ADHD treatment. To bridge this gap, we undertook a study based on a qualitatively-driven mixed methods design, combining qualitative data collection in the form of narrative interviews with 19 prison staff from a Swiss correctional facility with quantitative data collection in the form of a survey that included the Attitudes toward Prisoners scale. The interviews were analyzed with QSR NVIVO 11 and a qualitative content analysis approach was used to evaluate findings. Prison staff were generally aware of ADHD and its symptomology, believing it to a be "real," but "fashionable" disorder and favoring hereditary-genetic or biological explanatory models for its development. They viewed inmates with ADHD rather negatively, as complicating correctional efforts, and perceived them as sticking out, as tying up more resources and as frequently being involved in confrontations. Our findings suggest that difficulties in pragmatic aspects of communication and language comprehension may be perceived "as not listening or following instructions," creating additional tensions. Consequently, inmates with ADHD are more often exposed to disciplinary sanctions, such as solitary confinement-an intervention deemed "necessary" by staff. Therefore, staff training on ADHD might need to cover evidence on adverse effects. Non-pharmacological interventions for treatment were preferred and considered to be highly efficacious. Skepticism toward pharmacological treatment prevailed, even when benefits from stimulant medication were described. Interestingly, this skepticism was not the result of negative experiences with the misuse and diversion of stimulants. Acceptance of multimodal treatment among prison staff may require customized strategies.

Background Traumatic war experiences, like the ones the Yazidi had to undergo due to the attack of the so-called Islamic State (ISIS) in August 2014, are often followed by psychological consequences such as posttraumatic stress disorder (PTSD) and depression. A more detailed analysis of such specific survivor groups is needed, to develop and implement appropriate reparation and support measures.MethodsIn this study, 194 Yazidi women were examined. PTSD was assessed using the Essen Trauma Inventory (ETI) and depression using Beck’s Depression Inventory (BDI-II). The potential traumatic event (PTE) and further influential factors were compared between participants with PTSD and those with PTSD and depression, using inferential statistics.Results Participants showed high rates in prevalence and comorbidity for PTSD and depression. Those diagnosed with comorbid PTSD and depression experienced a higher number of PTEs and had been captured more often and for longer compared to those with PTSD. The number of PTEs experienced was then used to predict comorbid PTSD and depression.Conclusion Further research should consider the specific situation and the cultural expression of the Yazidi.

Even though different psychotherapeutic interventions for depression have shown to be effective, patients suffering from depression vary substantially in their treatment response. The goal of this study was to answer the following research questions: (1) What are the most important predictors determining optimal treatment allocation to cognitive behavioral therapy (CBT) or CBT with integrated exposure and emotion-focused elements (CBT-EE)?, and (2) Would model-determined treatment allocation using this predictive information result in better treatment outcomes? Bayesian Model Averaging (BMA) was applied to the data of a randomized controlled trial comparing the efficacy of CBT and CBT-EE in depressive outpatients. Predictions were made for every patient for both treatment conditions and an optimal versus a suboptimal treatment was identified in each case. An index comparing the two estimates, the Personalized Advantage Index (PAI), was calculated. Different predictors were found for both conditions. A PAI of 1.35 BDI-II points for the two conditions was found and 46% of the sample was predicted to have a clinically meaningful advantage in one of the therapies. Although the utility of the PAI approach must be further confirmed in prospective research, the present study study promotes the identification of specific interventions favorable for specific patients.