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Background Model projects for flexible and integrated treatment (FIT) in Germany aim at advancing the quality of care for people with mental disorders. A new FIT model project was established in 2017 at the Department of child and adolescent psychiatry (KJP) of the University Hospital Tübingen (Universitätsklinikum Tübingen, UKT). The study design of EVA_TIBAS presented here describes the evaluation of the FIT model project at the KJP of the UKT. This evaluation aims at quantifying the anticipated FIT model project changes, which are to improve patients’ cross-sectoral care at the same maximum cost as standard care. Methods EVA_TIBAS is a controlled cohort study using a mix of quantitative and qualitative methods. The FIT evaluation consists of three modules. In Module A, anonymized claims data of a statutory health insurance fund will be used to compare outcomes (duration of inpatient and day care psychiatric treatment, inpatient and day care psychiatric length of stay, outpatient psychiatric treatment in hospital, inpatient hospital readmission, emergency admission rate, direct medical costs) of patients treated in the model hospital with patients treated in structurally comparable control hospitals (estimated sample size = ca. 600 patients). In Module B, patient-reported outcomes (health related quality of life, symptom burden, return to psychosocial relationships (e.g. school, friends, hobbies), treatment satisfaction, societal costs) will be assessed quantitatively using validated questionnaires for the model and two control hospitals (estimated sample size = ca. 300 patients). A subsequent health economic evaluation will be based on cost-effectiveness analyses from both the insurance fund’s and the societal perspective. In Module C, about 30 semi-structured interviews will examine the quality of offer, effects and benefits of the service offered by the social service of the AOK Baden-Württemberg (for stabilizing the overall situation of care in the family) in the model hospital. A focus group discussion will address the quality of cooperation between employees of the university hospital and the social services. Discussion The results of this evaluation will be used to inform policy makers whether this FIT model project or aspects of it should be implemented into standard care. Trial registration This study was registered at ClinicalTrials.gov PRS (ID: NCT04727359 , date: 27 January 2021).

Mental illness is known to come along with a large mortality gap compared to thegeneral population and it is a risk for COVID-19 related morbidity andmortality. Achieving high vaccination rates in people with mental illness is therefore important. Reports are conflicting on whether vaccination rates comparable to those of the general population can be achieved and which variables represent risk factors for nonvaccination in people with mental illness. The COVID Ψ Vac study collected routine data on vaccination status, diagnostic groups, sociodemographics, and setting characteristics from in- and day-clinic patients of 10 psychiatric hospitals in Germany in August 2021. Logistic regression modeling was used to determine risk factors for nonvaccination. Complete vaccination rates were 59% ( = 776) for the hospitalized patients with mental illness versus 64% for the regionally and age-matched general population. Partial vaccination rates were 68% ( = 893) for the hospitalised patients with mental illness versus 67% for the respective general population and six percentage ( = 74) of this hospitalized population were vaccinated during the hospital stay. Rates showed a large variation between hospital sites. An ICD-10 group F1, F2, or F4 main diagnosis, younger age, and coercive accommodation were further risk factors for nonvaccination in the model. Vaccination rates were lower in hospitalized people with mental illness than in the general population. By targeting at-risk groups with low-threshold vaccination programs in all health institutions they get in contact with, vaccination rates comparable to those in the general population can be achieved.

IntroductionPsychosis, characterised by chronic symptoms often emerging in youth, imposes a substantial burden on individuals and healthcare systems. While early detection and intervention can mitigate this burden, there is limited evidence on the cost-effectiveness of such approaches. To address this lack of evidence, this study protocol outlines the health economic implications of an artificial intelligence (AI)-based intervention, the Computer-Assisted Risk-Evaluation (CARE), designed to prevent psychosis. The intervention uses AI technologies to enhance the diagnosis and treatment quality for individuals at high risk of psychosis.Methods and analysisThe health economic evaluation has been designed alongside a 12-month multicentre randomised controlled trial comparing CARE with treatment as usual from both payer and societal perspectives. An implementation cost analysis will complement the evaluation, and long-term consequences beyond the trial will be explored descriptively. Based on a literature review, an initial economic logic model will guide subsequent analyses by depicting CARE’s programme theory.The cost-effectiveness assessment will include averted cases of manifest psychosis and quality-adjusted life-years using the EuroQol 5-Dimensions 3-Level instrument. Other effectiveness outcomes will also be incorporated into a cost–consequence analysis. Cost-effectiveness acceptability curves reflecting statistical uncertainty will be constructed, incorporating various payer and societal willingness-to-pay values. The implementation cost analysis will follow a mixed-methods approach to capture facility-specific costs.A dark logic model, emphasising negative outcomes, will be developed to investigate long-term consequences. Further, the initial economic logic model will be refined using trial data and expert interviews. This comprehensive approach aims to provide decision-makers not only with evidence on the cost-effectiveness of CARE, but also with a broader understanding of the implications of the intervention.Ethics and disseminationThe study has received ethical approval and plans to disseminate its findings through publication in a peer-reviewed journal and conference presentations.Trial registration numberNCT05813080.

Background Bipolar disorders (BD) are severe mental illnesses with recurrent depressive and (hypo-)manic episodes and a chronic course. While anecdotal and cross-sectional studies suggest a link between BD and creativity, longitudinal evidence is limited. This study investigates the role of creativity in individuals with varying risk for developing BD, using data from the multicenter, prospective Early-BipoLife study. N  = 1,255 individuals aged 15–35 years were assessed and followed for over two years. Of these, N  = 1,105 were included in the analyses; 150 were excluded due to missing creativity questionnaires. Creativity was measured with the Barron-Welsh Art Scale (BWAS) and the Creative Achievement Questionnaire (CAQ); BD risk was assessed with the EPI bipolar . Analyses included comparisons of mean creativity scores across BD risk groups and logistic regressions testing prospective associations between continuous creativity scores and transition to manifest BD. To enhance clinical applicability, group comparisons and odds ratios (ORs) were also calculated, providing estimates of relative risk across subgroups defined by BD risk status and creativity level. Results At baseline (BL), participants at high BD risk scored significantly higher on the CAQ than those at low risk, while no differences were observed for BWAS scores. During FU, 25 of 1,105 individuals transitioned to manifest BD. Logistic regression analyses did not reveal significant associations between creativity and transitions. However, group comparisons indicated elevated transition likelihood in individuals with high BD risk, with the highest ORs in those combining high BD risk and high creativity (BWAS: OR = 7.05, 95% CI: 1.94–25.56; CAQ: OR = 5.57, 95% CI: 1.88–16.54) compared to low-risk individuals with low creativity. Conclusions High BD risk was associated with higher CAQ scores at BL, suggesting heightened creativity may precede transition. Prospective analyses over two years did not confirm this association, likely due to the small number of transitions. Nonetheless, cross-sectional differences and group comparisons suggest that individuals with both high BD risk and high creativity, particularly real-world accomplishments captured by the CAQ, may show an increased likelihood of transition. These preliminary findings warrant replication in larger, longer-term studies. Importantly, creativity should not be pathologized but considered both as a resource and as a potential modifier of risk trajectories.