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Many patients with bipolar II disorder (BPII) prefer to be more informed and involved in their treatment decision-making than they currently are. Limited knowledge and involvement in one's treatment is also likely to compromise optimal BPII management. This Phase II RCT aimed to evaluate the acceptability, feasibility, and safety of a world-first patient decision-aid website (e-DA) to improve treatment decision-making regarding options for relapse prevention in BPII. The e-DA's potential efficacy in terms of improving quality of the decision-making process and quality of the decision made was also explored.

The e-DA was based on International Patient Decision-Aid Standards and developed via an iterative co-design process. Adults with BPII diagnosis (n = 352) were recruited through a specialist outpatient clinical service and the social media of leading mental health organisations. Participants were randomised (11) to receive standard information with/without the e-DA (Intervention versus Control). At baseClinical Trials Registry ACTRN12617000840381 (prospectively registered 07/06/2017).

The evaluation process of French medical students will evolve in the next few years in order to improve assessment validity. Script concordance testing (SCT) offers the possibility to assess medical knowledge alongside clinical reasoning under conditions of uncertainty. In this study, we aimed at comparing the SCT scores of a large cohort of undergraduate medical students, according to the experience level of the reference panel.

In 2019, the authors developed a 30-item SCT and sent it to experts with varying levels of experience. Data analysis included score comparisons with paired Wilcoxon rank sum tests and concordance analysis with Bland & Altman plots.

A panel of 75 experts was divided into three groups 31 residents, 21 non-experienced physicians (NEP) and 23 experienced physicians (EP). Among each group, random samples of N = 20, 15 and 10 were selected. A total of 985 students from nine different medical schools participated in the SCT examination. learn more No matter the size of the panel (N = 20, 15 or 10), students' SCT scores were lower with the NEP group when compared to the resident panel (median score 67.1 vs 69.1, p < 0.0001 if N = 20; 67.2 vs 70.1, p < 0.0001 if N = 15 and 67.7 vs 68.4, p < 0.0001 if N = 10) and with EP compared to NEP (65.4 vs 67.1, p < 0.0001 if N = 20; 66.0 vs 67.2, p < 0.0001 if N = 15 and 62.5 vs 67.7, p < 0.0001 if N = 10). Bland & Altman plots showed good concordances between students' SCT scores, whatever the experience level of the expert panel.

Even though student SCT scores differed statistically according to the expert panels, these differences were rather weak. These results open the possibility of including less-experienced experts in panels for the evaluation of medical students.

Even though student SCT scores differed statistically according to the expert panels, these differences were rather weak. These results open the possibility of including less-experienced experts in panels for the evaluation of medical students.

Nearly half of all mental health disorders develop prior to the age of 15. Early assessments, diagnosis, and treatment are critical to shortening single episodes of care, reducing possible comorbidity and long-term disability. In Norway, approximately 20% of all children and adolescents are experiencing mental health problems. To address this, health officials in Norway have called for the integration of innovative approaches. A clinical decision support system (CDSS) is an innovative, computer-based program that provides health professionals with clinical decision support as they care for patients. CDSS use standardized clinical guidelines and big data to provide guidance and recommendations to clinicians in real-time. IDDEAS (Individualised Digital DEcision Assist System) is a CDSS for diagnosis and treatment of child and adolescent mental health disorders. The aim of IDDEAS is to enhance quality, competency, and efficiency in child and adolescent mental health services (CAMHS).

IDDEAS is a mixed-method788. Ongoing study, registered prospectively 8 April 2020 https//doi.org/10.1186/ISRCTN12094788.

Diabetes mellitus is a common chronic disease and a severe public health issue. The incidence trends for type 1 diabetes (TIDM) and type 2 diabetes (T2DM) have rarely been studied on a global scale. We aimed to determine the temporal and geographical trends of diabetes globally.

Data on diabetes mellitus, including incidence, prevalence from 1990 to 2017 were obtained from the 2017 Global Burden of Disease study. We calculated the estimated annual percentage changes (EAPCs) in age-standardized incidence rate (ASIR) of diabetes mellitus according to sex, region, and disease type.

The worldwide incident cases of diabetes mellitus has increased by 102.9% from 11,303,084 cases in 1990 to 22,935,630 cases in 2017 worldwide, while the ASIR increased from 234 /100,000 persons (95% UI, 219-249) to 285/100,000 persons (95% UI, 262-310) in this period [EAPC = 0.87, 95% confidence interval (CI)0.79-0.96]. The global ASIRs of T1DM and T2DM both demonstrated significant increase during 1990-2017, with EAPCs of 0.34 (95% CI,0.30-0.39) and 0.89 (95% CI,0.80-0.97), respectively. The ASIR trends also varied considerably by regions and countries. The increase in ASIR was greatest in high sociodemographic index regions (EAPC = 1.05, 95% CI0.92-1.17) and lowest in low-SDI regions (EAPC = 0.79, 95% CI0.71-0.88).

Both the number of incident cases and ASIR of diabetes mellitus increased significantly during 1990-2017 worldwide, but the temporal trends varied markedly across regions and countries.

Both the number of incident cases and ASIR of diabetes mellitus increased significantly during 1990-2017 worldwide, but the temporal trends varied markedly across regions and countries.

Clinical decision aids are used in various medical fields to support patients and clinicians when making healthcare decisions. Few attempts have been made to implement such tools in psychiatry. We developed Treatment E-Assist (TREAT); a routine outcome monitoring based computerized clinical decision aid, which generates personalized treatment recommendations in the care of people with psychotic disorders. The aim of this study is to investigate how TREAT is used and evaluated by clinicians and how this tool can be improved.

Clinicians working with TREAT during a clinical trial were asked to participate in semi-structured interviews. The Unified Theory of Acceptance and Use of Technology (UTAUT) was used as a sensitizing theory to structure a part of the interview questions. The transcripts were analyzed using inductive thematic analysis to uncover the main themes.

Thirteen clinicians (mean age 49) of which eight psychiatrists and five nurse practitioners, participated in this study. Eight clinicians experienced TREAT as beneficial, whereas five experienced no additional benefits.