Patients need to experience for themselves the merits of taking medication before accepting the need to take them long-term. Psychoeducational and cognitive-behavioral interventions need to be targeted at changing attributions to current positive symptoms. The presence of a key person in the community is crucial to improve compliance.

Aims and methodTo assess junior doctors' knowledge of the procedures involved in involuntary admission of patients detained under Sections 5(2), 2 and 3 of the Mental Health Act 1983. A semi-quantitative research study of junior trainees affiliated to two psychiatry training schemes was carried out.ResultsTrainees' knowledge of professionally relevant sections of the Mental Health Act was patchy. Knowledge correlated significantly with experience in clinical practice and with experience of using mental health legislation. Surprisingly, in-service training in mental health legislation had no effect on participants' knowledge.Clinical implicationsLack of knowledge and understanding raises the possibility of inappropriate use of the mental health legislation. This threatens patients' fundamental rights and can lead to complaints or litigation. There is a clear need to address this at an early stage in psychiatry training.

Background: Schizophrenia, a severe psychological disorder, shows symptoms such as hallucinations and delusions. In addition, patients with schizophrenia often exhibit a deficit in working memory which adversely impacts the attentiveness and the behavioral characteristics of a person. Although several clinical efforts have already been made to study working memory deficit in schizophrenia, in this paper, we investigate the applicability of a machine learning approach for identification of the brain regions that get affected by schizophrenia leading to the dysfunction of the working memory. Methods: We propose a novel scheme for identification of the affected brain regions from functional magnetic resonance imaging data by deploying group independent component analysis in conjunction with feature extraction based on statistical measures, followed by sequential forward feature selection. The features that show highest accuracy during the classification between healthy and schizophrenia subjects are selected. Results: This study reveals several brain regions like cerebellum, inferior temporal gyrus, superior temporal gyrus, superior frontal gyrus, insula, and amygdala that have been reported in the existing literature, thus validating the proposed approach. We are also able to identify some functional changes in the brain regions, such as Heschl gyrus and the vermian area, which have not been reported in the literature involving working memory studies amongst schizophrenia patients. Conclusions: As our study confirms the results obtained in earlier studies, in addition to pointing out some brain regions not reported in earlier studies, the findings are likely to serve as a cue for clinical investigation, leading to better medical intervention.

No abstract

No abstract