Swedish Mental Health Nurses' Experiences of Portrayals of Mental Illness in Public Media.

News reporting about mental illness lack perspectives of the mentally ill themselves and it is almost exclusively psychiatrists who are accessed when healthcare staff is consulted. The perspective of mental health nurses might contribute to the public understanding of mental illness. The purpose of this study was to describe mental health nurses' experiences of how mental illness is portrayed in media. Eight semi-structured interviews were conducted with qualified mental health nurses. A qualitative content analysis resulted in three categories: Negative portrayals of mental illness, Inconclusive images of mental illness and Biased dissemination of different perspectives. The conclusion of this study is that mental health nurses experience media portrayals of mental illness as negative and misleading with too much emphasis on the medical perspective while a holistic mental health nursing perspective is heavily obscured. Mental health nurses need to take a more prominent role in public reporting on mental health to resolve the current lack of relevant facts regarding mental illness. Further research is needed regarding portrayals of mental illness in social media and how the current lack of perspectives affects public perceptions of mental illness. In addition, further studies regarding the viewpoints of journalists reporting on mental illness are required.

Postmortem metabolomics as a high-throughput cause-of-death screening tool for human death investigations.

Autopsy rates are declining globally, impacting cause-of-death (CoD) diagnoses and quality control. Postmortem metabolomics was evaluated for CoD screening using 4,282 human cases, encompassing CoD groups: acidosis, drug intoxication, hanging, ischemic heart disease (IHD), and pneumonia. Cases were split 3:1 into training and test sets. High-resolution mass spectrometry data from femoral blood were analyzed via orthogonal-partial least squares discriminant analysis (OPLS-DA) to discriminate CoD groups. OPLS-DA achieved an R2 = 0.52 and Q2 = 0.30, with true-positive prediction rates of 68% and 65% for training and test sets, respectively, across all groups. Specificity-optimized thresholds predicted 56% of test cases with a unique CoD, average 45% sensitivity, and average 96% specificity. Prediction accuracies varied: 98.7% for acidosis, 80.5% for drug intoxication, 81.6% for hanging, 73.1% for IHD, and 93.6% for pneumonia. This study demonstrates the potential of large-scale postmortem metabolomics for CoD screening, offering high specificity and enhancing throughput and decision-making in human death investigations.