Experiences of individuals presenting to the emergency department for mental health reasons: A systematic mixed studies review.

OBJECTIVE: Emergency departments the world over have seen substantial increases in the number of individuals presenting for mental health reasons. However, we have a limited understanding of their experiences of care. The aim of this review was to systematically examine and synthesise literature relating to the experiences of individuals presenting to emergency department for mental health reasons. METHODS: We followed Pluye and Hong's seven-step approach to conducting a systematic mixed studies review. Studies were included if they investigated adult mental health experiences in emergency department from the users' perspective. Studies describing proxy, carer/family or care provider experiences were excluded. RESULTS: Sixteen studies were included. Thematic synthesis identified three themes and associated subthemes. Theme 1 - ED staff can make-or-break and ED experience - comprised: Feeling understood and heard; Engaging in judgement-free interactions; Receiving therapeutic support; Being actively and passively invalidated for presenting to the ED; and Once a psych patient, always a psych patient. Theme 2 - Being in the ED environment is counter-therapeutic - comprised: Waiting for an 'extremely' long time; and Lacking privacy. Theme 3 was Having nowhere else to go. CONCLUSIONS: The experiences described by individuals presenting to emergency department for mental health reasons were mostly poor. The results illustrate a need for increased mental health education and training for all emergency department staff. Employment of specialist and lived experience workers should also be prioritised to support more therapeutic relationships and emergency department environments. In addition, greater investment in mental health systems is required to manage the current crisis and ensure future sustainability.

On the classification of simple and complex biological images using Krawtchouk moments and Generalized pseudo-Zernike moments: a case study with fly wing images and breast cancer mammograms.

In image analysis, orthogonal moments are useful mathematical transformations for creating new features from digital images. Moreover, orthogonal moment invariants produce image features that are resistant to translation, rotation, and scaling operations. Here, we show the result of a case study in biological image analysis to help researchers judge the potential efficacy of image features derived from orthogonal moments in a machine learning context. In taxonomic classification of forensically important flies from the Sarcophagidae and the Calliphoridae family (n = 74), we found the GUIDE random forests model was able to completely classify samples from 15 different species correctly based on Krawtchouk moment invariant features generated from fly wing images, with zero out-of-bag error probability. For the more challenging problem of classifying breast masses based solely on digital mammograms from the CBIS-DDSM database (n = 1,151), we found that image features generated from the Generalized pseudo-Zernike moments and the Krawtchouk moments only enabled the GUIDE kernel model to achieve modest classification performance. However, using the predicted probability of malignancy from GUIDE as a feature together with five expert features resulted in a reasonably good model that has mean sensitivity of 85%, mean specificity of 61%, and mean accuracy of 70%. We conclude that orthogonal moments have high potential as informative image features in taxonomic classification problems where the patterns of biological variations are not overly complex. For more complicated and heterogeneous patterns of biological variations such as those present in medical images, relying on orthogonal moments alone to reach strong classification performance is unrealistic, but integrating prediction result using them with carefully selected expert features may still produce reasonably good prediction models.