Using machine learning to assist decision making in the assessment of mental health patients presenting to emergency departments.

Objective: The objective of this study was to assess the predictability of admissions to a MH inpatient ward using ML models, based on routine data collected during triage in EDs. This research sought to identify the most effective ML model for this purpose while considering the practical implications of model interpretability for clinical use.

Methods: The study utilised existing data from January 2016 to December 2021.

Sociodemographic Factors and Presentation Features of Individuals Seeking Mental Health Care in Emergency Departments: A Retrospective Cohort Study.

Emergency Department (ED) presentations for Mental Health (MH) help-seeking have been rising rapidly, with EDs as the main entry point for most individuals in Australia. The objective of this retrospective cohort study was to analyse the sociodemographic and presentation features of people who sought mental healthcare in two EDs located in a regional coastal setting in New South Wales (NSW), Australia from 2016 to 2021. This article is a part of a broader research study on the utilisation of machine learning in MH.

Artificial Intelligence in nursing: trustworthy or reliable?

Background: Trustworthiness in Artificial Intelligence (AI) innovation is a priority for governments, researchers and clinicians; however, clinicians have highlighted trust and confidence as barriers to their acceptance of AI within a clinical application. While there is a call to design and develop AI that is considered trustworthy, AI still lacks the emotional capability to facilitate the reciprocal nature of trust.

Aim: This paper aims to highlight and discuss the enigma of seeking or expecting trust attributes from a machine and, secondly, reframe the interpretation of trustworthiness for AI through evaluating its reliability and validity as consistent with the use of other clinical instruments.

Disproportionate mental health presentations to emergency departments in a coastal regional community in Australia of first nation people.

Emergency department (ED) presentations for mental health (MH) help-seeking have been rising rapidly in recent years. This research aims to identify the service usage demographic for people seeking MH care in the ED, specifically in this case, to understand the usage by First Nation people. This retrospective cohort study examined the sociodemographic and presentation characteristics of individuals seeking MH care in two EDs between 2016 and 2021.

The magmatic evolution of South-East Crater (Mt. Etna) during the February-April 2021 sequence of lava fountains from a mineral chemistry perspective.

Unlabelled: The South-East Crater (SEC) at Mt. Etna started a period of lava fountaining in December 2020, producing over 60 paroxysms until February 2022. The activity had an intense sequence from February 16 to April 1, 2021, totaling 17 paroxysmal events separated by repose times varying from 1 to 7 days.

Artificial intelligence (AI) and machine learning (ML) based decision support systems in mental health: An integrative review.

An integrative review investigating the incorporation of artificial intelligence (AI) and machine learning (ML) based decision support systems in mental health care settings was undertaken of published literature between 2016 and 2021 across six databases. Four studies met the research question and the inclusion criteria. The primary theme identified was trust and confidence.

Artificial intelligence: An eye cast towards the mental health nursing horizon.

There has been an international surge towards online, digital, and telehealth mental health services, further amplified during COVID-19. Implementation and integration of technological innovations, including artificial intelligence (AI), have increased with the intention to improve clinical, governance, and administrative decision-making. Mental health nurses (MHN) should consider the ramifications of these changes and reflect on their engagement with AI.

Quantitative chemical mapping of plagioclase as a tool for the interpretation of volcanic stratigraphy: an example from Saint Kitts, Lesser Antilles.

Unlabelled: Establishing a quantitative link between magmatic processes occurring at depth and volcanic eruption dynamics is essential to forecast the future behaviour of volcanoes, and to correctly interpret monitoring signals at active centres. Chemical zoning in minerals, which captures successive events or states within a magmatic system, can be exploited for such a purpose. However, to develop a quantitative understanding of magmatic systems requires an unbiased, reproducible method for characterising zoned crystals.

Evaluation of a general practitioner-led cardiometabolic clinic: Physical health profile and treatment outcomes for clients on clozapine.

The present study is a review of a cardiometabolic clinic for consumers taking clozapine. This clinic was recently established and co-located with the clozapine clinic at a regional hospital in New South Wales, Australia, to enhance engagement and improve the physical health outcomes of consumers taking antipsychotic medication. A descriptive analysis of clients' (n = 73) information collected during routine care for the first 6 months of the clinic's operation, from January 2016 to July 2016, was conducted.