International Journal of Mental Health Nursing最新文献

Waves of psychological research over 50 years have resulted in the development of scales to measure psychological resilience. Multiple psychological resilience definitions and factors have emerged during this time, making its measurement complex. The overall aim of the review was to identify and describe developments in the measurement of psychological resilience in the clinical mental healthcare setting. Specific objectives included (1) consideration of the validity and reliability of psychological resilience scales, (2) the effectiveness of the scales in clinical mental healthcare settings and (3) to identify the scope that resilience factors are addressed in the included scales. It provides a timely update regarding psychological resilience measurement tools and considers further developments that may be required. Between 2011 and 2024, databases were searched, and English-language, peer-reviewed papers with full text were extracted. Eligible studies were those reporting validated existing resilience measures or the outcomes of new measures for use in clinical mental healthcare settings. Seventeen studies met the inclusion criteria. The review demonstrated that psychological resilience measures require further development, particularly focusing on the utility of measurement tools in clinical mental healthcare settings. In this review, we highlight an existing gap in resilience measurement and underscore the need for a new measure of psychological resilience that can effectively assess individuals' subjective experience of their psychological resilience in clinical mental healthcare settings. The currently available psychological resilience measures included in this review do not directly reflect all the factors that might impact a client's depression or anxiety and warrant further research.

Intimate partner violence (IPV) transcends cultural, social and economic boundaries, affecting countless individuals globally. Recovery for IPV survivors is supported by their social networks, yet the readiness of these networks is often poorly understood. This perspective paper proposes an extension to existing network-oriented IPV support models by integrating a focus on the readiness and well-being of informal supporters towards the goal of enhancing IPV survivor recovery through effective networks. This paper presents the extended social network-oriented support model, incorporating the Informal Supporter Readiness Inventory. This tool assesses the readiness of informal supporters, incorporating factors, such as normative and individual beliefs about IPV, and context-specific factors, to enable identification and targeted assistance where needed. Additionally, the proposed model emphasises the importance of supporting the well-being of informal supporters, who frequently endure elevated levels of stress, anxiety and depression. By integrating these elements, the extended social network-oriented support model is designed to help professional supporters foster resilient and sustainable support networks for IPV survivors, with potential applicability across various healthcare disciplines. The extended model underscores the necessity of assessing and fostering both the readiness and well-being of informal supporters to enhance the recovery journey for IPV survivors.

Most domestic and family violence (DFV) research has focused on establishing prevalence and screening rates in public health and community samples. This study sought to address a gap in the literature by evaluating DFV screening and response practices in a private mental healthcare inpatient service and determining if clients of the service had unmet DFV needs. A prospective, convenience sample, mixed methods, cross-sectional survey of adult inpatient mental health consumers was employed. Sixty-two participants completed the Royal Melbourne Hospital Patient Family Violence Survey. Quantitative Likert-type and categorical responses were collated and analysed descriptively (count and percentage). Free-text responses were analysed using qualitative description within a content analysis framework. Sixty-five percent of participants had been screened for at least one DFV issue, on at least one occasion, with 35% not being screened, to their recall. Twenty-three percent reported disclosing DFV concerns, 82% felt very supported by the clinician's response to their disclosure, and 86% were provided with information they found helpful. Unmet needs were identified in 13% of participants, who had wanted to disclose DFV concerns but not feel comfortable to do so. No unscreened respondents disclosed DFV concerns, highlighting the need to uphold best practice guidelines for direct enquiry. Most disclosing clients were positive about the support they received. Indicated areas for improvement were screening rates, active follow-up, increasing psychology support levels and safety planning.

This research addresses the critical issue of identifying factors contributing to admissions to acute mental health (MH) wards for individuals presenting to the emergency department (ED) with MH concerns as their primary issue, notably suicidality. This study aims to leverage machine learning (ML) models to assess the likelihood of admission to acute MH wards for this vulnerable population. Data collection for this study used existing ED data from 1 January 2016 to 31 December 2021. Data selection was based on specific criteria related to the presenting problem. Analysis was conducted using Python and the Interpretable Machine Learning (InterpretML) machine learning library. InterpretML calculates overall importance based on the mean absolute score, which was used to measure the impact of each feature on admission. A person's ‘Age’ and ‘Triage category’ are ranked significantly higher than ‘Facility identifier’, ‘Presenting problem’ and ‘Active Client’. The contribution of other presentation features on admission shows a minimal effect. Aligning the models closely with service delivery will help services understand their service users and provide insight into financial and clinical variations. Suicidal ideation negatively correlates to admission yet represents the largest number of presentations. The nurse's role at triage is a critical factor in assessing the needs of the presenting individual. The gap that emerges in this context is significant; MH triage requires a complex understanding of MH and presents a significant challenge in the ED. Further research is required to explore the role that ML can provide in assisting clinicians in assessment.

Trauma-informed care (TIC) is an approach to healthcare practice that recognises the pervasiveness of trauma, and the deep and life-shaping impact this has on a person. The literature recognises the negative consequences of trauma both to the people who experience it, and the nurses who provide care for them. Professional supervision is an integral element of workforce wellbeing and practice development, and a largely unexplored avenue of support for those who deliver TIC. Strategies for delivery of TIC were clearly articulated in the background literature, however how professional supervision can support nurses who provide this was less obvious. The research aim was to explore the literature related to trauma-informed supervision in nursing to answer the question ‘what skills and strategies can a supervisor use to support nurses who provide TIC in adult populations?’. An integrative review method was used and identified fifteen published articles for inclusion. These were then analysed using a reflexive thematic analysis. Literature all came from the allied health field, due to paucity of literature related to nursing. Analysis revealed three themes that were developed into an emotion–cognition–action sequence; create a safe supervisory relationship; facilitate TIC learning; and build resilience. Discussion noted the intersection of review findings with the Supervision Alliance Model and TIC framework, and where other skills may be integrated to inform a trauma-informed supervisor.

Since 2002, National Outcomes and Casemix Collection of clinician-rated and consumer-rated outcome measures has become part of routine care within Australian clinical mental health services, aiming to ensure that services understand, improve and are accountable for effectiveness of treatment and care provision. Consumer-rated outcome measures, implemented well, support basic human rights of consumers to be asked, heard and included equally in their own care. However, their use has lagged due to clinician inertia, uncertainty about their value to clinical care, assumptions about consumers' capacity to complete the measures and organisational cultural issues that have hampered more holistic assessment, consumer inclusion and care collaboration. Much is known about negative, largely tokenistic use of such measures, poor uptake and dominance of clinical approaches to measurement that privilege clinical expertise; however, little is known about consumers' positive experiences of using consumer-rated measures, Therefore, our aims were as follows: to seek the views and experiences of mental health consumers of using consumer-rated measures in their encounters with clinicians; to understand better whether there were benefits (and if so what) of consumer-rated measures being used in routine mental health practice; to understand how feedback on the use of consumer-rated measures can inform training for mental health staff; and to promote their wider use within mental health services. In-depth interviews conducted with 10 Australian mental health consumers used interview questions co-designed with lived experience and clinical advocates. Descriptive thematic analyses produced four themes emphasising consumers' preferences for completing the measures, the importance of explaining their purpose, how the process validated their feelings and was an opportunity for self-reflection, sense-making, trust-building, and transparency in the encounter and empowerment. This research offers recommendations about the value of effective implementation of consumer-rated measures.

Nurses routinely face psychological challenges as part of their work, acutely so during times of crises when nurses may treat many severely injured and dying patients. While the need for such support is well documented in the literature, mental health support programmes aimed at healthcare workers, even when available, are often underutilised, especially by nurses. To gain insights about needed mental health supports for nurses and programme implementation, this study examines a programme launched following a surprise attack on Israel on 7 October, 2023, resulting in thousands of deaths and injuries and precipitating a war. The programme deployed 30 volunteer nurses trained in cognitive behavioural therapy, trauma support and mental health first aid to offer up to three, anonymous, 30-min online therapy sessions to nurses around Israel in December 2023. Using a qualitative descriptive design, we engaged 22 of these volunteers in one of the three focus groups lasting 60–90 min each. Our findings highlight a range of mental health issues—among both the volunteers and therapy recipients—as well as barriers to providing mental health support to nurses. The importance of normalising the pursuit of mental health support in nursing education and ensuring the availability of support in healthcare organisations was emphasised.

The Dynamic Appraisal of Situational Aggression: Youth Version (DASA:YV) is a brief instrument, most often used by nurses and was specifically designed to assess risk of imminent violence in youth settings. To date, it has been recommended that DASA:YV scores are interpreted in a linear manner, with high scores indicating a greater level of risk and therefore need more assertive and immediate intervention. This study re-analyses an existing data set using contemporary robust data analytic procedures to examine the predictive validity of the DASA:YV, and to determine appropriate risk bands. Mixed effect logistic regression models were used to determine whether the DASA:YV predicted aggression when the observations are correlated. Two approaches were employed to identify and test novel DASA:YV risk bands, where (1) three risk bands as previously generated for the adult DASA were used as a starting point to consider recategorising the DASA:YV into three risk bands, and (2) using a decision tree analysis method known as Chi-square automated interaction detection to produce risk bands. There was no statistically significant difference between a four and three category of risk band. AUC values were 0.85 for the four- and three-category options. A three-category approach is recommended for the DASA:YV. The new risk bands may assist nursing staff by providing more accurate categorisation of risk state. Identification of escalation in risk state may prompt early intervention, which may also prevent reliance on the use of restrictive practices when young people are at risk of acting aggressively.