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‘Inconvenient truth’: The domestic violence deaths we’re not talking about
No full textRecent cases of mothers allegedly killing their children have exposed an uncomfortable truth about domestic violence, writes Terry Goldsworthy
Legitimising allied health roles in advance care planning: the ACPEd intervention
No full textAbstractAim This research describes a multi-modal Advance Care Planning Education (ACPEd) program aimed primarily at allied health staff and evaluated participants’ i) characteristics; ii) pre- and post-education self-assessed confidence, knowledge and skills; iii) perceived scope of practice, role identity and role legitimacy; and iv) change in clinical practice over time.Background The research literature relating to continuing education outcomes for ACP does not include studies with allied health professionals, focusing predominantly on medical and nursing staff and students. This means that a sizable portion of the workforce may not be prepared to participate in, nor recognise the significance of ACP processes and documents.Methods This research was conducted within the Sunshine Coast Health Service, Queensland, Australia in collaboration with the University of the Sunshine Coast and Queensland Office of Advance Care Planning using a non-randomised, single arm, mixed-methods study to evaluate participant’s responses over time. Quantitative analysis of participants’ experiences before and after participation in the education intervention, and thematic analysis of discussions during an online learning circle 2 months after the intervention was undertaken.Results Four workshops were held over 2 days with 30 participants, of which 80% were from the allied health, and 20% from the nursing workforce. Statistically significant improvements in participants’ self-perceived knowledge, skill and confidence were recorded after the ACPEd program. Participants identified roles for allied health in ACP discussions. Three main themes emerged from the learning circle: 1)’It’s all about priorities’: overcoming the challenges of embedding ACP into clinical practice; 2) ‘That’s a role you can fill’: professional role identity and willingness to participate in ACP, and 3) ‘Keep it on the agenda’: The ACPEd program contribution to role perception and identity.Unique Contribution To our knowledge, this is the first study of ACP education aimed primarily at allied health professionals, that explored role perception and legitimacy and change in clinical practice over time. The mixed-methods approach allowed a rich interpretation of the data, and generated ideas for future practice and research.Implications for Policy or Practice Allied health staff can participate in ACP discussions, and education programs should be considered integral to support working to full scope of practice. Professional organisations could help legitimise allied health professional involvement in ACP through developing position papers that define scope of practice for ACP either separately, or as part of end-of-life clinical guidelines.<br/
Classifying OSHA construction accident reports: leveraging ensemble learning and lightweight large language models (l-LLMs)
No full textPurposeThis study aims to enhance the classification of construction accident reports by addressing challenges including limited high-quality datasets, class imbalance and constraints of traditional machine learning models. A novel framework integrating ensemble learning with lightweight large language models (l-LLMs) is proposed to improve the accuracy, robustness and practical utility of safety management in the construction industry.Design/methodology/approachA dataset of 10,994 Occupational Safety and Health Administration (OSHA) construction accident reports was manually labeled using the Occupational Injury and Illness Classification System (OIICS). To address class imbalance, random oversampling and Synthetic Minority Oversampling Technique (SMOTE) were applied and compared. Five l-LLMs (TinyBERT, MobileBERT, ELECTRA, DistilBERT and ALBERT) were fine-tuned for classification, and three ensemble methods (soft voting, hard voting and stacking) were evaluated.FindingsRandom oversampling substantially improved performance, whereas SMOTE decreased effectiveness. Ensemble classifiers consistently outperformed individual large language models (LLMs), with the soft-voting ensemble achieving the highest F1 score (0.9261 ± 0.0063), surpassing baseline models support vector machine (SVM), Naïve Bayes (NB) and long short-term memory (LSTM) network. The results demonstrate the framework’s ability to accurately classify rare and complex accident types, supporting early hazard detection, targeted safety training and risk mitigation strategies.Originality/valueThe study advances construction safety analytics by integrating ensemble learning with l-LLMs, offering a robust solution for imbalanced textual datasets. It highlights practical applications, including enhanced safety management, decision support and accident prevention, with potential adaptation to other datasets and international contexts. By linking technical innovation to tangible societal and economic benefits, the framework contributes to safer, more efficient construction practices and promotes a culture of safety
Green buys more than gold: Pollution, pay, and attractiveness of small and medium-sized enterprise employer brand
Get PDFObjective: The objective is to examine how signals about the environmental pollution of a Small and Medium-sized Enterprise affect its perceived attractiveness as an employer, and whether higher pay can offset the negative effect of such signals.Research Design & Methods: To test our hypotheses, which required investigation of causal relationships, we used an experimental research design. The participants were Gen Z business students (N = 125). We operationalised employer attractiveness as the intention to recommend the firm as an employer. To analyse data, we used one-way ANOVA with Tukey HSD post-hoc tests after verifying normality and homogeneity of variance.Findings: As expected, pollution information significantly lowered the intention to recommend (ANOVA: F(3, 121) = 11.433, p < 0.001). All three ‘polluting’ conditions scored significantly below the non-polluting control. Even a +50% wage premium did not restore attractiveness to control levels, and pay differences among polluting conditions were not statistically significant.Implications & Recommendations: Environmental harm is a strong negative labour-market signal that compensation alone cannot neutralise. Managers should prioritise real, measurable pollution reductions in employer branding, align HR policies with sustainability and operations to avoid ‘mixed signals’, and account for a hidden ‘recruitment tax’ when environmental performance is poor.Contribution & Value Added: The study extends signalling theory and employer branding research by documenting the ‘dark side’ of environmental signals: negative environmental impact depresses employer attractiveness, and higher pay, even substantial premiums, cannot compensate for this impact. The article offers causal, experimental evidence that clarifies the magnitude of these effects among young job seekers’
Decentralized Digital Asset Research Almanac: Volume 1: 2022
No full textThis almanac provides data and analysis on the performance of the largest DDAs, as measured by market capitalisation at coinmarketcap.com, providing data for academics, policymakers, and the public who research DDAs. The book analyses the performance of the eight largest DDAs, excluding stablecoins and exchange coins
A New Perspective on Alzheimer’s Risk: Index DevelopmentWith ADNI Data
No full textBackgroundAlzheimer's disease (AD) is a prevalent neurodegenerative condition impacting the elderly population. Despite its widespread occurrence, the precise etiological factors remain elusive, emphasizing the critical need for early detection and intervention to mitigate disease progression. This study aims to development of an Alzheimer's Risk Index, a novel tool designed to evaluate socio-demographic factors, lifestyle, medical history, behavioural patterns, and neuropsychological factors contributing to Alzheimer's risk and cognitive decline.MethodIn this study, we used participants aged 55 to 91 from the ADNI database and employed a unique method using Factor Analysis (FA) in the index developmentResultThis study's cutting-edge approach to index development using ADNI database and PCA provides valuable insights into potential associations between the Alzheimer's Risk Index and the prevalence of AD.ConclusionThis index is expected to be easily accessible to the general population as a guidance for seeking medical diagnosis of AD early detection
Imaging abnormalities of the acromioclavicular joint and subacromial space are common in asymptomatic shoulders: a systematic review
Get PDFOBJECTIVES: To determine the prevalence of acromioclavicular (AC) joint and subacromial space imaging abnormalities in asymptomatic adults, with a secondary objective of comparing findings between asymptomatic and symptomatic shoulders within the same study populations.METHODS: We conducted a systematic review of studies examining shoulder imaging abnormalities detected by X-ray, ultrasound (US), computed tomography (CT), and magnetic resonance imaging (MRI) in asymptomatic adults (PROSPERO registration CRD42018090041). This report focuses on AC joint and subacromial space abnormalities. Databases searched included Ovid MEDLINE, Embase, CINAHL and Web of Science from inception to June 2023. Our primary analysis used data from population-based studies, and risk of bias and certainty of evidence were evaluated with tools for prognostic studies.RESULTS: Thirty-one studies (4 X-ray, 11 US, 15 MRI, 1 both X-ray and MRI) provided useable prevalence data. One study was population-based (20 shoulders), 16 included miscellaneous study populations (2436 shoulders) and 14 focused on athletes (708 shoulders). The certainty of evidence was very low mainly due to high risk of bias, imprecision, and indirectness across studies. Clinical diversity precluded pooling. Population-based prevalence of acromioclavicular osteoarthritis (AC OA) ranged from 85% on MRI to 95% on X-ray. In other study populations, AC OA prevalence in asymptomatic shoulders varied from 6 to 47% on X-ray, 1 to 65% on US, and 0 to 82% on MRI. Among eight studies that included both asymptomatic and symptomatic shoulders, AC OA prevalence ranged from 13 to 95% in asymptomatic shoulders and from 20 to 100% in symptomatic shoulders.CONCLUSION: The prevalence of AC joint and subacromial space abnormalities in asymptomatic shoulders is highly variable, and often comparable to that in symptomatic shoulders. Due to the low certainty of evidence and significant variation among study populations, further research is needed to clarify these prevalence estimates and to guide evidence-based management of shoulder abnormalities
Implementation of a data-driven quality improvement program in primary care for patients with coronary heart disease: a mixed methods evaluation of acceptability, satisfaction, barriers and enablers
No full textBackground:The study aimed to understand the acceptability, satisfaction, uptake, utility and feasibility of a quality improvement (QI) intervention to improve care for coronary heart disease (CHD) patients in Australian primary care practices and identify barriers and enablers, including the impact of COVID-19.Methods:Within the QUality improvement for Effectiveness of care for people Living with heart disease (QUEL) study, 26 Australian primary care practices, supported by five Primary Health Networks (PHN) participated in a 1-year QI intervention (November 2019 - November 2020). Data were collected from practices and PHNs staff via surveys and semi-structured interviews. Quantitative and qualitative data were analysed with descriptive statistics and thematic analysis, respectively.Results:Feedback was received from 64 participants, including practice team members and PHN staff. Surveys were completed after each of six workshops and at the end of the study. Interviews were conducted with a subgroup of participants (n =9). Participants reported positive satisfaction with individual QI features such as learning workshops and monthly feedback reports. Overall, the intervention was well-received, with most participants expressing interest in participating in similar programs in the future. COVID-19 and lack of time were identified as common barriers, whereas team collaboration and effective leadership enabled practices' participation in the QI program. Additionally, 90% of the practices reported COVID-19 effected their participation due to vaccination rollout, telehealth set-up, and continuous operational review shifting their focus from QI. Conclusion:Data-driven QI programs in primary care can boost practice staff confidence and foster increased implementation. Barriers and enablers identified can also support other practices in prioritising effective strategies for future implementation
Unresolved jurisdictional issues in law enforcement access to data
No full textuthored by leading scholars in the field, this handbook delves into the intricate matter of digital evidence collection, adopting a comparative and intra-disciplinary approach. It focuses specifically on the increasingly important role of online service providers in criminal investigations, which marks a new paradigm in the field of criminal law and criminal procedure, raising particular challenges and fundamental questions. This scholarly work facilitates a nuanced understanding of the multi-faceted and cross-cutting challenges inherent in the collection of digital evidence, as it navigates the contours of current and future solutions against the backdrop of ongoing European and international policy-making. As such, it constitutes an indispensable resource for scholars and practitioners alike, offering invaluable insights into the evolving landscape of digital evidence gathering