Purpose Although study has shown that electronic performance monitoring (EPM) may have a positive impact on employee performance, it has also been suggested that it may lead to employee stress and dissatisfaction, which may inhibit performance. This study aims to provide a balanced perspective on this conflicting issue by using social information theory as an overarching framework. In addition, SIP theory was further refined by integrating attribution theory to reveal the conditions under which monitoring is most effective. Design/methodology/approach First, the authors conducted a series of confirmatory factor analyses (CFAs) using Mplus 8.3 software to assess the measurement validity of the model. A path model was then developed using maximum likelihood to test all hypotheses. Specifically, EPM was used as the independent variable, control attribution and feedback attribution as moderators, employees’ work goal progress and perceived privacy violation as mediators, and employees’ task performance as the outcome variable. Demographic variables (gender, age, education, tenure in current organization), LMX, positive affect and negative affect were entered into the model as control variables. Parametric bootstrap was used to test the mediator and the moderated mediator (5,000 repetitions, forming a 95% confidence interval) and construct the full path model. Findings The authors propose that EPM improves task performance by stimulating employees’ perception of work goal progress. Correspondingly, EPM will also stimulate employees’ perception of privacy violation, which will have an adverse impact on task performance. In addition, the authors consider employees’ different attributions of organizational implementation of EPM as moderators in the model and propose that feedback attributions strengthen the positive path of EPM-work goal progress-task performance and weaken the negative path of EPM-perceived privacy violation-task performance, while control attributions strengthen the negative path and weaken the positive path. The results supported most of the authors’ hypotheses. Research limitations/implications First, all variables were self-reported, which may lead to common method bias. However, some research suggests that self-reporting is not only an appropriate method for exploring issues within the realm of personal experience, but in some situations it is even superior to the evaluation of others. Nevertheless, the authors encourage future research to adopt multi-source data. Second, despite the use of a time-lagged design, causality could not be established. Therefore, future research is encouraged to use experiments to manipulate EPM and attributions to establish causal relationships between the variables. Third, the study was conducted in one country. In the future, this study can be replicated in other countries to solve relatively limited universal problems. Practical implications First, the research shows that EPM practice can effectively improve employees’ task performance, and the implementation of EPM is of great significance to both individual employees and organizations. However, although these technologies have significant advantages in improving work efficiency and optimizing performance management, the authors must also be wary of their potential adverse effects. Therefore, when introducing these advanced technologies, companies should carefully evaluate their potential negative effects to ensure that the application of technology will not have a negative impact on the well-being of employees. Second, the findings reveal that EPM practices do not always achieve the expected results. Therefore, if the company’s goal is to promote employees to make feedback attributions, it should formulate reasonable monitoring policies, explain the purpose of monitoring, and make monitoring more transparent to protect employee privacy and reduce the negative impact caused by privacy violation perception. Social implications With the continuous advancement of technology, EPM technology is also developing continuously, and more and more advanced technologies are being applied to employees’ performance management. For example, artificial intelligence and big data analysis technologies enable companies to monitor employees’ work performance in real time, generate detailed performance reports and provide personalized feedback. The study helps provide a theoretical basis for companies to balance efficiency and employee welfare, optimize management strategies and enhance the fairness of the work environment and employee satisfaction when implementing EPM. Originality/value First, innovation in theoretical perspective: social information processing (SIP) theory is systematically introduced into the field of e-performance monitoring research for the first time, providing a more balanced perspective on the contradictory views of EPM on employee performance. Second, research paradigm innovation: expanding the application scenarios and explanatory effectiveness of SIP theory. Most of the previous studies on SIP have focused on the effects and influence of leaders as information sources on employee behavior, while there is still a theoretical gap in the information transfer mechanism of human resource management practices. This study extends contextual cueing research from leadership behavior to HRTS by introducing SIP theory. Third, theoretical integration innovation: coupling SIP theory and attribution theory to build a comprehensive analysis model.

The digitalization of Indonesia’s judiciary has generated new ethical challenges for the legal profession, particularly in relation to access and use of electronic evidence. Key concerns include potential breaches of data confidentiality, manipulation of digital evidence, and the absence of clear ethical standards governing advocates in e-court proceedings. Current procedural law and the advocates’ code of ethics do not adequately address the complexities of electronic evidence, which inevitably raise issues of privacy, cybersecurity, and procedural justice. This study aims to examine the ethical dilemmas faced by lawyers in digital litigation in Indonesia and to formulate both normative and institutional solutions to strengthen professional accountability. Employing normative legal research in statutory, conceptual, and philosophical approaches, supported by case analysis involving evidence, the study highlights a regulatory gap in the advocates’ code of ethics and deficiencies in ethical oversight mechanisms. Missed leading in legal practices, especially in the electronic court, where everyone can access electronic evidence to support the need for regulation to protect electronic evidence in the electronic court. The findings suggest the need for reform through the incorporation of specific standards on electronic evidence within the code of ethics, enhancement of lawyers’ digital literacy, and establishment of technical guidelines by professional organizations and the Supreme Court.

Purpose This study examines the dual impact of artificial intelligence (AI) on business processes by systematically identifying and prioritizing both its value-creating benefits (bright-side) and risk-inducing consequences (dark-side). The study further aims to develop an integrated theoretical framework that explains how organizations can balance these opposing effects to achieve sustainable AI-driven business transformation. Design/methodology/approach A content-driven review of recent peer-reviewed literature was conducted to identify key positive and negative impacts of AI across five business process dimensions. Expert evaluations from 42 professionals were analyzed using the Fuzzy Technique for Order Preference by Similarity to Ideal Solution method to prioritize these impacts under uncertainty. Sensitivity analysis was performed to validate the robustness of the results, and an integrated theoretical framework was developed based on the empirical findings. Findings The results reveal that AI delivers its strongest benefits through enhanced financial risk forecasting, internal control, sustainability reporting and customer-facing automation, significantly improving operational efficiency and decision quality. However, the findings also highlight critical risks associated with inadequate governance, privacy invasion, ethical lapses and excessive reliance on automated systems. Governance-related risks emerged as the most severe challenges, indicating that the absence of robust ethical and regulatory frameworks can undermine the long-term value of AI adoption. Practical implications The study provides managers and policymakers with a structured decision-support approach to prioritize AI applications while proactively managing ethical, governance and data-related risks. Originality/value This research offers a novel integration of fuzzy multi-criteria decision analysis with theory development to present a balanced, data-driven understanding of AI's dual impact on business processes and organizational sustainability.

The rapid growth of digital technology has transformed the way individuals access education, employment, healthcare, governance, and information. In contemporary India, internet connectivity is no longer a luxury but an essential requirement for meaningful participation in social and economic life. This paper examines whether the Right to Digital Access can be recognized as an integral part of Article 21 of the Constitution of India, which guarantees the Right to Life and Personal Liberty. The background of the study lies in the judicial expansion of Article 21, where courts have interpreted “life” to include dignity, privacy, livelihood, and other essential rights necessary for a meaningful existence. The central research problem addressed in this paper is whether denial or unreasonable restriction of digital access affects the constitutional guarantee of life and liberty. The study also explores the connection between digital access and other fundamental rights, including freedom of speech and expression, equality, education, and privacy. The research adopts a doctrinal and analytical methodology. It relies on constitutional provisions, landmark judicial decisions, scholarly writings, and government policies related to digital infrastructure. Key judgments concerning privacy and internet restrictions have been examined to understand evolving judicial trends. The findings indicate that digital access is closely linked to the realization of multiple fundamental rights. Although it has not yet been expressly declared as an independent fundamental right, judicial reasoning suggests that access to the internet forms an important part of constitutional freedoms in the digital age. The paper concludes that recognizing digital access within the framework of Article 21 would strengthen democratic participation, promote equality, and ensure that technological progress benefits all sections of society. Keywords-Article 21, Right to Digital Access, Digital Divide, Internet Shutdown, Fundamental Rights

AI conversational agents in older adults with chronic disease: A scoping review.

Optimal decision-making and complex analysis in green supply chains considering blockchain and consumer privacy concern

Human activity recognition (HAR) is essential in many applications, such as smart homes, assisted living, healthcare monitoring, rehabilitation, physiotherapy, and geriatric care. Conventional methods of HAR use wearable sensors, e.g., acceleration sensors and gyroscopes. However, they are limited by issues such as sensitivity to position, user inconvenience, and potential health risks with long-term use. Optical camera systems that are vision-based provide an alternative that is not intrusive; however, they are susceptible to variations in lighting, intrusions, and privacy issues. The paper uses an optical method of recognizing human domestic activities based on pose estimation and deep learning ensemble models. The skeletal keypoint features proposed in the current methodology are extracted from video data using PoseNet to generate a privacy-preserving representation that captures key motion dynamics without being sensitive to changes in appearance. A total of 30 subjects (15 male and 15 female) were sampled across 2734 activity samples, including nine daily domestic activities. There were six deep learning architectures, namely, the Transformer (Transformer), Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), Multilayer Perceptron (MLP), One-Dimensional Convolutional Neural Network (1D CNN), and a hybrid Convolutional Neural Network–Long Short-Term Memory (CNN–LSTM) architecture. The results on the hold-out test set show that the CNN–LSTM architecture achieves an accuracy of 98.78% within our experimental setting. Leave-One-Subject-Out cross-validation further confirms robust generalization across unseen individuals, with CNN–LSTM achieving a mean accuracy of 97.21% ± 1.84% across 30 subjects. The results demonstrate that vision-based pose estimation with deep learning is a useful, precise, and non-intrusive approach to HAR in smart healthcare and home automation systems.

Breast Cancer (BC) is the most diagnosed and the second most frequent cause of death among women. Despite the wide application of mammography as a screening technique, the low sensitivity of this technique in dense breasts, and the risks of radiation are significant disadvantages. In diagnosing and early treatment planning of breast cancer, medical imaging is very important. This paper provides a framework for the segmentation and 3D reconstruction of breast tumors based on a 3D NIFTI image dataset. The preprocessing step entails using an integration of Non-Local Means (NLM) filter and Sobel edge detector to effectively minimize noise and maintain significant structure of the breast tissue. Among the three deep learning models, including UNet, ResNet, and a hybrid architecture of UNet-ResNet, the segmentation of tumor regions is carried out. These models are tested on traditional measures such as Dice Coefficient and Jaccard Index, with the hybrid UNet-ResNet model performing better than others, with a Dice coefficient of 1.38 and a Jaccard index of 0.08. After the segmentation, the volume of the tumor is estimated through the spatial dimensions of the tumor, and the Marching Cubes algorithm is used to create a 3D image of the cancerous tissue to be easily visualized. To prevent the invasion of patient privacy and data security, the system will involve encryption-based storage, anonymization, and secure access control, which are in line with healthcare data protection. This framework not only enhances the accuracy of tumor segmentation but also ensures safe handling of sensitive MRI data, which eventually helps in making better clinical decisions.

In India, the educational scenario began with the Gurukul system, which later transformed into the modern school system. The concept of schooling came to our country during British colonial rule. After many inventions and research developments, education entered a glorious phase. Nowadays, when we look at our surroundings, a new concept has emerged—AI, the abbreviation of Artificial Intelligence. It has been developing since the nineteenth century, and now in the twenty-first century, its progress has gone far beyond expectations and is still continuously advancing. Our education system is changing day by day, and we are accepting its positive aspects. In our country, development has taken place in almost all sectors. When this technology is properly used in the education system, it provides better opportunities to become more knowledgeable and empowered in every aspect. At the secondary level, education acts as a starting point for students to gain better experiences and opportunities. Through this, students can develop in all aspects and bring out their full potential. Artificial Intelligence has both positive and negative impacts on education. Although it helps students gain knowledge easily and efficiently, it also creates challenges such as data privacy issues, lack of trained teachers, high cost, and misuse by students. Therefore, its implementation must be carefully managed to ensure balanced development.

The study examines the role of Artificial Intelligence (AI) in enhancing teachers’ productivity and classroom management. For this purpose, a “Systematic Literature Review” of twenty-five (25) research papers was selected to analyse the phenomena. To analyse the data, three major themes were developed: a) AI and Teachers' productivity, b) AI and classroom management, and c) barriers and challenges teachers face when using AI tools and systems. To give the theoretical foundation, the Technology Acceptance Model (TAM), the Technological Pedagogical Content Knowledge (TPACK), and the Resource-Based View (RBV) were applied. The findings showed that AI enhances overall Teachers' productivity through advancements in administrative tasks, facilitation of lesson planning and design, content creation, and performance and workload evaluation, ultimately saving time. Moreover, the adoption of AI can enhance classroom management through automation, monitoring and assessment, behavioral tracking, and greater efficiency in the teaching and learning process. However, integration of AI in classroom settings remains challenging for teachers due to insufficient infrastructure, teachers’ resistance, a lack of technical training and skills, data privacy and security issues, ethical considerations, and inadequate institutional support. It can be recommended that implementing various types of training and awareness programs for teachers to enhance their competencies in using AI tools and systems in classroom settings.

Smartphones in cyber warfare raise serious ethical concerns due to a number of factors including obscuring the line between civilian and military technology, how they expose non-combatants to harm, and how they lack clear international regulation. The central ethical issues related to the use of smart phones in cyber warfare include: (1) Civilian vs. Combatant Distinction. Smartphones are primarily civilian devices, yet they can be weaponized allowing civilians to engage in cyber-attacks. This development undermines the principle of distinguishing between combatants and non-combatants, a cornerstone of international humanitarian law. (2) Collateral Damage. Malware or cyber operations launched via smartphones can unintentionally spread to civilian networks, hospitals, or financial systems. Unlike traditional weapons, cyber tools are hard to contain, making unintended harm more likely. (3) Privacy Violations. Smartphones store vast amounts of personal data. Using them in cyber warfare risks mass surveillance, identity theft, and exploitation of private information, raising ethical questions about consent and proportionality. (4) Accountability and Attribution. Cyber-attacks via smartphones are difficult to trace. This creates ambiguity about responsibility, making it harder to hold aggressors accountable under international law. (5) Escalation of Risks. Since smartphones are ubiquitous, their use in cyber warfare lowers the threshold for causing a conflict. Everyday devices could become tools of state-sponsored attacks, increasing the risk of escalation into broader wars. (6) Lack of Regulation. Unlike conventional warfare, cyber warfare has no equivalent of the Geneva or Hague Conventions. The absence of agreed-upon rules leaves smartphone-based attacks in a legal and ethical gray zone. This analysis will identify the ethical and anticipated ethical issues with the use of Smart Phones in Cyberwarfare and the ethical and anticipated ethical issues with identifying smart phones as an important factor in cyber warfare.

As digital transformation accelerates worldwide, personal identity authentication has become a global issue. In South Africa digital personal identity has become central to how individuals interact with government services, financial institutions, and online platforms. Digital identity refers to the authentication of users through personal attributes such as biometric data, voice, image, and behavioural patterns. While these systems offer efficiency and accessibility, they also introduce significant threats. Increasingly, digital personal identity is being cloned, manipulated, or misused through techniques like deepfakes, voice cloning, and biometric spoofing. The discussion examines whether South African law adequately protects individuals against the misuse of digital personal identity, particularly in the context of fraud. While financial gain is a common motive, misuse may also result in reputational harm, privacy violations, and unauthorised commercial exploitation. The analysis considers the legal framework governing digital personality fraud under the Protection of Personal Information Act (POPIA), the Cybercrimes Act, the Consumer Protection Act (CPA), and the common law remedy of actio iniuriarum, within the framework of constitutional rights to dignity and privacy. Comparative insights from Denmark, Tennessee (United States), the European Union, and the United Kingdom help contextualise South Africa’s approach. The discussion argues that while South African law provides substantive protection, enforcement remains challenging due to technological complexity, evidentiary burdens, and limited institutional capacity. Strengthening technical expertise, public awareness, and regulatory enforcement is essential to ensure meaningful protection for digital citizens. Drawing on global approaches, the discussion proposes targeted legal reforms to enhance accountability and safeguard digital personal identity against fraud.

Deepfakes are AI-generated images, videos, and texts that convincingly mimic real individuals. In recent years, such forgeries have proliferated across social media, and their role in fraud cases has increased markedly. However, detection tools often fail in real-world conditions; open-source detectors typically perform only half as well on "in-the-wild" content compared to curated test sets. This performance gap heightens the risk that fabricated content will undermine public trust and foster a climate of suspicion in which even authentic recordings are questioned—a phenomenon known as the "liar's dividend." In this case study, we examine how the July 2025 death of rock icon Ozzy Osbourne became a focal point for deepfake-driven misinformation and public speculation. Following a seated farewell concert in Birmingham, multiple synthetic videos surfaced, including one in which a digitally recreated Osbourne claimed he knew he was about to die. The clips sparked speculation about assisted suicide, prompting his daughter Kelly to publicly denounce the videos as fake and criticise those who shared them. When Osbourne died two weeks later, some commentators treated the deepfake as prophetic, fuelling conspiracy theories and amplifying public grief. This case illustrates broader ethical and governance challenges related to generative AI. Voice cloning and face-swapping services can create convincing media from minimal training data, yet developers rarely address issues of consent or privacy when sourcing material. Psychological factors such as fear of missing out (FOMO) encourage the viral spread of sensational content without verification. This paper’s primary contribution is a theoretical synthesis, which integrates existing technical, psychological, and governance perspectives on deepfake-driven misinformation through a single illustrative case study. Effective countermeasures must combine technical innovations—such as blockchain-based provenance tracking and robust detection—with clear policy frameworks that regulate data use and require transparent labelling of synthetic media. Public education remains essential to help individuals recognise deepfakes and preserve trust in authentic digital communication.

The increasing number of mobile applications in modern society has significantly increased the possibility of security vulnerabilities, particularly as users increasingly rely on these applications for sensitive tasks such as banking, communication, and e-commerce. Any flaw within a mobile application may result in significant privacy violations, financial loss, or data exposure. The development of secure mobile applications presents a persistent challenge, especially for novice developers who often lack the expertise or tools to detect vulnerabilities during the early stages of coding. As mobile platforms become increasingly complex and threats become more sophisticated, integrating effective security practices into the software development lifecycle (SDLC) has become imperative. While a variety of security tools exist to support vulnerability detection, many fail to offer real-time, developer-friendly support embedded directly within Integrated Development Environments (IDEs), leaving a critical security gap, especially for novice developers. This paper conducts a systematic literature review on developer-focused tools available for real-time mobile app security scanning and IDE integration. The review emphasises tools that assist developers directly within Integrated Development Environments (IDEs), focusing on practical support during coding rather than post-deployment analysis. The objective was to thoroughly identify both the strengths and weaknesses of the existing tools that provide real-time mobile app security scanning. The PRISMA 2020 statement, which provides a comprehensive framework for conducting systematic literature reviews, served as the foundational guideline for this study. A thorough search was conducted to retrieve relevant journal articles and conference papers published between 2020 and 2025. This selection criterion ensured that the study incorporated the most recent and relevant findings in the field. Each identified publication was meticulously evaluated for its relevance, quality, and contribution to the existing body of knowledge, thereby enriching the systematic review process. The findings suggest that while existing tools contribute significantly to automation, benchmarking, privacy scanning, malware detection, and dependency management, they remain fragmented and largely external to developer workflows. Most require execution outside the IDE, lack lightweight integration, and fail to deliver real-time vulnerability feedback during coding. Even industry tools such as MobSF, NowSecure, and Checkmarx provide powerful analysis but operate as standalone platforms rather than IDE-embedded solutions. This gap is particularly critical in agile and novice development contexts, where immediate, contextualised security feedback is necessary to prevent vulnerabilities at their source.

Unsupervised domain adaptation for medical image segmentation using adaptogen-perturbation.

Metaverse is a paradigm where people can interact in virtual environments using current technologies. The Metaverse is being advanced by artificial intelligence (AI) as it develops. These technologies have the power to significantly change how people communicate and live. Examples of these integrations include automating repetitive operations, creating customized user experiences based on their preferences and behaviors, and freeing up resources for more intricate and creative endeavors. The roles of artificial intelligence (AI) and other cutting-edge technologies in the Metaverse, such as the Internet of Things (IoT), virtual reality (VR), augmented reality (AR), extended reality (XR), and natural language processing (NLP), are comprehensively reviewed in this study. A systematic literature review was used to successfully achieve the goals of this study. In addition to addressing the research topics, this systematic evaluation of the literature aims to improve the understanding of security and privacy issues in metaverse for suggestive solutions. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline were used in this work to ensure transparency. Despite being hailed as a promising new technology, early experiences in Metaverse suggest that security procedures need to be strengthened and issues addressed for fulfilling its promises. Hence, this work attempts to address Metaverse Security issues by leveraging on zero-trust principles where Zero Trust Architecture (ZTA) frameworks for Metaverse are examined with the aim of enhancing security in the applications of metaverse.

Medical application is an effective extension of traditional medicine, which can provide users with convenient medical health and management services. However, how to improve the continuous acceptance and use of medical applications and relieve medical pressure has become an urgent issue to be explored. This study was intended to reveal the factors influencing the continuance intention of medical applications among the elderly. This study integrated the Value-Based Adoption Model, technology acceptance model, expectation confirmation theory, and trust model to construct an acceptance model for the continuous use of medical applications in the elderly. Quantitative empirical research was carried out by questionnaire survey and structural equation model. The results showed that confirmation significantly affected perceived ease of use and perceived usefulness. The perceived value, trust, satisfaction, perceived ease of use and perceived usefulness had a direct and significant positive effect on the continuance intention of medical applications in the elderly. In addition, perceived usefulness and perceived ease of use had a positive effect on satisfaction and trust. Meanwhile, perceived usefulness, perceived trust and value play a mediating role to some extent. However, the impact of privacy concern on perceived value and continuance intention was not significant. This study has expanded the technology acceptance model and its application, which can provide relevant improvement and optimization measures for medical application developers, providers, managers and researchers. It is expected to improve the user's continuance intention of medical applications, promoting the healthy and sustainable development of mHealth.

Clinician-writers are publishing a growing corpus of personal accounts about their healthcare practices in clinical and general readership journals. For many clinician-writers, personal and creative writing offers a means for expressing both the rewards and the costs of clinical work, while providing a means to honor their patients and bear witness to their suffering. Many accounts include private, intimate moments with patients and families. Emerging at a time of consequential economic changes in healthcare systems, the inclusion of humanities, ethics, and the arts-including creative writing in medical journals-has been recognized to increase professional satisfaction and reduce burnout among physicians but also to deepen comprehension of patients' concerns and to increase patients' trust in their doctors. Alongside digital platforms, clinician-written essays occupy growing space in contemporary medical publishing, influencing larger public discussions about health and society. Publishing such writing creates a complex ethical dilemma regarding patient privacy and confidentiality. In this essay, we reflect on the ethical dimensions that arise when a clinician-writer considers publishing a nonfiction account that describes a patient or exposes private aspects of the writer's self. We review the salient published literature and discuss the divergent ethical stances among clinician-writers regarding the choice to publish their writing and issues surrounding consent from patients to publish descriptions of them. An examination of journal policy guidelines reveals a paucity of attention to the particular contributions of reflective, personal, and creative writing. Instead, most journals seem to rely on informed-consent guidelines for clinical trials to guide writers of personal and creative essays in their ethical decisions. Addressing issues of privacy for patients and trustworthiness of clinicians with insights from humanities and creative disciplines can illuminate patients' perspectives and clinicians' creative contributions to effective care. We suggest initial concrete steps toward that aim.

Human dignity, as a core value of both international and domestic law, demands effective legal protection of personality rights in cross-border situations. This paper examines how private international law addresses conflicts of laws regarding violations of privacy, honor, image, and personal identity in a digitalized and globalized world. It explores the applicable law criteria (lex loci delicti, law of the domicile, party autonomy) and the limits of conflictual autonomy when fundamental rights are at stake. The paper suggests a balanced approach that reconciles state sovereignty with international imperatives regarding personality rights, especially in cases involving extraterritorial elements (e.g., online defamation, unauthorized image publication, commercial misuse of names).

This paper aims to synthesise the current, global evidence on addressing psychological concerns of women presenting with domestic and family violence within the ED and suggest avenues for future research. This discursive paper draws on clinical experience and research of the authors and critical synthesis of current literature on management of victim-survivors of DFV presenting with psychological symptoms in ED. Academic databases and grey literature were systematically searched to identify relevant sources, and findings were narratively synthesised. DFV victim-survivors often present with mental health symptoms in ED; however, many health professionals in EDs fail to correctly identify the underlying trauma and offer support to address DFV. The most reported barriers to DFV screening/identification include time constraints, privacy issues, and lack of education/training about DFV and its support mechanisms. As a result, only mental health symptoms are being treated, ignoring the broader psychosocial needs of DFV victim-survivors. Use of trauma-informed support models is recommended to address the mental and psychosocial needs of DFV victim-survivors visiting the ED. DFV victim-survivors visiting the ED are often treated for their mental health symptoms without addressing their underlying trauma and risk of future victimisation. To address the ongoing adverse impact of DFV, it is necessary to ensure holistic and continual support from ED professionals for victims. The importance of not only education but the implementation of sustained education and training programs surrounding DFV identification, screening, and cannot be understood. DFV is a global problem whereby many victim-survivors become healthcare patients. It would be poor decision making for clinicians to not prioritise appropriate responses to this societal problem within their clinical practice.