The rise of online gambling in Indonesia has emerged as a significant public health concern, driven by various psychological, social, and regulatory factors. Despite stringent laws prohibiting gambling, the accessibility and appeal of online platforms have led to increased participation, particularly among young adults. This phenomenon is characterized by a paradoxical sense of control that users feel while gambling online, which can lead to compulsive behaviors and addiction. The structural characteristics of online gambling platforms, including fast-paced games and easy accessibility, further exacerbate this issue. Social influences, particularly through social media and peer interactions, normalize gambling behaviors, making them more appealing to adolescents. Mental health issues, such as anxiety and depression, are closely linked to online gambling addiction, as individuals may use gambling as a coping mechanism. The COVID-19 pandemic has intensified these challenges, with many individuals turning to online gambling for entertainment during lockdowns. To address the growing prevalence of online gambling addiction, comprehensive regulatory frameworks are needed, alongside responsible gambling initiatives and public awareness campaigns. Collaboration among stakeholders, including government agencies, healthcare providers, and gambling operators, is crucial for effective intervention. Continuous monitoring and evaluation of online gambling trends will inform future policies and help identify emerging risks. By adopting a multifaceted approach, Indonesian policymakers and stakeholders can work towards minimizing the risks associated with online gambling and fostering a healthier environment for its citizens.

This quantitative study explores the influence of organizational culture on the turnover intentions of millennial employees within multinational corporations (MNCs) in Penang, Malaysia. As millennials increasingly comprise a substantial portion of the workforce, their turnover rates have significant implications for organizational efficacy. The research examined the relationship between key elements of organizational culture—namely employee empowerment, work-life balance, and reward systems—and millennials’ decisions to stay with or leave their employers. Data were gathered through a questionnaire distributed to 183 millennial employees in the Penang MNC sector, employing a random sampling approach and utilizing Google Forms for submission. The survey instruments were based on established scales from prior research to ensure robustness and relevance. The findings indicate that all the studied variables significantly affect turnover intentions, with employee empowerment emerging as the strongest predictor, followed by work-life balance, and then reward systems. These results underscore the critical role of organizational culture in shaping millennial turnover intentions. The study’s insights can guide MNCs in Penang to implement strategic initiatives aimed at fostering a positive work environment that emphasizes empowerment, balance, and appropriate rewards, thereby enhancing employee retention within this pivotal demographic. While this study provides detailed insights specific to the Malaysian context, its findings may serve as a preliminary reference point for MNCs in similar regional contexts, suggesting further research to explore the applicability of these insights globally.

Health data governance is essential for optimal processing of data collection, sharing, and reuse. Although the World Health Organization (WHO) has proposed practical guidelines for managing health data during the pandemic, the Organization for Economic Cooperation and Development (OECD) found that many countries still lack the use of health data for decision-making. Therefore, this research aimed to identify and assess the challenges faced by health organization in implementing health data governance from various countries based on research articles. The challenges were assessed based on key components of health data governance from practitioner and scientist perspectives. These components include stakeholder, policy, data management, organization, data governance maturity assessment, and goals. The method used followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for collecting and reporting. Data were collected from several databases online with large repositories of academic studies, including IEEE Xplore, ScienceDirect, National Library of Medicine, ProQuest, Taylor and Francis Group, Scopus, and Wiley Online libraries. Based on the 41 papers reviewed, the results showed that policy was found to be the biggest challenge for health data governance. This was followed by data management such as quality, ownership, and access, as well as stakeholders and data governance organization. However, there were no challenges regarding maturity assessment and data governance goals, as the majority of research focused on implementation. Policy and policymaker awareness were identified as major components for the implementation of health data governance. To address challenges in data management and governance organization, creating committees focused on these components proved to be an effective solution. These results provided valuable recommendations for regulators and leaders in a healthcare organization to optimally implement health data governance.

This research explores the advancement of Artificial Intelligence (AI) in Occupational Health and Safety (OHS) across high-risk industries, highlighting its pivotal role in mitigating the global incidence of occupational incidents and diseases, which result in approximately 2.3 million fatalities annually. Traditional OHS practices often fall short in completely preventing workplace incidents, primarily due to limitations in human-operated risk assessments and management. The integration of AI technologies has been instrumental in automating hazardous tasks, enhancing real-time monitoring, and improving decision-making through comprehensive data analysis. Specific AI applications discussed include drones and robots for risky operations, computer vision for environmental monitoring, and predictive analytics to pre-empt potential hazards. Additionally, AI-driven simulations are enhancing training protocols, significantly improving both the safety and efficiency of workers. Various studies supporting the effectiveness of these AI applications indicate marked improvements in risk management and incident prevention. By transitioning from reactive to proactive safety measures, the implementation of AI in OHS represents a transformative approach, aiming to substantially reduce the global burden of occupational injuries and fatalities in high-risk sectors.

Organizations are gradually focusing on creating a healthy workplace for their employees and becoming more people-centric. This occurs because a healthy workforce increases the work performance of the organisation and the personal development of its employees. This study aims to investigate the HR functions that impact employee motivation in the Malaysian banking sector. The three HR functions that were selected were training and development, rewards and recognition, and career management. The study utilised a cross-sectional design, and the research instruments were adapted from a number of past studies. A total of 350 respondents from the Malaysian banking industry were recruited. Using SPSS Version 26.0, the research hypotheses were examined. The results show that rewards and recognition are not significant predictors of employee motivation in the Malaysian banking industry; however, training and development and career management are significant predictors of employee motivation. These results will help the human resources department develop and improve its HR operations.