Search results

Sex and age estimation is important, particularly when information about the deceased is unavailable. There are limited radiological studies investigating side, sex and age differences in normal ankle morphometric parameters. The authors’ goal was to evaluate different ankle joint morphometric measurements and document variations among Egyptians.

A prospective study was conducted throughout 23 months on 203 (100 males and 103 females) adult Egyptians, aged between 20-69 years old, who were referred for a plain x-ray of bilateral normal ankle joints.

Ankle parameters showed no statistical difference between both sides, except for tarsal width (TaW) which was significantly higher on right than left side (26.92 ± 2.66 vs 26.18 ± 2.65 mm). Males showed significantly higher morphometric values except for anteroposterior gap (APG) and talus height (TaH) which were significantly higher in females (2.29 ± 0.80 vs 1.80 ± 0.61 mm and 13.01 ± 1.68 vs 11.87 ± 1.91 mm, respectively). There was significant increase in tibial arc length, APG, distance of level of MTiTh from anterior limit of mortise, distance of level of MTiTh from vertex of mortise, sagittal distance between tibial and talar vertices and sagittal radius of trochlea tali arc in old age group compared to young one. A significant decrease in tibial width, malleolar width, TaW and TaH was noted in old age group compared to young one.

Ankle joints of both sides are mostly symmetrical; however, there are significant differences in most morphometric values due to sex and age factors. These findings may be essential during side, sex and age determination.

This study aims to evaluate healthcare practitioners’ perceptions of electronic health record (EHR) systems and their effectiveness in supporting clinical decision-making in Tanzanian Primary Healthcare (PHC) facilities.

A mixed-methods approach was employed, combining quantitative data from structured questionnaires and qualitative insights from open-ended responses. The study was conducted in the Dodoma region of Tanzania, focusing on a diverse representation of PHC facilities, including district hospitals, health centres and dispensaries. Data were analysed using multiple linear regression for quantitative data, and thematic analysis was applied to qualitative responses.

The results revealed that while EHR systems are widely used in Tanzanian PHC facilities, their impact on clinical decision-making remains limited. Only a moderate portion of practitioners perceived EHR systems as effective in decision support, and frequent system use was negatively correlated with user satisfaction. Challenges such as inadequate training and support, system crashes, slow performance and poor usability and integration into clinical workflows were significant barriers to effectively utilising EHR systems.

This study contributes to the limited literature on EHR system implementation in low-resource settings, specifically Tanzania, by focusing on decision-support features within EHR systems. The findings offer valuable insights for healthcare policymakers, system designers and practitioners to optimise EHR implementation and improve healthcare outcomes in resource-constrained environments.

Competitiveness is an important personality trait that has been studied in various disciplines and has been shown to predict critical work outcomes at the individual level. Despite this, the role of competitiveness in groups and teams has received scant attention amongst organizational researchers. Aiming to promote future research on the role of competitiveness as both an adaptive and maladaptive trait – particularly in the context of work – the authors review competitiveness and its effects on individual and team stress and Well-Being, giving special attention to the processes of cohesion and conflict and situational moderators. The authors illustrate a dynamic multilevel model of individual and team difference factors, competitive processes, and individual and team outcomes to highlight competitiveness as a consequential occupational stressor. Furthermore, the authors discuss the feedback loops that inform the different factors, highlight important avenues for future research, and offer practical solutions for managers to reduce unhealthy competition.

A synthesis of integrated care models classified by their aims and central characteristics does not yet exist. We present a collection of five “archetypes” of integrated care, defined by their aims, to facilitate model comparison and dialogue.

We used a purposive literature search and expert consultation strategy to generate five archetypes. Data were extracted from included articles to describe the characteristics and defining features of integrated care models.

A total of 25 examples of integrated care models (41 papers) were included to generate five archetypes of integrated care. The five archetypes defined include: (1) whole population models, (2) life stage models, (3) disease-focused models, (4) identity group-based models and (5) equity-focused models.

The five presented archetypes offer a conceptual framework for academics, health system decision makers and patients, families, and communities seeking to develop, adapt, investigate or evaluate models of integrated care.

Two cross-cutting themes were identified, including (1) minimal reporting of patient, caregiver and community engagement efforts in integrated care development, implementation and evaluation, and (2) the nuanced emphasis and implementation of electronic data sharing methods across archetypes, and the need for further definition of the role of these data sharing methods.

The chapter provides a comprehensive outline of how technology can be harnessed to promote inclusivity within higher education. The article begins by defining inclusive education and explains how cross-cultural collaboration can be facilitated by technological intervention. The article focuses on how the amalgamation of different theories based on behaviorism, cognitivism, and constructivism is crucial for the successful implementation of inclusive education. It highlights the importance of emerging technologies in promoting inclusive pedagogy. It provides a strategic framework that uses artificial intelligence (AI) and different digital tools to cater the needs and aspirations of diverse and global higher educational institutions. Several case studies are also presented to help in understanding the barriers and corresponding strategies to enhance inclusivity. The impact of the strategy surpasses immediate learning enhancements which contribute to a broader vision for a more equitable, accessible, and interconnected educational ecosystem. The chapter concludes with a discussion on the challenges and ethical considerations for successful implementation of technologies to bring inclusive internationalization to higher education.

This paper aims to examine how bank stress tests affect bank tax planning.

The study uses US bank stress test bank size thresholds and a regression discontinuity design to investigate the effect of the Dodd-Frank Act and the instituted bank stress tests on bank tax planning. We use different measures of tax planning, including bank-specific measures and measures of tax avoidance, tax aggressiveness, and effective tax planning from recent literature. Our regression discontinuity and difference-in-differences regression analyses include bank and year fixed-effects and lagged bank characteristics to control for potential endogeneity.

This study finds that stress tests have the unintended consequences of intensifying tax planning and increasing tax avoidance. Stress-test banks increase tax avoidance by accelerating charge-offs, net interest, and non-interest expenses. However, this increase in tax planning is not optimally maximized, leading to lower effective tax planning compared to non-stress-test banks. Banks with a substantial increase in tax avoidance under the Dodd–Frank Act tend to increase their risk, investing in high-risk-weight assets and lending in riskier loan categories. These findings are consistent with tax minimization conditions under added regulatory attention and policy uncertainty.

Literature on bank tax planning is limited. Most tax avoidance literature excludes financial institutions such as bank holding companies mainly due to differences in business practices and regulatory frameworks. This study is the first to investigate tax planning behavior among US banks. The current study thus extends the research field by examining the effect of bank transparency regulations, such as bank stress tests, on bank tax planning activities. Our findings have a direct bank policy implication. They show that stress testing has the unintended consequences of increasing tax planning activities and consequently increasing risk-taking on banks with high tax avoidance, which goes against the goals of stress testing regulations.

This practice forum paper aims to present a theoretical framework to better develop the required supply chain management (SCM) competencies and the workforce needed for managing public health supply chains.

This framework is driven by iterative systems thinking, a deeper consideration of the SCM labor market and a comprehensive mapping of human resource system requirements. The framework centers around three tools. A labor market analysis assesses factors influencing supply of and demand for health SCM workers in a country context. To improve supply of and demand for workers, the SCM Professionalisation Framework provides reference documents to establish health SCM as a recognized profession. The human resources for SCM Theory of Change explains and assesses the conditions required to achieve optimal workforce performance at the organizational level. The Ministry of Health in Rwanda applied these three tools sequentially to assess and improve the supply and performance of its health SCM workforce.

The authors describe this framework, how the tools were applied in Rwanda, and early impressions of the results.

Practitioners can apply this approach to improve SCM competence and promote the attractiveness of health SCM positions by formalizing their professional status. This could lead to a pool of individuals who seek SCM qualifications and, in time, overcome the current shortage of health SCM workers. Employers can apply this approach to structured roles and workforce needs to meet health SCM system requirements. This would lead to a greater demand for and use of appropriately trained personnel.

This paper presents a novel, iterative, systems-thinking approach to develop human resources in public health supply chains. Rwanda is the first country to apply all three tools using this framework.

This chapter explores the ethical challenges arising from the integration of advanced artificial intelligence (AI) technologies into intelligent manufacturing systems. Machine learning (ML), augmented reality/virtual reality (AR/VR), digital twins, and human–robot collaboration (HRC) redefine industrial production, they bring forth unprecedented efficiencies and capabilities but also introduce complex ethical considerations. The text delves into issues such as data privacy, job displacement, the impact of automation on workforce dynamics, and the psychological effects of working alongside AI-powered systems. Through a detailed examination of these technologies and their implications, the chapter advocates for a dynamic ethical framework that evolves alongside technological advancements. This framework should prioritize human dignity, safety, and rights, involving all stakeholders in its development and implementation. By addressing the ethical implications of AI, AR/VR, digital twins, and HRC, the chapter underscores the necessity of balancing technological innovation with ethical responsibility. It calls for collaborative efforts involving policymakers, industry leaders, workers, and consumers to navigate the ethical landscape of intelligent manufacturing, aiming to harness the potential of these technologies responsibly for the betterment of society and the workforce.

This study investigates the mechanism of defensive word-of-mouth (WOM), which refers to consumers responding to unfair negative online reviews of a brand with which they identify.

Study 1 employs an experimental design that manipulates brand identification and the perceived fairness of negative WOM, using a gift card choice scenario to measure decision-making behavior. Study 2 involves a real event with Google reviews and follows a quasi-experimental design, manipulating identification with the university and using Google Maps star ratings to measure brand attitude.

Consumers with high brand identification are more likely to defend the brand when confronted with unfair negative WOM. However, they do not always exhibit defensive WOM in fair cases. Furthermore, the results show that the defensive WOM can strengthen consumers’ brand attitude and supportive behavior.

Encouraging defensive WOM by mobilizing brand advocates and highlighting the unfairness of negative WOM could be a practical strategy to defend the brand and minimize the risk of online firestorms. Notably, defensive WOM itself strengthens the relationship between consumers and the brand.

This study proposes a mechanism for the defensive WOM phenomenon and demonstrates that the rebound effect in brand attitude caused by negative WOM comes from consumers’ willingness to express defensive WOM. We draw on self-affirmation theory to address the gap in theoretical explanations for defensive WOM. This contributes to the literature on self-identity and WOM research by showing that consumers defend their identities through WOM communication.