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The study aims to explore the utilisation of Clinical Decision Support (CDS) tools in Tanzanian healthcare facilities by identifying the tools used, the challenges encountered and the adaptive strategies employed by healthcare practitioners. It utilises an Activity Theory (AT) approach to understand the dynamic interactions between healthcare providers, CDS tools and the broader healthcare system.

The research adopts a qualitative approach in two prominent regions of Tanzania, Dar es Salaam and Dodoma. It involves semi-structured interviews with 26 healthcare professionals and key stakeholders across ten healthcare facilities, supplemented by document reviews. The study employs AT to analyse the interactions between healthcare professionals, CDS tools and the broader healthcare system, identifying best practices and providing recommendations for optimising the use of CDS tools.

The study reveals that Tanzanian healthcare practitioners predominantly rely on non-computerised CDS tools, such as clinical guidelines prepared by the Ministry of Health. Despite the availability of Health Information Systems (HIS), these systems often lack comprehensive decision-support functionalities, leading practitioners to depend on traditional methods and their professional judgement. Significant challenges include limited accessibility to updated clinical guidelines, unreliable infrastructure and inadequate training. Adaptive strategies identified include using non-standardised tools like Medscape, professional judgement and reliance on past experiences and colleagues’ opinions.

The investigation was constrained by access limitations because it was challenging to get some respondents to share information. However, a sufficient number of individuals participated in the interviews, and their knowledge was very beneficial in understanding the procedures and tools for clinical decision support.

This study contributes to AT by extending its application to a low-resource healthcare setting, uncovering new dimensions of the theory related to socio-cultural and technological constraints in healthcare facilities in Tanzania. It provides valuable insights into the practical barriers and facilitators of HIS and CDS tool implementation in developing countries, emphasising the need for context-specific adaptations, robust training programs and user-centred designs. The findings highlight the resilience and imagination of healthcare practitioners in adapting to systemic limitations, offering recommendations to enhance clinical decision-making and improve patient care outcomes in Tanzania.

Public health measures implemented early in the COVID-19 pandemic brought the idea of essential work into the public discourse, as the public reflected upon what types of work are essential for society to function, who performs that work, and how the labour of essential workers is rewarded. This chapter focusses on the rewards associated with essential work. The authors develop an intersectional lens on work that was officially deemed essential in 2020 to highlight longstanding patterns of devaluation among essential workers, including those undergirded by systemic racism in employment and labour law. The authors use quantitative data from the CPS-MORG to examine earnings differences between essential and non-essential workers and investigate whether the essential worker wage gap changed from month to month in 2020. The authors find that patterns of valuation among essential workers cannot be explained by human capital or other standard labour market characteristics. Rather, intersectional wage inequalities in 2020 reflect historical patterns that are highly durable and did not abate in the first year of the global pandemic.

Drawing on interviews with two types of essential workers – wound clinicians and care workers – the chapter examines stigma management in dirty care work through the lens of emotion management. The study combines two dimensions of dirty work: physical taint in relation to bodywork and social taint linked to working in close proximity to socially stigmatized clients. Hence, stigma management extends to dealing with the physically and socially dirty features of essential care work. In addition, the authors’ assessment of social stigma includes how essential care workers also sought to alleviate the social stigma encountered by their clients. In so doing, the authors extend the literature on dirty work to identify how emotion management skills are central to the stigma management strategies of the essential care workers in this study. The authors demonstrate how both groups deal with their stigma by emphasizing the emotion management skills in ‘doing’ dirty work and in the ‘purpose’ of this work, which includes acknowledging how the authors attempt to address the social taint encountered by their clients. Additionally, by comparing two occupations with different contexts and conditions of work, the authors show how complex emotion management skills are gendered in care work to expand the understanding of gender and stigma management. Furthermore, these emotion management skills emanate from the deep relational work with clients rather than through occupational communities. The authors argue that by focussing on emotion management, the hidden skills of dirty work in gendered care work are illuminated and contribute to contemporary debates about whether stigma can be overcome.

Organizational scholars studying compensation often place an emphasis on certain employee groups (e.g., executives). Missing from this discussion is research on the compensation systems for low-wage jobs. In this review, the authors argue that workers in low-wage jobs represent a unique employment group in their understanding of rent allocation in organizations. The authors address the design of compensation strategies in organizations that lead to different outcomes for workers in low-wage jobs versus other workers. Drawing on and integrating human resource management (HRM), inequality, and worker literatures with compensation literature, the authors describe and explain compensation systems for low-wage work. The authors start by examining workers in low-wage work to identify aspects of these workers’ jobs and lives that can influence their health, performance, and other organizationally relevant outcomes. Next, the authors explore the compensation systems common for this type of work, building on the compensation literature, by identifying the low-wage work compensation designs, proposing the likely explanations for why organizations craft these designs, and describing the worker and organizational outcomes of these designs. The authors conclude with suggestions for future research in this growing field and explore how organizations may benefit by rethinking their approach to compensation for low-wage work. In sum, the authors hope that this review will be a foundational work for those interested in investigating organizational compensation issues at the intersection of inequality and worker and organizational outcomes.

The internet has evolved into an indispensable platform for seeking health information, particularly among transgender individuals. With an abundance of online resources available, extensive research into the credibility and reliability of this information is essential, as concerns about the quality of online resources persist. Transgender individuals are drawn to online health information due to the anonymity it offers, providing them with a sense of freedom from social isolation and the discomfort of experimenting with their transgender identity. However, it is crucial to assess the accuracy and reliability of the transgender health information available on the internet. This article aims to evaluate the quality of online transgender health resources by utilizing ten credibility indicators, along with six indicators to assess the veracity of the content.

A total of 179 online resources were meticulously reviewed after excluding any unnecessary and irrelevant ones, to ensure a comprehensive assessment.

The findings suggest that among the chosen resources, none of them meet all the criteria for maintaining high standards of accuracy and reliability in health information. In other words, none of these sources completely adhere to the established measures for ensuring that the information they provide is trustworthy and of high quality in the context of health.

The study provides valuable insights into the online realm of transgender health information, revealing both the strengths and weaknesses of the existing resources. By pinpointing areas that need enhancement and showcasing commendable practices, this research strives to promote a more knowledgeable and supportive online environment for individuals in search of transgender health information.

Common challenges for healthcare systems worldwide are population ageing, rising therapy spending and reduced economic resources. In response, AI can play a crucial role in facilitating managerial and economic objectives within a holistic vision of care and improve the experience of patients and professionals. AI may change the delivery of services and the demand for them as well. This raises questions of how to balance the supply and demand sides of healthcare services, how to leverage competitive positioning and how to differentiate strategies specific to the public and to the private sector.

The complex challenges facing the healthcare sector call for a revision of the ways it can provide high-quality services with economic sustainability. Revision can proceed along different pathways. Among the new paradigms of healthcare is the shift from a silo approach by hospitals towards an integrated, multidisciplinary approach. This entails restructuring hospitals in disease centres and exploring how AI can aid in the integration of hospital services and community care. Reorganization is vital to the development of patient-centred healthcare and the holistic approach. To achieve these goals, healthcare and policy decision-makers need to consider both the administrative and the clinical aspects of everyday issues. AI can play a key role in helping balance this duality. The overarching objective is to create interdisciplinary therapeutic and diagnostic pathways within care networks shared between the hospital and the community. This involves the analysis of huge amounts of data and interdisciplinary knowledge beyond the grasp of an individual. Therefore, knowing how AI can help in the development and reorganization of community healthcare is essential for clinical leaders to take advantage of this enormous opportunity in larger settings.

The aim of this chapter is to develop a conceptual model for the analysis of sustainable development and the ranking of cities based on selected standard criteria and metrics of smart cities. The conceptual framework contains standard and measurable indicators that influence the creation and survival of smart cities that could be self-sustaining, Green Resilient. We can measure the level of smartness of cities from two perspectives, first from the point of view of the degree of automation of services, infrastructure, buildings, transport, etc. and second from the point of view of planning the further development of the city in order to raise the quality of life of its citizens. Indicators should satisfy the principles of specificity, measurability, availability, relevance and timeliness (Schomaker, 1997). Researchers in the field of smart cities define different sets of characteristics, on which they construct a system of indicators that together describe the degree of development of a smart city. It must be taken into account the fact that there is no single set of indicators that would refer to the level of smartness of the city. It is a complex phenomenon, which occurs differently depending on the conceptual framework and the goal of classifying cities according to the complex characteristics of smartness, especially if you take into account the fact that the general well-being and quality of life of citizens are more important than only indicators of the quality of city services.

Limiting the use of antibiotics in food animals is a cornerstone of contemporary EU policy. Despite that marketing of antibiotics for growth promotion and nutrition has been banned since 2006, the use is still high and varied. This paper aims to investigate the forces behind the different usage patterns in Italy, with one of the EU’s most extensive use of antibiotics in animals, versus Sweden, with the union’s most restricted use, including how these usage patterns are related to EU and national policies.

The industrial network approach/the 4R resources interaction model is adopted to investigate the major forces behind the different antibiotic usage patterns. Furthermore, the study relies on the notion of three main characteristics related to the use of a resource activated in several user settings (Håkansson and Waluszewski, 2008, pp. 20–22). The paper investigates the Swedish and the Italian using settings, with a minimised, respectively, extensive usage of antibiotics. The study is exploratory in nature and based on qualitative data collected through a combination of primary and secondary sources.

The paper underlines the importance of integrating forces for policy to succeed in attempts to reduce the use of a particular resource. It reveals that Sweden’s radically reduced use was based on great awareness, close interactions between animal-based food producers and policy – and that integrating forces were supported by an era of state-protected food production, with promising ability to distribute the cost of change. The Italian characteristics hindering the integration of forces mounting for reduced use were restricted awareness, top-down business and policy interactions – and a great awareness about the difficulties of distributing the cost of change.

The study deals with the analysis of forces affecting the different usage of antibiotics within two EU settings. The investigation, based on the industrial network approach’s notion of connectivity of economic resources, that is, of exchange having a content and substance beyond discrete transactions, reveals how indirect related contextual forces, neglected by policy, have an important influence on the ability to achieve change, in this case of antibiotics usage patterns.