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The second chapter of this text provides an introduction to policy relating to mental health, addiction and dual diagnosis from three jurisdictions [Ireland, UK and Australia], chosen because of their close links to Irish people and mental health service provision. The chapter begins with an introduction, reflecting on key points raised in Chapter 1 and how they are relevant to this present chapter. A critical exploration of the policies within these three jurisdictional areas is then presented to highlight the strategic direction of mental health and addiction service provision within the three jurisdictions. This includes the acknowledgement that mental health and addiction services need to be integrated as the presence of dual diagnosis in modern society increases at an alarming rate. Finally, this chapter concludes with a link to each of the policies mentioned herein for those who wish to explore these issues further.

Mainland Tanzania has seen two decades of significant social policy reforms and transformations in its social and economic structures, whilst the country continues to grapple with persisting gender inequalities. This article examines Tanzania's social policy developments from a gender perspective. The authors analyse the level, reach and quality of social policy delivery to working-age women across the areas of health policy, social protection and employment policy during 2000–2021.

The article draws on qualitative research deploying the scoping review method. The data consist of diverse secondary materials, including academic publications, government policy documents, relevant statistics and other types of “grey” literature.

Tanzania has made significant advancements in the legal frameworks around welfare provision and has instituted increasingly gender-responsive government policy plans. The health and social protection sectors, in particular, have witnessed the introduction of large-scale measures expanding social policy implementation. However, social policy delivery remains two-tiered, with differences in provisions for women in the formal and informal sectors.

Social policy delivery and implementation have increased and diversified in Sub-Saharan Africa (SSA) during the new millennium, with a growing integration of gender-specific policy objectives. However, limited social policy scholarship has focused on the gendered effects of broader social policy models in SSA. The article remedies the concomitant knowledge gaps by examining various social policies and their impacts on working-age women in Mainland Tanzania. The authors also engage with the theoretical welfare regime literature and present an analytical framework for gender-sensitive assessment of emerging social policy models in the Global South.

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.

This chapter pays tribute to Andrew Jones' research in health programme evaluation, health-risky behaviour and income-related health inequalities by reviewing policy-relevant empirical studies in these domains using Italian data. In the first section, We discuss the impact of reimbursement systems on healthcare behaviour, particularly the transition from incurred-cost-based to prospective systems in hospitals. We explore incentive-driven practices like up-coding and cream skimming, while also considering the potential advantages of primary care incentives and the mixed outcomes associated with cost-sharing schemes. The second section delves into health-risk behaviours in Italy, encompassing substance use, preventive healthcare and responses to health information. The last section presents some evidence on socioeconomic status (SES)-related health disparities and discusses the necessity of accounting for these factors in the Italian National Health Service (NHS)'s resource allocation formula in line with British NHS experience.

This study compared approaches to school closures in four Latin American countries (Bolivia, Colombia, Ecuador, Peru), describing the impact on the health and educational wellbeing of school-age children and youth, and evaluating their approaches in regard to continuing education through the pandemic.

We collected 75 publicly available documents including scientific and gray literature (government documents and news releases), that referred to school closures and their impact on children’s health and wellbeing. We did thematic analyses using open, axial, and selective coding and applied the latest Health Promoting Schools standards and indicators to the findings.

Results showed that countries followed epidemiological reasons for prioritizing school closures while adopting some policies that abide by Health Promoting School principles. While they emphasized the need to reopen schools so that instruction could continue, school closures were among the longest in the world. The most significant impacts on wellbeing identified in the four countries were related to food security and mental health.

This study focused on a particular set of documents, and it may not capture the full spectrum of relevant information in different contexts or regions.

By comparing school closures approaches among four Latin American countries, this study highlights the importance of context-specific interventions. In a post-pandemic era, lessons learned from these experiences should help foster more resilient and inclusive educational systems and explore the paths forward for following the new Health Promoting Schools framework in the region.

Cross-country qualitative analyses on this topic are rare. This study adds to the knowledge base by eliciting lessons for future health education research and policy efforts.

This work aims to analyse the relationship between public health efficiency and well-being considering a panel of 102 Italian provinces from 2000 to 2016 and evaluates if there are omitted variable biases and endogeneity biases and also evaluates if there are heterogeneous effects among provinces with different income levels.

We use a multi-input and output bootstrap data envelopment analysis to assess public health efficiency. Then, we measure well-being indices using the min-max linear scaling transformation technique. A two-stage least squares model is used to identify the causal effect of improving public health efficiency on well-being to account for time-invariant heterogeneity, omitted variable bias and endogeneity bias.

After controlling for important economic factors, the results show a significant effect of an accountable and efficient public health system on well-being. Those effects are concentrated in the North, the most economically, geographically and environmentally advantageous areas.

The use of the sample mean, probably the oldest and most used method for aggregating the indicators, could be affected by variable compensation, with consequent misleading results in the process of constructing the well-being index. Another limitation is the use of lagged values of the main predictor as an instrument in the instrumental variables setting because it could lead to information loss. Finally, the availability of data over a long period of time.

The findings could help policymakers adopt measures to strengthen the public health system, encourage private providers and inspire countries worldwide.

These results draw the attention of local authorities, who play an important role in designing and implementing policies to stimulate local public health efficiency, which puts individuals in the conditions of achieving overall well-being in their communities.

For the first time in Italy, a panel of well-being indices was constructed by developing new methodologies based on microeconomic theory. Furthermore, for the first time, the assessment of the relationship between public health efficiency and well-being is carried out using a panel of 102 Italian provinces.

User involvement and co-production are imperative to the design, delivery and evaluation of service provision. This chapter provides a brief introduction to these concepts as they relate to mental health, addiction and dual diagnosis. This occurs through an exploration of models of user involvement, particularly, Arnstein’s ladder of participation and MHERs engagement continuum. This is followed by exploring the benefits of user involvement at both a micro and macro level. Co-production – as the highest form of participation is also introduced followed by how these concepts are noted within policy. These concepts are imperative to the creation of a recovery-orientated service that meets the needs of the whole person and their supporters.

Imprisonment impacts women’s childbearing and mothering experiences. Using sociological concepts of total institutions, pains of imprisonment and gendered pains of imprisonment, this study aims to explore the childbearing experiences of 18 Filipino incarcerated women.

A qualitative, inductive approach was undertaken to explore imprisoned women’s pregnancy experiences. This research project used reflexive thematic analysis to examine the data from semi-structured interviews with 18 Filipino pregnant prisoners.

The participants’ experiences of childbearing in prison were reflected in three overarching themes: lack of autonomy over pregnancy; reduced capacity to manage discomforts and needs; and coping with prison deprivations. These themes embody women’s experiences of how imprisonment disrupts Filipino women’s childbearing and mothering experiences. Furthermore, the results illustrated how the women navigated the prison regime to address their needs and cope with the pains of imprisonment.

Although there is a small but growing body of research specifically focusing on mothering and imprisonment, little consideration has been given to analyzing Filipino women’s pregnancy experiences in custody. This paper highlights an urgent need to reform correctional policies and practices to address incarcerated women’s distinct needs.

This chapter focuses on the COVID-19 pandemic’s impact on the recognition through discourses of essentiality, of low-status workers and more specifically of care aides as an occupational group that performs society’s ‘dirty work’. The pandemic appears as a privileged moment to challenge the normative hegemony of how work is valued within society. However, public recognition through political discourse is a necessary but insufficient element in producing social change. Based on the theory of performativity, this chapter empirically probes conditions and mechanisms that enable a transition from discourse of essentiality to substantive recognition of the work performed by care aides in healthcare organizations. The authors rely on three main sources of data: scientific-scholarly works, documents from government, various associations and unions, and popular media reports published between February 2020 and 1 July 2022. While discourse of essentiality at the highest level of politics is associated with rapid policy response to value the work of care aides, it is embedded in a system structure and culture that restrains the establishment of substantive policy that recognizes the nature, complexity, and societal importance of care aide work. The chapter contributes to the literature on performativity by demonstrating the importance of the institutionalization of competing logics in contemporary health and social care systems and how it limits the effectiveness of discourse in promulgating new values and norms and engineering social change.

The objective of this study is to reevaluate the correlation among pharmaceutical consumption, per capita income, and life expectancy across different age groups (at birth, middle age, and advanced age) within the OECD countries between 1998 and 2018.

We employ a two-step methodology, utilizing two independent approaches. Firstly, we con-duct the Dumitrescu-Hurlin pairwise panel causality test, followed by Machine Learning (ML) experiments employing the Causal Direction from Dependency (D2C) Prediction algorithm and a DeepNet process, thought to deliver robust inferences with respect to the nature, sign, direction, and significance of the causal relationships revealed in the econometric procedure.

Our findings reveal a two-way positive bidirectional causal relationship between GDP and total pharmaceutical sales per capita. This contradicts the conventional notion that health expenditures decrease with economic development due to general health improvements. Furthermore, we observe that GDP per capita positively correlates with life expectancy at birth, 40, and 60, consistently generating positive and statistically significant predictive values. Nonetheless, the value generated by the input life expectancy at 60 on the target income per capita is negative (−61.89%), shedding light on the asymmetric and nonlinear nature of this nexus. Finally, pharmaceutical sales per capita improve life expectancy at birth, 40, and 60, with higher magnitudes compared to those generated by the income input.

These results offer valuable insights into the intricate dynamics between economic development, pharmaceutical consumption, and life expectancy, providing important implications for health policy formulation.

Very few studies shed light on the nature and the direction of the causal relationships that operate among these indicators. Exiting from the standard procedures of cross-country regressions and panel estimations, the present manuscript strives to promote the relevance of using causality tests and Machine Learning (ML) methods on this topic. Therefore, this paper seeks to contribute to the literature in three important ways. First, this is the first study analyzing the long-run interactions among pharmaceutical consumption, per capita income, and life expectancy for the Organization for Economic Co-operation and Development (OECD) area. Second, this research contrasts with previous ones as it employs a complete causality testing framework able to depict causality flows among multiple variables (Dumitrescu-Hurlin causality tests). Third, this study displays a last competitive edge as the panel data procedures are complemented with an advanced data testing method derived from AI. Indeed, using an ML experiment (i.e. Causal Direction from Dependency, D2C and algorithm) it is believed to deliver robust inferences regarding the nature and the direction of the causality. All in all, the present paper is believed to represent a fruitful methodological research orientation. Coupled with accurate data, this seeks to complement the literature with novel evidence and inclusive knowledge on this topic. Finally, to bring accurate results, data cover the most recent and available period for 22 OECD countries: from 1998 to 2018.