Previous studies support the direct relationship between outdoor physical activity and natural spaces in cities. The Active City and Nature concept explores the relationship between urban, green and active environments; it aims to demonstrate the scientific evidence for the need for action to be taken to increase participation in active living and sport, leading to healthier cities and communities. Our research seeks to analyse the city’s natural spaces as scenarios to encourage physical activity and sport, through a combined study of qualitative research techniques: the use of a digital webGIS platform, collaborative maps made by citizens, and surveys conducted with citizens and the local government. This methodology has been tested in the city of Malaga, the European City of Sport 2020. The study of the city’s main sport areas, the waterfront and natural green spaces provided data on the types of physical activity taking place in each of these areas and the physical activity needs of citizens. This research argues that it is important to know the criteria of local communities for physical activity and/or sport in natural environments, as well as the main demands expressed. This will provide valuable information to design and manage natural public spaces as a means of promoting physical activity and healthy habits.

The implementation of data interoperability in healthcare relies heavily on policy frameworks. However, many hospitals across South Africa are struggling to integrate data interoperability between systems, due to insufficient policy frameworks. There is a notable awareness that existing policies do not provide clear actionable direction for interoperability implementation in hospitals. This study aims to develop a policy framework for integrating data interoperability in public hospitals in Gauteng Province, South Africa. The study employed a conceptual framework grounded in institutional theory, which provided a lens to understand policies for interoperability. This study employed a convergence mixed method research design. Data were collected through an online questionnaire and semi-structured interviews. The study comprised 144 clinical and administrative personnel and 16 managers. Data were analyzed through descriptive and thematic analysis. The results show evidence of coercive isomorphism that public hospitals lack cohesive policies that facilitate data interoperability. Key barriers to establishing policy framework include inadequate funding, ambiguous guidelines, weak governance, and conflicting interests among stakeholders. The study developed a policy to facilitate the integration of data interoperability in hospitals. This study underscores the critical need for the South African government, legislators, practitioners, and policymakers to consult and involve external stakeholders in the policy-making processes.

This research aims to identify the development of research theme trends that were carried out from 1999 to 2024. Thus, the study’s results can provide recommendations regarding research themes that can be developed to meet theoretical and practical needs. Researchers use bibliometric analysis to obtain the appropriate analysis. This analysis method can be developed to support the dynamic development of public health science with settings and researchers from developing countries, both through quantitative and qualitative interpretation. The analysis results show that over 25 years, public health science, from the perspective of researchers and developing countries, has experienced dynamic development. This change was driven by the emergence of various issues in society itself. For example, the 1999–2009 shows that lifestyle changes have resulted in multiple diseases. In the following period, the concept of sustainability emerged, which encouraged awareness of sustainable development and resource scarcity that would affect public health quality. As for the 2020–2024 period, the emergence of Covid 19 changed the previous research paradigm.

The rapid advancement of information and communication technology has greatly facilitated access to information across various sectors, including healthcare services. This digital transformation demands enhanced knowledge and skills among healthcare providers, particularly in comprehensive midwifery care. However, midwives in rural areas face numerous challenges such as limited resources, cultural factors, knowledge disparities, geographic conditions, and technological adoption. This research aims to evaluate the impact of AI utilization on midwives’ knowledge and behavior to optimize the implementation of healthcare services in accordance with Delima Midwife Service standards in rural settings. The analysis encompasses competencies, characteristics, information systems, learning processes, and health examinations conducted by midwives in adopting AI. The research methodology employs a cross-sectional approach involving 413 rural midwives selected proportionally. Results from Partial Least Squares Structural Equation Modeling indicate that all reflective evaluation variables meet the required criteria. Fornell-Larcker criterion demonstrates that the square root of AVE is greater than other variables. The primary findings reveal that information systems (0.029) and midwives’ competencies (0.033) significantly influence AI utilization. Furthermore, midwives’ competencies (0.002), characteristics (0.031), and AI utilization (0.011) also significantly impact midwives’ knowledge and behavior. Midwives’ characteristics also significantly affect their competencies (0.000), while midwives’ learning influences health examinations (0.000). Midwives’ knowledge and behavior affect the transformation of healthcare services in rural midwifery (0.022). The model fit results in a value of 0.097, empirically supporting the explanation of relationships among variables in the model and meeting the established linearity test.

Good health and well-being are embedded in the 3rd Goal amongst the UN Sustainable Development Goals. The primary objective of this research was to identify the most critical economic, social, and administrative barriers to implementing the Expanded Program on Immunization (EPI) in the Punjab Province of Pakistan. A sequential exploratory design and case study technique were used, employing both qualitative and quantitative methods. In the first stage, in-depth interviews with 50 key officials were conducted to identify the most critical barriers to the EPI program. A quantitative analysis was then performed based on the results obtained from qualitative analysis, and rank orders of barriers were received from the same health department experts. The results indicate that twenty-eight barriers can cause implementation problems for this program. Still, the ten barriers that gained the maximum hits are the most important barriers, which include Shortage of vaccinators, mismanagement of vaccines’ cold chain, biometric android application, ice-lined refrigerators, communication gap, inadequate legislation of EPI program, capacity building issues with EPI staff, Misconceptions about EPI program, lack of awareness of the parents and community, refusal cases and inadequate cooperation of lady health workers (LHWs). Coordinated efforts of the government and the public are highly recommended to address these barriers.

The increase in energy consumption is closely linked to environmental pollution. Healthcare spending has increased significantly in recent years in all countries, especially after the pandemic. The link between healthcare spending, greenhouse gas emissions and gross domestic product has led many researchers to use modelling techniques to assess this relationship. For this purpose, this paper analyzes the relationship between per capita healthcare expenditure, per capita gross domestic product and per capita greenhouse gas emissions in the 27 EU countries for the period 2000 to 2020 using Error Correction Westerlund, and Westerlund and Edgerton Lagrange Multiplier (LM) bootstrap panel cointegration test. The estimation of model coefficients was carried out using the Augmented Mean Group (AMG) method adopted by Eberhardt and Teal, when there is heterogeneity and cross-sectional dependence in cross-sectional units. In addition, Dumitrescu and Hurlin test has been used to detect causality. The findings of the study showed that in the long run, per capita emissions of greenhouse gases have a negative effect on per capita health expenditure, except from the case of Greece, Lithuania, Luxembourg and Latvia. On the other hand, long-term individual co-integration factors of GDP per capita have a positively strong impact on health expenditure per capita in all EU countries. Finally, Dumitrescu and Urlin’s causality results reveal a significant one-way causality relationship from GDP per capita and CO₂ emissions per capita to healthcare expenditure per capita for all EU countries.