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Disasters and pandemics pose challenges to health-care provision. Accordingly, the need for adopting innovative approach is required in providing care to patient. Therefore, the purpose of this study is to present telehealth as an innovative approach for providing care to patients and reducing spread of the infection and advocates for the adoption of telehealth for digitalized treatment of patients.

An integrative review methodology of existing evidence was conducted to provide implications for integration of telehealth for digitalized treatment of patients. This paper draws on Technology Organization Environment (TOE) framework to develop a model and propositions to investigate the factors that influence telehealth adoption from the perspective of the supply side and the demand side of medical services.

Findings from this study discuss applications adopted for telehealth and recommendations on how telehealth can be adopted for medical-care delivery. More importantly, the findings and propositions of this study can act as a roadmap to potential research opportunities within and beyond the pandemic. In addition, findings from this study help provide guidelines on how health practitioners can rapidly integrate telehealth into practice for public health emergencies.

This study identifies the social, technological and organizational factors that influence telehealth adoption, and opportunities of adopting telehealth during the public health emergencies. This study concludes that specific policy changes to improve integration of interoperable solutions; data security; better physical infrastructures; broadband access; better transition and workflow balance; availability of funding and remuneration; regulations and reimbursement; awareness; and training will improve telehealth adoption during public health emergencies.

This research proposes a novel risk assessment model to elucidate the risk propagation process of industrial safety accidents triggered by natural disasters (Natech), identifies key factors influencing urban carrying capacity and mitigates uncertainties and subjectivity due to data scarcity in Natech risk assessment.

Utilizing disaster chain theory and Bayesian network (BN), we describe the cascading effects of Natechs, identifying critical nodes of urban system failure. Then we propose an urban carrying capacity assessment method using the coefficient of variation and cloud BN, constructing an indicator system for infrastructure, population and environmental carrying capacity. The model determines interval values of assessment indicators and weights missing data nodes using the coefficient of variation and the cloud model. A case study using data from the Pearl River Delta region validates the model.

(1) Urban development in the Pearl River Delta relies heavily on population carrying capacity. (2) The region’s social development model struggles to cope with rapid industrial growth. (3) There is a significant disparity in carrying capacity among cities, with some trends contrary to urban development. (4) The Cloud BN outperforms the classical Takagi-Sugeno (T-S) gate fuzzy method in describing real-world fuzzy and random situations.

The present research proposes a novel framework for evaluating the urban carrying capacity of industrial areas in the face of Natechs. By developing a BN risk assessment model that integrates cloud models, the research addresses the issue of scarce objective data and reduces the subjectivity inherent in previous studies that heavily relied on expert opinions. The results demonstrate that the proposed method outperforms the classical fuzzy BNs.

The purpose of this paper is to develop a comprehensive understanding of the public safety risks of international construction projects (ICPs) from the perspective of threat and vulnerability. A novel and comprehensive risk assessment approach is developed from a systemic perspective and applied to the Belt and Road Initiative (BRI) to improve the public safety risk management strategy for ICPs in BRI.

First, a public safety risk indicator system was constructed from the two dimensions, namely threat and vulnerability. Next, an integrated measurement model was constructed by combining the Genetic Algorithm-Backpropagation (GA-BP) neural network, fuzzy comprehensive evaluation method and matter-element extension (MME) method. Data from 49 countries involved in the BRI, as well as five typical projects, were used to validate the model. Finally, targeted risk prevention measures were identified for use at the national, enterprise and project levels.

The findings indicate that while the vulnerability risks of typical projects in each region of the BRI were generally low, threat risks were high in West Asia and North Africa, Commonwealth of Independent States (CIS) countries and South Asia.

First, the structure of the public safety risk system of ICPs was analyzed using vulnerability and system theories. The connotation of public safety risk was defined based on two dimensions, namely threat and vulnerability. The idea of measuring threat risk with public data and measuring vulnerability risk with project data was clarified, and the risk measurement was integrated into the measurement results to help researchers and managers understand and systematically consider the public safety risks of ICPs. Second, a public safety risk indicator system was constructed, including 18 threat risk indicators and 14 vulnerability risk indicators to address the gaps in the existing research. The MEE model was employed to overcome the problem of incompatible indicator systems and provide stable and credible integrated measurement results. Finally, the whole-process public safety risk management scheme designed in this study can help to both provide a reference point for the Chinese enterprises and oversea contractors in market selection as well as improve ICP public safety risk management.

The occupational health risk associated with the production of prefabricated concrete components is often overlooked. This paper will use a damage assessment and cyclic mitigation (DACM) model to provide individualized exposure risk assessment and corresponding mitigation management measures for workers who are being exposed.

The DACM model is proposed based on the concept of life cycle assessment (LCA). The model uses Monte-Carlo simulation for uncertainty risk assessment, followed by quantitative damage assessment using disability-adjusted life year (DALY). Lastly, sensitivity analysis is used to identify the parameters with the greatest impact on health risks.

The results show that the dust concentration is centered around the mean, and the fitting results are close to normal distribution, so the mean value can be used to carry out the calculation of risk. However, calculations using the DACM model revealed that there are still some work areas at risk. DALY damage is most severe in concrete production area. Meanwhile, the inhalation rate (IR), exposure duration (ED), exposure frequency (EF) and average exposure time (AT) showed greater impacts based on the sensitivity analysis.

Based on the comparison, the DACM model can determine that the potential occupational health risk of prefabricated concrete component (PC) factory and the risk is less than that of on-site construction. It synthesizes field research and simulation to form the entire assessment process into a case-base system with the depth of the cycle, which allows the model to be continuously adjusted to reduce the occupational health damage caused by production pollution exposure.

This study is a theory-building effort to extend the risk perception attitude (RPA) framework by considering an organization-related factor. Specifically, this study examined how an organization-related factor, namely safety climate, and individual-related factors, namely risk perception and efficacy belief, jointly influence flight attendants’ occupational health and safety (OHS) information seeking intent.

About 486 flight attendants from an international air carrier, based in Hong Kong, participated in an online survey. Hierarchical regression was employed to examine the three-way interaction of risk perception, efficacy belief, and safety climate.

Results showed that safety climate moderated the effect of efficacy belief on the relationship between risk perception and OHS information seeking intent. For flight attendants who perceived a high safety climate, those who felt more efficacious had a higher intent for OHS information seeking than those who felt less efficacious. In contrast, for flight attendants who perceived a low safety climate, when they perceived a high level of risk, those with low efficacy had a higher information seeking intent than those with high efficacy.

Although the RPA framework has shown its potential to explicate how individual employees engage in OHS information seeking behavior, the framework has largely overlooked the importance of organization-related factors as an influential shaping force of individual employees’ behavior. To fill this research gap, this study extends the RPA framework by examining how safety climate moderates the relationship between risk perception and efficacy belief on flight attendants’ OHS information seeking intent. Safety climate also plays an important role in segmenting audience groups for OHS promotion.

The purpose of this research is to address the existing gap in the study of construction and demolition waste (C&DW) by focusing on its impact on human health throughout the entire life cycle. And this research provides a comprehensive assessment model that incorporates the release of gaseous pollutants and particulate matter during the whole life cycle of C&DW, thereby contributing to a more holistic understanding of its impact on human health.

The research was conducted in two stages. Firstly, the quantitative model framework of pollutants emitted by C&DW was established. Three types of pollutants were considered, namely nitrogen dioxide (NO₂), sulfur dioxide (SO₂) and inhalable particulate matter (PM10). Second, disability-adjusted life year (DALY) and willingness to pay (WTP) assessments were used to provide a monetary quantified health impact for pollutants released by C&DW.

The results show that the WTP value of PM10 is the highest among all pollutants and 8.68E+07 dollars/a, while the WTP value in the disposal stage accounts for the largest proportion compared to the generation and transportation stage. These findings emphasize the importance of PM10 and C&DW treatment stage for pollutant treatment.

The results of this study are of great significance for the management department to optimize the construction management scheme to reduce the total amount of pollutants produced by C&DW and its harm to human health. Meanwhile, this study fills the gap in existing research on the impact assessment of C&DW on human health throughout the whole life cycle, and provides reference and basis for future research and policy formulation.

The performance governance model, based on the use of performance information to improve governance, is particularly complex, considering the inter-institutional relationships and community involvement that it requires. In order to contribute to the scientific debate on this model, the paper aims to highlight what are the challenges in developing three variables of performance governance (operational performance measurement tools, governance integration and citizen involvement) in the public health context.

Based on the previous literature, we identified three variables that characterize the performance governance model. We then explored them through the case study methodology applied to the Apulia Regional Health System.

The analysis allows us to conclude that the healthcare system under consideration is still far from applying the performance governance model, but it highlights some factors that are preparatory to the same. Moreover, starting from the empirical evidence, some considerations arise regarding managerial and policy making implications for the variables investigated.

The paper contributes to a growing body of critical literature on performance governance contextualizing the analysis in a particularly relevant area of the public sector, namely public health. Furthermore, the research also identifies some potential risks of the performance governance model (rigidity in performance measurement tool, organization-objective-responsibility relationship, participatory illusion).

Construction accidents cause as much harm in Bangladeshi construction as it does globally. This study examines the primary causes of accidents and undertakes an impact assessment of neglecting safety protocols in construction projects in Bangladesh, funded publicly, privately and through a Public-Private Partnership (PPP).

Research was initiated with a comprehensive questionnaire from experts, sourcing data in Bangladesh's construction sector. Data analysis utilized Cronbach's alpha, relative important index and a fishbone diagram for causal visualization.

The study identified the three major causes of safety negligence as “Poor safety culture (RII = 0.857),” “Top management's inattention (RII = 0.825)” and “Lack of personal care (RII = 0.825).” Effects: “Rising project expenses (RII = 0.88),” “Increased medical costs (RII = 0.87)” and “Worker compensation expenses (RII = 0.87).” The study also used the Ishikawa-Fishbone and effect-flow diagrams to highlight accident causes/effects and compare their primary causes in PPP, public and private projects.

Research on construction safety in Bangladesh has mainly focused on identifying factors within specific construction sectors. Since the rules and regulations vary across these three sectors, different health and safety hazards may arise. As a result, this research fills a critical gap by providing a comparative study that examines the causes and impacts of different project types in the Bangladeshi construction industry. By pinpointing the result, this research aims to enhance the safety and well-being of the construction workers sector-wise, thereby contributing to the industry's sustainable growth.

Many waste-to-energy (WTE) plants are constructed and operated using the public-private partnership (PPP) mode in China. However, risk events of PPP WTE incineration projects sometimes occur. This study aims to clarify the relationship of risks in China's PPP WTE incineration projects and identify the key risks accordingly and risk transmission paths.

A risk list of PPP WTE incineration projects was obtained based on literature analysis. Moreover, a hybrid approach combining fuzzy sets, decision-making trial and evaluation laboratory (DEMATEL) and interpretive structural modeling (ISM) was developed to analyze the causality of risks, explore critical risks and reveal the risk transmission paths. The quantitative analysis process was implemented in MATLAB.

The results show that government decision-making risk, government credit risk, government supervision behavior risk, legal and policy risk, revenue and cost risk and management capacity risk are the critical risks of PPP WTE incineration projects in China. These critical risks are at different levels in the risk hierarchy and often trigger other risks.

Currently, there is a lack of exploration on the interaction between the risks of PPP WTE incineration projects. This study fills this gap by examining the key risks and risk transfer pathways of PPP WTE incineration projects from the perspective of risk interactions. The findings can help the public and private sectors to systematically understand the risks in PPP WTE incineration projects, thus enabling them to identify the risks that need to be focused on when making decisions and to optimize risk prevention strategies. The proposed hybrid approach can offer methodological ideas for risk analysis of other types of PPP projects.

In public health emergencies, seeking confirmed cases’ activity trajectory information (CCATI) is crucial to the public’s efforts to combat the epidemic. The public can stabilize their sentiments and mitigate the risk of cross-infection by obtaining CCATI. We investigated the factors influencing users' intentions to seek CCATI to enhance the government’s risk communication capabilities and improve information platform services.

We analyzed how information ecological factors affect the intention to seek CCATI through perceived value. Data was collected from 429 Chinese citizens during the fourth wave of the coronavirus disease 2019 (COVID-19) pandemic. We used the structural equation model technology and bootstrap mediation effect test to examine the model.

Information understandability, information relevance, perceived severity and perceived vulnerability directly and positively affect the intention of seeking CCATI. While, the above relationships are also partially mediated by emotional value and functional value. Social support directly and negatively affects the intention of seeking CCATI, while the relationship is also partially mediated by emotional value and functional value. Curiosity directly and positively affects the intention of seeking CCATI, while the relationship is also partially mediated by emotional value. The relationship between the quality of the search service and the intention of seeking CCATI is not significant, instead, it is fully mediated by functional value. The influence effect of information relevance on the intention of seeking CCATI is the greatest, followed by perceived vulnerability. The mediating effect of functional value is higher than emotional value.

The findings may help governments enhance their risk communication capabilities and improve epidemic prevention and control measures, enhancing the appeal of information platforms.

We focused on CCATI, an area with limited scholarly attention. We analyzed CCATI-seeking factors using an information ecology theory, introducing perceived value as a mediator, thus offering novel perspectives and models.