The achievement of sustainable development in Kenya has been hindered by the prevalence of HIV. The effects of HIV on sustainable development have been given less academic attention. HIV prevalence prevents people from achieving good health and well-being, which then makes them unable to conduct activities that lead to sustainable economic growth. The paper found that the prevalence of HIV causes economic hardship, destroys human capital development and human resources by reducing life expectancy and increasing mortality rates. It was equally found that the prevalence of HIV undermines social stability and mobility, reduces economic investments, influences food insecurity and makes people vulnerable. The paper found that the prevalence of HIV reduces labor supply and productivity, increases the cost of health services, promote inequality and poverty. The paper found that the prevalence of HIV was caused by the failure to integrate religion, culture and science infrastructure to achieve a holistic treatment acceptance and adherence that would overcome all misconceptions people have towards the disease. The paper found that while science provides effective HIV treatments, religious and cultural perspectives often shape community attitudes toward the disease. It was found that engaging religious and cultural as well as health workers or health advocates can help reduce stigma and promote ART adherence by aligning treatment messages with faith-based principles. The paper found that the integration that incorporates religion, culture, and science into HIV interventions would promote a more inclusive healthcare system that respects diverse beliefs while ensuring evidence-based treatment is accessible and widely accepted. The study was conducted through a qualitative methodology. Data was collected from secondary sources that included published articles, books and occasional papers as well as reports. Collected data was interpreted and analyzed through document analysis techniques.

In response to the rapid and dynamic changes in the economic environment, companies must improve their processes to maintain competitiveness. This includes enhancing their intellectual capital, with particular emphasis on effective onboarding processes, which play a crucial role in integrating new employees and retaining talent. This enhances the value of the organization’s intellectual capital and emphasizes onboarding—the training and integration of new employees—whose proper functioning impacts staff retention. Drawing on both Hungarian and predominantly foreign literature, we highlight onboarding processes and examine their implementation in Hungarian companies of various sizes. The research employed a mixed-method approach, combining semi-structured interviews and questionnaires. In-depth interviews were conducted with HR leaders from 13 Hungarian organizations to explore the existence of mentoring programs. Additionally, 161 employees across Hungary completed questionnaires, which examined their perspectives on onboarding processes and the relationship between mentoring programs and company size. We analyzed the data using chi-square tests to assess the strength of these relationships. While all large companies in our sample had formal mentoring programs, smaller companies displayed more variability, with some relying on informal or ad-hoc onboarding processes. Based on these results, we identified several key areas for improvement in onboarding processes. These include enhancing the structure of feedback interviews, ensuring more comprehensive communication channels, and strengthening mentoring programs across companies of all sizes. By addressing these gaps, companies can improve employee retention, engagement, and overall integration during the onboarding process, contributing to a more stable and motivated workforce.

Edible cutlery is a safe alternative that, if adopted, can act as a panacea to plastic pollution. Consumers who believe in a lifestyle of health and sustainability (LOHAS) can motivate others by taking the lead in this direction. This study has explored the psychological variables associated with LOHAS consumers in conjunction with the product attributes of edible cutlery to check whether these variables can influence lifestyle of health and sustainability (LOHAS) consumers to adopt edible cutlery. An empirical study on 210 LOHAS consumers using Partial Least Squares Structure Equation Modelling (PLS-SEM) and Importance Performance Matrix Analyses (IPMA) showed that social consciousness and subjective norms motivate them to adopt edible cutlery in restaurants. This finding has an implication for hospitality businesses using edible cutlery that can target LOHAS consumers with strategies that affect their social consciousness and subjective norm belief for better adoption intentions.

The objective of this research is to assess the current state of e-banking in Saudi Arabia. The banking industry is rapidly evolving to use e-banking as an efficient and appropriate tool for customer satisfaction. Traditional banks recommend online banking as a particular service to their customers in order to provide them with faster and better service. As a result of the rapid advancement of technology, banks have used e-banking and mobile banking to both accumulate users and conduct banking transactions. Nonetheless, the primary challenge with electronic banking is satisfying customers who use Internet banking. Thus, the current study seeks to determine what factors affect e-payment adoption with e-banking services. mobile banking, e-wallets, and e-banking, as well as the mediating role of customer trust, can drive e-payment adoption. We distributed the survey online and offline to a total of 336 participants. A convenience sampling technique was used; structure equation modeling (SEM), convergence and discriminant validity; and model fitness were achieved through Smart PLS 3. The findings have shown that mobile banking, e-banking, and e-wallets are three significant independent variables that mediate the role of customer trust in influencing e-payment adoption when using Internet banking services. They should emphasize trust-building activities, specifically in relation to the new ways of e-payment such as e-banking, m-payments, NFC, and e-proximity, which will further help reduce consumer perceptions of risk. The system developers should design user-friendly applications and e-payment apps to enhance consumers’ belief in using them for payment purposes over any Internet-enabled device. They should promptly respond to consumers in cases of failed e-payment transactions and be able to promptly demonstrate transparency in settling claims for such failed transactions. Future studies could benefit from implementing probability sampling to facilitate comparisons with non-probability sampling studies. This study selected responses from only Saudi Arabian adopters of mobile payment technology. We need to conduct research on non-adopters and analyze the results using the model we proposed in this study. Due to time and resource constraints, in depth research using a mixed-methods approach could not be conducted. Future studies can utilize a mixed-methods approach for further understanding.

The purpose of this study was to assess rural students’ computational thinking abilities. The following proofs were observed: (1) Students’ abstraction affected algorithmic thinking skills; (2) Students’ decomposition influenced algorithmic thinking skills; (3) Students’ abstraction impacted evaluation skills; (4) Students’ algorithmic thinking affected evaluation skills; (5) Students’ abstraction impacted generalization skills; (6) Students’ decomposition impacted generalization skills; (7) Students’ evaluation affected generalization skills. Gender differences were observed in the relationship among the computational thinking factors of junior high school students. This included the abstraction-generalization skills; evaluation-generalization skills; and decomposition-generalization skills relationships, which were moderated by the gender of the students. 258 valid surveys were collected, and they were utilized in the study. Conducting the descriptive, reliability, and validity analyses used SPSS software, and the structural equation modeling (SEM) was also conducted through Smart PLS software to assess the hypothetical relationships. There were gender disparities in the correlation among computational thinking components of the junior high school students’ studying in rural areas. Research has shown that male and female students may have different abstractions, evaluations, and generalizations related to computational thinking, with females being more strongly associated than males in non-programming learning contexts. These results are expected to provide relevant information in subsequent analyses and implement a computational thinking curriculum to overcome the still-existing gender gaps and promote computational thinking skills.

This research explores the advancement of Artificial Intelligence (AI) in Occupational Health and Safety (OHS) across high-risk industries, highlighting its pivotal role in mitigating the global incidence of occupational incidents and diseases, which result in approximately 2.3 million fatalities annually. Traditional OHS practices often fall short in completely preventing workplace incidents, primarily due to limitations in human-operated risk assessments and management. The integration of AI technologies has been instrumental in automating hazardous tasks, enhancing real-time monitoring, and improving decision-making through comprehensive data analysis. Specific AI applications discussed include drones and robots for risky operations, computer vision for environmental monitoring, and predictive analytics to pre-empt potential hazards. Additionally, AI-driven simulations are enhancing training protocols, significantly improving both the safety and efficiency of workers. Various studies supporting the effectiveness of these AI applications indicate marked improvements in risk management and incident prevention. By transitioning from reactive to proactive safety measures, the implementation of AI in OHS represents a transformative approach, aiming to substantially reduce the global burden of occupational injuries and fatalities in high-risk sectors.