Financial Health Research Articles

Multiple Linear Regression Analysis of Factors Contributing to the Spread of Cholera in Kenya from 2000 to 2022

Cholera is a deadly disease caused by consumption of either food or water that is contaminated with bacterium known as Vibro cholerae. In the 19<sup>th</sup> century, Cholera had spread across the globe from its original source in Ganges Delta, India. This research aimed to investigated the factors contributing to the spread of Cholera in Kenya from 2000 to 2022. The key objective was to fit a multiple linear regression model which aid in determining the goodness of fit as well as examining the relationship between different types of drinking water and spread of Cholera. Secondary data was obtained from United Nations International Children’s Emergency Fund (UNICEF) and World Health Organization (WHO). The results showed a strong positive linear relationship between Surface water and proportion of population affected by Cholera. 88% total variation in the proportion of population being affected by Cholera can be explained by the Unimproved Basic water (UBW), Surface water (SW) and Least Basic drinking water (LBW). Significantly this research encouraged the use of the least basic drinking water which clearly showed an inverse proportion to the proportion of population affected by Cholera. In addition to that, the researchers recommend improved access to clean water and create awareness on the dangers of using untreated water.

The Economic and Financial Health of Lithuanian Logistics Companies

The Economic and Financial Health of Lithuanian Logistics Companies

A cultural aspect, firms’ financial health and earnings management: evidence from the Asia-Pacific region

A cultural aspect, firms’ financial health and earnings management: evidence from the Asia-Pacific region

Multi-Dimensional Decomposition, Measurement, and Governance Mechanism of Relative Poverty in Chinese Households under the Goal of Common Prosperity: Empirical Analysis Based on CFPS2020 Data

From the perspective of household productivity, this paper analyzes the capital composition of the household and the formation mechanism of relative poverty. Based on the CFPS data in 2020, it uses the Alkire–Foster (AF) index to measure the breadth and depth of relative poverty in different regions and puts forward its governance mechanism. The results show that there are significant differences between urban and rural areas and among different regions. The relative poverty incidence rate is mainly concentrated in four indicators, accounting for 30.8% of the total number of indicators. From high to low, the incidences of relative poverty in a single dimension include financial assets, livelihood assets, health, and employment levels. The breadth is mainly reflected in economic capital, health, employment, and education level. The depth is reflected in financial assets, health level, and social network indicators. Except for the social capital dimension, the poverty in rural areas is higher than urban areas, and the central and western regions are higher than the eastern regions, showing a distinct characteristic of imbalanced urban–rural and regional development. This paper proposes the relative poverty governance mechanism of households’ capital accumulation, urban–rural integrated development and regional coordinated development.

NURS-05. CATALYZING AND INFORMING THE DEVELOPMENT OF MORE COMPREHENSIVE AND ACCESSIBLE PROGRAMS FOR CAREGIVERS OF YOUNG ADULT SURVIVORS OF CHILDHOOD BRAIN TUMORS

Abstract BACKGROUND The chronic and intensive care needs of young adult survivors of childhood brain tumors are most often addressed by their maternal caregivers with limited, specific psychosocial or other programs to reduce caregiving demands and enhance their family management. Using a social ecological perspective, the purpose of this study was to catalyze and inform the development of more comprehensive and accessible programs for caregivers of young adult survivors of childhood brain tumors. METHODS Semi-structured interviews were conducted with 21 maternal caregivers, 6 post baccalaureate students/professional coaches for a problem-solving intervention for maternal caregivers, and 16 neuro-oncology clinical experts using interview guides tailored to their roles and constructed based on the Consolidated Framework for Implementation Science. Qualitative. Interview data were analyzed using content analysis. RESULTS Barriers included: need for internet connected devices (microsystem level); lack of care matched to their identified needs (mesosystem); poor tracking of long-term survivors and lack of survivorship psychosocial services (macrosystem); and lack of supportive health care policies and funding mechanisms for individuals and organizations (exosystem). Facilitators included: web-based platform accessible to the individuals and population (microsystem); widespread acknowledgement regarding gaps in survivorship psychosocial care (mesosystem); partnerships with survivors of childhood brain tumors, caregivers, and organizations that treat them (macrosystem); and dissemination among childhood brain tumor treatment/survivorship programs, healthcare systems, and community organization and endorsement from them (exosystem). CONCLUSIONS Multilevel approaches that address barriers and facilitators for improving health equity for maternal caregivers of young adult survivors of childhood brain tumors incorporate the design and dissemination of accessible, web-based programs designed in partnership with survivors, caregivers, and organizations to build care matched to need, as well as organizational, political, and community advocacy.

Paternal Use of Metformin During the Sperm Development Period Preceding Conception and Risk for Major Congenital Malformations in Newborns.

Metformin is the most used oral antidiabetic medication. Despite its established safety profile, it has known antiandrogenic and epigenetic modifying effects. This raised concerns about possible adverse developmental effects caused by genomic alterations related to paternal use of metformin during the spermatogenesis period preceding conception. To assess the potential adverse intergenerational effect of metformin by examining the association between paternal metformin use during spermatogenesis and major congenital malformations (MCMs) in newborns. Nationally representative cohort study. A large Israeli health fund. 383 851 live births linked to fathers and mothers that occurred in 1999 to 2020. MCMs and parental cardiometabolic conditions were ascertained using clinical diagnoses, medication dispensing information, and laboratory test results. The effect of metformin use on MCMs was estimated using general estimating equations, accounting for concurrent use of other antidiabetic medications and parental cardiometabolic morbidity. Compared with unexposed fathers, the prevalence of cardiometabolic morbidity was substantially higher among fathers who used metformin during spermatogenesis, and their spouses. Whereas the crude odds ratio (OR) for paternal metformin exposure in all formulations and MCMs was 1.28 (95% CI, 1.01 to 1.64), the adjusted OR was 1.00 (CI, 0.76 to 1.31). Within specific treatment regimens, the adjusted OR was 0.86 (CI, 0.60 to 1.23) for metformin in monotherapy and 1.36 (CI, 1.00 to 1.85) for metformin in polytherapy, a treatment that was more common in patients with more poorly controlled diabetes. Laboratory test results for hemoglobin A1c to assess underlying diabetes severity were available only for a subset of the cohort. Paternal use of metformin in monotherapy does not increase the risk for MCMs. Association for metformin in polytherapy could potentially be explained by worse underlying parental cardiometabolic risk profile. None.

The Impact of a Company’s Management Strategy on Its Profitability, Stability, and Growth: A Focus on the Information Security Industry

This study concentrated on a business report that typically reveals a company’s non-financial information, aiming to uncover its strategic direction. Using text-mining techniques, the research extracted and analyzed the report’s overview sections, identifying key strategic themes categorized into the financial, customer, learning and growth, and internal process perspectives. The empirical analysis applied a two-stage model to assess how shifts in company strategies affect profitability, stability, and growth. This research provided insights into the management strategies and financial metrics within the information security sector, examining how strategic priorities shape financial health. The findings were as follows. Firstly, companies emphasizing financial strategies in their reports tended to exhibit higher profitability. Secondly, those focusing on customer-oriented strategies also reported greater profitability. Thirdly, companies prioritizing internal processes demonstrated increased organizational stability. Fourthly, an emphasis on learning and growth strategies was associated with lower stability but higher growth potential. This paper contributes to the field by offering a method to quantitatively analyze qualitative textual data, providing a more precise approach to understanding management strategies through direct content analysis of business reports. It also highlights the specific financial and strategic characteristics of information security firms, a relatively under-researched area, thereby offering valuable guidance for these companies in terms of strategic planning.

The CJEU’s Unintelligible Impairment of the Financial Health of EU Performers: Ever-Increasing Suspense in Neighbouring Rights

Abstract With the RAAP ruling in 2020, the Court of Justice of the European Union (CJEU) delivered a judgment with a far-reaching impact, both on the autonomy of Member States within the making of reservations under international treaties, and on revenues for collecting societies and neighbouring rightsholders in the EU. The controversial part of the judgment states that entering reservations on the granting of equitable remuneration for neighbouring rights on the basis of international treaties should only take place at EU level. This effectively leaves no autonomy to Member States within the principle of reciprocity, contrary to former popular belief by many Member States and scholars. The US has entered reservations with regard to EU countries under Art. 15(3) WIPO Performances and Phonograms Treaty (WPPT), thus no remuneration is disbursed for performances by EU artists in the US. Due to the US repertoire’s large presence in the EU, the latter’s performers will be left with a considerably smaller share of the revenues to be distributed by EU collecting societies. The European Commission must urgently finish the ongoing research and consultation on RAAP. Right now, too many requests by interest groups remain unanswered. The recommended (and hoped for) route is for the EU to invoke the principle of reciprocity and enter reservations for other WPPT parties that have entered such reservations with regard to EU countries. An extensive arrangement regarding reservations is necessary, also regarding situations where the relationship between fundamental rights and reciprocity provisions is currently unknown.

Relationship between bank value, tax avoidance, and profitability

This study explores the intricate relationships between bank value, tax avoidance, and profitability, which significantly affect the stability and strategies of financial institutions worldwide. Understanding these connections is vital for comprehending the financial dynamics of banks, key players in economic growth and stability. The study focuses on these three factors due to their intertwined roles in shaping fiscal policy effectiveness, shareholder satisfaction, and overall financial health. The aim of this study is to explore the relationships between the bank value, tax avoidance and profitability aiming to clarify their interactions and their impact on the Jrdanian banks. Ordinary Least Squares regression analysis is employed using a mixed-methods approach, including quantitative regression analysis and qualitative assessments. The study results reveal a significant direct link between bank tax avoidance and profitability. The increase in Return on Assets is associated with a substantial increase in tax avoidance. In the expanded model, bank value and size did not exhibit statistically significant incremental information over profitability in explaining tax avoidance. Profitability emerges as a dominant factor, overshadowing the potential impact of size and value. The results underscore profitability as a key driver in bank tax strategies, highlighting a potential area for regulatory scrutiny and strategic realignment. In conclusion, the study underscores the pivotal influence of bank profitability on tax avoidance strategies. Policymakers, practitioners, and researchers are encouraged to recognize the prominence of profitability in formulating tax strategies.

Post Flood Economic Challenges; Resilience and Rehabilitation Strategies With Thematic Analysis Approach. A Case of Larkana

Climate change has exacerbated the frequency and severity of floods, leading to devastating impacts worldwide. Pakistan has seen two catastrophic floods in recent years; at present, the full extent of the consequences of these calamities is still not fully acknowledged. Scarcity of water, rise in temperature, and floods are some cruel consequences that Pakistan has to bear. Floods may lead to huge economic problems not only for people in general but also for the communities. For instance, the condition of flooding in Larkana, which is the province where the agricultural activities are too much, could bring about financial and mental health problems. To tackle this research gap, this study implemented a qualitative research approach and conducted a thematic analysis to explore the economic challenges encountered in the Larkana region as a result of floods. Theme analysis is a method by which the researcher finds the sequential patterns in the data. Thus, the researcher is able to point out the issues that people face in reality. Resilient plans and rehabilitation measures can contribute to the solutions to these challenges, varying from immediate recovery to sustainable development. A multifaceted plan that encompasses immediate rescue operations and strengthening of resilience is a must. Social cohesion, environmental protection measures and governance issues are most relevant for the effective economic recovery after floods. The economic regeneration strategy in flood-prone areas must address complex issues to ensure local resilience and preparedness for the coming years.

An Evaluation of the Impact of Merger and Acquisition on the Financial Health of Banks: A Case Study of Atlas Mara Bank – Zambia

An Evaluation of the Impact of Merger and Acquisition on the Financial Health of Banks: A Case Study of Atlas Mara Bank – Zambia

Impact of Non-Performing Assets on Financial Performance: An Empirical Analysis of Primary Agricultural Development Banks in Punjab

This paper investigates the impact of Non-Performing Assets (NPAs) on the financial performance of Primary Agricultural Development Banks (PADBs) in Punjab. Utilizing financial data from 2010 to 2020, the study employs a panel regression model to analyse how NPAs affect key financial metrics. The results demonstrate a significant negative correlation between NPAs and financial performance indicators such as Return on Assets (ROA) and Return on Equity (ROE), highlighting the detrimental effects of high NPA levels on PADBs' financial health. It underscores the need for robust risk management practices, enhanced governance, and effective recovery mechanisms to mitigate the impact of NPAs. The findings suggest that addressing these challenges through targeted reforms and aligning PADBs with broader financial sector improvements is crucial for sustaining agricultural development and economic stability in Punjab. Keywords: NPAs, PADBs, Financial Performance, Risk Management, Agricultural Policies

HPR98 Consumption of Hospital Resources in Intensive Care Units in Brazil: A Challenge for Health Financing

HPR98 Consumption of Hospital Resources in Intensive Care Units in Brazil: A Challenge for Health Financing

AI in Dynamic Budgeting and Forecasting

Artificial Intelligence (AI) has emerged as a pivotal force in transforming a wide array of industries, and its impact on the financial sector, particularly in the domains of dynamic budgeting and forecasting, has been profound. Dynamic budgeting and forecasting are essential financial functions that involve the continuous allocation of resources and the prediction of future financial states. These processes are critical for organizations to maintain financial health, respond to market fluctuations, and align their resources with strategic objectives. Traditionally, budgeting and forecasting have relied heavily on historical data, linear models, and static assumptions, often resulting in rigid frameworks that struggle to adapt to the volatile and complex economic environments of today.The limitations of these conventional methods become increasingly apparent in the face of rapid technological advancements, global market dynamics, and unpredictable economic events. Traditional approaches tend to be time-consuming, inflexible, and prone to inaccuracies, especially when faced with sudden changes in market conditions or unexpected disruptions. These challenges have necessitated the exploration of more sophisticated, responsive, and predictive methods—enter AI. With its unparalleled ability to process vast datasets, identify hidden patterns, and make real-time adjustments, AI presents a formidable solution to the inefficiencies inherent in traditional budgeting and forecasting techniques. This paper delves into the integration of AI within dynamic budgeting and forecasting frameworks, examining the transformative potential of AI-driven methodologies. By leveraging advanced AI techniques such as machine learning, neural networks, and predictive analytics, organizations can significantly enhance the accuracy, efficiency, and adaptability of their financial forecasts. Machine learning, for instance, allows for the analysis of historical and real-time data, enabling the creation of models that can predict future financial scenarios with remarkable precision. Neural networks, with their capacity to model complex, non-linear relationships, offer further enhancement by allowing for the consideration of a multitude of variables and their interactions. Predictive analytics, on the other hand, provides organizations with the tools to foresee potential financial outcomes and adjust their strategies accordingly, thereby fostering a proactive rather than reactive approach to financial management. The research presented in this paper not only explores the theoretical underpinnings of AI in dynamic budgeting and forecasting but also provides an in-depth analysis of real-world applications. Through a series of case studies, the paper illustrates how leading organizations have successfully integrated AI into their financial planning processes, resulting in improved decision-making, more accurate forecasts, and ultimately, a stronger alignment with business goals. These case studies highlight the tangible benefits of AI-driven budgeting tools, such as reduced forecasting errors, enhanced resource allocation, and the ability to swiftly adapt to changing market conditions. Moreover, this paper employs a combination of mathematical models and analytical techniques to demonstrate the practical implementation of AI in budgeting and forecasting. It addresses the technical aspects of deploying AI models, such as the selection of appropriate algorithms, the integration of AI tools with existing financial systems, and the interpretation of AI-generated insights. The mathematical expressions and calculations included provide a clear illustration of how AI can be harnessed to optimize budgeting processes, reduce operational inefficiencies, and enhance financial performance. The literature review component of this paper further situates the discussion within the broader context of existing research, identifying the key trends, challenges, and opportunities in the application of AI to financial planning. It critically examines the successes and limitations of previous studies, thereby laying the groundwork for the new insights and recommendations that this paper contributes to the field. This paper offers a comprehensive understanding of the role of AI in revolutionizing traditional budgeting and forecasting methods. By exploring both the theoretical and practical dimensions of AI integration, the research provides valuable insights for financial managers, AI practitioners, and policymakers alike. The findings underscore the potential of AI to not only enhance the accuracy and adaptability of financial forecasts but also to fundamentally transform the way organizations approach budgeting, thereby enabling more informed, strategic, and agile financial decision-making in an increasingly complex and unpredictable world.

The Application of Machine Learning in Diagnosing the Financial Health and Performance of Companies in the Construction Industry

Diagnosing the financial health of companies and their performance is currently one of the basic questions that attracts the attention of researchers and experts in the field of finance and management. In this study, we focused on the proposal of models for measuring the financial health and performance of businesses. These models were built for companies doing business within the Slovak construction industry. Construction companies are identified by their higher liquidity and different capital structure compared to other industries. Therefore, simple classifiers are not able to effectively predict their financial health. In this paper, we investigated whether boosting ensembles are a suitable alternative for performance analysis. The result of the research is the finding that deep learning is a suitable approach aimed at measuring the financial health and performance of the analyzed sample of companies. The developed models achieved perfect classification accuracy when using the AdaBoost and Gradient-boosting algorithms. The application of a decision tree as a base learner also proved to be very appropriate. The result is a decision tree with adequate depth and very good interpretability.

Lived Experiences of Teachers Handling Bajao Learners in the Context of Blended Learning: A Phenomenological Approach

This study investigates teachers' perspectives on handling Bajao learners in the context of blended learning. Phenomenological qualitative research using interviews with seven (7) faculty members from Sta. Ana District, Davao City Division, was undertaken in order to contribute teachers' voices dealing with indigenous learners while implementing distance education. In-person interviews were conducted, audiotaped, transcribed, and evaluated for recurring themes. Member checks and peer reviews were used to verify the data. Several themes emerged from the teachers’ experiences with Bajao learners. Most participants shared their perspectives on the struggles of Bajao learners. Many expressed that Bajao learners and their families were reluctant to report symptoms for fear of financial and physical health consequences. Access to digital resources was a major issue for staying on track with distance learning. Many were unable to afford or have access to their daily necessities. Family financial strain, agitation, a poor learning environment, and behavioral fatigue posed challenges for teachers. Teachers must adopt certain strategies, such as (a) alternative student assessment delivery, (b) encouraging parental support through communication and a positive approach, and (c) outsourcing and the use of personal funds to meet needs. Participants reflected on teaching ideals and expressed their preference for face-to-face delivery. The review of blended learning delivery and the enhancement of programs aimed at improving Bajao's quality of life were also observed. Therefore, we recommend that public and private institutions collaborate to create culture-based instruction for Bajao learners.

A Scoping Review of Health Equity Interventions in Governmental Public Health.

Despite major efforts in research, practice, and policy, racial and ethnic disparities in health and health care persist in the United States. Interventions in collaboration with governmental public health may provide ways to address these persistent racial and ethnic health and health care disparities and improve health outcomes. To conduct a comprehensive review of health equity interventions performed in collaboration with public health agencies. This scoping review includes intervention studies from Ovid MEDLINE, PsycINFO, and Academic Search Premier, published between 2017 and 2023. The search strategy used terminology focused on 4 concepts: race/ethnicity, equity, health departments, and epidemiologic studies. The following inclusion criteria were determined a priori: (1) intervention tailored to reduce racial/ethnic health disparities, (2) public health department involvement, (3) health outcome measures, (4) use of epidemiologic study methods, (5) written in English, (6) implemented in the United States, (7) original data (not a commentary), and (8) published between January 2017 and January 2023. This review focused primarily on 4 dimensions of racial health equity interventions including intervention components, intervention settings, intervention delivery agents, and intervention outcomes. This review indicated that health equity interventions involving public health agencies focused on the following categories: (1) access to care, (2) health behavior, (3) infectious disease testing, (4) preventing transmission, and (5) cancer screening. Critical strategies included in interventions for reaching racial/ethnic minoritized people included using community settings, mobile clinics, social media/social networks, phone-based interventions, community-based workers, health education, active public health department involvement, and structural/policy change. This scoping review aims to provide an evidence map to inform public health agencies, researchers, and funding agencies on gaps in knowledge and priority areas for future research and to identify existing health equity interventions that could be considered for implementation by public health leaders.

Using Bibliometric Data to Define and Understand Publishing Network Equity in Anesthesiology.

Anesthesiology departments and professional organizations increasingly recognize the need to embrace diverse membership to effectively care for patients, to educate our trainees, and to contribute to innovative research. 1 Bibliometric analysis uses citation data to determine the patterns of interrelatedness within a scientific community. Social network analysis examines these patterns to elucidate the network's functional properties. Using these methodologies, an analysis of contemporary scholarly work was undertaken to outline network structure and function, with particular focus on the equity of node and graph-level connectivity patterns. Using the Web of Science, this study examines bibliographic data from 6 anesthesiology-specific journals between January 1, 2017, and August 26, 2022. The final data represent 4453 articles, 19,916 independent authors, and 4436 institutions. Analysis of coauthorship was performed using R libraries software. Collaboration patterns were assessed at the node and graph level to analyze patterns of coauthorship. Influential authors and institutions were identified using centrality metrics; author influence was also cataloged by the number of publications and highly cited papers. Independent assessors reviewed influential author photographs to classify race and gender. The Gini coefficient was applied to examine dispersion of influence across nodes. Pearson correlations were used to investigate the relationship between centrality metrics, number of publications, and National Institutes of Health (NIH) funding. The modularity of the author network is significantly higher than would be predicted by chance (0.886 vs random network mean 0.340, P < .01), signifying strong community formation. The Gini coefficient indicates inequity across both author and institution centrality metrics, representing moderate to high disparity in node influence. Identifying the top 30 authors by centrality metrics, number of published and highly cited papers, 79.0% were categorized as male; 68.1% of authors were classified as White (non-Latino) and 24.6% Asian. The highly modular network structure indicates dense author communities. Extracommunity cooperation is limited, previously demonstrated to negatively impact novel scientific work. 2 , 3 Inequitable node influence is seen at both author and institution level, notably an imbalance of information transfer and disparity in connectivity patterns. There is an association between network influence, article publication (authors), and NIH funding (institutions). Female and minority authors are inequitably represented among the most influential authors. This baseline bibliometric analysis provides an opportunity to direct future network connections to more inclusively share information and integrate diverse perspectives, properties associated with increased academic productivity. 3 , 4.

Determinants of the Financial Health of Deposit Guarantee Corporation in the Pandemic Era (Case Study at PT. XYZ Sharia)

PT. XYZ Sharia is a deposit guarantee corporation (“Lembaga Penjamin”), which obliged to maintain its financial health as explained in the Financial Services Authority Circular Letter Number 18/SEOJK.05/2018. During the pandemic era PT. XYZ Sharia is faced with strategic issues relating to the implementation of more effective risk management. This is expected to provide protection for the company against losses and maintain the company's financial health level in the very healthy category. This research aims to analyze the significance of liquidity calculations, Gearing Ratio, ROA, BOPO and claims ratio on the level of financial health of PT XYZ Sharia. The research used multiple linear regression analysis. The data are secondary data originating from the financial reports of PT XYZ Sharia for 2021-2022. The research found that the Gearing Ratio and BOPO had positive and significant effects on the company's health level. Simultaneously, liquidity, Gearing Ratio, ROA, BOPO and Claims Ratio have a significant effect on the company's financial health level. Keywords: BOPO, Claims Ratio, Deposit Guarantee Companies, Financial Health, Gearing Ratio, JEL Classifications: G23, I12, Liquidity, ROA.

Enhancing Financial Performance: The Crucial Role of Working Capital Management in E- Commerce Retail Sector

The rapid expansion of ecommerce stores has changed the competitive landscape, requiring new ways to maintain financial health. This study examines the critical role of working capital manag ement (WCM) in financial development in the ecommerce retail industry. Implementing WCM i nvolves monitoring existing assets and liabilities to ensure adequate capacity and efficiency. By analyzing key components such as inventory management, accounts receivable, and payroll, this study demonstrates how effectively WCM can increase revenue, reduce operating costs, and incr ease revenue. Case studies of ecommerce companies revealed best practices and the impact of te chnology solutions on WCM. Findings show that companies that maintain effective WCM are ab le to withstand business fluctuations and sustain longterm growth. This article highlights the imp ortance of integrating financial strategies and strategies into business management to improve fin ancial performance in e-commerce.