Advances In Knowledge Research Articles

Multi-modal transformer architecture for medical image analysis and automated report generation

Medical practitioners examine medical images, such as X-rays, write reports based on the findings, and provide conclusive statements. Manual interpretation of the results and report generation by examiners are time-consuming processes that lead to potential delays in diagnosis. We propose an automated report generation model for medical images leveraging an encoder–decoder architecture. Our model utilizes transformer architectures, including Vision Transformer (ViT) and its variants like Data Efficient Image Transformer (DEiT) and BERT pre-training image transformer (BEiT), as an encoder. These transformers are adapted for processing to extract and gain visual information from medical images. Reports are transformed into text embeddings, and the Generative Pre-trained Transformer (GPT2) model is used as a decoder to generate medical reports. Our model utilizes a cross-attention mechanism between the vision transformer and GPT2, which enables it to create detailed and coherent medical reports based on the visual information extracted by the encoder. In our model, we have extended the report generation with general knowledge, which is independent of the inputs and provides a comprehensive report in a broad sense. We conduct our experiments on the Indiana University X-ray dataset to demonstrate the effectiveness of our models. Generated medical reports from the model are evaluated using word overlap metrics such as Bleu scores, Rouge-L, retrieval augmentation answer correctness, and similarity metrics such as skip thought cs, greedy matching, vector extrema, and RAG answer similarity. Results show that our model is performing better than the recurrent models in terms of report generation, answer similarity, and word overlap metrics. By automating the report generation process and incorporating advanced transformer architectures and general knowledge, our approach has the potential to significantly improve the efficiency and accuracy of medical image analysis and report generation.

Epilepsy and musical perception. A perspective involving 14 patients.

The relationship between epilepsy and music is poorly understood. Musicogenic epilepsy, which involves seizures triggered by music, and epilepsy that triggers or involves musical experiences are rare. Anti-seizure medications (ASMs) may affect cognition and possibly the musical sphere. The relationship between epilepsy, ASMs and music perception is insufficiently investigated in the literature. This study describes the clinical characteristics of patients with epilepsy with advanced musical knowledge, and aims to understand the disease's involvement in the musical sphere. A qualitative study was conducted in epileptic patients with musical knowledge, investigating their musical perception before and after a diagnosis of epilepsy and after a change of ASM when this was possible. Questionnaires and recordings of music were used to assess musical perception. Fourteen patients had musical knowledge, and the majority of these (50%) had temporal lobe epilepsy. A total of 92.8% of the patients stated that epilepsy or its medications had affected them in the musical sphere. There was no clear relationship between the lateralisation of the epilepsy and musical involvement. 42.9% were professional musicians, and had to give up their profession. The patients prescribed with more than one ASM had greater musical involvement. Temporal lobe epilepsy appears to have the greatest effect on music perception, and more studies with ASM and music perception are needed to determine its effects.

Comprehensive Review on Natural Language Generation for Automated Report Writing in Finance

The financial industry is transforming with the advent of Natural Language Generation (NLG), a subset of Natural Language Processing (NLP), which automates data conversion into coherent and contextually relevant narratives. This paper presents a comprehensive review of NLG's application in financial report automation, tracing its evolution from template-based methods to advanced deep learning and knowledge graph techniques. We discuss the relevance of NLG in automating report generation, its role in enhancing data analysis and decision-making, and its potential to improve investor communications and compliance with regulations. The paper identifies research gaps, including the need for optimization, accuracy improvement, and the integration of machine learning models for better classification and prediction. A proposed methodology for structured report generation is outlined, leveraging deep learning architectures such as RNNs and LSTMs. Future work aims to address these gaps and further integrate NLG into financial reporting, promising to streamline processes, reduce costs, and provide more personalized and insightful financial narratives.

Artificial intelligence and decision-making in government functions: opportunities, challenges and future research

PurposeArtificial intelligence (AI) has received much attention due to its promethean-like powers to transform the management and delivery of public sector services. Due to the proliferation of research articles in this context, research to date is fragmented into research streams based on different types of AI technologies or a specific government function of the public sector (e.g. health, education). The purpose of this study is to synthesize this literature, identify challenges and opportunities, and offer a research agenda that guides future inquiry.Design/methodology/approachThis paper aggregates this fragmented body of knowledge by conducting a systematic literature review of AI research in public sector organisations in the Chartered Association of Business Schools (CABS)-ranked journals between 2012 and 2023.FindingsThe search strategy resulted in the retrieval of 2,870 papers, of which 61 were identified as primary papers relevant to this research. These primary papers are mapped to the ten classifications of the functions of government as classified by the Organisation for Economic Co-operation and Development (OECD), and the reported challenges and benefits aggregated.Originality/valueThis study advances knowledge by providing a state-of-the-art of AI research based the OECD classifications of government functions, reporting of claimed benefits and challenges and providing a research agenda for future research.

Plant-Derived Terpenoids: A Plethora of Bioactive Compounds with Several Health Functions and Industrial Applications-A Comprehensive Overview.

Terpenoids are a large class of natural secondary plant metabolites which are highly diverse in structure, formed from isoprene units (C-5), associated with a wide range of biological properties, including antioxidant, antimicrobial, anti-inflammatory, antiallergic, anticancer, antimetastatic, antiangiogenesis, and apoptosis induction, and are considered for potential application in the food, cosmetics, pharmaceutical, and medical industries. In plants, terpenoids exert a variety of basic functions in growth and development. This review gives an overview, highlighting the current knowledge of terpenoids and recent advances in our understanding of the organization, regulation, and diversification of core and specialized terpenoid metabolic pathways and addressing the most important functions of volatile and non-volatile specialized terpenoid metabolites in plants. A comprehensive description of different aspects of plant-derived terpenoids as a sustainable source of bioactive compounds, their biosynthetic pathway, the several biological properties attributed to these secondary metabolites associated with health-promoting effects, and their potential industrial applications in several fields will be provided, and emerging and green extraction methods will also be discussed. In addition, future research perspectives within this framework will be highlighted. Literature selection was carried out using the National Library of Medicine, PubMed, and international reference data for the period from 2010 to 2024 using the keyword "terpenoids". A total of 177,633 published papers were found, of which 196 original and review papers were included in this review according to the criteria of their scientific reliability, their completeness, and their relevance to the theme considered.

The consumer behavior in the context of counterfeit products: A bibliometric analysis

This article aims to identify the main areas of works devoted to the topic of counterfeit goods/brands consumption and to present the dynamics of changes in researchers’ interest in this subject. The research method used in the article was bibliometric analysis, complemented by content analysis of literature selected from the Scopus database. Research results: The main areas of research on the issue of counterfeit product consumption focused on 1) online consumer behavior and ethical aspects, 2) consumption of counterfeit products and brands, and 3) social aspects of consumption of counterfeit products. The earliest publications focus on purchasing behavior in the context of buying counterfeit products, followed by researchers who have focused on the ethical aspects of consuming counterfeit goods. More recent studies focus on the consumption and trade of counterfeit goods on the Internet. Conclusions: The ever-expanding global trade in counterfeit products poses a major challenge — it erodes business revenue, undermines innovation, and hampers economic growth. To effectively mitigate these phenomena, it is essential to have up-to-date knowledge of the latest scientific advances in the field. Research into the buyer behavior in the context of counterfeit goods can provide useful information for manufacturers about the scale of the problem and the possible need for remedial action.

A bright side to unethical pro-organizational behavior: Improving work performance by satisfying psychological needs

Despite scholarly efforts to unpack the outcomes of unethical pro-organizational behavior (UPB), its impact has not yet been fully understood. Drawing on self-determination theory, this research advances knowledge about the consequences of UPB by investigating its relationship with psychological needs fulfillment (PNF) and downstream service performance. This research further investigates whether the consequences of UPB are more pronounced among employees with a strong versus weak sense of work meaningfulness. Across a time-lagged multi-source survey (Study 1) and an experiment (Study 2), the results show that UPB is positively associated with PNF, particularly for employees with a strong sense of work meaningfulness, and that this relationship predicts higher in-role service performance and customer-oriented organizational citizenship behavior. Therefore, this research reveals a novel bright side to UPB, providing insight into factors motivates UPB and how to mitigate it.

Co-infection dynamics of B. afzelii and TBEV in C3H mice: insights and implications for future research.

Ticks are important vectors of disease, particularly in the context of One Health, where tick-borne diseases (TBDs) are increasingly prevalent worldwide. TBDs often involve co-infections, where multiple pathogens co-exist in a single host. Patients with chronic Lyme disease often have co-infections with other bacteria or parasites. This study aimed to create a co-infection model with Borrelia afzelii and tick-borne encephalitis virus (TBEV) in C3H mice and to evaluate symptoms, mortality, and pathogen level compared to single infections. Successful co-infection of C3H mice with B. afzelii and TBEV was achieved. Outcomes varied, depending on the timing of infection. When TBEV infection followed B. afzelii infection by 9 days, TBEV symptoms worsened and virus levels increased. Conversely, mice infected 21 days apart with TBEV showed milder symptoms and lower mortality. Simultaneous infection resulted in mild symptoms and no deaths. However, our model did not effectively infect ticks with TBEV, possibly due to suboptimal dosing, highlighting the challenges of replicating natural conditions. Understanding the consequences of co-infection is crucial, given the increasing prevalence of TBD. Co-infected individuals may experience exacerbated symptoms, highlighting the need for a comprehensive understanding through refined animal models. This study advances knowledge of TBD and highlights the importance of exploring co-infection dynamics in host-pathogen interactions.

PLASTIC POLLUTION IN LAGOS STATE, NIGERIA: CHALLENGES AND SUSTAINABLE SOLUTIONS

Plastic pollution poses a significant threat to environmental sustainability, with Nigeria, particularly Lagos State, facing substantial challenges in managing plastic waste. By evaluating the impact of plastic trash on the environment and human well-being and examining prior study findings, this review article critically investigates Lagos, Nigeria's current plastic pollution situation. The study explores existing waste management practices, including illegal disposal methods and infection of water bodies, highlighting the urgent need for sustainable solutions. By synthesizing insights from studies on waste-to-energy technologies and innovative approaches to plastic waste management, this review identifies key research gaps and proposes policy recommendations to deal with the intricate trouble of plastic pollution in Lagos State. The study emphasizes the significance of raising public awareness, putting into practice efficient waste management plans, and creating strong legislative frameworks to mitigate the negative effects that plastic pollution has on the environment and the health of the general people. This review advances knowledge on plastic pollution in Lagos State and offers useful data to policymakers, scholars, and interested parties working to make the state's environment cleaner and healthier for its residents.

Small- and Medium-Sized Enterprises: Trends and Future Perspectives for Sustainability and Digitalization in Germany

The objective of this research was to provide a review of the state-of-the-art literature related to sustainability and digitalization in SMEs to identify current trends and future perspectives within this vital sector. The focus is on German SMEs, which are considered benchmarks, given these firms’ critical role in the country’s economy and job market. A total of 55 peer-reviewed articles were analyzed with the support of the Atlas TI 24.1 software package, focusing on definitions, frameworks, research questions, hypotheses, primary findings, and direct reports from interviewees. Major current trends were identified, clustered in two groups: (1) digitalization, digital transformation, Industry 4.0, and performance; and (2) sustainability, innovation, entrepreneurship, and risk management. Three future perspectives were identified: disseminating digitalization in the market; incorporating sustainability into business models; and increasing investments in government support programs. While the study is focused on German SMEs, its findings are applicable to similar economies within the European Union and can serve as a reference for developing countries’ sustainable development goals (SDGs). This research advances knowledge on how SMEs play a critical role in the context of sustainability and digitalization, both now and in the future.

The Critical Vulnerability of an Authentic Leader as a Сatalyst for Achieving Outstanding Prosocial Results

Having been in management for more than 15 years, we have identified empirical evidence of critical vulnerability in business leaders who implemented large-scale organizational change and ultimately achieved outstanding prosocial outcomes. This vulnerability may present as resistance or criticism from stakeholders—employees, partners, and shareholders—marked by distrust in leadership vision and active sabotage of decisions, which potentially leads to the termination of the leader's powers. However, as the stakeholders' mindset evolves, the vulnerability tends to subside, paving the way for company consolidation, substantial organizational achievements, self-actualization for stakeholders and recognition for the leader. Such shift allows us to hypothesize that: 1) unique behavioral patterns of authentic leaders during organizational change implementation expose them to the observed critical vulnerability but ultimately lead to substantial prosocial results; 2) the main reason for leader vulnerability is the gap in leadership mindset levels between the leader and stakeholders at the onset of organizational change. Relying on the described assumptions, we executed preliminary research on leader vulnerability, aiming to explore unique leader behavior patterns that cause critical vulnerability. The study involved 8 top managers who are currently leading organizational changes within their organizations. We used purposive sampling to ensure participants’ significant leadership experience and their transformative impact. The research methodology relied on qualitative methods—in-depths interviews. Applying the Michigan Model of Leadership with its Competing Values Framework (CVF), we conducted a thematic analysis of the collected data. We determined that vulnerability typically manifests as a result of a strategic endeavor by leaders to ensure the evolution of stakeholder mindset for subsequent empowerment of them. The study advances knowledge about authentic leadership by emphasizing vulnerability's vital function in accomplishing remarkable prosocial organizational outcomes. More research will be required to create a framework for recognizing and assisting leaders who are critically vulnerable during organizational change implementation.

Challenges and Future Perspectives in Photocatalysis: Conclusions from an Interdisciplinary Workshop.

Photocatalysis is a versatile and rapidly developing field with applications spanning artificial photosynthesis, photo-biocatalysis, photoredox catalysis in solution or supramolecular structures, utilization of abundant metals and organocatalysts, sustainable synthesis, and plastic degradation. In this Perspective, we summarize conclusions from an interdisciplinary workshop of young principal investigators held at the Lorentz Center in Leiden in March 2023. We explore how diverse fields within photocatalysis can benefit from one another. We delve into the intricate interplay between these subdisciplines, by highlighting the unique challenges and opportunities presented by each field and how a multidisciplinary approach can drive innovation and lead to sustainable solutions for the future. Advanced collaboration and knowledge exchange across these domains can further enhance the potential of photocatalysis. Artificial photosynthesis has become a promising technology for solar fuel generation, for instance, via water splitting or CO2 reduction, while photocatalysis has revolutionized the way we think about assembling molecular building blocks. Merging such powerful disciplines may give rise to efficient and sustainable protocols across different technologies. While photocatalysis has matured and can be applied in industrial processes, a deeper understanding of complex mechanisms is of great importance to improve reaction quantum yields and to sustain continuous development. Photocatalysis is in the perfect position to play an important role in the synthesis, deconstruction, and reuse of molecules and materials impacting a sustainable future. To exploit the full potential of photocatalysis, a fundamental understanding of underlying processes within different subfields is necessary to close the cycle of use and reuse most efficiently. Following the initial interactions at the Lorentz Center Workshop in 2023, we aim to stimulate discussions and interdisciplinary approaches to tackle these challenges in diverse future teams.

Simulating Structural Dynamics of Metal Catalysts under Operative Conditions.

Structural reconstructions of metal catalysts have been recognized as common phenomena during catalytic reactions, which play a key role in their activities in heterogeneous catalysis. Precisely identifying the structures under the operative conditions becomes a prerequisite to establish a reliable structure-activity relationship and further rationalize the design of metal catalysts. However, real-time capture of the structural variations of catalysts at the atomic level with high-temporal resolution is a grand challenge for present in situ characterizations. During the past decade, significant progress has been made in theory to couple the structures with the reaction conditions to reproduce the experimental observations and predict the adsorbate-induced changes of catalysts in composition, morphology, size, etc. Modeling the dynamic correlation between the structure and activity of the metal catalysts brings us advanced knowledge of heterogeneous catalysis and becomes indispensable for accurate evaluation of the performance of metal catalysts.

Abstract We017: Tnni3k mediates postnatal reactive oxygen species through Prdx2 signaling to induce polyploidization in cardiomyocytes

Fetal CMs are characteristically diploid and regenerative, while adult CMs are polyploid and nonregenerative. Increased polyploidy in postmitotic CMs remains a significant barrier to regeneration in the adult heart. Previously, through the analysis of multiple mouse strains, our lab has shown that Tnni3k, a cardiac-specific kinase, increases polyploidy in the adult heart. The mechanisms that induce CM polyploidization are unknown but could be due to a multitude of changes including the postnatal increase in reactive oxygen species (ROS). ROS is essential in cardiac development and works to promote maturation and facilitate cell signaling. Using HEK293 cells, I have found that Tnni3k physically interacts with Prdx2, a prominent cytoplasmic ROS sensor. This interaction results in hyperactivated Tnni3k kinase activity. Comparing Tnni3k kinase activity with interaction of WT or catalytically dead Prdx2 showed hyperactivity dependent on Prdx2 catalysis. Polyploidization increases along with the increase in ROS after birth, and Tnni3k contributes to increased ploidy in mice. I hypothesize that Tnni3k mediates postnatal ROS through Prdx2 signaling to induce polyploidization in postnatal CMs. Discovering the consequences of this interaction could lead to advanced knowledge of CM cell cycle and provide new therapeutic targets.

Exploring a pilot alcohol and other drug (AOD) nurse practitioner mentoring program: Empirical research mixed methods: A pilot nurse practitioner mentoring program.

To explore the effectiveness and acceptability of a pilot mentoring program for alcohol and other drug (AOD) nurse practitioners (also known globally as addiction nurse practitioners). Mixed method evaluation. Two-phase evaluation comprising survey (demographics, pre- and post-program perceived competency and confidence) with 15 participants completing the pre survey and 10 participants completing the post survey, and qualitative interviews after the program with 10 participants. The quantitative results indicate statistically significant increases in some domains of perceived competence and confidence in treatment. Qualitative findings indicate that participants valued peer support and mentoring from experienced nurse practitioners. Where formal residency or internship programs for nurse practitioners do not exist, informal mentoring programs may address issues inherent in nurse practitioner transition that may impact retention. We recommend further exploration of mentoring programs with larger sample sizes to determine if self-reported clinical improvements are noted. Nurse practitioners are a vital part of the healthcare system; their advanced skills and knowledge place them in an ideal position to address prescriber shortages and access to care for populations underserved by healthcare. However, literature indicates that they are often underutilised, and transition to autonomous practice remains a challenge. Our exploration of a pilot mentoring program for nurse practitioners shows that their knowledge and perceived skills are high, yet peer assistance is valued in transitioning from advanced practice registered nurse to autonomous nurse practitioner. We recommend further trialling and evaluation of nurse practitioner mentoring programs to both increase supply of nurse practitioners and provide greater access to quality healthcare for underserved populations. What problem did the study address? The ability of nurse practitioners to offer advanced practice interventions such as diagnosis and medication management potentially provides a solution to healthcare resource shortages. However, current literature indicates that advanced nurses transitioning to nurse practitioner roles suffer transition shock, leading to burnout and poor retention. What were the main findings? Although this pilot mentoring program shows significant improvements in survey responses on confidence and capability, qualitative data shows that neophyte nurse practitioners value peer support and mentoring from more experienced practitioners. Participants described maintaining ongoing connections with both mentors and fellow mentees, which aided transition to the role of autonomous nurse practitioner. Where and on whom will the research have an impact? The results of this pilot mentoring program indicate that there is benefit to these programs for neophyte nurse practitioners in many specialties. This paper indicates that mentoring programs for nurse practitioners may provide a community of practice and may have a positive impact on transition shock. Good Reporting of a Mixed Methods Study (GRAMMS) checklist. No patient or public contribution.

Enhancing cassava grater design: A customer-driven approach using AHP, QFD, and TRIZ integration

Due to consistent cassava cultivation, small-scale processing centers rely heavily on the cassava grater. However, these machines face stagnation in innovation and design evolution, leading to inefficiencies, limited capacity, and inconsistent output. Adding to these challenges is the competitive global market, demanding a focus on design enhancements. This study employs a multi-faceted approach involving the Analytic Hierarchy Process (AHP), Quality Function Deployment (QFD) and Theory of Inventive Problem Solving (TRIZ) to prioritize customer requirements, propose technically aligned solutions, and offer innovative design options for cassava graters. A total of 10 customer requirements (CR), 21 technical solutions (TS), and 63 innovative design options (IDO) were established and prioritized, aiming for easy adoption by fabricators, engineers, manufacturers, and artisans. Implementing these insights boosts cassava grater efficiency and productivity and significantly advances knowledge. This work presents a thorough scientific framework for product design, empowering local manufacturers to remain viable and relevant in the rapidly changing field of product enhancement.

Success factors for interventions to reduce low-value imaging. Six crucial lessons learned from a practical case study in Norway

BackgroundSubstantial overuse of health care services is identified and intensified efforts are incited to reduce low-value services in general and in imaging in particular. ObjectiveTo report crucial success factors for developing and implementing interventions to reduce specific low-value imaging examinations based on a case study in Norway. Materials and methodsMixed methods design including one systematic review, one scoping review, implementation science, qualitative interviews, content analysis of stakeholders’ input, and stakeholder deliberations. ResultsThe description and analysis of an intervention to reduce low-value imaging in Norway identifies six general success factors: 1) Acknowledging complexity: advanced knowledge synthesis, competence of the context, and broad and strong stakeholder involvement is crucial to manage de-implementation complexity. 2) Clear consensus-based criteria for selecting low-value imaging procedures are key. 3) Having a clear target group is critical. 4) Stakeholder engagement is essential to ascertain intervention relevance and compliance. 5) Active and well-motivated intervention collaborators is imperative. 6) Paying close attention to the mechanisms of low-value imaging and the barriers to reduce it is decisive. ConclusionReducing low-value imaging is crucial to increase the quality, safety, efficiency, and sustainability of the health services. Reducing low-value imaging is a complex task and paying attention to specific practical success factors is key.

Management of Sepsis in the First 24 Hours: Bundles of Care and Individualized Approach.

Early diagnosis and prompt management are essential to enhance the outcomes of patients with sepsis and septic shock. Over the past two decades, evidence-based guidelines have guided appropriate treatment and recommended the implementation of a bundle strategy to deliver fundamental treatments within the initial hours of care. Shortly after its introduction, the implementation of a bundle strategy has led to a substantial decrease in mortality rates across various health care settings. The primary advantage of these bundles is their universality, making them applicable to all patients with sepsis. However, this same quality also represents their primary disadvantage as it fails to account for the significant heterogeneity within the septic patient population. Recently, the individualization of treatments included in the bundle has been suggested as a potential strategy for further improving the prognosis of patients with sepsis. New strategies for the early identification of microorganisms and their resistance patterns, advanced knowledge of antibiotic kinetics in critically ill patients, more conservative fluid therapy in specific patient populations, and early use of alternative vasopressors to catecholamines, as well as tailored source control based on patient conditions and site of infection, are potential approaches to personalize initial care for specific subgroups of patients. These innovative methodologies have the potential to improve the management of septic shock. However, their implementation in clinical practice should be guided by solid evidence. Therefore, it is imperative that future research evaluate the safety, efficacy, and cost-effectiveness of these strategies.

Investigating subsurface structural lineaments of the northwest Ethiopian plateau using gravity data

This study provides advanced knowledge of the subsurface structural characteristics of the northwest Ethiopian plateau. With its complex geologic structure, the Northwest Ethiopian plateau is being studied for density boundary mapping using geophysical methods. However, its application to the mapping of geological structures such as faults and contacts which appear as lineaments in gravity data has not been studied so far. Thus, the goal of this research is to increase our understanding of the subsurface structural lineaments and their depth beneath the Ethiopian plateau in the northwest using global gravity model GGMplus2013. These subsurface structural lineaments and their depths were investigated using the LTHG, EHGA, and tilt depth techniques. The results indicate that the main subsurface structural lineaments identified in the study region are dipping between 3.2 and 8 km and are developing in the NE-SW, N–S, E-W, and NW-SE orientations.

Financial Literacy and Mental Health: Empirical Evidence from China.

While financial literacy is a plausible determinant of mental health, there are relatively few studies exploring the relationship between financial literacy and mental health, and the existing literature focuses on a single construct of financial literacy in high-income settings. Our study addresses this by investigating whether there is an association between financial knowledge, attitudes, and behaviours and mental health in Chinese adults. We use data from the China Family Panel Studies, a nationally representative longitudinal survey. Mental health is measured using the Kessler Psychological Distress Scale (K6) and financial literacy is assessed using a unique module on financial literacy covering financial knowledge, financial attitudes and financial behaviours. We found that overall financial literacy and two of its dimensions (financial attitudes and financial behaviours) are always positively associated with mental health. A positive association between basic financial knowledge and mental health is also apparent but is mediated by households' finances. Our results are robust to using different outcome variables and estimation methods. Finally, we found that compared with their counterparts without debt, indebted respondents show a stronger sensitivity of mental health to basic financial knowledge, as well as a significant association between advanced financial knowledge and mental health, which persist when we control for households' finances. Our findings suggest that investments in financial education might significantly benefit mental health in Chinese adults. This is especially the case among indebted adults.