Browse publications by year: 2024

  1. Rajendran EG, Mohd Hairi F, Krishna Supramaniam R, T Mohd TAM
    Digit Health, 2024;10:20552076241256877.
    PMID: 39139190 DOI: 10.1177/20552076241256877
    BACKGROUND: Precision Public Health (PPH) is a newly emerging field in public health medicine. The application of various types of data allows PPH to deliver more tailored interventions to a specific population within a specific timeframe. However, the application of PPH possesses several challenges and limitations that need to be addressed.

    OBJECTIVE: We aim to provide evidence of the various use of PPH in outbreak management, the types of data that could be used in PPH application, and the limitations and barriers in the application of the PPH approach.

    METHODS AND ANALYSIS: Articles were searched in PubMed, Web of Science, and Science Direct. Our selection of articles was based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) for Scoping Review guidelines. The outcome of the evidence assessment was presented in narrative format instead of quantitative.

    RESULTS: A total of 27 articles were included in the scoping review. Most of the articles (74.1%) focused on PPH applications in performing disease surveillance and signal detection. Furthermore, the data type mostly used in the studies was surveillance (51.9%), environment (44.4), and Internet query data. Most of the articles emphasized data quality and availability (81.5%) as the main barriers in PPH applications followed by data integration and interoperability (29.6%).

    CONCLUSIONS: PPH applications in outbreak management utilize a wide range of data sources and analytical techniques to enhance disease surveillance, investigation, modeling, and prediction. By leveraging these tools and approaches, PPH contributes to more effective and efficient outbreak management, ultimately reducing the burden of infectious diseases on populations. The limitation and challenges in the application of PPH approaches in outbreak management emphasize the need to strengthen the surveillance systems, promote data sharing and collaboration among relevant stakeholders, and standardize data collection methods while upholding privacy and ethical principles.

  2. Tiong HY, So WZ, Yuen-Chun Teoh J, Isotani S, Zhu G, Ong TA, et al.
    Asian J Urol, 2024 Jul;11(3):443-449.
    PMID: 39139525 DOI: 10.1016/j.ajur.2022.12.002
    OBJECTIVE: To correlate the utility of the Fundamentals of Laparoscopic Surgery (FLS) manual skills program with the Objective Structured Assessment of Technical Skills (OSATS) global rating scale in evaluating operative performance.

    METHODS: The Asian Urological Surgery Training and Educational Group (AUSTEG) Laparoscopic Upper Tract Surgery Course implemented and validated the FLS program for its usage in laparoscopic surgical training. Delegates' basic laparoscopic skills were assessed using three different training models (peg transfer, precision cutting, and intra-corporeal suturing). They also performed live porcine laparoscopic surgery at the same workshop. Live surgery skills were assessed by blinded faculty using the OSATS rating scale.

    RESULTS: From March 2016 to March 2019, a total of 81 certified urologists participated in the course, with a median of 5 years of post-residency experience. Although differences in task time did not reach statistical significance, those with more surgical experience were visibly faster at completing the peg transfer and intra-corporeal suturing FLS tasks. However, they took longer to complete the precision cutting task than participants with less experience. Overall OSATS scores correlated weakly with all three FLS tasks (peg transfer time: r=-0.331, r 2=0.110; precision cutting time: r=-0.240, r 2=0.058; suturing with intra-corporeal knot time: r=-0.451, r 2=0.203).

    CONCLUSION: FLS task parameters did not correlate strongly with OSATS globing rating scale performance. Although FLS task models demonstrated strong validity, it is important to assimilate the inconsistencies when benchmarking technical proficiency against real-life operative competence, as evaluated by FLS and OSATS, respectively.

  3. Mohd Tohit NF, Haque M
    Cureus, 2024 Aug;16(8):e66723.
    PMID: 39139803 DOI: 10.7759/cureus.66723
    This scoping review aims to comprehensively explore the landscape of taboos and their impact on sexual and reproductive health. Titled "Forbidden Conversations," it delves into the intricate web of societal, cultural, and religious norms that have contributed to the elusive and often stigmatized nature of sexual and reproductive health topics. The review navigates through the multifaceted dimensions of these taboos, shedding light on their impact on individuals, communities, and public health while advocating for a paradigm shift toward open, inclusive, and informed dialogue. The analysis within this review spans a decade, capturing the most recent and relevant literature to map the landscape of taboos in sexual and reproductive health. It explores the persistent societal apprehensions and subsequent stigmatization surrounding topics such as menstruation, contraception, fertility, sexual orientation, and gender identity. The review contextualizes the multifaceted challenges presented by these prevailing norms by tracing historically rooted taboos and their evolution across different cultures and contexts. The scoping review identifies the profound implications of these taboos on public health, highlighting how they contribute to disparities in access to healthcare, perpetuate misinformation, and infringe upon the fundamental rights of individuals. It addresses the challenges in sexual education, emphasizing how these taboos impede comprehensive understanding and enforcement of sexual and reproductive health rights among adolescents and young adults. The intersectional approach taken in this review situates these taboos within broader systems of inequality, emphasizing the compounded impact they have on marginalized populations. Through this comprehensive exploration, the review aims to provide actionable insights and identify existing research, policy, and practice gaps. It seeks to lay the foundation for future initiatives that advocate for destigmatization, empowerment, and equity in sexual and reproductive health. Ultimately, "Forbidden Conversations" aims to steer the conversation toward openness and inclusivity while advocating for unbiased, comprehensive sexual and reproductive healthcare with dignity for all individuals.
  4. Yu KL, Ong HC, Zaman HB
    J Environ Manage, 2024 Sep;368:122085.
    PMID: 39142099 DOI: 10.1016/j.jenvman.2024.122085
    The production of renewable biofuel through microalgae and green technology can be a promising solution to meet future energy demands whilst reducing greenhouse gases (GHG) emissions and recovering energy for a carbon-neutral bio-economy and environmental sustainability. Recently, the integration of Energy Informatics (EI) technology as an emerging approach has ensured the feasibility and enhancement of microalgal biotechnology and bioenergy applications. Integrating EI technology such as artificial intelligence (AI), predictive modelling systems and life cycle analysis (LCA) in microalgae field applications can improve cost, efficiency, productivity and sustainability. With the approach of EI technology, data-driven insights and decision-making, resource optimization and a better understanding of the environmental impact of microalgae cultivation could be achieved, making it a crucial step in advancing this field and its applications. This review presents the conventional technologies in the microalgae-based system for wastewater treatment and bioenergy production. Furthermore, the recent integration of EI in microalgal technology from the AI application to the modelling and optimization using predictive control systems has been discussed. The LCA and techno-economic assessment (TEA) in the environmental sustainability and economic point of view are also presented. Future challenges and perspectives in the microalgae-based wastewater treatment to bioenergy production integrated with the EI approach, are also discussed in relation to the development of microalgae as the future energy source.
    MeSH terms: Artificial Intelligence; Biotechnology/methods; Informatics; Biofuels*; Waste Water*
  5. Yan X, Jia X, Feng L, Ge W, Kong B, Xia M, et al.
    Nurse Educ Pract, 2024 Aug 02;79:104087.
    PMID: 39142120 DOI: 10.1016/j.nepr.2024.104087
    OBJECTIVES: To address the nursing crisis, it is imperative to comprehend the factors that influence nursing competencies, which are crucial for the delivery of quality patient care.

    BACKGROUND: Facing demographic shifts and increasingly complex healthcare demands, China's nursing sector struggles with workforce shortages and the need to enhance core competencies. This research explores the interplay of social support, psychological resilience, mindfulness and nursing competencies in various hospital environments in China.

    METHODS: Through a cross-sectional survey, 941 nurses across tertiary, secondary and private healthcare settings completed self-assessment questionnaires. The analysis included multiple linear regression and comparative methods to assess how psychological resilience, mindfulness and social support have an impact on nursing competencies.

    RESULTS: Findings revealed a strong relationship between psychological resilience and nursing competencies, with resilience being a key predictor. Mindfulness and social support also significantly contributed to competency levels. Nurses in tertiary hospitals showed greater competencies than those in secondary or private facilities.

    CONCLUSION: Enhancing nursing competencies requires targeted interventions focusing on professional development and supportive workplace cultures. Incorporating psychological resilience, social support and mindfulness into nurse training is crucial for improving practice and policy.

  6. Yao D, Shen C, Zhang X, Tang J, Yu J, Tu M, et al.
    Food Chem, 2024 Dec 01;460(Pt 3):140663.
    PMID: 39142199 DOI: 10.1016/j.foodchem.2024.140663
    Gestational diabetes mellitus (GDM) is a prevalent metabolic disorder during pregnancy that alters the metabolites in human milk. Integrated Gas Chromatography-Mass Spectrometry (GC-MS) and Liquid Chromatography-Mass Spectrometry (LC-MS) were employed for comprehensive identification and comparison of metabolites in mature human milk (MHM) from women with and without GDM. A total of 268 differentially expressed metabolites (DEMs) were identified. Among these, linoleic acid, arachidonic acid, 9R-HODE and L-glutamic acid were significantly elevated and 12,13-DHOME was significantly decreased in MHM of women with GDM. These metabolites are significantly enriched in linoleic acid metabolism, fatty acid biosynthesis, galactose metabolism and ABC transporters pathways. Disorders in these metabolic pathways are associated with insulin resistance and poor glucose metabolism indicating these conditions may persist postpartum.
    MeSH terms: Adult; Chromatography, Liquid; Female; Humans; Gas Chromatography-Mass Spectrometry; Pregnancy; Metabolomics*
  7. Yu Y, Xu Y, Chen J, Yao Y, Liu Y, Chen Y, et al.
    Biomed Pharmacother, 2024 Sep;178:117254.
    PMID: 39142250 DOI: 10.1016/j.biopha.2024.117254
    BACKGROUND: Acute myocardial infarction (AMI) is a leading cause of mortality worldwide, with reduced elastin/collagen ratios exacerbating cardiac dysfunction due to collagen-rich scar tissue replacing necrotic myocardial cells. This study aims to evaluate pirfenidone's therapeutic effect on early cardiac function post-AMI and elucidate its impact on the elastin/collagen ratio.

    METHODS: Sprague-Dawley rats were divided into four groups: Sham, AMI, AMI treated with PBS (AMI-PBS), and AMI treated with pirfenidone (AMI-PFD) (n=12 each). AMI was induced via coronary artery ligation. The AMI-PFD and AMI-PBS groups received pirfenidone and PBS for 14 days, respectively. Cardiac function, fibrosis, serum cytokines, collagen and elastin content, and their ratios were assessed. Cardiac fibroblasts (CFs) from neonatal rats were categorized into control, hypoxia-induced (LO), LO+PBS, and LO+PFD groups. ELISA measured inflammatory factors, and RT-PCR analyzed collagen and elastin gene expression.

    RESULTS: The AMI-PFD group showed improved cardiac function and reduced serum interleukin-1β (IL-1β), IL-6, and transforming growth factor-β (TGF-β). Type I and III collagen decreased by 22.6 % (P=0.0441) and 34.4 % (P=0.0427), respectively, while elastin content increased by 79.4 % (P=0.0126). E/COLI and E/COLIII ratios rose by 81.1 % (P=0.0026) and 88.1 % (P=0.0006). CFs in the LO+PFD group exhibited decreased IL-1β, IL-6, TGF-β, type I and III collagen, with increased elastin mRNA, enhancing the elastin/collagen ratio.

    CONCLUSION: Pirfenidone enhances cardiac function by augmenting the early elastin/collagen ratio post-AMI.

    MeSH terms: Animals; Fibroblasts/drug effects; Fibroblasts/metabolism; Fibrosis; Male; Myocardium/metabolism; Myocardium/pathology; Cytokines/blood; Cytokines/metabolism; Rats, Sprague-Dawley; Rats
  8. Feng Y, Chow LS, Gowdh NM, Ramli N, Tan LK, Abdullah S
    PMID: 39142299 DOI: 10.1088/2057-1976/ad6f17
    Neuromyelitis optica spectrum disorder (NMOSD), also known as Devic disease, is an autoimmune central nervous system disorder in humans that commonly causes inflammatory demyelination in the optic nerves and spinal cord. Inflammation in the optic nerves is termed optic neuritis (ON). ON is a common clinical presentation; however, it is not necessarily present in all NMOSD patients. ON in NMOSD can be relapsing and result in severe vision loss. To the best of our knowledge, no study utilises deep learning to classify ON changes on MRI among patients with NMOSD. Therefore, this study aims to deploy eight state-of-the-art CNN models (Inception-v3, Inception-ResNet-v2, ResNet-101, Xception, ShuffleNet, DenseNet-201, MobileNet-v2, and EfficientNet-B0) with transfer learning to classify NMOSD patients with and without chronic ON using optic nerve magnetic resonance imaging. This study also investigated the effects of data augmentation before and after dataset splitting on cropped and whole images. Both quantitative and qualitative assessments (with Grad-Cam) were used to evaluate the performances of the CNN models. The Inception-v3 was identified as the best CNN model for classifying ON among NMOSD patients, with accuracy of 99.5%, sensitivity of 98.9%, specificity of 93.0%, precision of 100%, NPV of 99.0%, and F1-score of 99.4%. This study also demonstrated that the application of augmentation after dataset splitting could avoid information leaking into the testing datasets, hence producing more realistic and reliable results.
  9. Khodaei A, Moradi F, Oresegun A, Zubair HT, Bradley DA, Ibrahim SA, et al.
    Biomed Phys Eng Express, 2024 Aug 28;10(5).
    PMID: 39142303 DOI: 10.1088/2057-1976/ad6f14
    Radiation therapy plays a pivotal role in modern cancer treatment, demanding precise and accurate dose delivery to tumor sites while minimizing harm to surrounding healthy tissues. Monte Carlo simulations have emerged as indispensable tools for achieving this precision, offering detailed insights into radiation transport and interaction at the subatomic level. As the use of scintillation and luminescence dosimetry becomes increasingly prevalent in radiation therapy, there arises a need for validated Monte Carlo tools tailored to optical photon transport applications. In this paper, an evaluation process of the TOPAS (TOol for PArticle Simulation) Monte Carlo tool for Cerenkov light generation, optical photon transport and radioluminescence based dosimetry is presented. Three distinct sources of validation data are utilized: one from a published set of experimental results and two others from simulations performed with the Geant4 code. The methodology employed for evaluation includes the selection of benchmark experiments, making use of opt3 and opt4 Geant4 physics models and simulation setup, with observed slight discrepancies within the calculation uncertainties. Additionally, the complexities and challenges associated with modeling optical photons generation through luminescence or Cerenkov radiation and their transport are discussed. The results of our evaluation suggests that TOPAS can be used to reliably predict Cerenkov generation, luminescence phenomenon and the behavior of optical photons in common dosimetry scenarios.
    MeSH terms: Algorithms; Computer Simulation*; Humans; Luminescent Measurements/methods; Monte Carlo Method*; Software; Photons*; Luminescence
  10. Wang X, Zhang L, Cheng L, Wang Y, Li M, Yu J, et al.
    Cancer Lett, 2024 Aug 12.
    PMID: 39142499 DOI: 10.1016/j.canlet.2024.217184
    Prostate cancer (PCa) is the second most prevalent cancer in men worldwide, presenting a significant global public health challenge that necessitates early detection and personalized treatment. Recently, non-invasive liquid biopsy methods have emerged as promising tools to provide insights into the genetic landscape of PCa and monitor disease progression, aiding decision-making at all stages. Research efforts have concentrated on identifying liquid biopsy biomarkers to improve PCa diagnosis, prognosis, and treatment prediction. This article reviews recent research advances over the last five years utilizing extracellular vesicles (EVs) as a natural biomarker library for PCa, and discusses the clinical translation of EV biomarkers, including ongoing trials and key implementation challenges. The findings underscore the transformative role of liquid biopsy, particularly EV-based biomarkers, in revolutionizing PCa diagnosis, prediction, and treatment.
  11. Ahmad Fuad MH, Samsudin EZ, Yasin SM, Ismail N, Mohamad M, Muzaini K, et al.
    BMJ Open, 2024 Aug 13;14(8):e079877.
    PMID: 39142678 DOI: 10.1136/bmjopen-2023-079877
    OBJECTIVES: Occupational skin diseases (OSDs) pose significant risks to the health and well-being of restaurant workers. However, there is presently limited evidence on the burden and determinants of OSDs among this occupational group. This research aims to estimate the prevalence and associated factors of suspected OSDs among restaurant workers in Peninsular Malaysia.

    DESIGN: A secondary data analysis of the 2023 Registry of Occupational Disease Screening (RODS) was performed. The RODS survey tool, which included the Nordic Occupational Skin Questionnaire, a symptoms checklist and items on work-relatedness, was used to screen for OSDs. Logistic regression analyses were performed to identify associated factors.

    SETTING AND PARTICIPANTS: Restaurant workers (n=300) registered in RODS from February 2023 to April 2023, aged 18 years and above and working in restaurants across Selangor, Melaka and Pahang for more than 1 year, were included in the study, whereas workers who had pre-existing skin diseases were excluded.

    RESULTS: The prevalence of suspected OSDs among study participants was 12.3%. Higher odds of suspected OSDs among study participants were observed among those exposed to wet work (adjusted OR (AOR) 22.74, 95% CI 9.63 to 53.68) and moderate to high job stress levels (AOR 4.33, 95% CI 1.80 to 10.43).

    CONCLUSIONS: These findings suggest that OSDs are a significant occupational health problem among restaurant workers. Interventions targeting job content and wet work may be vital in reducing OSDs among this group of workers.

    MeSH terms: Adult; Female; Humans; Malaysia/epidemiology; Male; Middle Aged; Occupational Diseases/diagnosis; Occupational Diseases/epidemiology; Surveys and Questionnaires; Registries*; Risk Factors; Skin Diseases/diagnosis; Skin Diseases/epidemiology; Prevalence; Logistic Models; Young Adult
  12. Pan SQ, Hum YC, Lai KW, Yap WS, Ong CW, Tee YK
    Magn Reson Med Sci, 2024 Aug 14.
    PMID: 39143021 DOI: 10.2463/mrms.tn.2024-0069
    The quantitative analysis of pulsed-chemical exchange saturation transfer (CEST) using a full model-based method is computationally challenging, as it involves dealing with varying RF values in pulsed saturation. A power equivalent continuous approximation of B1 power was usually applied to accelerate the analysis. In line with recent consensus recommendations from the CEST community for pulsed-CEST at 3T, particularly recommending a high RF saturation power (B1 = 2.0 µT) for the clinical application in brain tumors, this technical note investigated the feasibility of using average power (AP) as the continuous approximation. The simulated results revealed excellent performance of the AP continuous approximation in low saturation power scenarios, but discrepancies were observed in the z-spectra for the high saturation power cases. Cautions should be taken, or it may lead to inaccurate fitted parameters, and the difference can be more than 10% in the high saturation power cases.
  13. Ong SC, Tay LX, Yee TF, Teh EE, Ch'ng ASH, Razali RM, et al.
    Sci Rep, 2024 Aug 14;14(1):18855.
    PMID: 39143230 DOI: 10.1038/s41598-024-69745-1
    Alzheimer's disease (AD) is an important geriatric disease that creates challenges in health policy planning. There is no previous attempt to quantify the actual direct healthcare cost of AD among older adults in Malaysia. This retrospective observational study with bottom-up micro-costing approach aimed to evaluate the direct healthcare expenditure on AD along with its potential predictors from healthcare providers' perspective, conducted across six tertiary hospitals in Malaysia. AD patients aged 65 and above who received AD treatment between 1 January 2016 and 31 December 2021 were included. Direct healthcare cost (DHC) of AD was estimated by extracting one-year follow-up information from patient medical records. As a result, 333 AD patients were included in the study. The mean DHC of AD was estimated RM2641.30 (USD 572.45) per patient per year (PPPY) from the healthcare payer's perspective. Laboratory investigations accounted for 37.2% of total DHC, followed by clinic care (31.5%) and prescription medicine (24.9%). As disease severity increases, annual DHC increases from RM2459.04 (mild), RM 2642.27 (moderate), to RM3087.61 (severe) PPPY. Patients aged 81 and above recorded significantly higher annual DHC (p = 0.003). Such real-world estimates are important in assisting the process of formulating healthcare policies in geriatric care.
    MeSH terms: Aged; Aged, 80 and over; Health Expenditures*; Female; Humans; Malaysia; Male; Retrospective Studies; Health Care Costs
  14. Balqis-Ali NZ, Ahmad N, Minhat HS, Fattah Azman AZ
    BMC Geriatr, 2024 Aug 14;24(1):685.
    PMID: 39143517 DOI: 10.1186/s12877-024-05211-x
    BACKGROUND: Although significant and disabling consequences are presented due to geriatric population-related depression, an insufficient comprehension of various biological, psychological, and social factors affecting this issue has been observed. Notably, these factors can contribute to geriatric population-related depression with low social support. This study aimed to identify factors associated with depression among the community-dwelling geriatric population with low social support in Malaysia.

    METHODS: This study used secondary data from a population-based health survey in Malaysia, namely the National Health Morbidity Survey (NHMS) 2018: Elderly Health. The analysis included 926 community-dwelling geriatric population aged 60 and above with low social support. The primary data collection was from August to October 2018, using face-to-face interviews. This paper reported the analysis of depression as the dependent variable, while various biological, psychological and social factors, guided by established biopsychosocial models, were the independent variables. Multiple logistic regression was applied to identify the factors. Analysis was performed using the complex sampling module in the IBM SPSS version 29.

    RESULTS: The weighted prevalence of depression among the community-dwelling geriatric population aged 60 and above with low social support was 22.5% (95% CI: 17.3-28.7). This was significantly higher than depression among the general geriatric Malaysian population. The factors associated with depression were being single, as compared to those married (aOR 2.010, 95% CI: 1.063-3.803, p: 0.031), having dementia, as opposed to the absence of the disease (aOR 3.717, 95% CI: 1.544-8.888, p: 0.003), and having a visual disability, as compared to regular visions (aOR 3.462, 95% CI: 1.504-7.972, p: 0.004). The analysis also revealed that a one-unit increase in control in life and self-realisation scores were associated with a 32.6% (aOR: 0.674, 95% CI: 0.599-0.759, p 

    MeSH terms: Aged; Aged, 80 and over; Female; Health Surveys/methods; Humans; Malaysia/epidemiology; Male; Middle Aged; Risk Factors; Social Support*; Prevalence
  15. Lim CP, Leow CH, Lim HT, Kok BH, Chuah C, Oliveira JIN, et al.
    Clin Exp Vaccine Res, 2024 Jul;13(3):202-217.
    PMID: 39144127 DOI: 10.7774/cevr.2024.13.3.202
    Structural vaccinology is pivotal in expediting vaccine design through high-throughput screening of immunogenic antigens. Leveraging the structural and functional characteristics of antigens and immune cell receptors, this approach employs protein structural comparison to identify conserved patterns in key pathogenic components. Molecular modeling techniques, including homology modeling and molecular docking, analyze specific three-dimensional (3D) structures and protein interactions and offer valuable insights into the 3D interactions and binding affinity between vaccine candidates and target proteins. In this review, we delve into the utilization of various immunoinformatics and molecular modeling tools to streamline the development of broad-protective vaccines against coronavirus disease 2019 variants. Structural vaccinology significantly enhances our understanding of molecular interactions between hosts and pathogens. By accelerating the pace of developing effective and targeted vaccines, particularly against the rapidly mutating severe acute respiratory syndrome coronavirus 2 and other prevalent infectious diseases, this approach stands at the forefront of advancing immunization strategies. The combination of computational techniques and structural insights not only facilitates the identification of potential vaccine candidates but also contributes to the rational design of vaccines, fostering a more efficient and targeted approach to combatting infectious diseases.
  16. Abdul Manan H, Mir IA, Humayra S, Tee RY, Vasu DT
    Front Psychol, 2024;15:1435243.
    PMID: 39144586 DOI: 10.3389/fpsyg.2024.1435243
    BACKGROUND: Adopting lifestyle interventions is pivotal in coronary artery disease (CAD) management and prevention to amplify cardiovascular and mental well-being. This study aims to quantify the effect of mindfulness-based interventions (MBIs) on anxiety, depression and stress in CAD patients.

    METHODS: A systematic review and meta-analysis of randomized controlled trials (RCTs) was conducted by searching four electronic databases (PubMed, CENTRAL, Scopus, and Science Direct) through December 2023. The risk of bias was assessed using the PEDro tool, and the study outcomes were expressed as standard mean difference at 95% CI.

    RESULTS: Out of 1838 yielded results, eight RCTs involving 623 participants with a mean age of 56.96 ± 4.89 met the prespecified eligibility criteria. The pooled results showed a statistically significant and beneficial effect of MBIs on CAD patients' mental health status in regards to anxiety (SMD = -0.83; 95% CI [-1.19, -0.46], p 

  17. Chen K, Luo S, Kin Tong DY
    Heliyon, 2024 Aug 15;10(15):e34744.
    PMID: 39144960 DOI: 10.1016/j.heliyon.2024.e34744
    As the main form of digital trade, cross-border e-commerce plays an important role, allowing China to expand its opening-up and promote the optimal foreign trade structure. It also provides opportunities for Chinese enterprises to develop digital technology. From the perspective of the establishment of China's cross-border e-commerce comprehensive pilot zone (CBECPZ), this article uses the multi-period DID method to examine the effects of cross-border e-commerce on enterprise digital technology innovation based on listed companies in the Shanghai and Shenzhen stock markets from 2007 to 2020. The CBECPZ dramatically promotes enterprise digital technology innovation. The mechanism test shows that the CBECPZ promotes digital technology innovation by financing constraint alleviation, digital transformation, and producer service industry agglomeration. The heterogeneity test shows that the direct effect is more significant in the enterprises of large-scale, non-state-owned, with high ICT correlation and in areas with strong government resource allocation capabilities. The research findings have important reference value for how to utilize cross-border e-commerce to promote digital technology innovation, and they also provide directional references for other developing countries to develop cross-border e-commerce.
  18. Al-Shami SA, Damayanti R, Adil H, Farhi F, Al Mamun A
    Heliyon, 2024 Aug 15;10(15):e34902.
    PMID: 39144969 DOI: 10.1016/j.heliyon.2024.e34902
    Batik, an Indonesian textile art form, holds immense economic and cultural importance. Small and medium enterprises (SMEs) specialising in batik play a crucial role in Indonesia's economic growth and cultural preservation, contributing significantly to the gross domestic product (GDP) and preserving the nation's heritage. Nevertheless, these enterprises face several challenges, such as slow growth and limited access to credit. The batik industry also lags in financial literacy and the adoption of digital marketing strategies, hindering its development. This quantitative study aims to investigate the relationship between financial literacy, digital financial literacy, and financial inclusion in batik SMEs and also examined the moderating effect of online social networks. A survey was conducted involving 535 managers, owners, and financial officers of small batik enterprises. Subsequently, the SmartPLS statistical analysis method was employed for data analysis. The results demonstrate that financial literacy and digital financial literacy play a significant role in accessing financial inclusion for batik small enterprises. Moreover, the utilisation of social media was found to moderate these relationships, amplifying the impact of financial and digital literacy on financial inclusion. The findings contribute to the existing knowledge, provide insights for enhancing batik small enterprises, and propose a digital financial model to promote financial inclusion.
  19. Lu J, Gulzar F, Lai Y
    Heliyon, 2024 Aug 15;10(15):e34467.
    PMID: 39145029 DOI: 10.1016/j.heliyon.2024.e34467
    In the context of China's transportation sector, which has faced escalating challenges in carbon emissions, this study delves into the intricate nexus between sustainable finance strategies and the imperative of achieving carbon neutrality. Spanning the years 2010-2022 across 30 provinces of China and employing a rigorous Panel Model methodology, our research sets out to achieve several pivotal objectives. These include assessing the tangible impact of sustainable finance initiatives on curtailing carbon emissions within the transportation domain, discerning the pivotal drivers that influence the trajectory of carbon neutrality endeavors, and critically evaluating the efficacy of policy interventions aimed at fostering sustainability. Our findings unearth a compelling narrative. Firstly, we observe a discernible positive correlation between the implementation of sustainable finance mechanisms-such as green bonds, sustainable investment portfolios, and innovative financial instruments-and the tangible reduction of carbon emissions within the transportation sector. Secondly, our analysis underscores the indispensable role of key drivers, ranging from technological advancements and regulatory frameworks to evolving consumer behavior and public consciousness, in steering the course towards carbon neutrality. Thirdly, our research underscores the pivotal impact of targeted policy interventions, emphasizing the efficacy of measures aimed at incentivizing sustainable practices, fostering stakeholder collaborations, and bolstering industry-wide accountability frameworks. In light of these insights, our study advocates for a nuanced policy landscape characterized by a multifaceted approach. By aligning financial incentives with sustainability goals, fostering technological innovation, and fostering robust regulatory frameworks, policymakers can catalyze a paradigm shift towards carbon neutrality in the transportation sector.
  20. Dahri NA, Yahaya N, Al-Rahmi WM, Noman HA, Alblehai F, Kamin YB, et al.
    Heliyon, 2024 Aug 15;10(15):e34900.
    PMID: 39145035 DOI: 10.1016/j.heliyon.2024.e34900
    Blended learning (BL), a teaching method merging online and face-to-face learning, is lauded for its potential to enrich educational outcomes and tackle challenges entrenched in conventional teaching practices. In countries like Pakistan, where equitable access to quality professional development remains an obstacle, BL is a promising avenue to surmount training barriers. While BL adoption has evolved swiftly, research into its integration within teacher training remains limited. Notably, no comprehensive model exists describing the motivational factors influencing teachers' perceptions and intentions regarding the blended mode of teacher training. This study aims to identify the motivational elements that motivate schoolteachers in teacher training institutions in Pakistan to incorporate blended learning into their programs. The motivational factors identified in BL literature have been employed to craft a motivation model grounded in their causal relationship. This quantitative study examines the interplay between multiple motivational factors and their impact on BL adoption within teacher training and the BL environment. Surveying 350 schoolteachers (participants) from teacher training institutions, we employed Structural Equation Modeling (SEM) techniques with Smart PLS 4.0 for data analysis. Results reveal that extrinsic and intrinsic motivational factors significantly influence teachers' motivation to adopt BL for training. Notably, "overall training quality" and "educational environment" were non-influential. Overall, the findings underscore that considering a blend of extrinsic and intrinsic factors can wield a 65 % influence on BL adoption. The study's results provide practical guidance for educational leaders, curriculum designers, and faculty members aiming to cultivate a unified blended learning environment for teacher professional development. These insights also underscore the importance of incorporating essential motivational factors into forthcoming blended learning training programs.
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