The most powerful and crucial concept today is a sustainable digital economy. This research is aimed to investigate the predictors of a sustainable digital economy in China. In addition, the mediating roles of social reforms and economic policies were investigated between good governance and a sustainable digital economy. This cross-sectional research considered partial least square-structural equational modeling (PLS-SEM) as an analysis technique. The data were collected from 317 managerial staff of the e-commerce industry in China via a self-structured questionnaire. A random sampling technique was applied in the data collection process. Results showed that good governance positively impacts the sustainable digital economy, social reforms, and economic policies. Additionally, an increase in social reforms and economic policies led to a sustainable digital economy in China. Social reforms and economic policies partially mediated the relationship between good governance and a sustainable digital economy. This research contributes to the body of knowledge by identifying components of a sustainable digital economy and examining whether good governance may aid in attaining a sustainable digital economy. Nowadays, research on the sustainable digital economy has got attention from policymakers and researchers around the globe. These outcomes suggest several ways to improve the sustainable digital economy in China. This research is not without limitations, such as cross-sectional and based on responses of the respondents. Several research avenues were discussed and can be influenced by many factors for future perspectives.
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http://dx.doi.org/10.3389/fpsyg.2021.773022 | DOI Listing |
Int J Syst Evol Microbiol
January 2025
Department of Life Sciences, University of Coimbra, CEMMPRE, ARISE, Coimbra, Portugal.
Three bacterial strains, designated FZUC8N2.13, FBOR7N2.3 and FZUR7N2.
View Article and Find Full Text PDFRadiology
January 2025
From the Department of Radiology, University of Washington, UW Medical Center-Montlake, Seattle, Wash (D.M.); Department of Radiology, OncoRad/Tumor Imaging Metrics Core (TIMC), University of Washington, Seattle, Wash (D.M.); Department of Radiology and Imaging Sciences, Emory University, Atlanta, Ga (M.v.A.); Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands (M.H.); Department of Radiology, Mayo Clinic, Rochester, Minn (T.L., E.E.W.); Departments of Cardiology and Radiology, Royal Brompton Hospital, London, United Kingdom (E.D.N.); School of Biomedical Engineering and Imaging Sciences, King's College, London, United Kingdom (E.D.N.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (B.D.A.); Department of Radiology, University of Cagliari, Cagliari, Italy (L.S.); Department of Radiology, University of Groningen, University Medical Center Groningen, Hanzeplein 1 Postbus 30 001, 9700 RB Groningen, the Netherlands (R.V.); Department of Medical Imaging, University Medical Imaging Toronto, University of Toronto, Toronto, Ontario, Canada (K.H.); and Toronto General Hospital Research Institute, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.H.).
Artificial intelligence (AI) offers promising solutions for many steps of the cardiac imaging workflow, from patient and test selection through image acquisition, reconstruction, and interpretation, extending to prognostication and reporting. Despite the development of many cardiac imaging AI algorithms, AI tools are at various stages of development and face challenges for clinical implementation. This scientific statement, endorsed by several societies in the field, provides an overview of the current landscape and challenges of AI applications in cardiac CT and MRI.
View Article and Find Full Text PDFCJC Open
January 2025
Genetics and Genome Biology, Research Institute, Peter Gilgan Centre for Research and Learning, The Hospital for Sick Children, Toronto, Ontario, Canada.
Sudden cardiac death is a leading cause of mortality in children with hypertrophic cardiomyopathy (HCM). The PRecIsion Medicine in CardiomYopathy consortium developed a validated tool (PRIMaCY) for sudden cardiac death risk prediction to help with implantable cardioverter defibrillator shared decision-making, as recommended by clinical practice guidelines. The mplemeting a udden Cardiac Dath isk Assessment ool in hildhood (INSERT-HCM) study aims to implement PRIMaCY into electronic health records (EHRs) and assess implementation determinants and outcomes.
View Article and Find Full Text PDFWorld J Hepatol
January 2025
Medical Affairs, Tatvacare, Ahmedabad 380058, Gujarāt, India.
Background: Non-alcoholic fatty liver disease (NAFLD) management requires sustainable lifestyle modifications. This study aimed to evaluate the effectiveness of the RESET care plan, a comprehensive program that is an integrated personalized diet, exercise, and cognitive behavior therapy, delivered MyTatva's digital health application enabled through a body composition analyzer (BCA) and smartwatch.
Aim: To evaluates the effectiveness of the comprehensive program delivered MyTatva's digital health app enabled through internet of thing devices.
J Oral Rehabil
January 2025
Department of Odontology, Faculty of Medicine, Umeå University, Umeå, Sweden.
Background: Psychosocial screening is a valuable part of the assessment of patients with orofacial pain, as psychosocial factors will affect prognosis and treatment outcomes. Paper-based questionnaires are predominately used to assess the degree of psychosocial comorbidity; however, digital alternatives for screening questionnaires may be more cost-effective and resource-saving if patients are receptive to using them.
Objective: To evaluate how patients perceive digital psychosocial screening in dentistry.
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