Download full-text PDF |
Source |
|---|
Publication Analysis
Top Keywords
Similar Publications
Revolutionizing faculty's intrinsic work motivation in China: A novel serial mediation model integrating value-based leadership, growth mindset, and teaching self-efficacy.
PLoS One
January 2025
School of Foreign Languages for International Business, Hebei Finance University, Baoding, Hebei, China.
This study presents a revolutionary understanding of how value-based leadership enhances the intrinsic work motivation of Chinese university faculty. A novel serial mediation model is introduced, highlighting the interplay between growth mindset and teaching self-efficacy in transmitting the impact of leadership to increased intrinsic motivation. Utilizing a comprehensive sample of 394 faculty members from across China, advanced SmartPLS 3.
View Article and Find Full Text PDFThe Association Between COVID-19 Vaccination Uptake and Information-Seeking Behaviors Using the Internet: Nationwide Cross-Sectional Study.
J Med Internet Res
January 2025
Department of Healthcare Economics and Quality Management, School of Public Health, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Background: The COVID-19 pandemic, declared in March 2020, profoundly affected global health, societal, and economic frameworks. Vaccination became a crucial tactic in combating the virus. Simultaneously, the pandemic likely underscored the internet's role as a vital resource for seeking health information.
View Article and Find Full Text PDFEliciting Preferences for the Uptake of Smoking Cessation Apps: Discrete Choice Experiment.
J Med Internet Res
January 2025
Behavioural and Implementation Science Group, School of Health Sciences, University of East Anglia, Norwich, United Kingdom.
Background: If the most evidence-based and effective smoking cessation apps are not selected by smokers wanting to quit, their potential to support cessation is limited.
Objective: This study sought to determine the attributes that influence smoking cessation app uptake and understand their relative importance to support future efforts to present evidence-based apps more effectively to maximize uptake.
Methods: Adult smokers from the United Kingdom were invited to participate in a discrete choice experiment.
Differentially Expressed Nedd4-binding Protein Ndfip1 Protects Neurons Against Methamphetamine-induced Neurotoxicity.
Neurotox Res
January 2025
Molecular Neuropsychiatry Section, Intramural Research Program, NIH/ NIDA, 21224, Baltimore, MD, U.S.A.
To identify factors involved in methamphetamine (METH) neurotoxicity, we comprehensively searched for genes which were differentially expressed in mouse striatum after METH administration using differential display (DD) reverse transcription-PCR method and sequent single-strand conformation polymorphism analysis, and found two DD cDNA fragments later identified as mRNA of Nedd4 (neural precursor cell expressed developmentally downregulated 4) WW domain-binding protein 5 (N4WBP5), later named Nedd4 family-interacting protein 1 (Ndfip1). It is an adaptor protein for the binding between Nedd4 of ubiquitin ligase (E3) and target substrate protein for ubiquitination. Northern blot analysis confirmed drastic increases in Ndfip1 mRNA in the striatum after METH injections, and in situ hybridization histochemistry showed that the mRNA expression was increased in the hippocampus and cerebellum at 2 h-2 days, in the cerebral cortex and striatum at 18 h-2 days after single METH administration.
View Article and Find Full Text PDFPredictive Optimization of Patient No-Show Management in Primary Healthcare Using Machine Learning.
J Med Syst
January 2025
Department of Computing, University of North Florida, 1 UNF Dr., Jacksonville, 32246, FL, USA.
The "no-show" problem in healthcare refers to the prevalent phenomenon where patients schedule appointments with healthcare providers but fail to attend them without prior cancellation or rescheduling. In addressing this issue, our study delves into a multivariate analysis over a five-year period involving 21,969 patients. Our study introduces a predictive model framework that offers a holistic approach to managing the no-show problem in healthcare, incorporating elements into the objective function that address not only the accurate prediction of no-shows but also the management of service capacity, overbooking, and idle resource allocation resulting from mispredictions.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!