Introduction: Adherence to ambulance and ED protocols is often suboptimal. Insight into factors influencing adherence is a requisite for improvement of adherence. This study aims to gain an in-depth understanding of factors that influence ambulance and emergency nurses' adherence to protocols.
Methods: Semi-structured interviews were held with ambulance nurses, emergency nurses, and physicians (N = 20) with medical end responsibility in the Netherlands to explore influencing factors. Content analysis was used to identify influencing factors.
Results: The main influencing factors for adherence were individual factors, including individual (clinical) experience, awareness, and the preference of following local protocols instead of national protocols. Organizational or external factors were involvement in protocol development, training and education, control mechanisms for adherence, and physicians' interest. Also of influence were protocol characteristics including integration of the advanced trauma life support approach, being in accordance with daily practice, and the generality of the content. Influencing factors could be a barrier as well as a facilitator for adherence.
Discussion: Factors influencing ambulance and emergency nurses' protocol adherence could be assigned to individual, organizational, and external categories, as well as to protocol characteristics. To improve adherence, implementation strategies should be tailored to identified factors. Multifaceted implementation strategies will be needed to improve adherence.
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http://dx.doi.org/10.1016/j.jen.2012.09.008 | DOI Listing |
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.
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 PDFJ 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 PDFJ Med Syst
January 2025
Department of Anesthesiology and Pain Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea.
Optimizing operating room (OR) utilization is critical for enhancing hospital management and operational efficiency. Accurate surgical case duration predictions are essential for achieving this optimization. Our study aimed to refine the accuracy of these predictions beyond traditional estimation methods by developing Random Forest models tailored to specific surgical departments.
View Article and Find Full Text PDFEnviron Monit Assess
January 2025
School of Energy and Power Engineering, Xihua University, No. 9999 Hongguang Street, Chengdu, 610039, Sichuan Province, China.
Analysis of crop water requirement and its influencing factors are important for optimal allocation of water resources. However, research on variations of climatic factors and their contribution to wheat water requirement in Xinjiang is insufficient. In our study, daily meteorological data during 1961‒2017 in Xinjiang was collected.
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