After introducing what is understood by teaching innovation and its requirements, various methodologies that can be applied in university and radiological teaching are presented, such as: the flipped classroom focuses on the student\'s previous study and the teacher\'s subsequent contribution to resolve doubts or highlight important aspects. Team learning or cooperative teaching allows learning among the students themselves. Problem-based or case-based learning encourages students, in teams or individually, to carry out structured learning based on learning objectives. Teaching based on games or simulation can facilitate knowledge acquisition playfully and practically. Personalized tutoring allows the transmission of knowledge in an individualized way. Various evaluation modalities that can be used for training purposes are also shown.

Endotracheal tube dislodgement is a common patient safety incident in clinical settings. Current clinical practices, primarily relying on bedside visual inspections and equipment checks, often fail to detect endotracheal tube displacement or dislodgement promptly. This study involved the development of a deep learning, artificial intelligence (AI)-based system for monitoring tube displacement. We also propose a randomized crossover experiment to evaluate the effectiveness of this AI-based monitoring system compared to conventional methods. The assessment will focus on immediacy in detecting and handling of tube anomalies, the completeness and accuracy of shift transitions, and the degree of innovation diffusion. The findings from this research are expected to offer valuable insights into the development and integration of AI in enhancing care provision and facilitating innovation diffusion in medical and nursing research.

BACKGROUND: The purpose of this study is to examine the use of electronic cigarettes (e-cigarettes) among college students in Hangzhou, and to analyze the influencing factors of their intention to use e-cigarettes.
METHODS: Using a stratified cluster sampling method, 775 students from two universities in Hangzhou were selected for an on-site questionnaire survey from March to April 2022. Adjusted logistic regression analysis was conducted on the influencing factors of use intention, based on innovation diffusion theory.
RESULTS: Within our sample of college students, 16.5% of students had tried e-cigarettes; 6.32% had used e-cigarettes in the past month, and 8.0% had the intention to use e-cigarettes. There were significant differences in willingness to use e-cigarettes among different genders, economic status, smoking status of close friends around them, and their own use of tobacco and alcohol (p<0.05). The logistic regression model showed that the observability of e-cigarettes (AOR=1.28; p<0.05), personal factors (AOR=1.39; p<0.05), and social systems (AOR=1.63; p<0.05), were all influencing factors of intention to use e-cigarettes.
CONCLUSIONS: College students in Hangzhou have a high intention to use e-cigarettes, and the impacts of the product itself, individual characteristics and the living environment are crucial. It is necessary to strengthen the promotion of tobacco knowledge at the social and family levels to reduce the occurrence of vaping.

In this work, we suggest a quantum-like simulator concept to study social processes related to the solution of NP-hard problems. The simulator is based on the solaser model recently proposed by us in the framework of information cascade growth and echo chamber formation in social network communities. The simulator is connected with the random laser approach that we examine in the A and D-class (superradiant) laser limits. Novel network-enforced cooperativity parameters of decision-making agents, which may be measured as a result of the solaser simulation, are introduced and justified for social systems. The innovation diffusion in complex networks is discussed as one of the possible impacts of our proposal.

The Covid-19 pandemic has dramatically changed how information is shared and processed worldwide. The COVID-19 pandemic has profoundly affected the globalization of information, causing shifts in communication, information dissemination, and technology. This paper investigates the impact of pandemics-related uncertainty on the index of de facto informational globalization (the measure based on high-technology exports, international patents, and used internet bandwidth). The paper uses the panel dataset of 18 Central and Eastern European (CEE) countries from 1990 to 2020. The results indicate that pandemics-related uncertainty negatively affects the informational globalization level in the CEE economies. The findings are robust in utilizing different estimation techniques and considering NATO member CEE countries.

In order to accelerate the development of smart agriculture and realize the green transformation of agriculture, the coupling of prospect theory and evolutionary game theory is introduced. Construct a two-party evolutionary game model for the adoption of intelligent spray technology in farmers\' cooperatives, analyze the evolution of farmers\' cooperatives and government strategy selection and its influencing factors according to the replication dynamic equation, and conduct numerical simulation experiments through Matlab software. The results show that the adoption of intelligent spray technology by farmers\' cooperatives and the government\'s choice of subsidies are the two optimal stable states of the evolutionary system. The government\'s subsidy policy can effectively stimulate farmers\' cooperatives to adopt intelligent spray technology, but when the government subsidy coefficient is greater than or equal to 70%, the decision-making evolution of the government and farmers\' cooperatives is unstable. The increase in farmers\' awareness of pesticide hazards, the scale of operation of farmers\' cooperatives, the price of high-quality agricultural products, and the sensitivity of farmers\' cooperatives to profits and losses contribute to the promotion of intelligent spray technology, and the damage probability of intelligent spray technology has a restraining effect.

BACKGROUND: Prior to the coronavirus disease 2019 (COVID-19) pandemic, studies of innovative telehealth perinatal care models showed similar clinical outcomes and perceived quality of care between groups receiving a combination of virtual video and in-person visits. However, these studies included primarily White, English-speaking participants, excluding those who were economically disenfranchised or did not speak English. The purpose of this qualitative study was to describe perinatal patients\' and providers\' experiences with telehealth during and after the acute phase of the COVID-19 pandemic to inform future utilization of telehealth to drive the delivery of high-quality, accessible, and equitable perinatal care to diverse communities.
METHODS: This descriptive qualitative study included a purposive sample of 14 patients and 17 providers who received or provided perinatal care via telehealth in either a certified nurse-midwifery practice or the nurse-family partnership care model between March 2020 and April 2022. Maximum variation sampling offered a diverse population based on race, ethnicity, and rurality. Researchers conducted 2 rounds of semistructured interviews with a focus on understanding social and geographic context.
RESULTS: Six themes were identified through inductive analysis: (1) unexpected advantages of telehealth, (2) patient empowerment, (3) providers\' fear of adverse outcomes, (4) concern for equitable care, (5) strategies to enhance the telehealth experience, and (6) strategies to address access to perinatal telehealth. Patients appreciated the increased ease and reduced cost of accessing visits, which led to fewer missed appointments. Health care providers saw great opportunity in telehealth but expressed concerns about accessibility for patients with language barriers or limited resources.
CONCLUSIONS: This study provides insight into priorities for continued telehealth utilization focused on providing equitable access to perinatal care. Rather than returning to practices from before the COVID-19 pandemic formed from longstanding routines and perceived limitations, providers are encouraged to capitalize on the rapid innovations in telehealth to build a more effective, equitable, and patient-centered approach to perinatal care.

Nurses frequently innovate in response to operational failures, regulations, procedures, and/or other workflow barriers that prevent them from delivering high-quality patient care. Unfortunately, most nurse innovations do not diffuse to a broader audience, depriving other nurses from taking advantage of solutions that have already been developed elsewhere. This under-diffusion is problematic from a societal and welfare point of view. The goal of this paper is to understand how diffusion shortage of nurse innovations can be reduced.
We develop a qualitative case study of a medical makerspace at the largest academic hospital in the Netherlands. This medical makerspace reported unusually high rates of nurse innovation diffusion. Our data collection includes on-site observations, archival data, secondary data, and fifteen in-depth interviews with key informants. Qualitative coding procedures and a combination of deductive and inductive reasoning are used to analyze the data.
Our data show that personal, organizational, regulatory, and market barriers prevent nurses from further developing and diffusion their innovations in an anticipatory manner. That is, because nurses expect that transforming an initial solution into an innovation that can be shared with others will be too time consuming and difficult they do not proceed with the further development. The medical makerspace that we investigated adequately addresses this problem by developing an innovation ecosystem that largely takes over the innovation and diffusion process.
We provide a concrete example of how a medical makerspace, and innovation support systems in a broader sense, can be designed to more adequately address the nurse innovation-diffusion gap. The two main elements of the practical solution that we identified are: (1) Support systems should facilitate that others may lead the development and diffusion of innovations and (2) The support system should promote that actors integrate their functional specializations within an innovation ecosystem. We make two theoretical contributions. First, we contribute to understanding barriers in the nurse innovation-diffusion process from a psychological point. Second, we identified that an ecosystem perspective is beneficial to develop innovation support systems in which diffusion occurs more often.

Efforts to reduce global greenhouse gas emissions have had limited success. For many, the hopes rest on new energy innovations to advance the energy transition process. In this paper, we develop a Responsible Research and Innovation (RRI) base indicator system to steer the design of innovations in the field of energy transition innovations and, thus, improve social acceptance of these innovations. We propose a guideline for its application to assist R&D performing organizations and funding organizations in the design, selection, and communication of research proposals. The indicator system is intended to promote early integration of environmental and social aspects, support the formation of teams aware of the different responsibility aspects of innovation, and monitor progress in regard to relevant RRI dimensions.

This study investigates the impact of renewable and non-renewable energy sources on carbon emissions in the context of China\'s 14th Five-Year Plan (2021-2025). The plan emphasises a \"Dual-control\" strategy of simultaneously setting energy consumption limits and reducing energy intensity for GDP (gross domestic product) in order to meet the targets of the five-year plan. Using a comprehensive dataset of Chinese energy and macroeconomic information spanning from 1990 to 2022, we conduct a Granger causality analysis to explore the relationship between energy sources and the level of air pollution. Our findings reveal a unidirectional link, wherein renewable energy contributes to a reduction in air pollution, while non-renewable energy sources lead to an increase. Despite the government\'s investment in renewable energy, our results show that China\'s economy remains heavily reliant on traditional energy sources (e.g., fossil fuels). This research is the first systematic examination of the interplay between energy usage and carbon emissions in the Chinese context. Our findings provide valuable insights for policy and market strategies aimed at promoting carbon neutrality and driving technological advancements in both government and industries.