Impact Of Different Models Research Articles

EEG-based emotional valence and emotion regulation classification: a data-centric and explainable approach

Emotion classification using electroencephalographic (EEG) data is a challenging task in the field of Artificial Intelligence. While many researchers have focused on finding the best model or feature extraction technique to achieve optimal results, few have attempted to select the best methodological steps for working with the dataset. In this study, we applied two different theoretical approaches based on the noise of the dataset: curriculum learning and confident learning. Curriculum learning involves presenting training examples to the model in a specific order, starting with easier examples and gradually increasing in difficulty. This approach has been shown to improve model performance. Confident learning is a method for identifying and correcting label errors in datasets. By identifying and correcting these errors, confident learning can improve the performance of machine learning models trained on noisy datasets. We then applied the Integrated Gradient technique in order to assess the explainability of each model. Our aim was to explore the impact of different models and methods on emotion classification performance using EEG data. We collected and used an EEG dataset in which participants rated the emotional valence of positive and negative pictures while performing an emotion regulation (ER) task, comparing a control condition (Look) with two ER strategies: cognitive reappraisal and expressive suppression. We performed a multilabel classification to identify emotional neutrality or polarization of emotional valence (both positive and negative) rated by participants and the emotion regulation strategy adopted during the task. We compared the performance of models trained on three datasets selected based on label noise and evaluated their suitability for this task. Our results suggest different patterns based on the architecture used for feature importance, highlighting both advantages and criticisms.

CONTINUITY OF CARER: WHAT DOES IT MEAN AND DOES IT MATTER TO MIDWIVES AND BIRTHING WOMEN?

This paper discusses key themes from a large-scale, long-term multi-perspective evaluation of caseload midwifery practice in the United Kingdom (UK). Caseload practice was introduced in several UK settings, on a pilot scale, following the publication of Changing Childbirth intended to put into practice its core principles of continuity, choice and control for women.1 A range of new midwifery practices were piloted and evaluated across the UK. Relatively little attention was given to defining and exploring the nature and meanings of the new models of practice, or to midwives in this new practice context. This has led to difficulty in comparing the impact of different models of practice. We draw on two aspects of our work – an ethnographic study of the experiences of midwives (with and without caseloads) and a study of the women's experiences and responses to care – to explore in greater depth the concepts involved in the caseload model and their meaning for women and for midwives in practice. Interviews were conducted with 40 women and 36 caseload midwives. Other forms of data collection, including questionnaires and observation were used and were analysed thematically using grounded theory principles. Themes emerging included autonomy, confidence, reciprocity and relationship: the idea of knowing and being known. On this basis we have argued that continuity is not an end in itself but an important means towards the end of women-centred care and should be considered in relation to other key themes such as autonomy and environment.

Impact of different models based on blood samples and images for bone marrow dosimetry after 177Lu-labeled somatostatin-receptor therapy

BackgroundPeptide receptor radionuclide therapy with 177Lu-DOTATATE is a recognized option for treating neuroendocrine tumors and has few toxicities, except for the kidneys and bone marrow. The bone marrow dose is generally derived from a SPECT/CT image-based method with four timepoints or from a blood-based method with up to 9 timepoints, but there is still no reference method. This retrospective single-center study on the same cohort of patients compared the calculated bone marrow dose administered with both methods using mono, bi- or tri-exponential models. For the image-based method, the dose was estimated using Planetdose© software. Pearson correlation coefficients were calculated. We also studied the impact of late timepoints for both methods.ResultsThe bone marrow dose was calculated for 131 treatments with the blood-based method and for 17 with the image-based method. In the former, the median absorbed dose was 15.3, 20.5 and 28.3 mGy/GBq with the mono-, bi- and tri-exponential model, respectively. With the image-based method, the median absorbed dose was 63.9, 41.9 and 60.8 with the mono-, bi- and tri-exponential model, respectively. Blood samples after 24h post-injection did not evidence any change in the absorbed bone marrow dose with the bi-exponential model. On the contrary, the 6-day post-injection timepoint was more informative with the image-based model.ConclusionThis study confirms that the estimated bone marrow dose is significantly lower with the blood-based method than with the image-based method. The blood-based method with a bi-exponential model proved particularly useful, without the need for blood samples after 24h post-injection. Nevertheless, this blood-based method is based on an assumption that needs to be more validated. The important difference between the two methods does not allow to determine the optimal one to estimate the true absorbed dose and further studies are necessary to compare with biological effects.

Predicting video popularity based on video covers and titles using a multimodal large-scale model and pipeline parallelism

In the era of traffic, controlling traffic is equivalent to mastering influence and economic benefits. At the video level, under the premise of the same video content, it is very important to study what kind of cover and title can be more attractive to people. Unlike most previous studies that focused on YouTube videos, our data came from Bilibilis videos. This paper tried to use two neural network models, ViT and Bert, combined with GPipe and backend fusion multimodal data fusion methods, to predict the possible click-through rate and popularity of a specific video based on its existing video cover and title. In the process, we switched to different visual and language models to complete the same training task, with the goal of comparing the impact of different models on the results. By adjusting the weight of two models, we finally achieved a good result of up to 62% accuracy.

The impact of the form of public governance on the economy

There is a direct connection between the model of the system of governance in a specific country and its impact on rights, freedoms, growth rates, and the standard of living of its population. In turn, the choice of a governance model depends on the action of various factors, such as the cultural level and development of society, the availability of natural reserves, the quality of the education and science system, and the level of development of the system of country’s governance. From a theoretical point of view, the parliamentary model of governance is considered the most favorable in terms of upholding citizens' rights and freedoms and promoting the well-being of the population. The presidential model ranks second, while the super-presidential model performs modestly. The testing of theoretical assumptions regarding the impact of different models of republican governance on a country's development was conducted using a sample of 147 countries. The sample encompassed the years 1995 to 2021 and was derived from the World Bank database. However, it is important to note that countries with forms of governance such as absolute monarchy or junta considered to be backward were excluded from the sample. The empirical testing conducted supports the hypothesis that countries with a parliamentary form of governance have higher expected growth and well-being for their population in the long run. However, the countries using super-presidential, presidential models of governance, and countries with limited constitutional monarchies, exhibit lower expected long-term growth rates of per capita income.

Initial-state and final-state effects on hadron production in small collision systems

Heavy meson production in reactions with nuclei is an active new frontier to understand QCD dynamics and the process of hadronization in nuclear matter. Measurements in various colliding systems at RHIC and LHC, including Pb-Pb, Xe-Xe, O-O, p-Pb, and p-O, enable precision tests of the medium-size, temperature, and mass dependencies of the in-medium parton propagation and shower formation. We employ a coupled DGLAP evolution framework that takes advantage of splitting functions recently obtained in softcollinear effective theory with Glauber gluons (SCETG) and hard thermal loop (HTL) motivated collisional energy loss effects. With jet quenching effects constrained to the nuclear modification factor of charged hadrons in Pb-Pb collisions at 5.02 TeV, we present predictions for light and heavy-meson in Xe-Xe, O-O and p-Pb collisions at the LHC.We find that the nuclear modification scales non-trivially with the quark mass and medium properties. In particular, there can be sizeable collision-induced attenuation of heavy mesons in small systems such as oxygen-oxygen and high-multiplicity p-Pb events. Finally, we analyze the impact of different models of initial-state parton dynamics on the search for QGP signatures in small colliding systems.

Impact of Different Models of Relocating Coal Mining Villages on the Livelihood Resilience of Rural Households—A Case Study of Huaibei City, Anhui Province

Applying the livelihood resilience theory to the relocation of coal mining villages, the present study explored the levels and the factors hindering livelihood resilience among farmers under different relocation models. This has important implications for enhancing the livelihood resilience of farmers during coal mining relocation and promoting rural revitalization in coal mining areas. Based on the livelihood resilience framework and the actual conditions of mining areas, we formulated an evaluation index system, employed the stratified mean square deviation method to determine weights, used the comprehensive index method to assess the livelihood resilience level, and investigated the obstacles to livelihood resilience among farmers under different relocation models using the random forest model. The results indicate the following: first, the overall livelihood resilience level in the coal mining relocation area of Huaibei City is low and is not significantly different among the four types, with the ranking being as follows: central village agglomeration type > township-centered village construction type > mining-village combination type > suburban community type. Significant differences exist in the indicators and dispersion levels of the resilience dimensions of buffering capacity, self-organization ability, and learning ability among farmers under different relocation models. Second, factors such as household deposits, labor force quantity, social networks, and participation in village collective meetings significantly affect the livelihood resilience level of farmers. However, the degree of influence varies under different relocation models. Third, improvements such as increasing employment opportunities, investing in education resources, and building social networks are necessary to improve farmers’ livelihoods under the four types of relocation models.

Prediction of exam scores using a multi-sensor approach for wearable exam stress dataset with uniform preprocessing.

Physiological signals, such as skin conductance, heart rate, and temperature, provide valuable insight into the physiological responses of students to stress during examination sessions. The primary objective of this research is to explore the effectiveness of physiological signals in predicting grades and to assess the impact of different models and feature selection techniques on predictive performance. We extracted a comprehensive feature vector comprising 301 distinct features from seven signals and implemented a uniform preprocessing technique for all signals. In addition, we analyzed different algorithmic selection features to design relevant features for robust and accurate predictions. The study reveals promising results, with the highest scores achieved using 100 and 150 features. The corresponding values for accuracy, AUROC, and F1-Score are 0.9, 0.89, and 0.87, respectively, indicating the potential of physiological signals for accurate grade prediction. The findings of this study suggest practical applications in the field of education, where the use of physiological signals can help students cope with exam stress and improve their academic performance. The importance of feature selection and the use of appropriate models highlight the importance of engineering relevant features for precise and reliable predictions.

Stratified support pattern-based internet-assisted self-management therapy for diabetes mellitus -mild cognitive impairment: a randomized controlled trial protocol

BackgroundMild cognitive impairment (MCI) associated with diabetes mellitus (DM) is common among older adults, and self-management is critical to controlling disease progression. However, both MCI and DM are heterogeneous diseases, and existing integrated self-management interventions do not consider patient differences. Grouping patients by disease characteristics could help to individualize disease management and improve the use of available resources. The current study sought to explore the feasibility and effectiveness of a stratified support model for DM-MCI patients.MethodsEighty-four DM-MCI patients will be randomly divided into an intervention group and a control group in a 1:1 ratio. The intervention group will receive a self-management intervention using the stratified support pattern-based internet-assisted therapy (SISMT), while the control group will receive the health manual intervention (HMI). The study recruiter will be blinded to the group allocation and unable to foresee which group the next participant will be assigned to. At the same time, the allocation will be also hidden from the research evaluators and participants. After 12 weeks and 24 weeks, cognitive function, blood glucose, self-management ability, psychological status, health literacy, and self-management behavior of patients in both groups will be measured and compared.DiscussionThis study developed a stratified support pattern-based internet-assisted to provide self-management intervention for patients with DM-MCI. The impact of different models and forms of self-management intervention on cognitive function, blood glucose management, and psychological status health literacy and self-management behavior of patients will be assessed. The results of this study will inform related intervention research on the stratified support pattern-based internet-assisted self-management therapy, and help to slow the decline of cognitive function in patients with DM-MCI.Trial registrationChiCTR2200061991. Registered 16 July 2022.

Residual Saturation Effects on CO2 Migration and Caprock Sealing: A Study of Permeability and Capillary Pressure Models

In CO2 geological storage, multiphase flow plays a vital role in the movement and distribution of CO2. However, due to the limitations of fluid buoyancy and capillary forces, CO2 encounters challenges in penetrating the caprock, and the potential for leakage remains a concern due to variations in injection conditions. The migration and distribution of CO2 in the process of CO2 geological storage in saline formations are determined by relative permeability and capillary pressure, which are key factors. Consequently, this study focuses on two essential models: relative permeability and capillary pressure models. A two-dimensional isothermal reservoir–caprock model was constructed, utilizing data from the Shenhua CCS demonstration project. The analysis indicates that the core parameters in the model are residual gas saturation and residual water saturation. Specifically, residual gas saturation governs the diffusion distance of CO2 within the reservoir–caprock system, while its combined effect with residual water saturation affects the permeation rate of CO2. Through the application of the Analytic Hierarchy Process (AHP) to analyze the impact of different models on caprock integrity, it was determined that when selecting caprock models and optimizing parameters, precedence should be given to models with lower residual saturation and caprocks that offer sufficient capillary pressure for optimal sealing effects. These research findings can serve as references for practical CO2 storage projects, providing guidance on activities such as adjusting water injection strategies and controlling gas injection pressures to optimize geological storage efficiency.

A regression analysis of the impact of routing and packing dependencies on the expected runtime

Problems with multiple interdependent components offer a better representation of the real-world situations where globally optimal solutions are preferred over optimal solutions for the individual components. One such model is the Travelling Thief Problem (TTP); while it may offer a better benchmarking alternative to the standard models, only one form of inter-component dependency is investigated. The goal of this paper is to study the impact of different models of dependency on the fitness landscape using performance prediction models (regression analysis). To conduct the analysis, we consider a generalised model of the TTP, where the dependencies between the two components of the problem are tunable through problem features. We use regression trees to predict the instance difficulty using an efficient memetic algorithm that is agnostic to the domain knowledge to avoid any bias. We report all the decision trees resulting from the regression model, which is the core in understanding the relationship between the dependencies (represented by the features) and problem difficulty (represented by the runtime). The regression model was able to predict the expected runtime of the algorithm based on the problem features. Furthermore, the results show that the contribution of the item value drop dependency is significantly higher than the velocity change dependency.

A comprehensive approach to SBR modelling for monitoring and control system design

The aim of this research is to provide a comprehensive description of the Sequencing Batch Reactor (SBR) modelling for monitoring, control, and plant operational optimisation validation. The paper provides a detailed modelling of the SBR, its components and constituent processes. For this purpose, the mass balance principle and continuity equations were provided with a reactive term implemented using Activated Sludge Model (ASM). The spatially discretised models (along the vertical axis) are then used in numerical experiments. Simulations performed enable comparison of the impact of different models of activated sludge settling velocity, as well as two different approaches to modelling reactions in the SBR. The latter was achieved by using the ASM2d and ASM3-BioP extended with an enzyme group modelling the lag phase observed in microorganisms during a rapid change in environmental conditions. The presented results have been obtained using the model of the SBR at Swarzewo in the North of Poland.

Optimal Strategy for Comfort-Based Home Energy Management System Considering Impact of Battery Degradation Cost Model

With the deployment of renewable energy generation, home energy storage systems (HESSs), and plug-in electric vehicles (PEVs), home energy management systems (HEMSs) are critical for end users to improve the increasingly complicated energy production and consumption in the home. However, few of the previous works study the impact of different models of battery degradation cost in the optimization strategy of a comfort-based HEMS framework. In this paper, a novel scheduling algorithm based on a mixed-integer programming (MIP) model is proposed for the HEMS. Total cost minimization, peak load shifting, and residents’ thermal comfort satisfaction are combined and considered in the optimal scheduling algorithm. The impact of battery degradation costs on the charging and discharging strategy of HESS and PEV is also compared and discussed in this case study. This case study shows that the proposed optimal algorithm of HEMS not only flattens the peak load and satisfies the thermal comfort of residents but also has better flexibility and economic advantages, reducing the electricity cost by 30.84% and total cost by 24.16%. The sensitivity analysis of the parameters for the charging and discharging strategy also guarantees the lowest cost and prolongs the service life of the battery.

МОДЕЛІ КОРПОРАТИВНОГО УПРАВЛІННЯ: ПОРІВНЯЛЬНИЙ АНАЛІЗ МОДЕЛЕЙ УПРАВЛІННЯ АКЦІОНЕРНИМИ ТОВАРИСТВАМИ ТА ЇХ ВПЛИВ НА ЕФЕКТИВНІСТЬ

Corporate governance in joint stock companies is a key aspect of modern business, determining the efficiency and sustainability of companies. Given the globalization and the growing volume of world financial markets, the study of corporate governance models and their impact on efficiency is becoming an extremely important task. In this article, a comparative analysis of various models of corporate governance in joint-stock companies is carried out in order to determine their impact on the efficiency of such companies. The purpose of this study is to systematize and compare different models of corporate governance, as well as to determine their impact on the financial efficiency and sustainability of joint-stock companies. The object of the research is corporate management in jointstock companies. The subject of research is management models, including control mechanisms, ownership structures, and strategic decision-making methods. To achieve the goal, the following methods were used in this study. Systematic analysis of scholarly sources, including academic articles, books, and reports, to summarize existing theoretical approaches to corporate governance. Analysis of financial statements of joint-stock companies, using financial indicators to compare different management models and their impact on performance indicators. Survey of leading specialists and heads of corporations to obtain practical insight into the implementation of various management models. In the course of the study, the main models of corporate governance were identified and analyzed, such as the equity capital model, the "feedback" corporate governance model (stakeholder model) and others. With the help of a comparative analysis, it was determined which of them contribute to higher financial efficiency and stability of companies. Based on the research, it was determined that the "feedback" model of corporate governance improves efficiency and ensures greater sustainability of joint-stock companies compared to other models. The implementation of this model is recommended in order to increase the competitiveness and sustainability of corporations on the international market. The article offers an important contribution to the understanding of the impact of different models of corporate governance on the business environment and provides practical recommendations for enterprise managers and decision-makers regarding the choice of the optimal governance model.

Impact of model assumptions on the inference of the evolution of ectomycorrhizal symbiosis in fungi

Ectomycorrhiza (ECM) is a symbiotic relation between plant and fungi that is essential for nutrient uptake of many stand forming trees. There are two conflicting views about the evolution of ECM in fungi suggesting (1) relatively few transitions to ECM followed by reversals to non-ECM, or (2) many independent origins of ECM and no reversals. In this study, we compare these, and other, hypotheses and test the impact of different models on inference. We assembled a dataset of five marker gene sequences (nuc58, nucLSU, nucSSU, rpb1, and rpb2) and 2,174 fungal taxa covering the three subphyla: Agaricomycotina, Mucoromycotina and Pezizomycotina. The fit of different models, including models with variable rates in clades or through time, to the pattern of ECM fungal taxa was tested in a Bayesian framework, and using AIC and simulations. We find that models implementing variable rates are a better fit than models without rate shift, and that the conclusion about the relative rate between ECM and non-ECM depend largely on whether rate shifts are allowed or not. We conclude that standard constant-rate ancestral state reconstruction models are not adequate for the analysis of the evolution of ECM fungi, and may give contradictory results to more extensive analyses.

Comparison of the GLIM criteria with specific screening tool for diagnosing malnutrition in hospitalized patients with cirrhosis: A descriptive cross-sectional study.

The Global Leadership Initiative on Malnutrition (GLIM) has been built to diagnose malnutrition; however, its validity among patients with cirrhosis remains enigmatic. We aimed to investigate the prevalence of malnutrition according to GLIM criteria and compare the differences by using a specific screening tool. We conducted a descriptive cross-sectional study analyzing hospitalized patients. The Royal Free Hospital-Nutritional Prioritizing Tool (RFH-NPT) was chosen as the screening tool. Estimated prevalence was shown with and without the initial screening process. Diverse combinations of phenotypic and etiologic criteria and distinct body mass index (BMI) cutoffs were applied to detect frequency of malnourished patients with cirrhosis. Overall, 363 patients were recruited (median age, 64 years; 51.2% female). The prevalence of malnutrition according to GLIM criteria with and without RFH-NPT screening was 33.3% and 36.4%, respectively. Low BMI and inflammation represented the most prevalent combination resulting in a malnutrition diagnosis (42.4%), followed by low BMI and reduced food intake (39.4%). By contrast, the least prevalence was found when combining reduced muscle mass with inflammation to diagnose malnutrition. Furthermore, the frequency of malnourished and well-nourished participants was not statistically different when using divergent BMI reference values across the study population. GLIM criteria may serve a specific proxy to diagnose malnutrition, along with RFH-NPT screening. Relevant investigation is required to report on the applied combination of phenotypic/etiologic criteria, taking into consideration the marked impact of different models. More attempts are warranted to delineate the prognostic role of GLIM criteria in the context of cirrhosis.

Improving the Continuity of Care for People Living with HIV Experiencing Incarceration in North Carolina Jails: Stakeholder Perspectives.

BACKGROUND Jail detention can disrupt the continuity of care for people living with HIV/AIDS (PLWH). Using a state's "Data to Care" (D2C) program might help overcome this barrier, but raises important questions of data security, personal privacy, resource allocation, and logistics.METHODS As part of a study involving in-depth expert stakeholder interviews, a 1-day workshop was convened to identify and discuss potential ethical challenges in extending North Carolina's D2C program to jail settings. Workshop participants included public health officials, community advocates, HIV clinicians, jail administrators, privacy experts, criminal justice researchers, and a formerly incarcerated PLWH. Workshop participants discussed the results of earlier stakeholder interviews with the goal of identifying the most important points to consider in assessing the merits of extending D2C surveillance to jail settings.RESULTS Although the workshop participants expressed support for improving the continuity of HIV care for jail detainees, they had mixed perspectives on whether a jail-based D2C program should include in-jail or post-release follow-up interventions. Their positions were influenced by their views on 4 sets of implementation issues: privacy/data-sharing; government assistance/overreach; HIV criminalization/exceptionalism; and community engagement.LIMITATIONS The limitations of this stakeholder engagement exercise include its purposive recruitment, relatively small number of participants, and limited duration.CONCLUSIONS Improving the continuity of HIV care in particular jail settings will depend on a number of local considerations. In deciding between models featuring in-jail and post-release follow-up care, the most important of these considerations will be the possibility of establishing good partnerships between the jail, the health department, and the community. Additional research on the dynamics and impact of different models is needed.

Impact of different models of rural land consolidation on rural household poverty vulnerability

Poverty elimination poses a great challenge to all countries around the world, and the Chinese government is consistently concerned with poverty issues. Rural land consolidation (RLC) is the important measure to alleviate poverty in rural China by improving the efficiency of land use. From the perspective of future poverty, the study analyzes the mechanism by which different RLC models, the government-dominant model and the Public-Private-Partnership (PPP) model, decrease poverty vulnerability by enhancing capabilities and endowing rights under the framework of the theory of capacity poverty proposed by Amartya Sen. Based on survey data of 562 rural households from Hubei and Guizhou Provinces, this study explores the role of and differences between two RLC models in decreasing the poverty vulnerability of registered and non-registered households through the PSM-DID estimator. The main findings are as follows: (1) The proportions of poor households and poverty vulnerability households in both registered and non-registered households have declined after the implementation of RLC, revealing that poverty vulnerability occurs along with poverty; (2) Both RLC models can significantly reduce the poverty vulnerability of both types of rural households. Furthermore, the effect of reducing the poverty vulnerability of non-registered households is greater than that of registered households; (3) The PPP RLC model reduces the poverty vulnerability much more effectively than the government-led model. Based on the above findings, the paper proposes corresponding policy recommendations for improving stability of RLC for poverty alleviation, thereby decreasing the probability of future poverty. Additionally, this study provides references for the developing areas and countries to make long-acting RLC policies for poverty alleviation.

The influence of nuclear models and Monte Carlo radiation transport codes on stray neutron dose estimations in proton therapy

PurposeThis study investigates the influence of several Monte Carlo radiation transport codes and nuclear models on the simulation of secondary neutron spectra and its impact on calculating and measuring the neutron doses in proton therapy. Materials and methodsThree different multi-purpose Monte Carlo radiation transport codes (FLUKA, MCNPX, Geant4) were used together with different available nuclear models, to calculate secondary neutron energy spectra at various points inside a water tank phantom with PMMA walls using a 10 × 10 cm2 rectangular, mono-energetic proton beam (110 MeV, 150 MeV, 180 MeV, 210 MeV). Using Kerma approximation secondary neutron doses were calculated applying fluence-to-dose equivalent conversion coefficients in water. Moreover, the impact of varying spectra for electrochemically etched CR39 detector calibration was analyzed for different codes and models. ResultsIn distal positions beyond the Bragg peak, results show largest variations between the codes, which was up to 53% for the high energy neutron fluence at 16 cm from the Bragg peak of the 110 MeV proton beam. In lateral positions, the variation between the codes is smaller and for the total neutron fluence within 20%. Variation in the nuclear models in MCNPX was only visible for the proton beam energies of 180 and 210 MeV and modeling the high energy neutron fluence which reached up to 23% for 210 MeV at 11 cm lateral from the beam axis. Impact on neutron dose equivalent was limited for the different models used (<8%) while it was pronounced for the different codes (45% at 16 cm from the Bragg peak of the 110 MeV proton beam). CR39 calibration factors in lateral positions were on average varying 10% between codes and 5% between nuclear models. ConclusionsThis study demonstrated a large impact on the neutron fluence spectra calculated by different codes while the impact of different models in MCNPX proved to be less prominent for the neutron modeling in proton therapy.

How COVID-19 has affected staffing models in intensive care: A qualitative study examining alternative staffing models (SEISMIC).

To understand how COVID-19 affected nurse staffing in intensive care units (ICUs) in England, and to identify factors that influenced, and were influenced by, pandemic staffing models. Exploratory qualitative study. Semi-structured, online interviews conducted July-September 2020 with regional critical care leaders including policy leads (n=4) and directors/lead nurses (n=10) across critical care networks in England. The six themes emerging from the framework analysis illustrate how the pre-pandemic ICU culture influenced ICU staffing models during the pandemic. Changes in staffing impacted on the workforce and the care delivered, whilst it was necessary to learn from, and adjust to, a rapidly changing situation. Variation across and between networks necessitated variation in responses. The overwhelming outcome was that the pandemic has challenged the central tenets of ICU nurse staffing. Pandemic nurse staffing models resulted in changes to ICU skill-mix and staffing numbers. Factors such as the impact of nurse staffing on care practices and on the workforce need to be taken into account when developing and testing future nurse staffing models for ICU. The extent to which ICUs will return to former staffing models is not yet known but there seems to be an appetite for change. In common with many countries, nurse staffing in English ICUs was adapted to address surge requirements during the COVID-19 pandemic. Findings highlight the challenge COVID-19 presented to pre-pandemic ICU nurse staffing guidelines, the impact on patient and staff well-being and the potential legacy for future staffing models. Study findings have implications for ICU nurse managers, researchers and policy makers: nurse staffing models need to be adaptable to the local context of care and future research should investigate the impact of different models on patients, staff and health service outcomes.