Types Of Events Research Articles

A contribuição de terapeutas ocupacionais no domínio da gestão de risco e desastres: um protocolo de revisão de escopo

Abstract Introduction Disasters bring human, socioeconomic, and environmental consequences and exacerbate situations of vulnerability. Both highly industrialized core countries and those facing economic difficulties are subject to these events. In Brazil, the COVID-19 pandemic and the collapse of dams highlight difficulties in anticipating and responding to these types of events. Actions of occupational therapy in the field of emergencies and disasters are scarce in the literature, notably in the sphere of prevention. Objective To explore the evidence of the contribution of occupational therapists in the field of risk management and disasters based on the characteristics, priorities, and main areas of interest of intellectual production in occupational therapy. Method A comprehensive search will be conducted in the journals Disasters, Hazards & Crisis in Public Policy, International Journal of Mass Emergencies and Disasters, and Risk, International Journal of Risk Reduction, and Journal of Contingencies and Crisis Management, as well as in the databases Occupational Therapy Literature Search Service (OTDBASE), PubMed, and Web of Science. Inclusion Criteria Actions and experiences in the field of occupational therapy, notably those of occupational therapists in risk and disaster management, found in peer-reviewed studies adopting quantitative, qualitative, and mixed methods, in Spanish, English, and Portuguese, without temporal restriction. The approach advocated by the Joanna Briggs Institute (JBI) for study selection, critical appraisal, and data collection and synthesis will be used.

Improbable but possible: Training children to accept the possibility of unusual events.

Young children tend to deny the possibility of events that violate their expectations, including events that are merely improbable, like making onion-flavored ice cream or owning a crocodile as a pet. Could this tendency be countered by teaching children more valid strategies for judging possibility? We explored this question by training children aged 4-12 (n = 128) to consider either the similarity between the target event and unusual events that have actually occurred or causal mechanisms that might bring the target event about. Both trainings increased children's acceptance of improbable events but only for the types of events addressed during training. Older children were more likely to accept improbable events, as were children who scored higher on a measure of cognitive reflection, but neither age nor cognitive reflection moderated the effects of training. These findings indicate that children can use both similarity and causality to assess possibility, but the use of this information is highly circumscribed, further demonstrating how robustly children conflate improbability with impossibility. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

CMBEE: A constraint-based multi-task learning framework for biomedical event extraction

Objective:Event extraction plays a crucial role in natural language processing. However, in the biomedical domain, the presence of nested events adds complexity to event extraction compared to single events, and these events usually have strong semantic relationships and constraints. Previous approaches ignored the binding connections between these complex nested events. This study aims to develop a unified framework based on event constraint information that jointly extract biomedical event triggers and arguments and enhance the performance of nested biomedical event extraction. Material and Methods:We propose a multi-task learning framework based on constraint information called CMBEE for the task of biomedical event extraction. The N-tuple form of event patterns is used to represent the constrained information, which is integrated into role detection and event type classification tasks. The framework use attention mechanism and gating mechanism to explore the fusion of multiple tuple information, as well as local and global constrained information fusion methods to dig further into the connections between events. Results:Experimental results demonstrate that our proposed method achieves the highest F1 score on a multilevel event extraction biomedical (MLEE) corpus and performs favorably on the biomedical natural language processing shared task 2013 Genia event corpus (GE 13). Conclusions:The experimental results indicate that modeling event patterns and constraints for multi-event extraction tasks is effective for complex biomedical event extraction. The fusion strategy proposed in this study, which incorporates different constraint information, helps to better express semantic information.

A Data-Driven Framework for Power System Event Type Identification via Safe Semi-Supervised Techniques

This paper investigates the use of phasor measurement unit (PMU) data with deep learning techniques to construct real-time event identification models for transmission networks. Increasing penetration of distributed energy resources represents a great opportunity to achieve decarbonization, as well as challenges in systematic situational awareness. When high-resolution PMU data and sufficient manually recorded event labels are available, the power event identification problem is defined as a statistical classification problem that can be solved by numerous cutting-edge classifiers. However, in real grids, collecting tremendous high-quality event labels is quite expensive. Utilities frequently have a large number of event records without in-depth details (i.e., unlabeled events). To bridge this gap, we propose a novel semi-supervised learning-based method to improve the performance of event classifiers trained with a limited number of labeled events by exploiting the information from massive unlabeled events. In other words, compared to existing data-driven methods, our method requires only a small portion of labeled data to achieve a similar level of accuracy. Meanwhile, this work discusses and addresses the performance degradation caused by class distribution mismatch between the training set and the real applications. Specifically, this method utilizes pseudo-labeling technique to investigate the value of unlabeled events and incrementally expands the training dataset. Moreover, a safe learning mechanism is developed to mitigate the impacts of class distribution mismatch and prevent performance degradation. Based on the proposed safe learning mechanism, our model does not directly use all unlabeled events during model training, but selectively uses them through a comprehensive evaluation procedure. Numerical studies on a sizable PMU dataset have been used to validate the performance of the proposed method.

Development of a Variable Cost Prediction Model for Hospitalized Critically Ill Patients in ICU

Introduction: Hospitalization of critically ill patients in the ICU is one of the most expensive areas of hospital care. Aim: The creation of a variable cost prediction model for hospitalized patients in ICU. Material and method: A retrospective observational study was carried out, using the bottom-up costing methodology. The study sample consisted of 204 hospitalized patients in the 7-bed ICU of 251 AGH, from January 1, 2016 to December 31, 2017. The demographic and clinical characteristics of the patients were recorded and the variable cost of hospitalization was accurately calculated, through an analytical recording of all the resources required for their treatment. Multivariable linear regression was implemented to investigate the impact of variables, derived from a systematic review conducted on determinants of intensive care costs. Gender, age, length of stay, APACHE II severity scale, type of patient (medical/surgical), and renal replacement therapy were used as independent variables. The average total daily cost of hospitalisation and the average daily costs of laboratory tests, medication, and consumables were used as dependent variables. Results: An increase in APACHE II by one unit and length of ICU stay by one day is associated with an increase in total daily cost by 2.74% and 1.82% respectively, while an increase in age by one year with a decrease of 0.4 %. A medical patient shows 11.62% higher total daily cost than a surgical patient, while renal replacement therapy increases the cost by 79.49%. Conclusions:Variable ICU cost is related to gender, age, severity scale,type of event and need for renal replacement therapy.

MANAGING THE THREAT OF MANPADS USE AGAINST CIVIL AVIATION

The research results presented in this study concern selected aspects of the threat to civil aviation with terrorist attacks using the Man-Portable Air Defense System – MANPADS. The authors assess the possibility of the development of this type of threat, paying attention to several most important premises resulting from the suitability of using this type of weapon by terrorists against civilian aircraft. On the basis of the results obtained from the conducted research, the authors assess the current state of possession of this type of weapon by terrorist organizations in the world and indicate the main sources of obtaining MANPADS. The cases of incidents related to attacks on civil aircraft presented in the material indicate a high mortality rate of this type of events, the main victims of which are passengers and aircraft crews. The last part of the discussion is an overview of modern on-board systems designed to protect civil aircraft against MANPADS attacks, which they may soon be equipped with.

The Heat Budget of the Tropical Pacific Mixed Layer during Two Types of El Niño Based on Reanalysis and Global Climate Model Data

The heat budget of the equatorial Pacific mixed layer during El Niño formation was studied based on reanalysis (GLORYS2V4) and model data for the modern climate. The focus of the study is on the so-called El Niño diversity, i.e., the existence of different types of events that are characterized by different locations and intensities, as well as significantly different teleconnection all around the world. The analysis of the processes that participate in the formation of different El Niño types may serve for a better understanding of the El Niño dynamic and contribute to improving its forecast. Two classifications, based on the location and intensity of the events, were considered: strong/moderate and Eastern Pacific (EP)/Central Pacific (CP). The analysis did not reveal a significant difference in the heat budget of the mixed layer between strong and EP El Niño events, as well as between moderate and CP events. The major difference in the generation mechanism of strong (EP) and moderate (CP) El Niño events consists of the magnitude of heating produced by ocean heat budget components with higher heating rates for strong (EP) events. The evolution of sea surface temperature anomalies (SSTA) is governed primarily by oceanic advection. The vertical advection (due to the thermocline feedback) is the main contributor to SSTA growth in the eastern Pacific regardless of El Niño’s type. In the Central Pacific, horizontal advection is more important than vertical one, with a stronger impact of meridional processes for both strong and moderate regimes. Furthermore, the evaluation of the CMIP5 model’s skill in the simulation of the processes responsible for the formation of different El Niño types was carried out. The analysis of the heat budget of the mixed layer in the CMIP5 ensemble demonstrated that the most successful models are CCSM4, CESM1-BGC, CMCC-CMS, CNRM-CM5, GFDL-ESM2M, and IPSL-CM5B-LR. They are capable of reproducing the most important contribution of the advection terms in the SSTA tendency, keeping the major role of the thermocline feedback (and vertical advection) in the eastern Pacific, and do not overestimate the contribution of zonal advective feedback. These models are recommended to be used for the analysis of El Niño mechanism modification in the future climate.

Sport event vs. art event? The effect of CSR-linked sponsorship event type on product purchase

Companies often administer sponsorship initiatives to fulfill their Corporate Social Responsibility (CSR), and this practice is called CSR-linked sponsorship. This study investigated whether and how CSR-linked sponsorship event type influences consumers' intention to purchase sponsors' products, underpinned by balance theory and P–O-X theory. Our experiment showed that CSR-linked sponsorship to sport (vs. art) provokes greater purchase intention. This effect was positively mediated by the perceived sincerity of the sponsor. These findings enrich the literature by extending the scope of CSR-linked sponsorship research and illuminating both the consequence of CSR-linked sponsorship event type and its underlying mechanism. Our findings also provide managerial insights into effectively selecting CSR-linked sponsorship event type in such a way to facilitate consumers' purchase of sponsors' products.

Cross-Regional Seismic Event Discrimination via Convolutional Neural Networks: Exploring Fine-Tuning and Ensemble Averaging

ABSTRACT The gradual densification of seismic networks has facilitated the acquisition of large amounts of data. However, alongside natural tectonic earthquakes, seismic networks also record anthropogenic events such as quarry blasts or other induced events. Identifying and distinguishing these events from natural earthquakes requires experienced interpreters to ensure that seismological studies of natural phenomena are not compromised by anthropogenic events. Advanced artificial intelligence methods have already been deployed to tackle this problem. One of the applications includes Convolutional Neural Networks (CNN) to discriminate different kinds of events, such as natural earthquakes and quarry blasts. In this study, we investigate the effects of ensemble averaging and fine-tuning on seismic event discrimination accuracy to estimate the potential of these methods. We compare discrimination accuracy of two different CNN model architectures across three datasets. This was done with the best models from an ensemble of each model architecture, as well as with ensemble averaging and fine-tuning methods. Soft voting was used for the CNN ensemble predictions. For the transfer learning approach, the models were pretrained with data from two of the datasets (nontarget regions) and fine-tuned with data from the third one (target region). The results show that ensemble averaging and fine-tuning of CNN models leads to better generalization of the model predictions. For the region with the lowest numbers of one event type, the combination of ensemble averaging and fine-tuning led to an increase in discrimination accuracy of up to 4% at station level and up to 10% at event level. We also tested the impact of the amount of training data on the fine-tuning method, showing, that to create a global model, the selection of comprehensive training data is needed.

The Spatiotemporal Variation Characteristics and Impacts of Summer Heatwaves, Droughts, and Compound Drought and Heatwave Events in Jiangsu Province, China

This study used the “Daily meteorological dataset of basic meteorological elements of China National Surface Weather Station (V3.0)” and applied the absolute threshold method and standardized precipitation evapotranspiration index to identify heatwave events and drought events. This study analyzed the spatiotemporal evolution patterns of three types of summer disaster events, namely, heatwave events, drought events, and compound drought and heatwave events, in Jiangsu Province from 1960 to 2018. Additionally, it investigated and verified the concurrent historical data of the identified years with the most severe occurrence of compound drought and heatwave events and calculated the monthly drought centers and summer accumulations of the standardized precipitation evapotranspiration index (SPEI-3). The results indicate that over the 59 years analyzed, the number of days with a threshold of 35 °C, which were considered hot days, was 503.2, accounting for 9.27% of the total summer days in Jiangsu Province. Both the number of hot days and the frequency of heatwave events showed a clear increasing trend from the northeastern coastal areas to the southwestern regions of Jiangsu Province. The total frequency of drought events at different stations in Jiangsu Province from 1960 to 2018 fell within the range of 50–64. The fitted slope of the frequency of compound drought and heatwave events in Jiangsu Province was −0.021 for the period 1960 to 1989, and 0.079 for the period 1990 to 2018, indicating a higher frequency compared with the preceding 30 years. This trend aligned with the rise in heatwave events experienced in Jiangsu Province in recent years. The frequency and duration of compound drought and heatwave events in Jiangsu Province exhibited an increasing spatial pattern from the southwestern parts to the northeastern parts. This study’s verification established that the identification of compound drought and heatwave events was relatively accurate.

Анализ характеристик движения глаз оператора для определения степени его утомления

The article presents a method for searching characteristics of eye movements that correlate with fatigue. There are many characteristics of eye movements to determine fatigue. All these characteristics are calculated from such basic concepts of gaze movement as fixation and saccade. Characteristics can also be divided by the types of physical events on which they are based. It is possible to distinguish such characteristics as speed, time, quantity, size, percentage, frequency and ratio characteristics. To search for correlations between eye movement characteristics and fatigue, a dataset of eye movements and the results of the VAS-F fatigue questionnaire were analyzed in 6 subjects. The data set consists of operator parameters such as eye movements, scene camera image and gaze direction. To determine the level of fatigue, the participant completed the VAS-F questionnaire. This questionnaire consists of 18 questions about the degree of fatigue or enrgetic of a person. Each record from the data set corresponds to a questionnaire result. 60 characteristics of eye movements and the corresponding VAS-F test values were analyzed and the correlation between them was calculated. The characteristics of eye movements were then sorted in descending order of the obtained correlation values. For further analysis, the first 20 characteristics with the highest correlation were selected from each participant. A search was then made for characteristics that were found in two-thirds or more of the participants among the first 20 characteristics. As a result, 10 characteristics of eye movements were found that correlated with VAS-F test scores for each participant.

Crypto market relationships with bric countries' uncertainty – A wavelet-based approach

This study focuses on exploring the relationships between different categories of crypto assets and measures of uncertainty in BRIC countries, specifically examining geopolitical risk (GPR) and economic policy uncertainty (EPU). Our findings indicate that the co-movement of the EPU and GPR indexes with different categories of crypto assets is influenced by factors such as the time period, investment horizons, and the type of event, and that it differs across crypto assets. An overall pattern is observed, suggesting that the crypto market does not act as a hedge against economic policy uncertainties (EPU) but demonstrates a hedging effect against geopolitical risk (GPR). This distinction in hedging effectiveness is influenced by the nature of events (COVID-19 and the Russian invasion of Ukraine), since investors' expectations and perception of risk differ during these events. Furthermore, our analysis shows that stablecoins and memecoins do not exhibit consistent results in relation to GPR and EPU, suggesting that they may not serve as reliable hedging instruments against geopolitical risks or economic policy uncertainties in the BRIC countries. Our findings carry important implications for investors, portfolio managers, policy makers, and researchers, offering insights into portfolio risk management, regulatory frameworks, and the behavior of the cryptocurrency market in the face of uncertainties.

Targeted treatment options for paediatric B-cell precursor acute lymphoblastic leukaemia patients with constitutional or somatic chromosome 21 alterations

BackgroundChromosome 21 is affected in ∼60% of paediatric B-cell precursor acute lymphoblastic leukaemia (BCP-ALL) patients and includes somatic and constitutional gains, intrachromosomal amplification of chromosome 21 (iAMP21), and the translocation t(12;21) resulting in the ETV6::RUNX1 gene fusion. MethodsSince these numeric and structural chromosome 21 alterations are not targetable, we studied the type and frequency of yet-proven targetable events co-occurring with chromosome 21 alterations. ResultsAmong 307 primary paediatric BCP-ALL cases, JAK/STAT pathway lesions were most frequent in patients with constitutional gain of chromosome 21 (Down syndrome ALL; 35/71, 49%) and iAMP21 (9/22, 41%). RAS pathway lesions were most frequent in high hyperdiploidy (62/108, 57%) and FLT3 lesions were most frequent in iAMP21 (7/22, 32%). Virtually all cases expressed CD19 and CD22 at the cell surface. Positivity for CD20 surface expression ranged from 67% in iAMP21 (8/12) to 20% in ETV6::RUNX1 (26/129). ConclusionActivated JAK/STAT, RAS or FLT3 signalling, and CD marker surface expression may provide targetable treatment options for the majority of chromosome 21-altered BCP-ALL cases.

The ideathon as an instrument for entrepreneurial education in university contexts

The purpose of this study is to provide support for the use of ideathons as a useful tool in entrepreneurial education, enhancing the practical perspective of students and constituting a sound basis for generating collaborative ecosystems in universities. The objectives include exploring and describing the main steps and issues in organising this type of event. Considering the descriptive nature of the phenomenon and the first-hand information available, the case study approach has been used. To do so, a number of interviews have been conducted with high-level management positions with extensive experience in the university and in private companies. As a result, we provide a set of guidelines for organising and running successful ideathons in social sciences: (1) planning, (2) budgeting, (3) training, (4) running the competition, and (5) networking and benefits. A successful ideathon should help improve the reputation of the institution. Students can also increase their employability due to enhanced entrepreneurial skills and their interaction with real companies during the competition. Considering the scarcity of studies addressing ideathon, from a theoretical and empirical point of view, we offer a social sciences approach to idea-generation events, which have traditionally been covered from technical areas (IT domain).

Safety and efficacy of ixoberogene soroparvovec in neovascular age-related macular degeneration in the United States (OPTIC): a prospective, two-year, multicentre phase 1 study

Gene therapy, successfully used in rare, monogenetic disorders, may prove to be a durable management approach for common, polygenetic conditions, including neovascular age-related macular degeneration (nAMD). Repeated injections, oftentimes monthly, and possibly for decades, of vascular endothelial growth factor antagonists (anti-VEGF), is the standard for nAMD. We hypothesised that an in-office, intravitreal administration of ixoberogene soroparvovec (ixo-vec, formerly ADVM-022), a single-dose gene therapy encoding for the proven anti-VEGF protein, aflibercept, would transform retinal cells to continually produce aflibercept to minimise treatment burden in nAMD. In this two-year, open-label, prospective, multicentre phase 1 study, patients with nAMD responding to anti-VEGF were assigned to four cohorts differing by ixo-vec dose (2×1011 vs 6×1011 vector genomes (vg/eye)) and prophylactic steroids (oral prednisone vs topical difluprednate). The primary outcome was the type, severity, and incidence of ocular and systemic adverse events (AEs); secondary endpoints included vision, central subfield thickness (CST), and the number of supplemental injections. This study was registered with ClinicalTrials.gov, NCT03748784. Thirty patients with nAMD were enrolled between November 14, 2018 and June 30, 2020at nine study sites in the United States. No systemic ixo-vec related AEs were noted. Across both dose groups the most common adverse event was anterior chamber cell, which was reported in 11 participants in the 6×1011 dose group and in 7 participants in the 2×1011 dose group; intraocular inflammation was responsive to topical corticosteroids, with no anterior chamber cells or vitreous cells observed in 2×1011 vg/eye patients at the end of the study. Vision and CST remained stable throughout two years with annualised anti-VEGF injections reduced by 80% (10.0 mean annualised anti-VEGF injections to 1.9) in 2×1011 vg/eye and 98% (9.8 mean annualised anti-VEGF injections to 0.2) in 6×1011 vg/eye cohorts. Ixo-vec was generally well-tolerated, maintained vision, and improved anatomical outcomes in nAMD, with a substantial reduction in anti-VEGF injections. A single administration of an in-office gene therapy, with vectorised protein with an already established clinical benefit, has the potential to revolutionise the management of common ocular disorders requiring ongoing, frequent therapeutic interventions. Adverum Biotechnologies.

INTRAINDIVIDUAL VARIABILITY ACROSS ADULTHOOD: DIVERSITY, VARIETY, AND ADHERENCE AS KEY INDICATORS OF DAILY LIFE

Abstract Alongside long-term change, lifespan theories highlight the importance of examining intraindividual variability (the fluctuations that occur in daily and momentary life) as an indicator of dynamic characteristics, like plasticity or rigidity. The present symposium demonstrates five unique characterizations and implications of variability in daily life across the adult lifespan. Paper 1 demonstrates that greater social activity variety is linked to lower mortality risk over 11 years, and this effect is stronger for older adults. Paper 2 finds that consistent adherence to health behaviors in daily life is linked to better cognitive function in midlife adults. Paper 3 finds that middle-aged adults experience greater diversity in types of positive events in daily life (positive event diversity) compared to older adults, and positive event diversity is associated with higher positive affect. Paper 4 establishes that positive affect with high mean levels and high variability (fragile high positive affect) is associated with greater odds of depression 10 years later. Lastly, Paper 5 demonstrates that although the spread of stressor types experienced in daily life (stressor diversity) declines with age across both cohorts, the types of stressors experienced in modern life differ from those experienced 18 years prior. Together, findings demonstrate how variability in daily life changes across age and has implications for health and well-being of older adults. Dr. Susan Charles will critically discuss these contributions to our understanding of aging in the context of Strength and Vulnerability Integration Theory and provide considerations for understanding the complexity of daily life across the lifespan.

Final Results from RIBBIT: A Randomized Phase III Study to Evaluate Efficacy and Quality of Life in Patients with Metastatic Hormone Receptor-Positive, HER2-Negative Breast Cancer Receiving Ribociclib in Combination with Endocrine Therapy or Chemotherapy with or without Bevacizumab in the First-Line Setting

Background: We investigated the efficacy and health-related quality of life (HRQoL) in patients receiving either ribociclib plus endocrine therapy (ET) or chemotherapy with/without bevacizumab as first-line treatment of metastatic hormone receptor (HR)-positive, HER2-negative breast cancer (BC). Patients and Methods: In this randomized, phase III study (RIBBIT), 38 patients diagnosed with metastatic HR-positive, HER2-negative BC with presence of visceral metastases recruited between May 2018 and December 2020 were randomly assigned in a 1:1 ratio to either arm A (ribociclib + ET) or arm B (chemotherapy with/without bevacizumab) at 12 sites in Germany. The primary endpoint was progression-free survival (PFS). Secondary endpoints included overall response rate (ORR), overall survival (OS), patient-reported HRQoL, and frequency and type of adverse events. During study conduction, the recruitment rate was persistently and considerably lower than originally expected. Therefore, the recruitment was ended prematurely. The study was initially designed to enroll and randomize 158 patients. Results: Median [95% CI] PFS was 27.3 months [19.1 – NA, parameter not estimable] in arm A and 15.8 months [8.2 – NA] in arm B. Complete responses were achieved only in arm A (n = 2, 10.5%). The ORR [95% CI] between arm A (57.9% [33.5–79.7]) and arm B (52.6% [28.9–75.6]) was comparable. Median OS [95% CI] was not reached in arm A, while in arm B median OS was 28.4 months [25.0 – NA]. Patients in arm A reported less burden by side-effects. No new safety signals emerged. Conclusion: Treatment of patients with visceral metastatic HR-positive, HER2-negative BC with ribociclib in combination with ET showed a tendency toward a more favorable clinical outcome. Despite small numbers of patients and sites, this head-to-head comparison with chemotherapy supports the use of ribociclib with ET in patients with visceral metastasis at risk of fast disease progression.

Автоматизация классификации сейсмических событий при сейсмомониторинге угольной шахты с использованием машинного обучения

The paper is dedicated to the development of an algorithm for automatic classification of geodynamic processes in the context of monitoring seismic activity in mines using machine learning methods. The importance of classifying geodynamic processes is noted in terms of understanding the nature of seismic phenomena, identifying their sources, assessing the potential hazard as well as their impact on the environment and the infrastructure of underground structures. The paper describes an algorithm for analyzing seismic activity based on the data obtained as the result of recording seismic events using the hardware complex and the GITS2 seismic monitoring software in a coal mine. The paper briefly examines the key artificial intelligence methods used to control and predict hazardous geodynamic phenomena. Particular attention is paid to the development of a machine learning model based on decision trees that demonstrates high accuracy in classifying seismic events. The classification accuracy of the developed model is 98,39% on the training set and 98,41% on the test set. This result indicates the high generalization ability of the model on new data and the absence of overfitting. Testing the algorithm on new data entering the system also confirms the high accuracy in classification of seismic event types with the level of 83–93%. This highlights the efficiency of machine learning methods in mine seismic control. After its trial operation, the developed machine learning model will be implemented in the GITS2 monitoring system, that will allow classification of the incoming seismic events in automatic mode.

Clinical nurses’ compassion fatigue psychological experience process: a constructivist grounded theory study

BackgroundClinical nurses are susceptible to compassion fatigue when exposed to various types of traumatic events in patients for extended periods of time. However, the developmental process, staging, and psychological responses distinct to each stage of compassion fatigue in nurses are not fully clarified. This study aimed to explore the processes of compassion fatigue and the psychological experiences specific to each phase of compassion fatigue among clinical nurses.MethodsCharmaz’s Constructivist Grounded Theory methodology was used in this qualitative research. Semi-structured interviews were conducted with 13 clinical nurses with varying degrees of compassion fatigue from December 2020 to January 2021. Interview data were analyzed using grounded theory processes.ResultsThe data were categorized into five separate categories and 22 sub-categories. This study found that the process of compassion fatigue is dynamic and cumulative, which was classified into five phases: compassion experience period, compassion decrement period, compassion discomfort period, compassion distress period, and compassion fatigue period.ConclusionClinical nurses who experience compassion fatigue may go through five stages that are stage-specific and predictable. The findings can shed light on local and global applications to better understand the problem of nurses’ compassion fatigue. The interventions for addressing compassion fatigue in clinical nurses should be stage-specific, targeted, and individualized.

Description of the management of a major hazard event in a high priority installation

Industrial accidents and accidents caused by natural disasters in factories, plants and power stations are the most dangerous and pose the greatest risk. As a result of social and economic development, more and more energy carriers, raw materials, semi-finished and finished products are produced and marketed, which may pose a risk to the environment and the public. In the course of our work, we have studied a facility or plant that is a high priority, including one where ammonia is present as part of the technology in quantities of over 1000 kg. We examined the different types of accidental events that can occur in this type of plant and the need and importance of the measures taken to deal with these events and their purpose. Our aim is to identify weaknesses, propose solutions and develop alternatives for improvement. To ensure the highest standards of safety and protection of workers at work and to emphasise the shared responsibility of senior management and all workers to achieve and maintain an effective safety management system. Through our work, we want to contribute to the improvement, development and safer management of activities in an operational high priority plant.