bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prevalence and correlators of burnout among health professionals during different stages of the COVID-19 pandemic in China
Authors: Qin Zhengshan , He Zhehao , Yang Qinglin , Meng Zeyu , Lei Qiuhui , Wen Jing , Shi Xiuquan , Liu Jun , Wang Zhizhong 
Published: April 2023

BackgroundPersistently increased workload and stress occurred in health professionals (HPs) during the past 3 years as the COVID-19 pandemic continued. The current study seeks to explore the prevalence of and correlators of HPs' burnout during different stages of the pandemic.MethodsThree repeated online studies were conducted in different stages of the COVID-19 pandemic: wave 1: after the first peak of the pandemic, wave 2: the early period of the zero-COVID policy, and wave 3: the second peak of the pandemic in China. Two dimensions of burnout, emotional exhaustion (EE) and declined personal accomplishment (DPA), were assessed using Human Services Survey for Medical Personnel (MBI-HSMP), a 9-item Patient Health Questionnaire (PHQ-9), and a 7-item Generalized Anxiety Disorder (GAD-7) to assess mental health conditions. An unconditional logistic regression model was employed to discern the correlators.ResultsThere was an overall prevalence of depression (34.9%), anxiety (22.5%), EE (44.6%), and DPA (36.5%) in the participants; the highest prevalence of EE and DPA was discovered in the first wave (47.4% and 36.5%, respectively), then the second wave (44.9% and 34.0%), and the third wave had the lowest prevalence of 42.3% and 32.2%. Depressive symptoms and anxiety were persistently correlated with a higher prevalence risk of both EE and DPA. Workplace violence led to a higher prevalence risk of EE (wave 1: OR = 1.37, 95% CI: 1.16–1.63), and women (wave 1: OR = 1.19, 95% CI: 1.00–1.42; wave 3: OR =1.20, 95% CI:1.01–1.44) and those living in a central area (wave 2: OR = 1.66, 95% CI: 1.20–2.31) or west area (wave 2: OR = 1.54, 95% CI: 1.26–1.87) also had a higher prevalence risk of EE. In contrast, those over 50 years of age (wave 1: OR = 0.61, 95% CI: 0.39–0.96; wave 3: OR = 0.60, 95% CI: 0.38–0.95) and who provided care to patients with COVID-19 (wave 2: OR = 0.73, 95% CI: 0.57–0.92) had a lower risk of EE. Working in the psychiatry section (wave 1: OR = 1.38, 95% CI: 1.01–1.89) and being minorities (wave 2: OR = 1.28, 95% CI: 1.04–1.58) had a higher risk of DPA, while those over 50 years of age had a lower risk of DPA (wave 3: OR = 0.56, 95% CI: 0.36–0.88).ConclusionThis three-wave cross-sectional study revealed that the prevalence of burnout among health professionals was at a high level persistently during the different stages of the pandemic. The results suggest that functional impairment prevention resources and programs may be inadequate and, as such, continuous monitoring of these variables could provide evidence for developing optimal strategies for saving human resources in the coming post-pandemic era.
Depression and anxiety among Macau residents during the COVID-19 outbreak: A network analysis perspective
Authors: Sun He-Li , Chen Pen , Feng Yuan , Si Tong Leong , Lam Mei Ieng , Lok Ka-In , Chow Ines Hang Iao , Su Zhaohui , Cheung Teris , Tang Yi-Lang , Jackson Todd , Sha Sha , Xiang Yu-Tao 
Published: April 2023

BackgroundThe 2019 novel coronavirus disease (COVID-19) outbreak affected people’s lifestyles and increased their risk for depressive and anxiety symptoms (depression and anxiety, respectively hereafter). We assessed depression and anxiety in residents of Macau during “the 6.18 COVID-19 outbreak” period and explored inter-connections of different symptoms from the perspective of network analysis.MethodsIn this cross-sectional study, 1,008 Macau residents completed an online survey comprising the nine-item Patient Health Questionnaire (PHQ-9) and seven-item Generalized Anxiety Disorder Scale (GAD-7) to measure depression and anxiety, respectively. Central and bridge symptoms of the depression-anxiety network model were evaluated based on Expected Influence (EI) statistics, while a bootstrap procedure was used to test the stability and accuracy of the network model.ResultsDescriptive analyses indicated the prevalence of depression was 62.5% [95% confidence interval (CI) = 59.47–65.44%], the prevalence of anxiety was 50.2% [95%CI = 47.12–53.28%], and 45.1% [95%CI = 42.09–48.22%] of participants experienced comorbid depression and anxiety. “Nervousness-Uncontrollable worry” (GADC) (EI = 1.15), “Irritability” (GAD6) (EI = 1.03), and “Excessive worry” (GAD3) (EI = 1.02) were the most central symptoms, while “Irritability” (GAD6) (bridge EI = 0.43), “restlessness” (GAD5) (bridge EI = 0.35), and “Sad Mood” (PHQ2) (bridge EI = 0.30) were key bridge symptoms that emerged in the network model.ConclusionNearly half of residents in Macau experienced comorbid depression and anxiety during the 6.18 COVID-19 outbreak. Central and bridge symptoms identified in this network analysis are plausible, specific targets for treatment and prevention of comorbid depression and anxiety related to this outbreak.
Reinfections and Cross-Protection in the 1918/19 Influenza Pandemic: Revisiting a Survey Among Male and Female Factory Workers
Authors: Matthes Katarina L. , Le Vu Mathilde , Bhattacharyya Urmila , Galliker Antonia , Kordi Maryam , Floris Joël , Staub Kaspar 
Published: April 2023

Objectives: The COVID-19 pandemic highlights questions regarding reinfections and immunity resulting from vaccination and/or previous illness. Studies addressing related questions for historical pandemics are limited.Methods: We revisit an unnoticed archival source on the 1918/19 influenza pandemic. We analysed individual responses to a medical survey completed by an entire factory workforce in Western Switzerland in 1919.Results: Among the total of n = 820 factory workers, 50.2% reported influenza-related illness during the pandemic, the majority of whom reported severe illness. Among male workers 47.4% reported an illness vs. 58.5% of female workers, although this might be explained by varied age distribution for each sex (median age was 31 years old for men, vs. 22 years old for females). Among those who reported illness, 15.3% reported reinfections. Reinfection rates increased across the three pandemic waves. The majority of subsequent infections were reported to be as severe as the first infection, if not more. Illness during the first wave, in the summer of 1918, was associated with a 35.9% (95%CI, 15.7–51.1) protective effect against reinfections during later waves.Conclusion: Our study draws attention to a forgotten constant between multi-wave pandemics triggered by respiratory viruses: Reinfection and cross-protection have been and continue to be a key topic for health authorities and physicians in pandemics, becoming increasingly important as the number of waves increases.
Gut Microbiome and Associated Metabolites Following Bariatric Surgery and Comparison to Healthy Controls
Authors: Ahmad Adilah F. , Caparrós-Martín Jose A. , Lee Silvia , O’Gara Fergal , Yeap Bu B. , Green Daniel J. , Ballal Mohammed , Ward Natalie C. , Dwivedi Girish 
Published: April 2023

The gut microbiome plays a significant role in regulating the host’s ability to store fat, which impacts the development of obesity. This observational cohort study recruited obese adult men and women scheduled to undergo sleeve gastrectomy and followed up with them 6 months post-surgery to analyse their microbial taxonomic profiles and associated metabolites in comparison to a healthy control group. There were no significant differences in the gut bacterial diversity between the bariatric patients at baseline and at follow-up or between the bariatric patients and the cohort of healthy controls. However, there were differential abundances in specific bacterial groups between the two cohorts. The bariatric patients were observed to have significant enrichment in Granulicatella at baseline and Streptococcus and Actinomyces at follow-up compared to the healthy controls. Several operational taxonomic units assigned to commensal Clostridia were significantly reduced in the stool of bariatric patients both at baseline and follow-up. When compared to a healthy cohort, the plasma levels of the short chain fatty acid acetate were significantly higher in the bariatric surgery group at baseline. This remained significant when adjusted for age and sex (p = 0.013). The levels of soluble CD14 and CD163 were significantly higher (p = 0.0432 and p = 0.0067, respectively) in the bariatric surgery patients compared to the healthy controls at baseline. The present study demonstrated that there are alterations in the abundance of certain bacterial groups in the gut microbiome of obese patients prior to bariatric surgery compared to healthy individuals, which persist post-sleeve gastrectomy.
Effective Generation of Functional Pancreatic β Cells from Human-Derived Dental Stem Cells of Apical Papilla and Bone-Marrow-Derived Stem Cells: A Comparative Study
Authors: Abuarqoub Duaa , Adwan Sofia , Zaza Rand , Wehaibi Suha , Aslam Nazneen , Jafar Hanan , Qinnah Nidal , Awidi Abdalla 
Published: April 2023

Diabetes Mellitus Type 1 is an autoimmune disease that occurs due to the destruction of insulin-producing cells (β cells), resulting in hyperglycemia. Therefore, diabetic patients depend on insulin treatment for the rest of their lives. Stem cells are considered a promising cellular therapy to replace the nonfunctional beta cells with functional and mature beta cells. Hence, in this study, we aimed to examine the potential of dental stem cells of apical papilla (SCAP) to differentiate into functional islet cell aggregates (ICAs), compared to the ICA generated from bone-marrow-derived stem cells (BM-MSCs). Our strategy was to induce the differentiation of SCAP and BM-MSCs into a definitive endoderm. The success of endodermal differentiation was determined by measuring the expression of definitive endodermal markers, FOXA2 and SOX-17, by flow cytometry. Next, the maturity and functionality of the differentiated cells were evaluated by measuring the amount of insulin and C-peptide secreted by the derived ICAs using ELISA. Additionally, the expression of mature beta cell markers—insulin, C-peptide, glucagon and PDX-1—was detected through confocal microscopy, while the staining of the mature islet-like clusters was detected by using diphenythiocarbazone (DTZ). Our results have shown that both SCAP and BM-MSCs were sequentially committed to a definitive pancreatic endoderm and β-cell-like cells by upregulating the expression of FOXA2 and SOX17 significantly (**** p < 0.0000 and *** p = 0.0001), respectively. Moreover, the identity of ICAs was confirmed by DTZ-positive staining, as well as by the expression of C-peptide, Pdx-1, insulin and glucagon at day 14. It was noted that at day 14, differentiated ICAs released insulin and C-peptides in a significant manner (* p < 0.01, *** p = 0.0001), respectively, exhibiting in vitro functionality. Our results demonstrated for the first time that SCAP could be differentiated into pancreatic cell lineage in a similar manner to BM-MSCs, suggesting a new unambiguous and nonconventional source of stem cells that could be used for stem cell therapy to treat diabetes.
A Machine Learning Approach to Predict HIV Viral Load Hotspots in Kenya Using Real-World Data
Authors: Kagendi Nancy , Mwau Matilu 
Published: April 2023

Background
Machine learning models are not in routine use for predicting HIV status. Our objective is to describe the development of a machine learning model to predict HIV viral load (VL) hotspots as an early warning system in Kenya, based on routinely collected data by affiliate entities of the Ministry of Health. Based on World Health Organization’s recommendations, hotspots are health facilities with ≥20% people living with HIV whose VL is not suppressed. Prediction of VL hotspots provides an early warning system to health administrators to optimize treatment and resources distribution.

Methods
A random forest model was built to predict the hotspot status of a health facility in the upcoming month, starting from 2016. Prior to model building, the datasets were cleaned and checked for outliers and multicollinearity at the patient level. The patient-level data were aggregated up to the facility level before model building. We analyzed data from 4 million tests and 4,265 facilities. The dataset at the health facility level was divided into train (75%) and test (25%) datasets.

Results
The model discriminates hotspots from non-hotspots with an accuracy of 78%. The F1 score of the model is 69% and the Brier score is 0.139. In December 2019, our model correctly predicted 434 VL hotspots in addition to the observed 446 VL hotspots.

Conclusion
The hotspot mapping model can be essential to antiretroviral therapy programs. This model can provide support to decision-makers to identify VL hotspots ahead in time using cost-efficient routinely collected data.
Implementing Organizational Ethics in Academic Environment – The Case of Croatian University
Authors: Lovrincevic Marina 
Published: April 2023

Despite its great importance as a crucial aspect of organizational culture, organizational ethics and the implementation of ethics initiatives at all levels of the organization are still largely misunderstood or even neglected, not only in the business world but also in academia. Given the role of universities in educating young people for the labour market and future jobs, the translation of defined and proclaimed ethical policies, norms, and formal documents into desirable ethical behaviours by individuals, departments, and faculties is a sine qua non requirement for any university. This is especially true in less developed countries and emerging economies where the challenge of creating an ethical environment in organizations, corporate or otherwise is even greater.

The main goal of the paper is to explore the interrelationship between formalized ethical policies and initiatives and demonstrated ethical behaviours at the organizational level, as well as to further investigate their role in shaping ethical behaviours of academic staff and, subsequently, ethical behaviours of students in an academic setting in a transitional economy. To achieve this goal, empirical research was conducted in 2021 using a specially designed questionnaire on a sample of 115 employees from one of the leading universities in Croatia. A moderated mediation model was designed and the analysis was conducted using PROCESS macro v4.0 for SPSS. The obtained results suggest that the effectiveness of standalone formalized ethical policies and initiatives is questionable in shaping ethical behaviours of academic staff, whereas these policies and initiatives in conjunction with actually demonstrated high ethical behaviours at the organizational level positively influence the ethical behaviours of academic staff. Moreover, the demonstrated ethical behaviours of academic staff plays an important mediating role in the positive impact of formalized ethical policies and initiatives on student ethical behaviours. In fact, demonstrated high ethical behaviour at the organizational level contribute positively to the indirect effects in this model. These and other findings of the research contribute to the relevant literature by providing additional confirmation of the importance of moving beyond formal ethics-related documents to actually demonstrated ethical behaviours in shaping ethical behaviours of individuals, in this case, university employees and students.
Information Security Posture to Organize and Communicate the Information Security Governance Program
Authors: Tran Dinh Uy , Jøsang Audun 
Published: April 2023

Information security practice has evolved greatly from being mostly a technical concern to also becoming a concern of executive management. As a result, there are many different frameworks, guidelines and certification programs for information security governance (ISG) and management. The purpose of these standards and certification programs is to help an organization develop a structured approach for governing and managing information security. However, these standards and guidelines are generic and not tailored for any specific organization. These frameworks usually specify “what” should be implemented but not “how”. Additionally, these frameworks do not specify “how” to communicate the information security posture (ISP) to the executive management in a simplistic manner. This paper first defines and conceptualizes the term information security posture, and then proposes a framework on “how” to communicate and organize the ISP. Our contribution complements ISG programs adopted by organizations to give executive management a better understanding and oversight. We argue that describing the ISP of an organization will support well-informed decision-making while ensuring alignment with business objectives.
Building positive reputation and low risk for financial organizations, through Culture
Authors: Christakou Roila 
Published: April 2023

In a continuously changing world environment, following financial crisis, pandemic crisis, wars, environmental disasters, along with the changes in the once “static” banking sector per-se, given the expansion of digital currencies, online financial services, expansion digital offerings, the rise of open-banking, one should expect a substantial change to an organisation’s reputation.
Risks are emerging from everywhere and have as a result the increased focus from investors and regulators on how culture is formed in financial institutions.
At the same time, culture (a quite diverse term that we will try in this paper to define and place in the banking sector frame), is considered to be a critical factor for banks to be able to respond effectively to all the changes and build long-lasting positive reputation and success. The ability to leverage the compliance program and embed ethics, top-down, contributes also significantly.
In this paper, we will try to define positive reputation for banks in this new era and set the grounds for the importance of understanding the need to manage or/and change Culture, along with aligning risks and people.
The Role of Machine Learning in Managing Uncertainty in Projects – A View on Early Warning Systems
Authors: Ekambaram Anandasivakumar , Vågbø Pål Christian , Van der Leyen Bjørn S. 
Published: April 2023

Machine learning techniques deals with, among other things, pattern recognition in large amounts of data to identify trends and possible events in the future regarding a given topic of interest. Machine learning methods are useful for addressing challenges in and creating new benefits for organisations. This paper looks at how machine learning can contribute to manage projects effectively.
Many organisations apply the concept of project. A part of them are purely project-based organisations, and a part of them carry out projects in addition to their mass-production activities and permanent operations. Within the realm of project management, this paper sets its focus on studying the role of machine learning in handling unexpected events and uncertainty in projects. One of the ways to deal with unexpected events and uncertainty is to capture early warning signs that can predict unexpected events.
A major failure of projects can be seen as a combined effect of a series of small failures, negative results or problems that have occurred over a period of time. Project teams may not notice or just ignore early warning signs of these problems and choose to work further in the project. This could finally lead to a major failure, at which point no preventive actions could save the project from the major failure. Several researchers have researched on early warning signs and systems within the context of projects. Early warning signs can be seen as some kind of a pattern recognition from a pool of relevant data.
This paper aims to answer the following two interrelated research questions: (1) What role does machine learning have in early warnings in projects? (2) How can machine learning contribute to effective project management (for example, handling uncertainty in projects)? This is a conceptual paper, based on literature study.
Some Features of Infectious Endocarditis during the Pandemic COVID-19 Infection
Authors: Родина Е.В. , Корженевская Н.И. , Гавриленко Д.И. , Корженевский Ж.Э. , Кадочкина Н.Г. 
Published: April 2023

Цель. Анализ клинических проявлений инфекционного эндокардита у пациентов, перенесших COVID-19-инфекцию. Материалы и методы. Проанализированы данные 66 пациентов с диагностированным инфекционным эндокардитом (ИЭ) в период с 2018 по 2022 г. в рамках обсервационного продольного с ретроспективным фрагментом исследования. Были выделены группы: перенесшие COVID-19-инфекцию и без COVID-19-инфекции, c первичным и вторичным ИЭ, с сопутствующими заболеваниями и без сопутствующей патологии. Далее проводились анализ и сопоставление групп по ключевым параметрам. Результаты. Установлено увеличение числа случаев ИЭ в течение анализируемого периода. С 2020 по 2022 г. в 25 случаях из 46 (54%, 95% ДИ 40,0–68,7) ИЭ был выявлен у подтвержденных реконвалесцентов после инфекции COVID-19. Не выявлено особенностей клинической картины ИЭ у пациентов, перенесших COVID-19-инфекцию. Преобладающими клиническими проявлениями были лихорадка, потливость, озноб. Среди выделенных при микробиологическом исследовании крови микроорганизмов 75% были грамположительными бактериями (n=9) с преобладанием семейства Enterococcaceae. Заключение. Повторная эхокардиография (ЭхоКГ) должна быть выполнена пациентам, перенесшим COVID-19-инфекцию, в том числе при отсутствии других очевидных показаний к данному исследованию. Для определения сроков и кратности повторной ЭхоКГ необходим анализ большой выборки пациентов с ИЭ.
The purpose of the study is to analyze the clinical manifestations of infective endocarditis in patients who have had COVID-19 infection. Material and methods. We analyzed the data of 66 patients with infective endocarditis (IE) in the period from 2018 to 2022, this study – is an observational longitudinal with a retrospective fragment. Selective groups were followed: patient after COVID-19 infection and without COVID-19 infection, with primary and secondary IE, with comorbidities and without comorbidities. Further, the groups were analyzed and compared by key parameters. Results. We observed an increase in the number of cases of IE during the analyzed period. From 2020 to 2022, 25 out of 46 cases (54%, 95% CI 40.0–68.7) had IE in confirmed convalescents after COVID-19 infection. There were no features of the clinical picture of IE in patients who underwent COVID-19 infection. The predominant clinical manifestations were fever, sweating, chills. Among the microorganisms isolated during microbiological blood analysis, 75% were gram-positive bacteria (n=9), with a predominance of the Enterococcaceae family. Conclusion. Repeat echocardiography should be performed in patients who have had a previous COVID-19 infection, including in the absence of other obvious indications for this study. To determine the timing and frequency of repeated echocardiography, it is necessary to analyze a large sample of patients with IE.