Workplace Bullying and Intention to Leave: The Mediating Role of Emotional Exhaustion

Bullying at work and its impact on employees' intention to leave are the focus of this study. Specifically, this research aims to determine the link between workplace bullying and emotional exhaustion and the intention to leave. Data were gathered from 234 employees working in the Saif group of Pakistan through questionnaires. The study sample was drawn using the convenience sampling technique. The non-probability sampling technique was used because of the Covid 19 situation;as per government notification, only 50% of the staff was present in the offices. This study used SPSS V. 25 for direct relationships, Hayes model 4 for mediation analysis, and for model fitness, we used CFA (Amos 22). The results show that workplace bullying has a statistically significant and positive impact on the intention to quit and emotional exhaustion plays a significant role in mediating this connection (β=0.38***, SE=0.074, LLCI=0.3077 and ULCI=0.6176). Based on these results, we conclude that workplace bullying is a mayor cause of employees' exhaustion and compels them to depart from an organisation at some point. In light of these results, supervisors or line managers play a vital role in organisational sustainability by retaining skilful employees by making the workplace environment friendly and cooperative in the long run.

Monkeypox Detection Using CNN with Transfer Learning.

Monkeypox disease is caused by a virus that causes lesions on the skin and has been observed on the African continent in the past years. The fatal consequences caused by virus infections after the COVID pandemic have caused fear and panic among the public. As a result of COVID reaching the pandemic dimension, the development and implementation of rapid detection methods have become important. In this context, our study aims to detect monkeypox disease in case of a possible pandemic through skin lesions with deep-learning methods in a fast and safe way. Deep-learning methods were supported with transfer learning tools and hyperparameter optimization was provided. In the CNN structure, a hybrid function learning model was developed by customizing the transfer learning model together with hyperparameters. Implemented on the custom model MobileNetV3-s, EfficientNetV2, ResNET50, Vgg19, DenseNet121, and Xception models. In our study, AUC, accuracy, recall, loss, and F1-score metrics were used for evaluation and comparison. The optimized hybrid MobileNetV3-s model achieved the best score, with an average F1-score of 0.98, AUC of 0.99, accuracy of 0.96, and recall of 0.97. In this study, convolutional neural networks were used in conjunction with optimization of hyperparameters and a customized hybrid function transfer learning model to achieve striking results when a custom CNN model was developed. The custom CNN model design we have proposed is proof of how successfully and quickly the deep learning methods can achieve results in classification and discrimination.

COVID-19 and Lifestyle Changes: A Cross-Sectional Study at Primary Care Settings in Dubai

Introduction: The first report on COVID-19 was in Wuhan, Hubei Province, China on December 31, 2019. COVID-19 was declared a pandemic by the World Health Organization on March 11, 2020. As a result of the COVID-19 pandemic, the world had to adopt certain modifications to hinder the transmission of the disease. These changes have affected patients' sleeping, dietary, and lifestyle habits. Little research is conducted on these changes among patients presenting at primary healthcare settings following the pandemic. Therefore, we conducted this study to determine the self-reported changes in these habits in patients attending primary health care centers of Dubai both before and during the pandemic. Material and Methods: A cross-sectional study was conducted among patients attending primary health care centers in Dubai from November 2020 to August 2021. Patients filled out an online questionnaire that included items for sociodemographic characteristics and study outcomes. The outcomes included changes in sleeping, smoking, dietary, and sporting habits both before and during the pandemic. Data were further stratified by gender. Results: A total number of 385 patients participated in this study. Significant changes in sleeping habits both before and during the pandemic were observed among included patients (p = 0.004) which were consistent in female patients only (p = 0.025). Most patients were not smokers both before and during the pandemic (92.98% vs. 92.46%);however, no significant change was noted across male (p = 0.503) and female patients (p = 0.391). There was a positive change in sporting habits across both male (p = 0.005) and female patients (p = 0.001). The majority of patients reported no change in the number of daily meals eaten (50.13%) following the pandemic. Conclusion: Our study highlighted that sleeping habits among primary care patients were negatively affected during the pandemic as compared to before. However, there was a positive change in their sporting habits with no change in smoking. Additionally, no substantial change in dietary habits was noted. However, further research is needed to confirm our findings.

A Standard-Based Citywide Health Information Exchange for Public Health in Response to COVID-19: Development Study.

BACKGROUND: Disease surveillance is a critical function of public health, provides essential information about the disease burden and the clinical and epidemiologic parameters of disease, and is an important element of effective and timely case and contact tracing. The COVID-19 pandemic demonstrates the essential role of disease surveillance in preserving public health. In theory, the standard data formats and exchange methods provided by electronic health record (EHR) meaningful use should enable rapid health care data exchange in the setting of disruptive health care events, such as a pandemic. In reality, access to data remains challenging and, even if available, often lacks conformity to regulated standards. OBJECTIVE: We sought to use regulated interoperability standards already in production to generate awareness of regional bed capacity and enhance the capture of epidemiological risk factors and clinical variables among patients tested for SARS-CoV-2. We described the technical and operational components, governance model, and timelines required to implement the public health order that mandated electronic reporting of data from EHRs among hospitals in the Chicago jurisdiction. We also evaluated the data sources, infrastructure requirements, and the completeness of data supplied to the platform and the capacity to link these sources. METHODS: Following a public health order mandating data submission by all acute care hospitals in Chicago, we developed the technical infrastructure to combine multiple data feeds from those EHR systems-a regional data hub to enhance public health surveillance. A cloud-based environment was created that received ELR, consolidated clinical data architecture, and bed capacity data feeds from sites. Data governance was planned from the project initiation to aid in consensus and principles for data use. We measured the completeness of each feed and the match rate between feeds. RESULTS: Data from 88,906 persons from CCDA records among 14 facilities and 408,741 persons from ELR records among 88 facilities were submitted. Most (n=448,380, 90.1%) records could be matched between CCDA and ELR feeds. Data fields absent from ELR feeds included travel histories, clinical symptoms, and comorbidities. Less than 5% of CCDA data fields were empty. Merging CCDA with ELR data improved race, ethnicity, comorbidity, and hospitalization information data availability. CONCLUSIONS: We described the development of a citywide public health data hub for the surveillance of SARS-CoV-2 infection. We were able to assess the completeness of existing ELR feeds, augment those feeds with CCDA documents, establish secure transfer methods for data exchange, develop a cloud-based architecture to enable secure data storage and analytics, and produce dashboards for monitoring of capacity and the disease burden. We consider this public health and clinical data registry as an informative example of the power of common standards across EHRs and a potential template for future use of standards to improve public health surveillance.

Gastronomic Tourism and Tourist Motivation: Exploring Northern Areas of Pakistan.

Gastronomic tourism is becoming an essential consideration among tourists when choosing a tourist destination. One of the main reasons for visiting a specific destination for almost 15% of tourists is "gastronomy". This has led to the development of a new kind of tourism called "Gastronomic Tourism". However, there has been minimal research on gastronomy tourism, specifically in Pakistan. The primary purpose of this study is to measure the level of satisfaction in a tourist destination and furthermore consider gastronomy as a component of visitor motivation. A survey of 307 tourists who had recently visited Pakistan's northern areas was undertaken to conduct the study. This has enabled us to better understand the variables that influence the behaviors and attitudes of tourists toward this popular tourist attraction. Gastronomy motivation impacts tourism location selection, and gastronomic experience influences satisfaction, according to the research. Specifically, tourists show a keen interest in gastronomic experiences after feeling satisfied with the destination and local foods, developing loyalty toward the destination.

Does Servant Leadership Control Psychological Distress in Crisis? Moderation and Mediation Mechanism

Purpose This study aims to investigate the impact of servant leadership on the psychological distress of healthcare staff during the Covid-19 crisis. The authors propose that work engagement mediates and mindfulness moderates the direct relationship between servant leadership and psychological distress. Methods Time-lagged data were collected from 277 healthcare staff working at different hospitals in Pakistan. Process Macro version 3.1 on SPSS 23 was used for statistical analysis. For model fitness, we used AMOS V 22. Results The results show that servant leadership is negatively related to psychological distress. Furthermore, work engagement mediates the relationship between servant leadership and psychological distress. Moreover, mindfulness is anticipated to moderate the direct relationship between servant leadership and psychological distress, drawing on the social exchange and conservation of resources theory. Discussion This study finds that servant leadership is vital for the mental health of healthcare staff. Thus, it extends the utility of the concept of servant leadership to the psychology and crisis management literature.

Examining Whistleblowing Intention: The Influence of Rationalization on Wrongdoing and Threat of Retaliation

Whistleblowers who expose wrongdoing often face several concerns, pressures, and threats of retaliation before reaching a final decision. Specifically, this study examines the effects of perceived seriousness of wrongdoing (PSW) and perceived threat of retaliation (PTR), as well as the impact of rationalization (RNL), comparing perceived seriousness of wrongdoing, perceived threat of retaliation and whistleblowing intention. Furthermore, this study aims to determine the mediating effect of anticipated regret (AR) on the relationship between perceived seriousness of wrongdoing and whistleblowing intention. We validated our model by analyzing data gathered across three stages from employees in the telecom sector in Pakistan. The key findings of our research may be summarized as follows: (i) individuals’ willingness to ‘blow the whistle’ increases as a result of perceived seriousness of wrongdoing;(ii) whistleblowers are more likely to opt to remain silent if they anticipate a greater threat of retaliation, and (iii) our study establishes a positive connection between perceived seriousness of wrongdoing and whistleblowing intention, indicating that perceived seriousness of wrongdoing enhances people’s willingness to blow the whistle, and whistleblowers are more likely to choose to emerge if the behaviour is more serious in nature;(iv) the data we have uncovered indicates a moderating role of rationalization in regulating the connections between perceived seriousness of wrongdoing, perceived threat of retaliation, and whistleblowing intention;and (v) the findings demonstrate that anticipated regret mediates the connection between perceived seriousness of wrongdoing and the intention to report wrongdoing. Additionally, the results are discussed in terms of their significance for corporate ethics researchers and managers, as well as for end-users who are interested in whistleblowing.

Towards Examining the Link Between Workplace Spirituality and Workforce Agility: Exploring Higher Educational Institutions.

PURPOSE: Spiritual inherited employees quickly shift to new changes that occur very quickly in our daily lives in different ways. We are inspired by the dynamic changes in our daily lives due to the Covid 19 situation, an urgent need to specify the shift from the traditional approach to the agile approach during a pandemic. This study aimed to figure out the effect of workplace spirituality on workforce agility; further, this study underpinning spillover theory to examine the role of job involvement as a mediator. METHODS: This study investigates a sample of 236 teaching and administrative staff working in public sector institutes located in Peshawar, Pakistan. For data analysis, we used SPSS v. 25, and for model fitness, we used AMOS version 22. Furthermore, we used Process Hayes (Model 4) to test the theoretical model and research hypothesis for mediation. RESULTS: This unique study offers a paradigm in which spirituality in the workplace substantially influences the agility of teaching and administrative professionals by positively mediating the effects of job involvement. DISCUSSION: An in-depth examination of the literature showed that no prior research had studied the connection between WPS, job involvement, and workforce agility. Furthermore, there is very little research regarding WPS and its connection with other components in the Covid 19 scenario. The current study was a modest attempt to address this gap in the literature. This research has succeeded in making substantial additions to management literature.

An interactive tool to forecast US hospital needs in the coronavirus 2019 pandemic.

OBJECTIVE: We developed an application (https://rush-covid19.herokuapp.com/) to aid US hospitals in planning their response to the ongoing Coronavirus Disease 2019 (COVID-19) pandemic. MATERIALS AND METHODS: Our application forecasts hospital visits, admits, discharges, and needs for hospital beds, ventilators, and personal protective equipment by coupling COVID-19 predictions to models of time lags, patient carry-over, and length-of-stay. Users can choose from 7 COVID-19 models, customize 23 parameters, examine trends in testing and hospitalization, and download forecast data. RESULTS: Our application accurately predicts the spread of COVID-19 across states and territories. Its hospital-level forecasts are in continuous use by our home institution and others. DISCUSSION: Our application is versatile, easy-to-use, and can help hospitals plan their response to the changing dynamics of COVID-19, while providing a platform for deeper study. CONCLUSION: Empowering healthcare responses to COVID-19 is as crucial as understanding the epidemiology of the disease. Our application will continue to evolve to meet this need.