Together a Catalyst: Learning From Our Co-Creative Arts-Based Inquiry About Our Teacher Selves During the Transition to Online Teaching

The COVID-19 pandemic necessitated many adjustments to everyday teaching at higher education institutions. While face-to-face lectures were the preferred teaching method of teacher educators prior to the COVID-19 pandemic, the shift to online teaching was heightened during the COVID-19 pandemic. This paper draws attention to the shifts we transitioned to as teacher educators teaching and researching via online platforms-specifically Zoom-in the context of the COVID-19 pandemic. This study explored how three teacher educators used co-creative arts-based inquiry to deepen their understanding of their shifting teacher 'selves' as online users. Object-inspired narratives and poetic inquiry were employed to co-flexively engage with our shifting teaching experiences and question our feelings of discomfort teaching online. Framed conceptually by an ethics of care and collaborative-creativity, we discuss the tensions and possibilities we experienced, and shared through our scholarly online conversations via Zoom to think through the shifts in our teacher selves and teaching. We highlight our online teaching experiences amidst the uncertainty and disruption of the COVID-19 pandemic. We then share the methodological insight of collaborative arts-based inquiry and how it facilitated reflexive dialogues and deep conversations that ignited self-learning and collective insights into the potential and possibilities of online teaching. Findings highlighted that co-creative, online engagement enabled sharing of emotional experiences and offered possibilities for transforming teacher selves. In addition, co-creative, online engagement enabled the cultivation of relational scholarly thinking. The article highlights the methodological insight of co-creative arts-based research in productively disrupting instrumental university discourse of online teaching.

Evaluating Efficiency of a Provincial Telerehabilitation Service in Improving Access to Care During the COVID-19 Pandemic

Scope: Early in the COVID-19 pandemic, community rehabilitation stakeholders from a provincial health system designed a novel telerehabilitation service. The service provided wayfinding and self-management advice to individuals with musculoskeletal concerns, neurological conditions, or post-COVID-19 recovery needs. This study evaluated the efficiency of the service in improving access to care. Methodology: We used multiple methods including secondary data analyses of call metrics, narrative analyses of clinical notes using artificial intelligence (AI) and machine learning (ML), and qualitative interviews. Conclusions: Interviews revealed that the telerehabilitation service had the potential to positively impact access to rehabilitation during the COVID-19 pandemic, for individuals living rurally, and for individuals on wait lists. Call metric analyses revealed that efficiency may be enhanced if call handling time was reduced. AI/ML analyses found that pain was the most frequently-mentioned keyword in clinical notes, suggesting an area for additional telerehabilitation resources to ensure efficiency. © 2023, University Library System, University of Pittsburgh. All rights reserved.

Piloting a Flexible Solicited Diary Study With Marginalized Latina Women During the COVID-19 Pandemic.

Little is known about the experiences of minority stress among Latina women who have sex with both women and men (WSWM), a sexual and gender minority group situated at the intersection of multiple marginalized identities. The current article presents an exploratory study aimed at addressing this knowledge gap. The research utilized a flexible diary-interview method (DIM) to investigate stress-related experiences among Mexican American WSWM residing in an economically disadvantaged community in the U.S. during the third wave of the COVID-19 pandemic. A detailed description of the study is provided, including information on the background, methodology, participants' experiences, and how the project was managed remotely by a virtual research team. Twenty-one participants were asked to maintain a diary for a 6-week period spanning from March to September 2021. They submitted weekly entries in diverse formats (visual, audio, typed, and handwritten) through a user-friendly website or via mail while communicating regularly with researchers over the phone. Following the diarizing period, in-depth semi-structured interviews were conducted to clarify pertinent information within the entries and validate researchers' preliminary interpretations. Out of the initial 21 enrollees, 14 participants stopped diarizing at different stages, and nine completed the entire study. Despite facing challenges exacerbated by the pandemic, participants reported the diary-keeping process as a positive experience that offered an authentic outlet to share parts of their lives they seldom reveal. The implementation of this study highlights two significant methodological insights. Firstly, it emphasizes the value of employing a DIM to explore intersectional narratives. Secondly, it underscores the importance of adopting a flexible and sensitive approach in qualitative health research, particularly when engaging individuals from minoritized groups.

The Impact of the COVID-19 Pandemic on Staff in Violence Against Women Services.

The COVID-19 pandemic has been harmful to survivors of abuse. Less understood is the impact on staff in the violence against women (VAW) service sector. Using interpretive description methodology, we examined staff experiences during the pandemic in Ontario, Canada, and found four core themes: (1) the emotional toll of the work; (2) remote (doesn't) work; (3) work restructuring; (4) efforts to stay well and subthemes nuancing staff experiences in a sector vulnerable to vicarious trauma. This research underscores the need to mitigate experiences of stress, heavy workloads, and guilt for staff in VAW services during crises and provides action-oriented recommendations.

Developing a Conceptual Model with Policy Implications to Better Support Healthcare Providers Working with Older Adults during a Pandemic: An Interpretive Descriptive Qualitative Study.

Although many studies cover the experiences of older adults during the COVID-19 pandemic, few address the daily impact upon health care workers' lives. We used an adapted interpretive description approach to analyze narrative data from 54 practitioners working with older adults, June-October 2021. Stemming from research with those working in the health field, this approach applies knowledge directly back to policy and practice. Analysis of narrative data from open-ended survey questions produced themes and conceptual mapping of practitioners' experiences. Findings illustrate: Advantages and disadvantages of going virtual; challenges of quickly changing policies; concerns about personal and patient safety during the pandemic; needs of the organization and staff; and work-life balance issues. Clearly defining policy-based solutions for delivering services during emergencies offers ways to improve practitioners' and older adults' quality of life.

Towards Detecting Fake News Using Natural Language Understanding and Reasoning in Description Logics

Fighting against misinformation and computational propaganda requires integrated efforts from various domains like law or education, but there is also a need for computational tools. I investigate here how reasoning in Description Logics (DLs) can detect inconsistencies between trusted knowledge and not trusted sources. The proposed method is exemplified on fake news for the new coronavirus. Indeed, in the context of the Covid-19 pandemic, many were quick to spread deceptive information. Since, the not-trusted information comes in natural language (e.g. "Covid-19 affects only the elderly”), the natural language text is automatically converted into DLs using the FRED tool. The resulted knowledge graph formalised in Description Logics is merged with the trusted ontologies on Covid-10. Reasoning in Description Logics is then performed with the Racer reasoner, which is responsable to detect inconsistencies within the ontology. When detecting inconsistencies, a "red flag” is raised to signal possible fake news. The reasoner can provide justifications for the detected inconsistency. This availability of justifications is the main advantage compared to approaches based on machine learning, since the system is able to explain its reasoning steps to a human agent. Hence, the approach is a step towards human-centric AI systems. The main challenge remains to improve the technology which automatically translates text into some formal representation. © 2022, Springer Nature Switzerland AG.

Visual Description of Digital IT Consulting Services Using DITCOS-DN: Proposal and Evaluation of a Graphical Editor

The digital transformation of the IT consulting domain recently gained momentum due to the Covid-19 pandemic. However, the range of IT consulting services that are fully digital is still very limited. Plus, there are no standardized and established methods for describing digital IT consulting services, nor there is any suitable tooling for digital IT consulting service provisioning. The present work aims to reduce this gap by contributing to establishing a well-defined approach to formally describing digital IT consulting services that could possibly be a candidate for standardization. Building upon (i) the ontology DITCOS-O, which provides the semantic basis for our approach, and (ii) the YAML-based description notation DITCOS-DN, which we leverage to describe digital IT consulting service models, we propose a graphical, web-based editor (called DITCOS-ModEd) to simplify service model maintenance. Following a design science based research process, we developed a prototype and empirically evaluated its applicability with the help of IT consultants. This first evaluation allowed us to identify some limitations and to plan specific improvements, both to the underlying artifacts DITCOS-O and DITCOS-DN, as well as to DITCOS-ModEd itself. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Machine Learning and Intelligent Network System based Covid 19 Health Care System

COVID-19 has lately infected a big number of people worldwide. Medical service frameworks are strained as a result of the infection. The emergency unit, which is part of the medical services area, has experienced several challenges as a result of the low data quality offered by existing ICU clinical equipment. The Internet of Things has enhanced the capability for essential information mobility in medical services in the twenty-first century. Nonetheless, many of today's ideal models use IoT innovation to assess patients' well-being. As a result, executives lack understanding regarding the most effective method to apply such innovation to ICU clinical equipment. The IoT Based Paradigm for Medical Equipment Management Systems, a breakthrough IoT-based paradigm for successfully administering clinical hardware in ICUs, is introduced in this study. During the COVID-19 episode, IoT technology is used to boost the data stream between clinical hardware, executive frameworks, and ICUs, enabling the maximum level of openness and reasonableness in clinical equipment redistribution. IoT MEMS conceptual and functional features were painstakingly drawn. Using IoT MEMS expands the capacity and limits of emergency clinics, effectively easing COVID-19. It will also have a substantial impact on the nature of the data and will improve the partners' trust and transparency. © 2022 IEEE.

Experiences of the COVID-19 Lockdown and Telehealth in Aotearoa New Zealand: Lessons and Insights from Mental Health Clinicians.

OBJECTIVE: The COVID-19 pandemic rapidly changed health service delivery and daily life. There is limited research exploring health professional experiences with these changes. This research explores mental health clinicians' experiences over the first COVID-19 lockdown in New Zealand to inform future pandemic responses and improve usual business practices. METHOD: Thirty-three outpatient mental health clinicians in three Aotearoa New Zealand regions took part in semi-structured interviews. Interviews were analysed thematically applying an interpretive description methodology. RESULTS: Three key themes emerged: (1) life in lockdown, (2) collegial support, and (3) maintaining well-being. Clinicians, fearful of contracting COVID-19, struggled to adapt to working from home while maintaining their well-being, due to a lack of resources, inadequate pandemic planning, and poor communication between management and clinicians. They were uncomfortable bringing clients notionally into their own homes, and found it difficult to separate home and work spheres. Maori clinicians reported feeling displaced from their clients and community. CONCLUSION: Rapid changes in service delivery negatively impacted clinician well-being. This impact is not lessened by a return to normal work conditions. Additional support is required to improve clinician work conditions and ensure adequate resourcing and supervision to enable clinicians to work effectively within a pandemic context.

Lessons from professional nursing associations' policy advocacy responses to the COVID-19 pandemic: An interpretive description.

BACKGROUND: Professional nursing associations across jurisdictions engaged in significant policy advocacy during the COVID-19 pandemic to support nurses, the public and health systems. While professional nursing associations have a long history of engaging in policy advocacy, scholars have rarely critically examined this important function. PURPOSE: The purpose of this study was twofold: (a) to examine how professional nursing associations engage in the process of policy advocacy and (b) to develop knowledge specific to policy advocacy in the context of a global pandemic. METHODS: This study was conducted using interpretive description. A total of eight individuals from four professional nursing associations (two local, one national and one international) participated. Data sources included semi-structured interviews conducted between October 2021 and December 2021 and internal and external documents produced by organizations. Data collection and analysis occurred concurrently. Within-case analysis was conducted prior to cross-case comparisons. FINDINGS: Six key themes were developed to illustrate the lessons learned from these organizations including their organization's role in supporting a wide audience (professional nursing associations as a compass); the scope of their policy priorities (bridging the gaps between issues and solutions), the breadth of their advocacy strategies (top down, bottom up and everything in between), the factors influencing their decision-making (looking in and looking out), their evaluation practices (focus on contribution, not attribution) and the importance of capitalizing on windows of opportunity. CONCLUSIONS: This study provides insight into the nature of policy advocacy carried out by professional nursing associations. IMPACT: The findings suggest the need for those leading this important function to think critically about their role in supporting a wide range of audiences, the breadth and depth of their policy priorities and advocacy strategies, the factors that influence their decision-making, and the ways in which their policy advocacy work can be evaluated to move towards greater influence and impact.

An Antiracism Community-Based Participatory Research With Organizations Serving Immigrant and Marginalized Communities, Including Asian Americans and Native Hawaiians/Pacific Islanders in the United States Pacific Northwest: Qualitative Description Study With Key Informants.

BACKGROUND: Asian American (AA) community leaders, Native Hawaiian/Pacific Islander (NH/PI) community leaders, and allies in the United States Pacific Northwest expressed concern that there are families and children from AA communities and NH/PI communities who experience and witness acts of xenophobia and racism. This can cause racial trauma. The long-time practice of aggregating AA and NH/PI data contributes to erasure and makes it challenging to advance health equity, such as allocating resources. According to AAPI Data's long-awaited report in June 2022, there are over 24 million AAs and 1.6 million NHs/PIs in the United States, growing by 40% and 30%, respectively, between 2010 and 2020. Philanthropic investments have not kept up with this substantive increase. The National Academies of Sciences, Engineering, and Medicine emphasized the need for effective partnerships to advance the health and well-being of individuals and communities in antiracism and system-level research. OBJECTIVE: The aim of this community-based participatory research qualitative description study was to identify perceptions and experiences regarding racial discrimination, race-based stress, and racial trauma; intergenerational healing and resiliency; and sharing the body with science from key informants of an academic and community partnership to inform antiracism coalition work. This partnership includes academic researchers and community leaders from community-based organizations and a health care organization serving immigrant and marginalized communities, including AAs and NHs/PIs in the United States Pacific Northwest. METHODS: In total, 10 key informants joined 1 of 2 participatory group discussions via videoconference for 2 hours in 2022. We used a semistructured and open-ended group interview guide. A qualitative participatory group-level assessment was conducted with the key informants and transcribed. Interpretations and meanings of the main points and the main themes were reflected upon, clarified, and verified with the key informants in real time. The field note-based data transcripts were manually coded using conventional content analysis. Reflexivity was used. RESULTS: There were 6 main themes: prejudice plus power in racism definition and working in solidarity to counter lateral oppression/false sense of security, microaggression as multilayers, "not assimilationist by nature" and responding differently to white superiority, intergenerational- and identity-related trauma, what is healing among People of Color and through a lens of resiliency and intergenerational connection and knowledge, and mistrust and fear in the research and health care systems surrounding intentions of the body. CONCLUSIONS: The themes highlight the importance of internal and intergenerational healing from racial trauma and the need for solidarity among communities of color to combat white supremacy and colonization. This work was foundational in an ongoing effort to dismantle racism and uplift the community voice through a cross-sector academic and community partnership to inform antiracism coalition work.

Remuneration, Job Satisfaction, and Performance of Health Workers During the COVID-19 Pandemic Period at the Dr. Soetomo Hospital Surabaya, Indonesia.

Purpose: One of the hospital management issues that has not been studied much during the COVID-19 Pandemic is the relationship between health workers' performance, job satisfaction and remuneration. This study aims to examine the relationship between remuneration, job satisfaction and the employee performance during 2019-2021. Materials and Methods: This study applied an employee satisfaction survey at a General Academic Hospital between 2019-2021. The population and samples were 716 employees. The data collection were based on the personnel database, remuneration database, and the annual Employee Satisfaction Survey Database for the period 2019-2021 at General Academic Hospital of Dr. Soetomo, Surabaya, Indonesia. Results: The results of the correlation test between Employee Satisfaction, Remuneration, and Performance based on employee performance objectives showed an insignificant positive correlation between the remuneration variable and satisfaction based on The Job Itself; very weak significant positive correlation between remuneration variable and Satisfaction based on Pay; a very weak significant positive correlation between the remuneration variable and Satisfaction based on Promotion; very weak significant positive correlation between remuneration variable and satisfaction based on supervision; significant positive correlation between remuneration variable and satisfaction based on coworkers; There is a significant positive correlation between remuneration and performance variables. Conclusion: The correlation between remuneration and employee satisfaction based on the Job Description Index shows that the components of the job itself, and coworkers have a positive but not significant relationship, while the components of pay, promotion, and supervision have a positive and significant relationship. Employees satisfaction with performance achievement have a positive and significant relationship, especially job satisfaction based on pay and supervision, but there is also a positive and insignificant relationship related to job satisfaction based on the job itself, promotion, and co-workers.

Residual Attention Deep SVDD for COVID-19 Diagnosis Using CT Scans

COVID-19 is the common name of the disease caused by the novel coronavirus (2019-nCoV) that appeared in Wuhan, China in 2019. Discovering the infected people is the most important factor in the fight against the disease. The gold-standard test to diagnose COVID-19 is polymerase chain reaction (PCR), but it takes 5–6 h and, in the early stages of infection, may produce false-negative results. Examining Computed Tomography (CT) images to diagnose patients infected with COVID-19 has become an urgent necessity. In this study, we propose a residual attention deep support vector data description SVDD (RADSVDD) approach to diagnose COVID-19. It is a novel approach combining residual attention with deep support vector data description (DSVDD) to classify the CT images. To the best of our knowledge, we are the first to combine residual attention with DSVDD in general, and specifically in the diagnosis of COVID-19. Combining attention with DSVDD naively may cause model collapse. Attention in the proposed RADSVDD guides the network during training and enables quick learning, residual connectivity prevents vanishing gradients. Our approach consists of three models, each model is devoted to recognizing one certain disease and classifying other diseases as anomalies. These models learn in an end-to-end fashion. The proposed approach attained high performance in classifying CT images into intact, COVID-19, and non-COVID-19 pneumonia. To evaluate the proposed approach, we created a dataset from published datasets and had it assessed by an experienced radiologist. The proposed approach achieved high performance, with the normal model attained sensitivity (0.96–0.98), specificity (0.97–0.99), F1-score (0.97–0.98), and area under the receiver operator curve (AUC) 0.99;the COVID-19 model attained sensitivity (0.97–0.98), specificity (0.97–0.99), F1-score (0.97–0.99), and AUC 0.99;and the non-COVID pneumonia model attained sensitivity (0.97–1), specificity (0.98–0.99), F1-score (0.97–0.99), and AUC 0.99. © 2023 Tech Science Press. All rights reserved.

Navigating multiple pandemics: A critical analysis of the impact of COVID-19 policy responses on gender-based violence services

COVID-19 illustrated what governments can do to mobilise against a global threat. Despite the strong governmental response to COVID-19 in Canada, another ‘pandemic', gender-based violence (GBV), has been causing grave harm with generally insufficient policy responses. Using interpretive description methodology, 26 interviews were conducted with shelter staff and 5 focus groups with 24 executive directors (EDs) from GBV service organizations in Ontario, Canada. Five main themes were identified and explored, namely that: (1) there are in fact four pandemics at play;(2) the interplay of pandemics amplified existing systemic weaknesses;(3) the key role of informal partnerships and community support, (4) temporary changes in patterns of funding allocation;and (5) exhaustion as a consequence of addressing multiple and concurrent pandemics. Implications and recommendations for researchers, policy makers, and the GBV sector are discussed.

Qualitative descriptive study during the COVID-19 pandemic on the needs of informal caregivers of Chinese minors who underwent craniopharyngioma surgery.

PURPOSE: To determine the needs of informal caregivers during the long-term health management of minors who have undergone craniopharyngioma surgery. Design and methodology This is a qualitative and descriptive research study. Purposive sampling was used to select participants, and semi-structured interviews were conducted to explore the needs of 21 informal caregivers for postoperative minors. Due to the COVID-19 pandemic, the respondents were provided with the options of online video call or offline one-on-one interviews. Following this, a content analysis method was conducted. RESULTS: Four themes and 14 sub-themes were extracted from the results of the study, including needs for relieving psychological stress (including psychological pressure on both minors and on caregivers); requirement for on-campus assistance (physical activity, eliminating verbal violence in schools, special education needs for child, healthcare services provided by school hospitals); demands for medical help (acquiring medical knowledge, need for medication management, convenience and reliable access to medical services, need for technological development, expectations of multidisciplinary cooperation, the necessity of health review reminders); and the desire for financial aid (charity platform assistance, inclination of government policy). CONCLUSIONS: In China, informal caregivers of young patients with onset craniopharyngioma require both the multidisciplinary cooperation of medical institutions and the multi-departmental cooperation of society. Information and medical technology advancements may benefit families with young patients. Improving community hospitals' medical services and encouraging the practical use of online medical treatment and prescriptions are both necessary in the context of COVID-19. PRACTICE IMPLICATIONS: By identifying the needs of informal caregivers, medical professionals are able to develop care plans and interventions aimed at reducing the burden of care for minors who have undergone craniopharyngioma surgery.

Targeting intracellular Neu1 for coronavirus infection treatment.

There are currently no effective therapies for COVID-19 or antivirals against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and vaccines appear less effective against new SARS-CoV-2 variants; thus, there is an urgent need to understand better the virulence mechanisms of SARS-CoV-2 and the host response to develop therapeutic agents. Herein, we show that host Neu1 regulates coronavirus replication by controlling sialylation on coronavirus nucleocapsid protein. Coronavirus nucleocapsid proteins in COVID-19 patients and in coronavirus HCoV-OC43-infected cells were heavily sialylated; this sialylation controlled the RNA-binding activity and replication of coronavirus. Neu1 overexpression increased HCoV-OC43 replication, whereas Neu1 knockdown reduced HCoV-OC43 replication. Moreover, a newly developed Neu1 inhibitor, Neu5Ac2en-OAcOMe, selectively targeted intracellular sialidase, which dramatically reduced HCoV-OC43 and SARS-CoV-2 replication in vitro and rescued mice from HCoV-OC43 infection-induced death. Our findings suggest Neu1 inhibitors could be used to limit SARS-CoV-2 replication in patients with COVID-19, making Neu1 a potential therapeutic target for COVID-19 and future coronavirus pandemics.

Variable feelings of cohesion, trust, individualism and exclusion and their consequences on Swiss public mental health during the ongoing COVID-19 pandemic

Introduction: The first cases of COVID-19 in Switzerland were related to the Milan cluster in February 2020. Border crossing restrictions were imposed and economic support measures worth 40 billion Swiss francs were announced. By 24th September 2021 Switzerland achieved a fully vaccination rate of 54%, confirmed 836'000 cases and 11'060 deaths. Objective(s): The objective was to describe and analyse the mental health of the general Swiss population under the ongoingCOVID-19 pandemic and it's social changes: including a case description, transgenerational influence and psychosocial treatment opportunities Methods: To answer the research question, I used deepened internet research, population interviews among different age gropus and colloquies with healthcare providers and federal authorities. Result(s): Different psychosocial phenomena lead to the transgenerational influence. Unfortunately, vaccination rate is slowed down by this pandemic's impacts on public mental health. While during the first wave the positive feelings of cohesion and trust dominated, the mood changed afterwards to anxiousness and reactive individualism. Among all generations the fear of infection was shown to be a general booster of anxiety and distress. In fact, Swiss experts perceive the corona crisis as a catalysator for depression and anxiety disorders. Conclusion(s): Specific psychosocial treatment has to address general and individual vulnerability factors. However, staying in touch with family members, pursuing meaningful activities and being physically active can all help to overcome COVID-19 related mental health issues.

Describing Digital IT Consulting Services: The DITCOS Ontology Proposal and its Evaluation

The digital transformation of the consulting sector has recently gained momentum due to the Covid-19 pandemic. In particular, the areas of financial and insurance services are receiving strong attention from digitization researchers. However, the field of IT consulting itself evaded the attention of scientists. Moreover, despite the heavy use of digital technologies such as on-line conferencing and digital collaboration, the actual consulting process itself has hardly changed. This indicates the weaknesses of IT consulting as a field in establishing true digital business models and consulting service delivery processes. The present paper makes a twofold contribution to the domain of digitization of the IT consulting domain. First, it introduces the DITCOS-O ontology for semantic description of digital IT consulting services. Second, the DITCOS-DN description notation is derived from DITCOS-O, as a new approach to ontology-based definition of domain specific languages. Then, DITCOS-DN is used to describe different real-world services. The result is the analysis of the coverage of real-world service and the comprehensibility of their digitally described service model representations with the help of IT consulting practitioners. © 2022 IEEE.

Residual Attention Deep SVDD for COVID-19 Diagnosis Using CT Scans

COVID-19 is the common name of the disease caused by the novel coronavirus (2019-nCoV) that appeared in Wuhan, China in 2019. Discovering the infected people is the most important factor in the fight against the disease. The gold-standard test to diagnose COVID-19 is polymerase chain reaction (PCR), but it takes 5–6 h and, in the early stages of infection, may produce false-negative results. Examining Computed Tomography (CT) images to diagnose patients infected with COVID-19 has become an urgent necessity. In this study, we propose a residual attention deep support vector data description SVDD (RADSVDD) approach to diagnose COVID-19. It is a novel approach combining residual attention with deep support vector data description (DSVDD) to classify the CT images. To the best of our knowledge, we are the first to combine residual attention with DSVDD in general, and specifically in the diagnosis of COVID-19. Combining attention with DSVDD naively may cause model collapse. Attention in the proposed RADSVDD guides the network during training and enables quick learning, residual connectivity prevents vanishing gradients. Our approach consists of three models, each model is devoted to recognizing one certain disease and classifying other diseases as anomalies. These models learn in an end-to-end fashion. The proposed approach attained high performance in classifying CT images into intact, COVID-19, and non-COVID-19 pneumonia. To evaluate the proposed approach, we created a dataset from published datasets and had it assessed by an experienced radiologist. The proposed approach achieved high performance, with the normal model attained sensitivity (0.96–0.98), specificity (0.97–0.99), F1-score (0.97–0.98), and area under the receiver operator curve (AUC) 0.99;the COVID-19 model attained sensitivity (0.97–0.98), specificity (0.97–0.99), F1-score (0.97–0.99), and AUC 0.99;and the non-COVID pneumonia model attained sensitivity (0.97–1), specificity (0.98–0.99), F1-score (0.97–0.99), and AUC 0.99. © 2023 Tech Science Press. All rights reserved.

ADOPTION OF TELECOMMUTING IN THE BANKING INDUSTRY: A TECHNOLOGY ACCEPTANCE MODEL APPROACH

Aim/Purpose Currently, the world faces unprecedented challenges due to COVID-19, particu-larly concerning individuals' health and livelihood and organizations and indus-trial performance. Indeed, the pandemic has caused rapid intensifying socio-economic effects. For instance, organizations are shifting from traditional work-ing patterns toward telecommuting. By adopting remote working, organizations might mitigate the impact of COVID-19 on their workforce, explicitly concern-ing their safety, wellbeing, mobility, work-life balance, and self-efficiency. From this perceptive, this study examines the factors that influence employees' behav-ioral intention to adopt telecommuting in the banking industry. Background The study's relevance stems from the fact that telecommuting and its benefits have been assumed rather than demonstrated in the banking sector. However, the pandemic has driven the implementation of remote working, thereby reveal-ing possible advantages of working from home in the banking industry. The study investigated the effect of COVID-19 in driving organizations to shift from traditional working patterns toward telecommuting. Thereby, the study in-vestigates the banking sector employees' behavioral intention to adopt telecom-muting. Methodology The study employed a survey-based questionnaire, which entails gathering data from employees of twelve banks in Jordan, as the banking sector in Jordan was the first to transform from traditional working to telecommuting. The sample for this research was 675 respondents;convenience sampling was employed as a sampling technique. Subsequently, the data were analyzed with the partial least square structural equation modeling (PLS-SEM) to statistically test the research model. Contribution Firstly, this study provides a deep examination and understanding of facilitators of telecommuting in a single comprehensive model. Secondly, the study pro-vides a deeper insight into the factors affecting behavioral intention towards tel-ecommuting from the employees' perspective in the banking sector. Finally, this study is the first to examine telecommuting in the emerging market of Jordan. Thereby, this study provides critical recommendations for managers to facilitate the implementation of telecommuting. Findings Using the Technology Acceptance Model (TAM), this study highlights signifi-cant relationships between telecommuting systems, quality, organizational sup-port, and the perceived usefulness and ease of use in telecommuting. Employ-ees who perceive telecommuting systems to be easy and receive supervision and training for using these systems are likely to adopt this work scheme. The results present critical theoretical and managerial implications regarding employees' be-havioral intentions toward telecommuting. Recommendations for Practitioners This study suggests the importance of work-life balance for employees when telecommuting. Working from home while managing household duties can cre-ate complications for employees, particularly parents. Therefore, flexibility in terms of working hours is needed to increase employees' acceptance of tele-commuting as they will have more control over their life. These increase em-ployees' perceived self-efficacy with telecommuting, which smooths the transi-tion toward remote working in the future. In addition, training will allow em-ployees to solve technical issues that can arise from using online systems. Recommendations for Researchers This study focused on the context of the banking sector. The sensitivity of data and transactions in this sector may influence employers' and employees' willing-ness to work remotely. In addition, the job descriptions of employees in banks moderate specific factors outlined in this model, including work-life balance. For instance, executive managers may have a higher overload in banks in con-trast to front-line employees. Thus, future studies should explore different con-texts, including manufacturing and consultation, to understand the industry's ef-fect on remote working. Similarly, future researc should concentrate on the in-fluence of job descriptions on employees' intentions toward telecommuting. Impact on Society The COVID-19 pandemic created a sudden shift towards telecommuting, which made employees struggle to adopt new work schemes. Therefore, managers had to provide training for their employees to be well prepared and increase their acceptance of telecommuting. Furthermore, telecommuting has a positive effect on work-life balance, it provides employees with the flexibility to organize their daily schedule into more activities. Along the same line, the study highlighted the correlation between work-life balance and telecommuting. Such a relation-ship provides further evidence for the need to understand employees' lifestyles in facilitating the adoption of telecommuting. Moreover, the study extends the stream of literature by outlining critical factors affecting employees' acceptance of telecommuting. Future Research Future studies should explore different contexts, including manufacturing and consultation, to understand the industry's effect on remote working. Similarly, future research should concentrate on the influence of job descriptions on em-ployees' intentions toward telecommuting. Furthermore, the research team con-ducted the study by surveying 12 banks. Future research recommends surveying the whole banking industry to add more validation to the model. © 2022 Informing Science Institute. All rights reserved.