The Impact of the Working Hours Among Malaysian Nurses on Their Ill-Being, Intention to Leave, and the Perceived Quality of Care: A Cross-Sectional Study During the COVID-19 Pandemic.

Purpose: This study explores the effect of working duration on nurses and their ill-being (ie, anxiety, depression, fatigue, and sleepiness), intention to leave, and the quality of nursing care. Methods: A questionnaire survey was employed for a convenience sample of 400 nurses at Malacca General Hospital in Malaysia who voluntarily participated in this cross-sectional study. The Statistical Package for the Social Sciences (SPSS) was used to treat and analyze the data. Descriptive statistics were generated, and Post Hoc analyses and ANOVA tests were conducted. Results: Findings indicated that working hours duration was significantly associated with nurses' anxiety (F (4, 394) = 10.362, p <0.001), depression (F (4, 395) = 23.041, p< 0.001), fatigue (F (4, 395) = 24.232, p< 0.001), sleepiness (F (4, 395) = 4.324, p < 0.002), quality of nursing care (F (4, 395) = 16.21, p <0.001) and intention leave their job, (F (4, 395) = 50.29, p <0.001). The results also revealed that working more than 14 hours was negatively associated with their perceived quality of nursing care and positively associated with their perceived ill-being and intention to leave. Conclusion: Shift length is an important issue, and nursing managers must consider shift length as it can adversely correlate with the nurses' perceptions of work and life.

Exposure Detection Applications Acceptance: The Case of COVID-19.

The pandemic's context is rife with numerous dangerous threats and high fear levels, influencing human decision-making. Such characteristics are identified by investigating the acceptance of exposure detection apps from the technology acceptance model (TAM) perspective. This study purposed a model to investigate protection technology acceptance, specifically exposure detection apps in the context of COVID-19. Quantitative study approach and a cross-section design targeted 586 participants from Saudi Arabia. As the study model is complex, the study hypotheses were analysed using the structural equation modelling-partial least squares (SEM-PLS3) approach. The findings support the entire model hypothesis except the link between social media awareness and exposure detection apps' intention. Mediation of COVID-19 anxiety and influence was confirmed as well. The current paper contributes to the technologies acceptance domain by developing a context-driven model comprising the major pandemic characteristics that lead to various patterns of technology acceptance. This study also fills the literature gap regarding mediating effects of social influence and COVID-19 anxiety in the relationship between trust in government and exposure detection apps implementation, and between COVID-19 anxiety and exposure detection apps implementation, respectively. The results may assist government agencies, health policymakers, and health organisations in the wide world and specifically Saudi Arabia, in their attempts to contain the COVID-19 pandemic spread.

Remotely Monitoring COVID-19 Patient Health Condition Using Metaheuristics Convolute Networks from IoT-Based Wearable Device Health Data.

Today, COVID-19-patient health monitoring and management are major public health challenges for technologies. This research monitored COVID-19 patients by using the Internet of Things. IoT-based collected real-time GPS helps alert the patient automatically to reduce risk factors. Wearable IoT devices are attached to the human body, interconnected with edge nodes, to investigate data for making health-condition decisions. This system uses the wearable IoT sensor, cloud, and web layers to explore the patient's health condition remotely. Every layer has specific functionality in the COVID-19 symptoms' monitoring process. The first layer collects the patient health information, which is transferred to the second layer that stores that data in the cloud. The network examines health data and alerts the patients, thus helping users take immediate actions. Finally, the web layer notifies family members to take appropriate steps. This optimized deep-learning model allows for the management and monitoring for further analysis.

The Role of Accounting Information System and Knowledge Management to Enhancing Organizational Performance in Iraqi SMEs

Small and Medium Enterprises (SMEs) in Iraq have experienced low performance due to the limited usage of accounting information systems (AIS) and the inability to exploit knowledge of management capabilities (KMC). These deficiencies have led to competitive pressures in the marketplace that have adversely affected their sales and production. This study investigates the role of AIS in terms of operation support, knowledge support, regulatory support, and the role of KMC, including knowledge acquisition, knowledge transfer, and knowledge utilized to enhance organizational performance in Iraqi SMEs. The target population was managers and owners in SMEs using AIS in Iraq’s cities. A non-probability purposive sampling technique was used to collect the data, and self-administered printed questionnaires were distributed to the SME managers and owners;236 questionnaires were used for analysis. Partial least squares was used to examine the role of AIS and the meditation of KMC through second-order analysis. The results showed that AIS and KMC have a positive and significant role in enhancing organizational performance. The study also found that KMC partially mediated between AIS and organizational performance. The findings show that managers and owners of SMEs should focus on AIS and pay more attention to KMC to improve organizational performance.

Risk of Fear and Anxiety in Utilising Health App Surveillance Due to COVID-19: Gender Differences Analysis

Although technology trends and acceptance have been considered crucial topics, limited research has examined stress-specific factors such as health anxiety in the context of the COVID-19 pandemic based on people’s attitudes toward a mobile health app using the Technology Acceptance Model (TAM). Accordingly, this study primarily highlights the psychological determinants stemming from the COVID-19 pandemic that affect the usage of a mobile health app. The study followed a cross-sectional design and adopted a snowball sampling technique to collect the data. The findings showed a significant association between perceived usefulness, perceived ease of use, and event-related fear and Tabaud App intention. The relationships between Tabaud App intention and COVID-19 anxiety on Tabaud App usage were also revealed. The study found a significant association between perceived ease of use and perceived usefulness. Additionally, the multi-group analysis showed that only two paths related to Tabaud App intention, perceived ease of use and perceived usefulness, differed significantly between males and females. Additionally, women experienced anxiety disorders more than men. The study contributes to the previous knowledge on the field by examining the psychological determinants resulting from the COVID-19 pandemic that influence using a mobile health app, namely, event-related fear and COVID-19 anxiety. The study results may help governments, health policymakers, and health organisations in Saudi Arabia contain the spread of the COVID-19 pandemic.

A Public Safety Compliance Model of Safety Behaviors in the Age of the COVID-19 Pandemic.

The outbreak of COVID-19 has placed a heavy burden on society, threatening the future of the entire world as the pandemic has hit health systems and economic sectors hard. Where time moves fast, continuing curfews and lockdown is impossible. This paper assembles three main safety behaviors, social distancing, wearing a facemask, and hygiene in one model (PSC Triangle) to be practiced by the public. Integrating public safety compliance with these behaviors is the main recommendation to slow the spread of COVID-19. Although some concerns and challenges face these practices, the shifting of public behaviors to be more safety-centered is appropriate and available as an urgent desire exists to return to normal life on the one hand and the medical effort to find effective cure or vaccine that has not yet succeeded on the other hand. Recommendations to enhance public safety compliance are provided.