This research study examines academic self-perceptions and course satisfaction among university students and associated factors during virtual classes. A cross-sectional online survey of (n = 328) undergraduate and postgraduate Saudi students who took virtual classes during the second semester of the academic year 2019–2020 and the first semester of the academic year 2020–2021 during the coronavirus disease 2019 (COVID-19) pandemic. The findings demonstrated students’ scores on negative academic self-perceptions (mean (M) = 9.84; standard deviation (S.D.) = 3.09) are significantly higher in comparison to positive academic self-perceptions (M = 7.71; S.D. = 2.46) and the difference was statistically significant, t(327) = 3.69, p < 0.001. The analysis demonstrated that mean differences were significant across ‘year of study’, ‘field of study’, ‘CGPA’ (cumulative grade points average), ‘employment status’, ‘on-site work’ and ‘being a parent of young child’ (p < 0.01). Correlation analysis shows a linear positive association between perceptions of workload and low technical support with negative academic self-perceptions (p < 0.001) and an inverse relationship with positive academic self-perceptions (p < 0.001). The multiple regression analysis demonstrated that the predictor variables in the model (perceptions of workload and technical support) explain 62% variance in negative academic self-perceptions and 41% variance in positive academic self-perceptions. Furthermore, the analysis demonstrated that positive academic self-perceptions bring a 32% variance in course satisfaction. These findings underscore the importance of balancing workload during online studies in higher education and provision of adequate technical support to reduce the negative academic self-perceptions which are associated with lower levels of course satisfaction. Students’ academic self-perceptions and course satisfaction during virtual studies are important factors to retain students’ motivation in learning and academic performance.

Patient safety concept has achieved more attention from healthcare organizations to improve the safety culture. This study aimed to investigate patient safety attitudes among doctors and nurses and explore associations between workload, adverse events, and experience with patient safety attitudes. The study used a descriptive cross-sectional design and the Turkish version of the Safety Attitudes Questionnaire. Participants included 73 doctors and 246 nurses working in two private hospitals in Northern Cyprus. The participants had negative perceptions in all patient safety domains. The work conditions domain received the highest positive perception rate, and the safety climate domain received the lowest perception rate among the participants. Nurses showed a higher positive perception than doctors regarding job satisfaction, stress recognition, and perceptions of management domains. There were statistically significant differences between experiences, workloads, adverse events, and total mean scores of patient safety attitudes. Policymakers and directors can improve the quality of care of patients and patient safety by boosting the decision-making of health care providers on several domains of safety attitudes. Patient safety needs to be improved in hospitals through in-service education, management support, and institutional regulations.

Background: The tobacco use epidemic is one of the major global public health challenges and causes > 7 million deaths each year, including ~70 000 Saudis who die from smoking-related diseases. Aims: To present recent government initiatives in Saudi Arabia that have been designed to combat tobacco use in the country. Methods: This was a review based on secondary data sources such as published reports, articles in newspapers, and research studies published in various journals. Results: We present initiatives taken from June 2017 to April 2019 by the Saudi government to combat tobacco use, including value-added tax on tobacco, antismoking campaigns, antismoking clinics, mobile apps and other initiatives. Conclusion: The study suggests that the government should evaluate the impact of these initiatives on tobacco control in Saudi Arabia.

This study aims to explore the potential mediation role of person-centeredness between the effects of the work environment and nurse reported quality and patient safety. A quantitative cross-sectional survey collected data from 1055 nurses, working in medical and surgical units, in twelve Malaysian private hospitals. The data collection used structured questionnaires. The Hayes macro explored the mediation effect of person-centeredness between the associations of work environment dimensions and care outcomes, controlling nurses’ demographics and practice characteristics. A total of 652 nurses responded completely to the survey (61.8% response rate). About 47.7% of nurses worked 7-h shifts, and 37.0% were assigned more than 15 patients. Higher workload was associated with unfavorable outcomes. Nurses working in 12-h shifts reported a lower work environment rating (3.46 ± 0.41, p < 0.01) and person-centered care (3.55 ± 0.35, p < 0.01). Nurses assigned to more than 15 patients were less likely to report a favorable practice environment (3.53 ± 0.41, p < 0.05), perceived lower person-centered care (3.61 ± 0.36, p < 0.01), and rated lower patient safety (3.54 ± 0.62, p < 0.05). Person-centeredness mediates the effect of nurse work environment dimensions on quality and patient safety. Medical and surgical nurses, working in a healthy environment, had a high level of person-centeredness, which, in turn, positively affected the reported outcomes. The function of person-centeredness was to complement the effects of the nurse work environment on care outcomes. Improving the nurse work environment (task-oriented) with a high level of person-centeredness (patient-oriented) was a mechanism through which future initiatives could improve nursing care and prevent patient harm.

Background Patient safety and quality are concerns of healthcare systems, and several reforms and efforts have focused on this concern. Person-centeredness and nurse work environment are key elements for providing high quality and safe patient care, as structural and process factors. Limited existing studies suggest a mediation role of person-centeredness from a nursing perspective. Accordingly, this study aim to explore the potential mediation role of person-centeredness between the effects of the work environment and nurse reported quality and patient safety. Methods A quantitative cross-sectional survey collected data from 1,055 nurses working in medical and surgical units in twelve Malaysian private hospitals. The data collection used structured questionnaires. The Hayes macro explored the mediation effect of person-centeredness between the associations of work environment dimensions and care outcomes, controlling nurses’ demographics and practice characteristics. Results A total of 652 nurses responded completely to the survey (61.8% response rate). About 47.7% of nurses worked 7-hour shifts, and 37.0% were assigned more than 15 patients. Higher workload was associated with unfavorable outcomes. Nurses working in 12-hour shifts reported a lower work environment rating (3.46 ± 0.41, p < 0.01) and person-centered care (3.55 ± 0.35, p < 0.01). Nurses assigned for more than 15 patients were less likely to report a favorable practice environment (3.53 ± 0.41, p < 0.05), perceived lower person-centered care (3.61 ± 0.36, p < 0.01), and rated lower patient safety (3.54 ± 0.62, p < 0.05). Person-centeredness mediates the effect of nurse work environment dimensions on quality and patient safety. Conclusion Medical and surgical nurses working in a healthy environment had a high level of person-centeredness, which is, in turn, positively affected the reported outcomes. The function of person-centeredness was to complement the effects of the nurse work environment on care outcomes. Improving the nurse work environment (task-oriented) with a high level of person-centeredness (patient-oriented) was a mechanism through which future initiatives could improve nursing care and preventing patient harm.

The COVID-19 pandemic has greatly affected the personal and academic lives of undergraduates in Saudi Arabia. Although studies have suggested that COVID-19 increased the prevalence of psychological health problems among undergraduates, the associations between the risk of depression and safety practices and the influence of gender on these associations have not been studied in detail. A cross-sectional online survey was conducted among preparatory-year undergraduates in a large public university in Saudi Arabia during the outbreak. Depressive symptoms were assessed using the Center for Epidemiological Studies Depression (CES-D) Scale, and the practice of eight precautionary behaviors was also assessed. Data analysis was performed using the chi-square test, multiple linear regression and Spearman’s correlation coefficient. In total, 3044 undergraduates were surveyed. The mean age was 18.6 years (SD = 0.84), and 61.9% (n = 1883) of the participants were female. Overall, 47.7% of the participants reported having elevated depressive symptoms. Overall mean values of CES-D scores were higher among female undergraduates than that of male undergraduates (18.08 versus 15.56, p < 0.01). There were inverse and weak but significant relationships between the CES-D score and frequent cleaning of hands (male: r = −0.116, p < 0.01; female: r = −0.098, p < 0.01), wearing a mask when going out (male: r = −0.172, p < 0.01; female: r = −0.135, p < 0.01), keeping social distance (male: r = −0.117, p < 0.01; female: r = −0.147, p < 0.01), and covering the nose when sneezing (male: r = −0.202, p < 0.01; female: r = −0.115, p < 0.01). Regression analysis indicated that adherence to precautionary measures was a strong predictor of reduction of depressive symptoms in the target population. Male gender was also found to be an independent predictor of reduction of depressive symptoms. Depressive symptoms were highly prevalent in this target group, and female undergraduates seemed to be more vulnerable to developing such symptoms. Results also indicated that female undergraduates were more likely to implement the protective measures for COVID-19. The promotion of precautionary measures seems to be effective in reducing distress in this target population, but further research is needed to confirm our assertions.

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 COVID-19 disease has spread worldwide since 2020, causing a high number of deaths as well as infections, and impacting economic, social and health systems. Understanding its dynamics may facilitate a better understanding of its behavior, reducing the impact of similar diseases in the future. Classical modeling techniques have failed in predicting the behavior of this disease, since they have been unable to capture hidden features in the data collected about the disease. The present research benefits from the high capacity of modern computers and new trends in artificial intelligence (AI), specifically three deep learning (DL) neural networks: recurrent neural network (RNN), gated recurrent unit (GRU), and long short-term memory (LSTM). We thus modelled daily new infections of COVID-19 in four countries (Saudi Arabia, Egypt, Italy, and India) that vary in their climates, cultures, populations, and health systems. The results show that a simple-structure RNN algorithm is better at predicting daily new infections and that DL techniques have promising potential in disease modeling and can be used efficiently even in the case of limited datasets.