This study aimed at exploring and comparing the vulnerability to COVID-19, demographic variables and perceived stress of frontline nurses. This study employed a quantitative comparative-correlational approach. Using the snowball sampling technique, we conducted this study involving 176 frontline nurses from hospitals of the Hail region, KSA. The frontline nurses showed high perceived infectability (x = 4.36) and germ aversion (x = 5.65) but were moderately stressed (19.19). Of the examined variables, only years of experience resulted in significant differences in germ aversion (F [3] = 8.980, p < 0.01). There was no statistically significant difference in perceived infectability and stress. Perceived infectability (r = −0.152, p < 0.05) and germ aversion (r = 0.007, p > 0.05) were negatively correlated to perceived stress. In this study, frontline nurses perceived moderate to high stress vulnerability to COVID-19. There were significant differences in germ aversion based on the duration of experience. It is noteworthy that perceived vulnerability to COVID-19 did not impact stress. Paying attention to concerns of nurses can potentially improve preventive practices and positive behaviours in combating the pandemic.

Background: A continuous and high frequency of alarms from monitoring and treatment devices can lead to nurses’ sensory exhaustion and alarm fatigue in critical care settings. Aim: The purpose of this study was to evaluate the level of alarm fatigue and determine the relationship between nurses’ sociodemographic and work-related factors and the level of alarm fatigue in critical care settings in Hail City, Saudi Arabia. Methods: Between May and July 2023, 298 nurses who worked in the emergency, intensive care, and critical care units of all the public hospitals in Hail City participated in a cross-sectional survey. Sociodemographic and work-related sheet and the Nurses’ Alarm Fatigue Questionnaire were used to collect data. Results: The total mean score of alarm fatigue was 26.38± 8.30 out of 44. The highest score was observed for the item “I pay more attention to the alarms in certain”, while the lowest score were observed for the items “I turn off the alarms at the beginning of every shift” with mean scores of 2.51 and 1.61, respectively. Nurses who were males, older than 30 years and Saudi citizens had significantly higher mean scores of alarm fatigue than their counterparts. In addition, significantly higher mean scores of alarm fatigue were noticed for nurses experienced for 10 years or more and who had regular morning shifts. Multiple linear regression showed that male (p=0.014), age (p=0.012), and Saudi nationality (p < 0.029) were the independent factors affecting the level of fatigue alarm among nurses. Conclusion: Nurses working in critical care settings at hospitals in Hail city are exposed to average levels of alarm fatigue, which can be influenced by sex, age, nationality, and experience of nurses. Therefore, it is imperative to manage alarm fatigue in critical care units by considering work-related and personality-related factors to ensure patient safety.

This study investigates the differences between nursing students' surface and deep approaches to learning across their demographic profiles. Further, this study explores the association between the participants’ ages, year levels, and learning approaches. From December 2019 to February 2020, we used a quantitative-comparative- correlational study design at the University of Hail KSA. A survey-based questionnaire was used to collect data from 349 randomly selected nursing students. One-way analysis of variance (ANOVA) and t-tests were used to examine the difference between the surface learning and the deep learning approaches of the participants across their profiles. Pearson's correlation coefficient was used to determine the relationship between participants' learning approaches, ages, and year levels. A significant difference in the deep learning approach was noted for age (F (3, 345) = 35.71; p = 0.01] and program type (bridging/regular) [t (347) = −8.81, p = 0.01]. A moderately positive significant correlation was found between age and both deep (r = 0.47, n = 349, p = 0.01) and surface (r = 0.45, n = 349, p = 0.01) learning approaches. This study shows that nursing students use both surface and deep learning approaches alike and are able to capitalise on either learning style. Both learning approaches are important and valuable in nursing education. The age of the student is correlated with the learning approach. Older students have higher scores for both deep and surface learning approaches. Academia must develop creative learning environments that can encourage students to use both approaches and to advance the transition to deep learning.