Purpose: Poor sleep and depressive symptoms are two negative effects of night shift work on physical and mental health. This study evaluated the correlation between sleep quality and depression symptoms among nurses in Saudi Arabia. Specifically, we assessed depressive symptoms and sleep quality observed among nurses who worked night shifts and compared the outcomes with those who worked exclusively day shifts in hospital settings. Patients and Methods: A total of 191 participants (55.5% men, 44.5% women) participated. The response rate was 63.6%. The hospital anxiety and depression scale (HADS) and Pittsburgh Sleep Quality Index (PSQI) were used to assess depression score and sleep quality, respectively. Results: Nurses who worked night shifts had substantially higher PSQI ratings (p< 0.05) than those who worked day shifts. In addition, there was a clear relationship between the HADS and PSQI scores. According to the binary logistic regression, longer working hours and inadequate sleep were both independently linked to depressive symptoms among nurses. Conclusion: Poor sleep quality brought on by night shifts may explain why Saudi nurses who work night shifts experience higher rates of depression than those who work day shifts only.

Compassion satisfaction, the pleasure gained from assisting others in their recovery from trauma, can help reduce the effects of burnout and secondary traumatic stress. As such, nurses’ job satisfaction can be increased by increasing compassion satisfaction and decreasing compassion fatigue. This study examined the incidence of compassion fatigue and other influencing variables, such as compassion satisfaction, burnout, and secondary traumatic stress, among Saudi nurses. This was a cross-sectional study using convenience sampling. Participants comprised 177 registered nurses from various nursing departments. Data collection included the Professional Quality of Life Scale based on lifestyle, demographic details, and occupation-related questions. The averages of scores for the variables, compassion satisfaction, burnout, and secondary traumatic stress, were recorded (37.1 ± 7.4, 25.7 ± 7.5, and 26.7 ± 6.4). Participants aged 36 or older comprised a negative factor for compassion satisfaction, while years of nursing experience and higher job satisfaction were favorable predictors. Together, these three variables accounted for 30.3% of the overall variation. Low job satisfaction and poor sleep negatively affected burnout, accounting for 39.8% of the total variance. The results offer insights into identifying the risks of compassion fatigue in nurses and help design strategies to address burnout and secondary traumatic stress while enhancing their compassion satisfaction levels.

Objectives: Promoting resilience and embracing healthy coping strategies can effectively assist nursing students in managing stress and enhancing their welfare. Nonetheless, a comprehensive understanding of the factors influencing their well-being and resilience, pivotal for both academic accomplishments and future career longevity, remains incomplete. Methods: A cross-sectional descriptive correlational design was adopted for this study. Participants comprised students enrolled in pre-registration nursing programs at both undergraduate and graduate levels. The World Health Organization-5 Well-Being Index and the 10-item Connor-Davidson Resilience Scale were utilized to assess psychological well-being and resilience, respectively. Results: The study involved 175 university nursing students selected through convenience sampling. On the 10-item Connor-Davidson Resilience Scale, the average score was 25.5, with undergraduate and graduate students scoring an average of 25.4 and 26.3, respectively. Nevertheless, the two groups had no statistically significant difference ( p = 0.526). Regarding perceived well-being, the average World Health Organization-5 score was 16.1, with no noticeable distinction between undergraduates and postgraduates ( p = 0.858). Notably, bivariate analysis revealed a moderate positive correlation between self-reported resilience and perceived well-being ( rp = 0.281, p = 0.001). Moreover, senior students exhibited significantly higher scores on the perceived well-being scale than junior students (17.0 vs 15.1, p = 0.010). Multivariable regression analysis also identified that self-reported resilience represents a consistent means of predicting perceived well-being (regression coefficient B = 0.22, p < 0.001). Conclusions: The outcomes indicate that university-based nursing students who exhibit higher levels of resilience have more positive perceptions of their well-being. Moreover, postgraduate students exhibit more significant resilience levels than undergraduate students.

Background: The integration of artificial intelligence (AI) into mental health care is reshaping psychological support systems, particularly for digitally literate populations such as nursing students. Given the high prevalence of anxiety and depression in this group, understanding their perceptions of AI-driven mental health support is critical for effective implementation. Objectives: to evaluate nursing students’ perceptions toward AI-driven mental health support and examine its relationship with anxiety, depression, and their attitudes to seeking professional psychological help. Methods: A cross-sectional survey was conducted among 176 undergraduate nursing students in northern Jordan. Results: Students reported moderately positive perceptions toward AI-driven mental health support (mean score: 36.70 ± 4.80). Multiple linear regression revealed that prior use of AI tools (β = 0.44, p < 0.0001), positive help-seeking attitudes (β = 0.41, p < 0.0001), and higher levels of psychological distress encompassing both anxiety (β = 0.29, p = 0.005) and depression (β = 0.24, p = 0.007) significantly predicted more positive perceptions. Daily AI usage was not a significant predictor (β = 0.15, p = 0.174). Logistic regression analysis further indicated that psychological distress, reflected by elevated anxiety (OR = 1.42, p = 0.002) and depression scores (OR = 1.32, p = 0.003), along with stronger help-seeking attitudes (OR = 1.35, p = 0.011), significantly increased the likelihood of using AI-based mental health support. Conclusions: AI-driven mental health tools hold promises as adjuncts to traditional counseling, particularly for nursing students experiencing psychological distress. Despite growing acceptance, concerns regarding data privacy, bias, and lack of human empathy remain. Ethical integration and blended care models are essential for effective mental health support.

Purpose: The present study aims to evaluate compassion satisfaction (CS), compassion fatigue (CF), and burnout levels in a population of nurses employed at medical city in Riyadh City, Saudi Arabia. Patients and Methods: A self-report survey was employed to gather data from 300 nurses at the selected medical city in Riyadh. The survey incorporated a demographic inquiry along with the utilization of the Professional Quality of Life Scale version 5 (ProQOL 5). The ProQOL scale is one of the most widely used measures of CS, CF, and burnout. The ProQOL scale assesses multiple domains of work experiences (ie CS, CF, and burnout). This survey was disseminated through email channels, and it garnered participation from 177 nurses, culminating in a response rate of 59%. Results: The study’s findings reveal that nurses displayed average mean levels of CS, CF, and burnout. Interestingly, the participants aged 18– 56 reported higher levels of burnout, particularly those in the age groups of 18– 25, 26– 35, and 36– 56. Moreover, those with under 10 years’ experience exhibited higher degrees of burnout and less CS compared to their more experienced counterparts. Additionally, nurses with professional qualifications demonstrated better scores on CS, CF, and burnout compared to those without such qualifications. Conclusion: The experience of CF and CS among nurses appears to be influenced by multiple variables, such as length of experience, age, and professional qualifications. Nurses in certain age groups and with less experience are more prone to experiencing burnout, while having professional qualifications seems to protect against adverse outcomes to some extent.

Depression affects approximately 350 million individuals globally and is the leading cause of disability. Depression among nursing students is an ongoing issue, yet little is known about the relationship between depression and its risk factors among nursing students in Saudi Arabia. The purpose of this study was to determine the prevalence of depression among a cohort of Saudi nursing students and to explore the risk factors associated with depression in this group. A cross-sectional design was employed for this study, which was conducted by the nursing faculty at King Saud University in Riyadh, Saudi Arabia. The researcher sampled 330 nursing students, with 252 students (a 76.3% response rate) randomly selected by the academic advising unit in the nursing college between January and February 2023. The participants completed an online survey based on the Arabic version of the Center for Epidemiologic Studies Depression Scale. The data were analyzed using univariate analysis and backward multi-variable logistic regression. The findings revealed that 65.1% of the participants scored 16 or above on the depression scale, indicating high levels of depressive symptoms. Univariate analysis identified several significant risk factors for depression, including sex (OR, 0.29; 95% CI, 0.16–0.51; p < 0.001), academic pressure (OR, 5.87; 95% CI, 2.04–16.84; p < 0.001), interpersonal relationships (evaluated by balance and harmony in thoughts, emotions, behavior, and interactions with others; categorized as good/fair or poor), and the relationship with the father, which were strongly associated with the presence of depression symptoms. Backward multi-variable logistic regression analysis further revealed that being male, experiencing reduced academic pressure, having stronger father–son relationships, and maintaining positive interpersonal relationships were significantly associated with decreased levels of depression (ORs ranged from 0.25 to 3.94). These findings highlight the need for family and school-based prevention interventions to help nursing students in college avoid depression.