The validation of the Arabic version of the resilience scale 14 (RS-14).

BACKGROUND/OBJECTIVES: Nurses in Lebanon are facing multiple crises and the severity of the situation calls for an empirical examination of their resilience status. Evidence indicates that resilience can buffer the negative effect of workplace stressors on nurses and is associated with favorable patient outcomes. The objective of this study was to test the psychometric properties of the Arabic Resilience Scale-14 that was utilized to measure resilience among Lebanese nurses, METHODS: Data was collected from nurses working in health care centers using a cross-sectional survey design. We estimated the confirmatory factor analysis using the Diagonally Weighted least Squares. Fit indices for the confirmatory factor analysis model included Model chi-square, root-mean squared error of approximation and Standardized Root Mean Square Residual. Statistical significance was set at p < 0.05. RESULTS: 1,488 nurses were included in the analysis. The squared multiple correlations values ranged from 0.60 to 0.97 thus supporting the construct validity of the originally hypothesized five factor model (self-reliance, purpose, equanimity, perseverance, and authenticity). CONCLUSIONS: The Arabic version of the Resilience Scale 14 tool is considered a valid tool for measuring resilience in any situation involving Arabic speaking nurses.

Exploring the effects of e-learning readiness and psychological distress on graduate students' e-learning satisfaction during the COVID-19 pandemic: A descriptive study from Lebanon.

The COVID-19 pandemic triggered a substantial surge in e-learning adoption, impacting students' lives and well-being. This study investigates factors influencing student satisfaction with e-learning in Lebanon during the pandemic, with a focus on disparities between public and private education sectors. Utilizing an online survey and convenience sampling techniques, we gathered data from 307 graduate students representing both sectors. Employing regression-based methods, our study identifies instructor readiness as the most influential factor affecting e-learning satisfaction (ß = 0.483, p < 0.001). Moreover, it reveals that heightened psychological distress diminishes student satisfaction (ß = -0.189, p = 0.013). Additionally, students exhibit varying learning preferences, with a clear preference for hybrid (66 %) and face-to-face (27 %) learning over online alternatives (7 %). Our study concludes by emphasizing the imperative of enhancing public education sector e-learning infrastructure and providing adapted psychological services to address the impact of the COVID-19 pandemic and future crises effectively.

Personality traits and high cigarette dependence among university students: Insights from Lebanon.

PURPOSE: The use of tobacco and cigarette products remains widespread globally, with varying patterns across countries. Understanding the factors influencing cigarette dependence among young adults is crucial for effective smoking prevention and control programs. Personality traits are one of the factors that influence smoking behaviour, yet the evidence on their role in high cigarette dependence among young adults remains inconclusive. This study aims to provide insights and initial evidence on the potential association between personality dimensions, sociodemographic factors, lifestyle habits, and high cigarette dependence among Lebanese university students. METHODS: A convenient sample of 212 student smokers from one private and one public university in Lebanon participated in an online survey. The survey included measures of personality traits using the Big-Five framework, sociodemographic factors, lifestyle habits, and the Fagerström Test for Cigarette Dependence (FTCD). Logistic regression models and mediation analysis were used to analyze the data. RESULTS: The results revealed significant associations between personality dimensions and high cigarette dependence among Lebanese university students. Smokers with higher levels of Openness to Experience were more likely to have high cigarette dependence (ß = 0.408, p < = 0.015). Conversely, smokers with higher levels of Conscientiousness (ß = -0.500, p < 0.001) and Agreeableness (ß = -0.491, p < 0.01) were less likely to have high cigarette dependence. Additionally, attending a public university (ß = 1.198, p = 0.018), having more close friends who smoke (ß = 0.525, p < 0.01), and switching to a cheaper cigarette brand (ß = 0.928, p < 0.05) were associated with a higher cigarette dependence. CONCLUSION: These findings highlight the importance of considering personality dimensions, sociodemographic factors, and lifestyle habits in understanding high cigarette dependence among Lebanese university students. The results can inform the development of targeted interventions to address high cigarette dependence in this population.

Predictive Machine Learning Models for Assessing Lebanese University Students' Depression, Anxiety, and Stress During COVID-19.

University students are experiencing a mental health crisis. COVID-19 has exacerbated this situation. We have surveyed students in 2 universities in Lebanon to gauge their mental health challenges. We have constructed a machine learning (ML) approach to predict symptoms of depression, anxiety, and stress based on demographics and self-rated health measures. Our approach involved developing 8 ML predictive models, including Logistic Regression (LR), multi-layer perceptron (MLP) neural network, support vector machine (SVM), random forest (RF) and XGBoost, AdaBoost, Naïve Bayes (NB), and K-Nearest neighbors (KNN). Following their construction, we compared their respective performances. Our evaluation shows that RF (AUC = 78.27%), NB (AUC = 76.37%), and AdaBoost (AUC = 72.96%) have provided the highest-performing AUC scores for depression, anxiety, and stress, respectively. Self-rated health is found to be the top feature in predicting depression, while age was the top feature in predicting anxiety and stress, followed by self-rated health. Future work will focus on using data augmentation approaches and extending to multi-class anxiety predictions.

A cross-sectional study of university students' mental health and lifestyle practices amidst the COVID-19 pandemic.

OBJECTIVES: University students are regarded as the backbone of society, and their mental health during a pandemic may have a substantial impact on their performance and life outcomes. The purpose of this study was to assess university students' mental health, specifically depression, anxiety, and stress, during Lebanon's extended COVID-19 pandemic, as well as the sociodemographic factors and lifestyle practices associated with it. METHODS: An online anonymous survey assessed the rates of mental health problems during COVID-19, controlling for socio-demographics and other lifestyle practices, in 329 undergraduate and graduate university students. Instruments utilized were the Patient Health Questionnaire (PHQ-9) for depression, the Beck Anxiety Inventory (21-BAI) for anxiety, and the Perceived Stress Scale (PSS-10) for stress. The study employed descriptive statistics and multiple logistic regression models to analyze the association between depression, anxiety, and stress with sociodemographic and lifestyle factors. Results were evaluated using adjusted odds ratios and confidence intervals, with a significance level of 0.05. RESULTS: Moderate to severe rates of depression, anxiety and stress among students were reported by 75.9%, 72.2%, and 89.3%, respectively. The odds of anxiety and stress were higher among women compared to men. Students who used private counseling services had higher odds of anxiety and stress than those who did not. Overall rated health was a major predictor of depression and anxiety, with the "poor" and "fair" overall-reported health groups having higher odds than the "Excellent" group. When compared to those who did not smoke, students who increased their smoking intake had higher odds of depression, anxiety and stress. Students who reduced their alcohol consumption had lower odds of anxiety compared to those who did not consume alcohol. Students who reduced their physical activity had higher odds than those who increased it. Finally, students who slept fewer than seven hours daily had higher odds of depression than those who slept seven to nine hours. CONCLUSION: Our findings indicate a national student mental health crisis, with exceptionally high rates of moderate to severe depression, anxiety, and stress. Factors such as gender, university program, overall rated health, importance of religion in daily decisions, private counseling, smoking cigarettes, alcohol consumption, physical activity, and sleeping, were all found to have an impact on mental health outcomes. Our study highlights the need for university administrators and mental health professionals to consider targeted mental health programming for students, particularly for women and those with poor or fair overall perceived health.

Factors motivating lebanese youth to adopt COVID-19 good practices: a cross-sectional study.

Background: It is now widely acknowledged that young people can be asymptomatic carriers of the COVID-19 virus. While vaccines are successful, COVID-19 good practices continue to be useful in controlling the virus transmission. This study aimed to investigate the associated risk factors impacting the youths' adoption of COVID-19 good practices in Lebanon. Methods: Data were collected through an online survey. The analyzed sample included 602 young people. Results: Our results indicate that around half the youth sample in our study adhere to COVID-19 good practices. COVID-19 good practices are more likely to be adopted by individuals who are more worried about their health and those who live with their partners. Furthermore, media trust was a significant predictor of COVID-19 good practices. Conclusion: Media can play a larger role in promoting good practices through youth-targeted programs. By identifying community influencers and encouraging peer-to-peer communication, it is possible to engage youth who distrust the media and persuade them to adopt COVID-19 good practices.

Coping with the COVID-19 pandemic: A cross-sectional study to investigate how mental health, lifestyle, and socio-demographic factors shape students' quality of life.

PURPOSE: The high prevalence of COVID-19 has had an impact on the Quality of Life (QOL) of people across the world, particularly students. The purpose of this study was to investigate the social, lifestyle, and mental health aspects that are associated with QOL among university students in Lebanon. METHODS: A cross-sectional study design was implemented using a convenience sampling approach. Data collection took place between November 2021 and February 2022, involving 329 undergraduate and graduate students from private and public universities. Quality of life was assessed using the Quality-of-Life Scale (QOLS). Descriptive statistics, Cronbach's alpha, and linear regression-based methods were used to analyze the association between QOL and socio-demographic, health-related, lifestyle, and mental health factors. The significance level for statistical analysis was predetermined at α = 0.05. RESULTS: The study participants' average (SD) QOL score was 76.03 (15.6) with a Cronbach alpha of 0.911. QOL was positively associated with importance of religion in daily decisions (ß = 6.40, p = 0.006), household income (ß = 5.25, p = 0.017), general health ratings (ß Excellent/poor = 23.52, p <0.001), access to private counseling (ß = 4.05, p = 0.020), physical exercise (ß = 6.67, p <0.001), and a healthy diet (ß = 4.62, p = 0.026); and negatively associated with cigarette smoking (ß increased = -6.25, p = 0.030), internet use (ß ≥4 hours = -7.01, p = 0.005), depression (ß = -0.56, p = 0.002) and stress (ß = -0.93, p <0.001). CONCLUSION: In conclusion, this study reveals the key factors that positively and negatively influence students' quality of life (QOL). Factors such as religion, higher income, and a healthy diet improve QOL, while depression, stress, excessive internet use, and cigarette smoking negatively impact it. Universities should prioritize initiatives like physical activity promotion, affordable nutritious options, destigmatizing mental health, counseling services, and self-help interventions to support student well-being and enhance their QOL.

A Machine Learning Study to Predict Anxiety on Campuses in Lebanon.

University students are experiencing a mental health crisis across the world. COVID-19 has exacerbated this situation. We have conducted a survey among university students in two universities in Lebanon to gauge mental health challenges experienced by students. We constructed a machine learning approach to predict anxiety symptoms among the sample of 329 respondents based on student survey items including demographics and self-rated health. Five algorithms including logistic regression, multi-layer perceptron (MLP) neural network, support vector machine (SVM), random forest (RF) and XGBoost were used to predict anxiety. Multi-Layer Perceptron (MLP) provided the highest performing model AUC score (AUC=80.70%) and self-rated health was found to be the top ranked feature to predict anxiety. Future work will focus on using data augmentation approaches and extending to multi-class anxiety predictions. Multidisciplinary research is crucial in this emerging field.

Personal Economic Worries in Response to COVID-19 Pandemic: A Cross Sectional Study.

Objectives: The emergence of the COVID-19 pandemic worsened Lebanon's economic situation and generated worries about living conditions. This study aimed to explain personal economic worries patterns among Lebanese young adults while accounting for demographics and mental health characteristics. Methods: A total sample of 988 Lebanese responses were collected, using an online survey. The analysis was conducted using regression-based methods. Results: Men exhibited higher economic worries than women. Lower levels of economic worries among people with higher wages were more pronounced. Lebanese retirees experience the highest economic worries compared to other employment status groups. Individuals with higher life satisfaction are less concerned about the economy. Mental wellbeing factors were positively associated with personal economic worries. Conclusion: The current study presents a seminal insight into the differences in economic worries caused by COVID-19 pandemic among individuals in a developing country context.

Health worries, life satisfaction, and social well-being concerns during the COVID-19 pandemic: Insights from Lebanon.

The COVID-19 outbreak has struck Lebanon in its worst period of instability, not only impacting physical health, but also increasing psychological distress. Using an online survey enhanced by response time measurement, this study describes the overall patterns in mental well-being outcomes and examines their association with sociodemographic characteristics during the COVID-19 pandemic. Furthermore, it identifies significant predictors for COVID-19 good practices. A total of 988 Lebanese were surveyed, with participants providing written online consent prior to filling the survey. Regression-based models were estimated. Findings show that individuals with higher education levels exhibit lower health concerns. People with children face higher health worries than those without. Men are more worried than women about their health and they are less satisfied with their lives during the pandemic. Descriptive statistics show that most Lebanese are very satisfied with their families (93.1%), but they are highly dissatisfied with their country (63%). Young adults and individuals who live alone exhibit significantly higher social well-being concerns. Age and having children were strong predictors for good COVID-19 practices. The odds of having good practices for older adults are 3.13 times higher than that of youth, while the odds for those with children are 3.18 times higher than those without. The findings of this study could pave the way for a well-coordinated national strategy and increased collaboration with public health professionals to mitigate the pandemic's adverse effects on mental health in the long-term.