Machine learning approaches for predicting suicidal behaviors among university students in Bangladesh during the COVID-19 pandemic: A cross-sectional study.

Psychological and behavioral stress has increased enormously during Coronavirus Disease 2019 (COVID-19) pandemic. However, early prediction and intervention to address psychological distress and suicidal behaviors are crucial to prevent suicide-related deaths. This study aimed to develop a machine algorithm to predict suicidal behaviors and identify essential predictors of suicidal behaviors among university students in Bangladesh during the COVID-19 pandemic. An anonymous online survey was conducted among university students in Bangladesh from June 1 to June 30, 2022. A total of 2391 university students completed and submitted the questionnaires. Five different Machine Learning models (MLMs) were applied to develop a suitable algorithm for predicting suicidal behaviors among university students. In predicting suicidal behaviors, the most crucial background and demographic features were relationship status, friendly environment in the family, family income, family type, and sex. In addition, features related to the impact of the COVID-19 pandemic were identified as job loss, economic loss, and loss of family/relatives due to COVID-19. Moreover, factors related to mental health include depression, anxiety, stress, and insomnia. The performance evaluation and comparison of the MLM showed that all models behaved consistently and were comparable in predicting suicidal risk. However, the Support Vector Machine was the best and most consistent performing model among all MLMs in terms of accuracy (79%), Kappa (0.59), receiver operating characteristic (0.89), sensitivity (0.81), and specificity (0.81). Support Vector Machine is the best-performing model for predicting suicidal risks among university students in Bangladesh and can help in designing appropriate and timely suicide prevention interventions.

Association between preference and e-learning readiness among the Bangladeshi female nursing students in the COVID-19 pandemic: a cross-sectional study.

BACKGROUND: The COVID-19 pandemic jeopardized the traditional academic learning calendars due to the closing of all educational institutions across the globe. To keep up with the flow of learning, most of the educational institutions shifted toward e-learning. However, the students' e-learning preference and e-learning readiness did not identify, particularly among the Bangladeshi female nursing students, where those can pose serious challenges. A cross-sectional study was carried out among the female nursing students between December 26, 2020, and January 11, 2021. A total of 237 students were recruited who have enrolled in e-learning at least the last 30 days of the participation. Multivariable linear regression models were fitted to find the association of students' preference, e-learning readiness domains, and other variables. RESULTS: A cross-sectional study was conducted among the female nursing students to assess perceived e-learning readiness in the subdomains of readiness; availability, technology use, self-confidence, acceptance and training. The findings of the study revealed that the prevalence of preference for e-learning was 43.46%. The students did not prefer e-learning compared to 'prefer group' has significantly less availability of technology (ß = - 3.01, 95% CI - 4.46, - 1.56), less use of technology (ß = - 3.08, 95% CI - 5.11, - 1.06), less self-confidence (ß = - 4.50, 95% CI - 7.02, - 1.98), less acceptance (ß = - 5.96, 95% CI - 7.76, - 4.16) and less training need (ß = - 1.86, 95% CI - 2.67, - 1.06). The age, degree, residence, parents' highest education, having a single room, and having any eye problems were significantly associated with the variation of availability of technology, use of technology, self-confidence, acceptance, and training need of e-learning. CONCLUSIONS: The outcomes of the study could be helpful while developing an effective and productive e-learning infrastructure regarding the preparedness of nursing colleges for the continuation of academia in any adverse circumstances like the COVID-19 pandemic.

Workplace violence and turnover intention among the Bangladeshi female nurses after a year of pandemic: An exploratory cross-sectional study.

During the COVID-19 pandemic, workplace violence was widespread against healthcare personnel. Workplace violence (WPV) against nurses exhilarates their turnover intention (TI). The objective of this study was to investigate the association between workplace violence and turnover intention and also identify other factors associated with TI among Bangladeshi female nurses. An exploratory cross-sectional study was carried out among 881 female nurses between April 26 and July 10, 2021. The TI of the female nurses was the outcome variable of this study. The primary exposure variable was WPV faced by the nurses. Workplace Violence Scale (WPVS) was used to measure the WPV, and Turnover Intention Scale-6 (TIS-6) was used to measure the TI of the nurses. Multiple linear regression model was fitted to find the adjusted association of TI with WPV and other study variables. A stratified analysis by type of job (government vs. private) was also performed. The majority of the nurses (74.46%) faced low to high levels of WPV. The overall mean score of TIS was found 16.33 (± 4.72). Multiple linear regression analysis revealed that compared to government jobholders, the mean score of TIS (15.81 vs. 17.20) was found significantly higher among the private jobholders (p < 0.001). Nurses exposed to the intermediate and high level of WPV had a significantly higher TI score (ß = 4.35, 95% CI: 3.36, 5.34) than the non-exposures. The TI of private jobholders was found significantly higher (ß = 2.04, 95% CI: 1.09, 3.00) than the government jobholders. Compared to diploma degree holders, significantly higher TI was observed among the B.Sc. degree holders (ß = 0.86, 95% CI: 0.22, 1.55) and M.Sc. degree holders (ß = 1.46, 95% CI: 0.58, 2.34). Besides, the nurses who did not get timely salaries scored higher TI (ß = 1.17, 95% CI: 0.12, 2.22). Moreover, the nurses who did not receive any training against WPV scored significantly higher TI (ß = 1.89, 95% CI: 1.03, 2.74). The stratified analysis by type of job also revealed significant factors of TI in government and private settings. This study found a high prevalence of WPV and a high rate of TI among Bangladeshi female nurses. Moreover, this study explored an association between WPV and TI. The study findings could help policymakers facilitate a comfortable working environment by preventing WPV and addressing the factors to reduce nurses' frequent TI.

Lifestyle and Comorbidity-Related Risk Factors of Severe and Critical COVID-19 Infection: A Comparative Study Among Survived COVID-19 Patients in Bangladesh.

BACKGROUND: Severe COVID-19 infections have already taken more than 4 million lives worldwide. Factors, such as socio-demographics, comorbidities, lifestyles, environment, and so on, have been widely discussed to be associated with increased severity in many countries. The study aimed to determine the risk factors of severe-critical COVID-19 in Bangladesh. METHODS: This was a comparative cross-sectional study among various types of COVID-19 patients (both hospitalized and non-hospitalized) confirmed by reverse transcription polymerase chain reaction (RT-PCR). We have selected 1500 COVID-19 positive patients using a convenient sampling technique and analyzed lifestyle and comorbidity-related data using IBM SPSS-23 statistical package software. Chi-square test and multinomial logistic regression were used to determine risk factors of life-threatening COVID-19 infection. RESULTS: The mean age of the study participants was 43.23 (±15.48) years. The study identified several lifestyle-related factors and common commodities as risk factors for severe-critical COVID-19. The patient's age was one of the most important predictors, as people >59 years were at higher risk (AOR=18.223). Among other lifestyle factors, active smoking (AOR=1.482), exposure to secondary smoking (AOR=1.728), sleep disturbance (AOR=2.208) and attachment with SLT/alcohol/substance abuse (AOR=1.804) were identified as significant predictors for severe-critical COVID-19. Patients those were overweight/obese (AOR=2.105), diabetic (AOR=4.286), hypertensive (AOR=3.363), CKD patients (AOR=8.317), asthma patients (AOR=2.152), CVD patients (AOR=7.747) were also at higher risk of severe-critical COVID-19 infection. CONCLUSION: This study has identified several vital lifestyles and comorbidity-related risk factors of severe-critical COVID-19. People who have these comorbidities should be under high protection, and risky lifestyles of the general population should modify through the proper educational campaign.

Association Between Smoking and COVID-19 Severity: Evidence from Bangladesh.

PURPOSE: Previous studies have explored several risk factors for coronavirus disease 2019 (COVID-19) severity, but there is still a lack of association with smoking. Our study aims to find out the association between smoking and COVID-19 severity. SUBJECTS AND METHODS: This comparative study was conducted among hospitalized severely and critically ill COVID-19 patients, as well as asymptomatic, mild, and moderate patients from the list of the city corporation (Dhaka, Bangladesh), as confirmed by reverse-transcription polymerase chain reaction (RT-PCR). A total of 2022 adults aged ≥18 years were enrolled in this study. RESULTS: The mean age of the patients was 41.17 years; 66.96% of the patients were male, 57.02% were aged above 35 years, and 81.50% of the patients had ever been married; and 33.09% cases were mild and 14.99% were severe. Among the patients, 29.4% were ever-smokers. Smoking status, duration, and frequency, and the presence of comorbidities were significantly associated with COVID-19 severity (p<0.001). Ever-smokers were 1.35 times (95% CI: 0.74-2.45), 1.30 times (95% CI: 0.58-2.87), and 2.45 times (95% CI: 1.07-5.61) more likely to be mild, severe, and critical cases in comparison to non-smokers. CONCLUSION: This study revealed a strong association between smoking and COVID-19 severity that calls for mass awareness and cessation campaigns from governments and voluntary organizations.

Availability and use of technology for e-learning: to what extent do these impact Bangladeshi university students? A cross-sectional study.

Background: E-learning is making education globally and conveniently attainable with the deliverance of advanced technology. However, this mode of academia is still not commonly practiced locally. Thus, the study aimed to investigate technological availability, usability, and association to university students' perceived stress due to e-learning curriculum. Methods: A cross-sectional study commenced among Bangladeshi university students enrolled in the e-learning curriculum. A total of 1162 university students were included. The main explanatory variables were related to the availability of technology and the use of technology. The outcome variable was perceived e-learning stress. In statistical analysis, p-value < 0.05 was considered statistically significant with a 95% confidence interval. Results: In this study, lack of technological availability and usability were associated with higher level of perceived e-learning stress. Being female, living in rural areas, and outside of Dhaka division were found the associated factors in the lack of technological availability and usability. Conclusions: A significant association between the availability and usability of technology with perceived e-learning stress was observed. Thus, measures should be taken to initialize e-learning adaptivity by increasing technological growth across the nation, considering educational preparedness for future catastrophes.