The purpose of this study was to investigate the prevalence of depression and anxiety among Bangladeshi university students during the COVID-19 pandemic. It also aimed at identifying the determinants of depression and anxiety. A total of 476 university students living in Bangladesh participated in this cross-sectional web-based survey. A standardized e-questionnaire was generated using the Google Form, and the link was shared through social media—Facebook. The information was analyzed in three consecutive levels, such as univariate, bivariate, and multivariate analysis. Students were experiencing heightened depression and anxiety. Around 15% of the students reportedly had moderately severe depression, whereas 18.1% were severely suffering from anxiety. The binary logistic regression suggests that older students have greater depression (OR = 2.886, 95% CI = 0.961–8.669). It is also evident that students who provided private tuition in the pre-pandemic period had depression (OR = 1.199, 95% CI = 0.736–1.952). It is expected that both the government and universities could work together to fix the academic delays and financial problems to reduce depression and anxiety among university students.

The recent outbreak of viral zoonotic disease–monkeypox–caused by the monkeypox virus, has infected many people worldwide. This study aims to explore the knowledge, attitudes, and practices (KAP) concerning monkeypox among university students in Bangladesh. Data were collected using purposive snowball sampling from 887 university students through an online survey using Google Form. The participants were mostly in their twenties (M = 22.33 [SD 2.01] years), and they spent, on average, 2.59 [SD 1.91] hours/day on electronic and social media. The participants generally showed moderate knowledge (39.5%), low attitude (25.1%), and moderate practice (48.6%) toward monkeypox, with 47.6% having had a moderate KAP score. Findings further showed that personal attributes of university students, i.e., age, sex, year of schooling, residence, living status, geographical distribution, e.g., division, were statistically and significantly associated with knowledge, attitudes, and practices regarding monkeypox and overall KAP score. It is also apparent that health status, susceptibility to monkeypox, and exposure to social media were the most common factors significantly associated with knowledge, attitudes, and practices regarding monkeypox and overall KAP score. The current study’s findings underscore the need for developing appropriate information, education, and communication (IEC) materials and their dissemination, which could play an important role in reducing the risk of monkeypox and similar other infectious diseases, particularly among students in Bangladesh.

Domestic violence against women is a prevalent in Liberia, with nearly half of women reporting physical violence. However, research on the biosocial factors contributing to this issue remains limited. This study aims to predict women’s vulnerability to domestic violence using a machine learning approach, leveraging data from the Liberian Demographic and Health Survey (LDHS) conducted in 2019–2020.We employed seven machine learning algorithms to achieve this goal, including ANN, KNN, RF, DT, XGBoost, LightGBM, and CatBoost. Our analysis revealed that the LightGBM and RF models achieved the highest accuracy in predicting women’s vulnerability to domestic violence in Liberia, with 81% and 82% accuracy rates, respectively. One of the key features identified across multiple algorithms was the number of people who had experienced emotional violence.These findings offer important insights into the underlying characteristics and risk factors associated with domestic violence against women in Liberia. By utilizing machine learning techniques, we can better predict and understand this complex issue, ultimately contributing to the development of more effective prevention and intervention strategies.

Background. The primary objective of this research was to investigate how socioeconomic and demographic factors influence the usage of contraceptives by women in 18 developing countries. Methods. The study used the latest DHS data from 18 developing countries in order to acquire a broad perspective of contraceptive methods. We applied meta-analysis techniques for 18 developing countries to find out the summary results. Results. The overall summary effect showed that the variable respondent education ( ; 95% CI: 1.17 to 1.65), husband education ( ; 95% CI: 1.32 to 1.93), type of place of residence ( ; 95% CI 0.78 to 0.98), current working status ( ; 95% CI 1.30 to 1.66), age of the respondent ( ; 95% CI 2.35 to 4.93), breastfeeding status ( ; 95% CI 1.11 to 1.62), and desire for more children ( ; 95% CI 0.43 to 0.65) were the significant factors for contraceptive utilization in developing countries. Conclusions. According to the findings of this descriptive study, the respondent’s age, level of education, and work status were shown to be the most significant factors that influence the usage of contraceptives in developing countries. It is necessary to take reasonable steps in order to increase the rate of utilizing methods of contraception among women of reproductive age who are uneducated, living in rural areas, and unemployed.