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Violence against physicians in the workplace is a prevalent global issue, and Bangladesh is no exception. Such violence significantly disrupts healthcare delivery and the attainment of universal health coverage. This study aimed to comprehensively evaluate the prevalence, nature and associated risk factors of workplace violence (WPV) against physicians in Bangladesh.
This descriptive cross-sectional study was conducted at a public tertiary care hospital involving 441 physicians with a minimum tenure of 6 months. Data were gathered through a structured self-reported questionnaire, and statistical analyses were performed by using SPSS V.25.
Out of the surveyed physicians, 67.3% (n=297) reported experiencing violence, categorised as 84.5% psychological, 13.5% physical and 2% sexual in nature. Predominant forms of psychological violence included bullying (48.8%) and threats (40.1%). The mean age of exposed physicians was 32.5±4.3 (SD) years. Those working in the emergency unit (45.8%), surgery and allied departments (54.2%), engaging in rotating shift work (70%), morning shifts (59.6%) and postgraduate trainees (68%) were frequently subjected to violence. Factors significantly associated with WPV included placement in surgery and allied departments (p
A higher proportion of physicians at the early to mid-level stages of their careers, especially those in rotating shifts and surgery-related departments, reported incidence of WPV. Urgent intervention from policy-makers and healthcare entities is imperative to implement preventive measures. Strengthening security measures, establishing antiviolence policies and providing comprehensive training programmes are crucial steps towards ensuring a safer work environment for healthcare professionals.
by Muntequa Imtiaz Siraji, Ahnaf Akif Rahman, Mirza Muntasir Nishat, Md Abdullah Al Mamun, Fahim Faisal, Lamim Ibtisam Khalid, Ashik Ahmed
Depression is a psychological state of mind that often influences a person in an unfavorable manner. While it can occur in people of all ages, students are especially vulnerable to it throughout their academic careers. Beginning in 2020, the COVID-19 epidemic caused major problems in people’s lives by driving them into quarantine and forcing them to be connected continually with mobile devices, such that mobile connectivity became the new norm during the pandemic and beyond. This situation is further accelerated for students as universities move towards a blended learning mode. In these circumstances, monitoring student mental health in terms of mobile and Internet connectivity is crucial for their wellbeing. This study focuses on students attending an International University of Bangladesh to investigate their mental health due to their continual use of mobile devices (e.g., smartphones, tablets, laptops etc.). A cross-sectional survey method was employed to collect data from 444 participants. Following the exploratory data analysis, eight machine learning (ML) algorithms were used to develop an automated normal-to-extreme severe depression identification and classification system. When the automated detection was incorporated with feature selection such as Chi-square test and Recursive Feature Elimination (RFE), about 3 to 5% increase in accuracy was observed by the method. Similarly, a 5 to 15% increase in accuracy has been observed when a feature extraction method such as Principal Component Analysis (PCA) was performed. Also, the SparsePCA feature extraction technique in combination with the CatBoost classifier showed the best results in terms of accuracy, F1-score, and ROC-AUC. The data analysis revealed no sign of depression in about 44% of the total participants. About 25% of students showed mild-to-moderate and 31% of students showed severe-to-extreme signs of depression. The results suggest that ML models, incorporating a proper feature engineering method can serve adequately in multi-stage depression detection among the students. This model might be utilized in other disciplines for detecting early signs of depression among people.This study was designed to identify the patterns, prevalence and risk factors of intimate partner violence (IPV) against female adolescents and its association with mental health problems.
Cross-sectional survey.
Dumuria Upazila (subdistrict) under the Khulna district of Bangladesh.
A total of 304 participants were selected purposively based on some specifications: they must be female adolescents, residents of Dumuria Upazila and married during the COVID-19 pandemic when under 18 years of age.
By administering a semi-structured interview schedule, data were collected regarding IPV using 12 five-point Likert scale items; a higher score from the summation reflects frequent violence.
The findings suggest that the prevalence of physical, sexual and emotional IPV among the 304 participants, who had an average age of 17.1 years (SD=1.42), was 89.5%, 87.8% and 93.7%, respectively, whereas 12.2% of the participants experienced severe physical IPV, 9.9% experienced severe sexual IPV and 10.5% experienced severe emotional IPV. Stepwise regression models identified age at marriage (p=0.001), number of miscarriages (p=0.005), education of spouse (p=0.001), income of spouse (p=0.016), age gap between spouses (p=0.008), marital adjustment (p
During the COVID-19 pandemic, an increase in IPV and mental health problems among early married adolescents was documented. To reduce physical and mental harm and to assure their well-being, preventive and rehabilitative measures should be devised.
FreshRSS 