Feelings of isolation, insecurity, and instability triggered by COVID-19 could have a long-term impact on the mental health status of individuals. The aim of this study was to examine the prevalence of mental health symptoms (anxiety, depression, and stress) in Bangladesh and the factors associated with these symptoms during the COVID-19 pandemic. From 1 to 30 April 2020, we used a validated self-administered questionnaire to conduct a cross-sectional study on 10,609 participants through an online survey platform. We assessed mental health status using the Depression, Anxiety, and Stress Scale (DASS-21). The total depression, anxiety, and stress subscale scores were divided into normal, mild, moderate, severe, and multinomial logistic regression was used to examine associated factors. The prevalence of depressive symptoms was 15%, 34%, and 15% for mild, moderate, and severe depressive symptoms, respectively. The prevalence of anxiety symptoms was 59% for severe anxiety symptoms, 14% for moderate anxiety symptoms, and 14% for mild anxiety symptoms, while the prevalence for stress levels were 16% for severe stress level, 22% for moderate stress level, and 13% for mild stress level. Multivariate analyses revealed that the most consistent factors associated with mild, moderate, and severe of the three mental health subscales (depression, anxiety, and stress) were respondents who lived in Dhaka and Rangpur division, females, those who self-quarantined in the previous seven days before the survey, and those respondents who experienced chills, breathing difficulty, dizziness, and sore throat. Our results showed that about 64%, 87%, and 61% of the respondents in Bangladesh reported high levels of depression, anxiety, and stress, respectively. There is a need for mental health support targeting women and those who self-quarantined or lived in Dhaka and Rangpur during the pandemic.

This study investigated the perception and awareness of risk among adult participants in Bangladesh about Coronavirus Disease 2019 (COVID-19). During the lockdown era in Bangladesh at two different time points, from 26−31 March 2020 (early lockdown) and 11−16 May 2020 (late lockdown), two self-administered online surveys were conducted on 1005 respondents (322 and 683 participants, respectively) via social media. To examine risk perception and knowledge-related factors towards COVID-19, univariate and multiple linear regression models were employed. Scores of mean knowledge (8.4 vs. 8.1, p = 0.022) and perception of risk (11.2 vs. 10.6, p < 0.001) differed significantly between early and late lockdown. There was a significant decrease in perceived risk scores for contracting SARS-Cov-2 [β = −0.85, 95%CI: −1.31, −0.39], while knowledge about SARS-Cov-2 decreased insignificantly [β = −0.22, 95%CI: −0.46, 0.03] in late lockdown compared with early lockdown period. Self-quarantine was a common factor linked to increased perceived risks and knowledge of SARS-Cov-2 during the lockdown period. Any effort to increase public awareness and comprehension of SARS-Cov-2 in Bangladesh will then offer preference to males, who did not practice self-quarantine and are less worried about the propagation of this kind of virus.

Purpose: The study aims to assess the awareness, perception and adoption of artificial intelligence (AI) in Bangladesh’s healthcare sector.Design/methodology/approach: This study utilizes a quantitative methodology. A survey with structured questionnaire was conducted with a sample of 399 healthcare professionals and public members through stratified random sampling. Descriptive statistics summarized participant demographics, while inferential statistical techniques, including regression analysis, examined relationships between AI readiness and adoption.Findings: Using a conceptual framework, the study explored factors influencing AI adoption in Bangladesh’s healthcare sector. The measurement model confirmed reliability and validity, with strong factor loadings and discriminant validity. Structural model analysis revealed that social media influence (SMI) and technological awareness (TA) significantly enhanced readiness for AI (RAI) (path coefficients: 0.354 and 0.162, respectively). Perceived risk (PR) had a weaker positive effect (0.123), while perceived susceptibility (PS) and personal innovativeness (PI) were insignificant. Mediation analysis showed that RAI significantly mediated the effects of TA and PR on the adaptation of AI (AAI).Research limitations/implications: The study suggests policymakers develop robust regulatory frameworks to address privacy concerns, enhance trust in AI and implement educational initiatives to improve AI literacy among healthcare stakeholders in Bangladesh.Originality/value: This study offers insights into AI adoption in Bangladesh’s healthcare sector. It addresses gaps in awareness and perceptions among professionals and the public, contributing to the limited research in this context.

Background: Hijras in Bangladesh face considerable discrimination, stigma, and violence despite the 2013 legislation that recognized Hijras as a third gender. There is a dearth of published literature describing the extent of human rights violations among this population and their associated factors. Methods: A questionnaire was administered to 346 study participants aged 15 years and older, living in five urban cities of Bangladesh who self-identified as Hijra, in 2019. The six human rights violation indicators (Economic, Employment, Health, Education, Social and Civic and Political Right) assessed were categorized as binary. Associations between sociodemographic characteristics and the six human rights violations were tested using univariate and multivariate logistic regression. Results: Human right violations including economic, educational, political, employment, health and social/civil right violations were reported in 73.3%, 59.3%, 58.5%, 46.4%, 42.7%, and 34.4% of the participants, respectively. Economic rights violations were associated with bisexuality (Adjusted odds ratios [AOR] 3.60, 95%CI: 1.57, 8.26) and not living with family (AOR 2.71, 95%CI: 1.21, 6.09), while Hijras who earned more than 10,000 Bangladesh Taka experienced higher odds of educational (AOR 2.77, 95%CI: 1.06, 7.19) and political rights violations (AOR 4.30, 95%CI: 1.06, 7.44). Living in Dhaka city was associated with a reduced odds for economic and political rights violation while experiencing violations of one human right could lead to violation of another in the Hijra community. Conclusion: Human rights violations were common in Bangladesh Hijras, particularly the Bisexual Hijras. Media and educational awareness campaigns are needed to address the underlying roots of a violation. Programs focused on the families, young people and high-income earners of this community are needed in Bangladesh.