Challenges faced by medical officers in providing healthcare services at upazila health complexes and district hospitals in Bangladesh - a qualitative study.

Background: Upazila Health Complexes (UHCs) and District Hospitals (DHs) play a crucial role in the healthcare delivery system of Bangladesh. But very few research has been conducted to find out the prevailing challenges of the medical officers working in these tiers. The objective of the study was to identify the challenges faced by medical officers in providing healthcare services at UHCs and DHs. Methods: In-depth interviews of 51 medical officers from 17 UHCs and nine DHs were done between March and April 2021. All participants were purposively sampled. Data were transcribed verbatim and analysed using thematic analysis. Findings: Inadequate service rooms, unavailability of proper medical equipment, poor housing conditions, lack of public amenities, shortage of health workforce, lack of laboratory services, and excessive workload were the common challenges mentioned by the medical officers in providing healthcare services in UHCs and DHs. Lack of workplace safety, security, and undue pressure from local political leaders and journalists made the work environment fearful. The absence of proper implementation of policy related to higher education, posting, transfer, and promotion was also stated as challenge for the medical officers. Interpretation: Infrastructural improvements along with increased safety and security of the doctors at their workplace and transparent implementation of reformed policies are essential to reduce the workplace challenges of medical officers in UHCs and DHs of Bangladesh. Funding: The study was funded by Hospital Services Management, Directorate General Of Health Services (DGHS), Mohakhali, Dhaka, and Bangabandhu Sheikh Mujib Medical University.

Impact of extreme weather events on mental health in South and Southeast Asia: A two decades of systematic review of observational studies.

Extreme weather events in South and Southeast Asia exert profound psychosocial impacts, amplifying the prevalence of mental illness. Despite their substantial consequences, there is a dearth of research and representation in the current literature. We conducted a systematic review of observational studies published between January 1, 2000, and January 20, 2024, to examine the impact of extreme weather events on the mental health of the South and Southeast Asian population. Quality assessment of the included studies was conducted using the Newcastle-Ottawa Scale (NOS) quality appraisal checklist. The search retrieved 70 studies that met the inclusion criteria and were included in our review. Most were from India (n = 22), and most used a cross-sectional study design (n = 55). Poor mental health outcomes were associated with six types of extreme weather events: floods, storm surges, typhoons, cyclones, extreme heat, and riverbank erosion. Most studies (n = 41) reported short-term outcome measurements. Findings included outcomes with predictable symptomatology, including post-traumatic stress disorder, depression, anxiety, general psychological distress, emotional distress and suicide. Limited studies on long-term effects showed higher mental disorders after floods and typhoons, while cyclone-exposed individuals had more short-term distress. Notably, the review identified over 50 risk factors influencing mental health outcomes, categorized into six classes: demographic, economic, health, disaster exposure, psychological, and community factors. However, the quantitative evidence linking extreme weather events to mental health was limited due to a lack of longitudinal data, lack of control groups, and the absence of objective exposure measurements. The review found some compelling evidence linking extreme weather events to adverse mental health in the South and Southeast Asia region. Future research should focus on longitudinal study design to identify the specific stressors and climatic factors influencing the relationship between climate extremes and mental health in this region.

Factors contributing to online child sexual abuse in Bangladesh: A qualitative inquiry.

Background: Children globally, including in Bangladesh, are facing various forms of online sexual abuse including sextortion, exploitation, body shaming, and blackmail. They are also coerced into engaging in intimate activities, harassed through the sending of sexual content, among other forms of abuse. We aimed to explore the root cause of online child sexual abuse (OCSA) in Bangladesh. Methods: This qualitative research design utilized in-depth interviews (IDIs) and key informant interviews (KIIs) between February and April 2022. The study sample comprised 21 school-going children aged 13-17 years, selected from two different geographical settings (10 from rural areas and 11 from urban areas) in Bangladesh using purposive sampling techniques. They participated in in-depth interviews (IDIs) while additional data was obtained through key informant interviews (KIIs) with 11 multidisciplinary stakeholders. Results: Children from both rural and urban areas reported facing abuse in various ways, such as being asked to send naked photos, being invited to be naked in video calls, and being invited to have virtual sex, among others, over the internet. Conclusions: The government should consider integrating OCSA education into secondary levels. Additionally, there should be efforts to ensure a safe online environment through content scrutiny, promotion of outdoor activities, and community campaigns. An anonymous reporting system must be implemented, and strict measures under the Children's Act must be enforced against perpetrators. Further intervention studies are needed to ensure effective child protection measures in Bangladesh.

The Effect of the COVID-19 Pandemic on Pulmonary Tuberculosis Control in the Selected Upazila Health Complexes of Dhaka Division, Bangladesh.

Despite the enormous disruption of tuberculosis (TB) services reported globally, Bangladesh's impact is not well documented. We aimed to assess the effect of the COVID-19 pandemic on the TB control program in Bangladesh from patients' and service providers' perspectives. We conducted a cross-sectional study from November-December 2021 at six conveniently selected Upazila Health Complexes (UHC) of the Dhaka division, Bangladesh. We conducted face-to-face interviews among 180 pulmonary TB service recipients and all TB service providers working in the selected UHC. We also reviewed TB registries from each UHC. All data were summarized using descriptive statistics tools. We found a 31% reduction in presumptive TB cases during 2021 compared to 2020. Other TB services, such as testing, were reduced by 16-36% during the same period. Service receivers reported a lack of transportation (95%), and a lack of adequate human resources (89%) as critical barriers to receiving and providing TB service, respectively. The findings of our study showed substantial interruption of TB service delivery during the COVID-19 pandemic, threatening the recent progress and pushback from achieving the 2035 End TB targets. Early mitigation of TB service delivery through adopting remote follow-ups using digital health technology and integrating COVID-19 and TB screening is essential for the continuity of essential TB services and achieving global TB targets.

A Novel Method for Parkinson's Disease Diagnosis Utilizing Treatment Protocols.

It makes no difference whether a person is male or female when it comes to neurodegenerative disorders; both sexes are equally susceptible to their devastating effects. Sometimes, it is unclear why a person in their life got a condition that is well-known in the world, such as Parkinson's disease. Other times, it is evident why the individual obtained the ailment (PD). In modern times, a variety of cutting-edge algorithms that are based on treatment protocols have been developed for the purpose of diagnosing Parkinson's disease. The approach that is presented in this article is the most current one; it was created using deep learning, and it can predict how severely Parkinson's disease would affect a patient. In order to diagnose this condition, it is necessary to conduct a comprehensive medical history, a history of any past treatments, physical exams, and certain blood tests and brain films. Because they are less time-consuming and costly, diagnoses are becoming an increasingly important part of medical practice. The diagnosis of Parkinson's disease by the physician is supported by the findings of the present research, which analyzed the voices of 253 participants. Preprocessing is done in order to get the most accurate results possible from the data. In order to carry out the technique of balancing, a methodical sampling approach was used to choose the data that would afterwards be evaluated. Using a feature selection approach that was determined by the magnitude of the label's influence, many data groups were created and organized. DT, SVM, and kNN are three methods that are used in classification algorithms and performance assessment criteria. The model was developed as a result of selecting the classification method and data group that had the greatest performance value. This decision led to the creation of the model. During the process of building the model, the SVM technique was used, and data comprising 45% of the original data set were utilized. The information was arranged in descending order of significance, beginning with the most pertinent. In addition to achieving exceptional outcomes in every other aspect of the project, the performance accuracy target was successfully met at 86 percent. As a consequence of this, it has been decided that the physician will be provided with medical decision support with the assistance of the data set obtained from the speech recordings of the individual who may have Parkinson's disease and the model that has been developed. This has led to the conclusion that medical decision support will be offered to the physician.

Compliance of healthcare workers with the infection prevention and control guidance in tertiary care hospitals: quantitative findings from an explanatory sequential mixed-methods study in Bangladesh.

OBJECTIVES: To assess healthcare workers' (HCWs) compliance with the infection prevention and control (IPC) practices and identify the factors influencing this compliance using the Health Belief Model as the theoretical framework. DESIGN: Quantitative data from an explanatory sequential mixed-methods study were employed in this research. PARTICIPANTS AND SETTINGS: From 17 May to 30 August 2020, 604 physicians and nurses working at six randomly selected tertiary care facilities in Dhaka City in Bangladesh took part in this study. PRIMARY AND SECONDARY OUTCOME MEASURES: Compliance with the WHO's guidance on IPC measures, as well as the associated factors, was the primary outcome. RESULTS: A mean compliance score of 0.49 (±0.25) was observed on a 0-1 scale. HCWs were most compliant with the medical mask wearing guidelines (81%) and were least compliant with the high-touch surface decontamination regulations (23%). Compliance with the IPC guidance was significantly associated with increasing age, female sex, working as a nurse, having non-communicable diseases and history of exposure to patients with COVID-19. Perceived benefits (B=0.039, 95% CI 0.001 to 0.076), self-efficacy (B=0.101, 95% CI 0.060 to 0.142) and cues to action (B=0.045, 95% CI 0.002 to 0.088) were positively associated with compliance. Compliance with IPC guidance was 0.061 times greater among participants who reported low perceived barriers compared with those with high perceived barriers. CONCLUSION: Overall, compliance with IPC guidance among HCWs was unsatisfactory. As self-efficacy exerted the greatest contribution to compliance, it should be emphasised in any endeavour to improve HCWs' IPC adherence. Such interventions should also focus on perceived barriers, including unreliability of the information sources, unsafe working places and unavailability of protective equipment and cues to action, including trust in the administration and availability of adequate IPC guidance.

Duration and Risk Factors of Post-COVID Symptoms Following Recovery Among the Medical Doctors in Bangladesh.

A large number of coronavirus disease 2019 (COVID-19) recovered patients are suffering from related symptoms. We conducted telephone interviews with 186 COVID-19 recovered medical doctors to determine the post-COVID symptoms, duration, and associated risk factors. About 70% of participants had at least one acute post-COVID symptom, including fatigue (43.0%), sleep disturbance (13.4%), lack of concentration (11.8%), breathing difficulty (10.2%), headache (6.5%), and muscle pain (6.5%). However, about 24% of participants reported having long post-COVID symptoms. Logistic regression analysis showed that female sex (odds ratio {OR}, 2.79; 95% CI, 1.28-6.06; p-value: 0.010) and comorbid conditions (OR, 2.28; 95% CI, 1.08-4.79; p: value, 0.030) are risk factors for the long post-COVID symptoms.

The Association Between Coronary Artery Calcification and Subclinical Cerebrovascular Diseases in Men: An Observational Study.

AIM: Coronary artery calcification (CAC) is an independent predictor of stroke and dementia, in which subclinical cerebrovascular diseases (SCVDs) play a vital pathogenetic role. However, few studies have described the association between CAC and SCVDs. Therefore, the aim of this study was to assess the clinical relationship between CAC and SCVDs in a healthy Japanese male population. METHODS: In this observational study, 709 men, free of stroke, were sampled from a city in Japan from 2010 to 2014. CAC was scored using the Agatston method. The following SCVDs were assessed using magnetic resonance imaging: intracranial arterial stenosis (ICAS), lacunar infarction, deep and subcortical white matter hyperintensity (DSWMH), periventricular hyperintensity (PVH), and microbleeds. The participants were categorized according to CAC scores as follows: no CAC (0), mild CAC (1-100), and moderate-to-severe CAC (＞100). The adjusted odds ratios of prevalent SCVDs were computed in reference to the no-CAC group using logistic regression. RESULTS: The mean (standard deviation) age of the participants was 68 (8.4) years. Participants in the moderate-to-severe CAC category showed significantly higher odds of prevalent lacunar infarction, DSWMH, and ICAS in age-adjusted and risk-factor-adjusted models. Microbleeds and PVH, in contrast, did not show any significant associations. The trends for CAC with lacunar infarction, DSWMH, and ICAS were also significant (all P-values for trend ≤ 0.02). CONCLUSIONS: Higher CAC scores were associated with higher odds of lacunar infarction, DSWMH, and ICAS. The presence and degree of CAC may be a useful indicator for SCVDs involving small and large vessels.