Predicting place of delivery choice among childbearing women in East Africa: a comparative analysis of advanced machine learning techniques.

Background: Sub-Saharan Africa faces high neonatal and maternal mortality rates due to limited access to skilled healthcare during delivery. This study aims to improve the classification of health facilities and home deliveries using advanced machine learning techniques and to explore factors influencing women's choices of delivery locations in East Africa.

Method: The study focused on 86,009 childbearing women in East Africa.

Health information-seeking behavior among people living with the two common chronic diseases in low and middle-income countries (LMICs). A systematic review and meta-analysis.

Objective: The main aim of this review was to systematically collect and summarize the available evidence on health information-seeking behavior among people living with the two common types of chronic diseases in LMICs.

Methods: For this systematic review and meta-analysis, we searched PubMed, Embase, Scopus, Google Scholar, and forward and backward citations from included studies. The preferred reporting items for Systematic Reviews and Meta-Analyses (PRISMA) procedure were followed to develop and report the review.

Spatial variations and predictors of overweight/obesity among under-five children in Ethiopia: A geographically weighted regression analysis of the 2019 Ethiopian Mini Demographic and Health Survey.

Background: Overweight/ obesity among under-five children is an emerging public health issue of the twenty-first century. Due to the quick nutritional and epidemiological change, non-communicable diseases, premature death, disability, and reproductive disorders have grown in low-income countries. Besides, little attention has been given.

Readiness of big health data analytics by technology-organization-environment (TOE) framework in Ethiopian health sectors.

Background: Big health data is a large and complex dataset that the health sector has collected and stored continuously to generate healthcare evidence for intervening the future healthcare uncertainty. However, data use for decision-making practices has been significantly low in developing countries, especially in Ethiopia. Hence, it is critical to ascertain which elements influence the health sector's decision to adopt big health data analytics in health sectors.

Prediction of delayed breastfeeding initiation among mothers having children less than 2 months of age in East Africa: application of machine learning algorithms.

Background: Delayed breastfeeding initiation is a significant public health concern, and reducing the proportion of delayed breastfeeding initiation in East Africa is a key strategy for lowering the Child Mortality rate. However, there is limited evidence on this public health issue assessed using advanced models. Therefore, this study aimed to assess prediction of delayed initiation of breastfeeding initiation and associated factors among women with less than 2 months of a child in East Africa using the machine learning approach.

Understanding the predictors of health professionals' intention to use electronic health record system: extend and apply UTAUT3 model.

Background: The implementation of Electronic Health Record (EHR) systems is a critical challenge, particularly in low-income countries, where behavioral intention plays a crucial role. To address this issue, we conducted a study to extend and apply the Unified Theory of Acceptance and Use of Technology 3 (UTAUT3) model in predicting health professionals' behavioral intention to use EHR systems.

Methods: A quantitative research approach was employed among 423 health professionals in Southwest Ethiopia.

Predicting adverse birth outcome among childbearing women in Sub-Saharan Africa: employing innovative machine learning techniques.

Background: Adverse birth outcomes, including preterm birth, low birth weight, and stillbirth, remain a major global health challenge, particularly in developing regions. Understanding the possible risk factors is crucial for designing effective interventions for birth outcomes. Accordingly, this study aimed to develop a predictive model for adverse birth outcomes among childbearing women in Sub-Saharan Africa using advanced machine learning techniques.

Employing advanced supervised machine learning approaches for predicting micronutrient intake status among children aged 6-23 months in Ethiopia.

Background: Although micronutrients (MNs) are important for children's growth and development, their intake has not received enough attention. MN deficiency is a significant public health problem, especially in developing countries like Ethiopia. However, there is a lack of empirical evidence using advanced statistical methods, such as machine learning.

Factors associated with neonatal jaundice among neonates admitted at referral hospitals in northeast Ethiopia: a facility-based unmatched case-control study.

Background: Neonatal jaundice is a significant contributor to illness and death in newborns, leading to frequent admissions to neonatal intensive care units. To better understand this issue, a study was conducted to identify the factors contributing to neonatal jaundice among newborns admitted to Dessie and Woldia comprehensive specialized hospitals in northeast Ethiopia.

Methods: The study took place from April 1 to May 30, 2022, using unmatched case-control design.

COVID-19 vaccine acceptance in the second wave of the pandemic among university students in Ethiopia: application of the health belief model.

Background: The first case of COVID-19 virus was reported in Africa on 14 February 2020. The pandemic became more aggressive in the continent during the second wave than the first wave. Promoting vaccination behavior is an unparalleled measure to curb the spread of the pandemic.

Acceptance of electronic medical records and associated factor among physicians working in University of Gondar comprehensive specialized hospital: A cross-sectional study.

Objective: Electronic Medical Records (EMRs) are digitalized medical record systems that collect, store, and display patient data. It is individual patient clinical information electronically gathered and made instantly available to all physicians in the healthcare chain, assisting in the delivery of coherent and consistent care. However, the acceptance of the electronic medical record status of physicians in Ethiopia is limitedly known due to knowledge, attitude, and computer skill gaps.

The effect of capacity building evidence-based medicine training on its implementation among healthcare professionals in Southwest Ethiopia: a controlled quasi-experimental outcome evaluation.

Background: Evidence-based medicine (EBM) bridges research and clinical practice to enhance medical knowledge and improve patient care. However, clinical decisions in many African countries don't base on the best available scientific evidence. Hence, this study aimed to determine the effect of training interventions on background knowledge and awareness of EBM sources, attitude, competence, and practice of EBM among healthcare professionals.

Micronutrient intake and associated factors among pregnant women in East Africa: Multilevel logistic regression analysis.

Background: Micronutrient deficiencies during pregnancy pose significant public health issues, considering the potential for negative consequences not only during pregnancy but also throughout life. Anemia in pregnant women is becoming a significant problem in developing countries, with scientific evidence indicating that 41.8 percent of women worldwide suffer from anemia.

Spatial distribution of short birth interval and associated factors among reproductive age women in Ethiopia: spatial and multilevel analysis of 2019 Ethiopian mini demographic and health survey.

Background: Short Birth Interval negatively affects the health of both mothers and children in developing countries. Studies conducted in Ethiopia on the spatial variation and determinants of individual and community-level factors about short birth intervals were limited. Thus, this study was intended to assess the spatial variation of the short birth interval and its determinants in Ethiopia.

Health professionals' routine practice documentation and its associated factors in a resource-limited setting: a cross-sectional study.

Objectives: Documenting routine practice is significant for better diagnosis, treatment, continuity of care and medicolegal issues. However, health professionals' routine practice documentation is poorly practised. Therefore, this study aimed to assess health professionals' routine practice documentation and associated factors in a resource-limited setting.

Digital Health Literacy During the COVID-19 Pandemic Among Health Care Providers in Resource-Limited Settings: Cross-sectional Study.

Background: Digital health literacy is the use of information and communication technology to support health and health care. Digital health literacy is becoming increasingly important as individuals continue to seek medical advice from various web-based sources, especially social media, during the pandemics such as COVID-19.

Objective: The study aimed to assess health professionals' digital health literacy level and associated factors in Southwest Ethiopia in 2021.

Spatial distribution of vitamin A rich foods intake and associated factors among children aged 6-23 months in Ethiopia: spatial and multilevel analysis of 2019 Ethiopian mini demographic and health survey.

Background: Inadequate micronutrients in the diet and vitamin A deficiency are worldwide public health problems. In developing regions, many preschool children are undernourished, become blind every year and died before the age of 23 months. This study was aimed to explore the spatial distribution of vitamin A rich foods intake among children aged 6-23 months and identify associated factors in Ethiopia.

Determinants of wasting among children aged 6-59 months in North-East Ethiopia: a community-based case-control study.

Objective: Childhood acute malnutrition, in the form of wasting defined by Weight-for-Height Z-Scores, is a major public health concern. It is one of the main reasons for the death of children in developing countries like Ethiopia. Accordingly, this study aimed to assess determinants of wasting among children aged 6-59 months in Meket district, North Wollo zone, North-East Ethiopia.

Utilisation of health management information and its determinant factors among health professionals working at public health facilities in North Wollo Zone, Northeast Ethiopia: a cross-sectional study.

Objective: The study aimed to assess health management information utilisation and associated factors among health professionals working at public health facilities in North Wollo Zone, Northeast Ethiopia.

Setting: The study was conducted at public health facilities in the North Wollo Zone, Northeast Ethiopia.

Participants: A total of 664 (56.

Information seeking about COVID-19 and associated factors among chronic patients in Bahir Dar city public hospitals, Northwest Ethiopia: a cross-sectional study.

Background: The health impacts of COVID-19 are not evenly distributed in societies. Chronic patients are highly affected and develop dangerous symptoms of COVID-19. Understanding their information seeking about COVID-19 may help to improve the effectiveness of public health strategies in the future, the adoption of safety measures, and minimize the spread of the pandemic.

Healthcare providers' readiness for electronic health record adoption: a cross-sectional study during pre-implementation phase.

Background: The adoption of an electronic health record (EHR) in the healthcare system has the potential to make healthcare service delivery effective and efficient by providing accurate, up-to-date, and complete information. Despite its great importance, the adoptions of EHR in low-income country settings, like Ethiopia, were lagging and increasingly failed. Assessing the readiness of stakeholders before the actual adoption of EHR is considered the prominent solution to tackle the problem.