Employing machine learning models to predict pregnancy termination among adolescent and young women aged 15-24 years in East Africa.

Pregnancy termination is still a sensitive and continuing public health issue due to several political, economic, religious, and social concerns. This study assesses the applications of machine learning models in the prediction of pregnancy termination using data from eleven national datasets in East Africa. Nine machine learning models, namely: Random Forests (RF), Decision Tree, Logistic Regression, Support Vector Machine, eXtreme Gradient Boosting (XGB), AdaBoost, CatBoost, K-nearest neighbor, and feedforward neural network models were used to predict pregnancy termination, with six evaluation criteria utilized to compare their performance.

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.

Timely initiation of breastfeeding and its associated factors among immediate postpartum mother-newborn pairs in Debre Tabor comprehensive specialized hospital, South Gondar Zone, North West, Ethiopia.

Background: Initiation of breast feeding within one hour of birth is the easiest and most cost-effective intervention to reduce the risk of neonatal morbidity and mortality. Conducting studies immediately after an hour of birth for the timely initiation of breastfeeding has the significance of initiating breastfeeding and acting immediately. However, there was a paucity of information in the region as well as in the country at large.

Predictors of Mental Health Literacy and Information Seeking Behavior Toward Mental Health Among University Students in Resource-Limited Settings.

Background: This paper investigated mental health literacy level and information seeking behavior, and mental health-related information sources in limited-resource settings, in the case of Ethiopian university students.

Methods: A cross-sectional, self-administered web-based survey was conducted among Dilla University students, from 1 January to 29 February 2022, with a total of 780 respondents. We presented descriptive statistics using mean, standard deviations, and proportions.

Spatial trends and projections of chronic malnutrition among children under 5 years of age in Ethiopia from 2011 to 2019: a geographically weighted regression analysis.

Introduction: Undernutrition is a serious global health issue, and stunting is a key indicator of children's nutritional status which results from long-term deprivation of basic needs. Ethiopia, the largest and most populous country in Sub-Saharan Africa, has the greatest rate of stunting among children under the age of five, yet the problem is unevenly distributed across the country. Thus, we investigate spatial heterogeneity and explore spatial projection of stunting among under-five children.

Spatial distribution and associated factors of measles vaccination among children aged 12-23 months in Ethiopia. A spatial and multilevel analysis.

Introduction: In Ethiopia, measles continues to be the cause of a significant number of vaccine-preventable infant morbidity and mortality due to the low vaccination rate. However, understanding the geographical distribution of the measles-containing vaccine first dose (MCV1) and identifying associated factors is crucial to setting up appropriate interventions. This study aimed to explore the spatial distribution and associated factors of MCV1 coverage among children aged 12-23 months in Ethiopia using national representative data.

Exploring Spatial Variations and Determinants of Dietary Diversity Among Children in Ethiopia: Spatial and Multilevel Analysis Using EDHS (2011-2016).

Introduction: Dietary diversity has a significant impact on children's nutritional health. For developing and implementing interventions, it is critical to understand the regional distribution of dietary diversity and underlying factors. However, the application of spatial techniques in dietary studies has not been well documented.

Barriers to the Adoption of Electronic Medical Record System in Ethiopia: A Systematic Review.

Background: Electronic medical records (EMRs) can improve the quality of health care and patient safety. Various countries have gone through the local application of EMRs to various health care organizations in national implementation and integration of EMRs. Ethiopia lags far in the back in this regard, as solely some hospitals have implemented EMR.

Factors Influencing COVID-19 Vaccination Demand and Intent in Resource-Limited Settings: Based on Health Belief Model.

Background: Vaccination is, without doubt, one of the most outstanding health interventions in reducing unprecedented damages of coronavirus disease (COVID-19). Globally, several vaccines have been produced to be effective against COVID-19. This survey aimed to assess the demand and intent towards the COVID-19 vaccine among the general population in Ethiopia.

Tracking progress in anthropometric failure among under-five children in Ethiopia: a geospatial and multilevel analysis.

Background: Undernutrition is a major public health concern among under-five children in many developing countries. This work evaluated the overall prevalence of under-nutrition by using a composite index of anthropometric failure (CIAF), which helps in the detection of children with multiple anthropometric failures. This research also includes the Spatio-temporal distribution of childhood anthropometric failures across time.