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. Therefore, this study aimed to use advanced supervised algorithms to predict the micronutrient intake status in Ethiopian children aged 6-23 months. Methods: A total weighted of 2,499 children aged 6-23 months from the Ethiopia Demographic and Health Survey 2016 data set were utilized. The data underwent preprocessing, with 80% of the observations used for training and 20% for testing the model. Twelve machine learning algorithms were employed. To select best predictive model, their performance was assessed using different evaluation metrics in Python software. The Boruta algorithm was used to select the most relevant features. Besides, seven data balancing techniques and three hyper parameter tuning methods were employed. To determine the association between independent and targeted feature, association rule mining was conducted using the a priori algorithm in R software. Results: According to the 2016 Ethiopia Demographic and Health Survey, out of 2,499 weighted children aged 12-23 months, 1,728 (69.15%) had MN intake. The random forest, catboost, and light gradient boosting algorithm outperformed in predicting MN intake status among all selected classifiers. Region, wealth index, place of delivery, mothers' occupation, child age, fathers' educational status, desire for more children, access to media exposure, religion, residence, and antenatal care (ANC) follow-up were the top attributes to predict MN intake. Association rule mining was identified the top seven best rules that most frequently associated with MN intake among children aged 6-23 months in Ethiopia. Conclusion: The random forest, catboost, and light gradient boosting algorithm achieved a highest performance and identifying the relevant predictors of MN intake. Therefore, policymakers and healthcare providers can develop targeted interventions to enhance the uptake of micronutrient supplementation among children. Customizing strategies based on identified association rules has the potential to improve child health outcomes and decrease the impact of micronutrient deficiencies in Ethiopia.

Employing supervised machine learning algorithms for classification and prediction of anemia among youth girls in Ethiopia.

In developing countries, one-quarter of young women have suffered from anemia. However, the available studies in Ethiopia have been usually used the traditional stastical methods. Therefore, this study aimed to employ multiple machine learning algorithms to identify the most effective model for the prediction of anemia among youth girls in Ethiopia. A total of 5642 weighted samples of young girls from the 2016 Ethiopian Demographic and Health Survey dataset were utilized. The data underwent preprocessing, with 80% of the observations used for training the model and 20% for testing. Eight machine learning algorithms were employed to build and compare models. The model performance was assessed using evaluation metrics in Python software. Various data balancing techniques were applied, and the Boruta algorithm was used to select the most relevant features. Besides, association rule mining was conducted using the Apriori algorithm in R software. The random forest classifier with an AUC value of 82% outperformed in predicting anemia among all the tested classifiers. Region, poor wealth index, no formal education, unimproved toilet facility, rural residence, not used contraceptive method, religion, age, no media exposure, occupation, and having more than 5 family size were the top attributes to predict anemia. Association rule mining was identified the top seven best rules that most frequently associated with anemia. The random forest classifier is the best for predicting anemia. Therefore, making it potentially valuable as decision-support tools for the relevant stakeholders and giving emphasis for the identified predictors could be an important intervention to halt anemia among youth girls.

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. A total of 320 neonates paired with their mothers were involved, including 64 cases and 256 controls. Data were collected through a structured interviewer-administered questionnaire and a review of medical records. The collected data were analyzed using SPSS Version 23, and a multivariate logistic regression model was employed to understand the relationship between independent factors and the occurrence of neonatal jaundice. Statistical significance was determined at a threshold of P value less than 0.05. RESULTS: The study findings revealed that maternal age over 35 years, residing in urban areas [adjusted odds ratio (AOR) = 2.4, 95% confidence interval (CI): 1.23, 4.82], male gender (AOR = 4.3, 95% CI: 1.90, 9.74), prematurity (AOR = 3.9, 95% CI: 1.88, 8.09), and ABO incompatibility (AOR = 2.6, 95% CI: 1.16, 5.96) were significant determinants of neonatal jaundice. Conversely, the study indicated that cesarean birth was associated with a 76% lower likelihood of infant jaundice compared to vaginal delivery (AOR = 0.24, 95% CI: 0.08, 0.72). CONCLUSION: To prevent, diagnose, and treat neonatal jaundice effectively, efforts should primarily focus on managing ABO incompatibility and early detection of prematurity. Additionally, special attention should be given to neonates born through vaginal delivery, those with mothers over 35 years old, and those residing in urban areas, as they are at higher risk of developing newborn jaundice. Close monitoring of high-risk mother-infant pairs during the antenatal and postnatal periods, along with early intervention, is crucial for reducing the severity of neonatal jaundice in this study setting.

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. Regarding this, the health belief model (HBM) is the major model for understanding health behaviors. This study aimed to examine predictors of intended COVID-19 vaccine acceptance in the second wave of the pandemic among university students in Ethiopia using HBM. Methods: A cross-sectional study was conducted among 423 randomly selected medical and health science students at the University of Gondar from 21 August to 15 September 2020. Analysis of data was performed using STATA 14.0. Linear regression analysis was applied and a p value of less than 0.05 was used to declare statistical significance. Results: Among the total participants, 293 [72.2% (95.0%: CI: 67.2-76.8)] of them scored above the mean of COVID-19 vaccine acceptance. HBM explained nearly 46.3% (adjusted R2 = 0.463) variance in intention to receive the COVID-19 vaccine. Year of study (ß = 0.288; 95% CI: 0.144-0.056), using social media (ß = 0.58; 95% CI: 1.546-2.804), existing chronic disease (ß = 0.12; 95% CI: 0.042-0.433), perceived overall health condition (ß = 0.117; 95% CI: 0.307-0.091), perceived susceptibility (ß = 0.58; 95% CI: 1.546-2.804), perceived benefit (ß = 0.338; 95% CI: 1.578-2.863), and cues to action (ß = 0.49; 95% CI: 0.388-0.99) were significantly associated with intended COVID-19 vaccine acceptance at p value < 0.5. Conclusion: Approximately, three-quarters of the participants were above the mean score of COVID-19 vaccine acceptance, which is higher compared to previous reports in resource-limited settings. Interventions in this study setting chould include placing emphasis on the risks of acquiring COVID-19, enhancing perceived benefits of COVID-19 vaccination and improving cues to action by advocating COVID-19 vaccination. Our findings also implied that social media health campaigns are significant factor in COVID-19 vaccination behavioral change in this study setting.

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. This study aims to assess the acceptance of electronic medical records and associated factors among physicians working in Ethiopia. Methods: A cross-sectional study was conducted among physicians working in Gondar Comprehensive Specialized Hospital. A total of 205 physicians were included. Data were collected through a self-administered structured questionnaire. Descriptive and Logistic regression were conducted. Result: A one hundred ninety-eight participants returned the questionnaire from the total yielding a response rate of 96.6%. The proportion of those who have good acceptance for EMR was 72.2% and about 48.5%, 78.3%, and 59.6%, were sufficient computer skills, Good knowledge, and a favorable attitude toward EMR respectively. Age ≤ 30 years (AOR = 0.13 (0.02, 0.57), working experience AOR = 0.15 (0.04, 0.54), working department AOR = 0.09 (0.01, 0.90), good computer skills AOR = 8.42 (6.45, 16.02), Good knowledge AOR = 5.21 (1.22, 12.28), and favorable attitude AOR = 15.24 (12.06, 25.94) were significantly associated towards EMR acceptance. Conclusion: Generally, in this study, physicians' acceptance of electronic medical records was good. Age, year of experience, working department, good computer skills, good knowledge, and favorable attitude were significantly associated with physicians' acceptance of the electronic medical record. Improving computer skills, enhancing positive attitudes, and increasing the knowledge of the health care professionals are vital interventions to enhance and improve the acceptance of EMR system in the study area.

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. METHOD: We designed a controlled group quasi-experimental pre-post test study to evaluate the effect of capacity-building EBM training. A total of 192 healthcare professionals were recruited in the study (96 from the intervention and 96 from the control group). We used a difference-in-differences (DID) analysis to determine the effect of the training. Along the way, we used a fixed effect panel-data regression model to assess variables that could affect healthcare professionals' practice of EBM. The cut point to determine the significant effect of EBM training on healthcare professionals' background knowledge and awareness of EBM sources, attitude, and competence was at a P-value < 0.05. RESULT: The DID estimator showed a significant net change of 8.0%, 17.1%, and 11.4% at P < 0.01 on attitude, competence, and practice of EBM, respectively, whereas no significant increment in the background knowledge and awareness of EBM sources. The fixed effect regression model showed that the attitude [OR = 2.288, 95% CI: (1.049, 4.989)], competence [OR = 4.174, 95% CI: 1.984, 8.780)], technical support [OR = 2.222, 95% CI: (1.043, 3.401)], and internet access [OR = 1.984, 95% CI: (1.073, 4.048)] were significantly affected EBM practice. CONCLUSION: The capacity-building training improved attitude, competence, and EBM practice. Policymakers, government, and other concerned bodies recommended focusing on a well-designed training strategy to enhance the attitude, competence, and practice towards EBM among healthcare professionals. It was also recommended to enhance internet access and set mechanisms to provide technical support at health facilities.

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. As a result, investigating the pooled prevalence and factors associated with micronutrient intake among pregnant women in East Africa is critical to alleviate the burden of micronutrient deficiency among pregnant women. METHOD: The pooled prevalence of micronutrient intake with a 95% Confidence Interval (CI) was reported and presented in a forest plot for East Africa Countries using STATA version 14.1. Intra-class Correlation Coefficient (ICC), Likelihood Ratio (LR) test, Median Odds Ratio (MOR), and deviance (-2LLR) values were used for model comparison and fitness. Adjusted Odds Ratios (AOR) with a 95% Confidence Interval (CI) and p-value ≤0.05 in the multilevel logistic model were used to declare significant factors associated with micronutrient intake. RESULT: The pooled prevalence of micronutrient intake in East African countries was 36.07% (95% CI: 35.82%, 36.33%). In the multilevel logistic regression model, women from the highest wealth quintile were 1.06 [AOR = 1.09, 95%CI: 1.00, 1.11] more likely to take micronutrients compared to their counterparts. Mothers who attained primary education, secondary education, and tertiary education had 1.20 times [AOR = 1.20, 95% CI: 1.15, 1.26], 1.28 times [AOR = 1.28, 95% CI: 1.19, 1.36] and 1.22 times [AOR = 1.22, 95% CI: 1.07, 1.38] more likely take micronutrient compared to mothers who attained no education, respectively. CONCLUSION: The overall prevalence of micronutrient intake in East Africa was low. Only 36% of the study participants had micronutrient intake practice. Socioeconomic factors (education level, and household wealth status) have been shown to influence micronutrient intake. Therefore, it is necessitates the continuation of ongoing projects as well as the development of fresh ones that concentrate on these variables and include effective treatments and programs, especially among underprivileged and vulnerable populations.

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. METHODS: This study is a secondary analysis of the Ethiopian Demographic and Health Survey (mini EDHS 2019). A total of 1784 reproductive-age women were included in the analysis. The global spatial autocorrelation (Global Moran's I) and the Getis-Ord statistics tool were used to detect the presence of clustering and the high/low hotspot areas of SBI respectively. Ordinary kriging was used to interpolate short birth intervals, and spatial scan statistics were employed to identify spatial clusters with high and low SBI. A multilevel multivariable model was used to identify predictors of a short birth interval. RESULTS: The prevalence of SBI was 62.89% (95%CI: 59.3, 69.7) in Ethiopia. High clustering of SBI was observed in all parts of Somali, in Afar (zones 1, 3, 4, &5), Oromia (Guje, Bale, & West Harerge), and northern Tigray. The most likely significant primary cluster was observed in the Somali region. Women who lived in the primary cluster were 24% more likely to have a short birth interval than those who lived outside the window. In the multilevel mixed-effect analysis age 25-34 [(AOR = 0.40, 95% CI: 0.35, 0.45)], 35-49 [(AOR = 0.44, 95% CI: 0.38, 0.51)], Muslim religion follower [(AOR = 3.5, 95% CI: 2.7, 4.69)], no formal education [(AOR = 0.5, 95% CI: 0.37, 0.70)], primary education[(AOR = 0.4, 95%CI: 0.28, 0.53)], and secondary education [(AOR = 0.3, 95% CI: 0.24, 0.48)], middle [(AOR: 1.3, 95% CI: 1.2, 1.52)], rich wealth status [(AOR: 1.4, 95% CI: 1.3, 1.68)], female sex children [(AOR: 1.2, 95% CI: 1.09, 1.42)], and two or fewer ideal number of children [(AOR = 0.2, 95% CI: 0.25, 0.32)] were found to be significant predictors of SBI. CONCLUSION: Overall, SBI was high and significantly clustered across the region of Ethiopia. Age, religion, education, wealth status, the sex of the indexed child, and the ideal number of children were found to be significantly associated with short birth intervals. Hence, the government should design a health promotion strategy and public health awareness in the identified hotspot areas of SBI and should scale up family planning and the wealth status of reproductive-age women.

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. METHODS: An institution-based cross-sectional study design was used from 24 March up to 19 April 2022. Stratified random sampling and a pretested self-administered questionnaire were used among 423 samples. Epi Info V.7.1 and STATA V.15 software were used for data entry and analysis, respectively. Descriptive statistics and a logistic regression model were employed to describe the study subjects and to measure the strength of association between dependent and independent variables, respectively. A variable with a p value of <0.2 in bivariate logistic regression was considered for multivariable logistic regression. In multivariable logistic regression, ORs with 95% CIs and a p value of <0.05 were considered to determine the strength of association between dependent and independent variables. RESULTS: Health professionals' documentation practice was 51.1% (95% CI: 48.64 to 53.1). Lack of motivation (adjusted OR (AOR): 0.41, 95% CI: 0.22 to 0.76), good knowledge (AOR: 1.35, 95% CI: 0.72 to 2.97), taking training (AOR: 4.18, 95% CI: 2.99 to 8.28), using electronic systems (AOR: 2.19, 95% CI: 1.36 to 3.28), availability of standard documentation tools (AOR: 2.45, 95% CI: 1.35 to 4.43) were statistically associated factors. CONCLUSIONS: Health professionals' documentation practice is good. Lack of motivation, good knowledge, taking training, using electronic systems and the availability of documentation tools were significant factors. Stakeholders should provide additional training, and encourage professionals to use an electronic system for documentation practices.

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. METHODS: An institution-based cross-sectional study was conducted from January to April 2021 in Ethiopia. Simple random sampling technique was used to select 423 study participants among health professionals. SPSS (version 20) software was used for data entry and analysis. A pretested self-administered questionnaire was used to collect the required data. Multivariable logistic regression was used to examine the association between the digital health literacy skill and associated factors. Significance value was obtained at 95% CI and P<.05. RESULTS: In total, 401 study subjects participated in the study. Overall, 43.6% (n=176) of respondents had high digital health literacy skills. High computer literacy (adjusted odds ratio [AOR] 4.43, 95% CI 2.34-5.67; P=.01); master's degree and above (AOR 3.42, 95% CI 2.31-4.90; P=.02); internet use (AOR 4.00, 95% CI 1.78-4.02; P=.03); perceived ease of use (AOR 2.65, 95% CI 1.35-4.65; P=.04); monthly income of >15,000 Ethiopian birr (>US $283.68; AOR 7.55, 95% CI 6.43-9.44; P<.001); good knowledge of eHealth (AOR 2.22, 95% CI 1.32-4.03; P=.04); favorable attitudes (AOR 3.11, 95% CI 2.11-4.32; P=.04); and perceived usefulness (AOR 3.43, 95% CI 2.43-5.44; P=.02) were variables associated with eHealth literacy level. CONCLUSIONS: In general, less than half of the study participants had a high digital health literacy level. High computer literacy, master's degree and above, frequent internet use, perceived ease to use, income of >15,000 Ethiopian birr (>US $283.68), good knowledge of digital health literacy, favorable attitude, and perceived usefulness were the most determinant factors in the study. Having high computer literacy, frequent use of internet, perceived ease of use, perceived usefulness, favorable attitude, and a high level of education will help to promote a high level of digital health literacy.

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. METHODS: Ethiopian Mini Demographic and Health Survey 2019 dataset with a total 1407 children aged 6-23 months was used. Data management and processing were done using STATA version 15 software and Microsoft Office Excel. ArcMap version 10.7 software was used for mapping and spatial visualization of the distribution. Spatial scan statistics was performed using SaTScan version 9.5 software for Bernoulli-based model. Multilevel mixed effect logistic regression model was employed to identify associated factors. RESULTS: Overall, 38.99% (95% CI: 36.46-41.62) of children aged 6- 23 months took vitamin A rich foods. Poor intake of vitamin A rich foods was significantly clustered Dire Dawa city, Somali and Harari regions of Ethiopia. Children aged 6-23 months lived in the primary cluster were 70% (RR = 1.70, P-value < 0.001) more likely to intake vitamin A rich foods than children lived outside the window. In the multilevel mixed effect logistic regression analysis, Primary educational status (AOR:1.42, 95% CI: 1.05, 1.93) and higher educational status (AOR:3.0, 95% CI: 1.59, 5.65) of mother, Dire Dawa (AOR:0.49, 95% CI: 0.22, 1.12) city, Afar (AOR: 0.16, 95% CI: 0.07, 0.36), Amhara (AOR: 0.37, 95% CI: 0.19, 0.71) and Somali (AOR: 0.02, 95% CI: 0.003, 0.08) regions of Ethiopia, children aged 13-23 months (AOR: 1.80, 95% CI: 1.28, 2.36), Mothers' exposure to media (AOR: 1.41, 95% CI: 1.04, 1.92) were statistically significant factors for vitamin A rich foods intake among children aged 6-23 months. CONCLUSIONS: Only 4 out of ten children took vitamin A rich foods which is too low compared to the national target and significantly clustered in Ethiopia. Mother's educational status, Region, Child age and Mother's media exposure are significant factors vitamin A rich foods intake. Stakeholders should strengthen mothers' education status, creating awareness for mothers on child feeding and using locally available natural resource to produce vitamin A rich foods.

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. SETTING: The study was conducted among communities in Meket district, North Wollo zone, North-East Ethiopia. PARTICIPANTS: A total of 327 (109 cases and 218 controls) children aged 6-59 months participated in the study. Children from 6 months to 59 months of age who match the definition of case/wasted/ and control/not wasted were eligible for the study. However, children who had physical deformities which make anthropometric measurements inconvenient were excluded from the study. PRIMARY AND SECONDARY OUTCOME MEASURES: The main outcome measure was wasting. RESULT: The mean ages of the cases and controls were 21.77±11.41 months and 20.13±11.39 months, respectively. Factors that were significantly associated with wasting were: maternal decision making on the use of household money (adjusted odd ratio (AOR)=3.04, 95% CI 1.08 to 7.83), complementary feeding started in a month (AOR=3.02, 95% CI 1.097 to 6.97), food diversity score (AOR=2.64, 95% CI 1.64 to 5.23), frequency of complementary feeding (AOR=6.68, 95% CI 3.6 to 11.25) and history of acute respiratory infections (ARIs) 2 weeks preceding the survey (AOR=3.21, 95% CI 1.07 to 7.86). CONCLUSION: Our result implies that the right time to introduce complementary foods, the frequency of feeding and also the amount of food consumed were some of the crucial factors that needed to be changed in child nutrition to reduce wasting. Furthermore, within the framework of our study, the empowerment of women in the decision-making process and the prevention of ARI should be seen as a necessary benchmark for acute malnutrition.

Digital health literacy to share COVID-19 related information and associated factors among healthcare providers worked at COVID-19 treatment centers in Amhara region, Ethiopia: A cross-sectional survey.

Background: Coronavirus (CoV) is a novel respiratory virus that can cause severe acute respiratory syndrome (SARS). It affects millions of people in the world and thousands of people in Ethiopia. In responding to this, digital health technologies help to reduce COVID-19 outbreaks by sharing accurate and timely COVID-19 related information. Additionally, digital solutions are used for remote consulting during the pandemic, in creating COVID-19 related awareness, for distribution of the vaccine, and so on. Therefore, this study aimed to assess digital health literacy to share COVID-19 related information and associated factors among healthcare providers who worked at COVID-19 treatment centers in the Amhara region, Northwest Ethiopia. Method: An institutional-based cross-sectional survey was conducted from April 4 to May 4, 2021. The study included 476 healthcare providers who worked at COVID-19 treatment centers in the Amhara region. A pretested, structured self-administered questionnaire was used to collect data. EpiData 4.6 and SPSS version 26 were used for data entry and analysis respectively. Bi-variable and Multivariable logistic regression analysis was used to identify factors associated with the dependent variable. A P-value of less than 0.05 was used to declare statistical significance. Result: A total of 456 respondents were participated in the study, with 95.8% response rate. Digital health literacy to share COVID-19 related information found to be 50.4% (95% CI: 46-55). Educational status [AOR = 4.37, 95% CI(2.08-9.17)], training [AOR = 3.00, 95% CI (1.80-5.00)], attitude [AOR = 1.99, 95% CI(1.18-3.36)], perceived usefulness [AOR = 2.01, 95% CI(1.22-3.32)], perceived ease of use [AOR = 2.00, 95% CI(1.25-3.21)] and smartphone access [AOR = 5.21, 95% CI(2.34-9.62)] were significantly associated with digital health literacy to sharing of COVID-19 related information at P-value less than 0.05. Conclusion: This finding indicated that approximately half of the respondents had digital health literacy to share COVID-19 related information which was inadequate. Improving respondents' educational status, computer training, smartphone access, perceived usefulness, perceived ease of use, and attitude was necessary to measure digital health literacy to sharing of COVID-19 related information.

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 (56.3% male and 43.7% female) health professionals participated in the study. All health professionals permanently working in North Wollo Zone were included in this study. However, health professionals who were not present during the data collection period by any means and who had less than 6 months of experience were not included in this study. PRIMARY AND SECONDARY OUTCOME MEASURES: The main outcome measure was health management information utilisation. RESULT: About 58.4% (n=388) (95% CI: 54.4% to 62.0%) of the study participants use health management information. The multivariable logistic regression model indicated that participants who had managerial positions are more likely to use health management information with an adjusted OR (AOR) of 3.11 and 95% CI 1.84 to 5.24. Similarly, having a good motivation level (AOR=4.42 (95% CI: 2.82 to 6.93)), perceived good culture of health information (AOR=6.17 (95% CI: 3.35 to 11.36)), a standard set of indicators (AOR=4.11 (95% CI: 2.65 to 6.38)), having good governance of health information system (AOR=1.75 (95% CI:1.13 to 2.72)) and health management information system (HMIS) training (AOR=3.10 (95% CI: 1.89 to 5.07)) were the predictors positively associated with higher utilisation of health management information. CONCLUSION: This study revealed that utilisation of health management information was still inadequate. Enhancing motivation, building a culture of information use, having standardised indicators, strengthening the governance of health information systems and comprehensive HMIS training were measures to be taken to improve utilisation of health management information in this study setting.

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. However, there is little evidence on information seeking specifically on COVID-19 in this study setting. Therefore, this study aimed to assess information seeking about COVID-19 and associated factors among chronic patients. METHOD: An institutional-based cross-sectional study supplemented with qualitative data was conducted at Bahir Dar city public hospitals in Northwest Ethiopia from April 8 to June 15, 2021. A total of 423 chronic patients were selected using systematic random sampling techniques with an interval of 5. Bi-variable and multivariable logistic regression analysis was fitted to identify factors associated with information seeking about COVID-19. A p-value < 0.05 was used to declare statistical significance. Qualitative data were analyzed using a thematic approach. Finally, it was triangulated with quantitative findings. RESULT: The proportion of information seeking about COVID-19 among chronic patients was 44.0% (95% CI = 39.0, 49.0). Being living in urban [AOR = 4.4, 95% CI (2.01, 9.58)], having high perceived susceptibility to COVID-19 [AOR = 3.4, 95%CI (1.98, 5.70)], having high perceived severity to COVID-19 [AOR = 1.7, 95%CI (1.04, 2.91)], having high self-efficacy to COVID-19 [AOR = 4.3, 95%CI (2.52, 7.34)], and having adequate health literacy [AOR = 1.8, 95%CI (1.10, 3.03)] were significant factors associated with information-seeking about COVID-19. CONCLUSION: The overall proportion of information seeking about COVID-19 among chronic patients was low. Thus, health promotion programs should emphasize the chronic patients living in a rural area; enhance perceived risk and severity of COVID-19, enhancing self-efficacy and health literacy interventions to improve information seeking.

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. However, little is known about healthcare providers' EHR readiness in this study setting. Accordingly, this research was conducted aiming at examining healthcare providers' readiness for EHR adoption and associated factors in southwestern Ethiopia. METHODS: An institutional-based cross-sectional study was conducted from September 1 to October 30, 2021. A total of 423 healthcare providers working in public hospitals were selected using a simple random sampling technique. Multivariable logistic regression was fitted to identify determinant factors of overall healthcare providers' readiness after the other covariates were controlled. RESULT: In this study, the overall good readiness level of EHR adoption was 52.8% (n = 204) [95% CI of 47.9% to 56.6%]. Age, computer literacy, computer access at health facilities, attitude towards EHRs, awareness about EHRs, perceived benefit, and perceived technology self-efficacy were significantly associated with the overall health care providers' readiness for the adoption of EHR using a cut point of P-value less than 0.05. CONCLUSION: Around half of the respondents had a good level of overall healthcare providers' readiness for the adoption of EHR which was considered inadequate. This finding implied that a huge effort is required to improve readiness before the actual implementation of EHRs. The finding implied that younger-aged groups were more ready for such technology which in turn implied; the older one needs more concern. Enhancing computer literacy, confidence building to raise self-efficacy of such technology, addressing the issue of computer availability at health facilities, building a positive attitude, awareness campaign of EHR, and recognizing the usefulness of such systems were the necessary measures to improve EHR readiness in this setting. Additionally, further studies are recommended to encompass all types of EHR readiness such as organizational readiness, technology readiness, societal readiness, and so on. Additionally, exploring the healthcare provider opinion with qualitative study and extending the proposed study to other implementation settings are recommended to be addressed by future works.

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. METHODS: A cross-sectional study design using a two-stage stratified sampling technique was used. The analysis was performed using STATA 14.2, ArcGIS 10.8, and SaTScan version 9.6 software. To find significant related factors with measles vaccination, researchers used multilevel logistic regression. RESULTS: The prevalence of MCV1 in Ethiopia was 58.5%. A spatial variation of MCV1 coverage was observed across the study area. The most likely significant primary clusters with low MCV1 coverage were observed in Liben, Afder, Shebelle, Korahe, and Nogob zones of the Somali region; Bale and Guji zones of the Oromia region, and Gedeo and Sidama zones of the SNNPR. Rural areas, maternal primary education, secondary and above school education, Orthodox religion, Muslim religion, health facility delivery, and Afar region were significantly associated with MCV1 vaccination. CONCLUSION: The overall MCV1 coverage in Ethiopia was low. Aside from the inadequate coverage, there was a geographical variation across the country. Low MCV1 coverage areas should be prioritized to improve vaccination efforts to control measles across the country.

COVID-19 related knowledge sharing practice and associated factors among healthcare providers worked in COVID-19 treatment centers at teaching hospitals in Northwest Ethiopia: A cross-sectional study.

BACKGROUND: COVID-19 is a pandemic that causes many deaths and disrupts the lives of the world population on an unprecedented scale. Healthcare providers are on the frontline in the struggle against this pandemic. In this regard, knowledge sharing is very crucial for healthcare professionals to provide safe, effective, and quality patient care during the COVID-19 pandemic. Accurate and timely COVID-19 related knowledge helps for making evidence-based decisions, during the management of the pandemic. Therefore, this study aimed to assess COVID-19 related knowledge sharing practices and associated factors among healthcare providers who worked in COVID-19 treatment centers at specialized teaching hospitals in the Amhara Regional State, Northwest Ethiopia. METHOD: An institutional-based cross-sectional survey was conducted from April 1 to May 30, 2021. The study included 476 healthcare providers who worked in COVID-19 treatment centers at specialized teaching hospitals in Northwest Ethiopia. A pretested and structured self-administered questionnaire was used to collect data. EpiData 4.6 and SPSS version 23 were used for data entry and analysis respectively. Bi-variable and Multivariable logistic regression analysis was used to identify factors associated with the dependent variable. A P-value of less than 0.05 was used to declare statistical significance. RESULT: A total of 454 respondents, with a response rate of 95.4%, were participated in the study. About, 55.3% (95% CI: 51-60.2) of healthcare providers had a good level of COVID-19 knowledge-sharing practice. Phone type [AOR = 4.05, 95% CI (1.99-8.25)], computer access [AOR = 2.09, 95% CI (1.12-3.92)], awareness [AOR = 2.01, 95% CI (1.20-3.39)], willingness [AOR = 1.77, 95% CI (1.05-2.97)] and educational status [AOR = 2.94, 95% CI (1.92-5.71)] were significantly associated with the COVID-19 knowledge sharing practices in the multivariable logistic regression model. CONCLUSION: The finding implied that above half of the healthcare providers in this study setting were good at sharing their COVID-19 related knowledge. Policymakers, government, and other concerned bodies should stress to improve computer access, awareness creation, enhancing healthcare providers' willingness to share their COVID-19 related knowledge, introducing smartphone technology, and rising healthcare providers' educational status are necessary measures to improve COVID-19 related knowledge sharing practice in this study setting.

Spatial Variations and Determinants of Acute Malnutrition Among Under-Five Children in Ethiopia: Evidence from 2019 Ethiopian Demographic Health Survey.

Background and aims: Childhood acute malnutrition, in the form of wasting defined by a severe weight loss as a result of acute food shortage and/or illness. It is a critical public health problem that needs urgent attention in developing countries, like Ethiopia. Despite its variation between localities, the risk factors and its geospatial variation were not addressed enough across the various corner of the country. Therefore, the current study was undertaken to assess spatial variation and factors associated with acute malnutrition among under-five children in Ethiopia. Methods: A total weighted sample of 4 955 under-five children were included from the 2019 Demographic and Health Survey. Getis-Ord spatial statistical tool used to identify the hot and cold spot areas of severe and acute malnutrition. A multilevel multivariable logistic regression model using was used to examine predictors of acute malnutrition. In the multivariable multilevel analysis, Adjusted Odds Ratio with 95% CI was used to declare significant determinants of acute malnutrition among children. Result: Among 4 955 under-five children, 7% of them were wasted and 1% of them were severely wasted in Ethiopia during the 2019 national demographic survey. The distribution was followed some spatial geo-locations where most parts of Somali were severely affected (RR = 1.46, P37 value <0.001), and the distribution affected few areas of Afar, Gambella, and Benishangul Gumz regions. Factors that significantly associated with childhood wasting were: gender(male)1.9 (1.3-2.7), age (above 36 months) 0.5 (0.2-0.9), wealth index(richest) 0.5 (0.2-0.8), and water source (unimproved source) 1.5 (1.0-2.3). Conclusions: Our finding implies, the distribution of childhood wasting was not random. Regions like Afar, Somali, and pocket areas in Gambella and SNNP should be considered as priority areas nutritional interventions for reducing acute malnutrition. The established socio-demographic and economic characteristics can be also used to develop strategies.

Willingness to use telemedicine during COVID-19 among health professionals in a low income country.

INTRODUCTION: The coronavirus disease 2019 pandemic has prompted rapid restructuring of the health-care system in an effort to stop the spread of the pandemic. Thus, telemedicine is more preferable in order to prevent the COVID-19 pandemic when face to face meeting is forbidden, allowing provision of health service over a distance. This study aimed to assess willingness to use telemedicine and factors that will determine their extent of willingness during COIVID-19 among healthcare providers working in south west of Ethiopia. METHODS: Institutional based cross-sectional study design was applied to assess willingness to use telemedicine among healthcare providers working at public health hospitals in south west of Ethiopia. Self-administered questionnaires were used. We have used Epi-info for data entry and Analysis of Moment Structure (AMOS) for analysis. A structural equation modeling was performed to identify factors associated with willingness to use telemedicine at 95% confidence interval (CI). RESULT: In this study, less than half of respondents had high willingness to use telemedicine. Ease of use (ß = 0.79, 95% CI: [0.72, 0.86], p < 0.01), attitude (ß = 0.91, 95% CI: [0.87, 0.95], p < 0.01) and patient-physician relationships (ß = 0.67, 95% CI: [0.54, 0.70], p < 0.01) were variables associated with willingness to use telemedicine. Anxiety towards technology (ß = 0.74, 95% CI: [0.69, 0.79], p < 0.01) and patient-physician relationships (ß = 0.87, 95% CI: [0.81, 0.92], p < 0.01) were determinant factors of attitude to use telemedicine. CONCLUSIONS: The overall willingness to use telemedicine during COVID-19 in this setting is 46.5%. Addressing the problem related with ease of use, attitude and patient-physician relationships will help to increase the overall willingness to use telemedicine during COVID-19. An attempt to improving patient-physician relationship, provision of technical training for ease of use and working on healthcare providers' attitude will help to improve the willingness to use telemedicine.