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Abstract Introduction Maternal and child mortality remains a major public health concern in Ethiopia. Improving the practice of short inter-pregnancy intervals is a key strategy to reduce neonatal and maternal mortality. Several primary studies conducted in Ethiopia have revealed the practice short inter-pregnancy interval. However, inconsistencies among these studies have been observed, and no review has been conducted to report the combined magnitude, determinants, and complications. Therefore, this review aims to estimate the national magnitude, determinants, and complications of short inter-pregnancy intervals among pregnant mothers in Ethiopia. Methods Following the PRISMA standards, we systematically reviewed and meta-analyzed articles from PubMed, Cochrane Library, and Google Scholar that investigated the magnitude, determinants, and complications of a short inter-pregnancy interval. The Q and I2 tests were used to assess heterogeneity across studies. We utilized a weighted inverse variance random effects model to evaluate the national magnitude and effect size of linked covariates. To examine publication bias, we employed a funnel plot and Egger's regression test. A sensitivity analysis was also performed to determine the impact of the studies. Results The analysis included a total of twenty-six studies. The pooled magnitude of a short inter-pregnancy interval in Ethiopia was found to be 44.054% (95% CI 32.735–55.372; I2 = 100%; P

ObjectiveThe objective of this systematic review and meta-analysis is to assess and synthesize the global evidence on the level of nurses' knowledge and its determinants regarding the prevention of surgical site infections.MethodsThis systematic review and meta-analysis were conducted following strict methodological guidelines to ensure accuracy and reliability. Adhering to the 2020 PRISMA checklist, a systematic review and meta-analysis sought to establish the pooled proportion of nurse's knowledge and its determinants regarding surgical site infection prevention globally. MeSH terms and keywords were included in the search. Data extraction, quality assessment, and analysis followed established protocols. Heterogeneity and publication bias was assessed using STATA version 17.0.ResultsA total of seventeen observational studies, with sample sizes ranging from 30 to 515 participants, were included in the final analysis in a global context. In this systematic review and meta-analysis, the pooled proportion of nurses with good knowledge of surgical site infection prevention is 62% (95% CI: 50-74%) when assessed using a dichotomous scale. However, when knowledge is measured using a three-point Likert scale, the pooled proportion of those with good knowledge drops to 46% (95% CI: 21-72%), with an additional 27% (95% CI: 16-38%) demonstrating fair or moderate knowledge.Conclusion and recommendationThis systematic review and meta-analysis is the first to synthesize data on nurses' knowledge of surgical site infection (SSI) prevention. The findings reveal poor knowledge levels, highlighting the need for targeted educational interventions globally. While the pooled odds ratio is not statistically significant, training, longer service years, and higher education improve SSI prevention knowledge by enhancing critical thinking, boosting confidence, and fostering adherence to evidence-based practices. Future research should focus on identifying factors influencing nurses' knowledge, particularly through longitudinal and interventional studies. Policymakers should incorporate international guidelines such as those recommended by the World Health Organization (WHO) and the Centers for Disease Control and Prevention (CDC) into nursing curricula, supported by robust assessment tools and educator training, to improve knowledge transfer and implementation of best practices.

BackgroundStunting is a vital indicator of chronic undernutrition that reveals a failure to reach linear growth. Investigating growth and nutrition status during adolescence, in addition to infancy and childhood is very crucial. However, the available studies in Ethiopia have been usually focused in early childhood and they 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 stunting among adolescent girls in Ethiopia.MethodsA total of 3156 weighted samples of adolescent girls aged 15-19 years were used from the 2016 Ethiopian Demographic and Health Survey dataset. The data was pre-processed, and 80% and 20% of the observations were used for training, and testing the model, respectively. Eight machine learning algorithms were included for consideration of model building and comparison. The performance of the predictive model was evaluated using evaluation metrics value through Python software. The synthetic minority oversampling technique was used for data balancing and Boruta algorithm was used to identify best features. Association rule mining using an Apriori algorithm was employed to generate the best rule for the association between the independent feature and the targeted feature using R software.ResultsThe random forest classifier (sensitivity = 81%, accuracy = 77%, precision = 75%, f1-score = 78%, AUC = 85%) outperformed in predicting stunting compared to other ML algorithms considered in this study. Region, poor wealth index, no formal education, unimproved toilet facility, rural residence, not used contraceptive method, religion, age, no media exposure, occupation, and having one or more children were the top attributes to predict stunting. Association rule mining was identified the top seven best rules that most frequently associated with stunting among adolescent girls in Ethiopia.ConclusionThe random forest classifier outperformed in predicting and identifying the relevant predictors of stunting. Results have shown that machine learning algorithms can accurately predict stunting, making them potentially valuable as decision-support tools for the relevant stakeholders and giving emphasis for the identified predictors could be an important intervention to halt stunting among adolescent girls.

Objective To assess the determinants of knowledge of preconception care (PCC) among healthcare providers in Ethiopia.Design Systematic review and meta-analysis.Data source Comprehensive literature searches were conducted in PubMed, Scopus and Health Internetwork Access to Research Initiative (HINARI) published until 20 March 2024.Eligibility criteria for selecting studies Primary studies that reported the prevalence, determinants or associated factors were included.Data extraction and analysis Three authors extracted all the relevant data using a standardised Joanna Briggs Institute data extraction format. Meta-analysis was done using a random-effects model. A funnel plot and Egger’s test were done to assess publication bias, which was corrected by trim and fill analysis.Result Out of 102 studies, the final analysis included six studies involving 2758 healthcare providers. The pooled knowledge of PCC among healthcare providers in Ethiopia was determined to be 51.43% (Adjusted OR), with a 95% CI ranging from 41.21% to 61.65%. Several factors were identified as determinants of healthcare providers’ knowledge based on the pooled estimate. These factors include having an educational qualification above a BSc degree (OR=2.36, 95% CI 1.46, 3.08), the presence of guidelines in their institution (OR=2.07, 95% CI 1.37, 2.77), working in hospitals (OR=2.68, 95% CI 1.83, 3.53) and receiving training on PCC and related topics (OR=4.05, 95% CI 2.52, 5.59).Conclusion Healthcare professionals exhibited limited knowledge of PCC in Ethiopia. Key elements influencing their comprehension encompass advanced educational credentials beyond a BSc degree, adherence to institutional guidelines, employment in hospital settings and exposure to specialised training. The ORs linked to these factors highlight the substantial influence of education, institutional procedures, hospital roles and specific training in enhancing healthcare providers’ expertise. Enhancing awareness and understanding among healthcare practitioners through customised educational programmes, institutional structures and organised training efforts stands out as a crucial approach to improve healthcare services and results throughout Ethiopia.PROSPERO registration number CRD42024516077.

Objectives To identify the determinants of traditional birth attendants’ utilisation among reproductive-age women in Ethiopia.Design Cross-sectional study design.Setting Ethiopia.Participants A total of 3979 weighted samples of reproductive-age women were included.Outcome measure Traditional birth attendant utilisation.Results This study found a high prevalence (29.76%) of Ethiopian mothers using traditional birth attendants for delivery, based on data from the 2019 Ethiopian Demographic and Health Survey. Mothers with higher education (adjusted OR (AOR)=0.11, 95% CI: 0.01 to 0.62), who had four or more antenatal care visits (AOR=0.34, 95% CI: 0.21 to 0.54), communities with lower levels of education (AOR=2.21, 95% CI: 1.30 to 3.73), communities with higher poverty levels (AOR=1.71, 95% CI: 1.99 to 2.96) and those from peripheral regions (AOR=3.41, 95% CI: 1.77 to 6.56) were found to be predictors of traditional birth attendants.Conclusion This study indicates a high prevalence (29.76%) of Ethiopian mothers using traditional birth attendants, highlighting the need for targeted interventions to promote skilled birth attendance. Policymakers should focus on implementing educational programmes targeting reproductive-age women and improving access to quality antenatal care. Specific initiatives could include community-based educational workshops and subsidies for transportation to healthcare facilities. Furthermore, mothers in remote and border districts should receive specialised attention in terms of resource allocation, including skilled personnel and enhanced healthcare access.

IntroductionPeripheral neuropathy is a nerve disorder that causes pain, numbness, and tingling in different parts of the body. It is a major and common clinical problem associated with several chemotherapeutic medications frequently used in cancer treatment, with prevalence rates ranging from 19% to 85%. To the best of the authors’ knowledge, there is a lack of data on the magnitude and determinants of chemotherapy-induced peripheral neuropathy in Ethiopia.ObjectiveThis study aimed to assess the magnitude and associated factors of chemotherapy-induced peripheral neuropathy among adult cancer patients undergoing chemotherapy in northwest Ethiopia oncology centers in 2022.MethodAn institutional-based cross-sectional study was conducted on 406 eligible adult cancer patients undergoing chemotherapy in northwest Ethiopia oncology centers, between May and July 2022.ResultsOut of 406 adult cancer patients included in the study, 54.4% had peripheral neuropathy. The stage of cancer (AOR = 4.36 [95% CI: 1.76; 10.8]), comorbidity (AOR = 2.74 [95% CI: 1.28; 5.83]), drug regimen (AOR = 2.99 [95% CI: 1.36; 6.54]), and cycle of therapy (AOR = 4.00 [CI: 1.67; 9.65]) were significantly associated with the magnitude of chemotherapy-induced peripheral neuropathy.ConclusionChemotherapy-induced peripheral neuropathy is a common adverse event among Ethiopian cancer patients treated with various chemotherapeutic drugs. Therefore, it is necessary to establish more effective diagnostic methods and incorporate validated assessment tools, such as the European Organization for Research and Treatment of Cancer tools, either alone or in combination with other clinical instruments, into the routine evaluation of all patients receiving chemotherapeutic drug.

IntroductionResilience is the dynamic adaptive process of maintaining or recovering mental health from stressors, such as trauma, challenging life circumstances, critical transitions, or physical illnesses. Resilience after adversity can be fostered through protective factors and the implementation of interventions that promote resilience. Hence, it is essential to investigate both protective and vulnerable factors to reduce the negative effects of unfavorable life events and increase resilience through positive risk-response interventions.ObjectiveTo assess the effect of previous adversity, protecting factors, and resilience-promoting interventions to possess resilience after adversity in a global context.MethodsThe study included English language articles sourced from PubMed, Embase, Scopus, Web of Sciences, the Cochrane Database of Systematic Reviews, Scopus, and Google Scholar published before 15 April 2024. These articles reported the effect of adversity, protecting factors, and/or resilience-promoting interventions to possess resilience after adversity in a global context without a population age limitation. The quality of the included studies was assessed using the Assessment of Multiple Systematic Reviews. A weighted inverse-variance random-effects model was applied to find the pooled estimates. The subgroup analysis, heterogeneity, publication bias, and sensitivity analysis were also assessed.ResultsA total of 44 articles (n = 556,920 participants) were included in this umbrella review. From the random-effects model analysis, the pooled effect of adversity on the development of resilience was 0.25 (p < 0.001). The pooled effects of adversity-protective factors and resilience-promoting interventions after adversity were 0.31 (p < 0.001) and 0.42 (p < 0.001), respectively. The pooled effects of specific adversity protective factors were 0.26, 0.09, 0.05, 0.34, 0.23, and 0.43 for the availability of support, cognitive ability, community cohesion, positive self-perception, religious involvement, and self-regulation, respectively. The pooled effects of specific resilience-promoting interventions were 0.30, 0.21, 0.51, and 0.52 for cognitive behavior therapy (CBT) interventions, mindfulness-based interventions, mixed interventions, and resilience-promoting interventions, respectively.ConclusionThe findings of this umbrella review revealed that people who experienced early adversity can develop resilience later in life. The study highlights the need to consider adversity protective factors, such as availability of support (family, friends, and school), cognitive ability, community cohesion, positive self-perception, religious involvement, and self-regulation, and resilience-promoting interventions, including CBT interventions, mindfulness-based interventions, and mixed interventions, to enhance resilience promotion programs.

Abstract 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.

IntroductionAttention-deficit hyperactivity disorder (ADHD) is a neuropsychiatric condition that affects children. Its magnitude varies by area, ranging from 0.2% to 26.8%. Even though there is debate, culture and geographical location may have little or no influence on the epidemiology of ADHD worldwide. Despite this variation, debate over the national prevalence and location of ADHD is unknown in Ethiopia. Therefore, this study aimed to assess the pooled prevalence of ADHD and its contributing factors among children.MethodsElectronic databases, including Google Scholar, PubMed, Scopus, EMBASE, Web of Science, ScienceDirect, and institutional repositories, were searched. The studies that covered the prevalence and/or risk factors of ADHD in children were included in the collection. The Joanna Briggs Institute quality rating tool was used to rate the quality of each study. The data were extracted using Microsoft Excel 2019, and the statistical analysis was performed using STATA 17.0. Using a random-effects model, we evaluated the combined prevalence of ADHD and associated factors. The Cochrane Q-test and I2 test statistics were used to quantify the heterogeneity. Furthermore, publication bias was examined using funnel plot graphs and Egger's tests. A Galbraith plot was employed to illustrate outliers. Sensitivity analysis was also applied.ResultThis study included a total of six articles with 4,338 participants. The pooled prevalence estimate of ADHD was 8.81% [95% confidence interval (CI), 4.52–13.11; I2 = 96.95%; P = 0.001]. Age 6–12 [adjusted odds ratio (AOR) = 3.51 (95% CI, 1.38–5.64), I2 = 0%; P = 0.001], being male [AOR = 1.94 (95% CI, 1.09–2.79), I2 = 0%; P = 0.001], and living with a single parent [AOR = 4.92 (95% CI, 1.24–861), I2 = 0%; P = 0.001] were significant variables.Conclusion and recommendationOne out of every 12 children in Ethiopia suffers from ADHD. Living with a single parent, being male, and being between the ages of 6 and 12 were risk factors for ADHD. A nationwide study with a large sample size may be required to ascertain the true impact of ADHD. It may be crucial to improve school health services to identify ADHD early and lessen its long-term effects.

BackgroundAlthough 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.MethodsA 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.ResultsAccording 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.ConclusionThe 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.

Abstract Attrition rate is higher in developing nations and it leftovers a major obstacle to enhance the benefits of therapy and achieve the 90–90–90 plan targets. Despite this fact, data on the incidence and its predictors of attrition among human immune deficiency virus infected children on antiretroviral therapy are limited in developing countries including Ethiopia especially after the test and treat strategy implemented. This study aimed to assess the incidence and predictors of attrition among human immune deficiency virus infected children on antiretroviral therapy in Amhara Comprehensive Specialized Hospitals, Northwest Ethiopia. A retrospective follow-up study was conducted among 359 children on ART from June 14, 2014, to June 14, 2022. Study participants were selected using simple random sampling method and the data were collected using Kobo Toolbox software and analysis was done by STATA version 14. Both bi-variable and multivariable Cox regression models were fitted to ascertain predictors. Lastly, an AHR with a 95% CI was computed and variables with a p-value of

Abstract Background Nurses with reduced work ability had a high risk of disability pension, sickness absences, retirement intention, and leave their job and profession early. Nurses frequently suffer from job related stress, occupational fatigue and sleep problems, which can further compromise their work ability. Aims of the study The aim of this study was to assess perceived work ability and its associated factors among nurses working in the Northwest of Amhara regional state Referral Hospitals, Northwest Ethiopia, 2022. Methods A multicenter, an institutional based, cross-sectional study was conducted among 410 nurses working in five selected Referral hospitals, found in the Northwest of Amhara regional state, Northwest Ethiopia, 2022. The data were collected using a structured, self-administered questionnaire and entered using Epi info version 7.2.5 software, analyzed using SPSS version 25. Summary statistics (median or IQR for continuous data and frequency and percentage for categorical variables) were used. The ordinal logistic regression was used to assess’ the presence of association between dependent and independent variables. Results The findings of this study revealed that 59.0% of nurses had poor level of work ability, whereas 34.4% and 6.6% of nurses had sub-optimal and optimal level of work ability respectively. Multivariable ordinal logistic regression revealed that being male [AOR = 2.43; 95% CI (1.52, 3.91)], being BSC nurse [AOR = 0.21; 95% CI (0.08, 0.51)], nurses who had poor sleep quality [AOR = 0.34; 95% CI (0.12, 0.98)] and nurses who had chronic disease [AOR = 0.18; 95% CI (0.08, 0.41)] were significantly associated with nurses’ level of work ability, p-value

Cerebral palsy (CP) is the most common motor disability in childhood which causes a child's behavioral, feeding, and sleep difficulties. It remains a poorly studied health problem in Africa. The main aim of this study was assessing the pooled prevalence of Cerebral Palsy (CP) and its clinical characteristics in Africa context. Systematic review and meta-analysis were conducted using Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines to search articles from electronic databases (Cochrane library, Ovid platform) (Medline, Embase, and Emcare), Google Scholar, CINAHL, PubMed, Maternity and Infant Care Database (MIDIRS). The last search date was on 12/05/ 2023 G. C. A weighted inverse variance random-effects model was used to estimate the pooled estimates of cerebral palsy and its types. The subgroup analysis, publication bias and sensitivity analysis were done. Studies on prevalence and clinical characteristics of cerebral palsy were included. The primary and secondary outcomes were prevalence and clinical characteristics of cerebral palsy respectively. A total of 15 articles with (n = 498406 patients) were included for the final analysis. The pooled prevalence of cerebral palsy in Africa was found to be 3·34 (2·70, 3·98). The most common type is spastic cerebral palsy accounting 69·30% (66·76, 71·83) of all cases. The second one is quadriplegic cerebral palsy which was found to be 41·49% (33·16, 49·81). Ataxic cerebral palsy accounted 5·36% (3·22, 7·50). On the other hand, dyskinetic cerebral palsy was found to be 10.88% (6·26, 15·49). About 32·10% (19·25, 44.95) of cases were bilateral while 25·17% (16·84, 33·50) were unilateral. The incidence of cerebral palsy in Africa surpasses the reported rates in developed nations. Spastic and quadriplegic subtypes emerge as the most frequently observed. It is recommended to channel initiatives toward the strategic focus on preventive measures, early detection strategies, and comprehensive management protocols.

Introduction: Turnover intention measures the likelihood that a nurse may soon depart from their current job or that the organization might be considering terminating nurses from their positions. It serves as a reliable predictor of actual turnover. Turnover intention results in deterioration in the standard of nursing care, compromise in patient safety, drop in customer service standards, and inadequate healthcare management. Methods: A cross-sectional study was conducted among 385 nurses employed in three selected government hospitals located in Bahir Dar city, Amhara region. Data collection employed a self-administered questionnaire, with entries managed through EpiData version 4.6 and subsequently transferred to STATA version 14 for coding, cleaning, and analysis. Binary logistic regression was employed to assess the association between dependent and independent variables. Variables with a p-value

Abstracts: Background: Lower limb lymphoedema, characterized by persistent swelling in the legs due to lymphatic dysfunction, not only imposes a physical burden but is also associated with significant mental depression. While emerging research suggests a strong link between lower limb lymphoedema and depression, the extent of the problem remains underexplored. This study aims to investigate the relationship between lower limb lymphoedema and mental depression through a meta-analysis of existing studies. Methods: A comprehensive search was conducted across databases including PubMed, MEDLINE, EMBASE, International Scientific Indexing, Web of Science, and Google Scholar. Study quality was assessed using the Joanna Briggs Institute (JBI) critical appraisal tool. A weighted inverse variance random-effects model was used for pooled estimates, along with subgroup analysis, heterogeneity assessment, publication bias testing, and sensitivity analysis. The prediction interval was computed to estimate where future observations may fall. The review protocol was registered in PROSPERO (CRD42024541596). Results: Thirteen studies involving 3503 patients with lower limb lymphoedema due to lymphatic filariasis, podoconiosis, or leprosy were included. The pooled estimate of depression related to lower limb lymphoedema was 38.4 % (95 % CI: 26.3 %, 50.5 %). High heterogeneity (I2 = 81.48 %) highlighted significant variability among the studies. Depression was more prevalent among leprosy patients (38.1 %) and podoconiosis patients (36.4 %), showing little difference between the two. However, the prevalence was notably lower among those with lymphatic filariasis (22.4 %). A higher prevalence of depression was found in Africa (39.4 %) compared to other regions (36.1 %). Conclusion: Patients with lower limb lymphoedema experience disproportionately high rates of mental depression compared to the general population. Integrating mental health assessment and treatment into care packages for lymphoedema management is essential, with special attention needed for leprosy patients.

IntroductionAcute coronary syndrome (ACS) is the most common cause of morbidity and mortality in patients with coronary heart disease. Furthermore, the recurrence of this problem has significant adverse outcomes. However, there is insufficient information pertaining to this problem in Ethiopia; hence, this study aims to assess the incidence rate and identify the predictors of ACS recurrence in the West Amhara region.MethodsA retrospective follow-up study was conducted among 469 patients diagnosed with primary ACS. Data from the patient chart were collected using a pre-tested structured data extraction tool. The study employed the Weibull regression analysis model, and the effect size was measured using an adjusted hazard ratio (HR) with a 95% confidence interval (CI). The statistical significance of the findings was established based on a p-value