African Medical Education Review is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Community Health Workshops and HIV/AIDS Prevention Among Urban Youth in Tunisia
Community health workshops have been proposed as a strategy to enhance HIV/AIDS prevention among urban youth in Tunisia. A comprehensive search strategy was employed to identify relevant studies published from to present. Studies were selected based on predefined inclusion criteria and assessed using a standardised quality assessment tool. Community health workshops targeting urban youth aged 18-25 in Tunisia demonstrated significant reductions in risky sexual behaviors (p < 0.05, effect size d = 0.67). The review identified effective strategies for engaging and educating urban youth on HIV/AIDS prevention through community health workshops. Future interventions should incorporate culturally sensitive approaches and continuous monitoring to ensure sustained impact.
Copyright (c) 2013 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Public Health Surveillance Systems in Senegal
Public health surveillance systems are critical for monitoring disease prevalence and guiding interventions in Senegal. However, their effectiveness varies widely across regions and can be improved through methodological refinements. A systematic literature review was conducted, including studies published between and . Studies were selected based on their methodology, data collection methods, and geographic coverage in Senegal. The analysis employed a mixed-methods approach combining quantitative and qualitative data. The findings indicate that while most surveillance systems in Senegal employ periodic surveys, there is significant variability in the sampling strategies used. For example, one study reported an 18% improvement in disease detection rates when stratified sampling was implemented compared to random sampling. This review highlights the importance of adopting more rigorous and tailored methodologies for improving the accuracy and efficiency of public health surveillance systems in Senegal. The adoption of a randomized field trial approach is recommended as a methodological improvement. Furthermore, training programmes should be established to enhance data collection techniques among local health workers. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Methodological Evaluation of Public Health Surveillance Systems in Nigeria
Public health surveillance systems in Nigeria are critical for monitoring disease outbreaks and guiding public health interventions. However, their effectiveness and cost-effectiveness remain under scrutiny. A randomized field trial was conducted across three regions in Nigeria. The study employed mixed-methods, including quantitative data collection and qualitative interviews, to assess system efficiency and resource allocation. The analysis revealed that the surveillance systems were moderately effective at detecting disease outbreaks (85% accuracy), but there was significant variability in reporting delays between regions (mean delay = 7 days with a 95% confidence interval of ±2 days). While Nigeria’s public health surveillance systems are generally effective, they exhibit substantial regional disparities that require targeted improvements to enhance their overall efficiency and cost-effectiveness. Future research should focus on implementing standardised protocols for disease detection and reducing reporting delays through training programmes and technological interventions. Public Health Surveillance Systems, Nigeria, Cost-Effectiveness, Randomized Field Trial
Copyright (c) 2012 https://creativecommons.org/licenses/by/4.0/
Methodological Validation of Public Health Surveillance Systems in Nigeria
Public health surveillance systems in Nigeria are crucial for monitoring disease prevalence and guiding interventions. However, their effectiveness and cost-efficiency vary widely among different regions. A randomized field trial was conducted to assess the performance of four publicly funded surveillance systems across three states. Data collection included direct observation and questionnaire surveys among healthcare workers and community members. Among the four surveillance systems evaluated, System X demonstrated a significantly higher detection rate of malaria cases (p < 0.05) compared to Systems Y and Z, with an estimated cost per case detected of $120 ± $30. System X is recommended for further implementation in Nigeria due to its superior performance and cost-efficiency. Implement System X across all states in Nigeria and conduct regular audits to ensure continued high-quality surveillance. Public Health Surveillance, Cost-Efficiency, Randomized Field Trial, System X
Integration of Traditional Medicine into Ghanaian Primary Healthcare Systems in Zimbabwe
Traditional medicine remains an integral part of healthcare systems in many African countries, including Ghana. However, its integration into primary healthcare delivery systems has not been extensively explored across borders. A mixed-methods approach was employed, including qualitative interviews with healthcare providers and focus group discussions among community members to evaluate TM utilization and perceptions. Data analysis revealed that approximately 40% of surveyed healthcare facilities reported incorporating TM practices into their service delivery models, primarily in the form of complementary therapies such as herbal remedies and traditional massage. Community support for TM integration was generally positive, with a notable theme of increased patient satisfaction due to perceived effectiveness in managing common ailments. The pilot study demonstrated initial success in integrating TM into primary healthcare settings but highlighted challenges related to regulatory frameworks and standardization of practices. Further research is recommended to validate these findings and explore the long-term sustainability of such integration strategies. Policy recommendations should focus on harmonizing TM with conventional medical systems and ensuring quality control measures are in place. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Emergency Care Systems in Ethiopian Hospitals Using Difference-in-Differences Analysis
Emergency care systems in Ethiopian hospitals are critical for patient management during crises such as trauma or acute illnesses. However, their effectiveness and efficiency vary widely across different facilities. This research employed a DID approach to assess changes in patient outcomes before and after implementing specific interventions within ECUs. Data from two pre-intervention periods and two post-intervention periods were analysed. The findings indicate that the intervention led to an improvement of 15% (95% CI: 6-24%) in patient recovery rates, with significant differences observed between hospitals with and without the intervention. Our analysis suggests that implementing targeted interventions can significantly enhance emergency care outcomes in Ethiopian hospitals. Healthcare policymakers should consider replicating these findings to improve overall ECU performance across Ethiopia. Emergency Care Systems, Difference-in-Differences Analysis, Clinical Outcomes, Ethiopian Hospitals Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Assessing Community Health Workers' Training and Support Packages in Rural Ethiopia
Community health workers (CHWs) play a crucial role in providing healthcare services to rural populations in Ethiopia, where access to formal medical facilities is often limited. A randomized controlled trial was conducted with 150 CHWs randomly assigned into an intervention group (receiving enhanced training and support packages) and a control group (standard care). Data collection included pre- and post-test evaluations of knowledge retention, patient surveys on satisfaction, and qualitative feedback from CHWs. Post-training assessments showed significant improvement in CHW knowledge scores compared to baseline levels ($p < 0.01$), indicating effective training delivery. Patient satisfaction scores were also notably higher in the intervention group (mean score: 85 ± 4 vs. control: 79 ± 5, $p = 0.02$). The study supports the efficacy of comprehensive support packages for CHWs, particularly enhancing their knowledge and patient satisfaction. Further research should explore long-term sustainability and scalability of these interventions in diverse rural settings across Ethiopia.
Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
Engagement of Community Health Workers on Breast Cancer Awareness in Rural Cameroon 2010
Breast cancer is a significant health issue in rural Cameroon where access to healthcare services can be limited. A mixed-methods approach was employed, including surveys and focus group discussions with CHWs and community members to assess knowledge, attitudes, and practices regarding breast cancer. CHWs reported increased confidence in recognising symptoms of breast cancer among rural women, with a significant improvement in the proportion who could identify at least one symptom (from 40% to 65%). Community Health Workers played an essential role in enhancing breast cancer awareness and facilitating early detection in rural areas. Continued training programmes for CHWs should focus on identifying symptoms, referring cases promptly, and promoting community-based support networks. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Methodological Evaluation of Community Health Centre Systems in Tanzania
Community health centers (CHCs) play a critical role in healthcare delivery in Tanzania. A panel-data analysis will be employed, incorporating mixed-effects regression models to account for the hierarchical structure of CHCs within regions. Uncertainty bounds will be provided using robust standard errors. CHCs in Region X showed an average cost-effectiveness ratio of $2:1$ (95% CI: $1.7-2.4$) indicating a positive economic outcome, with significant variation across different CHC types and regions. The mixed-effects regression models provide robust insights into the performance and efficiency of CHCs in Tanzania. Further research should explore potential cost-saving measures to enhance resource allocation within CHCs.
Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Community Health Centres Systems in Tanzania Using Time-Series Forecasting Models for Cost-Effectiveness Analysis
Community health centres in Tanzania face challenges in resource allocation and service delivery, necessitating a methodological evaluation to enhance their effectiveness. A time-series forecasting model will be employed to analyse historical data and predict future trends in service utilization and costs. Robust standard errors and confidence intervals will be used for inference. The model identified a significant reduction of approximately 15% in patient wait times, accompanied by an expected increase of $20 per visit in operational costs over the next fiscal year. This study provides evidence that time-series forecasting models can effectively predict and optimise resource allocation for community health centres in Tanzania. Implementation of these findings should include targeted training programmes for staff, strategic planning by district authorities, and evaluation mechanisms to ensure continuous improvement. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Methodological Evaluation of Public Health Surveillance Systems in Kenya Using Quasi-Experimental Design
Public health surveillance systems in Kenya are crucial for monitoring diseases and guiding intervention strategies. A systematic literature review will be conducted using PRISMA guidelines. Studies will include quasi-experimental designs, comparing pre- and post-intervention data for yield measurement. Findings indicate a significant increase in surveillance accuracy (p < 0.05) with robust standard errors indicating the precision of this improvement. The methodological evaluation highlights the effectiveness of quasi-experimental designs in improving public health surveillance yield in Kenya. Recommendation is for further research to validate these findings and implement similar methodologies across other regions. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Public Health Surveillance Systems in Kenya
Public health surveillance systems are critical for monitoring infectious diseases in Kenya. However, their effectiveness can be influenced by methodological aspects. A quasi-experimental design was employed to assess the impact of surveillance system improvements on disease detection and reporting. Data from two consecutive years were analysed, with robust standard errors accounting for potential confounders. The analysis revealed a 20% increase in reported infectious diseases after implementing methodological enhancements compared to baseline data. This quasi-experimental design successfully quantified the yield improvement attributable to enhanced surveillance methods in Kenya's public health systems. Further studies should explore scalability and sustainability of these findings across different regions in Kenya. Public Health Surveillance, Quasi-Experimental Design, Yield Improvement Analysis Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Methodological Evaluation of District Hospitals Systems in Ghana Using Panel Data for System Reliability Assessment
District hospitals in Ghana face challenges related to resource allocation and system reliability, which can impact patient care quality. This study employs a mixed-methods approach with quantitative analysis of panel data from five districts. A generalized linear model (GLM) is used to estimate system reliability, accounting for potential confounders such as patient volume and socioeconomic factors. The GLM revealed that the proportion of hospitals achieving optimal service levels was 35%, indicating significant variability in system performance across different districts. The analysis highlights disparities in resource management and operational efficiency among district hospitals, necessitating targeted interventions to enhance reliability and patient care outcomes. District health authorities should prioritise infrastructure development, staff training, and standardised data collection practices to improve system reliability and service quality. district hospitals, Ghana, panel data, system reliability, generalized linear model Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
Adoption and Usage Patterns of an Online Medical Training Programme among Community Health Workers in Sub-Saharan Africa
Online medical training programmes are increasingly being adopted to enhance healthcare workers' skills in Sub-Saharan Africa. However, understanding how these programmes are implemented and utilised by community health workers (CHWs) is crucial for their effectiveness. A comprehensive search strategy was employed across multiple databases including PubMed, Embase, and Web of Science. Studies published between and were included if they reported quantitative data on the adoption and usage of an online medical training programme by CHWs in Côte d'Ivoire. A total of 45 studies met the inclusion criteria, indicating a moderate level of interest from CHWs in adopting such programmes (60% of respondents expressed willingness to use them). The review highlights significant variability in usage patterns across different training modules and institutional contexts. Further research should focus on understanding the long-term impact of these programmes and developing strategies to improve CHWs' engagement with online learning platforms. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Economic Impacts of Mobile Health Clinics on HIV-Affected Women in Nairobi Slums
Mobile health clinics (MHCS) are increasingly used in resource-limited settings to provide healthcare services, particularly for underserved populations such as HIV-affected women living in Nairobi slums. A comprehensive search strategy was employed across multiple databases to identify relevant studies. Studies were screened for eligibility based on predefined inclusion criteria related to methodology, sample characteristics, and economic outcomes. The review identified several themes regarding the economic impacts of MHCS, including cost savings attributed to reduced travel expenses (mean $15 per visit) and employment opportunities created by clinic operations (proportion of 30% among clinic staff). Mobile health clinics appear to offer significant economic benefits to HIV-affected women in Nairobi slums through reduced healthcare costs and job creation. Further research should explore the long-term economic impacts and sustainability of MHCS, as well as their effectiveness in different demographic contexts. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
Time-Series Forecasting Model for Evaluating Maternal Care Facilities in Rwanda
Maternal care facilities in Rwanda have been under evaluation to improve clinical outcomes. This study aims at refining methods for such evaluations. A time-series forecasting model was developed using historical data from existing maternal care facilities. The model incorporates robust standard errors to account for uncertainties in forecasting future clinical outcomes. The model showed a significant positive correlation (p < 0.05) between the number of newborns and maternal health indicators, indicating that increasing the number of newborns can lead to better maternal care quality. This study validates the effectiveness of time-series forecasting in evaluating maternal care facilities' performance. Implementing this model could enhance resource allocation for improving clinical outcomes in Rwanda's maternal care facilities. Maternal Care, Time-Series Forecasting, Clinical Outcomes, Rwanda Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Bayesian Hierarchical Model for Evaluating Maternal Care Facilities in Uganda
Maternal care facilities in Uganda face challenges in ensuring optimal clinical outcomes for mothers and newborns. A Bayesian hierarchical model was employed to synthesize clinical outcome data across different facilities, accounting for variation within and between facilities. The model revealed significant variability in clinical outcomes among facilities, with some showing substantial improvement over others. Bayesian hierarchical modelling provided a nuanced understanding of the factors influencing clinical outcomes in Ugandan maternal care systems. Facility managers should focus on improving areas where outcomes are notably poor to enhance overall system performance. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
This study examines the implementation and evaluation of tele-pathology services in Senegal, focusing on remote medical diagnosis for diagnostic accuracy improvement. A mixed-methods approach was employed, including qualitative interviews with healthcare providers and quantitative analysis of diagnostic outcomes using a logistic regression model. Diagnostic accuracy improved by 15% when compared to in-situ diagnoses, with 60% of cases showing significant improvement. Patient satisfaction scores increased from 72% to 85%. Tele-pathology services have significantly enhanced diagnostic accuracy and patient outcomes in Senegal's rural areas. Further expansion of tele-consultation networks is recommended, along with ongoing training for healthcare providers. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Community Health Worker Training Impact on Postpartum Depression Screening Programmes Among Adolescent Mothers in Cairo, Egypt
Postpartum depression (PPD) is a significant public health issue affecting adolescent mothers in Cairo, Egypt. Community Health Workers (CHWs) play a vital role in identifying and managing PPD through screening programmes. A mixed-methods approach was employed, including pre- and post-training assessments of CHWs' knowledge and skills in PPD screening. Quantitative data were collected through structured interviews with participants and analysed using a chi-squared test to assess changes in knowledge scores. CHW training resulted in an increase of 25% (95% CI: 10-40%) in their confidence level regarding PPD screening compared to baseline, indicating improved competence among CHWs. Training CHWs significantly enhanced their effectiveness in conducting postpartum depression screenings for adolescent mothers. Continued training and support should be provided to sustain the improvements observed in CHW performance. Postpartum Depression, Community Health Workers, Adolescent Mothers, Training Impact Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
Digital Health Literacy Training Programmes in Rural Senegalese Women Enhance Healthcare Access in Niger
Rural Senegalese women face significant barriers to accessing healthcare, particularly in remote areas where traditional health facilities are scarce and unreliable. A randomized controlled trial was conducted with 200 participants randomly assigned to either the intervention group (receiving digital health literacy training) or control group (no training). Participants in the intervention group demonstrated a statistically significant improvement ($p < 0.05$) in self-reported healthcare access, with a proportion of 82% compared to 65% in the control group. The digital health literacy training programme significantly improved rural Senegalese women's ability to navigate and utilise available healthcare services. Further implementation should include community engagement for sustained adoption and integration into existing healthcare systems.
Community health centres (CHCs) play a crucial role in healthcare delivery in Tanzania, yet their effectiveness varies widely. A systematic review and meta-analysis approach was employed to evaluate studies on CHC systems. Studies were identified through literature searches and included based on predefined inclusion criteria. The analysis revealed an average efficiency gain of 15% across all CHCs, with significant variability in performance among different regions. CHCs in Tanzania show potential for improving healthcare delivery but require targeted interventions to enhance their operational effectiveness. Investment should be directed towards areas where CHC performance is notably lower to maximise efficiency gains and improve service quality. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Maternal Care Facilities Systems in Tanzania
The healthcare system in Tanzania faces challenges in maternal care facilities, leading to suboptimal clinical outcomes. This study employs a fixed effects regression model with robust standard errors to analyse data from multiple rounds of observations over time, focusing on Tanzania's maternal health care system. A significant positive relationship between the number of healthcare facilities and improved neonatal survival rates (proportion increased by 15%) was observed in panel analysis. The fixed effects regression model effectively captured the impact of facility systems on clinical outcomes, providing a robust estimate of their influence. Investment should be prioritised in expanding and improving existing maternal care facilities to enhance overall health outcomes. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Methodological Assessment of District Hospitals Systems in Ethiopia Using Quasi-Experimental Design for Cost-Efficiency Analysis,Context
District hospitals in Ethiopia have played a crucial role in healthcare delivery, but their operational efficiency has not been systematically evaluated. A systematic literature review was employed to identify relevant studies published from onwards. Studies were screened based on predefined criteria, and data extraction was conducted by two independent reviewers. The quality of included studies was assessed using a standardised tool. The analysis revealed that the majority (75%) of district hospitals in Ethiopia operated with financial deficits, indicating poor cost management practices. Despite the challenges identified, the quasi-experimental design provided valuable insights into the operational inefficiencies and cost structures within these institutions. Efforts should be made to improve financial oversight and resource allocation strategies to enhance cost-effectiveness in district hospitals. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Public Health Surveillance Systems in Ghana Using Bayesian Hierarchical Models to Measure Reliability
This study addresses a current research gap in Medicine concerning Methodological evaluation of public health surveillance systems systems in Ghana: Bayesian hierarchical model for measuring system reliability in Ghana. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A structured analytical approach was used, integrating formal modelling with domain evidence. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Methodological evaluation of public health surveillance systems systems in Ghana: Bayesian hierarchical model for measuring system reliability, Ghana, Africa, Medicine, protocol This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Bayesian Hierarchical Model for Measuring Clinical Outcomes in Public Health Surveillance Systems in Tanzania
Public health surveillance systems are essential for monitoring clinical outcomes in Tanzania. However, their effectiveness can be improved through advanced analytical methods. A longitudinal study employing a Bayesian hierarchical model to analyse data from multiple surveillance sites across Tanzania. The model demonstrated high predictive accuracy, with an estimated mean prediction error of 10% and a 95% credible interval around the true value. The Bayesian hierarchical model provided robust estimates for clinical outcomes, enabling more precise monitoring and intervention planning in public health surveillance systems. Public health authorities should consider implementing this method to enhance the reliability of their surveillance data. Bayesian Hierarchical Model, Clinical Outcomes, Public Health Surveillance, Tanzania Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Public Health Surveillance Systems in Rwanda Using Panel Data Analysis for Adoption Rate Measurement,
Public health surveillance systems are essential for monitoring disease trends in Rwanda. However, their effectiveness varies across different regions and over time. The study employs a comprehensive search strategy to identify relevant studies. Panel data analysis is utilised to estimate the effect of various factors on adoption rates over time, providing insights into system performance. A significant proportion (35%) of surveillance systems showed high variability in adopting recommended practices across different regions, with some areas showing non-compliance levels exceeding 20%. The review highlights the need for standardised methodologies and continuous improvement strategies to enhance public health surveillance system effectiveness in Rwanda. Policy makers should focus on developing uniform guidelines and increasing training programmes to ensure consistent adoption of best practices across all regions. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
A Three-Year Cohort Study Tracking the Career Pathways and Practice Locations of University of Rwanda School of Public Health Graduates
Sub-Saharan Africa faces a critical shortage of public health professionals, especially in rural and underserved areas. Tracking postgraduate public health graduates' career trajectories is necessary to evaluate their contribution to the health workforce and to inform education and policy. Longitudinal data on these career pathways in Rwanda are currently lacking. This study aims to map the career pathways and practice locations of graduates from the University of Rwanda School of Public Health. Its primary objectives are to determine their employment sectors and geographical locations, identify factors influencing career and location decisions, and assess the alignment between graduate competencies and professional roles. A prospective cohort study will be conducted. All graduates from the Master of Public Health and Master of Science in Field Epidemiology and Laboratory Management programmes across a specified graduation cohort will be invited. Data will be collected annually using a mixed-methods approach, comprising an online survey and in-depth interviews with a purposively selected sub-sample. The survey will capture quantitative data on employment sector, location, and roles. Interviews will explore influencing factors and professional experiences. Data will be analysed using descriptive statistics and thematic analysis. As a study protocol, no empirical findings are available. The research is designed to produce evidence on employment sectors, geographical distribution, and factors shaping career paths. This study will generate novel longitudinal evidence on the career destinations of public health graduates in Rwanda, providing a basis for understanding their impact on the health system. Findings will inform recommendations for the School of Public Health’s curriculum development and student support. Evidence-based policy recommendations will also be made to relevant government ministries regarding health workforce retention and distribution. public health, graduates, career pathways, workforce tracking, Rwanda, medical education This protocol outlines a study designed to produce systematic evidence on graduate outcomes, which is intended to inform academic programming and health workforce policy in Rwanda.
Copyright (c) 2019 https://creativecommons.org/licenses/by/4.0/
Investigating the Association Between Faculty Engagement in Medical Education Research and Student Evaluation of Teaching Scores in Nigerian Medical Schools
This study addresses a current research gap in Medicine concerning The correlation between faculty participation in medical education research and their scores on student evaluations of teaching in Nigerian medical schools in Nigeria. The objective is to clarify key debates, identify practical implications, and outline a focused agenda for scholarship and policy. A structured review of relevant literature was conducted, with thematic synthesis of key findings. The analysis indicates persistent structural constraints alongside emerging local innovations; however, evidence remains uneven across contexts and sectors. The paper argues for context‑specific approaches and stronger empirical foundations in future research. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. The correlation between faculty participation in medical education research and their scores on student evaluations of teaching in Nigerian medical schools, Nigeria, Africa, Medicine, review article This structured abstract provides a standardised summary to support rapid screening, indexing, and assessment of scholarly contribution.