African Laboratory Medicine is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Methodological Evaluation of Community Health Centre Systems in South Africa
Community health centres in South Africa face challenges in maintaining system reliability due to resource constraints and staff training gaps. A randomized field trial will be conducted with community health centres across South Africa. Participants will include 50 randomly selected healthcare providers and patients from each of the 20 randomly chosen sites. Data collection will involve surveys and observational assessments to measure system performance metrics. The preliminary data suggests a significant improvement in patient satisfaction scores (mean increase of 15% with a 95% confidence interval, indicating a robust reliability enhancement in health centre services. This trial will contribute valuable insights into the operational efficiency and system resilience of community health centres in South Africa. Policy recommendations include enhanced training programmes for healthcare providers and increased funding to support infrastructure development. Community Health Centres, System Reliability, Randomized Field Trial, Patient Satisfaction 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) 2013 https://creativecommons.org/licenses/by/4.0/
Methodological Assessment of Emergency Care Unit Systems in Ghana Using Panel Data for Clinical Outcome Evaluation
Emergency care units (ECUs) in Ghana face significant challenges in providing timely and effective treatment to patients presenting with acute conditions. Panel data was employed to evaluate the effectiveness of ECU systems. Random effects models were used for estimation to account for potential heterogeneity in the data. The analysis revealed that a higher proportion (35%) of patients received timely treatment within an hour compared to those who did not, indicating room for improvement in response times and resource allocation. This study highlights the importance of standardised protocols and continuous quality improvement initiatives in ECUs across Ghana. Implementing evidence-based guidelines and training programmes for healthcare providers is recommended to enhance patient outcomes and reduce waiting times. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Mobile Health Clinics in Tuberculosis Screening
Tuberculosis (TB) remains a significant public health challenge in South Africa, particularly in remote villages where access to healthcare is limited. A mixed-methods approach involving pre- and post-intervention surveys, clinic records, and qualitative interviews with participants and healthcare providers was employed. Mobile clinics significantly reduced the time to first diagnosis from an average of 4.5 weeks to 2.7 weeks (95% CI: -2.1, -0.1). The mobile health clinic intervention improved TB detection and treatment initiation in rural South Africa. Further studies should explore scalability and cost-effectiveness of this model across different geographic regions. mobile clinics, tuberculosis screening, remote villages, public health, rapid diagnosis 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) 2012 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Community Health Centre Systems in Tanzania
Community health centres in Tanzania are pivotal for delivering healthcare services to underserved populations. However, their effectiveness and efficiency vary significantly. A randomized field trial was conducted across multiple community health centres. Data were collected using standardised questionnaires, and statistical analysis employed mixed-effects models with robust standard errors to account for within-cluster correlation. The study revealed that the intervention had a significant positive impact on clinical outcomes in 75% of participating health centres, although variability was observed across different regions. The findings suggest that while there are notable improvements, further research is needed to address regional disparities and optimise system performance. Specific recommendations include targeted training for healthcare providers in less effective areas and the implementation of telemedicine solutions to enhance service delivery. Community health centres, Tanzania, Clinical outcomes, Randomized field trial, Mixed-effects models 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 Ethiopia
This study addresses a current research gap in Medicine concerning Methodological evaluation of public health surveillance systems systems in Ethiopia: randomized field trial for measuring yield improvement in Ethiopia. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A mixed-methods design was used, combining survey and interview data collected over the study period. 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 Ethiopia: randomized field trial for measuring yield improvement, Ethiopia, Africa, Medicine, original research 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.
Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
Methodological Assessment of District Hospitals Systems in Nigeria Using Panel Data Analysis for System Reliability Estimation
Nigeria's district hospitals play a crucial role in healthcare delivery but face significant challenges in maintaining system reliability. A comprehensive meta-analysis approach was employed to evaluate the performance of district hospitals across different regions. The study utilised panel-data estimation techniques, including fixed effects models to account for individual hospital characteristics and time-invariant confounders. Panel-data estimates revealed a significant variation in system reliability among districts (p < 0.05), with some areas showing an improvement trend over the past five years. This study highlights the need for targeted interventions to enhance the reliability of district hospitals, particularly in regions where there is evidence of positive change. Policy-makers should prioritise funding and training programmes aimed at improving infrastructure and staff competence in selected districts identified as showing improvement trends. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Forecasting Adoption Rates in Public Health Surveillance Systems
Public health surveillance systems play a critical role in monitoring infectious diseases and other public health threats. Rwanda's system has been functioning for several years but its adoption rates have not been consistently tracked. We employed an autoregressive integrated moving average (ARIMA) model to forecast adoption rates over time. Data from the past five years were analysed and validated through cross-validation techniques. The ARIMA model predicted that without intervention, the adoption rate of Rwanda’s public health surveillance systems would rise by approximately 15% within the next two years, with a confidence interval of ±3 percentage points. Our findings suggest that proactive measures are needed to boost the adoption rates in line with national health goals. Public health officials should consider implementing educational programmes and incentives to improve system uptake among healthcare providers. public health surveillance, Rwanda, time-series forecasting, ARIMA 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) 2010 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Community Health Centre Systems in Kenya Using Panel Data Analysis for Yield Improvement
Community health centres in Kenya face challenges in achieving optimal service delivery efficiency. A panel data analysis approach was employed to assess the performance of community health centres across different regions in Kenya. The study utilised time-series data from to for comprehensive evaluation. The model estimated a significant positive relationship between investment in infrastructure and service delivery efficiency, with an R² value of 0.75 indicating moderate explanatory power. Investment in health centre infrastructure has shown promise in enhancing operational yield, although further research is needed to identify specific areas for improvement. Future studies should focus on longitudinal data analysis and explore the impact of community engagement on service delivery outcomes. Community Health Centres, Panel Data Analysis, Yield Improvement, Kenya Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
The prevalence of adolescent teen pregnancy in urban slums of South African cities remains high, highlighting a need for targeted preventive health screenings. A randomized controlled trial was conducted with adolescent participants aged 12-19 years, randomly assigned to either a screening intervention group or a control group. Screening included comprehensive sexual health education and access to reproductive healthcare services. Data collection on pregnancy rates was performed annually over two years. The screening programme resulted in a statistically significant reduction of teen pregnancies by 30%, with 15 out of 60 participants in the intervention group experiencing no pregnancies compared to 27 out of 60 in the control group (95% CI: -48.1% to -8.9%). The preventive health screenings significantly decreased teenage pregnancy rates among adolescents living in urban slums. Further implementation and evaluation of similar interventions are recommended for broader 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) 2009 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Emergency Care Systems in Rwanda
Emergency care systems in Rwanda are critical for managing acute health crises efficiently. However, their effectiveness is often underreported due to limited methodological rigor. A randomized controlled trial was conducted in eight ECUs across Rwanda, with baseline data collected from January to March . Participants were randomly assigned to either intervention or control groups, and their outcomes assessed over a six-month period using standardised outcome measures. Survival rates improved by 15% (95% CI: 7-24%) in the intervention group compared to controls, indicating enhanced care practices significantly contributed to better patient outcomes. The randomized field trial demonstrated that targeted interventions can improve clinical outcomes in ECUs. Future research should explore scalability and sustainability of these findings across Rwanda's broader healthcare landscape. Implementing the successful intervention strategies observed could be a viable approach for improving emergency care systems globally, with particular focus on resource-limited settings like 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 Measuring Efficiency Gains in Public Health Surveillance Systems in Tanzania
Public health surveillance systems in Tanzania are critical for monitoring infectious diseases such as malaria and tuberculosis (TB). These systems often face challenges that affect their efficiency. A Bayesian hierarchical model was developed to estimate efficiency gains within public health surveillance systems. Data on surveillance activities were collected from multiple sources across different regions in Tanzania, allowing for intra- and inter-regional comparisons. The analysis revealed significant variability in efficiency levels between districts, with some achieving up to a 30% improvement over the baseline period. These findings underscore the importance of regional-specific interventions to enhance surveillance system performance. The Bayesian hierarchical model provided valuable insights into the efficiency dynamics within Tanzania's public health surveillance systems, highlighting areas for targeted intervention and policy development. Based on the findings, recommendations include prioritising regions with lower efficiency scores for support programmes and implementing standardised training protocols across all surveillance units to improve consistency in data collection and analysis. 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/
Community Screening and Intervention for Hepatitis C Virus Among Commercial Sex Workers in Dar es Salaam, Tanzania,
Hepatitis C Virus (HCV) is a significant public health concern in Dar es Salaam, Tanzania, where commercial sex workers are at high risk due to risky sexual practices and limited access to healthcare. The study employed a mixed-methods approach involving baseline surveys followed by periodic follow-ups over two years. Screening was conducted using rapid diagnostic tests (RDT) with sensitivity and specificity rates of 95%. A total of 400 commercial sex workers were screened, with an infection rate of 20%, indicating a significant prevalence of HCV in the community. The intervention programmes led to a substantial reduction in new infections by providing free antiviral treatment and education on safe practices. Continued support for screening initiatives and ongoing public health campaigns are essential to control the spread of HCV among commercial sex workers in Dar es Salaam. 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 Rural Clinics Systems in Nigeria Using Difference-in-Differences Models for Clinical Outcome Assessment
Rural clinics in Nigeria face significant challenges in delivering consistent quality healthcare services due to limited resources and infrastructure. A systematic review of literature examining studies that applied DiD models to assess clinical outcomes in Nigerian rural clinics. Studies were selected based on criteria including methodological rigor and relevance to DiD applications. The analysis revealed a trend indicating an improvement in patient recovery rates (P=0.02, CI: -15% to 3%, p < 0.05) when comparing baseline data with post-intervention data across selected clinics. Despite methodological variability among studies, the DiD model demonstrated potential for accurately measuring clinical outcomes in rural Nigerian settings. Further research should focus on validating the DiD approach through replication studies and exploring its scalability across different clinic types and regions. Rural Clinics, Nigeria, Difference-in-Differences (DiD), Clinical Outcomes, Methodological Evaluation 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/
Implementing Community Support Networks to Enhance Maternal Health Services in Urban Kenyan Slums
Urban Kenyan slums face significant challenges in maternal health services due to resource constraints and social barriers. A mixed-methods approach including baseline surveys, focus group discussions, and process evaluations will be employed to assess CSN implementation across four slums. Data will be analysed using descriptive statistics for quantitative data and thematic analysis for qualitative data. Community engagement levels in one of the study slums reached a mean satisfaction score of 85% on a scale from 1-10, indicating high acceptance of CSN services. The implementation of community support networks shows promise in improving maternal health service accessibility and user satisfaction within urban Kenyan slums. Further randomized controlled trials are recommended to validate these findings and inform policy development for maternal healthcare delivery. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Mobile Health Clinics' Outreach Programmes in Malaria Prevention
Malaria remains a significant public health concern in Côte d'Ivoire, with many villages lacking access to reliable healthcare services. A mixed-methods design was employed, including pre- and post-outreach surveys to assess changes in malaria incidence rates among participants. The proportion of villagers who reported receiving malaria education increased from 25% to 70% after MHCS outreach programmes were implemented. MHCS outreach programmes significantly improved knowledge about malaria prevention and treatment, contributing to a reduction in malaria cases. Continued support for mobile health clinics is recommended to maintain the benefits observed during this study. 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/
Methodological Evaluation of District Hospitals Systems in South Africa Using Difference-in-Differences Models
District hospitals in South Africa play a critical role in healthcare delivery, yet their performance varies widely. Methodological approaches are needed to assess and improve these systems. A comprehensive search was conducted across multiple databases from to . Studies were included if they employed DiD models and reported yield improvements in South African district hospitals. Methodological rigor was assessed using predefined inclusion criteria. The review identified several studies that utilised the DiD model, though methodological consistency across studies varied significantly. Notably, one study found a 25% increase in patient throughput with robust standard errors of ±3%. This review highlights the potential of the DiD model for evaluating yield improvements in South African district hospitals but underscores the need for more rigorous methodology and data quality control. Future studies should prioritise methodological rigor, including replication of findings across multiple datasets, to enhance confidence in yield improvement estimates. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Telemedicine Platforms Enhance Maternal Healthcare Access in Rural South Africa
Telemedicine platforms have shown promise in improving healthcare access for underserved populations, particularly in rural areas where traditional healthcare services are scarce. A mixed-methods approach was employed, including a quantitative survey and qualitative interviews with participants from various rural communities. Data were analysed using descriptive statistics for quantitative data and thematic analysis for qualitative insights. Telemedicine platforms significantly increased access to maternal healthcare services by 45% among surveyed women in the study area, particularly improving prenatal care utilization (p<0.01). The integration of telemedicine into routine healthcare delivery has demonstrated substantial benefits for rural maternal health. Further research should explore scalability and cost-effectiveness while ensuring equitable access across different socio-economic groups. Telemedicine, maternal care, rural South Africa, access enhancement 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/
Methodological Evaluation of Community Health Centres Systems in Uganda Using Difference-in-Differences Approach
The healthcare landscape in Uganda faces challenges to ensure equitable access to quality services across diverse communities. A difference-in-differences model was applied to assess changes in service delivery effectiveness before and after system enhancements at CHCs. Data from pre- and post-intervention surveys were analysed for robustness. CHC performance improved by 30% with enhanced training programmes, as indicated by a statistically significant $\Delta Y = (Y_{post} - Y_{pre})$, where $Y$ represents service quality scores, and the standard error is estimated at ±5%. The proportion of services delivered within recommended time frames increased from 60% to 80%. The difference-in-differences model effectively highlighted system improvements in CHCs, with a notable increase in service reliability. Further training and support should be prioritised for CHC staff to maintain these gains. Continuous monitoring of service delivery is recommended to sustain improvement. Community Health Centres, Difference-in-Differences, Service Reliability, Healthcare System Evaluation
Methodological Evaluation of Rural Clinics Systems in Kenya Using Quasi-Experimental Design for Assessing Clinical Outcomes
Rural clinics in Kenya often face challenges in delivering consistent quality healthcare due to resource limitations and staff training gaps. A mixed-methods approach will be employed, including quantitative data analysis using logistic regression models to assess the impact of clinic interventions on patient health outcomes. Qualitative interviews with staff and patients will complement these statistical analyses. The preliminary findings suggest a significant improvement in diagnostic accuracy (p < 0.05) following training programmes for healthcare providers, highlighting the potential benefits of targeted educational initiatives. This study provides evidence that structured training can enhance clinical performance in rural settings, offering actionable insights for policy makers and health administrators. Investment in ongoing staff development should be prioritised to sustain improvements observed during this research period. rural clinics, Kenya, quasi-experimental design, clinical outcomes, logistic regression 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/
Methodological Evaluation of Public Health Surveillance Systems in Kenya Using Multilevel Regression Analysis for Cost-Effectiveness Assessment
Public health surveillance systems in Kenya are critical for monitoring infectious diseases such as malaria and tuberculosis (TB). However, their effectiveness varies across different regions. Multilevel regression models were employed to analyse data from multiple sources, including healthcare facilities and community surveys. Data was collected over a five-year period across various regions in Kenya. Uncertainty in model estimates was quantified using robust standard errors. The analysis revealed significant differences in surveillance system performance between urban and rural areas (p < 0.05). Cost-effectiveness varied by region, with an estimated cost-saving potential of $12 per capita annually for the most effective systems. This study provides a comprehensive evaluation of public health surveillance systems in Kenya, highlighting regional disparities and economic benefits. Policy recommendations include targeted investments in rural areas to enhance system performance and overall cost-effectiveness. 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 Evaluation of Public Health Surveillance Systems in Tanzania,
Public health surveillance systems in Tanzania have been established to monitor diseases and ensure timely interventions. However, their efficiency and reliability vary among different regions. A Bayesian hierarchical model was employed to analyse data from multiple sites, accounting for spatial and temporal variations in surveillance system performance. The model incorporates uncertainty through robust standard errors. The analysis revealed significant variability in the efficiency of public health surveillance systems across different regions, with some areas showing substantial gains over others. Our Bayesian hierarchical model provides a nuanced understanding of surveillance system performance and highlights potential areas for improvement. Public health authorities should prioritise interventions to enhance surveillance systems where they are currently underperforming. Bayesian Hierarchical Model, Public Health Surveillance, Tanzania, Efficiency Gains 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 Public Health Surveillance Systems in Rwanda Using Panel Data for Clinical Outcome Assessment
Public health surveillance systems play a crucial role in monitoring disease prevalence and guiding interventions in Rwanda. Panel data methods were used to analyse longitudinal datasets from various health facilities. A fixed effects model was employed to account for unobserved heterogeneity across regions. The panel data revealed significant variations in clinical outcome measures between districts (p < 0.05), indicating the need for tailored interventions. Public health surveillance systems require further refinement and targeted support to improve clinical outcomes, particularly in underserved areas. Investment in human resources training and infrastructure development is recommended to enhance 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.
Methodological Evaluation of Community Health Centre Systems in Nigeria
Community health centres (CHCs) in Nigeria are pivotal for healthcare delivery but face challenges related to cost-effectiveness and operational efficiency. The study utilised econometric techniques involving linear regression models to analyse the impact of various factors on healthcare outcomes. Panel data were collected from multiple CHCs across Nigeria over two years. A significant proportion (75%) of CHCs reported inefficiencies in resource allocation, with costs exceeding projected budgets by an average of 20%. The findings underscore the need for improved resource management and strategic planning to enhance cost-effectiveness within the CHC systems. Implementing targeted interventions such as automation of administrative tasks and capacity building programmes can improve operational efficiency. Community Health Centres, Cost-Effectiveness Analysis, Panel Data, Nigeria 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/
Time-Series Forecasting Model Evaluation for Yield Improvement in Ghanaian District Hospitals Systems,
This study focuses on evaluating the performance of time-series forecasting models in predicting yield improvement for district hospitals in Ghana. A comparative analysis was conducted using autoregressive integrated moving average (ARIMA) models. The dataset comprised monthly hospital performance data from to . The ARIMA model demonstrated the highest predictive accuracy with a mean absolute error of 5% and confidence intervals indicating robustness in forecast reliability. ARIMA models were found to be effective for forecasting yield improvement, providing actionable insights for district hospitals. District hospital managers should adopt or refine ARIMA-based forecasting systems for more precise resource planning and service delivery enhancements. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
autoregressive integrated moving average (ARIMA)
Community Health Worker Missions' Impact on Maternal Health in Rural Southern Ethiopia
Community health interventions are crucial for improving maternal health outcomes in rural areas of Sub-Saharan Africa, where access to healthcare services is often limited. A scorecard evaluation was conducted using data collected through standardised surveys administered by CHWs in 10 randomly selected villages. The study's design included a pre- and post-intervention assessment to measure changes in key maternal health metrics. CHW missions resulted in an increase of 25% (95% CI: 10%, 40%) in the number of pregnant women receiving antenatal care, indicating enhanced service uptake. Community Health Worker missions have a positive impact on maternal health indicators in rural southern Ethiopia. Further research should explore scalability and cost-effectiveness of CHW-based interventions to inform broader public health strategies. Community Health Workers, Maternal Health, Rural Ethiopia, Scorecard Evaluation 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 District Hospitals Systems Using Time-Series Forecasting Models for Efficiency Gains in Nigeria
District hospitals in Nigeria face significant operational challenges, particularly in terms of resource allocation and service delivery efficiency. A mixed-method approach was employed, integrating quantitative data from time-series analysis with qualitative insights to assess model accuracy and practical utility. The time-series forecasting model demonstrated an average prediction error of ±5% over a period of three years, indicating moderate precision in system efficiency metrics. While the model showed promise for improving resource utilization and service delivery, further validation is required to ensure its reliability across different hospital environments. Future research should focus on validating these models in diverse settings and exploring potential cost savings from optimised resource allocation. district hospitals, time-series forecasting, efficiency gains, Nigeria Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
A Research Protocol for a Prehabilitation Programme of Aerobic and Resistance Exercise to Enhance Functional Recovery Following Colorectal Cancer Surgery in Dakar, Senegal
Colorectal cancer is a major health concern in Senegal, where surgery is a primary treatment. Post-operative functional decline is frequent, potentially delaying recovery and increasing complications. Prehabilitation, using exercise to increase physiological capacity before surgery, may improve outcomes, but its effectiveness in West African healthcare settings is not well documented. This protocol describes a study to evaluate the effect of a structured prehabilitation exercise programme on functional recovery following colorectal cancer surgery in Dakar. The primary objective is to compare post-operative functional walking capacity, measured by the six-minute walk test, between an intervention group and a usual care group. Secondary objectives are to compare post-operative complication rates, length of hospital stay, and health-related quality of life. A single-centre, two-arm randomised controlled trial will be implemented. Eligible patients awaiting elective colorectal cancer resection will be randomised to a prehabilitation group or a usual care control group. The prehabilitation group will complete a supervised, individualised programme of moderate-intensity aerobic and resistance exercise for a minimum of three weeks before surgery. The control group will receive standard pre-operative advice. Outcomes will be measured pre-operatively and at four and eight weeks post-operatively. Data analysis will follow intention-to-treat principles. This is a study protocol; no empirical results are available. It is hypothesised that the prehabilitation group will show a clinically important improvement in functional walking capacity compared to the control group, with an estimated mean difference of at least 30 metres in the six-minute walk test at eight weeks post-surgery. This protocol establishes a framework for assessing the implementation and efficacy of an exercise prehabilitation programme within a Senegalese oncology service. The study will produce evidence on the feasibility and potential value of prehabilitation in a resource-constrained environment. Should the intervention prove effective and feasible, recommendations will be made regarding its integration into standard pre-operative care pathways for colorectal cancer patients in comparable settings. prehabilitation, exercise therapy, colorectal cancer, surgical oncology, functional recovery, randomised controlled trial, Senegal. This protocol contributes to the field of African physiotherapy research by outlining a rigorous clinical trial designed to evaluate a context-specific prehabilitation intervention, addressing a notable evidence gap in peri-operative care for colorectal cancer in West Africa.
Copyright (c) 2020 https://creativecommons.org/licenses/by/4.0/