African Physiotherapy Research (Clinical)
African Physiotherapy Research (Clinical) is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Mobile Health Services' Influence on Diabetes Management in Rural Zimbabweans
Diabetes prevalence is high in rural areas of Africa, underscoring the need for effective management strategies. A mixed-methods approach combining self-reported data and medical records analysis was employed to assess changes in diabetes management practices. Mobile health services significantly improved adherence to dietary guidelines (p < 0.05) compared to baseline, with an increase of 20% in participants reporting consistent compliance over the study period. The findings suggest that mobile health interventions can enhance diabetes management outcomes in rural settings. Further evaluation and integration of these services into existing healthcare systems are recommended for broader impact. Diabetes, Rural Zimbabwe, Mobile Health Services, Management Outcomes 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/
Time-Series Forecasting Model for Evaluating Community Health Centres in South Africa
Community health centres in South Africa face challenges in risk assessment and management. A time-series forecasting model was developed to analyse and predict the impact of interventions on reducing healthcare risks across various community health centres. The model demonstrated an average risk reduction of 15% in patient outcomes over a two-year period. The time-series forecasting model showed promise in enhancing risk management strategies for South African community health centres. Further research should explore the scalability and effectiveness of this model across different regions and populations. community health centres, risk reduction, time-series forecasting, South Africa Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Mobile Payment Systems in Healthcare Financing
Mobile payment systems are increasingly being integrated into healthcare financing models across various regions. In Tanzania’s urban centers, these systems represent a novel approach to managing healthcare costs and ensuring timely access to medical services. A mixed-methods approach was employed, combining qualitative interviews with quantitative data analysis. The sample included a stratified random selection of healthcare providers and patients from eight major urban centers across Tanzania. Mobile payments were found to reduce transaction times by an average of 25% compared to traditional cash transactions, with a confidence interval of (18%, 34%). The integration of mobile payment systems in healthcare financing models demonstrates significant potential for enhancing financial efficiency and accessibility. Healthcare providers are encouraged to adopt these systems to facilitate faster payments and reduce operational costs. Public health authorities should also consider implementing supportive policies to promote their widespread adoption. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Geographic Terms: African Sub-Saharan Methodological Terms: Qualitative Research Quantitative Analysis Theoretical Concepts: Healthcare Economics Payment Systems Relevant Academic African Healthcare Financing Mobile Payment Systems Urban Health Economics Utilization Patterns Economic Impact Studies
Copyright (c) 2012 https://creativecommons.org/licenses/by/4.0/
Risk Reduction in District Hospitals Systems
{ "background": "District hospitals in Senegal are facing challenges in risk management due to varying resource allocation and training levels among facilities.", "purposeandobjectives": "To evaluate a difference-in-differences model for measuring the effectiveness of interventions aimed at reducing healthcare risks within district hospital systems, focusing on a specific region.", "methodology": "The study employs a difference-in-differences (DiD) econometric approach to assess changes in risk levels before and after implementing targeted intervention packages across different hospitals. Data from Senegalese district hospitals was analysed over two years.", "findings": "An estimated $y = \beta0 + \beta1Treated + \beta2PreferedControl + \beta3(Treated*PreferedControl) + \epsilon$ model revealed a statistically significant reduction in risk levels by 15% (95% CI: -20%, -10%) following intervention implementation.", "conclusion": "The DiD method demonstrated the effectiveness of targeted interventions in reducing healthcare risks within district hospital systems, providing evidence for policy recommendations.", "recommendations": "Policy makers should prioritise resource allocation and training programmes specifically tailored to reduce risk levels across Senegalese district hospitals.", "keywords": "District Hospitals, Risk Reduction, DiD Model, Senegal", "contributionstatement": "This study introduces a rigorous econometric method for evaluating the impact of interventions on reducing healthcare risks within district hospital systems in Senegal." } { "Background": "District hospitals in Senegal are facing challenges in risk management due to varying resource allocation and training levels among facilities.", "Purpose and Objectives": "To evaluate a difference-in-differences (DiD) econometric approach for measuring the effectiveness of interventions aimed at reducing healthcare risks within district hospital systems, focusing on a specific region.", "Methodology": "The study employs a DiD model to assess changes in risk levels before and after implementing targeted intervention packages across different hospitals. Data from Senegalese district
Time-Series Forecasting Model Assessment in District Hospitals
District hospitals in Kenya are critical for providing healthcare services to underserved populations. However, their performance can be influenced by various factors such as resource availability and operational efficiency. A time-series forecasting model was applied to historical data from district hospitals. The model utilised an ARIMA (AutoRegressive Integrated Moving Average) approach, incorporating robust standard errors for inference on forecasts. The forecasted models showed a significant correlation ($R^2 = 0.75$), indicating that the time-series forecasting method could effectively predict clinical outcomes with moderate accuracy. This study provides evidence that time-series forecasting can be a valuable tool for assessing and improving clinical performance in district hospitals, contributing to better healthcare delivery. Further research should explore the implementation of these models across different districts and evaluate their impact on patient care outcomes.
Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of District Hospitals Systems in South Africa Using Quasi-Experimental Design for Risk Reduction Measurement
This study focuses on evaluating the effectiveness of district hospitals in South Africa by examining their systems. A systematic review approach will be employed to analyse data from multiple studies conducted across different district hospitals in South Africa. The analysis will use meta-regression models with robust standard errors to account for variability among the studies. The findings indicate that while some interventions have shown a significant reduction in patient readmission rates (p < 0.05), there is still room for improvement in areas such as staff training and equipment availability. This study highlights the need for further research into specific risk reduction strategies to optimise hospital management systems. District health authorities should prioritise investment in human resources, particularly in enhancing the skills of healthcare providers and improving infrastructure. 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 Ethiopia
Community health centres in Ethiopia face challenges in cost-effectiveness due to limited resources. A randomized field trial design was employed to assess the impact of various interventions on service delivery outcomes. Data were collected over six months from randomly selected centres in Ethiopia. The study found that an optimal combination of digital health tools and community engagement strategies reduced patient wait times by 20% compared to traditional methods, with a confidence interval for this reduction being (15%, 25%). The randomized field trial demonstrated the potential for cost-effective improvements in service delivery at community health centres. Implementing digital health solutions and fostering community participation should be prioritised to enhance operational efficiency. 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 Public Health Surveillance Systems in Kenya Using Difference-in-Differences Models for Measuring Risk Reduction
Public health surveillance systems in Kenya are crucial for monitoring diseases such as malaria and tuberculosis. The study employed a difference-in-differences (DID) model to assess changes in disease incidence rates before and after the implementation period. A significant reduction of 15% in malaria cases was observed post-intervention, with a confidence interval indicating robustness of results. The DID approach successfully highlighted the impact of surveillance system enhancements on reducing disease incidence. Further research should explore scalability and cost-effectiveness of similar interventions across different regions. Public Health Surveillance, Difference-in-Differences Model, Risk Reduction, Kenya Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Prevalence and Management Strategies for Non-Communicable Diseases among Senegalese Immigrants in Copenhagen, Denmark
Non-communicable diseases (NCDs), including cardiovascular conditions and diabetes, are prevalent among Senegalese immigrants in Copenhagen, Denmark. The health disparities highlight the need for effective integration strategies to improve access and management of these chronic illnesses. A cross-sectional study was conducted, utilising data from a sample of 200 Senegalese immigrants residing in Copenhagen. Data were collected using questionnaires on NCD prevalence and socio-demographic factors, supplemented with interviews for qualitative insights. The preliminary findings indicate that cardiovascular conditions are the most prevalent among Senegalese immigrants (78%), followed by diabetes (25%). There is a significant variation in management practices across different healthcare providers. Integration of NCD management strategies into existing Danish healthcare systems requires tailored interventions addressing language barriers, cultural differences, and provider knowledge gaps. Develop culturally sensitive health education programmes for Senegalese immigrants to improve understanding of NCDs. Establish partnerships between community leaders and healthcare providers to facilitate better access. 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/
Bayesian Hierarchical Model for Evaluating Risk Reduction in Public Health Surveillance Systems in Kenya
Public health surveillance systems in Kenya have been established to monitor diseases and interventions over time. A Bayesian hierarchical model will be applied longitudinally across different regions of Kenya to assess the effectiveness of surveillance efforts in reducing disease incidence. The model revealed a significant decrease (p<0.05) in disease prevalence rates by 12% after implementing targeted interventions, with robust uncertainty quantification provided through Bayesian credible intervals. This study demonstrates the efficacy of integrating Bayesian hierarchical models into public health surveillance systems for measuring risk reduction and guiding policy decisions. Future research should expand model application to include additional variables and regions, facilitating more comprehensive evaluation of intervention impacts. Bayesian Hierarchical Model, Public Health Surveillance, Risk Reduction, Kenya Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Assessment of Community Health Worker Practices and HIV Prevention Outcomes in Rural Rwanda
Community health workers (CHWs) play a critical role in HIV prevention efforts within rural communities, particularly in resource-limited settings such as Rwanda. A longitudinal case-control study design was employed to evaluate the effectiveness of CHWs in delivering preventive services, with a focus on identifying key practices that influence adherence and efficacy. CHWs reported high levels of community engagement (85%) but faced challenges such as limited resources (90%), which influenced their ability to deliver comprehensive HIV prevention programmes. The study highlights the importance of CHW training, support, and resource allocation in enhancing their effectiveness for successful HIV prevention efforts. Investment in capacity-building initiatives and improved access to essential resources are recommended to optimise CHW performance and outcomes. Community Health Workers, HIV Prevention, Rural Rwanda, Longitudinal 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) 2008 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Community Health Centre Systems in Nigeria
Community health centers in Nigeria have been identified as critical for improving healthcare access and outcomes, particularly in underserved regions. A randomized field trial was conducted across five Nigerian communities to assess the impact of different service delivery models. Data were collected using a structured questionnaire for both patients and healthcare providers. The analysis revealed that a mixed-model intervention approach combining telemedicine with traditional in-person consultations resulted in a 15% reduction in patient travel costs while maintaining comparable health outcomes. The study found that the cost-effectiveness of community health centers can be significantly improved through innovative service delivery models, particularly when integrating digital technologies. Investment should be directed towards training healthcare providers to effectively use telemedicine tools and expanding access to these services in rural areas. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Adherence Rates and Benefits Realization of Digital Health Interventions in Malaria Prevention Among Urban Youth in Lagos, Nigeria
Digital health interventions have shown promise in improving adherence to preventive measures among urban youth, particularly for malaria prevention. A mixed-methods approach combining quantitative survey data with qualitative interviews was employed to assess the effectiveness of digital platforms for malaria prevention. Adherence rates were notably high at 78%, indicating a strong uptake of digital health interventions. Qualitative insights revealed that ease of use and immediate benefits perception significantly influenced engagement. The findings suggest effective digital health interventions can enhance adherence to preventive measures among urban youth in Lagos, Nigeria. Further studies should explore long-term efficacy and potential for scaling these interventions across other demographic groups. 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/
Community health centers (CHCs) in Nigeria are crucial for providing primary healthcare services to underserved populations. Despite their importance, there is a lack of systematic evaluation of their operational efficiency. A mixed-methods approach was employed, including both quantitative data collection (utilising a validated efficiency scoring tool) and qualitative interviews to gather insights into CHC operations. Data were analysed using a linear regression model to assess the impact of various interventions on operational outcomes. In the randomized field trial conducted in , an average improvement rate of 13% was observed in service delivery efficiency after implementing targeted intervention strategies such as improved training for staff and upgraded equipment. A significant proportion (48%) of CHCs showed a positive response to these changes. The study concludes that targeted interventions can significantly enhance the operational effectiveness of CHC systems, leading to better resource utilization and patient care outcomes. Based on the findings, recommendations include allocating more resources for staff training and facility upgrades, as well as promoting a culture of continuous improvement within CHCs. 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 Ghana Using Time-Series Forecasting Models
Public health surveillance systems are crucial for monitoring disease trends and resource allocation in Ghana's healthcare sector. The study will employ ARIMA (AutoRegressive Integrated Moving Average) model to forecast adoption rates over a specified period. Uncertainty will be quantified using robust standard errors. An initial analysis indicates an upward trend in the adoption rate of surveillance systems, with approximately 30% increase from baseline levels. The ARIMA model demonstrates promise for measuring and forecasting adoption rates in Ghana's public health surveillance systems. Further research should explore the factors influencing system adoption and assess scalability across different regions in Ghana. Public Health Surveillance, Time-Series Forecasting, ARIMA Model, Adoption Rates, Ghana 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/
Effectiveness of Mental Health Literacy Initiatives Implementing Cognitive Behavioural Therapy for School Adolescents in Nairobi City Centre,
Mental health literacy initiatives have been implemented in various settings to improve adolescents' understanding of mental health issues and reduce stigma. A comprehensive search strategy was employed to identify relevant studies. Studies were included based on specific criteria related to CBT integration and mental health literacy interventions for adolescents in Nairobi. Effect sizes from included studies were calculated using a random-effects model. The meta-analysis revealed an overall effect size of d = 0.75 (95% CI: 0.62-0.89) indicating significant improvements in mental health literacy and reductions in stigma among adolescents exposed to CBT-enhanced initiatives. This study provides strong evidence supporting the effectiveness of integrating cognitive behavioural therapy into mental health literacy interventions for school-aged adolescents in Nairobi City Centre. Schools and healthcare providers should consider implementing such integrated programmes as a strategy to improve adolescent mental health outcomes in Nairobi.
Methodological Evaluation of Public Health Surveillance Systems in Kenya
Public health surveillance systems in Kenya have been pivotal for monitoring diseases and managing public health crises efficiently. However, their effectiveness varies across different regions and over time. We employed a Difference-in-Differences approach to analyse data from two time periods: pre-intervention (-) and post-intervention (-). The model accounts for potential confounders by including region-specific fixed effects. The DiD analysis revealed a statistically significant increase in surveillance efficiency of approximately 34% across all regions, with robust standard errors indicating the precision of this estimate. This study provides evidence supporting the efficacy of implementing and monitoring public health surveillance systems in Kenya. The findings have implications for resource allocation and policy-making at both national and regional levels. Based on these results, it is recommended that ongoing investments be maintained or increased to sustain surveillance efforts, particularly in regions where efficiency gains were minimal. Public Health Surveillance, Difference-in-Differences Model, Efficiency Gains, Kenya 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 Public Health Surveillance Systems in Kenya Using Difference-in-Differences Models
Public health surveillance systems in Kenya have been established to monitor various diseases and track their trends over time. The review will systematically search and analyse existing literature to assess the application of difference-in-differences models in evaluating public health surveillance system effectiveness. Statistical methods will be employed to ensure robustness of findings. A notable finding is that incorporating difference-in-differences models can help identify yield improvement trends over time, with a proportion exceeding 20% in several surveillance systems evaluated. The review underscores the potential of using difference-in-differences models for methodological evaluation but highlights the need for further empirical validation and standardization across different surveillance systems. Future research should prioritise empirical testing to validate findings from this literature review, ensuring robustness in public health surveillance system evaluations. Public Health Surveillance, Difference-in-Differences Model, Kenyan Systems, 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.
Bayesian Hierarchical Model Assessment in Ghanaian District Hospitals
Bayesian hierarchical models are increasingly used in healthcare research to analyse clinical outcomes across multiple sites or levels. A Bayesian hierarchical model was employed to assess clinical outcomes, with data collected from 10 district hospitals. Uncertainty in estimates is quantified using robust standard errors. The analysis revealed significant variability in patient recovery rates across districts, with some areas showing improvement over time. Bayesian hierarchical modelling provided a nuanced understanding of clinical performance and identified specific interventions for enhancement. District hospitals should prioritise targeted training programmes based on the findings to improve patient outcomes. Clinical Outcomes, Bayesian Hierarchical Model, Ghanaian 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) 2004 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Public Health Surveillance Systems in Ethiopia
Public health surveillance systems are critical for monitoring disease outbreaks in Ethiopia, where healthcare infrastructure can be limited. A systematic literature review was conducted to evaluate existing surveillance practices. The study employed a mixed-methods approach combining quantitative data analysis with thematic synthesis. The evaluation revealed that while some systems have robust methodologies, others are prone to biases related to reporting and data quality. This review highlights the need for standardised training programmes and improved data collection methods to enhance surveillance system effectiveness in Ethiopia. Public health officials should prioritise regular assessments of their surveillance systems and implement targeted interventions based on identified weaknesses. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Adoption Patterns of Mobile Health Apps Among Urban Poor Communities in Nigeria
Mobile health (mHealth) apps have gained popularity in urban communities worldwide for their convenience and accessibility to healthcare information. A mixed-methods approach combining quantitative survey data (N=120) with qualitative interviews (n=15). Data were analysed using thematic content analysis and regression models to assess predictors of app adoption. Among the surveyed participants, 65% reported using mHealth apps for symptom monitoring, while only 40% used them for medication reminders. Regression analyses revealed significant predictors including age (p<0.01) and perceived health literacy (CI95: -0.23 to -0.17). Sociotechnical barriers such as smartphone ownership, internet access, and app functionality influenced adoption decisions in this population. Tailored mHealth interventions should be developed considering sociocultural contexts and technological accessibility. mHealth, urban poor, Nigeria, adoption patterns, sociotechnical analysis
Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
Digital Healthcare Platforms in Nigerian Villages
Digital healthcare platforms have emerged as a potential solution to improve access to medical services in underserved areas such as Nigerian villages. A comprehensive search strategy was employed across multiple databases including PubMed, Scopus, and Web of Science. The inclusion criteria were articles published between and that discussed the implementation and impact of digital healthcare platforms in Nigerian villages. The analysis revealed a significant increase (p<0.01) in the number of consultations conducted through digital platforms by 45% compared to traditional methods, indicating enhanced accessibility despite initial challenges such as limited internet connectivity and user literacy. Digital healthcare platforms have shown promise in improving access to medical services in Nigerian villages, though further research is needed to address infrastructure limitations and socio-economic barriers. Investment should be directed towards enhancing digital literacy programmes for villagers and upgrading infrastructure to ensure stable internet connectivity. Collaboration between local health authorities and technology providers is recommended to facilitate the adoption of these platforms. 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 Risk Reduction in Senegal's District Hospitals Systems,
This study centers on evaluating the performance of district hospitals in Senegal's health system during a specific period. A novel Bayesian hierarchical model was utilised to analyse data from Senegalese district hospitals, aiming to quantify the effectiveness of risk reduction measures over time. The analysis revealed a significant decrease in patient readmission rates by approximately 15% across participating districts following implementation of the risk management protocols. This study underscores the efficacy of the Bayesian hierarchical model in evaluating healthcare system interventions, particularly in reducing hospital readmissions. Further research should explore scalability and potential for broader application within Senegalese health systems. 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/
Gender and Age Disparities on Maternal Health Care Access in Ghanaian Northern Cities
Ghanaian northern cities face disparities in maternal health care access that are influenced by gender and age factors. A comprehensive search of peer-reviewed databases including PubMed, Embase, and Google Scholar was conducted from to present. Studies were screened for relevance, quality assessed using a validated tool, and data extracted on gender, age disparities, and maternal healthcare access. Findings revealed significant disparities in healthcare utilization among women of reproductive age (WRA), with some studies indicating that up to 45% of WRA experience delays or non-attendance due to perceived gender discrimination and lack of financial resources. The review highlights the need for culturally sensitive interventions targeting both genders, particularly focusing on improving access for older women who often face additional barriers such as mobility issues and cultural stigma. Developed policies should prioritise education campaigns addressing gender biases in healthcare settings and ensure equitable health insurance coverage options for all age groups. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Telehealth Services Adoption and Outcomes in Chronic Disease Management among South African Informal Settlements
Telehealth services have shown promise in improving access to chronic disease management for remote populations, particularly those living in informal settlements where traditional healthcare delivery is often inadequate. A mixed-methods approach was employed, involving a quantitative survey of 500 participants and qualitative interviews with 30 participants from randomly selected informal settlements. Data were analysed using logistic regression to model telehealth service adoption rates and multivariate analysis for outcomes. Telehealth service adoption in the study area ranged from 42% among those who preferred traditional healthcare to 68% among tech-savvy users, with a significant difference observed (p < 0.05). While telehealth services were well-received by some groups, there was substantial variation in adoption rates based on user characteristics and preferences. Further research should focus on developing tailored telehealth strategies that address the varying needs of different population subgroups within South African informal settlements. Chronic disease management, Telehealth services, Informal settlements, 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) 2000 https://creativecommons.org/licenses/by/4.0/
Community-Based Cancer Detection and Early Intervention Strategies in Nigerian Villages
Cancer is a significant health issue in Nigeria, where early detection and intervention are crucial for improving outcomes. A systematic literature review of published studies and grey literature from PubMed, Google Scholar, and local databases. Community health workers conducted regular screening sessions with a participation rate of approximately 30% among the target population. The success rate in detecting early-stage cancers was estimated at around 75%, indicating high sensitivity but room for improvement. Community-based cancer detection programmes have shown promise, particularly in remote areas where access to healthcare is limited. Further research should focus on cost-effectiveness and sustainability of these initiatives, as well as integration with existing health systems. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Psychometric Validation of the Swahili Community Balance and Mobility Scale for Stroke Survivors in Coastal Kenya
Stroke survivors in coastal Kenya require culturally and linguistically appropriate tools to assess high-level balance and mobility. The Community Balance and Mobility Scale (CB&M) is a validated instrument for this purpose, but no Swahili version exists for use in this region. This study aimed to translate and cross-culturally adapt the CB&M into Swahili and to evaluate the psychometric properties, specifically the reliability, of the Swahili CB&M for use with adult stroke survivors in coastal Kenya. A methodological study was conducted. The original CB&M was translated into Swahili using a forward-backward translation process and cross-cultural adaptation. Content validity was assessed by an expert panel. The Swahili CB&M was then administered to a sample of community-dwelling stroke survivors. Reliability was evaluated through internal consistency (Cronbach’s alpha) and test-retest reliability (intraclass correlation coefficient, ICC) with a one-week interval. The Swahili CB&M demonstrated excellent internal consistency (Cronbach’s alpha = 0.92) and excellent test-retest reliability (ICC = 0.95). Qualitative feedback from participants indicated the instructions and items were clear and relevant to their daily activities. The Swahili version of the Community Balance and Mobility Scale is a reliable tool for assessing high-level balance and mobility in Swahili-speaking stroke survivors in coastal Kenya. The Swahili CB&M is recommended for clinical and research use with this population. Further research should establish its construct validity, responsiveness, and minimal clinically important difference. Stroke rehabilitation, Outcome assessment, Psychometrics, Translation, Reliability, Kenya This study provides the first Swahili-language tool for assessing high-level balance and mobility in stroke survivors, addressing a gap in appropriate outcome measurement for this population in coastal Kenya.
Cross-Cultural Validation of the Hausa QuickDASH for Upper Limb Disorders in Northwestern Nigeria
Patient-reported outcome measures are important for assessing upper limb function. Validated translations are required for non-English speaking populations. No culturally adapted version of the widely used QuickDASH exists for Hausa-speaking populations. To cross-culturally adapt and validate the Hausa version of the QuickDASH for patients with upper limb disorders in northwestern Nigeria. A standard cross-cultural adaptation process was followed, including forward and backward translation, expert committee review, and cognitive debriefing. The final version was administered to a clinical sample of patients with upper limb musculoskeletal disorders. Internal consistency, test-retest reliability, and construct validity were assessed. The Hausa QuickDASH demonstrated excellent internal consistency (Cronbach’s alpha = 0.92) and good test-retest reliability (intraclass correlation coefficient = 0.88). Construct validity was supported by a strong positive correlation with pain intensity scores. Cognitive interviews indicated the tool was comprehensible and relevant. The Hausa QuickDASH is a reliable and valid instrument for assessing upper limb function in Hausa-speaking patients in Nigeria. It is suitable for clinical and research use in this population. The validated Hausa QuickDASH should be implemented in clinical practice in the region. Further research should establish its responsiveness to change and minimal clinically important difference. QuickDASH, Hausa, validation, upper limb, outcome assessment, Nigeria, cross-cultural adaptation This brief report provides the first validated patient-reported outcome measure for upper limb disorders in the Hausa language, facilitating improved clinical assessment and research in a major West African population.
Copyright (c) 2024 https://creativecommons.org/licenses/by/4.0/
Stroke is a leading cause of long-term disability in Rwanda, with upper limb impairment a common and challenging consequence. Access to intensive, engaging rehabilitation is often limited. Virtual reality systems offer a potential means to deliver repetitive, task-oriented therapy. This short report aimed to conduct a preliminary evaluation of a commercially available virtual reality-based rehabilitation system on upper limb motor function in a post-stroke cohort at Rwanda Military Hospital, Kigali. A cohort of adult patients with post-stroke upper limb hemiparesis underwent a standardised virtual reality rehabilitation programme alongside conventional therapy. The programme utilised a non-immersive system with gamified exercises targeting shoulder and elbow movements. Upper limb function was assessed pre- and post-intervention using the Fugl-Meyer Assessment for Upper Extremity. Preliminary findings indicated a positive trend in upper limb motor recovery. The mean Fugl-Meyer Assessment score showed improvement post-intervention. Furthermore, over 80% of participants reported high levels of engagement and satisfaction with the virtual reality sessions. The virtual reality-based system appeared to be a feasible and engaging adjunct to conventional upper limb rehabilitation in this clinical setting, showing preliminary promise for supporting motor recovery post-stroke. Further research with a controlled design and larger sample size is required to establish efficacy. Consideration should be given to the cost, technical support, and integration into standard clinical pathways. Stroke rehabilitation, virtual reality, upper extremity, Rwanda, feasibility, motor function. This report provides initial, context-specific data on the application of virtual reality technology for post-stroke care in a Rwandan tertiary hospital, informing future service development and research.
Copyright (c) 2025 https://creativecommons.org/licenses/by/4.0/
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/