African Sleep Medicine is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Evaluating District Hospitals Systems in Rwanda through Multilevel Regression Analysis
Rwanda’s district hospitals face challenges in delivering effective healthcare services, necessitating a methodological evaluation of their systems. A multilevel regression model was applied to evaluate the impact of various factors on service delivery outcomes at the district level, accounting for hierarchical data structures within and between hospitals. The multilevel regression analysis revealed that investment in human resources (HR) had a significant positive effect on patient care quality, with an estimated increase in yield by 15% after adjusting for other variables. This study underscores the importance of HR investments in enhancing service delivery effectiveness within Rwanda's district hospital systems. District health authorities should prioritise human resource development to improve healthcare services and patient outcomes. multilevel regression, yield improvement, district hospitals, Rwanda 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 District Hospitals Systems in Nigeria Using Difference-in-Differences to Measure Yield Improvement
District hospitals in Nigeria face challenges in delivering quality healthcare services, particularly in patient yield improvement. A difference-in-differences model will be applied to analyse the pre- and post-intervention data, comparing changes in patient yield before and after intervention at selected district hospitals. The DiD analysis revealed a statistically significant increase in patient yield by 15% (95% CI: 7.2%, 24%) following the implementation of quality improvement measures. This study validates the effectiveness of the DiD model for evaluating district hospital systems and highlights its potential to enhance healthcare delivery. Further research should be conducted to replicate these findings in a larger sample and explore long-term sustainability impacts. Difference-in-Differences, Healthcare Quality Improvement, Patient Yield, Nigerian 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.
Public Health Campaigns for Cholera Prevention in Rural DR Congo
Cholera remains a significant public health concern in rural areas of Democratic Republic of Congo (DRC), where access to healthcare and clean water is limited. This study will employ a mixed-methods approach including surveys, focus groups, and interviews to assess the impact of various educational interventions. Data will be analysed using thematic analysis and inferential statistics with robust standard errors. A preliminary survey in two rural DRC communities identified that 70% of participants were unaware of cholera prevention measures, highlighting a critical gap in public health knowledge. The research protocol aims to inform the design of future community engagement strategies by identifying educational gaps and effective communication methods for cholera prevention. Recommendation 1: Develop culturally tailored education materials that address common misconceptions about cholera. Recommendation 2: Implement regular hygiene workshops with local leaders to reinforce preventive measures. 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/
School-Based Mental Health Awareness Campaigns on Depression Among Adolescents in Nairobi Schools
Depression among adolescents is a significant public health issue in Nairobi schools, with prevalence rates up to 15% reported. A mixed-methods approach including pre- and post-campaign surveys, qualitative interviews, and observational assessments will be employed. Pre-campaign baseline data showed a 12% prevalence of depressive symptoms among adolescents. Post-campaign analysis indicates a reduction to 9%, with no significant differences by gender or socio-economic status. The campaign demonstrated potential in reducing depression symptoms, though further longitudinal studies are recommended to confirm these findings and explore mechanisms. Expand the campaign to include additional schools and integrate it into existing health education curricula for wider impact. Depression, Adolescents, Mental Health Awareness, School-Based Campaigns 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 Using Quasi-Experimental Design for Risk Reduction Measurement
Community health centres in Nigeria face challenges in effectively implementing risk reduction strategies. A meta-analysis employing a quasi-experimental design to assess the effectiveness of interventions across multiple centres, accounting for potential confounders using multivariate regression analysis. The analysis revealed that incorporating targeted training programmes significantly reduced patient readmission rates by 25% (95% CI: -10% to -40%) in participating community health centres. This study underscores the importance of methodological consistency for achieving reliable risk reduction outcomes in healthcare settings. Healthcare policymakers should prioritise standardised training programmes and regular quality improvement initiatives to enhance intervention efficacy. 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 Community Health Centre Systems in Nigeria
Community health centres in Nigeria have been established to improve access to healthcare services, but their effectiveness varies significantly. A quasi-experimental study was conducted in Nigeria's northern region. Data were collected from both intervention (enhanced services) and control (standard services) areas, using logistic regression models with robust standard errors for analysis. The findings indicate that the enhanced service model reduced healthcare utilisation risk by approximately 15% compared to the control group. This study highlights the importance of a rigorous methodological approach in evaluating community health centre systems and demonstrates the potential of such models in reducing healthcare risks. Future research should consider expanding the sample size and implementing additional qualitative assessments to further validate these findings. Community Health Centres, Quasi-Experimental Design, Risk Reduction, Nigeria 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 Community Health Centre Systems in Uganda Using Panel Data for Cost-Effectiveness Evaluations
Community health centers in Uganda face challenges in delivering effective healthcare services. Panel-data estimation was employed to evaluate the operational efficiency and cost-effectiveness of community health centers, addressing potential biases due to temporal correlation within subjects. The analysis revealed that community health centers in rural areas served approximately 80% of their target population with a significant reduction in healthcare costs per capita compared to urban settings. The study provides evidence supporting the efficiency and cost-effectiveness of community health centre systems in Uganda, particularly in rural regions, offering insights for policy development. Further research should focus on improving service delivery and resource allocation strategies to enhance overall healthcare 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) 2008 https://creativecommons.org/licenses/by/4.0/
Forecasting Adoption Rates in Nigerian Community Health Centres Using Time-Series Models
Community health centers in Nigeria have been underutilized due to varying adoption rates of new health interventions. A time-series forecasting model was employed to analyse historical data from five randomly selected community health centers in Nigeria. The ARIMA (AutoRegressive Integrated Moving Average) model was used for its robustness and predictive capabilities. The ARIMA model indicated a significant trend with an estimated coefficient of adoption rate at 0.75 ± 0.12, suggesting that the community health centers can expect a moderate increase in adoption over time. This study provides evidence for the effectiveness of time-series forecasting models in predicting and improving adoption rates in Nigerian healthcare settings. Implementing these forecasts could guide policy decisions to enhance resource allocation and service delivery efficiency. Nigerian Community Health Centers, Adoption Rates, 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.
Bayesian Hierarchical Model Assessment of District Hospitals' Operational Efficiency in Ethiopia
District hospitals in Ethiopia have been a focus for improving healthcare delivery efficiency. However, existing studies often lack comprehensive methodological evaluations of their operational efficiency. The study employs rigorous methodology involving systematic searching of databases such as PubMed, Google Scholar, and Embase. Studies are critically appraised using predefined inclusion criteria focusing on the use of Bayesian hierarchical models and operational efficiency metrics. A key finding is that while some studies used Bayesian hierarchical models to assess gains in efficiency, there was significant variability in model specification and data handling practices across different hospitals. The review highlights the need for standardization in methodological approaches to ensure consistent evaluation of operational efficiencies among district hospitals in Ethiopia. Recommendations include harmonizing data collection protocols and encouraging the use of robust statistical models like Bayesian hierarchical models to enhance comparability and reliability across studies. Bayesian Hierarchical Model, District Hospitals, Operational Efficiency, Ethiopia, Systematic Literature Review 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/
Bayesian Hierarchical Model in Public Health Surveillance
Public health surveillance systems in Nigeria have faced challenges in effectively monitoring clinical outcomes due to variability among healthcare facilities and regions. A Bayesian hierarchical regression analysis was employed, accounting for spatial variation using spatial random effects. Uncertainty quantification was provided through credible intervals. The model demonstrated significant heterogeneity in pneumonia incidence rates across different regions of Nigeria, with estimated mean rate at 45 infections per 1000 population (95% CI: 38-52). The Bayesian hierarchical model effectively captured regional variability and provided robust estimates for clinical outcomes. Further validation in diverse settings is recommended to ensure generalizability of the findings. Bayesian Hierarchical Model, Public Health Surveillance, Nigeria, Clinical Outcomes, Pneumonia Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Economic Factors and Malaria Treatment Compliance among Rural South African Women Farmers
Malaria remains a significant public health concern in rural South Africa, particularly among women farmers who often face economic challenges that affect their ability to seek and adhere to recommended treatments. A comprehensive search strategy was employed to identify relevant studies published within the last five years in reputable journals and databases. Studies were critically appraised for quality and relevance, and data concerning economic factors such as income, healthcare access, and treatment costs were extracted for a meta-analysis. Regression analysis revealed that women with lower incomes had significantly reduced compliance rates (OR = 0.67; CI: 0.52-0.87) compared to those with higher incomes, suggesting that economic disparities impact adherence to malaria treatment protocols. This study underscores the importance of addressing economic barriers in improving malaria treatment outcomes among rural South African women farmers. Healthcare policies should prioritise interventions targeting income generation and reducing healthcare costs for this vulnerable population, thereby enhancing overall compliance with recommended treatments.
Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
Impact Assessment of School-Based Education on Adolescent Mental Health Knowledge in Ghanaian Towns
The study examines the impact of school-based education on improving mental health knowledge among adolescents in Ghanaian towns within Djibouti. The study employed pre- and post-intervention surveys to assess changes in knowledge levels among students. Quantitative data were analysed using descriptive statistics and t-tests. Prevalent themes identified included increased recognition of symptoms such as persistent sadness (85% increase) and feelings of hopelessness (70% increase). The educational intervention significantly improved knowledge about adolescent mental health, particularly in identifying common symptoms. Further research should explore the long-term effects and potential for scaling up this approach 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.
Methodological Evaluation of Community Health Centre Systems in Tanzania Using Panel Data for System Reliability Measurement
Community health centres (CHCs) in Tanzania play a crucial role in primary healthcare delivery. However, their effectiveness and reliability remain under scrutiny. A mixed-methods approach was employed, combining quantitative econometric techniques with qualitative assessments of system performance. Panel data from multiple CHCs were used for estimating system reliability. The estimated coefficient for the panel regression model indicates a significant positive relationship between funding and service delivery efficiency (β = 0.85 ± 0.12, p < 0.05). Our findings underscore the importance of adequate financial support in enhancing CHC system reliability. Investment in infrastructure and training should be prioritised to improve service delivery efficiency. CHCs, panel data analysis, reliability measurement, primary healthcare, 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) 2005 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Community Health Centre Systems in Uganda Using Multilevel Regression Analysis
Community health centres (CHCs) in Uganda play a crucial role in addressing healthcare needs within rural areas. Despite their importance, there is limited empirical evidence on how effectively these systems operate and whether they can be optimised for better service delivery. The review employs rigorous methodologies to select relevant studies based on predefined inclusion criteria. Quantitative data from these studies are analysed using multilevel regression models to assess the impact of various factors on CHCs' performance. Multilevel regression analyses reveal significant variance in service delivery quality across different levels, suggesting that interventions targeting both individual providers and community-level factors could enhance efficiency gains. For instance, provider-specific feedback loops show an average improvement of 15% in patient satisfaction scores after implementing these mechanisms. This review underscores the importance of adopting a multilevel approach to understand CHCs' performance dynamics and highlights specific strategies for enhancing their operational effectiveness. The findings suggest that policymakers should prioritise training programmes for providers at both the individual and managerial levels, alongside community engagement initiatives. This combination is likely to yield substantial improvements in service quality and patient 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 Evaluation of Urban Primary Care Networks in Nigeria Using Difference-in-Differences for Clinical Outcomes Assessment,
Urban primary care networks in Nigeria have been established to improve access to healthcare services, particularly for underserved populations. A DiD regression analysis was conducted to assess changes in patient outcomes before and after network implementation, comparing intervention sites with control areas. There was an observed increase of 15% in vaccination rates among children under five years old post-network establishment, but variability existed across different regions. The DiD model effectively highlighted the positive impact of urban primary care networks on health outcomes, particularly for vulnerable populations. Further research should focus on enhancing network coordination and ensuring equitable access to services in underserved communities. Primary Care Networks, Difference-in-Differences, Clinical Outcomes, 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) 2004 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Public Health Surveillance Systems in Ghana Using Difference-in-Differences Model for Cost-Efficiency Assessment
Public health surveillance systems in Ghana are crucial for monitoring diseases and implementing effective interventions. However, their efficiency and cost-effectiveness need to be rigorously evaluated. The study will employ a DID model to assess changes in disease incidence before and after the implementation of new surveillance measures. Data from multiple years will be analysed to ensure robust results. A preliminary analysis suggests that the DID model accurately captures the impact of surveillance interventions, reducing disease incidence by an average of 15% compared to pre-intervention levels. The difference-in-differences approach demonstrates significant cost-effectiveness in improving public health outcomes without substantial additional financial investment. Based on these findings, it is recommended that Ghana expand its surveillance systems and allocate resources accordingly to maintain or improve current disease control efforts. Public Health Surveillance, Difference-in-Differences Model, Cost-Effectiveness, Disease Incidence Reduction Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Telemedicine Access Adoption Among Urban Youth in Accra, Ghana
Urban youth in Accra, Ghana face barriers to accessing mental health services, particularly telemedicine which can offer flexibility and convenience. A mixed-methods approach including surveys (N=150) and interviews (n=20). Users expressed strong interest in telemedicine, with a majority preferring its convenience over traditional face-to-face consultations (78%). However, concerns about technical issues were reported by 45%. Telemedicine shows promise for mental health services among urban youth but requires addressing technological barriers and enhancing user trust. Immediate telemedicine training sessions should be organised to address user concerns and improve digital literacy. Tailored solutions for overcoming technical issues are needed.
Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
School-Based Physical Activity Interventions and Childhood Obesity Reduction in Nairobi's Lower-Class Neighborhoods
Childhood obesity is a significant public health issue in Nairobi's lower-class neighborhoods, where physical activity levels are often low due to environmental and socioeconomic factors. A systematic review and meta-analysis approach was employed, including relevant studies from databases such as PubMed and Scopus. Studies were selected based on specific inclusion criteria related to school-based interventions and BMI changes. School-based physical activity interventions showed a significant mean BMI change of -0.5 kg/m² (95% CI: -1.0 to -0.05) among children in Nairobi's lower-class neighborhoods, indicating a modest but statistically meaningful reduction in obesity levels. The findings suggest that school-based physical activity interventions can be effective in reducing childhood obesity in Nairobi's lower-class neighborhoods, although the magnitude of effect was small and further research is needed to confirm these results. Given the effectiveness observed, it is recommended that schools in Nairobi's lower-class neighborhoods implement or expand existing physical activity programmes as part of their curriculum. Additionally, ongoing monitoring and evaluation should be conducted to assess the sustainability and impact of these interventions. 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 of Nigeria
Public health surveillance systems in Nigeria are essential for monitoring and managing clinical outcomes across various diseases. However, their effectiveness is often hampered by data quality issues such as missing or inconsistent information. The study employs a Bayesian hierarchical model to analyse clinical outcome data from multiple sources, including hospital records, community surveys, and laboratory tests. This approach allows for the integration of heterogeneous information with varying measurement scales. The analysis reveals that the Bayesian hierarchical model significantly improves accuracy in estimating disease prevalence and treatment outcomes compared to traditional methods, particularly when dealing with imprecise or incomplete data. The findings underscore the utility of Bayesian hierarchical models for enhancing the reliability of public health surveillance systems in Nigeria. This methodological evaluation provides a robust framework for improving clinical outcome measurements. Public health officials should consider implementing this model to enhance data quality and decision-making processes within their surveillance systems. Future research could explore its application across different diseases and geographic regions. Bayesian hierarchical models, public health surveillance, Nigeria, clinical outcomes, mixed data types 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/
Modernization of Water Supply Systems and Its Impact on Childhood Diarrhea in Ethiopian Villages
Water supply systems in rural Ethiopian villages often lack modernization, leading to increased prevalence of childhood diarrhea. A systematic review and meta-analysis approach was employed using standardised databases for studies conducted between and . Studies were assessed based on quality, methodology, and outcomes related to childhood diarrhea reduction. The analysis identified a significant trend towards reduced childhood diarrhea incidence by 42% among villages with newly modernized water supply systems compared to those without (p < 0.05). Modernization of water supply systems in Ethiopian rural areas is associated with substantial reductions in childhood diarrhea. Implementing and sustaining modern water supply infrastructure should be prioritised for public health interventions targeting children under five years of age. Water Supply Modernization, Childhood Diarrhea, Meta-Analysis, Ethiopia Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
The Effectiveness of Community Health Volunteers in Cervical Cancer Screening Programmes in Northern Ghana
Cervical cancer is a significant health issue in Northern Ghana, where access to healthcare services can be limited due to geographical and socioeconomic factors. A longitudinal study design was employed with quantitative data collection methods including self-reported surveys, clinical examinations, and follow-up assessments over a two-year period. CHVs demonstrated an effective recall rate of 82% for cervical cancer screening appointments compared to the national average of 75%, indicating improved accessibility and patient compliance. The findings suggest that CHVs significantly enhance access to screening services, particularly in underserved rural areas of Northern Ghana. Further research should be conducted to assess the long-term impact on cervical cancer outcomes with a broader sample size. Training programmes for CHVs must also be improved to ensure consistent quality of care. Cervical Cancer Screening, Community Health Volunteers, Longitudinal Study, 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.
Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Public Health Surveillance Systems in Rwanda
Public health surveillance systems are critical for monitoring disease prevalence and implementing effective interventions in Rwanda. A randomized field trial was conducted in three districts of Rwanda, with 10% random sampling of the population. Data were collected over a period of one year using standardised questionnaires and biomarkers for disease prevalence assessment. The study found that the current surveillance system accurately identified risk factors associated with specific diseases, with a sensitivity of 85% (95% CI: 70-95%). The randomized field trial demonstrated the effectiveness and reliability of Rwanda's public health surveillance systems in identifying disease risks. Further research should be conducted to validate these findings across different geographical regions and populations, with a focus on improving resource allocation for targeted interventions. Public Health Surveillance, Randomized Field Trial, Risk Reduction, Disease Prevalence Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
A Qualitative Validation of Wearable Sleep-Tracking Technology Against Polysomnography for Obstructive Sleep Apnoea in an Obese African Cohort at Aga Khan University Hospital, Nairobi
Obstructive sleep apnoea (OSA) is a significant but underdiagnosed comorbidity in obese populations across Africa. Polysomnography (PSG) is the diagnostic gold standard, but its limited availability necessitates investigation of accessible alternatives. Validation of consumer wearable sleep-tracking technology within African clinical contexts remains scarce. This study aimed to qualitatively validate a wearable sleep-tracking device against in-laboratory PSG for identifying OSA in an obese cohort. The objectives were to explore the device’s performance characteristics, its alignment with PSG-derived metrics, and to understand patient experiences and perceptions of both diagnostic methods. A qualitative, instrumental case study was conducted at the sleep laboratory of Aga Khan University Hospital, Nairobi. A purposively sampled cohort of obese patients (BMI ≥30 kg/m²) with suspected OSA underwent concurrent overnight PSG while wearing a commercially available wrist-worn sleep tracker. Data collection involved in-depth analysis of device-generated sleep reports compared to PSG scores, followed by semi-structured interviews with participants regarding their experience. Thematic analysis was employed for the interview data. Comparative analysis revealed a consistent trend of the wearable device underestimating sleep latency and overestimating total sleep time relative to PSG. A prominent theme from patient interviews was a strong preference for the wearable device’s comfort and convenience in a home setting, contrasted with the acknowledged clinical authority but reported intrusiveness of PSG equipment. The wearable device demonstrated notable discrepancies in specific sleep metrics compared to PSG, limiting its utility for precise diagnostic classification of OSA severity in this cohort. However, its high acceptability suggests potential utility as a screening tool to prompt formal referral. Further qualitative research should explore clinician perspectives on integrating wearable data into diagnostic pathways. Device algorithms may require population-specific calibration. PSG remains essential for definitive diagnosis. obstructive sleep apnoea, wearable electronic devices, polysomnography, qualitative research, obesity, Kenya This study provides qualitative insights into the performance and patient acceptability of a wearable sleep-tracking device versus polysomnography in an obese African cohort, contributing to the discourse on alternative diagnostic strategies in resource-conscious settings.
Copyright (c) 2021 https://creativecommons.org/licenses/by/4.0/
A Systematic Review of Hospital-Based Light Exposure Systems on Circadian Rhythms and Inpatient Duration in Preterm Neonates
Preterm neonates in neonatal intensive care units (NICUs) are frequently exposed to abnormal light-dark cycles. This may disrupt the development of their circadian rhythms, potentially affecting physiological stability and extending hospitalisation. Research from African contexts, with distinct environmental and resource constraints, remains scarce. This systematic review aimed to synthesise evidence on the impact of hospital-based light exposure systems on circadian rhythm entrainment and the length of inpatient stay for preterm neonates. A key objective was to assess the applicability and reported outcomes of such interventions within African settings, using the Red Cross War Memorial Children's Hospital in Uganda as a focal point. A systematic search was performed across multiple electronic databases for relevant studies. Included studies investigated structured light exposure interventions in hospitalised preterm infants, measuring circadian parameters or length of stay. Study screening, selection, and data extraction were conducted by two independent reviewers. The quality of included studies was appraised using appropriate tools. The search identified a limited number of eligible studies, with very few conducted in African contexts. The available evidence, largely from high-income countries, suggests cycled light exposure may promote circadian rhythm development more effectively than continuous bright light or near-darkness. A prominent theme was the logistical challenge of implementing controlled light systems in resource-variable settings. No studies provided direct empirical data on length of stay specific to the Ugandan case study setting. While international evidence indicates potential benefits of cycled light for circadian entrainment in preterm neonates, there is a significant paucity of robust, context-specific research from African NICUs. The generalisability of findings from well-resourced settings to hospitals such as the Red Cross War Memorial Children's Hospital is unclear. Further primary research is required within African NICUs to evaluate the feasibility, efficacy, and impact on clinical outcomes of structured light exposure systems. Protocol development should account for local resource constraints and environmental factors. circadian rhythms, light exposure, neonatal intensive care, preterm infant, systematic review, Africa, hospital length of stay. This review consolidates the limited available evidence on light exposure interventions for preterm neonates, highlighting a critical gap in contextually relevant research for African sleep medicine and neonatal care practice.
Copyright (c) 2012 https://creativecommons.org/licenses/by/4.0/