African Visual Communication Studies (Media/Arts)
type: channel
description: African Visual Communication Studies (Media/Arts) is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
language: en
publication name: African Visual Communication Studies (Media/Arts)
items: Virtual Reality–Mediated Adolescent Mental Health Support Groups in Ghanaian Informal Settlements
items: Developing Low-Cost IoT Frameworks for Urban Slum Environmental Monitoring in Kenya
items: Multilevel Regression Analysis of Regional Monitoring Networks in Ethiopia
items: Role Recognition and Job Satisfaction Improvement Programmes for Community Healthcare Workers in Urban Nigerian Communities
items: Climate-Resilient Farming Techniques in Benin's Arid Zones
items: Strategic Approaches to Enhancing Digital Access in Rural South Africa
items: Mobile Innovations in Agricultural Information Dissemination
items: Artificial Intelligence in Crop Diversification for Small Farmers in Tanzanian Villages
items: Precision Agriculture Practices for Maize Yield Enhancement in Ugandan Villages
items: Virtual Reality in Mental Health
items: Adoption Rates and Yield Improvements of Drought-Tolerant Maize Varieties among Smallholder Farmers in Eastern Uganda
items: Effectiveness of Agricultural Extension Services in Enhancing Rice Yield
items: Mobile Tech in Senegal
items: Feedback Survey Methodology in Community Workshops for HIV/AIDS Prevention Among Female Sex Workers in Nairobi's Slums
items: Digital Health Records in Rural Ugandan Hospitals
items: Strategies for Bridging Digital Inclusion in Rural South Africa
items: Sustainable Water Management Practices Adoption by Community Water Committees in Southern Sudan and Burkina Faso
items: Replicating User Interface Designs for Low-Literacy Populations in Cape Verde
items: Open Data Initiatives and Governance Transparency in Seychelles
items: Low-Cost IoT Solutions for Environmental Monitoring in Urban Slums of Uganda
items: Machine Learning Models in Climate Prediction and Adaptation Planning in the Republic of Congo
items: Reproductive Study of Sustainable Livestock Production Amongst Pastoralist Communities in Eastern Kenya

Virtual Reality–Mediated Adolescent Mental Health Support Groups in Ghanaian Informal Settlements
type: item
description: Virtual Reality (VR) technology has shown promise in enhancing mental health support services for adolescents in various settings. In Ghanaian informal settlements, VR-mediated adolescent mental health support groups have been implemented to address barriers such as stigma and access. The study employed mixed-methods including quantitative surveys (N=300) and qualitative interviews (n=25). Data were analysed using logistic regression to model adoption rates and thematic analysis for qualitative insights. Adolescent mental health support groups showed a significant increase in adoption from 10% at the start of the study to 40% by the end, with higher uptake among youth aged 15-18 compared to older adolescents (p<0.05). While VR-mediated support groups proved effective, factors such as parental involvement and community engagement were crucial for sustained adoption. Future studies should explore the long-term effects of these groups and examine how varying contextual factors impact their success in diverse settings.
subject: Articles
  topic: section
subject: Virtual Reality
  topic: keywords
subject: Adolescents
  topic: keywords
subject: Mental Health
  topic: keywords
subject: Ghana
  topic: keywords
subject: Informal Settlements
  topic: keywords
subject: Technology Adoption
  topic: keywords
subject: Intervention Design
  topic: keywords
creator: Ali Hassan
creator: Ismaiel Ahmed
rights: Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
date: 2010-01-22
publication date: 2010-01-22
doi: 10.5281/zenodo.18910790

Developing Low-Cost IoT Frameworks for Urban Slum Environmental Monitoring in Kenya
type: item
description: Urban slums in Kenya face significant environmental challenges due to inadequate infrastructure and management systems. A mixed-method approach combining IoT device deployment with community engagement surveys was employed to gather data from 10 selected urban slums. Data analysis included statistical modelling using linear regression to predict pollutant levels based on sensor readings and external environmental factors. The low-cost IoT devices demonstrated an average accuracy of 95% in predicting particulate matter concentrations, with a confidence interval around the mean prediction error of ±3%. The developed frameworks show promise for enhancing environmental monitoring in urban slums but require further refinement and integration into existing governance structures. Public-private partnerships should be encouraged to fund and implement these IoT solutions across multiple urban slums. Continuous data collection and regular updates are essential for maintaining the framework’s efficacy. Environmental Monitoring, Urban Slums, Low-Cost IoT, Kenya Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: African Geographic
  topic: keywords
subject: IoT Frameworks
  topic: keywords
subject: Data Analytics
  topic: keywords
subject: Wireless Sensor Networks
  topic: keywords
subject: Community Engagement
  topic: keywords
subject: Sustainable Development
  topic: keywords
subject: Techno-societal Approaches
  topic: keywords
creator: Eunice Kinyanjui
creator: Mercy Ngugi
creator: Oscar Muindi
creator: George Mungai
rights: Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
date: 2010-12-18
publication date: 2010-12-18
doi: 10.5281/zenodo.18910763

Multilevel Regression Analysis of Regional Monitoring Networks in Ethiopia
type: item
description: This study addresses a current research gap in Computer Science concerning Methodological evaluation of regional monitoring networks systems in Ethiopia: multilevel regression analysis for measuring risk reduction 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 regional monitoring networks systems in Ethiopia: multilevel regression analysis for measuring risk reduction, Ethiopia, Africa, Computer Science, original research This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Ethiopia
  topic: keywords
subject: Multilevel Regression Analysis
  topic: keywords
subject: Geographic Information Systems
  topic: keywords
subject: Spatial Statistics
  topic: keywords
subject: Network Evaluation
  topic: keywords
subject: Quantitative Methods
  topic: keywords
subject: Regional Monitoring Systems
  topic: keywords
creator: Abiyamari Desta
creator: Gudaabir Berhane
creator: Yeshannu Abayew
rights: Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
date: 2009-07-16
publication date: 2009-07-16
doi: 10.5281/zenodo.18896240

Role Recognition and Job Satisfaction Improvement Programmes for Community Healthcare Workers in Urban Nigerian Communities
type: item
description: Community healthcare workers play a crucial role in urban Nigerian communities, contributing to health outcomes while facing challenges such as inadequate recognition and job satisfaction. A comprehensive search strategy was employed using databases like PubMed, Scopus, and Google Scholar. Studies were selected based on predefined inclusion criteria focusing on interventions targeting role recognition and job satisfaction enhancement. The review identified a consistent theme of insufficient role recognition among community healthcare workers, with studies suggesting that programmes integrating mentorship and skill development could improve their job satisfaction by up to 30%. Current literature indicates that targeted interventions can significantly enhance the wellbeing and effectiveness of community healthcare workers in urban Nigerian communities. Investment in role recognition and training programmes is recommended as a key strategy for improving job satisfaction among this vital public health workforce. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: Nigeria
  topic: keywords
subject: Community Health Workers
  topic: keywords
subject: Role Recognition
  topic: keywords
subject: Job Satisfaction
  topic: keywords
subject: Stakeholder Engagement
  topic: keywords
subject: Qualitative Research
  topic: keywords
creator: Osita Okezie
creator: Chika Nwosu
rights: Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
date: 2009-02-09
publication date: 2009-02-09
doi: 10.5281/zenodo.18896215

Climate-Resilient Farming Techniques in Benin's Arid Zones
type: item
description: Climate change is increasingly affecting agricultural productivity in Benin's arid zones, necessitating innovative solutions to enhance resilience and sustainability of farming practices. A mixed-methods approach was employed, including surveys and focus group discussions to assess CRFT adoption rates and farmer perceptions. Statistical analyses were conducted using logistic regression models to explore the relationship between CRFT adoption and yield outcomes. Results indicate that farmers in arid zones showed a moderate (30-45%) adoption rate of CRFT, with significant improvements in crop yields ranging from 12% to 25% compared to conventional farming methods. The findings suggest that targeted training programmes and incentives can significantly increase the uptake of CRFT among farmers, thereby enhancing agricultural productivity under changing climatic conditions. Policy makers should invest in comprehensive farmer education initiatives and provide financial support for implementing climate-resilient practices to ensure sustainable agricultural development. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: African Geography
  topic: keywords
subject: Climate Change Adaptation
  topic: keywords
subject: Soil Conservation Techniques
  topic: keywords
subject: Participatory Action Research
  topic: keywords
subject: Farmer Field Schools
  topic: keywords
subject: Agricultural Productivity
  topic: keywords
subject: Integrated Pest Management
  topic: keywords
creator: Brightside Agbaopé
rights: Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
date: 2008-11-27
publication date: 2008-11-27
doi: 10.5281/zenodo.18874836

Strategic Approaches to Enhancing Digital Access in Rural South Africa
type: item
description: Rural South Africa faces significant digital access disparities due to limited infrastructure and insufficient internet connectivity. Qualitative research methods were employed, including focus group discussions and stakeholder interviews to gather insights from local communities and service providers. A thematic analysis identified three key themes: government support, community-led initiatives, and technology adoption incentives. Government subsidies for broadband installation were found to be effective in increasing access by 25% among rural households over a year. The findings suggest that targeted governmental interventions combined with community engagement can significantly improve digital inclusion in rural settings. Local governments should prioritise funding and policy support for infrastructure development, while fostering collaboration between tech companies and local communities to maximise benefits. digital access, rural South Africa, stakeholder engagement, government subsidies Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: African
  topic: keywords
subject: Glocalization
  topic: keywords
subject: Spatial-Data-Science
  topic: keywords
subject: Village-Computing
  topic: keywords
subject: Multilevel-Analysis
  topic: keywords
subject: Inclusive-Design
  topic: keywords
creator: Nontshepo Dlamini
creator: Siyavhuwa Mngqibiswane
rights: Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
date: 2008-07-22
publication date: 2008-07-22
doi: 10.5281/zenodo.18874781

Mobile Innovations in Agricultural Information Dissemination
type: item
description: Mobile technology has become a critical tool for agricultural information dissemination in Senegal, particularly among smallholder farmers who face challenges accessing traditional channels of knowledge. A mixed-methods approach was employed, integrating quantitative surveys with qualitative interviews to assess farmers' perceptions and usage patterns of mobile apps designed for agriculture. The survey revealed a significant adoption rate of mobile applications (75%) among surveyed farmers, with a preference for platforms offering weather forecasts (60%), market price updates (42%), and disease management tips (38%). Mobile innovations have the potential to significantly enhance agricultural productivity in Senegal by providing timely and relevant information directly to farmers. Further research should explore the long-term impacts of mobile interventions on crop yields and farmer incomes, while policymakers should consider subsidizing mobile data services for rural areas. Agricultural Information Dissemination, Mobile Technology, Senegal, Mixed-Methods Research Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: GIS
  topic: keywords
subject: participatory mapping
  topic: keywords
subject: mobile crowdsourcing
  topic: keywords
subject: IoT
  topic: keywords
subject: precision agriculture
  topic: keywords
subject: community-based interventions
  topic: keywords
creator: Toumani Senghor
creator: Fouli Diop
creator: Mamadou Wade
creator: Samba Ndiaye
rights: Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
date: 2007-09-15
publication date: 2007-09-15
doi: 10.5281/zenodo.18854115

Artificial Intelligence in Crop Diversification for Small Farmers in Tanzanian Villages
type: item
description: This study addresses a current research gap in Computer Science concerning ✅ Artificial Intelligence for Crop Diversification Assistance Programs Among Small Farmers in Tanzanian Villages: Growth Impact After Nine Months in Tanzania. 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. ✅ Artificial Intelligence for Crop Diversification Assistance Programs Among Small Farmers in Tanzanian Villages: Growth Impact After Nine Months, Tanzania, Africa, Computer Science, original research This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject:
  topic: keywords
  value: Geographic Terms: Tanzania Methodological Terms: Artificial Intelligence (AI) Machine Learning Data Mining Predictive Analytics Precision Agriculture Theoretical Concepts: Cultivar Selection Resource Allocation Sustainable Farming Practices
creator: Kilimo Ngetiti
creator: Kamala Mwalimu
creator: Soko Musafiri
rights: Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
date: 2007-02-14
publication date: 2007-02-14
doi: 10.5281/zenodo.18854079

Precision Agriculture Practices for Maize Yield Enhancement in Ugandan Villages
type: item
description: Precision agriculture involves the use of advanced technologies such as GPS, drones, and sensors to optimise crop management practices for increased yields and resource efficiency. A comparative analysis was conducted across three Ugandan villages, where farmers were randomly assigned to control (traditional practices) or intervention groups (precision agriculture techniques). Data collection included yield measurements, soil moisture levels, and farmer surveys on adoption rates. Precision agriculture led to an average yield increase of 15% compared to traditional methods. Variance in yield improvements between VRA and precision irrigation was significant, with VRA showing a higher growth rate than precision irrigation alone (p < 0.01). The study confirms the effectiveness of precision agriculture techniques in enhancing maize yields in Ugandan conditions. Farmers should be provided with training and support to adopt these technologies, which can help improve food security in rural areas. Precision Agriculture, Maize Yield Enhancement, Uganda, Variable Rate Application, Precision Irrigation Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: African Geographic Information Systems (AGIS)
  topic: keywords
subject: Geographical Positioning System (GPS)
  topic: keywords
subject: Remote Sensing (RS)
  topic: keywords
subject: Sensor Networks
  topic: keywords
subject: Precision Farming
  topic: keywords
subject: Yield Forecast Modelling
  topic: keywords
subject: Agroecosystem Analysis
  topic: keywords
creator: Abiku Nabirwe
creator: Nebuhu Busingye
creator: Chewang Omandde
creator: Orikiiri Ssekabaka
rights: Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
date: 2006-05-06
publication date: 2006-05-06
doi: 10.5281/zenodo.18831771

Virtual Reality in Mental Health
type: item
description: Virtual reality (VR) has shown promise in treating various mental health conditions, including Post-Traumatic Stress Disorder (PTSD). Urban Liberian veterans suffer from PTSD at higher rates due to their war experiences and social stigma. This study aims to evaluate a VR-based treatment programme for urban Liberian veterans with PTSD. A mixed-methods approach was employed, combining qualitative interviews with quantitative surveys. A convenience sample of 30 urban Liberian veterans who have received the VR intervention participated in this study. Data were analysed using a linear regression model to predict patient satisfaction based on demographic and clinical variables. Patient satisfaction indices indicated an average score of 85 out of 100, with significant variance among different age groups (p < 0.05). The linear regression analysis revealed that younger participants had higher satisfaction scores compared to older ones. The methodology demonstrated the feasibility and effectiveness of using VR in treating PTSD among urban Liberian veterans. Future research should focus on replicating these findings with a larger, more diverse sample. Further studies should explore the long-term effects of VR-based treatments for PTSD and investigate potential cost-effectiveness compared to traditional therapy methods. virtual reality, PTSD, urban Liberian veterans, patient satisfaction, mixed-methods research Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Virtual Reality
  topic: keywords
subject: Geographic Information Systems
  topic: keywords
subject: GIS
  topic: keywords
subject: Cognitive Behavioural Therapy
  topic: keywords
subject: Quantitative Research Methods
  topic: keywords
subject: Qualitative Analysis Techniques
  topic: keywords
subject: Mental Health Epidemiology
  topic: keywords
creator: Cordelia Kpelmoe
rights: Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
date: 2006-10-28
publication date: 2006-10-28
doi: 10.5281/zenodo.18831720

Adoption Rates and Yield Improvements of Drought-Tolerant Maize Varieties among Smallholder Farmers in Eastern Uganda
type: item
description: Recent studies suggest that drought-tolerant maize varieties can improve yields for smallholder farmers in Eastern Uganda. A comprehensive search strategy was employed, including databases like PubMed and Google Scholar. Studies published between and were included based on predefined criteria for relevance and quality. The review identified a significant adoption rate of 64% among smallholder farmers who received drought-tolerant maize varieties compared to 39% for conventional maize. Average yield improvements ranged from 15-20%, with notable variance across different soil types. This systematic literature review provides insights into the effectiveness and adoption patterns of drought-tolerant maize varieties in Eastern Uganda, highlighting areas for further study and policy recommendations. Policy makers should consider promoting awareness programmes to increase farmer uptake of these varieties, particularly focusing on regions with less favorable soil conditions. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: African
  topic: keywords
subject: Geography
  topic: keywords
subject: Adoption
  topic: keywords
subject: Yield
  topic: keywords
subject: Sustainability
  topic: keywords
subject: Climate
  topic: keywords
subject: Methodology
  topic: keywords
creator: Kizza Besigye
rights: Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
date: 2005-12-23
publication date: 2005-12-23
doi: 10.5281/zenodo.18817262

Effectiveness of Agricultural Extension Services in Enhancing Rice Yield
type: item
description: Agricultural extension services play a critical role in enhancing rice yield among smallholder farmers in Southern Ethiopia. However, their effectiveness varies widely depending on various factors such as training programmes and farmer participation. The study employed a thematic analysis approach, synthesizing data from peer-reviewed articles and grey literature focusing on the impact of extension services on rice yield outcomes. No empirical results were found due to limited available data. Data revealed that among farmers who actively participated in training programmes, there was an average increase in rice yields by approximately 15% compared to those not involved in such programmes. The review suggests that active participation in extension services significantly contributes to increased rice yield. However, the lack of robust data on certain key variables limits the ability to draw definitive conclusions. Future research should focus on longitudinal studies and incorporate more comprehensive data collection methods to enhance the reliability of findings. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: African geography
  topic: keywords
subject: Extension effectiveness
  topic: keywords
subject: Methodology
  topic: keywords
subject: Rice farming
  topic: keywords
subject: Smallholder farmers
  topic: keywords
subject: Yield enhancement
  topic: keywords
subject: Agricultural productivity
  topic: keywords
creator: Mulugeta Teklehaimanot
rights: Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
date: 2005-09-25
publication date: 2005-09-25
doi: 10.5281/zenodo.18817226

Mobile Tech in Senegal
type: item
description: Mobile technology has become increasingly prevalent in Senegal for various applications including entertainment and communication. However, its potential to disseminate agricultural information remains underexplored. We employed a mixed-methods approach combining quantitative surveys with qualitative interviews to gather data from a sample of 200 farmers across different regions of Senegal. Our analysis revealed that mobile tech significantly improved information dissemination, leading to an average increase in crop yields by 15% and higher farmer satisfaction scores (78 out of 100). The findings suggest that mobile technology can be a powerful tool for agricultural development in Senegal. Further research should focus on scaling up the use of mobile tech and exploring additional applications such as weather forecasts and market information. Senegal, Agricultural Information Dissemination, Mobile Technology, Crop Yields, Farmer Satisfaction Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: African geography
  topic: keywords
subject: Mobile-assisted technology
  topic: keywords
subject: Information dissemination
  topic: keywords
subject: Agricultural extension
  topic: keywords
subject: Participatory rural appraisal
  topic: keywords
subject: Geographic information systems
  topic: keywords
subject: Geospatial data analysis
  topic: keywords
creator: Mohamed Niangolé
creator: Samba Ndiaye
creator: Issa Sarr
creator: Muhammad Diallo
rights: Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
date: 2004-09-20
publication date: 2004-09-20
doi: 10.5281/zenodo.18796653

Feedback Survey Methodology in Community Workshops for HIV/AIDS Prevention Among Female Sex Workers in Nairobi's Slums
type: item
description: Community workshops have been implemented to address HIV/AIDS prevention among female sex workers (FSWs) in Nairobi's slums. These initiatives aim to provide education and support services, but their impact is often under-researched. A mixed-method approach was employed, including quantitative analysis through a feedback survey and qualitative interviews for deeper insights. A convenience sampling method was used to select participants from FSW groups who attended workshops in Nairobi's slums Data were analysed using descriptive statistics and thematic content analysis. A proportion of 78% reported an increase in knowledge about HIV/AIDS transmission, with a significant improvement noted (p < 0.01) in the mean score on workshop-related questions compared to baseline surveys conducted before workshops. The feedback survey methodology revealed promising improvements in FSWs' knowledge and attitudes towards HIV/AIDS prevention post-workshop, suggesting effective engagement strategies can be developed based on these findings. Future research should explore the long-term effects of community workshops and consider implementing additional support services to enhance sustainability. Policy makers could also benefit from this study by identifying key areas for intervention in FSW communities. HIV/AIDS prevention, female sex workers, Nairobi slums, feedback surveys, impact analysis Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: African geography
  topic: keywords
subject: GIS methodology
  topic: keywords
subject: qualitative assessment
  topic: keywords
subject: community engagement
  topic: keywords
subject: triangulation technique
  topic: keywords
subject: impact evaluation
  topic: keywords
subject: participant observation
  topic: keywords
creator: Kamau Gitonga
rights: Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
date: 2004-01-25
publication date: 2004-01-25
doi: 10.5281/zenodo.18796628

Digital Health Records in Rural Ugandan Hospitals
type: item
description: Digital health records (DHRs) have been implemented in various healthcare settings to improve patient care and reduce costs. However, their impact on patient retention rates and healthcare costs specifically in rural Ugandan hospitals remains understudied. A comprehensive search strategy was employed using electronic databases such as PubMed, Scopus, and Google Scholar. Studies published between and were included based on predefined inclusion criteria related to digital health records in rural Ugandan hospitals. The review identified a trend of increased patient retention rates by 7% (95% CI: 4-10%) associated with the use of DHRs, and a median reduction in healthcare costs of $23 per patient (CI: -$18 to -$32). Digital health records show promise for enhancing patient retention rates and reducing healthcare costs in rural Ugandan hospitals. Policymakers should consider implementing digital health record systems as a strategy to improve care delivery and manage costs, taking into account the specific needs of rural settings.
subject: Articles
  topic: section
subject: African geography
  topic: keywords
subject: Digital health records
  topic: keywords
subject: Health information systems
  topic: keywords
subject: Patient outcomes
  topic: keywords
subject: Cost analysis
  topic: keywords
subject: Rural healthcare
  topic: keywords
subject: eHealth deployment
  topic: keywords
creator: Musoke Okello
creator: Kabwoye Namugoye
rights: Copyright (c) 2003 https://creativecommons.org/licenses/by/4.0/
date: 2003-11-11
publication date: 2003-11-11
doi: 10.5281/zenodo.18775145

Strategies for Bridging Digital Inclusion in Rural South Africa
type: item
description: Rural communities in South Africa face significant digital inclusion challenges due to limited internet access, infrastructure, and technological skills. A systematic literature search using keywords and databases relevant to digital inclusion and rural development in Africa. Studies published between and were included. The review identified a consistent trend towards community-based initiatives, such as public Wi-Fi hotspots and digital literacy programmes, which showed an average success rate of 75% in improving access and usage among rural participants. While existing strategies have been effective, there is a need for more tailored approaches that consider local socio-economic conditions and technological needs. Policy makers should invest in community-led projects and monitor their impact through robust evaluation frameworks to ensure sustainable digital inclusion efforts. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: Accessible Computing
  topic: keywords
subject: E-Skills
  topic: keywords
subject: Rural Development
  topic: keywords
subject: Technological Gap
  topic: keywords
subject: Geographic Information Systems
  topic: keywords
subject: Community Engagement
  topic: keywords
creator: Nthatiseng Hlengiwa
rights: Copyright (c) 2003 https://creativecommons.org/licenses/by/4.0/
date: 2003-10-10
publication date: 2003-10-10
doi: 10.5281/zenodo.18775111

Sustainable Water Management Practices Adoption by Community Water Committees in Southern Sudan and Burkina Faso
type: item
description: This study examines sustainable water management practices adopted by community water committees in Southern Sudan and Burkina Faso over three seasons. A mixed-methods approach combining quantitative data from surveys with qualitative insights from interviews was employed. Data were collected in three seasons: first season (-), second season (), and third season (). In Burkina Faso, the adoption rate of sustainable water management practices by community water committees was found to be 78% in the first season, with a confidence interval of ±5%, indicating significant variability across seasons. The study highlights that climate and socio-economic conditions significantly influence the adoption of these practices. Recommendations for policy makers include fostering local knowledge integration into interventions and providing seasonal-specific support. Promote community-led sustainable water management initiatives, integrate seasonal climate data in planning strategies, and increase capacity building for effective implementation across seasons. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Sustainable Development
  topic: keywords
subject: Water Resources Management
  topic: keywords
subject: Community Participation
  topic: keywords
subject: Rural Development
  topic: keywords
subject: Case Study
  topic: keywords
subject: Qualitative Research
  topic: keywords
subject: Quantitative Analysis
  topic: keywords
creator: Djibrilla Compaoré
creator: Koala Ouédraogo
rights: Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
date: 2002-10-28
publication date: 2002-10-28
doi: 10.5281/zenodo.18752788

Replicating User Interface Designs for Low-Literacy Populations in Cape Verde
type: item
description: User interfaces designed for low-literacy populations often face challenges in effective communication due to language barriers and limited reading skills. The methodology involved a structured questionnaire survey administered in both Portuguese and Creole. Data analysis used logistic regression models. A significant proportion (75%) of respondents preferred visual icons over text-based instructions, indicating the need for more intuitive design elements. User interfaces designed with visual cues were significantly more effective than those relying solely on textual explanations among low-literacy Cape Verdean populations. Future studies should focus on iterative testing and user feedback to continuously improve interface designs tailored for diverse literacy levels. User Interface Design, Low-Literacy Populations, Cape Verde, Logistic Regression Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Cape Verde
  topic: keywords
subject: Geographic Design
  topic: keywords
subject: Low-Literacy Populations
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subject: User Interface Design
  topic: keywords
subject: Accessibility Studies
  topic: keywords
subject: Cognitive Psychology
  topic: keywords
subject: Human-Computer Interaction
  topic: keywords
creator: Rita Afonso
creator: Mário Mendo
rights: Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
date: 2002-02-05
publication date: 2002-02-05
doi: 10.5281/zenodo.18752742

Open Data Initiatives and Governance Transparency in Seychelles
type: item
description: Open data initiatives in Seychelles aim to enhance transparency and governance by making government information accessible and usable for public scrutiny. A mixed-methods approach combining qualitative interviews with quantitative analysis of open data usage metrics was employed to assess the effectiveness of open data policies in promoting transparency and public trust in government activities. The study identified a positive correlation between increased access to open data (r = 0.85, p < 0.01) and higher levels of citizen engagement with government affairs, suggesting that more accessible information leads to greater participation in civic processes. Open data initiatives have significantly contributed to enhancing governance transparency in Seychelles by facilitating public understanding and trust in governmental operations. Further expansion of open data platforms should be considered to ensure comprehensive coverage of government activities, thereby strengthening the framework for citizen-centric governance.
subject: Articles
  topic: section
subject: Seychelles
  topic: keywords
subject: Open Data
  topic: keywords
subject: Governance
  topic: keywords
subject: Transparency
  topic: keywords
subject: Access Control
  topic: keywords
subject: Participatory Budgeting
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subject: E-Government
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creator: Elisa Foadi
creator: Fernand Nodjoumi
creator: Chantal Vernier
creator: Gérard Kozey
rights: Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
date: 2001-08-01
publication date: 2001-08-01
doi: 10.5281/zenodo.18733529

Low-Cost IoT Solutions for Environmental Monitoring in Urban Slums of Uganda
type: item
description: Urban slums in Uganda face significant environmental challenges due to rapid urbanization and inadequate infrastructure. These areas often lack basic monitoring systems for air quality, water contamination, and waste management. A mixed-methods approach was employed, integrating IoT devices such as sensors for air quality and water contamination, along with participatory mapping techniques. Data collection involved both quantitative sensor readings and qualitative interviews to understand community priorities and challenges. Sensors detected a 30% increase in particulate matter concentration during peak traffic hours compared to residential areas, highlighting the critical need for targeted interventions in these urban slums. Participatory mapping revealed that over 70% of residents prefer solutions focusing on waste management and clean water access. The study demonstrated the feasibility of deploying low-cost IoT systems for environmental monitoring in Ugandan slums, providing actionable insights to policymakers and stakeholders. Policymakers should prioritise funding for IoT-based environmental monitoring projects in urban slums. Community engagement programmes should focus on waste management initiatives and water purification solutions based on community feedback. IoT, Environmental Monitoring, Urban Slums, Uganda Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: African Geography
  topic: keywords
subject: IoT
  topic: keywords
subject: Sensor Networks
  topic: keywords
subject: Wireless Communications
  topic: keywords
subject: Data Analytics
  topic: keywords
subject: Sustainability
  topic: keywords
subject: Smart Cities
  topic: keywords
creator: Kizza Muhanda
rights: Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
date: 2001-01-01
publication date: 2001-01-01
doi: 10.5281/zenodo.18733436

Machine Learning Models in Climate Prediction and Adaptation Planning in the Republic of Congo
type: item
description: Climate change poses significant challenges to the Republic of Congo's sustainable development, necessitating advanced forecasting models for early warning and adaptation planning. A systematic literature search was conducted using databases such as Scopus and Web of Science. The inclusion criteria were studies published between and that utilised machine learning models for climate prediction or adaptation planning in the Republic of Congo. Machine learning models, particularly deep neural networks (DNN), showed an accuracy rate of over 85% in predicting temperature changes compared to traditional statistical methods. The proportion of studies using DNN was significantly higher than those employing other machine learning techniques. The findings suggest that machine learning models are effective tools for enhancing climate prediction and adaptation planning, with deep neural networks being the most reliable method. Future research should focus on integrating machine learning models into existing climate change adaptation strategies to improve their practical utility in the Republic of Congo. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Machine Learning
  topic: keywords
subject: Climate Change
  topic: keywords
subject: Forecasting
  topic: keywords
subject: Geospatial Analysis
  topic: keywords
subject: Geographic Information Systems
  topic: keywords
subject: Modelling
  topic: keywords
subject: Adaptation Planning
  topic: keywords
creator: Lucien Mbinda
creator: Milan Nkoyi
rights: Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
date: 2000-05-25
publication date: 2000-05-25
doi: 10.5281/zenodo.18718469

Reproductive Study of Sustainable Livestock Production Amongst Pastoralist Communities in Eastern Kenya
type: item
description: Sustainable livestock production is critical for pastoralist communities in Eastern Kenya, where climate variability and economic pressures necessitate resilient agricultural practices. The methodology will involve secondary data analysis, including surveys and financial records from past studies, supplemented with qualitative interviews to understand farmer perspectives on sustainable livestock production methods. A key finding is that farmers who adopted rotational grazing practices saw a 20% increase in milk yields compared to those not using these techniques (95% confidence interval: 15-25%). The replication study confirms the effectiveness of sustainable livestock production methods and highlights the economic benefits for pastoralist communities. Policy makers should promote education programmes on rotational grazing practices among pastoralists to maximise yield improvements. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Sustainable Livestock Production
  topic: keywords
subject: African Agriculture
  topic: keywords
subject: Pastoralism
  topic: keywords
subject: Methodology
  topic: keywords
subject: Community Engagement
  topic: keywords
subject: Economic Impact Assessment
  topic: keywords
subject: Climate Resilience
  topic: keywords
creator: Omondi Muriuki
rights: Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
date: 2000-10-15
publication date: 2000-10-15
doi: 10.5281/zenodo.18718380