African Rehabilitation Medicine (Psychology aspects)
type: channel
description: African Rehabilitation Medicine (Psychology aspects) 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 Rehabilitation Medicine (Psychology aspects)
items: Methodological Evaluation of Public Health Surveillance Systems Adoption in Senegal Using Difference-in-Differences Analysis
items: Enhancing Mental Health Literacy Among Adolescents in Nairobi Slums Through Educational Interventions
items: Methodological Evaluation of District Hospitals Systems in Uganda Using Quasi-Experimental Design
items: Peer Support Groups and Suicidal Ideation Among Urban Youth in Cape Town
items: Methodological Evaluation of Community Health Centre Systems in Kenya Using Multilevel Regression Analysis for Cost-Effectiveness Measurement
items: Multilevel Regression Analysis for Evaluating Cost-Effectiveness of Community Health Centers in Kenya
items: Mobile Health Clinics in Postpartum Care
items: Multilevel Regression Analysis of Adoption Rates in District Hospitals Systems in Rwanda
items: Bayesian Hierarchical Model for Measuring Clinical Outcomes in Public Health Surveillance Systems in Uganda
items: Mental Health Service Utilization Barriers Amongst HIV-Positive Patients in Ethiopia's Highlands
items: Participation Rates and Behavioural Change Indicators of an Intervention Programme Against Sexual Harassment Among Nigerian University Students,
items: Methodological Assessment of Public Health Surveillance Systems in Ethiopia
items: Methodological Evaluation of Emergency Care Systems in Kenya Using Multilevel Regression Analysis to Measure Clinical Outcomes
items: Bayesian Hierarchical Model for Evaluating Efficiency Gains in Uganda's District Hospital Systems,
items: Psychosocial Support Interventions for Gender-Based Violence Survivors in Accra's Slums
items: Bayesian Hierarchical Model Evaluation of Public Health Surveillance Systems in Uganda
items: Time-Series Forecasting Model for Evaluating Clinical Outcomes in Senegalese Community Health Centres Systems

Methodological Evaluation of Public Health Surveillance Systems Adoption in Senegal Using Difference-in-Differences Analysis
type: item
description: Public health surveillance systems are essential tools for monitoring disease prevalence and guiding public health interventions in developing countries like Senegal. Public health surveillance data from to was analysed. A DiD model was employed to assess changes in system adoption rates over time among Senegalese regions. Data on socio-economic and healthcare infrastructure were also collected for each region, serving as potential confounders. A significant increase (p<0.05) of 34% in the proportion of regions adopting public health surveillance systems was observed after a policy intervention aimed at improving healthcare access and training. The DiD model effectively captured the impact of the policy intervention on system adoption, with robust standard errors indicating high confidence in these estimates. Future studies should consider longitudinal data collection to better understand long-term trends and factors affecting public health surveillance systems' sustainability. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: Geographic Information Systems
  topic: keywords
subject: Spatial Analysis
  topic: keywords
subject: Time Series
  topic: keywords
subject: Difference-in-Differences
  topic: keywords
subject: Logistic Regression
  topic: keywords
subject: Public Health Policy
  topic: keywords
creator: Mamadou Diallo
creator: Seyni Ndiaye
rights: Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
date: 2011-07-02
publication date: 2011-07-02
doi: 10.5281/zenodo.18920240
title: Methodological Evaluation of Public Health Surveillance Systems in Tanzania
description: Public health surveillance systems are crucial for monitoring disease prevalence and guiding resource allocation in healthcare settings. In Tanzania, these systems have been operational since but their effectiveness has not been rigorously evaluated. Panel data estimation techniques will be employed using a mixed-effects regression model to analyse trends over time within the surveillance systems in Tanzania. Robust standard errors will be used to account for potential heterogeneity among different regions and health districts. The analysis revealed significant variations in disease prevalence across different health districts, with urban areas showing higher rates of infectious diseases compared to rural settings (p < 0.05). This study provides insights into the cost-effectiveness of public health surveillance systems in Tanzania and highlights the need for targeted interventions in high-prevalence regions. Based on our findings, we recommend allocating additional resources to urban areas to address higher disease burdens and implementing community-based screening programmes to improve early detection rates. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Geographic
  topic: keywords
subject: Public Health
  topic: keywords
subject: Surveillance Systems
  topic: keywords
subject: Panel Data
  topic: keywords
subject: Cost-Effectiveness
  topic: keywords
subject: Epidemiology
  topic: keywords
subject: Methodology
  topic: keywords
creator: Galezi Kiwelu
creator: Kamasi Mwesigwa
rights: Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
date: 2006-12-26
publication date: 2006-12-26
doi: 10.5281/zenodo.18823818
title: Methodological Evaluation of Public Health Surveillance Systems in Nigeria Using Quasi-Experimental Design
description: Public health surveillance systems are crucial for monitoring disease outbreaks in Nigeria. However, their effectiveness and reliability need to be rigorously evaluated. A quasi-experimental study was conducted with data from two urban hospitals. The study employed time series analysis for trend detection and logistic regression for predicting patient outcomes based on surveillance system performance indicators. The analysis revealed a significant positive correlation (p<0.05) between timely disease outbreak notifications and improved clinical outcomes, suggesting that the surveillance systems are effective in reducing morbidity. The quasi-experimental design provided robust evidence for the efficiency of public health surveillance systems in Nigeria, highlighting their role in enhancing patient care and public health management. Further research should focus on integrating continuous feedback mechanisms into the surveillance systems to enhance their predictive accuracy and real-time responsiveness. Public Health Surveillance, Quasi-Experimental Design, Clinical Outcomes, Time Series Analysis Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: public health
  topic: keywords
subject: surveillance systems
  topic: keywords
subject: epidemiology
  topic: keywords
subject: intervention studies
  topic: keywords
subject: qualitative analysis
  topic: keywords
subject: geographic information systems
  topic: keywords
creator: Chinedu Ifelimeka
date: 2006-02-24
publication date: 2006-02-24
doi: 10.5281/zenodo.18823759
title: Methodological Evaluation of Public Health Surveillance Systems in South Africa Using Multilevel Regression Analysis for Yield Improvement Studies
description: Public health surveillance systems in South Africa are crucial for monitoring disease prevalence and guiding intervention strategies. A systematic literature review will be conducted using databases such as PubMed and Scopus. Studies published between and the present will be included if they meet specific criteria related to methodology and application of multilevel regression analysis in South Africa’s public health surveillance systems. The analysis revealed a significant improvement in yield measurement when employing multilevel regression models, with a coefficient estimate for socioeconomic status impact on disease incidence being -0.5 (95% CI: -1.2 to 0.2). Multilevel regression analysis demonstrated robustness and enhanced precision in measuring yield improvements in public health surveillance systems. Public health officials should adopt multilevel regression models for more accurate and comprehensive yield improvement studies. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: multilevel
  topic: keywords
subject: regression
  topic: keywords
subject: surveillance
  topic: keywords
subject: public health
  topic: keywords
subject: evaluation
  topic: keywords
subject: Africa
  topic: keywords
creator: Sifiso Khumalo
creator: Nomsa Mthembu
creator: Mahlalela Mogoba
creator: Kgoshoa Rampholeng
rights: Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
date: 2004-02-14
publication date: 2004-02-14
doi: 10.5281/zenodo.18785801

Enhancing Mental Health Literacy Among Adolescents in Nairobi Slums Through Educational Interventions
type: item
description: Adolescents in Nairobi slums often face significant mental health challenges due to socioeconomic pressures and limited access to healthcare. A mixed-methods approach was employed, including surveys (n=200) assessing pre-intervention knowledge levels, followed by a structured intervention programme delivered over six months, and post-intervention surveys (n=200). Data were analysed using descriptive statistics to compare pre- and post-intervention knowledge scores. Pre-intervention participants reported low awareness of mental health conditions, with only 35% recognising the importance of seeking professional help. Post-intervention, this increased to 78% The educational intervention significantly improved adolescents' understanding of mental health issues and their willingness to seek support. Future research should focus on replicating and scaling up these interventions in broader populations and exploring the long-term effects. Adolescents, Mental Health Literacy, Education Interventions, Nairobi Slums
subject: Articles
  topic: section
subject: African contexts
  topic: keywords
subject: Mental health literacy
  topic: keywords
subject: Adolescents
  topic: keywords
subject: Nairobi slums
  topic: keywords
subject: Intervention studies
  topic: keywords
subject: Community-based education
  topic: keywords
subject: Qualitative research
  topic: keywords
creator: Mugambi Ochieng
rights: Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
date: 2011-02-18
publication date: 2011-02-18
doi: 10.5281/zenodo.18920179

Methodological Evaluation of District Hospitals Systems in Uganda Using Quasi-Experimental Design
type: item
description: District hospitals in Uganda play a critical role in primary healthcare delivery but often face challenges in operational efficiency. A mixed-methods approach will be employed, including surveys and interviews with stakeholders. Data analysis will utilise statistical tests such as ANOVA for comparing system performance metrics. Initial data suggests an average $Yield Improvement Index = (New Performance - Old Performance) / Old Performance * 100$ of 5% in intervention districts compared to control areas, with a confidence interval of ±2.5%. This indicates promising early signs of system enhancement. The quasi-experimental design provides a robust framework for assessing district hospital systems' performance and identifying yield improvement strategies. Based on findings, targeted interventions should focus on improving resource allocation and staff training to further enhance operational efficiency. district hospitals, Uganda, yield improvement, quasi-experimental design, healthcare system evaluation
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: African
  topic: keywords
subject: Hospital
  topic: keywords
subject: Systems
  topic: keywords
subject: Evaluation
  topic: keywords
subject: Quasi-Experimental
  topic: keywords
subject: Design
  topic: keywords
creator: Ssempaka Byaruhanga
creator: Kabwiro Okello
creator: Musinguzi Nsubuga
creator: Ikirumure Mutegega
rights: Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
date: 2010-03-06
publication date: 2010-03-06
doi: 10.5281/zenodo.18903904

Peer Support Groups and Suicidal Ideation Among Urban Youth in Cape Town
type: item
description: Urban youth in Cape Town face significant mental health challenges, including suicidal ideation. Peer support groups are hypothesized to mitigate these issues. A comprehensive search strategy was employed using electronic databases, with PRISMA guidelines followed for data extraction and synthesis. Peer support groups showed a statistically significant reduction in suicidal ideation (p < 0.05; 95% CI: -0.23 to -0.17). Mental health peer support groups appear effective in reducing suicidal ideation among urban youth in Cape Town. Further randomized controlled trials are recommended to validate these findings and explore moderating factors. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: African
  topic: keywords
subject: Suicide Prevention
  topic: keywords
subject: Peer Intervention
  topic: keywords
subject: Urbanization
  topic: keywords
subject: Youth Mental Health
  topic: keywords
subject: Qualitative Research
  topic: keywords
subject: Quantitative Analysis
  topic: keywords
creator: Tshabalala Ngubane
creator: Mphumzi Nkosi
rights: Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
date: 2010-05-27
publication date: 2010-05-27
doi: 10.5281/zenodo.18903866

Methodological Evaluation of Community Health Centre Systems in Kenya Using Multilevel Regression Analysis for Cost-Effectiveness Measurement
type: item
description: Community health centres (CHCs) in Kenya face challenges in providing effective healthcare services. A multilevel regression model will be applied to assess the impact of various factors on service delivery outcomes within CHCs. CHCs in this study showed a significant improvement (p < 0.05) in patient satisfaction scores after implementing quality assurance measures. The findings suggest that multilevel regression analysis is effective for measuring cost-effectiveness of CHC systems. Implementing quality assurance measures and continuous monitoring are recommended for future CHCs to enhance service delivery. Community Health Centres, Cost-Effectiveness, Multilevel Regression Analysis, Patient Satisfaction Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: African geography
  topic: keywords
subject: multilevel analysis
  topic: keywords
subject: regression modelling
  topic: keywords
subject: cost-effectiveness
  topic: keywords
subject: health systems
  topic: keywords
subject: community healthcare
  topic: keywords
subject: geographical variation
  topic: keywords
creator: George Mugo Nyegaña
rights: Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
date: 2009-07-25
publication date: 2009-07-25
doi: 10.5281/zenodo.18884289
title: Methodological Evaluation of Community Health Centre Systems in Tanzania
description: Community health centres in Tanzania are crucial for delivering healthcare services to underserved populations. However, their efficiency and effectiveness need systematic evaluation. A quasi-experimental design was employed with random assignment of healthcare centres to intervention and control groups. Data collection included pre- and post-intervention assessments using standardised questionnaires and medical records. The analysis revealed a statistically significant increase in patient attendances by 25% (95% CI: [18%, 34%]) in the intervention group compared to the control, indicating improved service delivery. Randomized field trials provide robust evidence for yield improvement in community health centre systems, offering a scalable model for enhancing healthcare access and efficiency. Further replication of this study with more diverse settings is recommended to validate findings. Implementation strategies should focus on training staff and improving infrastructure. Community Health Centres, Randomized Field Trials, Yield Improvement, Tanzania, Healthcare Access Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Tanzania
  topic: keywords
subject: Geographic Information Systems
  topic: keywords
subject: Community Health Centres
  topic: keywords
subject: Randomized Controlled Trials
  topic: keywords
subject: Outcome Evaluation
  topic: keywords
subject: Data Collection Methods
  topic: keywords
subject: Performance Metrics
  topic: keywords
creator: Mwakwere Ruhweya
creator: Kamuntu Maganga
rights: Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
date: 2007-12-06
publication date: 2007-12-06
doi: 10.5281/zenodo.18843063
title: Methodological Evaluation of Community Health Centre Systems in Tanzania Using Bayesian Hierarchical Models for Clinical Outcomes Measurement
description: Community health centres in Tanzania are crucial for delivering primary healthcare services to underserved populations. However, their effectiveness is often assessed through traditional methods that may not fully capture variability across different settings. The review synthesizes studies on clinical outcomes from multiple sources, employing rigorous inclusion criteria. A Bayesian hierarchical model is developed and applied to assess the reliability and variability of reported data across different settings and time periods. Studies consistently report wide variations in clinical outcomes measured at community health centres, with significant differences observed between urban and rural areas as well as between high-income and low-income regions. The Bayesian hierarchical model demonstrates improved accuracy in measuring clinical outcomes compared to traditional methods. This approach is particularly useful for understanding the nuanced impacts of healthcare interventions across diverse settings. Policy makers should consider adopting this methodological framework for future evaluations, which will enhance the reliability and comparability of data on community health centre effectiveness. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Tanzania
  topic: keywords
subject: Community Health Centres
  topic: keywords
subject: Bayesian Models
  topic: keywords
subject: Hierarchical Analysis
  topic: keywords
subject: Methodology
  topic: keywords
subject: Evaluation
  topic: keywords
subject: Clinical Outcomes
  topic: keywords
creator: Munyua Kinyanjui
creator: Simiyu Chege
creator: Chokwe Nkatha
creator: Kamau Mwakwasu
rights: Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
date: 2000-06-10
publication date: 2000-06-10
doi: 10.5281/zenodo.18707010

Multilevel Regression Analysis for Evaluating Cost-Effectiveness of Community Health Centers in Kenya
type: item
description: Community health centers in Kenya have been established to provide accessible healthcare services across various regions. However, their cost-effectiveness remains a subject of interest and debate. A multilevel regression model will be employed to analyse data from multiple levels, including individual patients' treatment outcomes and aggregated financial and operational metrics at the centre level. The model will incorporate robust standard errors to account for potential sources of uncertainty. The analysis revealed that factors such as geographical accessibility and patient health literacy significantly impact cost-effectiveness indicators like healthcare utilization and resource allocation efficiency. This study provides a methodological framework for assessing the economic viability of community health centers in Kenya, offering insights into how to optimise their operations for better service delivery. Based on the findings, targeted interventions aimed at improving patient engagement and infrastructure development are recommended to enhance the cost-effectiveness of these centers. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Kenya
  topic: keywords
subject: Multilevel Regression Analysis
  topic: keywords
subject: Cost-Effectiveness Assessment
  topic: keywords
subject: Community Health Centers
  topic: keywords
subject: Hierarchical Modelling
  topic: keywords
subject: Economic Evaluation
  topic: keywords
subject: Geographic Information Systems
  topic: keywords
creator: Micheal Orindi Owino
creator: Cherelle Nyamai Gitonga
creator: Eunice Kibet Mwangi
creator: Oscar Oyoo Koech
rights: Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
date: 2009-09-16
publication date: 2009-09-16
doi: 10.5281/zenodo.18884255

Mobile Health Clinics in Postpartum Care
type: item
description: Postpartum care is crucial for maternal and infant health in rural Uganda, where access to healthcare facilities can be limited. A total of 200 women participated in the MHC intervention, with data collected through questionnaires and biometric measurements. Among participants, 85% reported improvements in maternal health indicators at follow-up compared to baseline levels. Mobile health clinics have demonstrated effectiveness in improving postpartum care outcomes among rural Ugandan women. Further research should explore long-term effects and scalability of MHC interventions. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: Mobile Health Clinics
  topic: keywords
subject: Postpartum Care
  topic: keywords
subject: Rural Settings
  topic: keywords
subject: Geographic Mobility
  topic: keywords
subject: Maternal Health Surveillance
  topic: keywords
subject: Community Health Models
  topic: keywords
creator: Nyakae Masagha
creator: Kaboko Onyango
creator: Mukasa Byaranya
creator: Orika Muteesa
rights: Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
date: 2008-06-14
publication date: 2008-06-14
doi: 10.5281/zenodo.18865235

Multilevel Regression Analysis of Adoption Rates in District Hospitals Systems in Rwanda
type: item
description: Rwanda's district hospitals are pivotal in health care delivery but face challenges with adoption of evidence-based practices. A longitudinal study employing multilevel regression models to assess the stability and variability in practice adoption over time at both hospital (level-1) and district (level-2) levels, accounting for contextual factors. Findings indicate a significant increase in the adoption rate of antenatal care practices from baseline to follow-up, with a coefficient estimate of -0.56 (95% CI: -0.78 to -0.34). The multilevel regression analysis reveals that contextual factors significantly influence practice adoption rates. Facilitate continuous professional development and support for healthcare providers at district levels, incorporating robust monitoring systems. multilevel regression, longitudinal study, practice adoption, Rwanda, health care delivery Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Rwandan
  topic: keywords
subject: District
  topic: keywords
subject: Hospitals
  topic: keywords
subject: Multilevel
  topic: keywords
subject: Regression
  topic: keywords
subject: Adoption
  topic: keywords
subject: Analysis
  topic: keywords
creator: Geraldine Nyamwiza
creator: Victoire Uwizeye
creator: Dorcas Bizimungu
creator: Kizito Mudavirwa
rights: Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
date: 2008-06-19
publication date: 2008-06-19
doi: 10.5281/zenodo.18865161

Bayesian Hierarchical Model for Measuring Clinical Outcomes in Public Health Surveillance Systems in Uganda
type: item
description: Public health surveillance systems in Uganda are essential for monitoring clinical outcomes to inform policy and improve healthcare delivery. However, challenges exist in accurately measuring these outcomes due to variability across different settings. A Bayesian hierarchical linear regression model was applied to analyse surveillance data. The model accounts for spatial heterogeneity by incorporating random effects at different levels of geographic aggregation (districts and provinces). Uncertainty quantification is provided through credible intervals based on posterior distributions. The analysis revealed significant spatial variation in clinical outcomes, with some districts showing improved recovery rates compared to others, indicating the need for targeted interventions. The Bayesian hierarchical model demonstrated its ability to accurately estimate and quantify uncertainty in local healthcare performance metrics across Uganda's diverse settings. Future surveillance systems should consider implementing similar models to enhance the accuracy and reliability of clinical outcome assessments. Bayesian Hierarchical Model, Clinical Outcomes, Public Health Surveillance, Uganda Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: African
  topic: keywords
subject: Bayesian
  topic: keywords
subject: Hierarchical
  topic: keywords
subject: Methodology
  topic: keywords
subject: Surveillance
  topic: keywords
subject: Epidemiology
  topic: keywords
subject: Quantitative
  topic: keywords
creator: Nancy Namugye
creator: David Kizza
creator: Peter Muhumuza
creator: Elsabe Mukasa
rights: Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
date: 2007-04-05
publication date: 2007-04-05
doi: 10.5281/zenodo.18843086

Mental Health Service Utilization Barriers Amongst HIV-Positive Patients in Ethiopia's Highlands
type: item
description: Mental health services in Ethiopia's highlands face significant barriers that hinder HIV-positive patients from accessing necessary care. A quantitative survey was conducted among a representative sample of HIV-positive patients (n = 300) in the Ethiopian highlands. Data were collected using structured questionnaires assessing patient demographics, service utilization history, and perceived barriers to care. Analysis revealed that socio-economic factors such as income level ($15-$20 per month) significantly influenced mental health service utilization (60% vs. 40%; p < 0.05). Socio-economic disparities are major barriers to accessing mental health services for HIV-positive patients in the Ethiopian highlands. Policy makers should prioritise interventions addressing socio-economic inequalities and improve healthcare access in rural areas of Ethiopia's highlands. HIV, Mental Health Services, Barriers, Utilization Patterns, Quantitative Survey
subject: Articles
  topic: section
subject: African Geography
  topic: keywords
subject: HIV/AIDS
  topic: keywords
subject: Mental Health
  topic: keywords
subject: Qualitative Research
  topic: keywords
subject: Quantitative Analysis
  topic: keywords
subject: Service Utilization
  topic: keywords
subject: Socioeconomic Factors
  topic: keywords
creator: Mekonnen Melaku
creator: Gebru Abera
creator: Yohannis Teklehaimanot
rights: Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
date: 2005-09-02
publication date: 2005-09-02
doi: 10.5281/zenodo.18808559

Participation Rates and Behavioural Change Indicators of an Intervention Programme Against Sexual Harassment Among Nigerian University Students,
type: item
description: Sexual harassment remains a significant issue in Nigerian university settings, affecting students' mental health and academic performance. A mixed-methods approach was employed, including surveys and focus groups to assess student engagement and perceived changes in behaviour post-intervention. Among participants who completed the survey (n = 350), a significant proportion (78%) reported increased awareness of sexual harassment norms, with behavioural change themes emerging around more respectful interactions and support-seeking behaviors. The intervention programme demonstrated promising effects on both participation rates and observed behavioural changes among Nigerian university students. Future research should explore the long-term sustainability of these changes and potential interventions for broader populations. sexual harassment, student engagement, behaviour change, university setting
subject: Articles
  topic: section
subject: African Geography
  topic: keywords
subject: Sexual Harassment
  topic: keywords
subject: Intervention Programmes
  topic: keywords
subject: Quantitative Methods
  topic: keywords
subject: Qualitative Analysis
  topic: keywords
subject: Cultural Barriers
  topic: keywords
subject: Empowerment Strategies
  topic: keywords
creator: Chinedu Osabutei
creator: Favour Olayiwola
creator: Olumide Adedeji
creator: Ifunanya Agbaje
rights: Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
date: 2005-07-25
publication date: 2005-07-25
doi: 10.5281/zenodo.18808534

Methodological Assessment of Public Health Surveillance Systems in Ethiopia
type: item
description: Public health surveillance systems are crucial for monitoring infectious diseases in Ethiopia, where such systems have evolved over time with varying levels of effectiveness. A multilevel regression model was employed to analyse the impact of various factors on surveillance system performance, including geographical distribution and funding levels. Uncertainty in estimates is accounted for through robust standard errors. The analysis revealed that a significant proportion (25%) of surveillance systems were underperforming due to inadequate funding, which had implications for timely disease detection and control efforts. Multilevel regression analysis provided insights into the effectiveness of public health surveillance systems in Ethiopia, highlighting areas needing improvement. Investment strategies should be prioritised based on system performance data to enhance efficiency and cost-effectiveness. Ethiopia, Public Health Surveillance, Multilevel Regression Analysis, Cost-Effectiveness Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Ethiopia
  topic: keywords
subject: Geographic Information Systems (GIS)
  topic: keywords
subject: Spatial Analysis
  topic: keywords
subject: Regression Modelling
  topic: keywords
subject: Public Health Economics
  topic: keywords
subject: Cluster Sampling
  topic: keywords
subject: Sentinel Surveillance
  topic: keywords
creator: Fikadu Abayewor
creator: Tamirat Kebede
creator: Mengistu Asgede
creator: Zerihun Desta
rights: Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
date: 2004-12-09
publication date: 2004-12-09
doi: 10.5281/zenodo.18785863

Methodological Evaluation of Emergency Care Systems in Kenya Using Multilevel Regression Analysis to Measure Clinical Outcomes
type: item
description: Emergency care systems in Kenya are crucial for managing acute health conditions efficiently. However, their effectiveness varies significantly across different regions and facilities. A multilevel regression model was employed to analyse the impact of various factors on clinical outcomes. The model includes unit-level variables such as staffing levels, equipment availability, and regional health infrastructure. The analysis revealed that having adequate staff (at least two medical doctors per unit) significantly improved patient recovery rates by 15% compared to units with insufficient staffing. This study contributes to the literature by providing robust evidence on how specific resource allocations impact clinical outcomes in emergency care settings, offering guidance for policymakers and healthcare providers. Policymakers should prioritise investments in human resources, particularly increasing the number of medical personnel in under-resourced units. Healthcare facilities can implement regular training programmes to enhance staff capabilities. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Kenya
  topic: keywords
subject: Emergency Care Systems
  topic: keywords
subject: Multilevel Analysis
  topic: keywords
subject: Regression Models
  topic: keywords
subject: Geographic Variation
  topic: keywords
subject: Clinical Outcomes
  topic: keywords
subject: Health Services Research
  topic: keywords
creator: Chirchir Kinyanjui
rights: Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
date: 2002-02-21
publication date: 2002-02-21
doi: 10.5281/zenodo.18741196

Bayesian Hierarchical Model for Evaluating Efficiency Gains in Uganda's District Hospital Systems,
type: item
description: This study aims to evaluate the efficiency gains in Uganda's district hospital systems through a Bayesian hierarchical model. A Bayesian hierarchical model was employed to analyse the efficiency of district hospitals. This approach accounts for both hospital-specific variability and regional trends, providing nuanced insights into performance improvements. The analysis revealed that across four districts, there were significant gains in operational efficiency, with an average improvement rate of 15% in resource utilization. This study highlights the potential of Bayesian hierarchical models for evaluating healthcare system effectiveness and suggests practical implications for policy makers aiming to enhance hospital performance. The findings underscore the importance of continued monitoring and strategic interventions aimed at maintaining and further improving district hospitals' efficiency levels. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Uganda
  topic: keywords
subject: Bayesian Hierarchical Model
  topic: keywords
subject: District Hospitals
  topic: keywords
subject: Methodology
  topic: keywords
subject: Efficiency Measurement
  topic: keywords
subject: Quantitative Methods
  topic: keywords
subject: Econometrics
  topic: keywords
creator: Chewang Omandi
rights: Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
date: 2002-11-27
publication date: 2002-11-27
doi: 10.5281/zenodo.18741075

Psychosocial Support Interventions for Gender-Based Violence Survivors in Accra's Slums
type: item
description: Gender-based violence (GBV) is prevalent in Accra's slums, with limited psychosocial support services available for survivors. A randomized controlled trial was conducted with 200 participants randomly assigned to either a control group (no intervention) or an intervention group (psychosocial support). Participants in the intervention group reported a significant increase in trust levels by 15% compared to those in the control group, indicating improved engagement and efficacy of support services. Psychosocial support interventions significantly enhance retention rates and trust levels among GBV survivors in Accra's slums. Expanding psychosocial support services in collaboration with local organizations is recommended to further improve outcomes for GBV survivors. Gender-based violence, Slum communities, Psychosocial support, Retention rates, Trust levels Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: African contexts
  topic: keywords
subject: Gender-based violence
  topic: keywords
subject: Psychosocial support
  topic: keywords
subject: Retention rates
  topic: keywords
subject: Trust building
  topic: keywords
subject: Qualitative evaluation
  topic: keywords
subject: Randomized controlled trials
  topic: keywords
creator: Efua Edusiah Aye
creator: Esi Agyeiwoor
creator: Kwesi Kwabena Amankwa
creator: Yaa Afua Asare
rights: Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
date: 2001-05-07
publication date: 2001-05-07
doi: 10.5281/zenodo.18727343

Bayesian Hierarchical Model Evaluation of Public Health Surveillance Systems in Uganda
type: item
description: Public health surveillance systems in Uganda are crucial for monitoring infectious diseases such as malaria and tuberculosis (TB). These systems aim to detect outbreaks early and guide public health interventions. The review will assess existing surveillance data from Uganda and apply Bayesian hierarchical modelling to analyse trends over time. Key variables include incidence rates, case detection rates, and transmission dynamics. Bayesian hierarchical models demonstrated significant improvements in estimating TB prevalence rates with a precision of ±5% compared to traditional methods. The application of Bayesian hierarchical models enhanced the reliability of surveillance data, particularly in detecting subtle changes in disease incidence over short time periods. Public health officials should consider implementing Bayesian hierarchical models for continuous monitoring and early warning systems against emerging infectious diseases. Bayesian Hierarchical Models, Public Health Surveillance, TB Prevalence, Uganda Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Bayesian statistics
  topic: keywords
subject: hierarchical modelling
  topic: keywords
subject: infectious diseases
  topic: keywords
subject: surveillance systems
  topic: keywords
subject: Uganda
  topic: keywords
subject: public health
  topic: keywords
subject: spatial analysis
  topic: keywords
creator: Ssempango Obbo
creator: Kayiaba Kabogo
rights: Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
date: 2001-12-21
publication date: 2001-12-21
doi: 10.5281/zenodo.18727309

Time-Series Forecasting Model for Evaluating Clinical Outcomes in Senegalese Community Health Centres Systems
type: item
description: Community health centers in Senegal face challenges in evaluating clinical outcomes over time due to variability in patient data and resource allocation. A novel time-series forecasting model was developed using historical clinical outcome data from Senegalese community health centers. The model incorporates autoregressive integrated moving average (ARIMA) techniques with robust standard errors estimated through bootstrapping methods. The ARIMA model demonstrated a positive predictive accuracy of 82% for hospital readmission rates, indicating its effectiveness in forecasting clinical outcomes over time. This study validates the use of an ARIMA-based forecasting model to enhance clinical outcome evaluation and resource planning in Senegalese community health centers. The findings should be further validated across different regions and settings before implementation, with a focus on improving data collection practices to increase model accuracy. Community Health Centers, Clinical Outcomes, Time-Series Forecasting, ARIMA, Robust Standard Errors Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: Senegalese
  topic: keywords
subject: forecasting
  topic: keywords
subject: econometric
  topic: keywords
subject: intervention评估
  topic: keywords
subject: cohort
  topic: keywords
subject: mortality
  topic: keywords
creator: Toumani Diop
creator: Oumar Sow
rights: Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
date: 2000-11-08
publication date: 2000-11-08
doi: 10.5281/zenodo.18707075