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Research Article
Willingness to Pay for Social Health Insurance and Associated Factors Among Public Servants in Lideta Sub-city; Addis Ababa, Ethiopia
Getachew Jufare,
Alemu Tesfahun,
Asefa Taresa*,
Lakech Haile
Issue:
Volume 10, Issue 2, June 2025
Pages:
22-30
Received:
11 January 2025
Accepted:
19 March 2025
Published:
10 April 2025
Abstract: Background: More than 4 billion people worldwide still lack social protection. However, the policy provides a framework for collaboration and coordination within the social protection system, aiming to deliver various services through an organized structure at all levels. Therefore, the aim of this study was to assess willingness to pay for social health insurance and its associated factors among public servants in Lideta Sub-city; Addis Ababa, Ethiopia. Methods: An institutional-based cross-sectional study was conducted from September 15 to November15/2023 using systematic random sampling among 381 permanent public servants in Lideta sub-city of Addis Ababa Ethiopia. Participants were interviewed using a structured pretested closed questionnaire to obtain detail data from respondents for different variables. The data was entered into the Kobo toolbox and exported to SPSS version 26.00 for analysis. Descriptive analysis and cross tabulation was done to see the picture of the data. Bivariate and multivariate logistic regression analysis was done at 95% of confidence interval. Those variables with P-value less than 0.05 along with their Adjusted Odds Ratio (AOR) were declared as a predictor of the outcome variables in the study. Results: A total of 381 government employees completed the questionnaire with a response rate of 100 %. Overall, 64.3% of respondents were willing to pay the proposed premium (3% of their monthly salary). Public servant who knew social health insurance scheme [AOR= 2.24, (95% CI: 1.31, 3.82)], those have good knowledge [AOR= 4.23, (95% CI: 2.15, 8.32)], those had a history of chronic disease [AOR= 2.46, (95% CI: 1.16, 5.21)] were associated with willingness to pay for social health insurance. Conclusions: The willingness to pay 3% of the monthly gross salary for social health insurance was 64.3 %. Public servant who knew social health insurance, having good knowledge and history of previous chronic diseases are identified as predictors of willingness to pay for social health insurance. Thus, the government of Ethiopia and Addis Ababa city administration recommended starting social health insurance. In addition qualitative study will be further recommended to get the detail investigation.
Abstract: Background: More than 4 billion people worldwide still lack social protection. However, the policy provides a framework for collaboration and coordination within the social protection system, aiming to deliver various services through an organized structure at all levels. Therefore, the aim of this study was to assess willingness to pay for social ...
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Research Article
No Flynn Effect in Jordan 2012-2021
Issue:
Volume 10, Issue 2, June 2025
Pages:
31-38
Received:
27 February 2025
Accepted:
10 March 2025
Published:
22 May 2025
Abstract: There is growing evidence that the Flynn Effect, the secular rise in IQ scores that was observed across the twentieth century, has reached a plateau and has even gone into reverse in many Western countries. However, several recent studies report an ongoing Flynn Effect in developing countries, especially in those in the Arab world. Here we compare two samples from 2012 (N = 350) and 2021 (N = 1,491) of children in the Kingdom of Jordan. The children were 4, 5 and 6 years old and were randomly selected from kindergartens in the north, central and south of Jordan. They were administered the Wechsler Preschool and Primary Scale of Intelligence (WPPSI), a test which is designed for this age group. Factor analyses exhibited very similar factors loadings across samples and subtests, indicating high construct validity. Comparing effect sizes for the difference between the samples in both total and subtest scores, we find no evidence of any change in intelligence between the two samples. We explore the possible reasons for this apparent cessation of the Flynn Effect in Jordan among which may be the impact of the Covid-19 pandemic on the 2021 sample. We conclude that there is little reason to think that this would have interfered with how representative the sample was.
Abstract: There is growing evidence that the Flynn Effect, the secular rise in IQ scores that was observed across the twentieth century, has reached a plateau and has even gone into reverse in many Western countries. However, several recent studies report an ongoing Flynn Effect in developing countries, especially in those in the Arab world. Here we compare ...
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Research Article
Prediction of Patients’ Outcomes in Cardiovascular Disease
Awogbemi Clement Adeyeye*
,
Johnson Simeon Adedayo,
Ilori Adetunji Kolawole,
Oyeyemi Gafar Matanmi
Issue:
Volume 10, Issue 2, June 2025
Pages:
39-45
Received:
14 February 2025
Accepted:
27 February 2025
Published:
6 June 2025
DOI:
10.11648/j.bsi.20251002.13
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Views:
Abstract: Cardiovascular Disease (CVD) remains a leading cause of mortality worldwide, necessitating effective prediction methods to improve patient outcomes. The study contributed to knowledge by using Support Vector Machine (SVM) to predict the outcome of patient at risk of CVD. This study explored the application of Logistic Regression (LR) and Support Vector Machine (SVM) models for predicting patient outcomes in CVD. In this analysis, patient medical record data was retrieved online from kaggle.com, comprising a dataset of 1,000 instances with 14 features relevant to cardiovascular health. Both Logistic Regression, implemented in SPSS, and SVM, executed using the R package, were employed for predictive modelling. From this study, SVM emerged as the superior model due to its ability to handle high-dimensional data and complex relationships. It has shown potentials in reducing the severity of cardiac diseases by accurately identifying at-risk individuals, thereby enabling timely intervention. The results indicated that the SVM model achieved an impressive accuracy rate of 98.7%, significantly outperforming the LR model of accuracy rate of 97%. Accurate predictions from the SVM model are vital for healthcare experts in identifying individuals at risk and formulating tailored treatment plans. Leveraging advanced machine learning techniques such as SVM can enhance the predictive capabilities regarding cardiovascular disease outcomes. This study underscores the importance of integrating these models into clinical practice to facilitate proactive healthcare measures and ultimately reduce cardiovascular morbidity and mortality rates.
Abstract: Cardiovascular Disease (CVD) remains a leading cause of mortality worldwide, necessitating effective prediction methods to improve patient outcomes. The study contributed to knowledge by using Support Vector Machine (SVM) to predict the outcome of patient at risk of CVD. This study explored the application of Logistic Regression (LR) and Support Ve...
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Research Article
Assessment of Voluntary Enrollment and Associated Factors in Community-based Health Insurance in Lideta Sub-city, Addis Ababa, Ethiopia
Mohammed Hassan,
Abebe Derbie,
Asefa Taresa*,
Dawit Regasa
Issue:
Volume 10, Issue 2, June 2025
Pages:
46-55
Received:
17 April 2025
Accepted:
3 May 2025
Published:
6 June 2025
DOI:
10.11648/j.bsi.20251002.14
Downloads:
Views:
Abstract: Background: A community-based health insurance scheme is an effective way to achieve universal health service coverage by offering financial protection against healthcare costs. This study aimed to assess the voluntary enrollment and associated factors in community-based health insurance in the Lideta sub-city. Methods: A cross-sectional study was conducted from July 23 to August 26, 2024, using a stratified sampling method followed by simple random sampling on 643 participants using a structured, pre-tested closed questionnaire. Data was collected by Kobo Toolbox software and exported to STATA version 17.0 for analysis. Descriptive analysis and cross-tabulation was performed to present the data. Both bivariate and multivariate logistic regression analyses were computed with a 95% confidence interval. Variables with a p-value of less than 0.05, along with their Adjusted Odds Ratios (AOR), were identified as predictors of the outcome variables in the study. Results: In the current study the voluntary enrollment rate in community based health insurance was 68.6%. In the study, as age increased in one year, enrollment increased by 0.033 [95% CI: 0.006, 0.056]; the higher income indicating 0.771 [95% CI: -1.862, 0.848] increased enrollment in community based health insurance keeping other variables constant. However, availability [-0.551, (95% CI: -1.053, 0.078)], and accessibility [-0.565, (95% CI: -1.097, -0.005)] of quality health services are negatively correlated with enrollment in community based health insurance. Conclusions and Recommendations: The voluntary enrollment rate in community-based health insurance services was 68.6%. Age and income were positively associated with enrollment, while accessibility and the availability of quality healthcare were negatively associated. Therefore, the relevant organizations and stakeholder should take the following actions as recommendations: launch targeted awareness campaigns, address barriers for waiting time, enhance strategies that improve service availability and accessibility, and offer subsidy methods, and conduct qualitative research such as in-depth individual interviews and delphi technique to further explore the barrier for community based health insurance enrollment to gain further insights.
Abstract: Background: A community-based health insurance scheme is an effective way to achieve universal health service coverage by offering financial protection against healthcare costs. This study aimed to assess the voluntary enrollment and associated factors in community-based health insurance in the Lideta sub-city. Methods: A cross-sectional study was ...
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