Published

Abstract

The notion of having an efficient health system at a cost–effective value for money, is of most interest to policymakers (Mirella, 2013). Health care financiers including governments, insurers and households are interested in knowing which health system has the largest health benefits yet spends at a minimal cost (Tulchinsky,2014). Cross-country comparison and benchmarking are useful tools to assess and compare health systems. However, frail comparisons of health systems may bring inaccurate insights to policy makers (Lopes, 2015). Thus, this study will generate a scale that compare countries accurately by addressing the fractality of the data.The Current health expenditure data is highly fractal with highly unequal distribution of health spending globally. Because of the wide disparity of data, median is the best positional average to use instead of the mean. This will give a more accurate representation of the health spending of all countries. Through fractal analysis we can generate a scale that will place corresponding countries on a continuum with respect to their CHE for cross country comparisons. Through generating a scale that can place countries in a continuum, there will be a fair comparison of the health outcomes.This CHE scale is a better reference because it addresses the fractality of the CHE data. Those belonging to the same cluster are self-affine countries. Self-affine countries are similarly comparable enough to make a fair comparison of health outcomes. Nine scales were created. Countries belonging to the same scale are comparably similar enough to make an inferential finding. In line with the findings of the study, the following conclusions were drawn: (1) That the fractal dimension of current health index of 2015 is 1.003 which means that the extent of self-similarity is low; (2) that the generated scaling may be used for comparison for self-affine countries; (3) the Philippines can benchmark from self-affine countries.

Abstract

The 2019 novel (new) coronavirus has since spread globally, resulting in an ongoing pandemic. In light of this outbreak, the COVID-19 Inter-Agency Task Force (IATF) has placed the Philippines under Community Quarantine to manage the Corona Virus Disease situation. Before easing the implementation of community quarantine, the country needs a careful evaluation of the pandemic situation to prevent another wave of infection. Thus, the crucial question is, “which provinces have the highest risk of increasing COVID-19 cases?” This study sheds light on that question by analyzing the Network Measures of Centrality. Moreover, this study provides a visual representation of the influential provinces whose networks are crucial to the spread of COVID-19 infection. This study analyzed the transmission of COVID 19 in clusters of a network by generating a modularity structure, degree centrality, and eigenvector centrality. Modularity structure is the cluster of provinces who share a strong and dense connection between each other. The degree centrality is the province (edge) that have the highest risk of catching the COVID-19 infection due to its connection to provinces (nodes) who have high cases of COVID-19 infection. And the eigenvector is the province with high case of COVID-19 infection that are influential in transmitting COVID-19 to linked provinces. The Gephi software was used for network visualization and analysis. Results show that, high levels of modularity can be observed. There are 7 clusters generated from the graph. The first cluster accounts for 30.23% of the total number of provinces. The 2nd cluster accounts for 17.44%, the 3rd cluster 9.3. The Degree centrality shows that cluster 1 has the highest degree centrality wherein Cebu is linked to 32 provinces, NCR to 14 provinces, Laguna to 7 provinces, Davao to 5 provinces, Cagayan Valley to 4 provinces, Cotabato to 3 provinces, and Zamboanga linked to 2 other provinces. Moreover, cluster 1 is also the eigenvector which consists of influenctial nodes that can significantly affect the rate of the COVID-19 transmission. Through this study, we have shown that connections between networks can be analyzed in terms of the centrality and eigenvectors of a matrix. This study recommends that containment effort to prevent exponential rise the COVID-19 cases must be focused on Cebu City for the following reasons; (1) Cebu City belongs to the cluster with the highest modularity class; (2) Cebu city has the highest degree centrality; and Cebu City belongs to the cluster with the highest eigenvector centrality.

Abstract

The increasing incidence of calamity calls for the development of modeling and prediction indicators to assess the impact of disaster on health. The study evaluated the health risk of residents through the development and validation of the DRR mathematical model for health in disaster-prone areas in the Province of Bukidnon. The model measured the extent of the hazard, exposure, vulnerabilities, adaptive capacity, and disaster risk reduction of residents affected by the disaster. This study focused on five disaster-prone barangays in Bukidnon.Using the mixed-method design, results revealed that themes and derived meanings from literature created qualitative risk estimation and disaster risk reduction model for health. The DRR parameter was found to be consistent with the observations conducted in various barangays in Bukidnon. The application of DRR model revealed that Barangay Batangan has the highest risk reduction despite having the highest magnitude of risk among the five barangays.

Abstract

An effectively functioning health system is one of the many factors that determine the health of a population. Work and involvement of nurses in their job represent an indispensable part of the healthcare industries. Investigating on work values and job involvement of nurses is essential in this fast-changing healthcare scenario. The research study was conducted using a descriptive – correlational design utilizing the quantitative research approach to Staff Nurses in public hospitals. The level of work values is perceived by the nurses as very important, which means that work values are always applied in the work setting. The level of job involvement of staff nurses is generally very good. The respondents rated first in rank in “enthusiastic to go to work and commitment to my job is hard to be broken” and last in rank in terms of being uninterested in their job. The staff nurses are very much involved in their job. On the other hand, the profile on age, gender, civil status, highest educational attainment, monthly income, length of service, and designation are not significantly related to the staff’s level of work values and job involvement. However, it is noted that there is a significant relationship between the work values and job involvement of public nurses. Thus, as the level of work values increases, the level of job involvement of the staff nurses increases. The study showed that the profile of the respondents is not a determinant factor of work values and job involvement of the public nurses. It is noted that the higher the work values, the better are the job involvement of nurses in the nursing organization.

Abstract

Well-being is a positive perception and usually related to satisfaction allied with emotion and determined by social variables in economics, socio-cultural, environment, and health. The determination and validation of indexes of well-being applicable to Filipinos are the intentions of the study. The study utilized the descriptive research design with the total population of five thousand one hundred five (N=5, 105) and a sample size (n = 1000) of one thousand household heads in Malaybalay City, Philippines. Survey questionnaires used in the study were validated utilizing the Delphi technique and the reliability test was done using Cronbach Alpha.  The top three indicators that yield the greater optimal weights are the better indicators of well-being among Filipinos.  The result of the study shows that the better indicators for well-being are housing, income, and community.

Abstract

This study reports on the development and validation of an instrument for measuring the research culture of different academic institutions. The Research Culture Index (RCI) is an instrument shows the sum of different dimensions namely research competency, research process and research productivity. There were 535 respondents which included the administrators, researchers, and faculty members from six State Universities and Colleges in Region. The validation was done through Delphi method and underwent reliability test using Cronbach Alpha, yielding high-reliability result of 0.8 for two trials. The study revealed that among the three dimensions of the Research Culture Index, research competency significantly influenced the outcome of RCI in the academe as reflected by its high optimal weight. The three prime universities in Region X namely: Mindanao State of Science and Technology; Bukidnon State University and Central Mindanao University, have high research culture index. Demographic data further shows that age has a significant bearing on dimension 1: research competency of the faculty, while the academic rank of the faculty has a significant bearing on the two dimensions namely, research competency, and research process.   Keywords: Research Culture Index (RCI), Research Competency, Research Process,  Research Productivity

Abstract

This study was conducted to determine the quality of health among marginalized barangays in Malaybalay City. The study aimed to identify and assess the morbidity rates of the following diseases: waterborne, vector borne, communicable and non-communicable; and assessed the health conditions of individuals in marginalized communities and correlate the incidence/cases of waterborne, vector borne, communicable and non-communicable diseases with the barangays’ poverty index. Regression analysis was used to correlate poverty and health. Findings revealed that poverty status has moderate positive relationship with the incidence of dengue, tuberculosis and diarrhea, while there is only slight positive relationship between poverty status and the occurrence of diabetes among the marginalized barangays.Keywords;  waterborne, vector borne, communicable and non-communicable diseases, poverty and health.

Abstract

This study was conducted to determine the quality of health among marginalized barangays in Malaybalay City. The study aimed to identify and assess the morbidity rates of the following diseases: waterborne, vector borne, communicable and non-communicable; and assessed the health conditions of individuals in marginalized communities and correlate the incidence/cases of waterborne, vector borne, communicable and non-communicable diseases with the barangays’ poverty index. Regression analysis was used to correlate poverty and health. Findings revealed that poverty status has moderate positive relationship with the incidence of dengue, tuberculosis and diarrhea, while there is only slight positive relationship between poverty status and the occurrence of diabetes among the marginalized barangays.Keywords;  waterborne, vector borne, communicable and non-communicable diseases, poverty and health