Applying logistic regression analysis to identify patient’s satisfaction predictors with general practitioner assistance: evidence from four Italian regions.

In the last years the interest for patient experience with health care services largely increased. Several surveys have been conducted in order to observe if health care systems answer to the overall patient needs. In 2000 World Health Organization challenged modern health care providers to ensure responsiveness to patients, i.e. to deliver also non-health assistance (respect for dignity, confidentiality, prompt attention, quality of amenities, access to social support networks, choice of provider, etc.). Poor evidence is available in Italy about connections between perceived quality and the capability of the healthcare system to respond to patients’ needs. This work aims at investigating patient experience with General Practitioner (GP) assistance and at measuring the impact of personal and organizational characteristics on overall satisfaction and on willingness to recommend. In 2009 a sample survey was conducted in four regions of Italy (Tuscany, Piedmont, Umbria, and Liguria). About 15.000 citizens answered to a large questionnaire related to Primary Care services, including a section dedicated to General Practitioner (GP) assistance. A logistic regression analysis was applied to analyze which are the predictors of overall satisfaction with GP, focusing mainly on variables related to patient’s expectations, continuity of care and organizational aspects (e.g. scheduled access, waiting time, health case history, etc.) and if there are differences across the four Italian Regions. Econometric analysis has been carried out through both ordered logistic regression and generalised ordered logit models. The inhabitants of the four Italian Regions refer a nice experience with GP assistance: more than 85% of them judged excellent or good the overall service. Generally, in some regions patient expectations affect more the willingness to recommend GP to friends or family members than the overall judgement on service. Besides, the findings provide convincing evidence that GP is a nodal point in the continuity of care process .: patient satisfaction, general practitioner, organizational aspects, continuity of care

Housing Satisfaction in South Korea

Since April 2013, the Korean government has implemented a series of plans to stabilize the housing market, which has suffered from falling housing prices and surging rent after the 2008 financial crisis. This study estimates the effectiveness of the government\u27s plans by analyzing the housing satisfaction of 2012 and 2014 Korea Housing Survey (KHS). The data used in this study are collected from the KHS carried out by the Ministry of Land, Infrastructure and Transport (MOLIT) This study uses 2012 and 2014 KHS to show that some variables and subcategories of household and housing attributes have positive or negative correlation with housing satisfaction. The analysis of 2012 and 2014 KHS indicates a few tendencies about how the government\u27s plans affect housing market. First, the government\u27s plans are likely to lower the dissatisfaction of the households living in \u27Jeonse\u27 and \u27monthly rent\u27 housing; but the positive impact is considered to be insufficient to completely stabilize the rental housing market. Second, the government\u27s plans are likely to more positively affect the households living in \u27metropolitan\u27 and \u27other region\u27 than in \u27capital area.\u27 Third, the supply extension plan of public rental housing is likely to be effective because residents living in public rental housing tend to be satisfied with their housing. Finally, despite the introduction of the Housing Voucher Program, recipient households are dissatisfied with their housing. Therefore, the housing authority will need to have consistent interest in their housing satisfaction

Comparing Passenger Satisfaction, Employees’ Perspective and Performance on Quality and Safety Indicators: A field study

This paper aims to analyze the impact that different attributes related to a Regional Airport service and the socio-economic factors of the passengers have on the passenger’s overall satisfaction. The study also compared passenger and employee satisfaction in relation to the service offered by the airport, to identify possible critical areas of improvement. An Ordinal Logistic Regression (OLR) approach was used to model how the attributes considered for qualifying airport services and the socio-economic variables impact the predicted variable (i.e., passenger satisfaction). Furthermore, the results were triangulated to include quality and safety performance indicators as an objective anchor point for the performance of the company. The findings indicate interesting areas of difference between the perceptions of the passengers and airport employees regarding a company’s services and its performance. The company managers in the key areas of operation were then asked to select the main areas of improvement among the ones highlighted by the survey’s results. Quality and safety indicators were also helpful in enriching the analysis and indicating good synergy with the suggestions collected from the passengers’ and the employees’ surveys, offering yet another complementary perspective

Development of value-added materials from municipal plastic solid waste

Abstract: Continuous consumption of plastic materials that brings about rapid and more plastic wastes (PWs) generation has become an issue of concern globally, specifically in low-income countries (LCs) where waste management services are still at an infant stage and are inadequate and unstainable. The explosion and acute generation of PWs are dependent on many factors including, incessant migration of citizens in search of greener pastures from rural areas to cities and continuous influx of economic migrants from surrounding African nations and other nations of the world to sub Sahara Africa (SSA) region, changes in consumption pattern, rapid economic and industrial growth etc. The most startling thing about the severe plastic waste (PW) generation is that many citizens are not even aware of the negative/damaging impact of their activities on public health and the natural environment. Besides, the management of PW is now a challenge owing to factors like; insufficient budget for waste management (WM), unavailability of land spaces in cities for the construction of new disposal facilities, bad legislation and policies; and poor education and awareness campaigns. Hence, this study aims to enlighten the populace on the need for a change of attitude and behaviour towards municipal plastic solid waste management and to support recycling for greener cities and a sustainable future. To achieve this, a cross section of the students of the University of Johannesburg, South Africa were interviewed via a structured questionnaire survey and a logistic prediction model was developed to evaluate the attitudes and behaviours of the students towards recycling. Moreover, polystyrene plastic wastes (PSPWs) were recycled via solvothermal technique (chemical recycling) where a hybrid organic-inorganic nanocomposite (a value-added material) was developed. The synthesised nanocomposites (NCs) were characterized by XPS and EDX; XRD, FTIR, SEM, TEM and DLS; TGA, DSC and BET. Moreover, the neat (control) and unprocessed recycled polystyrene (rPS) were also characterized by NMR and GPC.Ph.D. (Chemical Engineering

Comparing the Performance of Ordinal Logistic Regression and Artificial Neural Network when Analyzing Ordinal Data

The purpose of this study is to compare the performance of the Ordinal Logistic Regression (OLR) and Artificial Neural Network (ANN) models when analyzing ordinal data using different scenarios by varying the combinations of the marginal probability distributions and correlation coefficients. Two internal links in the Service Profit Chain (SPC), the relationship between employee perceived value of the internal and external determinants of employee satisfaction and employee overall satisfaction and the relationship between employee overall satisfaction and job performance are used as a framework to build the OLR and ANN models. Ordinal data collected from surveys at two trainining restaurants (Taylors' Dining at Oklahoma State University, USA and Fajar Teaching Restaurant at Universitas Negeri Malang, Indonesia) and simulated correlated ordinal data are fitted to the OLR and ANN models in order to compare the mean of misclassification rates from each model. A model with a lower misclassification rate is preferred.The application of the OLR and ANN models to analyze a causal relationship between one input variable and one output variable results in no statistically significant difference between the means of the misclassification rates resulting from both models for all three scenarios tested. On the other hand, the application of the OLR and ANN models to analyze a causal relationship between three input variables and one output variable results in a statistically significant difference between the means of the misclassification rates resulting from both models for all three scenarios tested. The OLR model outperforms the ANN model when it is used to analyze ordinal data that has similar marginal probabilities and correlation coefficients to Taylors' data. In contrast, the ANN model outperforms the OLR model when it is used to analyze ordinal data that has marginal probabilities and correlation coefficients either similar to FTR's data or randomly distributed. These results suggest that the complexity of the problem, which is represented by the number of input variables (attributes), and the complexity of the data structures, which is represented by the correlation coefficient and marginal probability distribution including the kurtosis, should be considered before fitting data sets to either the OLR or ANN models.Industrial Engineering & Managemen