Compensated Cadaver Organ Donation: Will a small fee waiver work?

This article analyzes the use of monetary incentives to increase the supply of cadaver organs. The research focuses on whether a waiver of a driver\u27s license fee can increase the proportion of society declaring to be a cadaver organ donor. In addition, the dynamics of organ donation are addressed using a bivariate regression to test if being a college student, religion, age, gender, income, and overall knowledge of donation has a significant impact on whether one chooses to be cadaver organ donor. Finally, the concern that a monetary and altruistic market can coexist is addressed in this research. Utilizing sample Z-statistics, it is found that a small incentive has the potential to significantly impact the number of cadaver organ donors. A significant finding is that students are more likely to become cadaver organ donors when offered the $30 fee waiver, whereas religion, gender, and income do not statistically impact ones decision

1967 The Analysis

https://jdc.jefferson.edu/analysis/1015/thumbnail.jp

Geospatial Analysis of Property Values Using Spatial & Social Ratings Data

Wohnen in städtischen Zentren ist sowohl politisch als auch im Marktkontext ein heikles Thema. Dies gilt insbesondere für den Wohnungsmarkt in Berlin, wo weit verbreitete Spekulationen und internationale Investitionen in kurzer Zeit zu einem starken Anstieg der Immobilien- und Mietkosten geführt haben. Für alle Beteiligten in dieser Gleichung (Politiker, Anwohner, Immobilieninvestoren / Entwickler) ist es wichtig zu verstehen, was Preis und Nachfrage in diesem einzigartigen Umfeld antreibt. Um diese Dynamik zu modellieren, verwendet diese Arbeit eine geographically-weighted Regression (GWR) und erweitert die hedonische Preismethode (HPM) um Merkmale wie Beliebtheit einer Nachbarschaft, Zugang zur Natur (Parks, Flüsse, usw.), Zugang zu öffentlichen Verkehrsmitteln, und Nähe zu Einkaufsmöglichkeiten und Einkaufsmöglichkeiten Schulen, unter anderem. Google Ortsdaten und Rezensionen repräsentieren die allgemeine Beliebtheit von Standorten. Öffentliche Daten des Berliner Senats und des VBB liefern räumliche Informationen zu natürlichen Ressourcen bzw. zum Zugang zu öffentlichen Verkehrsmitteln. Kernel-Dichteschätzung (KDE) wird verwendet, um räumliche Muster und die Verteilung von Orten von Interesse (POIs) zu analysieren, wobei die Hotspot-Analyse unter Verwendung der Getis-Ord-Statistik durchgeführt wird. Die Immobiliendaten stammen aus einem Datensatz von Buchungen, die auf einer lokalen Plattform für möblierte Mietwohnungen vorgenommen wurden. Die GWR-Ergebnisse zeigen eine hohe Korrelation zwischen POI-Clustering und Preis sowie signifikante Verbesserungen der Modellleistung. Dem GWR gelingt es insbesondere, die räumliche Heterogenität von Merkmalseffekten zu erfassen, die von der globalen OLS-Regression übersehen werden. Diese Studie bietet eine einzigartige Verbindung von öffentlichen und privaten Datenquellen, um zu einer neuartigen Analyse des Berliner Immobilienmarktes zu gelangen.Housing in urban centres is a sensitive issue both politically and in a market context. This is particularly true for the housing market in Berlin, Germany, where widespread speculation and international investment have resulted in sharp increases in property and rental costs in a short period of time. For all stakeholders in this equation (politicians, residents, property investors/developers), it is important to understand what drives price and demand in this unique environment. To model these dynamics, this thesis employs a geographically weighted regression(GWR) and extends the hedonic pricing method (HPM) to include features involving neighbourhood popularity, access to nature (parks, rivers), access to public transportation, and proximity to shopping and schools, among other kinds of locations. Google place data & review counts represent general popularity of locations. Public data from the Berlin Senate and the VBB provide geospatial information on natural resources and access to public transportation, respectively. Kernel density estimation (KDE) is employed to analyse spatial patterns and distribution of places of interest (POIs), with hotspot analysis performed using the Getis-Ord statistic. Property data comes from a dataset of bookings made on a local platform for furnished apartment rentals. GWR results show a high correlation between POI clustering and price as well as significant improvements in model performance. The GWR notably succeeds in capturing spatial heterogeneity in feature effects that global OLS regression overlooks. This study provides a unique marriage of public and private data sources to arrive at a novel analysis of the Berlin property market

Same Story, Different Name: A Survey of the Causes and Effects of the Medicalization of Post-Traumatic Stress Disorder

As society sees a rise in the addition of medical issues to the DSM that were previously deemed non-medical conditions, there is reason for a multi-variate analysis to take place. Post-traumatic Stress Disorder was added to the DSM-III in 1980 and has seen change both in the DSM-IV and DSM V. To understand these transitions, we start with a historical analysis of the mental health condition to legitimize its need for medicalization. This will then be followed by an analysis of the medicalization process in order to understand the progress that has been made as a mental health condition that requires medical and/or psychological treatment. Its medicalization encompasses empirical data, modern diagnostic and theoretical measures employed, treatment methods, both current and prospective. By understanding the process of its medicalization we can then understand its subsequent sociocultural implications