Understanding the nature and dimensions of litigation crowdfunding: A visual analytics approach.

The escalating cost of civil litigation is leaving many defendants and plaintiffs unable to meet legal expenses such as attorney fees, court charges and others. This significantly impacts their ability to sue or defend themselves effectively. Related to this phenomenon is the ethics discussion around access to justice and crowdfunding. This article explores the dimensions that explain the phenomenon of litigation crowdfunding. Using data from CrowdJustice, a popular Internet fundraising platform used to assist in turning legal cases into publicly funded social cases, we study litigation crowdfunding through the lenses of the number of pledges, goal achievement, target amount, length of description, country, case category, and others. Overall, we see a higher number of cases seeking funding in the categories of human rights, environment, and judicial review. Meanwhile, the platform offers access to funding for other less prominent categories, such as voting rights, personal injury, intellectual property, and data & privacy. At the same time, donors are willing to donate more to cases related to health, politics, and public services. Also noteworthy is that while donors are willing to donate to education, animal welfare, data & privacy, and inquest-related cases, they are not willing to donate large sums to these causes. In terms of lawyer/law firm status, donors are more willing to donate to cases assisted by experienced lawyers. Furthermore, we also note that the higher the number of successful cases an attorney presents, the greater the amount raised. We analyzed valence, arousal, and dominance in case description and found they have a positive relationship with funds raised. Also, when a case description is updated on a crowdsourcing site, it ends up being more successful in funding-at least in the categories of health, immigration, and judicial review. This is not the case, however, for categories such as public service, human rights, and environment. Our research addresses whether litigation crowdfunding, in particular, levels the playing field in terms of opening up financing opportunities for those individuals who cannot afford the costs of litigation. While it may support social justice, ethical concerns with regards to the kinds of campaigns must also be addressed. Most of the ethical concerns center around issues relating to both the fundraisers and donors. Our findings have ethical and social justice implications for crowdfunding platform design.

Understanding the Dimensions of Medical Crowdfunding: A Visual Analytics Approach.

BACKGROUND: Medical crowdfunding has emerged as a growing field for fundraising opportunities. Some environmental trends have driven the emergence of campaigns to raise funds for medical care. These trends include lack of medical insurance, economic backlash following the 2008 financial collapse, and shortcomings of health care regulations. OBJECTIVE: Research regarding crowdfunding campaign use, reasons, and effects on the provision of medical care and individual relationships in health systems is limited. This study aimed to explore the nature and dimensions of the phenomenon of medical crowdfunding using a visual analytics approach and data crawled from the GoFundMe crowdfunding platform in 2019. We aimed to explore and identify the factors that contribute to a successful campaign. METHODS: This data-driven study used a visual analytics approach. It focused on descriptive analytics to obtain a panoramic insight into medical projects funded through the GoFundMe crowdfunding platform. RESULTS: This study highlighted the relevance of positioning the campaign for fundraising. In terms of motivating donors, it appears that people are typically more generous in contributing to campaigns for children rather than those for adults. The results emphasized the differing dynamics that a picture posted in the campaign brings to the potential for medical crowdfunding. In terms of donor's motivation, the results show that a picture depicting the pediatric patient by himself or herself is the most effective. In addition, a picture depicting the current medical condition of the patient as severe is more effective than one depicting relative normalcy in the condition. This study also drew attention to the optimum length of the title. Finally, an interesting trend in the trajectory of donations is that the average amount of a donation decreases with an increase in the number of donors. This indicates that the first donors tend to be the most generous. CONCLUSIONS: This study examines the relationship between social media, the characteristics of a campaign, and the potential for fundraising. Its analysis of medical crowdfunding campaigns across the states offers a window into the status of the country's health care affordability. This study shows the nurturing role that social media can play in the domain of medical crowdfunding. In addition, it discusses the drivers of a successful fundraising campaign with respect to the GoFundMe platform.

Healthcare Expenditure and Economic Performance: Insights From the United States Data.

This research explores the association of public health expenditure with economic performance across the United States. Healthcare expenditure can result in better provision of health opportunities, which can strengthen human capital and improve the productivity, thereby contributing to economic performance. It is therefore important to assess the phenomenon of healthcare spending in a country. Using visual analytics, we collected economic and health data from the Bureau of Economic Analysis and the Bureau of Labor Statistics for the years 2003-2014. The overall results strongly suggest a positive correlation between healthcare expenditure and the economic indicators of income, GDP, and labor productivity. While healthcare expenditure is negatively associated with multi-factor productivity, it is positively associated with the indicators of labor productivity, personal spending, and GDP. The study shows that an increase in healthcare expenditure has a positive relationship with economic performance. There are also variations across states that justify further research. Building on this and prior research, policy implications include that the good health of citizens indeed results in overall better economy. Therefore, investing carefully in various healthcare aspects would boost income, GDP, and productivity, and alleviate poverty. In light of these potential benefits, universal access to healthcare is something that warrants further research. Also, research can be done in countries with single-payer systems to see if a link to productivity exists there. The results support arguments against our current healthcare system's structure in a limited way.

Studying Public Perception about Vaccination: A Sentiment Analysis of Tweets.

Text analysis has been used by scholars to research attitudes toward vaccination and is particularly timely due to the rise of medical misinformation via social media. This study uses a sample of 9581 vaccine-related tweets in the period January 1, 2019 to April 5, 2019. The time period is of the essence because during this time, a measles outbreak was prevalent throughout the United States and a public debate was raging. Sentiment analysis is applied to the sample, clustering the data into topics using the term frequency-inverse document frequency (TF-IDF) technique. The analyses suggest that most (about 77%) of the tweets focused on the search for new/better vaccines for diseases such as the Ebola virus, human papillomavirus (HPV), and the flu. Of the remainder, about half concerned the recent measles outbreak in the United States, and about half were part of ongoing debates between supporters and opponents of vaccination against measles in particular. While these numbers currently suggest a relatively small role for vaccine misinformation, the concept of herd immunity puts that role in context. Nevertheless, going forward, health experts should consider the potential for the increasing spread of falsehoods that may get firmly entrenched in the public mind.

The influence of education on health: an empirical assessment of OECD countries for the period 1995-2015.

BACKGROUND: A clear understanding of the macro-level contexts in which education impacts health is integral to improving national health administration and policy. In this research, we use a visual analytic approach to explore the association between education and health over a 20-year period for countries around the world. METHOD: Using empirical data from the OECD and the World Bank for 26 OECD countries for the years 1995-2015, we identify patterns/associations between education and health indicators. By incorporating pre- and post-educational attainment indicators, we highlight the dual role of education as both a driver of opportunity as well as of inequality. RESULTS: Adults with higher educational attainment have better health and lifespans compared to their less-educated peers. We highlight that tertiary education, particularly, is critical in influencing infant mortality, life expectancy, child vaccination, and enrollment rates. In addition, an economy needs to consider potential years of life lost (premature mortality) as a measure of health quality. CONCLUSIONS: We bring to light the health disparities across countries and suggest implications for governments to target educational interventions that can reduce inequalities and improve health. Our country-level findings on NEET (Not in Employment, Education or Training) rates offer implications for economies to address a broad array of vulnerabilities ranging from unemployment, school life expectancy, and labor market discouragement. The health effects of education are at the grass roots-creating better overall self-awareness on personal health and making healthcare more accessible.

An Empirical Study of Chronic Diseases in the United States: A Visual Analytics Approach.

In this research we explore the current state of chronic diseases in the United States, using data from the Centers for Disease Control and Prevention and applying visualization and descriptive analytics techniques. Five main categories of variables are studied, namely chronic disease conditions, behavioral health, mental health, demographics, and overarching conditions. These are analyzed in the context of regions and states within the U.S. to discover possible correlations between variables in several categories. There are widespread variations in the prevalence of diverse chronic diseases, the number of hospitalizations for specific diseases, and the diagnosis and mortality rates for different states. Identifying such correlations is fundamental to developing insights that will help in the creation of targeted management, mitigation, and preventive policies, ultimately minimizing the risks and costs of chronic diseases. As the population ages and individuals suffer from multiple conditions, or comorbidity, it is imperative that the various stakeholders, including the government, non-governmental organizations (NGOs), policy makers, health providers, and society as a whole, address these adverse effects in a timely and efficient manner.

Preventive Healthcare: A Neural Network Analysis of Behavioral Habits and Chronic Diseases.

The research aims to explore the association between behavioral habits and chronic diseases, and to identify a portfolio of risk factors for preventive healthcare. The data is taken from the Behavioral Risk Factor Surveillance System (BRFSS) database of the Centers for Disease Control and Prevention, for the year 2012. Using SPSS Modeler, we deploy neural networks to identify strong positive and negative associations between certain chronic diseases and behavioral habits. The data for 475,687 records from BRFS database included behavioral habit variables of consumption of soda and fruits/vegetables, alcohol, smoking, weekly working hours, and exercise; chronic disease variables of heart attack, stroke, asthma, and diabetes; and demographic variables of marital status, income, and age. Our findings indicate that with chronic conditions, behavioral habits of physical activity and fruit and vegetable consumption are negatively associated; soda, alcohol, and smoking are positively associated; and income and age are positively associated. We contribute to individual and national preventive healthcare by offering a portfolio of significant behavioral risk factors that enable individuals to make lifestyle changes and governments to frame campaigns and policies countering chronic conditions and promoting public health.

Big data analytics in healthcare: promise and potential.

OBJECTIVE: To describe the promise and potential of big data analytics in healthcare. METHODS: The paper describes the nascent field of big data analytics in healthcare, discusses the benefits, outlines an architectural framework and methodology, describes examples reported in the literature, briefly discusses the challenges, and offers conclusions. RESULTS: The paper provides a broad overview of big data analytics for healthcare researchers and practitioners. CONCLUSIONS: Big data analytics in healthcare is evolving into a promising field for providing insight from very large data sets and improving outcomes while reducing costs. Its potential is great; however there remain challenges to overcome.