Mapping power law distributions in digital health social networks: methods, interpretations, and practical implications

BACKGROUND: Social networks are common in digital health. A new stream of research is beginning to investigate the mechanisms of digital health social networks (DHSNs), how they are structured, how they function, and how their growth can be nurtured and managed. DHSNs increase in value when additional content is added, and the structure of networks may resemble the characteristics of power laws. Power laws are contrary to traditional Gaussian averages in that they demonstrate correlated phenomena. OBJECTIVES: The objective of this study is to investigate whether the distribution frequency in four DHSNs can be characterized as following a power law. A second objective is to describe the method used to determine the comparison. METHODS: Data from four DHSNs—Alcohol Help Center (AHC), Depression Center (DC), Panic Center (PC), and Stop Smoking Center (SSC)—were compared to power law distributions. To assist future researchers and managers, the 5-step methodology used to analyze and compare datasets is described. RESULTS: All four DHSNs were found to have right-skewed distributions, indicating the data were not normally distributed. When power trend lines were added to each frequency distribution, R(2) values indicated that, to a very high degree, the variance in post frequencies can be explained by actor rank (AHC .962, DC .975, PC .969, SSC .95). Spearman correlations provided further indication of the strength and statistical significance of the relationship (AHC .987. DC .967, PC .983, SSC .993, P<.001). CONCLUSIONS: This is the first study to investigate power distributions across multiple DHSNs, each addressing a unique condition. Results indicate that despite vast differences in theme, content, and length of existence, DHSNs follow properties of power laws. The structure of DHSNs is important as it gives insight to researchers and managers into the nature and mechanisms of network functionality. The 5-step process undertaken to compare actor contribution patterns can be replicated in networks that are managed by other organizations, and we conjecture that patterns observed in this study could be found in other DHSNs. Future research should analyze network growth over time and examine the characteristics and survival rates of superusers.

Stress, time pressure, and decision making

This study surveys parents with children who are deaf or hard of hearing from one private school in St. Louis, Missouri. The issue of stress and time pressure on decision making is addressed and the importance of how stress and time pressure effect parents’ decisions regarding their children who are deaf and hard of hearing.

Health in Brazil 5 Violence and injuries in Brazil: the effect, progress made, and challenges ahead

Although there are signs of decline, homicides and traffic-related injuries and deaths in Brazil account for almost two-thirds of all deaths from external causes. In 2007, the homicide rate was 26.8 per 100 000 people and traffic-related mortality was 23.5 per 100 000. Domestic violence might not lead to as many deaths, but its share of violence-related morbidity is large. These are important public health problems that lead to enormous individual and collective costs. Young, black, and poor men are the main victims and perpetrators of community violence, whereas poor black women and children are the main victims of domestic violence. Regional differentials are also substantial. Besides the sociocultural determinants, much of the violence in Brazil has been associated with the misuse of alcohol and illicit drugs, and the wide availability of firearms. The high traffic-related morbidity and mortality in Brazil have been linked to the chosen model for the transport system that has given priority to roads and private-car use without offering adequate infrastructure. The system is often poorly equipped to deal with violations of traffic rules. In response to the major problems of violence and injuries, Brazil has greatly advanced in terms of legislation and action plans. The main challenge is to assess these advances to identify, extend, integrate, and continue the successful ones.

Lehman Flips for Clickers

The clicker is a versatile, easy to use electronic multiple choice device that helps provide instant feedback on what students are learning. In both hybrid and on-site classes, clickers provide a way to rapidly collect an answer to a question from every student; an answer for which they are all individually accountable. In this session, Biological sciences lecturer Rena Quinlan will describe her use of clickers with large classes that help students achieve defined course outcomes.

Essays on health care reform, wealth inequality, and demography

This thesis contains three chapters. The first chapter uses a general equilibrium framework to simulate and compare the long run effects of the Patient Protection and Affordable Care Act (PPACA) and of health care costs reduction policies on macroeconomic variables, government budget, and welfare of individuals. We found that all policies were able to reduce uninsured population, with the PPACA being more effective than cost reductions. The PPACA increased public deficit mainly due to the Medicaid expansion, forcing tax hikes. On the other hand, cost reductions alleviated the fiscal burden of public insurance, reducing public deficit and taxes. Regarding welfare effects, the PPACA as a whole and cost reductions are welfare improving. High welfare gains would be achieved if the U.S. medical costs followed the same trend of OECD countries. Besides, feasible cost reductions are more welfare improving than most of the PPACA components, proving to be a good alternative. The second chapter documents that life cycle general equilibrium models with heterogeneous agents have a very hard time reproducing the American wealth distribution. A common assumption made in this literature is that all young adults enter the economy with no initial assets. In this chapter, we relax this assumption – not supported by the data – and evaluate the ability of an otherwise standard life cycle model to account for the U.S. wealth inequality. The new feature of the model is that agents enter the economy with assets drawn from an initial distribution of assets. We found that heterogeneity with respect to initial wealth is key for this class of models to replicate the data. According to our results, American inequality can be explained almost entirely by the fact that some individuals are lucky enough to be born into wealth, while others are born with few or no assets. The third chapter documents that a common assumption adopted in life cycle general equilibrium models is that the population is stable at steady state, that is, its relative age distribution becomes constant over time. An open question is whether the demographic assumptions commonly adopted in these models in fact imply that the population becomes stable. In this chapter we prove the existence of a stable population in a demographic environment where both the age-specific mortality rates and the population growth rate are constant over time, the setup commonly adopted in life cycle general equilibrium models. Hence, the stability of the population do not need to be taken as assumption in these models.

Structural health evaluation by optimization techinique and artificial neural network

This paper presents two different approaches to detect, locate, and characterize structural damage. Both techniques utilize electrical impedance in a first stage to locate the damaged area. In the second stage, to quantify the damage severity, one can use neural network, or optimization technique. The electrical impedance-based, which utilizes the electromechanical coupling property of piezoelectric materials, has shown engineering feasibility in a variety of practical field applications. Relying on high frequency structural excitations, this technique is very sensitive to minor structural changes in the near field of the piezoelectric sensors, and therefore, it is able to detect the damage in its early stage. Optimization approaches must be used for the case where a good condensed model is known, while neural network can be also used to estimate the nature of damage without prior knowledge of the model of the structure. The paper concludes with an experimental example in a welded cubic aluminum structure, in order to verify the performance of these two proposed methodologies.