Measuring and Anticipating the Impact of Data Reuse.

In this dissertation, I examined data citations in the social sciences, measured the scholarly impact of data reuse as well as explored factors that are associated with whether a dataset is reused. The guiding question for this dissertation is: What is the scholarly impact of data reuse? How can stakeholders anticipate the impact the data they fund, create, or curate will have? I addressed this question is three parts. First, in order to quantify the scholarly impact of data reuse, I looked at identifying reuse through data citation patterns. My study extends previous studies by taking a more nuanced view of how social scientists use citations to acknowledge others’ prior work on which they are building. Second, I developed a suite of impact metrics for data. By testing these metrics on a varied group of social science datasets, I was demonstrated their use and shed light on how these datasets can be high impact in different ways. Finally, I explored what factors correlate with reuse and with high impact. Examining data reuse in the social science literature showed that reusers of data regularly cite data producers’ publications, rather than citing data directly or crediting the data provider. Where they cite the data provider, they typically do so in addition to citing the data producer. This finding suggests that data reusers distinguish between the contributions producers make when they create data and when they share it: in essence, data reusers use citations to credit both actions. The four measures of reuse impact I developed highlighted different aspects of impact for data; no datasets were high-impact across the board, and few were consistently low-impact. The three metrics based on citations were especially divergent, suggesting that data can have an impact in multiple and varying ways. Finally, I showed that two characteristics of data are particularly related to whether the data are reused or not: the size of the data and how actively used they are. Together, these findings indicate that sharing data contributes to scholarship above and beyond the initial contribution a scientist makes when she creates data and publishes from them.PhDInformationUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/102481/1/kfear_1.pd

Analgesic antipyretic use among young children in the TEDDY study : No association with islet autoimmunity

Background: The use of analgesic antipyretics (ANAP) in children have long been a matter of controversy. Data on their practical use on an individual level has, however, been scarce. There are indications of possible effects on glucose homeostasis and immune function related to the use of ANAP. The aim of this study was to analyze patterns of analgesic antipyretic use across the clinical centers of The Environmental Determinants of Diabetes in the Young (TEDDY) prospective cohort study and test if ANAP use was a risk factor for islet autoimmunity. Methods: Data were collected for 8542 children in the first 2.5 years of life. Incidence was analyzed using logistic regression with country and first child status as independent variables. Holm's procedure was used to adjust for multiplicity of intercountry comparisons. Time to autoantibody seroconversion was analyzed using a Cox proportional hazards model with cumulative analgesic use as primary time dependent covariate of interest. For each categorization, a generalized estimating equation (GEE) approach was used. Results: Higher prevalence of ANAP use was found in the U.S. (95.7%) and Sweden (94.8%) compared to Finland (78.1%) and Germany (80.2%). First-born children were more commonly given acetaminophen (OR 1.26; 95% CI 1.07, 1.49; p = 0.007) but less commonly Non-Steroidal Anti-inflammatory Drugs (NSAID) (OR 0.86; 95% CI 0.78, 0.95; p = 0.002). Acetaminophen and NSAID use in the absence of fever and infection was more prevalent in the U.S. (40.4%; 26.3% of doses) compared to Sweden, Finland and Germany (p < 0.001). Acetaminophen or NSAID use before age 2.5 years did not predict development of islet autoimmunity by age 6 years (HR 1.02, 95% CI 0.99-1.09; p = 0.27). In a sub-analysis, acetaminophen use in children with fever weakly predicted development of islet autoimmunity by age 3 years (HR 1.05; 95% CI 1.01-1.09; p = 0.024). Conclusions: ANAP use in young children is not a risk factor for seroconversion by age 6 years. Use of ANAP is widespread in young children, and significantly higher in the U.S. compared to other study sites, where use is common also in absence of fever and infection