Transition of young people with chronic conditions: a cross-sectional study of patient perceptions before and after transfer from pediatric to adult health care.

UNLABELLED: The aim of this study was to compare perceived barriers to and the most preferred age for successful transition to adult health care between young people with chronic disorders who had not yet transferred from pediatric to adult health care (pre-transfer) and those who had already transferred (post-transfer). In a cross-sectional study, we compared 283 pre-transfer with 89 post-transfer young people, using a 28-item questionnaire that focused on perceived barriers to transition and beliefs about the most preferred age to transfer. Feeling at ease with the pediatrician was the most important barrier to successful transition in both groups, but was rated significantly higher in the pre-transfer compared to the post-transfer group (OR = 2.03, 95 %CI 1.12-3.71). Anxiety and lack of information were the next most important barriers, rated equally highly by the two groups (OR = 0.67, 95 %CI 0.35-1.28 and OR = 0.71, 95 %CI 0.36-1.38, respectively). More than 80 % of the respondents in both groups reported that 16-19 years was the most preferred age to transfer; more than half of all the respondents reported 18-19 years and older as the most preferred age. CONCLUSION: Better transition planning through the provision of regular and more detailed information about adult health-care providers and the transition process could reduce anxiety and contribute to a more positive attitude to overcome perceived barriers to transition from young people's perspective. Young people's preferences about transferring to adult health care provide a challenge to those children's hospitals that transfer to adult health care at a younger age.

Fast and Rigorous Computation of Gene and Pathway Scores from SNP-Based Summary Statistics.

Integrating single nucleotide polymorphism (SNP) p-values from genome-wide association studies (GWAS) across genes and pathways is a strategy to improve statistical power and gain biological insight. Here, we present Pascal (Pathway scoring algorithm), a powerful tool for computing gene and pathway scores from SNP-phenotype association summary statistics. For gene score computation, we implemented analytic and efficient numerical solutions to calculate test statistics. We examined in particular the sum and the maximum of chi-squared statistics, which measure the strongest and the average association signals per gene, respectively. For pathway scoring, we use a modified Fisher method, which offers not only significant power improvement over more traditional enrichment strategies, but also eliminates the problem of arbitrary threshold selection inherent in any binary membership based pathway enrichment approach. We demonstrate the marked increase in power by analyzing summary statistics from dozens of large meta-studies for various traits. Our extensive testing indicates that our method not only excels in rigorous type I error control, but also results in more biologically meaningful discoveries.

Are Public Private Partnerships that Rigid ? And Why ? : Evidence from Toll Road Concession Contracts

Transport concession contracts are commonly said to be standardized and too rigid. They would not allow public authorities to adapt them to evolving context and circumstances. This paper aims at challenging this view and, more particularly, the view that contractual rigidity for transport concessions is exogenous. Using a transaction cost framework, we disentangle between three main determinants of contractual rigidity: traffic uncertainty; connivance between contracting parties; quality of the institutional environment. Using an original database of toll road concession contracts, we observe a great variety of provisions for toll adjustment. We find that these exogenous determinants significantly influence contractual choices.