A number of publishers and funders, including PLOS, have recently adopted policies requiring researchers to share the data underlying their results and publications. Such policies help increase the reproducibility of the published literature, as well as make a larger body of data available for reuse and re-analysis. In this study, we evaluate the extent to which authors have complied with this policy by analyzing Data Availability Statements from 47,593 papers published in PLOS ONE between March 2014 (when the policy went into effect) and May 2016. Our analysis shows that compliance with the policy has increased, with a significant decline over time in papers that did not include a Data Availability Statement. However, only about 20% of statements indicate that data are deposited in a repository, which the PLOS policy states is the preferred method. More commonly, authors state that their data are in the paper itself or in the supplemental information, though it is unclear whether these data meet the level of sharing required in the PLOS policy. These findings suggest that additional review of Data Availability Statements or more stringent policies may be needed to increase data sharing.

BackgroundSignificant efforts are underway within the biomedical research community to encourage sharing and reuse of research data in order to enhance research reproducibility and enable scientific discovery. While some technological challenges do exist, many of the barriers to sharing and reuse are social in nature, arising from researchers’ concerns about and attitudes toward sharing their data. In addition, clinical and basic science researchers face their own unique sets of challenges to sharing data within their communities. This study investigates these differences in experiences with and perceptions about sharing data, as well as barriers to sharing among clinical and basic science researchers.MethodsClinical and basic science researchers in the Intramural Research Program at the National Institutes of Health were surveyed about their attitudes toward and experiences with sharing and reusing research data. Of 190 respondents to the survey, the 135 respondents who identified themselves as clinical or basic science researchers were included in this analysis. Odds ratio and Fisher’s exact tests were the primary methods to examine potential relationships between variables. Worst-case scenario sensitivity tests were conducted when necessary.Results and DiscussionWhile most respondents considered data sharing and reuse important to their work, they generally rated their expertise as low. Sharing data directly with other researchers was common, but most respondents did not have experience with uploading data to a repository. A number of significant differences exist between the attitudes and practices of clinical and basic science researchers, including their motivations for sharing, their reasons for not sharing, and the amount of work required to prepare their data.ConclusionsEven within the scope of biomedical research, addressing the unique concerns of diverse research communities is important to encouraging researchers to share and reuse data. Efforts at promoting data sharing and reuse should be aimed at solving not only technological problems, but also addressing researchers’ concerns about sharing their data. Given the varied practices of individual researchers and research communities, standardizing data practices like data citation and repository upload could make sharing and reuse easier.

We sought to review the state of the science for research on multiple gestations. A literature search was performed with the use of PubMed for studies to quantify the representation of multiple gestations for a sample period (2012e2016) that were limited to phase III and IV randomized controlled trials, that were written in English, and that addressed at least 1 of 4 major pregnancy complications: fetal growth restriction or small-for-gestational-age fetus, gestational diabetes mellitus, preeclampsia, and preterm delivery. Of the 226 studies that are included in the analysis, multiple pregnancies were most represented in studies of preterm delivery: 17% of trials recruited both singleton and multiple pregnancies; another 18% of trials recruited only multiple pregnancies. For trials that studied preeclampsia, fetal growth restriction, and gestational diabetes mellitus, 17%, 8%, and 2%, respectively, recruited both singleton and multiple gestations. None of the trials on these 3 topics were limited to women with a multiple pregnancy. Women with a multiple pregnancy are at risk for complications similar to those of women with singleton pregnancies, but their risk is usually higher. Also, the pathophysiologic condition for some complications differs in multiple gestations from those that occur in singleton gestations. Conditions that are unique to multiple pregnancies include excess placenta, placental crowding or inability of the uteroplacental unit to support the normal growth of multiple fetuses, or suboptimal placental implantation sites with an increased risk of abnormal placental location. Other adverse outcomes in multiple gestations are also influenced by twin-specific risk factors, most notably chorionicity. Although twins have been well represented in many studies of preterm birth, these studies have failed to identify adequate predictive tests (short cervical length established over 2 decades ago remains the single best predictor), to establish effective interventions, and to differentiate the underlying pathophysiologic condition of twin preterm birth. Questions about fetal growth also remain. Twin growth deviates from that of singleton gestations starting at approximately 32 weeks of gestation; however, research with long-term follow-up is needed to better distinguish pathologic and physiologic growth deviations, which include growth discordance among pairs (or more). There are virtually no clinical trials that are specific to twins for gestational diabetes mellitus or preeclampsia, and subgroups for multiple pregnancies in existing trials are not large enough to allow definite conclusions. Another important area is the determination of appropriate maternal nutrition or micronutrient supplementation to optimize pregnancy and child health. There are also unique aspects to consider for research design in multiple gestations, such as designation and tracking of the correct fetus prenatally and through delivery. The correct statistical methods must be used to account for correlated data because multiple fetu...