Ushering in a New Era of Open Science Through Data Sharing
Available from: Susan Jane Bull
- "Data may be misinterpreted, or the subject of biased, inappropriate , or poorly designed studies (Greenhalgh, 2009; Kirwan, 1997; Pisani, Whitworth, Zaba, & Abou-Zahr, 2010a; Rathi et al., 2012; Spertus, 2012; Wieseler et al., 2012). The results of such studies may mislead health care providers and regulators, lead to false hopes or unfounded concerns about treatments, reduce public confidence in research, and result in litigation (Anderson & Merry, 2009; Castellani, 2013; Kuntz, 2013; Mello et al., 2013; Nisen & Rockhold, 2013; Ross & Krumholz, 2013). In addition, incentives for novel biomedical research may be reduced, if secondary data users can " free-ride " on the efforts of those collecting the data (Castellani, 2013; Langat et al., 2011; "
[Show abstract] [Hide abstract]
ABSTRACT: There is increasing support for sharing individual-level data generated by medical and public health research. This scoping review of empirical research and conceptual literature examined stakeholders' perspectives of ethical best practices in data sharing, particularly in low- and middle-income settings. Sixty-nine empirical and conceptual articles were reviewed, of which, only five were empirical studies and eight were conceptual articles focusing on low- and middle-income settings. We conclude that support for sharing individual-level data is contingent on the development and implementation of international and local policies and processes to support ethical best practices. Further conceptual and empirical research is needed to ensure data sharing policies and processes in low- and middle-income settings are appropriately informed by stakeholders' perspectives.
© The Author(s) 2015.
Available from: Pamela Saunders
- "The issue of sharing data from research studies is important for advancing science and medicine (Marshall 1990; Spertus 2012; Ross et al. 2013; Wilhelm et al. 2014). While the research on data sharing examines sharing among academic communities , it does not explore data sharing with "
[Show abstract] [Hide abstract]
ABSTRACT: Data sharing is a key biomedical research theme for the 21st century. Biomedical data sharing is the exchange of data among (non)affiliated parties under mutually agreeable terms to promote scientific advancement and the development of safe and effective medical products. Wide sharing of research data is important for scientific discovery, medical product development, and public health. Data sharing enables improvements in development of medical products, more attention to rare diseases, and cost-efficiencies in biomedical research. We interviewed 11 participants about their attitudes and beliefs about data sharing. Using a qualitative, thematic analysis approach, our analysis revealed a number of themes including: experiences, approaches , perceived challenges, and opportunities for sharing data.
Available from: Nicole Wolfe
- "The incomplete or total lack of reporting of drug trials is so common that our perceptions of the true benefits and harms of drugs are generally much too positive
[5,6,9,12,13]. There have been prominent cases of well known drugs, such as gabapentin, oseltamivir, and rofecoxib where the analysis of unpublished data revealed important insights about the benefits and harms of those drugs not previously identified in their initial publications
.Therefore, it is critical that systematic reviews of drugs, which are often used as the basis for clinical practice guidelines, identify and include unpublished data from drug trials. The Cochrane Collaboration is a major producer of rigorous systematic reviews of health care interventions, but only 12% of Cochrane reviews from 2000 to 2006 included unpublished trials
[Show abstract] [Hide abstract]
Authors of systematic reviews have difficulty obtaining unpublished data for their reviews. This project aimed to provide an in-depth description of the experiences of authors in searching for and gaining access to unpublished data for their systematic reviews, and to give guidance on best practices for identifying, obtaining and using unpublished data.
This is a qualitative study analyzing in-depth interviews with authors of systematic reviews who have published Cochrane reviews or published systematic reviews outside of The Cochrane Library. We included participants who 1) were the first or senior author of a published systematic review of a drug intervention, 2) had expertise in conducting systematic reviews, searching for data, and assessing methodological biases, and 3) were able to participate in an interview in English. We used non-random sampling techniques to identify potential participants. Eighteen Cochrane authors were contacted and 16 agreed to be interviewed (89% response rate). Twenty-four non-Cochrane authors were contacted and 16 were interviewed (67% response rate).
Respondents had different understandings of what was meant by unpublished data, including specific outcomes and methodological details. Contacting study authors was the most common method used to obtain unpublished data and the value of regulatory agencies as a data source was underappreciated. Using the data obtained was time consuming and labor intensive. Respondents described the collaboration with other colleagues and/or students required to organize, manage and use the data in their reviews, generally developing and using templates, spreadsheets and computer programs for data extraction and analysis. Respondents had a shared belief that data should be accessible but some had concerns about sharing their own data. Respondents believed that obtaining unpublished data for reviews has important public health implications. There was widespread support for government intervention to ensure open access to trial data.
Respondents uniformly agreed that the benefit of identifying unpublished data was worth the effort and was necessary to identify the true harms and benefits of drugs. Recent actions by government, such as increased availability of trial data from the European Medicines Agency, may make it easier to acquire critical drug trial data.
Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed. The impact factor represents a rough estimation of the journal's impact factor and does not reflect the actual current impact factor. Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence agreement may be applicable.