Search

Objective: This research explored how time-to-event dental articles were indexed and reported, and sought solutions to help improve the reporting and identification of these articles, so that they could be more easily found and used to inform practice and research. Methods: Articles reporting time-to-event dental outcomes in humans were identified from the 50 dental journals with the highest impact factor for 2008. These were handsearched, identifying 'case' articles (n=95), active controls (likely false positives, n=91), and passive controls (other true negatives, n=6796). The medical subject headings (MESH) that had been assigned to the articles in MEDLINE, and words used in titles and abstracts describing time-to-events were compared between the 'cases' and controls. Time-to-event words and figures within articles were also sought, and reporting quality was assessed. Search strategies to identify time-toevent articles were developed, using indexing terms and free-text words. An independent cohort of articles was used to validate the search strategies, consisting of 148 time-to-event articles handsearched from 6514 articles in the 50 dental journals with the highest impact factor for 2012. The findings of the research were used to draft guidance to improve reporting, which was circulated amongst 78 stakeholder experts for comment, and modified. Results: MeSH indexing of time-to-event analyses was inconsistent and inaccurate, author descriptions in abstracts and titles varied, and the quality of time-to-event reporting and graphics in the body of those articles was poor. The burden faced by someone wishing to find and use these articles was considered high. Sensitive, precise and optimized electronic search strategies were developed and validated with sensitivities up to 92% and precisions up to 93%. The draft guidance attracted comment from 46 experts across 15 countries, with approximately 90% of the 130 comments accepted into the revised version. The importance of good quality reporting was endorsed, and there was high interest in commending the guidance to authors, reviewers, and training dental specialists. Conclusions: This research programme explored how time-to-event dental articles were reported, and used those findings to suggest solutions that would help to improve the identification and use of these data, reducing research waste.

Biological sciences literature can be extraordinarily difficult to understand. Papers are commonly filled with terminology unique to a particular sub-discipline. Readers with expertise outside that sub-discipline often have difficulty understanding information the author is trying to convey. The WikiPDF project that is the subject of this thesis helps readers understand the biological sciences literature by automatically generating a customized glossary for each page of any technical paper available in Adobe Portable Document Format (PDF) format. WikiPDF relies on the Wikipedia®, an on-line encyclopedia created and supported by a host of volunteers, as a source of definitions used in its glossaries. WikiPDF uses the National Institutes of Health (NIH) Medline/PubMed database of journal papers to organize, index, and locate WikiPDF glossaries. Design and implementation of this project relied exclusively on open-source software, including the Linux operating system, the Apache Tomcat web server, and the MySQL relational database system.