Clinical research projects at a German medical faculty: follow-up from ethical approval to publication and citation by others

BACKGROUND: Only data of published study results are available to the scientific community for further use such as informing future research and synthesis of available evidence. If study results are reported selectively, reporting bias and distortion of summarised estimates of effect or harm of treatments can occur. The publication and citation of results of clinical research conducted in Germany was studied. METHODS: The protocols of clinical research projects submitted to the research ethics committee of the University of Freiburg (Germany) in 2000 were analysed. Published full articles in several databases were searched and investigators contacted. Data on study and publication characteristics were extracted from protocols and corresponding publications. RESULTS: 299 study protocols were included. The most frequent study design was randomised controlled trial (141; 47%), followed by uncontrolled studies (61; 20%), laboratory studies (30; 10%) and non-randomised studies (29; 10%). 182 (61%) were multicentre studies including 97 (53%) international collaborations. 152 of 299 (51%) had commercial (co-)funding and 46 (15%) non-commercial funding. 109 of the 225 completed protocols corresponded to at least one full publication (total 210 articles); the publication rate was 48%. 168 of 210 identified publications (80%) were cited in articles indexed in the ISI Web of Science. The median was 11 citations per publication (range 0-1151). CONCLUSIONS: Results of German clinical research projects conducted are largely underreported. Barriers to successful publication need to be identified and appropriate measures taken. Close monitoring of projects until publication and adequate support provided to investigators may help remedy the prevailing underreporting of research.

Strobe-Statement: Wie berichtet man eine Beobachtungsstudie?

Eine internationale Gruppe schlägt eine Checkliste mit 22 Punkten vor, die von Studiendesign und Methoden bis zum Umgang mit quantitativen Variablen reicht.

STROBE Statement: linee guida per descrivere gli studi osservazionali

Much of biomedical research is observational. The reporting of such research is often inadequate, which hampers the assessment of its strengths and weaknesses and of a study’s generalizability. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Initiative developed recommendations on what should be included in an accurate and complete report of an observational study. We defined the scope of the recommendations to cover three main study designs: cohort, casecontrol, and cross-sectional studies. We convened a 2-day workshop in September 2004, with methodologists, researchers, and journal editors to draft a checklist of items. This list was subsequently revised during several meetings of the coordinating group and in e-mail discussions with the larger group of STROBE contributors, taking into account empirical evidence and methodological considerations. The workshop and the subsequent iterative process of consultation and revision resulted in a checklist of 22 items (the STROBE Statement) that relate to the title, abstract, introduction, methods, results, and discussion sections of articles. Eighteen items are common to all three study designs and four are specific for cohort, case-control, or cross-sectional studies. A detailed “Explanation and Elaboration” document is published separately and is freely available on the web sites of PLoS Medicine, Annals of Internal Medicine, and Epidemiology. We hope that the STROBE Statement will contribute to improving the quality of reporting of observational studies.

An Experience-Driven Pedagogy for the Instruction of Software Testing in Computer Science

In the realm of computer programming, the experience of writing a program is used to reinforce concepts and evaluate ability. This research uses three case studies to evaluate the introduction of testing through Kolb's Experiential Learning Model (ELM). We then analyze the impact of those testing experiences to determine methods for improving future courses. The first testing experience that students encounter are unit test reports in their early courses. This course demonstrates that automating and improving feedback can provide more ELM iterations. The JUnit Generation (JUG) tool also provided a positive experience for the instructor by reducing the overall workload. Later, undergraduate and graduate students have the opportunity to work together in a multi-role Human-Computer Interaction (HCI) course. The interactions use usability analysis techniques with graduate students as usability experts and undergraduate students as design engineers. Students get experience testing the user experience of their product prototypes using methods varying from heuristic analysis to user testing. From this course, we learned the importance of the instructors role in the ELM. As more roles were added to the HCI course, a desire arose to provide more complete, quality assured software. This inspired the addition of unit testing experiences to the course. However, we learned that significant preparations must be made to apply the ELM when students are resistant. The research presented through these courses was driven by the recognition of a need for testing in a Computer Science curriculum. Our understanding of the ELM suggests the need for student experience when being introduced to testing concepts. We learned that experiential learning, when appropriately implemented, can provide benefits to the Computer Science classroom. When examined together, these course-based research projects provided insight into building strong testing practices into a curriculum.