Reducing waste from incomplete or unusable reports of biomedical research.
By P. Glasziou, Douglas G. Altman, P. Bossuyt, I. Boutron, Mike Clarke, S. Julious, Susan Michie, David Moher, Elizabeth Wager. The Lancet, 2014
1,136 citations recorded by the source corpus.
Subfields: Molecular Biology, Public Health, Environmental and Occupational Health, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/01d7653f2f9acc752e14f5be18c3f9d0ea376226
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Molecular Biology
- John P. A. Ioannidis
- David Moher
- K. F. Schulz
- C. Begley
- John Shawe-Taylor
- Douglas G. Altman
- Susan Michie
- Trisha Greenhalgh
In Public Health, Environmental and Occupational Health
- Douglas G. Altman
- David Moher
- K. F. Schulz
- John P. A. Ioannidis
- Matthias Egger
- Susan Michie
- Matthew J. Page
- I. Boutron
In Statistics and Probability
- David Moher
- Douglas G. Altman
- K. F. Schulz
- John P. A. Ioannidis
- Matthew J. Page
- Johannes B Reitsma
- Matthias Egger
- Stanley E. Lazic
Citations in the corpus
- The ARRIVE guidelines 2.0: updated guidelines for reporting animal research (2020, background): “…that scientific publications often lack key information and that there continues to be considerable scope for improvement (McCance, 1995, Hackam & Redelmeier, 2006, Kilkenny et al. 2009, Macleod et al. 2009, Rice et al. 2009, van der Worp et al. 2010, Glasziou et al. 2014, Macleod et al. 2015).”
- Preferred Reporting Items for a Systematic Review and Meta-analysis of Diagnostic Test Accuracy Studies: The PRISMA-DTA Statement (2018, methodology): “Study characteristicsb 18 For each included study, provide citations and present key characteristics including (1) participant characteristics (presentation, prior testing), (2) clinical setting, (3) study design, (4) target condition definition, (5) index test, (6) reference standard, (7) sample si”
- Evaluations of the uptake and impact of the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) Statement and extensions: a scoping review (2017, background): “This can contribute to the failure to implement the findings of SRs into clinical practice [2].”
- Reproducibility in Science: Improving the Standard for Basic and Preclinical Research (2015, positive): “Institutions may also serve the goal of improving research credibility and efficiency if they adopt appointment and promotion standards that, instead of relying on publication in top tier journals as a surrogate for quality, recognizes the importance of reproducible research findings rather than fla”
- CONSORT Statement for Randomized Trials of Nonpharmacologic Treatments: A 2017 Update and a CONSORT Extension for Nonpharmacologic Trial Abstracts. (2017, background): “I reporting is responsible for a great deal of avoidable waste in research (1, 2).”
- The REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) Statement (2015, background): “By improving the quality of reporting of research using routinely collected health data, we seek to reduce unclear research reports and achieve the tenets of the scientific process: discovery, transparency, and replicability [18].”
- Guidelines for Accurate and Transparent Health Estimates Reporting: the GATHER statement (2016, positive): “Recent reports on waste in research have highlighted that full documentation of research, including protocols for sharing data and code, increase the value of research that is undertaken [20,21].”
- STARD 2015: An Updated List of Essential Items for Reporting Diagnostic Accuracy Studies. (2015, background): “Unfortunately, deficiencies in the reporting of research have been highlighted in several areas of clinical medicine (1).”
- Reporting guidelines for health care simulation research: extensions to the CONSORT and STROBE statements (2016, background): “As has been shown in other fields of medicine [20], the quality of reporting in health professions education”
- Reporting animal research: Explanation and Elaboration for the ARRIVE guidelines 2019 (2019, background): “If a systematic review is not available, take care to avoid selectively citing studies that corroborate the results, or only those that report statistically significant findings [206].”
- The Human Behaviour-Change Project: harnessing the power of artificial intelligence and machine learning for evidence synthesis and interpretation (2017, background): “recognised and addressed: for example, the Lancet series “Research: increasing value, reducing waste” [1] and the”