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A systematic review of comparisons between protocols or registrations and full reports in primary biomedical research

Overview of attention for article published in BMC Medical Research Methodology, January 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (91st percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

Mentioned by

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45 tweeters

Citations

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4 Dimensions

Readers on

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28 Mendeley
Title
A systematic review of comparisons between protocols or registrations and full reports in primary biomedical research
Published in
BMC Medical Research Methodology, January 2018
DOI 10.1186/s12874-017-0465-7
Pubmed ID
Authors

Guowei Li, Luciana P. F. Abbade, Ikunna Nwosu, Yanling Jin, Alvin Leenus, Muhammad Maaz, Mei Wang, Meha Bhatt, Laura Zielinski, Nitika Sanger, Bianca Bantoto, Candice Luo, Ieta Shams, Hamnah Shahid, Yaping Chang, Guangwen Sun, Lawrence Mbuagbaw, Zainab Samaan, Mitchell A. H. Levine, Jonathan D. Adachi, Lehana Thabane

Abstract

Prospective study protocols and registrations can play a significant role in reducing incomplete or selective reporting of primary biomedical research, because they are pre-specified blueprints which are available for the evaluation of, and comparison with, full reports. However, inconsistencies between protocols or registrations and full reports have been frequently documented. In this systematic review, which forms part of our series on the state of reporting of primary biomedical, we aimed to survey the existing evidence of inconsistencies between protocols or registrations (i.e., what was planned to be done and/or what was actually done) and full reports (i.e., what was reported in the literature); this was based on findings from systematic reviews and surveys in the literature. Electronic databases, including CINAHL, MEDLINE, Web of Science, and EMBASE, were searched to identify eligible surveys and systematic reviews. Our primary outcome was the level of inconsistency (expressed as a percentage, with higher percentages indicating greater inconsistency) between protocols or registration and full reports. We summarized the findings from the included systematic reviews and surveys qualitatively. There were 37 studies (33 surveys and 4 systematic reviews) included in our analyses. Most studies (n = 36) compared protocols or registrations with full reports in clinical trials, while a single survey focused on primary studies of clinical trials and observational research. High inconsistency levels were found in outcome reporting (ranging from 14% to 100%), subgroup reporting (from 12% to 100%), statistical analyses (from 9% to 47%), and other measure comparisons. Some factors, such as outcomes with significant results, sponsorship, type of outcome and disease speciality were reported to be significantly related to inconsistent reporting. We found that inconsistent reporting between protocols or registrations and full reports of primary biomedical research is frequent, prevalent and suboptimal. We also identified methodological issues such as the need for consensus on measuring inconsistency across sources for trial reports, and more studies evaluating transparency and reproducibility in reporting all aspects of study design and analysis. A joint effort involving authors, journals, sponsors, regulators and research ethics committees is required to solve this problem.

Twitter Demographics

The data shown below were collected from the profiles of 45 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 25%
Student > Master 5 18%
Unspecified 4 14%
Student > Ph. D. Student 3 11%
Student > Bachelor 3 11%
Other 6 21%
Readers by discipline Count As %
Medicine and Dentistry 10 36%
Unspecified 7 25%
Agricultural and Biological Sciences 4 14%
Pharmacology, Toxicology and Pharmaceutical Science 2 7%
Computer Science 1 4%
Other 4 14%

Attention Score in Context

This research output has an Altmetric Attention Score of 23. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 February 2018.
All research outputs
#713,477
of 13,605,107 outputs
Outputs from BMC Medical Research Methodology
#102
of 1,253 outputs
Outputs of similar age
#32,783
of 391,045 outputs
Outputs of similar age from BMC Medical Research Methodology
#19
of 146 outputs
Altmetric has tracked 13,605,107 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,253 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.1. This one has done particularly well, scoring higher than 91% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 391,045 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 146 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.