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X Demographics
Mendeley readers
Attention Score in Context
| Title |
The GRADE evidence-to-decision framework: a report of its testing and application in 15 international guideline panels
|
|---|---|
| Published in |
Implementation Science, July 2016
|
| DOI | 10.1186/s13012-016-0462-y |
| Pubmed ID | |
| Authors |
Ignacio Neumann, Romina Brignardello-Petersen, Wojtek Wiercioch, Alonso Carrasco-Labra, Carlos Cuello, Elie Akl, Reem A. Mustafa, Waleed Al-Hazzani, Itziar Etxeandia-Ikobaltzeta, Maria Ximena Rojas, Maicon Falavigna, Nancy Santesso, Jan Brozek, Alfonso Iorio, Pablo Alonso-Coello, Holger J. Schünemann |
| Abstract |
Judgments underlying guideline recommendations are seldom recorded and presented in a systematic fashion. The GRADE Evidence-to-Decision Framework (EtD) offers a transparent way to record and report guideline developers' judgments. In this paper, we report the experiences with the EtD frameworks in 15 real guideline panels. Following the guideline panel meetings, we asked methodologists participating in the panel to provide feedback regarding the EtD framework. They were instructed to consider their own experience and the feedback collected from the rest of the panel. Two investigators independently summarized the responses and jointly interpreted the data using pre-specified domains as coding system. We asked methodologists to review the results and provide further input to improve the structure of the EtDs iteratively. The EtD framework was well received, and the comments were generally positive. Methodologists felt that in a real guideline panel, the EtD framework helps structuring a complex process through relatively simple steps in an explicit and transparent way. However, some sections (e.g., "values and preferences" and "balance between benefits and harms") required further development and clarification that were considered in the current version of the EtD framework. The use of an EtD framework in guideline development offers a structured and explicit way to record and report the judgments and discussion of guideline panels during the formulation of recommendations. In addition, it facilitates the formulation of recommendations, assessment of their strength, and identifying gaps in research. |
X Demographics
The data shown below were collected from the profiles of 37 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 5 | 14% |
| United States | 5 | 14% |
| Canada | 4 | 11% |
| Chile | 2 | 5% |
| Spain | 2 | 5% |
| Italy | 1 | 3% |
| Ireland | 1 | 3% |
| South Africa | 1 | 3% |
| Australia | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 14 | 38% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 26 | 70% |
| Scientists | 6 | 16% |
| Practitioners (doctors, other healthcare professionals) | 3 | 8% |
| Science communicators (journalists, bloggers, editors) | 2 | 5% |
Mendeley readers
The data shown below were compiled from readership statistics for 83 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 1% |
| Spain | 1 | 1% |
| Canada | 1 | 1% |
| Unknown | 80 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 12 | 14% |
| Student > Master | 12 | 14% |
| Other | 10 | 12% |
| Student > Ph. D. Student | 8 | 10% |
| Professor | 5 | 6% |
| Other | 21 | 25% |
| Unknown | 15 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 36 | 43% |
| Nursing and Health Professions | 7 | 8% |
| Social Sciences | 4 | 5% |
| Computer Science | 2 | 2% |
| Philosophy | 2 | 2% |
| Other | 12 | 14% |
| Unknown | 20 | 24% |
Attention Score in Context
This research output has an Altmetric Attention Score of 25. 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 26 April 2022.
All research outputs
#1,453,000
of 24,775,802 outputs
Outputs from Implementation Science
#262
of 1,782 outputs
Outputs of similar age
#27,103
of 364,169 outputs
Outputs of similar age from Implementation Science
#7
of 29 outputs
Altmetric has tracked 24,775,802 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 1,782 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.9. This one has done well, scoring higher than 85% 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 364,169 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 92% of its contemporaries.
We're also able to compare this research output to 29 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.