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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Identifying potential indicators to measure the outcome of translational cancer research: a mixed methods approach
|
|---|---|
| Published in |
Health Research Policy and Systems, December 2015
|
| DOI | 10.1186/s12961-015-0060-5 |
| Pubmed ID | |
| Authors |
Frédérique Thonon, Rym Boulkedid, Maria Teixeira, Serge Gottot, Mahasti Saghatchian, Corinne Alberti |
| Abstract |
In a context where there is an increasing demand to evaluate the outcome of bio-medical research, our work aims to develop a set of indicators to measure the impact of translational cancer research. The objective of our study was to explore the scope and issues of translational research relevant to evaluation, explore the views of researchers on the evaluation of oncological translational research, and select indicators measuring the outcomes and outputs of translational research in oncology by consensus. Semi-structured interviews amongst 23 researchers involved in translational cancer research were conducted and analysed using thematic analysis. A two-round modified Delphi survey of 35 participants with similar characteristics was then performed followed by a physical meeting. Participants rated the feasibility and validity of 60 indicators. The physical meeting was held to discuss the methodology of the new indicators. The main themes emerging from the interviews included a common definition for translational research but disagreements about the exact scope and limits of this research, the importance of multidisciplinarity and collaboration for the success of translational research, the disadvantages that translational research faces in current evaluation systems, the relative lack of pertinence of existing indicators, and propositions to measure translational cancer research in terms of clinical applications and patient outcomes. A total of 35 participants took part in the first round survey and 12 in the second round. The two-round survey helped us select a set of 18 indicators, including four that seemed to be particularly adapted to measure translational cancer research impact on health service research (number of biomarkers identified, generation of clinical guidelines, citation of research in clinical guidelines, and citation of research in public health guidelines). The feedback from participants helped refine the methodology and definition of indicators not commonly used. Indicators need to be accepted by stakeholders under evaluation. This study helped the selection and refinement of indicators considered as the most relevant by researchers in translational cancer research. The feasibility and validity of those indicators will be tested in a scientometric study. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 58 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 17% |
| Researcher | 8 | 14% |
| Student > Master | 5 | 9% |
| Student > Bachelor | 5 | 9% |
| Student > Doctoral Student | 4 | 7% |
| Other | 13 | 22% |
| Unknown | 13 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 11 | 19% |
| Biochemistry, Genetics and Molecular Biology | 4 | 7% |
| Computer Science | 4 | 7% |
| Agricultural and Biological Sciences | 3 | 5% |
| Nursing and Health Professions | 3 | 5% |
| Other | 16 | 28% |
| Unknown | 17 | 29% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 10 December 2015.
All research outputs
#15,866,607
of 23,577,654 outputs
Outputs from Health Research Policy and Systems
#1,110
of 1,238 outputs
Outputs of similar age
#231,241
of 390,883 outputs
Outputs of similar age from Health Research Policy and Systems
#28
of 32 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,238 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.1. This one is in the 7th percentile – i.e., 7% of its peers scored the same or lower than it.
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 390,883 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 32 others from the same source and published within six weeks on either side of this one. This one is in the 3rd percentile – i.e., 3% of its contemporaries scored the same or lower than it.