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On-going collaborative priority-setting for research activity: a method of capacity building to reduce the research-practice translational gap

Overview of attention for article published in Health Research Policy and Systems, May 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (76th percentile)
  • Average Attention Score compared to outputs of the same age and source

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Title
On-going collaborative priority-setting for research activity: a method of capacity building to reduce the research-practice translational gap
Published in
Health Research Policy and Systems, May 2015
DOI 10.1186/s12961-015-0014-y
Pubmed ID
Authors

Jo Cooke, Steven Ariss, Christine Smith, Jennifer Read

Abstract

International policy suggests that collaborative priority setting (CPS) between researchers and end users of research should shape the research agenda, and can increase capacity to address the research-practice translational gap. There is limited research evidence to guide how this should be done to meet the needs of dynamic healthcare systems. One-off priority setting events and time-lag between decision and action prove problematic. This study illustrates the use of CPS in a UK research collaboration called Collaboration and Leadership in Applied Health Research and Care (CLAHRC). Data were collected from a north of England CLAHRC through semi-structured interviews with 28 interviewees and a workshop of key stakeholders (n = 21) including academics, NHS clinicians, and managers. Documentary analysis of internal reports and CLAHRC annual reports for the first two and half years was also undertaken. These data were thematically coded. Methods of CPS linked to the developmental phase of the CLAHRC. Early methods included pre-existing historical partnerships with on-going dialogue. Later, new platforms for on-going discussions were formed. Consensus techniques with staged project development were also used. All methods demonstrated actual or potential change in practice and services. Impact was enabled through the flexibility of research and implementation work streams; 'matched' funding arrangements to support alignment of priorities in partner organisations; the size of the collaboration offering a resource to meet project needs; and the length of the programme providing stability and long term relationships. Difficulties included tensions between being responsive to priorities and the possibility of 'drift' within project work, between academics and practice, and between service providers and commissioners in the health services. Providing protected 'matched' time proved difficult for some NHS managers, which put increasing work pressure on them. CPS is more time consuming than traditional approaches to project development. CPS can produce needs-led projects that are bedded in services using a variety of methods. Contributing factors for effective CPS include flexibility in use and type of available resources, flexible work plans, and responsive leadership. The CLAHRC model provides a translational infrastructure that enables CPS that can impact on healthcare systems.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 137 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Indonesia 1 <1%
New Zealand 1 <1%
Unknown 135 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 25 18%
Student > Ph. D. Student 20 15%
Student > Master 17 12%
Other 12 9%
Student > Doctoral Student 10 7%
Other 25 18%
Unknown 28 20%
Readers by discipline Count As %
Social Sciences 32 23%
Medicine and Dentistry 23 17%
Nursing and Health Professions 14 10%
Psychology 6 4%
Engineering 5 4%
Other 23 17%
Unknown 34 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 30 March 2016.
All research outputs
#5,391,451
of 22,803,211 outputs
Outputs from Health Research Policy and Systems
#638
of 1,213 outputs
Outputs of similar age
#63,042
of 264,554 outputs
Outputs of similar age from Health Research Policy and Systems
#8
of 13 outputs
Altmetric has tracked 22,803,211 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,213 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 47th percentile – i.e., 47% 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 264,554 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 76% of its contemporaries.
We're also able to compare this research output to 13 others from the same source and published within six weeks on either side of this one. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.