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Evidence for Health I: Producing evidence for improving health and reducing inequities

Overview of attention for article published in Health Research Policy and Systems, March 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (81st percentile)
  • Above-average Attention Score compared to outputs of the same age and source (62nd percentile)

Mentioned by

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17 X users
facebook
1 Facebook page

Citations

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21 Dimensions

Readers on

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170 Mendeley
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Title
Evidence for Health I: Producing evidence for improving health and reducing inequities
Published in
Health Research Policy and Systems, March 2016
DOI 10.1186/s12961-016-0087-2
Pubmed ID
Authors

Anne Andermann, Tikki Pang, John N Newton, Adrian Davis, Ulysses Panisset

Abstract

In an ideal world, researchers and decision-makers would be involved from the outset in co-producing evidence, with local health needs assessments informing the research agenda and research evidence informing the actions taken to improve health. The first step in improving the health of individuals and populations is therefore gaining a better understanding of what the main health problems are, and of these, which are the most urgent priorities by using both quantitative data to develop a health portrait and qualitative data to better understand why the local population thinks that addressing certain health challenges should be prioritized in their context. Understanding the causes of these health problems often involves analytical research, such as case-control and cohort studies, or qualitative studies to better understand how more complex exposures lead to specific health problems (e.g. by interviewing local teenagers discovering that watching teachers smoke in the school yard, peer pressure, and media influence smoking initiation among youth). Such research helps to develop a logic model to better map out the proximal and distal causes of poor health and to determine potential pathways for intervening and impacting health outcomes. Rarely is there a single 'cure' or stand-alone intervention, but rather, a continuum of strategies are needed from diagnosis and treatment of patients already affected, to disease prevention, health promotion and addressing the upstream social determinants of health. Research for developing and testing more upstream interventions must often go beyond randomized controlled trials, which are expensive, less amenable to more complex interventions, and can be associated with certain ethical challenges. Indeed, a much neglected area of the research cycle is implementation and evaluation research, which often involves quasi-experimental research study designs as well as qualitative research, to better understand how to derive the greatest benefit from existing interventions and ways of maximizing health improvements in specific local contexts. There is therefore a need to alter current incentive structures within the research enterprise to place greater emphasis on implementation and evaluation research conducted in collaboration with knowledge users who are in a position to use the findings in practice to improve health.

X Demographics

X Demographics

The data shown below were collected from the profiles of 17 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 170 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 <1%
Unknown 169 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 26 15%
Researcher 20 12%
Student > Ph. D. Student 20 12%
Student > Doctoral Student 13 8%
Other 12 7%
Other 41 24%
Unknown 38 22%
Readers by discipline Count As %
Medicine and Dentistry 51 30%
Nursing and Health Professions 23 14%
Social Sciences 18 11%
Psychology 6 4%
Environmental Science 3 2%
Other 21 12%
Unknown 48 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 16 January 2019.
All research outputs
#3,498,251
of 24,021,239 outputs
Outputs from Health Research Policy and Systems
#523
of 1,284 outputs
Outputs of similar age
#56,169
of 303,905 outputs
Outputs of similar age from Health Research Policy and Systems
#10
of 24 outputs
Altmetric has tracked 24,021,239 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,284 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.1. This one has gotten more attention than average, scoring higher than 59% 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 303,905 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 81% of its contemporaries.
We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.