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Evaluating and Using Observational Evidence: The Contrasting Views of Policy Makers and Epidemiologists

Overview of attention for article published in Frontiers in Public Health, December 2016
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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 (90th percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

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Title
Evaluating and Using Observational Evidence: The Contrasting Views of Policy Makers and Epidemiologists
Published in
Frontiers in Public Health, December 2016
DOI 10.3389/fpubh.2016.00267
Pubmed ID
Authors

Lily O’Donoughue Jenkins, Paul M. Kelly, Nicolas Cherbuin, Kaarin J. Anstey

Abstract

Currently, little is known about the types of evidence used by policy makers. This study aimed to investigate how policy makers in the health domain use and evaluate evidence and how this differs from academic epidemiologists. By having a better understanding of how policy makers select, evaluate, and use evidence, academics can tailor the way in which that evidence is produced, potentially leading to more effective knowledge translation. An exploratory mixed-methods study design was used. Quantitative measures were collected via an anonymous online survey (n = 28), with sampling from three health-related government and non-government organizations. Semi-structured interviews with policy makers (n = 20) and epidemiologists (n = 6) were conducted to gather qualitative data. Policy makers indicated systematic reviews were the preferred research resource (19%), followed closely by qualitative research (16%). Neither policy makers nor epidemiologists used grading instruments to evaluate evidence. In the web survey, policy makers reported that consistency and strength of evidence (93%), the quality of data (93%), bias in the evidence (79%), and recency of evidence (79%) were the most important factors taken into consideration when evaluating the available evidence. The same results were found in the qualitative interviews. Epidemiologists focused on the methodology used in the study. The most cited barriers to using robust evidence, according to policy makers, were political considerations (60%), time limitations (55%), funding (50%), and research not being applicable to current policies (50%). The policy maker's investigation did not report a systematic approach to evaluating evidence. Although there was some overlap between what policy makers and epidemiologists identified as high-quality evidence, there was also some important differences. This suggests that the best scientific evidence may not routinely be used in the development of policy. In essence, the policy-making process relied on other jurisdictions' policies and the opinions of internal staff members as primary evidence sources to inform policy decisions. Findings of this study suggest that efforts should be directed toward making scientific information more systematically available to policy makers.

X Demographics

X Demographics

The data shown below were collected from the profiles of 27 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 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 61 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 25%
Student > Ph. D. Student 11 18%
Professor 5 8%
Student > Master 5 8%
Student > Postgraduate 4 7%
Other 10 16%
Unknown 11 18%
Readers by discipline Count As %
Social Sciences 11 18%
Medicine and Dentistry 10 16%
Psychology 5 8%
Nursing and Health Professions 4 7%
Agricultural and Biological Sciences 3 5%
Other 10 16%
Unknown 18 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 15 April 2020.
All research outputs
#2,149,706
of 24,820,264 outputs
Outputs from Frontiers in Public Health
#966
of 13,128 outputs
Outputs of similar age
#42,433
of 430,709 outputs
Outputs of similar age from Frontiers in Public Health
#10
of 66 outputs
Altmetric has tracked 24,820,264 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,128 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one has done particularly well, scoring higher than 92% 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 430,709 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 90% of its contemporaries.
We're also able to compare this research output to 66 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.