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Moving beyond individual choice in policies to reduce health inequalities: the integration of dynamic with individual explanations

Overview of attention for article published in Journal of Public Health, March 2018
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#17 of 1,755)
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

twitter
255 tweeters

Citations

dimensions_citation
8 Dimensions

Readers on

mendeley
48 Mendeley
citeulike
1 CiteULike
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Title
Moving beyond individual choice in policies to reduce health inequalities: the integration of dynamic with individual explanations
Published in
Journal of Public Health, March 2018
DOI 10.1093/pubmed/fdy045
Pubmed ID
Authors

N M Kriznik, A L Kinmonth, T Ling, M P Kelly

Abstract

A strong focus on individual choice and behaviour informs interventions designed to reduce health inequalities in the UK. We review evidence for wider mechanisms from a range of disciplines, demonstrate that they are not yet impacting on programmes, and argue for their systematic inclusion in policy and research. We identified potential mechanisms relevant to health inequalities and their amelioration from different disciplines and analysed six policy documents published between 1976 and 2010 using Bacchi's 'What's the problem represented to be?' framework for policy analysis. We found substantial evidence of supra-individualistic and relational mechanisms relevant to health inequalities from sociology, history, biology, neuroscience, philosophy and psychology. Policy documents sometimes expressed these mechanisms in policy rhetoric but rarely in policy recommendations, which continue to focus on individual behaviour. Current evidence points to the potential of systematically applying broader thinking about causal mechanisms, beyond individual choice and responsibility, to the design, implementation and evaluation of policies to reduce health inequalities. We provide a set of questions designed to enable critique of policy discussions and programmes to ensure that these wider mechanisms are considered.

Twitter Demographics

The data shown below were collected from the profiles of 255 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 48 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 27%
Student > Master 11 23%
Student > Bachelor 5 10%
Student > Ph. D. Student 4 8%
Unspecified 4 8%
Other 11 23%
Readers by discipline Count As %
Unspecified 13 27%
Medicine and Dentistry 11 23%
Social Sciences 10 21%
Nursing and Health Professions 5 10%
Psychology 4 8%
Other 5 10%

Attention Score in Context

This research output has an Altmetric Attention Score of 152. 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 03 February 2019.
All research outputs
#99,795
of 13,902,005 outputs
Outputs from Journal of Public Health
#17
of 1,755 outputs
Outputs of similar age
#4,623
of 276,356 outputs
Outputs of similar age from Journal of Public Health
#1
of 38 outputs
Altmetric has tracked 13,902,005 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,755 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.7. This one has done particularly well, scoring higher than 99% 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 276,356 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 98% of its contemporaries.
We're also able to compare this research output to 38 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 97% of its contemporaries.