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Barriers and enablers to delivery of the Healthy Kids Check: an analysis informed by the Theoretical Domains Framework and COM-B model

Overview of attention for article published in Implementation Science, May 2014
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (61st percentile)

Mentioned by

twitter
4 tweeters

Citations

dimensions_citation
90 Dimensions

Readers on

mendeley
227 Mendeley
citeulike
1 CiteULike
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Title
Barriers and enablers to delivery of the Healthy Kids Check: an analysis informed by the Theoretical Domains Framework and COM-B model
Published in
Implementation Science, May 2014
DOI 10.1186/1748-5908-9-60
Pubmed ID
Authors

Karyn E Alexander, Bianca Brijnath, Danielle Mazza

Abstract

More than a fifth of Australian children arrive at school developmentally vulnerable. To counteract this, the Healthy Kids Check (HKC), a one-off health assessment aimed at preschool children, was introduced in 2008 into Australian general practice. Delivery of services has, however, remained low. The Theoretical Domains Framework, which provides a method to understand behaviours theoretically, can be condensed into three core components: capability, opportunity and motivation, and the COM-B model. Utilising this system, this study aimed to determine the barriers and enablers to delivery of the HKC, to inform the design of an intervention to promote provision of HKC services in Australian general practice.

Twitter Demographics

The data shown below were collected from the profiles of 4 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 227 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 <1%
Australia 1 <1%
Canada 1 <1%
Unknown 223 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 59 26%
Student > Ph. D. Student 48 21%
Researcher 29 13%
Student > Bachelor 20 9%
Student > Postgraduate 10 4%
Other 29 13%
Unknown 32 14%
Readers by discipline Count As %
Psychology 53 23%
Medicine and Dentistry 36 16%
Nursing and Health Professions 32 14%
Social Sciences 24 11%
Agricultural and Biological Sciences 7 3%
Other 31 14%
Unknown 44 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 02 June 2014.
All research outputs
#6,060,480
of 11,344,222 outputs
Outputs from Implementation Science
#936
of 1,201 outputs
Outputs of similar age
#69,047
of 183,857 outputs
Outputs of similar age from Implementation Science
#36
of 41 outputs
Altmetric has tracked 11,344,222 research outputs across all sources so far. This one is in the 46th percentile – i.e., 46% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,201 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.9. This one is in the 21st percentile – i.e., 21% 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 183,857 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.
We're also able to compare this research output to 41 others from the same source and published within six weeks on either side of this one. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.