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Implementing a QCancer risk tool into general practice consultations: an exploratory study using simulated consultations with Australian general practitioners

Overview of attention for article published in British Journal of Cancer, March 2015
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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 (87th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

Mentioned by

news
1 news outlet
twitter
4 tweeters

Citations

dimensions_citation
19 Dimensions

Readers on

mendeley
101 Mendeley
Title
Implementing a QCancer risk tool into general practice consultations: an exploratory study using simulated consultations with Australian general practitioners
Published in
British Journal of Cancer, March 2015
DOI 10.1038/bjc.2015.46
Pubmed ID
Authors

P P-C Chiang, D Glance, J Walker, F M Walter, J D Emery

Abstract

Background:Reducing diagnostic delays in primary care by improving the assessment of symptoms associated with cancer could have significant impacts on cancer outcomes. Symptom risk assessment tools could improve the diagnostic assessment of patients with symptoms suggestive of cancer in primary care. We aimed to explore the use of a cancer risk tool, which implements the QCancer model, in consultations and its potential impact on clinical decision making.Methods:We implemented an exploratory 'action design' method with 15 general practitioners (GPs) from Victoria, Australia. General practitioners applied the risk tool in simulated consultations, conducted semi-structured interviews based on the normalisation process theory and explored issues relating to implementation of the tool.Results:The risk tool was perceived as being potentially useful for patients with complex histories. More experienced GPs were distrustful of the risk output, especially when it conflicted with their clinical judgement. Variable interpretation of symptoms meant that there was significant variation in risk assessment. When a risk output was high, GPs were confronted with numerical risk outputs creating challenges in consultation.Conclusions:Significant barriers to implementing electronic cancer risk assessment tools in consultation could limit their uptake. These relate not only to the design and integration of the tool but also to variation in interpretation of clinical histories, and therefore variable risk outputs and strong beliefs in personal clinical intuition.British Journal of Cancer advance online publication, 3 March 2015; doi:10.1038/bjc.2015.46 www.bjcancer.com.

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 101 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
United States 1 <1%
Unknown 99 98%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 35 35%
Researcher 11 11%
Student > Master 11 11%
Unspecified 10 10%
Student > Ph. D. Student 10 10%
Other 24 24%
Readers by discipline Count As %
Medicine and Dentistry 65 64%
Unspecified 12 12%
Nursing and Health Professions 6 6%
Psychology 5 5%
Business, Management and Accounting 3 3%
Other 10 10%

Attention Score in Context

This research output has an Altmetric Attention Score of 13. 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 27 July 2015.
All research outputs
#898,574
of 11,258,663 outputs
Outputs from British Journal of Cancer
#704
of 7,351 outputs
Outputs of similar age
#25,671
of 209,261 outputs
Outputs of similar age from British Journal of Cancer
#53
of 139 outputs
Altmetric has tracked 11,258,663 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,351 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one has done particularly well, scoring higher than 90% 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 209,261 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 87% of its contemporaries.
We're also able to compare this research output to 139 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 61% of its contemporaries.