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The CRISP colorectal cancer risk prediction tool: an exploratory study using simulated consultations in Australian primary care

Overview of attention for article published in BMC Medical Informatics and Decision Making, January 2017
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (54th percentile)

Mentioned by

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4 tweeters

Citations

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10 Dimensions

Readers on

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86 Mendeley
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Title
The CRISP colorectal cancer risk prediction tool: an exploratory study using simulated consultations in Australian primary care
Published in
BMC Medical Informatics and Decision Making, January 2017
DOI 10.1186/s12911-017-0407-7
Pubmed ID
Authors

Jennifer G Walker, Adrian Bickerstaffe, Nadira Hewabandu, Sanjay Maddumarachchi, James G Dowty, Mark Jenkins, Marie Pirotta, Fiona M Walter, Jon D Emery

Abstract

In Australia, screening for colorectal cancer (CRC) with colonoscopy is meant to be reserved for people at increased risk, however, currently there is a mismatch between individuals' risk of CRC and the type of CRC screening they receive. This paper describes the development and optimisation of a Colorectal cancer RISk Prediction tool ('CRISP') for use in primary care. The aim of the CRISP tool is to increase risk-appropriate CRC screening. CRISP development was informed by previous experience with developing risk tools for use in primary care and a systematic review of the evidence. A CRISP prototype was used in simulated consultations by general practitioners (GPs) with actors as patients. GPs were interviewed to explore their experience of using CRISP, and practice nurses (PNs) and practice managers (PMs) were interviewed after a demonstration of CRISP. Transcribed interviews and video footage of the 'consultations' were qualitatively analyzed. Themes arising from the data were mapped onto Normalization Process Theory (NPT). Fourteen GPs, nine PNs and six PMs were recruited from 12 clinics. Results were described using the four constructs of NPT: 1) Coherence: Clinicians understood the rationale behind CRISP, particularly since they were familiar with using risk tools for other conditions; 2) Cognitive participation: GPs welcomed the opportunity CRISP provided to discuss healthy and unhealthy behaviors with their patients, but many GPs challenged the screening recommendation generated by CRISP; 3) Collective Action: CRISP disrupted clinician-patient flow if the GP was less comfortable with computers. GP consultation time was a major implementation barrier and overall consensus was that PNs have more capacity and time to use CRISP effectively; 4) Reflexive monitoring: Limited systematic monitoring of new interventions is a potential barrier to the sustainable embedding of CRISP. CRISP has the potential to improve risk-appropriate CRC screening in primary care but was considered more likely to be successfully implemented as a nurse-led intervention.

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

Geographical breakdown

Country Count As %
Unknown 86 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 21 24%
Student > Bachelor 10 12%
Student > Master 10 12%
Other 6 7%
Student > Postgraduate 5 6%
Other 13 15%
Unknown 21 24%
Readers by discipline Count As %
Medicine and Dentistry 37 43%
Business, Management and Accounting 3 3%
Nursing and Health Professions 3 3%
Agricultural and Biological Sciences 2 2%
Computer Science 2 2%
Other 12 14%
Unknown 27 31%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 13 November 2018.
All research outputs
#8,558,747
of 15,550,283 outputs
Outputs from BMC Medical Informatics and Decision Making
#720
of 1,410 outputs
Outputs of similar age
#154,929
of 356,722 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#1
of 1 outputs
Altmetric has tracked 15,550,283 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,410 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one is in the 46th percentile – i.e., 46% 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 356,722 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 54% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them