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Using willingness-to-pay to establish patient preferences for cancer testing in primary care

Overview of attention for article published in BMC Medical Informatics and Decision Making, August 2016
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (64th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

Mentioned by

twitter
5 tweeters

Citations

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1 Dimensions

Readers on

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35 Mendeley
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Title
Using willingness-to-pay to establish patient preferences for cancer testing in primary care
Published in
BMC Medical Informatics and Decision Making, August 2016
DOI 10.1186/s12911-016-0345-9
Pubmed ID
Authors

Sandra Hollinghurst, Jonathan Banks, Lin Bigwood, Fiona M. Walter, Willie Hamilton, Tim J. Peters

Abstract

Shared decision making is a stated aim of several healthcare systems. In the area of cancer, patients' views have informed policy on screening and treatment but there is little information about their views on diagnostic testing in relation to symptom severity. We used the technique of willingness-to-pay to determine public preferences around diagnostic testing for colorectal, lung, and pancreatic cancer in primary care in the UK. Participants were approached in general practice waiting rooms and asked to complete a two-stage electronic survey that described symptoms of cancer, the likelihood that the symptoms indicate cancer, and information about the appropriate diagnostic test. Part 1 asked for a binary response (yes/no) as to whether they would choose to have a test if it were offered. Part 2 elicited willingness-to-pay values of the tests using a payment scale followed by a bidding exercise, with the aim that these values would provide a strength of preference not detectable using the binary approach. A large majority of participants chose to be tested for all cancers, with only colonoscopy (colorectal cancer) demonstrating a risk gradient. In the willingness-to-pay exercise participants placed a lower value on an X-ray (lung cancer) than the tests for colorectal or pancreatic cancer and X-ray was the only test where risk was clearly related to the willingness-to-pay value. Willingness-to-pay values did not enhance the binary responses in the way intended; participants appeared to be motivated differently when responding to the two parts of the questionnaire. More work is needed to understand how participants perceive risk in this context and how they respond to questions about willingness-to-pay. Qualitative methods could provide useful insights.

Twitter Demographics

The data shown below were collected from the profiles of 5 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 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 35 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 7 20%
Student > Master 7 20%
Researcher 6 17%
Student > Ph. D. Student 5 14%
Other 2 6%
Other 8 23%
Readers by discipline Count As %
Unspecified 12 34%
Medicine and Dentistry 10 29%
Nursing and Health Professions 5 14%
Social Sciences 2 6%
Economics, Econometrics and Finance 2 6%
Other 4 11%

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 17 August 2016.
All research outputs
#6,080,329
of 12,057,012 outputs
Outputs from BMC Medical Informatics and Decision Making
#468
of 1,079 outputs
Outputs of similar age
#94,546
of 266,075 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#16
of 39 outputs
Altmetric has tracked 12,057,012 research outputs across all sources so far. This one is in the 49th percentile – i.e., 49% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,079 research outputs from this source. They receive a mean Attention Score of 4.9. This one has gotten more attention than average, scoring higher than 56% 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 266,075 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 64% of its contemporaries.
We're also able to compare this research output to 39 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 58% of its contemporaries.