Title |
A regret theory approach to decision curve analysis: A novel method for eliciting decision makers' preferences and decision-making
|
---|---|
Published in |
BMC Medical Informatics and Decision Making, September 2010
|
DOI | 10.1186/1472-6947-10-51 |
Pubmed ID | |
Authors |
Athanasios Tsalatsanis, Iztok Hozo, Andrew Vickers, Benjamin Djulbegovic |
Abstract |
Decision curve analysis (DCA) has been proposed as an alternative method for evaluation of diagnostic tests, prediction models, and molecular markers. However, DCA is based on expected utility theory, which has been routinely violated by decision makers. Decision-making is governed by intuition (system 1), and analytical, deliberative process (system 2), thus, rational decision-making should reflect both formal principles of rationality and intuition about good decisions. We use the cognitive emotion of regret to serve as a link between systems 1 and 2 and to reformulate DCA. |
X Demographics
The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 3 | 43% |
Belgium | 1 | 14% |
Ecuador | 1 | 14% |
India | 1 | 14% |
United Kingdom | 1 | 14% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 3 | 43% |
Practitioners (doctors, other healthcare professionals) | 2 | 29% |
Scientists | 2 | 29% |
Mendeley readers
The data shown below were compiled from readership statistics for 107 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 3 | 3% |
Italy | 1 | <1% |
Vietnam | 1 | <1% |
Hungary | 1 | <1% |
Brazil | 1 | <1% |
Ecuador | 1 | <1% |
United Kingdom | 1 | <1% |
India | 1 | <1% |
Unknown | 97 | 91% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 22 | 21% |
Student > Ph. D. Student | 19 | 18% |
Student > Master | 12 | 11% |
Student > Doctoral Student | 9 | 8% |
Professor | 9 | 8% |
Other | 28 | 26% |
Unknown | 8 | 7% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 39 | 36% |
Engineering | 10 | 9% |
Psychology | 10 | 9% |
Computer Science | 8 | 7% |
Business, Management and Accounting | 7 | 7% |
Other | 20 | 19% |
Unknown | 13 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 12 June 2023.
All research outputs
#7,149,194
of 23,852,694 outputs
Outputs from BMC Medical Informatics and Decision Making
#671
of 2,046 outputs
Outputs of similar age
#29,757
of 87,689 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#8
of 15 outputs
Altmetric has tracked 23,852,694 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 2,046 research outputs from this source. They receive a mean Attention Score of 5.0. This one has gotten more attention than average, scoring higher than 66% 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 87,689 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 65% of its contemporaries.
We're also able to compare this research output to 15 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 53% of its contemporaries.