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Mendeley readers
Attention Score in Context
Title |
Dual processing model of medical decision-making
|
---|---|
Published in |
BMC Medical Informatics and Decision Making, September 2012
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DOI | 10.1186/1472-6947-12-94 |
Pubmed ID | |
Authors |
Benjamin Djulbegovic, Iztok Hozo, Jason Beckstead, Athanasios Tsalatsanis, Stephen G Pauker |
Abstract |
Dual processing theory of human cognition postulates that reasoning and decision-making can be described as a function of both an intuitive, experiential, affective system (system I) and/or an analytical, deliberative (system II) processing system. To date no formal descriptive model of medical decision-making based on dual processing theory has been developed. Here we postulate such a model and apply it to a common clinical situation: whether treatment should be administered to the patient who may or may not have a disease. |
X Demographics
The data shown below were collected from the profiles of 10 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
India | 2 | 20% |
United Kingdom | 2 | 20% |
United States | 1 | 10% |
Australia | 1 | 10% |
Unknown | 4 | 40% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 6 | 60% |
Practitioners (doctors, other healthcare professionals) | 3 | 30% |
Science communicators (journalists, bloggers, editors) | 1 | 10% |
Mendeley readers
The data shown below were compiled from readership statistics for 244 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 4 | 2% |
Germany | 2 | <1% |
United States | 2 | <1% |
Mexico | 1 | <1% |
Unknown | 235 | 96% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Bachelor | 37 | 15% |
Student > Master | 34 | 14% |
Researcher | 29 | 12% |
Student > Ph. D. Student | 25 | 10% |
Student > Doctoral Student | 14 | 6% |
Other | 57 | 23% |
Unknown | 48 | 20% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 72 | 30% |
Psychology | 26 | 11% |
Nursing and Health Professions | 25 | 10% |
Computer Science | 10 | 4% |
Social Sciences | 9 | 4% |
Other | 45 | 18% |
Unknown | 57 | 23% |
Attention Score in Context
This research output has an Altmetric Attention Score of 16. 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 09 December 2021.
All research outputs
#2,296,832
of 25,826,146 outputs
Outputs from BMC Medical Informatics and Decision Making
#127
of 2,165 outputs
Outputs of similar age
#14,876
of 188,076 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#3
of 42 outputs
Altmetric has tracked 25,826,146 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,165 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done particularly well, scoring higher than 94% 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 188,076 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 42 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.