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X Demographics
Mendeley readers
Attention Score in Context
| Title |
How do physicians decide to treat: an empirical evaluation of the threshold model
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, June 2014
|
| DOI | 10.1186/1472-6947-14-47 |
| Pubmed ID | |
| Authors |
Benjamin Djulbegovic, Shira Elqayam, Tea Reljic, Iztok Hozo, Branko Miladinovic, Athanasios Tsalatsanis, Ambuj Kumar, Jason Beckstead, Stephanie Taylor, Janice Cannon-Bowers |
| Abstract |
According to the threshold model, when faced with a decision under diagnostic uncertainty, physicians should administer treatment if the probability of disease is above a specified threshold and withhold treatment otherwise. The objectives of the present study are to a) evaluate if physicians act according to a threshold model, b) examine which of the existing threshold models [expected utility theory model (EUT), regret-based threshold model, or dual-processing theory] explains the physicians' decision-making best. |
X Demographics
The data shown below were collected from the profiles of 9 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 Kingdom | 2 | 22% |
| New Zealand | 1 | 11% |
| Australia | 1 | 11% |
| India | 1 | 11% |
| Unknown | 4 | 44% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 44% |
| Scientists | 3 | 33% |
| Practitioners (doctors, other healthcare professionals) | 2 | 22% |
Mendeley readers
The data shown below were compiled from readership statistics for 136 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 5 | 4% |
| United States | 1 | <1% |
| France | 1 | <1% |
| Canada | 1 | <1% |
| Unknown | 128 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 29 | 21% |
| Student > Ph. D. Student | 25 | 18% |
| Student > Master | 17 | 13% |
| Student > Bachelor | 13 | 10% |
| Professor | 8 | 6% |
| Other | 32 | 24% |
| Unknown | 12 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 35 | 26% |
| Psychology | 27 | 20% |
| Social Sciences | 9 | 7% |
| Economics, Econometrics and Finance | 8 | 6% |
| Nursing and Health Professions | 7 | 5% |
| Other | 30 | 22% |
| Unknown | 20 | 15% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 26 September 2016.
All research outputs
#5,707,840
of 22,757,090 outputs
Outputs from BMC Medical Informatics and Decision Making
#505
of 1,985 outputs
Outputs of similar age
#53,486
of 228,027 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#5
of 23 outputs
Altmetric has tracked 22,757,090 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 1,985 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 74% 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 228,027 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 76% of its contemporaries.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.