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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Development and preliminary user testing of the DCIDA (Dynamic computer interactive decision application) for ‘nudging’ patients towards high quality decisions
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, August 2014
|
| DOI | 10.1186/1472-6947-14-62 |
| Pubmed ID | |
| Authors |
Nick Bansback, Linda C Li, Larry Lynd, Stirling Bryan |
| Abstract |
Patient decision aids (PtDA) are developed to facilitate informed, value-based decisions about health. Research suggests that even when informed with necessary evidence and information, cognitive errors can prevent patients from choosing the option that is most congruent with their own values. We sought to utilize principles of behavioural economics to develop a computer application that presents information from conventional decision aids in a way that reduces these errors, subsequently promoting higher quality decisions. |
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 % |
|---|---|---|
| Canada | 2 | 29% |
| India | 2 | 29% |
| Unknown | 3 | 43% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 86% |
| Practitioners (doctors, other healthcare professionals) | 1 | 14% |
Mendeley readers
The data shown below were compiled from readership statistics for 88 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 3 | 3% |
| Unknown | 85 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 16 | 18% |
| Researcher | 13 | 15% |
| Student > Bachelor | 10 | 11% |
| Student > Master | 9 | 10% |
| Other | 7 | 8% |
| Other | 19 | 22% |
| Unknown | 14 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 14 | 16% |
| Medicine and Dentistry | 9 | 10% |
| Social Sciences | 9 | 10% |
| Psychology | 7 | 8% |
| Engineering | 7 | 8% |
| Other | 24 | 27% |
| Unknown | 18 | 20% |
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 17 January 2016.
All research outputs
#5,708,288
of 22,759,618 outputs
Outputs from BMC Medical Informatics and Decision Making
#504
of 1,985 outputs
Outputs of similar age
#53,271
of 229,519 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#7
of 30 outputs
Altmetric has tracked 22,759,618 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 229,519 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 30 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.