| Title |
Modeling the efficacy of persuasive strategies for different gamer types in serious games for health
|
|---|---|
| Published in |
User Modeling and User-Adapted Interaction, July 2014
|
| DOI | 10.1007/s11257-014-9149-8 |
| Authors |
Rita Orji, Julita Vassileva, Regan L. Mandryk |
X Demographics
The data shown below were collected from the profiles of 8 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 | 25% |
| United States | 1 | 13% |
| Spain | 1 | 13% |
| Netherlands | 1 | 13% |
| Unknown | 3 | 38% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 4 | 50% |
| Members of the public | 2 | 25% |
| Practitioners (doctors, other healthcare professionals) | 1 | 13% |
| Science communicators (journalists, bloggers, editors) | 1 | 13% |
Mendeley readers
The data shown below were compiled from readership statistics for 419 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | <1% |
| Austria | 3 | <1% |
| Italy | 2 | <1% |
| Brazil | 2 | <1% |
| Netherlands | 1 | <1% |
| Sweden | 1 | <1% |
| Germany | 1 | <1% |
| Mexico | 1 | <1% |
| Canada | 1 | <1% |
| Other | 2 | <1% |
| Unknown | 401 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 90 | 21% |
| Student > Master | 80 | 19% |
| Student > Bachelor | 52 | 12% |
| Researcher | 33 | 8% |
| Student > Doctoral Student | 26 | 6% |
| Other | 59 | 14% |
| Unknown | 79 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 163 | 39% |
| Psychology | 32 | 8% |
| Social Sciences | 27 | 6% |
| Engineering | 19 | 5% |
| Design | 17 | 4% |
| Other | 62 | 15% |
| Unknown | 99 | 24% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 02 March 2021.
All research outputs
#4,989,161
of 24,229,740 outputs
Outputs from User Modeling and User-Adapted Interaction
#36
of 193 outputs
Outputs of similar age
#46,617
of 231,324 outputs
Outputs of similar age from User Modeling and User-Adapted Interaction
#1
of 2 outputs
Altmetric has tracked 24,229,740 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 193 research outputs from this source. They receive a mean Attention Score of 4.6. This one has done well, scoring higher than 81% 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 231,324 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 79% of its contemporaries.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them