| Title |
Building new computational models to support health behavior change and maintenance: new opportunities in behavioral research
|
|---|---|
| Published in |
Translational Behavioral Medicine, May 2015
|
| DOI | 10.1007/s13142-015-0324-1 |
| Pubmed ID | |
| Authors |
Donna Spruijt-Metz, Eric Hekler, Niilo Saranummi, Stephen Intille, Ilkka Korhonen, Wendy Nilsen, Daniel E. Rivera, Bonnie Spring, Susan Michie, David A. Asch, Alberto Sanna, Vicente Traver Salcedo, Rita Kukakfa, Misha Pavel |
X Demographics
The data shown below were collected from the profiles of 24 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 | 7 | 29% |
| Spain | 4 | 17% |
| Ireland | 1 | 4% |
| Canada | 1 | 4% |
| Unknown | 11 | 46% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 14 | 58% |
| Scientists | 5 | 21% |
| Practitioners (doctors, other healthcare professionals) | 5 | 21% |
Mendeley readers
The data shown below were compiled from readership statistics for 257 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 5 | 2% |
| United States | 2 | <1% |
| Sweden | 1 | <1% |
| Unknown | 249 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 66 | 26% |
| Researcher | 45 | 18% |
| Student > Master | 27 | 11% |
| Student > Doctoral Student | 20 | 8% |
| Other | 17 | 7% |
| Other | 39 | 15% |
| Unknown | 43 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 51 | 20% |
| Psychology | 50 | 19% |
| Medicine and Dentistry | 23 | 9% |
| Social Sciences | 22 | 9% |
| Nursing and Health Professions | 12 | 5% |
| Other | 36 | 14% |
| Unknown | 63 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 18. 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 03 October 2016.
All research outputs
#2,114,062
of 25,998,826 outputs
Outputs from Translational Behavioral Medicine
#113
of 1,094 outputs
Outputs of similar age
#26,123
of 283,691 outputs
Outputs of similar age from Translational Behavioral Medicine
#2
of 14 outputs
Altmetric has tracked 25,998,826 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 1,094 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.0. This one has done well, scoring higher than 89% 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 283,691 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 90% of its contemporaries.
We're also able to compare this research output to 14 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.