| Title |
Predicting the clinical outcome of stimulant medication in pediatric attention-deficit/hyperactivity disorder: data from quantitative electroencephalography, event-related potentials, and a go/no-go test
|
|---|---|
| Published in |
Neuropsychiatric Disease and Treatment, February 2014
|
| DOI | 10.2147/ndt.s56600 |
| Pubmed ID | |
| Authors |
Geir Ogrim, Juri Kropotov, Jan Ferenc Brunner, Gian Candrian, Leiv Sandvik, Knut A Hestad |
| Abstract |
We searched for predictors of the clinical outcome of stimulant medication in pediatric attention-deficit/hyperactivity disorder (ADHD), emphasizing variables from quantitative electroencephalography, event-related potentials (ERPs), and behavioral data from a visual go/no-go test. |
X Demographics
The data shown below were collected from the profiles of 6 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 States | 1 | 17% |
| Unknown | 5 | 83% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 4 | 67% |
| Science communicators (journalists, bloggers, editors) | 1 | 17% |
| Members of the public | 1 | 17% |
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 States | 2 | 1% |
| Russia | 1 | <1% |
| Australia | 1 | <1% |
| Brazil | 1 | <1% |
| Unknown | 131 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 23 | 17% |
| Student > Bachelor | 17 | 13% |
| Student > Ph. D. Student | 16 | 12% |
| Student > Master | 14 | 10% |
| Student > Doctoral Student | 8 | 6% |
| Other | 25 | 18% |
| Unknown | 33 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 38 | 28% |
| Medicine and Dentistry | 16 | 12% |
| Neuroscience | 15 | 11% |
| Engineering | 5 | 4% |
| Computer Science | 4 | 3% |
| Other | 17 | 13% |
| Unknown | 41 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 13 February 2018.
All research outputs
#3,401,630
of 25,371,288 outputs
Outputs from Neuropsychiatric Disease and Treatment
#489
of 3,132 outputs
Outputs of similar age
#38,836
of 322,717 outputs
Outputs of similar age from Neuropsychiatric Disease and Treatment
#5
of 58 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,132 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one has done well, scoring higher than 84% 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 322,717 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 87% of its contemporaries.
We're also able to compare this research output to 58 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 91% of its contemporaries.