The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Latent Impulsivity Subtypes in Substance Use Disorders and Interactions with Internalizing and Externalizing Co-Occurring Disorders
|
|---|---|
| Published in |
Frontiers in Psychiatry, February 2018
|
| DOI | 10.3389/fpsyt.2018.00027 |
| Pubmed ID | |
| Authors |
Rodrigo Marín-Navarrete, Aldebarán Toledo-Fernández, Luis Villalobos-Gallegos, Carlos Roncero, Nestor Szerman, María Elena Medina-Mora |
| Abstract |
This study explored the clinical importance of latent impulsivity subtypes within a sample of individuals with substance use disorders (SUDs) and high rates of co-occurring disorders (CODs) receiving residential treatment, aiming to assess the heterogeneity of the associations between SUDs and CODs across such impulsivity subtypes. The abbreviated Barratt impulsiveness scale was used to assess motor and cognitive (attentional and nonplanning) impulsivity, a structured interview for diagnosis of SUD and CODs, and other clinimetric measures for severity of substance use. Latent class analysis was conducted to extract subgroups of impulsivity subtypes and Poisson regression to analyze effects of interactions of classes by CODs on severity of substance use. 568 participants were evaluated. Results featured a four-class model as the best-fitted solution: overall high impulsivity (OHI); overall low impulsivity; high cognitive-low motor impulsivity; and moderate cognitive-low motor impulsivity (MC-LMI). OHI and MC-LMI concentrated on most of the individuals with CODs, and individuals within OHI and MC-LMI showed more severity of substance use. The expression of this severity relative to the impulsivity subtypes was modified by their interaction with internalizing and externalizing CODs in very heterogeneous ways. Our findings suggest that knowing either the presence of trait-based subtypes or CODs in individuals with SUDs is not enough to characterize clinical outcomes, and that the analysis of interactions between psychiatric categories and behavioral traits is necessary to better understand the expressions of psychiatric disorders. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 40% |
| Unknown | 3 | 60% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 60 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 8 | 13% |
| Other | 6 | 10% |
| Student > Postgraduate | 6 | 10% |
| Student > Ph. D. Student | 6 | 10% |
| Student > Doctoral Student | 5 | 8% |
| Other | 11 | 18% |
| Unknown | 18 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 18 | 30% |
| Medicine and Dentistry | 12 | 20% |
| Neuroscience | 3 | 5% |
| Social Sciences | 1 | 2% |
| Biochemistry, Genetics and Molecular Biology | 1 | 2% |
| Other | 2 | 3% |
| Unknown | 23 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 23 March 2018.
All research outputs
#3,900,481
of 26,367,306 outputs
Outputs from Frontiers in Psychiatry
#2,387
of 13,087 outputs
Outputs of similar age
#82,978
of 457,792 outputs
Outputs of similar age from Frontiers in Psychiatry
#42
of 119 outputs
Altmetric has tracked 26,367,306 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,087 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.6. 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 457,792 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 81% of its contemporaries.
We're also able to compare this research output to 119 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.