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There is more to mental illness than negative affect: comprehensive temperament profiles in depression and generalized anxiety

Overview of attention for article published in BMC Psychiatry, May 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)

Mentioned by

blogs
1 blog
twitter
2 tweeters
facebook
1 Facebook page
wikipedia
6 Wikipedia pages

Citations

dimensions_citation
13 Dimensions

Readers on

mendeley
38 Mendeley
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Title
There is more to mental illness than negative affect: comprehensive temperament profiles in depression and generalized anxiety
Published in
BMC Psychiatry, May 2018
DOI 10.1186/s12888-018-1695-x
Pubmed ID
Authors

Irina Trofimova, William Sulis

Abstract

Temperament and mental illness are thought to represent varying degrees along the same continuum of neurotransmitter imbalances. A taxonomy of temperament could provide the basis for a new taxonomy of mental illness. Most popular models of temperament, being based heavily on emotionality traits, show very poor ability to discriminate between mental disorders. The main goal of this study was to examine whether a temperament model based on modern neurophysiology and possessing an extensive set of non-emotionality traits provides better discrimination between Major Depression (MD), Generalized Anxiety (GAD) and Comorbid MD and GAD, in comparison to emotionality-based temperament models. Using the Structure of Temperament Questionnaire, the temperament profiles of 687 individuals (396 clients of private psychiatric and psychological practice, and 291 control subjects) were compared across four adult age groups (18-24, 25-45, 46-65, 66-84). MD and GAD appear to be accurately distinguished by the traits of Motor Endurance and Motor Tempo (much lower values in depression), and Neuroticism (much higher value in anxiety). Comorbids can be distinguished based on a significant decrease in the traits of Plasticity, Intellectual Endurance, Sensitivity to Probabilities, and increased Impulsivity. These effects seemed independent of age and gender. The results suggest the benefits of including non-emotionality-related traits and the usefulness of a functional approach to both taxonomy of temperament and classification of mental disorders.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 38 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 18%
Student > Master 6 16%
Student > Ph. D. Student 5 13%
Student > Doctoral Student 4 11%
Professor > Associate Professor 3 8%
Other 8 21%
Unknown 5 13%
Readers by discipline Count As %
Psychology 9 24%
Medicine and Dentistry 7 18%
Social Sciences 4 11%
Biochemistry, Genetics and Molecular Biology 3 8%
Neuroscience 2 5%
Other 6 16%
Unknown 7 18%

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 28 October 2019.
All research outputs
#1,767,416
of 16,101,505 outputs
Outputs from BMC Psychiatry
#686
of 3,603 outputs
Outputs of similar age
#48,397
of 280,928 outputs
Outputs of similar age from BMC Psychiatry
#1
of 1 outputs
Altmetric has tracked 16,101,505 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,603 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one has done well, scoring higher than 80% 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 280,928 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 82% of its contemporaries.
We're also able to compare this research output to 1 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