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Depression sum-scores don’t add up: why analyzing specific depression symptoms is essential

Overview of attention for article published in BMC Medicine, April 2015
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)

Mentioned by

twitter
86 tweeters
facebook
3 Facebook pages
googleplus
1 Google+ user

Citations

dimensions_citation
215 Dimensions

Readers on

mendeley
489 Mendeley
citeulike
1 CiteULike
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Title
Depression sum-scores don’t add up: why analyzing specific depression symptoms is essential
Published in
BMC Medicine, April 2015
DOI 10.1186/s12916-015-0325-4
Pubmed ID
Authors

Eiko I Fried, Randolph M Nesse

Abstract

Most measures of depression severity are based on the number of reported symptoms, and threshold scores are often used to classify individuals as healthy or depressed. This method - and research results based on it - are valid if depression is a single condition, and all symptoms are equally good severity indicators. Here, we review a host of studies documenting that specific depressive symptoms like sad mood, insomnia, concentration problems, and suicidal ideation are distinct phenomena that differ from each other in important dimensions such as underlying biology, impact on impairment, and risk factors. Furthermore, specific life events predict increases in particular depression symptoms, and there is evidence for direct causal links among symptoms. We suggest that the pervasive use of sum-scores to estimate depression severity has obfuscated crucial insights and contributed to the lack of progress in key research areas such as identifying biomarkers and more efficacious antidepressants. The analysis of individual symptoms and their causal associations offers a way forward. We offer specific suggestions with practical implications for future research.

Twitter Demographics

The data shown below were collected from the profiles of 86 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 489 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 <1%
Belgium 1 <1%
Canada 1 <1%
Netherlands 1 <1%
Spain 1 <1%
Switzerland 1 <1%
Poland 1 <1%
Unknown 479 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 105 21%
Researcher 81 17%
Student > Master 79 16%
Student > Bachelor 67 14%
Student > Doctoral Student 35 7%
Other 63 13%
Unknown 59 12%
Readers by discipline Count As %
Psychology 218 45%
Medicine and Dentistry 65 13%
Neuroscience 29 6%
Social Sciences 21 4%
Agricultural and Biological Sciences 12 2%
Other 51 10%
Unknown 93 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 52. 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 01 September 2020.
All research outputs
#439,410
of 15,965,216 outputs
Outputs from BMC Medicine
#355
of 2,491 outputs
Outputs of similar age
#8,078
of 228,423 outputs
Outputs of similar age from BMC Medicine
#1
of 1 outputs
Altmetric has tracked 15,965,216 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,491 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 37.3. This one has done well, scoring higher than 85% 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 228,423 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 96% 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