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Lifestyle predictors of depression and anxiety during COVID-19: a machine learning approach

Overview of attention for article published in Trends in Psychiatry and Psychotherapy, January 2022
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About this Attention Score

  • Among the highest-scoring outputs from this source (#40 of 208)
  • Good Attention Score compared to outputs of the same age (70th percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

Mentioned by

twitter
7 X users

Readers on

mendeley
76 Mendeley
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Title
Lifestyle predictors of depression and anxiety during COVID-19: a machine learning approach
Published in
Trends in Psychiatry and Psychotherapy, January 2022
DOI 10.47626/2237-6089-2021-0365
Pubmed ID
Authors

Mario Simjanoski, Pedro L. Ballester, Jurema Corrêa da Mota, Raquel B. De Boni, Vicent Balanzá-Martínez, Beatriz Atienza-Carbonell, Francisco I. Bastos, Benicio N. Frey, Luciano Minuzzi, Taiane de Azevedo Cardoso, Flavio Kapczinski

Timeline

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X Demographics

X Demographics

The data shown below were collected from the profiles of 7 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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 76 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 76 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 12 16%
Researcher 8 11%
Student > Bachelor 5 7%
Student > Master 4 5%
Student > Ph. D. Student 3 4%
Other 8 11%
Unknown 36 47%
Readers by discipline Count As %
Unspecified 12 16%
Medicine and Dentistry 10 13%
Computer Science 4 5%
Psychology 4 5%
Nursing and Health Professions 3 4%
Other 6 8%
Unknown 37 49%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 April 2022.
All research outputs
#7,105,733
of 25,145,981 outputs
Outputs from Trends in Psychiatry and Psychotherapy
#40
of 208 outputs
Outputs of similar age
#150,904
of 515,949 outputs
Outputs of similar age from Trends in Psychiatry and Psychotherapy
#5
of 22 outputs
Altmetric has tracked 25,145,981 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 208 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. 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 515,949 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
We're also able to compare this research output to 22 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.