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Evaluating machine learning-enabled and multimodal data-driven exercise prescriptions for mental health: a randomized controlled trial protocol

Overview of attention for article published in Frontiers in Psychiatry, January 2024
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (55th percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

Mentioned by

twitter
3 X users

Citations

dimensions_citation
3 Dimensions

Readers on

mendeley
45 Mendeley
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Title
Evaluating machine learning-enabled and multimodal data-driven exercise prescriptions for mental health: a randomized controlled trial protocol
Published in
Frontiers in Psychiatry, January 2024
DOI 10.3389/fpsyt.2024.1352420
Pubmed ID
Authors

Miaoqing Tan, Yanning Xiao, Fengshi Jing, Yewei Xie, Sanmei Lu, Mingqiang Xiang, Hao Ren

Timeline

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X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 45 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 8 18%
Student > Bachelor 3 7%
Student > Master 3 7%
Student > Ph. D. Student 2 4%
Other 1 2%
Other 3 7%
Unknown 25 56%
Readers by discipline Count As %
Unspecified 8 18%
Nursing and Health Professions 3 7%
Engineering 2 4%
Sports and Recreations 1 2%
Mathematics 1 2%
Other 2 4%
Unknown 28 62%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 30 January 2024.
All research outputs
#16,206,605
of 26,383,519 outputs
Outputs from Frontiers in Psychiatry
#5,538
of 13,128 outputs
Outputs of similar age
#165,738
of 381,154 outputs
Outputs of similar age from Frontiers in Psychiatry
#153
of 528 outputs
Altmetric has tracked 26,383,519 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,128 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.9. This one has gotten more attention than average, scoring higher than 57% 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 381,154 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 55% of its contemporaries.
We're also able to compare this research output to 528 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 70% of its contemporaries.