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Patient-centered activity monitoring in the self-management of chronic health conditions

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 (98th percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
twitter
115 X users
facebook
4 Facebook pages
wikipedia
2 Wikipedia pages
googleplus
2 Google+ users

Citations

dimensions_citation
277 Dimensions

Readers on

mendeley
516 Mendeley
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Title
Patient-centered activity monitoring in the self-management of chronic health conditions
Published in
BMC Medicine, April 2015
DOI 10.1186/s12916-015-0319-2
Pubmed ID
Authors

Emil Chiauzzi, Carlos Rodarte, Pronabesh DasMahapatra

Abstract

As activity tracking devices become smaller, cheaper, and more consumer-accessible, they will be used more extensively across a wide variety of contexts. The expansion of activity tracking and personal data collection offers the potential for patient engagement in the management of chronic diseases. Consumer wearable devices for activity tracking have shown promise in post-surgery recovery in cardiac patients, pulmonary rehabilitation, and activity counseling in diabetic patients, among others. Unfortunately, the data generated by wearable devices is seldom integrated into programmatic self-management chronic disease regimens. In addition, there is lack of evidence supporting sustained use or effects on health outcomes, as studies have primarily focused on establishing the feasibility of monitoring activity and the association of measured activity with short-term benefits. Monitoring devices can make a direct and real-time impact on self-management, but the validity and reliability of measurements need to be established. In order for patients to become engaged in wearable data gathering, key patient-centered issues relating to usefulness in care, motivation, the safety and privacy of information, and clinical integration need to be addressed. Because the successful usage of wearables requires an ability to comprehend and utilize personal health data, the user experience should account for individual differences in numeracy skills and apply evidence-based behavioral science principles to promote continued engagement. Activity monitoring has the potential to engage patients as advocates in their personalized care, as well as offer health care providers real world assessments of their patients' daily activity patterns. This potential will be realized as the voice of the chronic disease patients is accounted for in the design of devices, measurements are validated against existing clinical assessments, devices become part of the treatment 'prescription', behavior change programs are used to engage patients in self-management, and best practices for clinical integration are defined.

X Demographics

X Demographics

The data shown below were collected from the profiles of 115 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 516 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 1%
United Kingdom 3 <1%
Austria 1 <1%
Canada 1 <1%
Sweden 1 <1%
Iran, Islamic Republic of 1 <1%
Saudi Arabia 1 <1%
Unknown 502 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 99 19%
Student > Master 91 18%
Researcher 64 12%
Student > Bachelor 54 10%
Student > Doctoral Student 34 7%
Other 84 16%
Unknown 90 17%
Readers by discipline Count As %
Medicine and Dentistry 98 19%
Computer Science 67 13%
Nursing and Health Professions 49 9%
Engineering 33 6%
Social Sciences 29 6%
Other 123 24%
Unknown 117 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 100. 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 24 February 2024.
All research outputs
#424,567
of 25,401,381 outputs
Outputs from BMC Medicine
#326
of 4,012 outputs
Outputs of similar age
#4,848
of 279,973 outputs
Outputs of similar age from BMC Medicine
#12
of 82 outputs
Altmetric has tracked 25,401,381 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,012 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 45.5. This one has done particularly well, scoring higher than 91% 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 279,973 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 98% of its contemporaries.
We're also able to compare this research output to 82 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.