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Evaluating and selecting mobile health apps: strategies for healthcare providers and healthcare organizations

Overview of attention for article published in Translational Behavioral Medicine, September 2014
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#16 of 475)
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

blogs
1 blog
twitter
52 tweeters
facebook
3 Facebook pages

Citations

dimensions_citation
74 Dimensions

Readers on

mendeley
297 Mendeley
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Title
Evaluating and selecting mobile health apps: strategies for healthcare providers and healthcare organizations
Published in
Translational Behavioral Medicine, September 2014
DOI 10.1007/s13142-014-0293-9
Pubmed ID
Authors

Edwin D Boudreaux, Molly E Waring, Rashelle B Hayes, Rajani S Sadasivam, Sean Mullen, Sherry Pagoto, Boudreaux ED, Waring ME, Hayes RB, Sadasivam RS, Mullen S, Pagoto S, Boudreaux, Edwin D, Waring, Molly E, Hayes, Rashelle B, Sadasivam, Rajani S, Mullen, Sean, Pagoto, Sherry

Abstract

Mobile applications (apps) to improve health are proliferating, but before healthcare providers or organizations can recommend an app to the patients they serve, they need to be confident the app will be user-friendly and helpful for the target disease or behavior. This paper summarizes seven strategies for evaluating and selecting health-related apps: (1) Review the scientific literature, (2) Search app clearinghouse websites, (3) Search app stores, (4) Review app descriptions, user ratings, and reviews, (5) Conduct a social media query within professional and, if available, patient networks, (6) Pilot the apps, and (7) Elicit feedback from patients. The paper concludes with an illustrative case example. Because of the enormous range of quality among apps, strategies for evaluating them will be necessary for adoption to occur in a way that aligns with core values in healthcare, such as the Hippocratic principles of nonmaleficence and beneficence.

Twitter Demographics

The data shown below were collected from the profiles of 52 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 297 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 <1%
Portugal 1 <1%
Brazil 1 <1%
United Kingdom 1 <1%
Hungary 1 <1%
Turkey 1 <1%
Netherlands 1 <1%
Unknown 289 97%

Demographic breakdown

Readers by professional status Count As %
Student > Master 74 25%
Student > Ph. D. Student 53 18%
Student > Bachelor 42 14%
Researcher 35 12%
Student > Doctoral Student 19 6%
Other 74 25%
Readers by discipline Count As %
Computer Science 63 21%
Medicine and Dentistry 60 20%
Psychology 33 11%
Unspecified 31 10%
Nursing and Health Professions 29 10%
Other 81 27%

Attention Score in Context

This research output has an Altmetric Attention Score of 44. 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 18 July 2018.
All research outputs
#310,969
of 11,993,883 outputs
Outputs from Translational Behavioral Medicine
#16
of 475 outputs
Outputs of similar age
#6,991
of 211,208 outputs
Outputs of similar age from Translational Behavioral Medicine
#1
of 23 outputs
Altmetric has tracked 11,993,883 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 475 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.9. This one has done particularly well, scoring higher than 96% 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 211,208 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 23 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.