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Using a mobile health application to support self-management in chronic obstructive pulmonary disease: a six-month cohort study

Overview of attention for article published in BMC Medical Informatics and Decision Making, June 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (88th percentile)

Mentioned by

twitter
20 tweeters

Citations

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59 Dimensions

Readers on

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32 Mendeley
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Title
Using a mobile health application to support self-management in chronic obstructive pulmonary disease: a six-month cohort study
Published in
BMC Medical Informatics and Decision Making, June 2015
DOI 10.1186/s12911-015-0171-5
Pubmed ID
Authors

Maxine Hardinge, Heather Rutter, Carmelo Velardo, Syed Ahmar Shah, Veronika Williams, Lionel Tarassenko, Andrew Farmer

Abstract

Self-management strategies have the potential to support patients with chronic obstructive pulmonary disease (COPD). Telehealth interventions may have a role in delivering this support along with the opportunity to monitor symptoms and physiological variables. This paper reports findings from a six-month, clinical, cohort study of COPD patients' use of a mobile telehealth based (mHealth) application and how individually determined alerts in oxygen saturation levels, pulse rate and symptoms scores related to patient self-initiated treatment for exacerbations. The development of the mHealth intervention involved a patient focus group and multidisciplinary team of researchers, engineers and clinicians. Individual data thresholds to set alerts were determined, and the relationship to exacerbations, defined by the initiation of stand-by medications, was measured. The sample comprised 18 patients (age range of 50-85 years) with varied levels of computer skills. Patients identified no difficulties in using the mHealth application and used all functions available. 40 % of exacerbations had an alert signal during the three days prior to a patient starting medication. Patients were able to use the mHealth application to support self- management, including monitoring of clinical data. Within three months, 95 % of symptom reporting sessions were completed in less than 100 s. Home based, unassisted, daily use of the mHealth platform is feasible and acceptable to people with COPD for reporting daily symptoms and medicine use, and to measure physiological variables such as pulse rate and oxygen saturation. These findings provide evidence for integrating telehealth interventions with clinical care pathways to support self-management in COPD.

Twitter Demographics

The data shown below were collected from the profiles of 20 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 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 32 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 28%
Student > Master 5 16%
Researcher 4 13%
Student > Bachelor 4 13%
Professor > Associate Professor 2 6%
Other 3 9%
Unknown 5 16%
Readers by discipline Count As %
Medicine and Dentistry 6 19%
Nursing and Health Professions 4 13%
Computer Science 4 13%
Social Sciences 3 9%
Agricultural and Biological Sciences 2 6%
Other 8 25%
Unknown 5 16%

Attention Score in Context

This research output has an Altmetric Attention Score of 13. 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 08 February 2016.
All research outputs
#1,397,088
of 14,568,969 outputs
Outputs from BMC Medical Informatics and Decision Making
#116
of 1,336 outputs
Outputs of similar age
#26,964
of 231,020 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#1
of 1 outputs
Altmetric has tracked 14,568,969 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,336 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. 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 231,020 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 88% 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