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A tailored, interactive health communication application for patients with type 2 diabetes: study protocol of a randomised controlled trial

Overview of attention for article published in BMC Medical Informatics and Decision Making, February 2013
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2 X users

Citations

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15 Dimensions

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187 Mendeley
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Title
A tailored, interactive health communication application for patients with type 2 diabetes: study protocol of a randomised controlled trial
Published in
BMC Medical Informatics and Decision Making, February 2013
DOI 10.1186/1472-6947-13-24
Pubmed ID
Authors

Nina Weymann, Martin Härter, Jörg Dirmaier

Abstract

Type 2 diabetes is an increasingly common chronic condition whose prognosis can be improved by patient involvement and self-management. Patient involvement can be fostered by web-based Interactive Health Communication Applications (IHCAs) combining health information with decision support, social support and/or behaviour change support. They reach great numbers of patients at low cost and provide high-quality information and support at the time, place and learning speed patients prefer. Still, online tools often suffer from high attrition. Tailoring content and tone of IHCAs to the individual patient´s needs might improve their effectiveness. This study aims to test the effectiveness and usage of a tailored IHCA combining health information with decision support and behaviour change support for patients with type 2 diabetes.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 187 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 2 1%
United States 2 1%
Denmark 1 <1%
Australia 1 <1%
Unknown 181 97%

Demographic breakdown

Readers by professional status Count As %
Student > Master 41 22%
Student > Ph. D. Student 31 17%
Student > Bachelor 21 11%
Student > Doctoral Student 12 6%
Researcher 11 6%
Other 31 17%
Unknown 40 21%
Readers by discipline Count As %
Medicine and Dentistry 47 25%
Nursing and Health Professions 23 12%
Social Sciences 17 9%
Psychology 11 6%
Computer Science 7 4%
Other 30 16%
Unknown 52 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 06 August 2013.
All research outputs
#15,263,666
of 22,696,971 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,306
of 1,980 outputs
Outputs of similar age
#185,258
of 287,582 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#36
of 39 outputs
Altmetric has tracked 22,696,971 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,980 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 24th percentile – i.e., 24% of its peers scored the same or lower than it.
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 287,582 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 39 others from the same source and published within six weeks on either side of this one. This one is in the 5th percentile – i.e., 5% of its contemporaries scored the same or lower than it.