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EMPOWER-support of patient empowerment by an intelligent self-management pathway for patients: study protocol

Overview of attention for article published in BMC Medical Informatics and Decision Making, March 2015
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  • Above-average Attention Score compared to outputs of the same age (53rd percentile)
  • Average Attention Score compared to outputs of the same age and source

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25 Dimensions

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267 Mendeley
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Title
EMPOWER-support of patient empowerment by an intelligent self-management pathway for patients: study protocol
Published in
BMC Medical Informatics and Decision Making, March 2015
DOI 10.1186/s12911-015-0142-x
Pubmed ID
Authors

Sarah Mantwill, Maddalena Fiordelli, Ramona Ludolph, Peter J Schulz

Abstract

Diabetes education together with patient empowerment has shown to be key to effective self-management behavior. When delivered through information and communication technologies (ICT), this solution has shown to lead to better health outcomes. However, the potential of ICT and their integration into the healthcare environment have not yet been fully exploited. ICT should be in particular used to facilitate communication and information exchange between patient and healthcare providers. In addition, systems should include components facilitating behavior change using empowerment approaches such as goal-setting. Funded by the European Commission (FP7-ICT-2011-288209) a web/mobile based platform (EMPOWER) has been developed, which aims at supporting self-management activities of diabetes patients and their treating physicians in Germany and Turkey. The platform semantically integrates multiple information sources, such as electronic and personal health records (EHR/PHR). Patients can register patterns of daily living, record blood glucose levels, design disease management plans and set long- and short-term goals. The project actively involves the treating physician, who has the possibility to set recommendations for the patient and to monitor his/her progress on the platform. In the test-phase of EMPOWER, patients will be assigned to an intervention group and a control group. Data will be collected at baseline and three months after the intervention started. In addition, qualitative interviews will be conducted to collect extra information on usability and usefulness. Outcome measures include amongst others the Problem Areas in Diabetes questionnaire (PAID), the Summary of Diabetes Self-Care Activities and scales evaluating doctor-patient interaction. Physiological parameters, such as physical activity or blood glucose levels will be collected via the platform. Further, log files and number of logins will serve as independent variables. The interplay between multiple sources, including EHR, patients' own registered information and physicians' recommendations on one platform can have important practice implications. It might not only improve self-management activities in diabetes patients but it will also facilitate physician's work, and ultimately the physician patient relationship. The trial has been registered with Deutsches Register Klinischer Studien (German register of clinical trials) under DRKS00007699 on January 30, 2015.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 267 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 2 <1%
United Kingdom 1 <1%
United States 1 <1%
Unknown 263 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 41 15%
Student > Master 41 15%
Student > Ph. D. Student 38 14%
Student > Doctoral Student 20 7%
Student > Bachelor 15 6%
Other 52 19%
Unknown 60 22%
Readers by discipline Count As %
Medicine and Dentistry 57 21%
Nursing and Health Professions 31 12%
Computer Science 26 10%
Social Sciences 20 7%
Psychology 10 4%
Other 42 16%
Unknown 81 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 12 April 2015.
All research outputs
#12,920,756
of 22,797,621 outputs
Outputs from BMC Medical Informatics and Decision Making
#876
of 1,987 outputs
Outputs of similar age
#119,899
of 262,952 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#21
of 35 outputs
Altmetric has tracked 22,797,621 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,987 research outputs from this source. They receive a mean Attention Score of 4.9. This one has gotten more attention than average, scoring higher than 53% 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 262,952 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 53% of its contemporaries.
We're also able to compare this research output to 35 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.