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Psychosocial impacts of hybrid closed‐loop systems in the management of diabetes: a review

Overview of attention for article published in Diabetic Medicine, February 2018
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  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (57th percentile)

Mentioned by

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1 policy source
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4 X users

Citations

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89 Dimensions

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202 Mendeley
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Title
Psychosocial impacts of hybrid closed‐loop systems in the management of diabetes: a review
Published in
Diabetic Medicine, February 2018
DOI 10.1111/dme.13567
Pubmed ID
Authors

C. Farrington

Abstract

There is a pressing need for new treatment regimens that enable improved glycaemic control and reduced diabetes self-management burdens. Closed-loop, or artificial pancreas, systems represent one of the most promising avenues in this regard. Closed-loop systems connect wearable continuous glucose monitor (CGM) sensors to smartphone- or tablet-mounted algorithms that process and model CGM data to deliver precise and frequently updated doses of fast-acting insulin (and glucagon in dual-hormone systems) to users via wearable pumps. Recent studies have demonstrated that closed-loop systems offer significant benefit in terms of improved glycaemic control. However, less attention has been paid to the psychosocial impact on users of closed-loop systems. This article reviews recent research on psychosocial aspects of closed-loop usage in light of preceding research on user experience of currently available technologies such as insulin pumps and CGM sensors. The small, but growing body of research in this field reports generally positive user experience and a number of experienced benefits including: reassurance and reduced anxiety, improved sleep and confidence, and 'time off' from diabetes demands. However, these benefits are counterbalanced by important challenges, ranging from variable levels of trust to concerns about physical bulk, technical glitches and difficulties incorporating closed-loop systems into everyday life. Future research should explore psychosocial aspects of closed-loop usage in more diverse groups and with regard to clinicians, as well as users, to ensure that the clinical benefits of closed-loop systems are realized at scale in routine medical care.

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 202 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 202 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 25 12%
Student > Master 24 12%
Researcher 20 10%
Student > Ph. D. Student 18 9%
Other 10 5%
Other 30 15%
Unknown 75 37%
Readers by discipline Count As %
Medicine and Dentistry 34 17%
Nursing and Health Professions 25 12%
Psychology 19 9%
Social Sciences 10 5%
Business, Management and Accounting 6 3%
Other 32 16%
Unknown 76 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 30 March 2021.
All research outputs
#6,621,593
of 25,998,826 outputs
Outputs from Diabetic Medicine
#1,407
of 3,944 outputs
Outputs of similar age
#129,632
of 477,007 outputs
Outputs of similar age from Diabetic Medicine
#22
of 52 outputs
Altmetric has tracked 25,998,826 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 3,944 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.8. This one has gotten more attention than average, scoring higher than 64% 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 477,007 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 72% of its contemporaries.
We're also able to compare this research output to 52 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 57% of its contemporaries.