Evidence map›Paper›PMID 36992765›Full record

ArticleFrontiers in clinical diabetes and healthcare2022

Barriers to Uptake of Open-Source Automated Insulin Delivery Systems: Analysis of Socioeconomic Factors and Perceived Challenges of Caregivers of Children and Adolescents With Type 1 Diabetes From the OPEN Survey.

Antonia Huhndt, Yanbing Chen, Shane O'Donnell, Drew Cooper, Hanne Ballhausen, Katarzyna A Gajewska, Timothée Froment, Mandy Wäldchen, Dana M Lewis, Klemens Raile and 2 more

Open access · goldFull text read
In one paragraph

Article in Frontiers in clinical diabetes and healthcare, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.3field-weighted citation impact, top 19% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 10 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 5 institutions in 4 countries.

Antonia HuhndtDepartment of Paediatric Endocrinology and Diabetes, Charité-Universitätsmedizin Berlin, Berlin, Germany.
Yanbing ChenSchool of Public Health, Physiotherapy & Sports Science, University College Dublin, Belfield, Ireland.
Shane O'DonnellSchool of Sociology, University College Dublin, Belfield, Ireland.
Drew CooperDepartment of Paediatric Endocrinology and Diabetes, Charité-Universitätsmedizin Berlin, Berlin, Germany.
Hanne BallhausenDepartment of Paediatric Endocrinology and Diabetes, Charité-Universitätsmedizin Berlin, Berlin, Germany.
Katarzyna A Gajewska#dedoc° Diabetes Online Community, Dedoc Labs GmbH, Berlin, Germany.
Timothée Froment#dedoc° Diabetes Online Community, Dedoc Labs GmbH, Berlin, Germany.
Mandy WäldchenSchool of Sociology, University College Dublin, Belfield, Ireland.
Dana M LewisOpenAPS, Seattle, WA, United States.
Klemens RaileDepartment of Paediatric Endocrinology and Diabetes, Charité-Universitätsmedizin Berlin, Berlin, Germany.
Timothy C SkinnerDepartment of Psychology, University of Copenhagen, Copenhagen, Denmark.
Katarina BrauneDepartment of Paediatric Endocrinology and Diabetes, Charité-Universitätsmedizin Berlin, Berlin, Germany.
Charité - Universitätsmedizin Berlin · DEUniversity College Dublin · IEBerlin Institute of Health at Charité - Universitätsmedizin Berlin · DERoyal College of Surgeons in Ireland · IEUniversity of Copenhagen · DK

Funding

Wellcome Trust
6 · The paper itself

Abstract

Background: As a treatment option for people living with diabetes, automated insulin delivery (AID) systems are becoming increasingly popular. The #WeAreNotWaiting community plays a crucial role in the provision and distribution of open-source AID technology. However, while a large percentage of children were early adopters of open-source AID, there are regional differences in adoption, which has prompted an investigation into the barriers perceived by caregivers of children with diabetes to creating open-source systems. Methods: This is a retrospective, cross-sectional and multinational study conducted with caregivers of children and adolescents with diabetes, distributed across the online #WeAreNotWaiting online peer-support groups. Participants-specifically caregivers of children not using AID-responded to a web-based questionnaire concerning their perceived barriers to building and maintaining an open-source AID system. Results: 56 caregivers of children with diabetes, who were not using open-source AID at the time of data collection responded to the questionnaire. Respondents indicated that their major perceived barriers to building an open-source AID system were their limited technical skills (50%), a lack of support by medical professionals (39%), and therefore the concern with not being able to maintain an AID system (43%). However, barriers relating to confidence in open-source technologies/unapproved products and fear of digital technology taking control of diabetes were not perceived as significant enough to prevent non-users from initiating the use of an open-source AID system. Conclusions: The results of this study elucidate some of the perceived barriers to uptake of open-source AID experienced by caregivers of children with diabetes. Reducing these barriers may improve the uptake of open-source AID technology for children and adolescents with diabetes. With the continuous development and wider dissemination of educational resources and guidance-for both aspiring users and their healthcare professionals-the adoption of open-source AID systems could be improved.

Indexed as

accessautomated insulin deliverybarriersclosed-loopdiabetes technologydigital innovationhealth inequalitieshuman factors

Identifiers

PMID36992765
PMCPMC10012142
OpenAlexW4287377892

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read42
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.