ArticleJournal of diabetes science and technology2020
Patient-Driven Diabetes Technologies: Sentiment and Personas of the #WeAreNotWaiting and #OpenAPS Movements.
Article in Journal of diabetes science and technology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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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.
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.
Who cites it
7 citing papers in PubMed, 19 citations in OpenAlex.
- Perceived Penalties for Sharing Patient Beliefs with Health Care Providers.Medical decision making : an international journal of the Society for Medical Decision Making · 2024Article
- Analysis of "Hybrid Closed Loop Using a Do-It-Yourself Artificial Pancreas System in Adults With Type 1 Diabetes".Journal of diabetes science and technology · 2024Article
- [Position paper: Open-source technology in the treatment of people living with diabetes mellitus-an Austrian perspective : Technology Committee of the Austrian Diabetes Association].Wiener klinische Wochenschrift · 2024Article
- Article
- The Experiences of Stakeholders Using Social Media as a Tool for Health Service Design and Quality Improvement: A Scoping Review.International journal of environmental research and public health · 2022Article
- Article
- A scoping review of Do-It-Yourself Automated Insulin Delivery system (DIY AID) use in people with type 1 diabetes.PloS one · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPatients with diabetes have developed innovative do-it-yourself (DIY) methods for adapting existing medical devices to better fit individual needs.
methodA multiple method study used Symplur Analytics to analyze aggregated Twitter data of #WeAreNotWaiting and #OpenAPS tweets between 2014 and 2017 to examine DIY patient-led innovation. Conversation sentiment was examined between diabetes stakeholders to determine changes over time. Two hundred of the most shared photos were analyzed to understand visual representations of DIY patient-led innovations. Finally, discourse analysis was used to identify the personas who engage in DIY patient-led diabetes technologies activities and conversations on Twitter.
resultsA total of 7886 participants who generated 46 578 tweets were included. Sentiment analysis showed that 82%-85% of interactions around DIY patient-led innovation was positive among patient/caregiver and physician groups. Through photo analysis, five content themes emerged: (1) disseminating media and conference coverage, (2) showcasing devices, (3) celebrating connections, (4) providing instructions, and (5) celebrating accomplishments. Six personas emerged across the overlapping userbase: (1) fearless leaders, (2) loopers living it up, (3) parents on a mission, (4) the tech titans, (5) movement supporters, and (6) healthcare provider advocates. Personas had varying goals and behaviors within the community.
conclusions#WeAreNotWaiting and #OpenAPS on Twitter reveal a fast-moving patient-led movement focused on DIY patient innovation that is further mobilized by an expanding and diverse userbase. Further research is indicated to bring technology savvy persons with diabetes into conversation with healthcare providers and researchers alike.
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What Socratic holds
Registered trials
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 Socratic graph.