Patient-Driven Diabetes Technologies: Sentiment and Personas of the #WeAreNotWaiting and #OpenAPS Movements.


Journal

Journal of diabetes science and technology
ISSN: 1932-2968
Titre abrégé: J Diabetes Sci Technol
Pays: United States
ID NLM: 101306166

Informations de publication

Date de publication:
11 2020
Historique:
pubmed: 7 7 2020
medline: 12 10 2021
entrez: 7 7 2020
Statut: ppublish

Résumé

Patients with diabetes have developed innovative do-it-yourself (DIY) methods for adapting existing medical devices to better fit individual needs. A 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. A 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. #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.

Sections du résumé

BACKGROUND
Patients with diabetes have developed innovative do-it-yourself (DIY) methods for adapting existing medical devices to better fit individual needs.
METHOD
A 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.
RESULTS
A 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.

Identifiants

pubmed: 32627587
doi: 10.1177/1932296820932928
pmc: PMC7645133
doi:

Substances chimiques

Biomarkers 0
Blood Glucose 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

990-999

Références

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pubmed: 31127724
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pubmed: 22221955
BMC Health Serv Res. 2017 Nov 23;17(1):770
pubmed: 29169360
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pubmed: 30198751
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pubmed: 1391155
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pubmed: 27568913
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pubmed: 27510442
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pubmed: 30854884
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pubmed: 31183929
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pubmed: 27913173
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pubmed: 30348013

Auteurs

Michelle L Litchman (ML)

College of Nursing, University of Utah, Salt Lake City, USA.

Heather R Walker (HR)

University of Utah Health, Salt Lake City, USA.

Caroline Fitzgerald (C)

Hope Lab, Inc., San Francisco, CA, USA.

Mariana Gomez Hoyos (M)

Beyond Type 1, Menlo Park, CA, USA.

Dana Lewis (D)

OpenAPS, Seattle, WA, USA.

Perry M Gee (PM)

Intermountain Healthcare, Salt Lake City, UT, USA.

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Classifications MeSH