Observational studyJournal of diabetes science and technology2019
What Are PWDs (People With Diabetes) Doing Online? A Netnographic Analysis.
Observational study in Journal of diabetes science and technology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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.
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
23 citing papers in PubMed.
- Utilization of Netnography as a Health Care Research Methodology: Scoping Review.Journal of medical Internet research · 2025Article
- The forgotten - overcoming challenges in diabetes care for marginalized populations.Expert review of endocrinology & metabolism · 2025Review
- Young Adults With Type 1 Diabetes and Their Perspectives on Diabetes-Related Social Media: Qualitative Study.JMIR diabetes · 2025Article
- Evaluation of a Canadian social media platform for communicating perinatal health information during a pandemic.PLOS digital health · 2025Article
- Examining the Emotional and Physical Health Impact in Users of Open-Source Automated Insulin Delivery and Sources of Support: Qualitative Analysis of Patient Narratives.Journal of medical Internet research · 2025Article
- Exploring the Potential Impact of GLP-1 Receptor Agonists on Substance Use, Compulsive Behavior, and Libido: Insights from Social Media Using a Mixed-Methods Approach.Brain sciences · 2024Article
- Characterization of COVID-19 vaccine clinical trial discussions on the social question-and-answer site Quora.Trials · 2023Article
- GLP-1 Receptor Agonists and Related Mental Health Issues; Insights from a Range of Social Media Platforms Using a Mixed-Methods Approach.Brain sciences · 2023Article
- Experience with burdens of diabetes device use that affect uptake and optimal use in people with type 1 diabetes.Endocrine connections · 2023Review
- Barriers and Facilitators to Diabetes Device Adoption for People with Type 1 Diabetes.Current diabetes reports · 2022Review
- "It Got Likes, But I Don't Think People Understood": A Qualitative Study of Adolescent Experiences Discussing Type 1 Diabetes on Social Media.Journal of diabetes science and technology · 2022Article
- Mapping Individual Differences on the Internet: Case Study of the Type 1 Diabetes Community.JMIR diabetes · 2021Article
- COVID-19 Pandemic Impact on Substance Misuse: A Social Media Listening, Mixed Method Analysis.Brain sciences · 2021Article
- Why #WeAreNotWaiting-Motivations and Self-Reported Outcomes Among Users of Open-source Automated Insulin Delivery Systems: Multinational Survey.Journal of medical Internet research · 2021Article
- Making Diabetes Care Fit-Are We Making Progress?Frontiers in clinical diabetes and healthcare · 2021Article
- Mukbang and Disordered Eating: A Netnographic Analysis of Online Eating Broadcasts.Culture, medicine and psychiatry · 2020Article
- Factors Engaging Users of Diabetes Social Media Channels on Facebook, Twitter, and Instagram: Observational Study.Journal of medical Internet research · 2020Observational
- Facebook as a Medium for the Support and Enhancement of Ambulatory Care for People With Diabetes: Qualitative Realist Evaluation of a Real-World Trial.JMIR diabetes · 2020Article
- Topic Modeling and User Network Analysis on Twitter during World Lupus Awareness Day.International journal of environmental research and public health · 2020Article
- Social Media in the Diabetes Community: a Novel Way to Assess Psychosocial Needs in People with Diabetes and Their Caregivers.Current diabetes reports · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSocial media have become a crucial channel for patient empowerment and peer support. New qualitative research underscores the fact that this "support" transcends mental health concerns, to actually provide patients with important practical tips and tricks for diabetes self-care, and product selection/decision-making information from peers.
methodsNetnography is an emerging methodology that applies an ethnographic research approach to studying activity on the social web. Researchers embed themselves in the online environment to take an observational "deep dive" into online conversations to identify themes, sentiments, and perceptions. Using this methodology in summer 2017, a team of researchers captured and analyzed hundreds of diabetes-related posts on prominent platforms Facebook, Twitter, YouTube, Instagram, Tumblr, Pinterest, Reddit, and Quora.
resultsOur team identified 6 major trends, or "life themes," in diabetes patient social media, providing insights into patient sentiments and needs. A topology of social media channels emerged, indicating which platforms are used most often for each life theme.
conclusionsFindings indicate that social media provides a significant source not only of moral support and camaraderie, but also critical education on thriving with diabetes. Importantly, we observed strong evidence of peer influence on patients' therapy and diabetes technology purchasing decisions.
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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 OpenQuestion graph.