ArticleJMIR diabetes2019
Small Data and Its Visualization for Diabetes Self-Management: Qualitative Study.
Article in JMIR diabetes, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled 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.
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
9 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- User experiences and perceptions on the use of digital health technologies in the management of type 2 diabetes: an integrative systematic review.Frontiers in clinical diabetes and healthcare · 2026Pooled it
- A Systematic Review on Visualizations for Self-Generated Health Data for Daily Activities.International journal of environmental research and public health · 2022Pooled it
- Perceptions of Using Multiple Mobile Health Devices to Support Self-Management Among Adults With Type 2 Diabetes: A Qualitative Descriptive Study.Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing · 2021Trial
- Diabetes self-management: a qualitative study of education needs, practices and caregiver support in the Keta Municipality of Ghana.BMJ public health · 2024Article
- Towards a Remote Patient Monitoring Platform for Comprehensive Risk Evaluations for People with Diabetic Foot Ulcers.Sensors (Basel, Switzerland) · 2024Article
- [Mediating effect of self-efficacy on self-management ability and self-management behavior in patients with type 2 diabetes mellitus].Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences · 2023Article
- Health Care Providers' Utilization of and Perspectives on Mobile Health Technology for Diabetes and Pregnancy Support.Diabetes spectrum : a publication of the American Diabetes Association · 2021Article
- Seriously ill pediatric patient, parent, and clinician perspectives on visualizing symptom data.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAs digital healthcare expands to include the use of mobile devices, there are opportunities to integrate these technologies into the self-management of chronic disease. Purpose built apps for diabetes self-management are plentiful and vary in functionality; they offer capability for individuals to record, manage, display, and interpret their own data. The optimal incorporation of mobile tablets into diabetes self-care is little explored in research, and guidelines for use are scant.
objectiveThe purpose of this study was to examine an individual's use of mobile devices and apps in the self-management of type 2 diabetes to establish the potential and value of this ubiquitous technology for chronic healthcare.
methodsIn a 9-month intervention, 28 patients at a large multidisciplinary healthcare center were gifted internet connected Apple iPads with preinstalled apps and given digital support to use them. They were invited to take up predefined activities, which included recording their own biometrics, monitoring their diet, and traditional online information seeking. Four online surveys captured the participants' perceptions and health outcomes throughout the study. This article reports on the qualitative analysis of the open-ended responses in all four surveys.
resultsUsing apps, participants self-curated small data sets that included their blood glucose level, blood pressure, weight, and dietary intake. The dynamic visualizations of the data in the form of charts and diagrams were created using apps and participants were able to interpret the impact of their choices and behaviors from the diagrammatic form of their small personal data sets. Findings are presented in four themes: (1) recording personal data; (2) modelling and visualizing the data; (3) interpreting the data; and (4) empowering and improving health.
conclusionsThe modelling capability of apps using small personal data sets, collected and curated by individuals, and the resultant graphical information that can be displayed on tablet screens proves a valuable asset for diabetes self-care. Informed by their own data, individuals are well-positioned to make changes in their daily lives that will improve their health.
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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.