ArticleJMIR mHealth and uHealth2017
One Drop | Mobile on iPhone and Apple Watch: An Evaluation of HbA1c Improvement Associated With Tracking Self-Care.
Article in JMIR mHealth and uHealth, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis 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
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Behavior Change Content, Understandability, and Actionability of Chronic Condition Self-Management Apps Available in France: Systematic Search and Evaluation.JMIR mHealth and uHealth · 2019Pooled it
- Personalized nutrition in type 2 diabetes remission: application of digital twin technology for predictive glycemic control.Frontiers in endocrinology · 2024Trial
- One Drop App With an Activity Tracker for Adults With Type 1 Diabetes: Randomized Controlled Trial.JMIR mHealth and uHealth · 2020Trial
- The Influence of the Smart Glucose Manager Mobile Application on Diabetes Management.Journal of diabetes science and technology · 2019Trial
- Effects of a Novel Blood Glucose Forecasting Feature on Glycemic Management and Logging in Adults With Type 2 Diabetes Using One Drop: Retrospective Cohort Study.JMIR diabetes · 2022Article
- Efficacy of Digitally Supported and Real-Time Self-Monitoring of Blood Glucose-Driven Counseling in Patients with Type 2 Diabetes Mellitus: A Real-World, Retrospective Study in North India.Diabetes, metabolic syndrome and obesity : targets and therapy · 2022Article
- Content Analysis of Apps for Growth Monitoring and Growth Hormone Treatment: Systematic Search in the Android App Store.JMIR mHealth and uHealth · 2020Article
- Accuracy of Apple Watch Measurements for Heart Rate and Energy Expenditure in Patients With Cardiovascular Disease: Cross-Sectional Study.JMIR mHealth and uHealth · 2019Article
- Impact of Use Frequency of a Mobile Diabetes Management App on Blood Glucose Control: Evaluation Study.JMIR mHealth and uHealth · 2019Article
- Improving patient self-care using diabetes technologies.Therapeutic advances in endocrinology and metabolism · 2019Review
- Advances in Care for Insulin-Requiring Patients Without Closed Loop.Diabetes technology & therapeutics · 2018Article
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe One Drop | Mobile app supports manual and passive (via HealthKit and One Drop's glucose meter) tracking of self-care and glycated hemoglobin A
objectiveWe assessed the HbA
methodsIn June 2017, we identified people with diabetes using the One Drop | Mobile app on iPhone and Apple Watch who entered two HbA
resultsUsers had T1D (n=65) or T2D (n=191), were 22.7% (58/219) female, with diabetes for a mean 8.34 (SD 8.79) years, and tracked a mean 2176.35 (SD 3430.23) self-care activities between HbA
conclusionsUsing One Drop | Mobile on iPhone and Apple Watch may favorably impact glycemic control.
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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.