One drop | Mobile on iPhone and apple watch: an evaluation of hbA1c improvement associated with tracking self-care
Open accessAbstract
Background: The One Drop | Mobile app supports manual and passive (via HealthKit and One Drop’s glucose meter) tracking of self-care and glycated hemoglobin A1c (HbA1c). Objective: We assessed the HbA1c change of a sample of people with type 1 diabetes (T1D) or type 2 diabetes (T2D) using the One Drop | Mobile app on iPhone and Apple Watch, and tested relationships between self-care tracking with the app and HbA1c change. Methods: In June 2017, we identified people with diabetes using the One Drop | Mobile app on iPhone and Apple Watch who entered two HbA1c measurements in the app 60 to 365 days apart. We assessed the relationship between using the app and HbA1c change. Results: Users 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 HbA1c entries. There was a significant 1.36% or 14.9 mmol/mol HbA1c reduction (F=62.60, P<.001) from the first (8.72%, 71.8 mmol/mol) to second HbA1c (7.36%, 56.9 mmol/mol) measurement. Tracking carbohydrates was independently associated with greater HbA1c improvement (all P<.01). Conclusions: Using One Drop | Mobile on iPhone and Apple Watch may favorably impact glycemic control.
AI snapshot
Written from the paper’s full text.
TL;DR
In a retrospective analysis of 256 One Drop | Mobile users on iPhone and Apple Watch, HbA1c fell significantly by 1.36% (14.9 mmol/mol) over a median of about 4 months. Carbohydrate tracking was independently associated with greater HbA1c improvement, though the nonrandomized, self-selected design precludes causal conclusions.
Key findings
- Among 256 users (65 with T1D, 191 with T2D; 22.7% female; mean diabetes duration 8.34 years), adjusted HbA1c decreased from 8.72% (71.8 mmol/mol) to 7.36% (56.9 mmol/mol), a 1.36% (14.9 mmol/mol) reduction (F=62.60, P<.001) over a median 4.06 months (IQR 2.82).
- In the T2D-only adjusted model, HbA1c decreased by 1.27% (13.9 mmol/mol), from 8.16% (65.7 mmol/mol) to 6.89% (51.8 mmol/mol) (F=364.50, P<.001).
- Users with T1D had an average 0.41% higher HbA1c than users with T2D (F=4.38, P=.04), but there was no time-by-diabetes-type interaction.
- Tracking carbohydrates was independently associated with greater HbA1c improvement, including after adjusting for covariates and insulin status in users with T2D (all P<.01).
Methods
- Retrospective analysis of existing One Drop | Mobile data; on June 6, 2017, the authors identified users with T1D or T2D using the app on iPhone and Apple Watch who had manually entered at least two HbA1c values 60 to 365 days apart (N=256).
- Self-care tracking was measured as counts of food/carbohydrates, activity, blood glucose, and medication entries between HbA1c measurements; HbA1c was self-reported. Invalid HbA1c data were excluded using HbA1c=(90-day mean blood glucose + 77.3)/35.6 and a >2.0% difference (n=44 excluded); missing gender and diabetes duration were handled with multiple imputation.
- Mixed-effects repeated measures models tested HbA1c change, and multiple regression models tested relationships between self-care tracking and HbA1c change.
Limitations
- Stated by the paper: this was not a randomized controlled trial, preventing causal conclusions; the sample was self-selected, limiting generalizability; HbA1c was self-reported rather than laboratory-assayed; passively collected data have reliability and validity issues; app features were not evaluated or adjusted for; and age and socioeconomic status were unknown.
- Evident from the text: missing data for gender (37/256, 14.4%) and diabetes duration (47/256, 18.3%) required multiple imputation; self-care variables were non-normal and dichotomized to tracked versus not tracked; and the sample was 84.8% US and 22.7% female, which may further limit generalizability.
Model-written summary. Check it against the paper before relying on it.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
5 of 12 cited sources checked · 0 supported · 0 flagged · accuracy not yet measured
- Premisecitation
An HbA1c of 7.0% or greater puts people with diabetes at risk of developing macrovascular and microvascular complications.
“An HbA1c of 7.0% or greater puts people with diabetes at risk of developing macrovascular and microvascular complications, whereas a HbA1c less than 7.0% or reducing HbA1c by 1.0% prevents complications [5,6].”
Quote in the paperSubstantial claim1 of 2 sources checked- cites [5] source
The Abstract says hyperglycemia affects both microvascular and macrovascular complications, and the Results associate lower HbA1c with lower cardiovascular risk. The paper studies people with type 1 diabetes and does not establish 7.0% as a threshold at which complications develop; the Results compare 8.0% with 7.2% instead. Page numbers are not provided in our copy. (LLM, conf=0.87)
Experimental — accuracy not yet measured - cites [6] 1998, Lancet source
- Premisecitation
For the few diabetes apps that have been studied, they significantly reduce HbA1c by an average 0.49%.
“For the few that have, they significantly reduce glycated hemoglobin A1c (HbA1c) by an average 0.49% [4].”
Quote in the paperSubstantial claim1 of 1 sources checked- cites [4] source
The Results report a mean HbA1c reduction of 0.49% versus control for app users with type 2 diabetes, and the Type 2 Diabetes section reports that this reduction was statistically significant (pages not specified). The claim does not limit its statement to type 2 diabetes; the paper reports inadequate data to establish effectiveness for type 1 diabetes. (LLM, conf=0.88)
Experimental — accuracy not yet measured
- Findingown data
Among people with type 1 or type 2 diabetes using One Drop | Mobile on iPhone and Apple Watch who entered two HbA1c measurements 60 to 365 days apart, HbA1c decreased by 1.36% (14.9 mmol/mol) from the first to the second measurement (adjusted model, F=62.60, P<.001).
“There was a significant 1.36% or 14.9 mmol/mol HbA1c reduction (F=62.60, P<.001) from the first (8.72%, 71.8 mmol/mol) to second HbA1c (7.36%, 56.9 mmol/mol) measurement.”
- Also stated in: § Results · plain
“In unadjusted and adjusted models, there was a significant 1.36% (14.9 mmol/mol) HbA1c reduction (unadjusted and adjusted F=62.60, P<.001) during a median 4.06 (IQR 2.82) months (unadjusted: 8.26% [66.8 mmol/mol] to 6.90% [51.9 mmol/mol]; adjusted 8.72% [71.8 mmol/mol] to 7.36% [56.9 mmol/mol]).”
- Also stated in: § Discussion · plain
“HbA1c decreased by 1.36% (14.9 mmol/mol) in a median of approximately 4 months.”
Quote in the paperSubstantial claim - Also stated in: § Results · plain
- Findingown data
Using the app to track carbohydrates was associated with greater HbA1c improvement even after adjusting for covariates and insulin status for users with type 2 diabetes (all P<.01).
“Tracking carbohydrates was independently associated with greater HbA1c improvement (all P<.01).”
- Also stated in: § Results · plain
“Finally, using the app to track carbohydrates was associated with greater HbA1c improvement even after adjusting for covariates and insulin status for users with T2D (all P<.01).”
- Also stated in: § Discussion · plain
“Using the app to track carbohydrates was independently associated with HbA1c improvement.”
Quote in the paperSubstantial claim - Also stated in: § Results · plain
- Findingown data
After adjusting for a priori covariates and insulin status, users with type 2 diabetes had a 1.27% (13.9 mmol/mol) HbA1c reduction (F=364.50, P<.001).
“After adjusting for a priori covariates and insulin status, users with T2D had a 1.27% (13.9 mmol/mol) HbA1c reduction (F=364.50, P<.001; 8.16% [65.7 mmol/mol] to 6.89% [51.8 mmol/mol]).”
Quote in the paperSubstantial claim
- Interpretationown data
Users' age and socioeconomic status were unknown, preventing generalizability to all ages and socioeconomic groups.
“Finally, we do not know users’ age or socioeconomic status (eg, income, education, insurance status), preventing generalizability to all ages and socioeconomic groups.”
Quote in the paperNot a substantial claim - Premisecitation
Self-reported recall of a HbA1c test is highly sensitive (99%) to medical records and claims data documenting an actual HbA1c test.
“Self-reported recall of a HbA1c test is highly sensitive (99%) to medical records and claims data documenting an actual HbA1c test [9].”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [9] Fowles, JB, 1999, Int J Qual Health Care source
- Premisecitation
A self-reported HbA1c result is sensitive (79%) to a lab HbA1c test result.
“A self-reported HbA1c result is sensitive (79%) to a lab HbA1c test result [10].”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [10] KumarSMosesonHUppalJOsbornCYHeymanMJuusolaJImpact of a diabetes mobile app with in-app coaching on glycemic control (63LB)2017American Diabetes Association 77th Scientific SessionsJun 9-13, 2017San Diego, CA
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Interpretationown data
Using One Drop | Mobile on iPhone and Apple Watch may favorably impact glycemic control.
“Using One Drop | Mobile on iPhone and Apple Watch may favorably impact glycemic control.”
- Also stated in: § Discussion · hedged
“One Drop | Mobile on Apple Watch delivers all three benefits and, based on our findings, may improve glycemic control.”
Quote in the paperSubstantial claim - Also stated in: § Discussion · hedged
- Study design and conductnone given
HbA1c measurements were self-reported rather than assessed with a laboratory assay.
“HbA1c measurements were self-reported rather than assessed with a laboratory assay.”
Quote in the paperSubstantial claim - Interpretationnone given
The sample was self-selected, limiting generalizability.
“The sample was self-selected, limiting generalizability.”
Quote in the paperNot a substantial claim
- Classified as probably not a substantial claim. 7
- May combine two claims. 7
Classified as probably not a substantial claim. May combine two claims.
PremisecitationPassive data collection makes a more useful and less burdensome diabetes app.
“Passive data collection makes a more useful and less burdensome diabetes app [1,8].”
Quote in the paperSubstantial claim2 of 2 sources checked- cites [1] source
In “There’s an App for That,” the paper describes manual diabetes-data logging as burdensome and says successful apps are likely to combine passive data collection with interactive incentives and personalized feedback. This supports the less-burdensome rationale, but does not establish that passive collection alone makes an app more useful. (LLM, conf=0.83)
Experimental — accuracy not yet measured - cites [8] source
The Methods describe a meter with wireless connectivity that lets users review blood-glucose data on a mobile app, and the Discussion reports positive responses to the app’s guidance and advice. But the paper does not establish that passive data collection, specifically, makes the app more useful or less burdensome; its usability findings concern the combined meter system and app. (LLM, conf=0.84)
Experimental — accuracy not yet measured
May combine two claims.
PremisecitationAn HbA1c less than 7.0% or reducing HbA1c by 1.0% prevents complications.
“An HbA1c of 7.0% or greater puts people with diabetes at risk of developing macrovascular and microvascular complications, whereas a HbA1c less than 7.0% or reducing HbA1c by 1.0% prevents complications [5,6].”
Quote in the paperSubstantial claim1 of 2 sources checked- cites [5] source
The Results report that lower mean HbA1c was associated with reduced cardiovascular-event risk, and the Conclusions report a cardiovascular benefit from intensive therapy in people with type 1 diabetes. The paper does not establish that HbA1c below 7.0%, or a 1.0-percentage-point reduction, prevents complications; its reported comparison is 8% versus 7.2%, and it describes reduced risk rather than prevention. (LLM, conf=0.89)
Experimental — accuracy not yet measured - cites [6] 1998, Lancet source
May combine two claims.
Findingown dataIn the adjusted model, users with type 1 diabetes had an average 0.41% higher HbA1c than users with type 2 diabetes, with no time by diabetes type interaction.
“In the adjusted model, users with T1D had an average 0.41% (F=4.38, P=.04) higher HbA1c than users with T2D, but there was no time by diabetes type interaction.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataSelf-reported HbA1c and 90-day mean blood glucose were strongly correlated (ρ=.75, P<.001), including when stratified by diabetes type (T1D: ρ=.84; T2D: ρ=.72).
“Self-reported HbA1c and 90-day mean blood glucose were strongly correlated (ρ=.75, P<.001), even when stratified by diabetes type (T1D: ρ=.84, P<.001; T2D: ρ=.72, P<.001).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenThe One Drop | Mobile app has features that were not evaluated or adjusted for in the analyses.
“The One Drop | Mobile app has features we did not evaluate or adjust for in our analyses.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductcitationMultiple imputation corrected for missing data on gender and duration of diagnosed diabetes.
“Two variables had missing data: gender (37/256, 14.4%) and duration of diagnosed diabetes (47/256, 18.3%). Multiple imputation corrected for missing data on these variables [13].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [13] Rubin, DB, 1987, Multiple Imputation for Nonresponse in Surveys source
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenAll One Drop | Mobile app users must actively agree to a EULA detailing data ownership and use.
“All One Drop | Mobile app users must actively agree to a EULA detailing data ownership and use.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
Study design and conductcitationTo exclude invalid self-reported HbA1c data, users with a greater or less than 2.0% difference between self-reported HbA1c and 90-day mean blood glucose were excluded (n=44).
“To exclude invalid self-reported HbA1c data, we used the formula HbA1c=(90-day mean blood glucose + 77.3)/35.6 [11] to compare self-reported HbA1c to 90-day mean blood glucose, and excluded users with a greater or less than 2.0% difference (n=44 were excluded).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [11] Rohlfing, CL, 2002, Diabetes Care source
May combine two claims.
Study design and conductown dataEach of four self-care types had a non-normal distribution by Shapiro-Wilk test, so each self-care variable was dichotomized to tracked versus not tracked.
“Across each of four self-care types, the Shapiro-Wilk test statistic ranged from 0.22 to 0.86 (all P<.001), signifying a non-normal distribution. We dichotomized each self-care variable to tracked versus not tracked to satisfy assumptions of statistical tests.”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationreasoningThis is not a randomized controlled trial, preventing causal conclusions.
“This is not a randomized controlled trial, preventing causal conclusions.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationMore than 1500 mobile apps support diabetes management.
“The digital diabetes ecosystem is booming [1,2], with more than 1500 mobile apps supporting diabetes management [3], yet very few diabetes apps have been studied.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [3] Research2Guidance20162017-08-04Diabetes app market report 2016-2021 https://research2guidance.com/product/diabetes-app-market-report-2016-2021/
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductnone givenOne Drop, IDS received an exemption for institutional review board approval and a waiver of informed consent from Solutions IRB to study all de-identified data owned by One Drop IDS.
“One Drop, Informed Data Systems Inc (IDS) received an exemption for institutional review board approval and a waiver of informed consent from Solutions IRB, an independent ethics review company (Little Rock, AR and Yarnell, AZ) to study all de-identified data owned by One Drop IDS.”
Quote in the paperNot a substantial claim
The paper relies on this without support.
Diabetes self-care improves HbA1c levels.
“Diabetes self-care (eg, eating fewer carbohydrate grams, being more active, taking medications) improves HbA1c levels.”
The paper relies on this without support.
Very few diabetes apps have been studied.
“yet very few diabetes apps have been studied.”
The paper relies on this without support.
No study has explored the health benefit of a tethered diabetes mobile phone and smartwatch app.
“no study to our knowledge has explored the health benefit of this type of digital solution.”
The paper relies on this without support.
This study is the first to evaluate the HbA1c benefit of a tethered diabetes mobile phone and smartwatch app.
“To our knowledge, this study is the first to evaluate the HbA1c benefit of a tethered diabetes mobile phone and smartwatch app.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The DT technology offers a unique and comprehensive approach to diabetes management, setting itself apart from other digital tools such as Livongo, Omada Health, One Drop, and mySugr.
“The DT technology offers a unique and comprehensive approach to diabetes management, setting itself apart from other digital tools such as Livongo (29), Omada Health (30), One Drop (31), and mySugr (32).”
From Personalized nutrition in type 2 diabetes remission: application of digital twin technology for predictive glycemic control (2024) · cites this paper as [31]
Experimental — accuracy not yet measuredOne Drop achieved a 1.36% HbA1c reduction at a median follow-up of approximately 4 months.
“In comparison, Livongo reported a 1.1% reduction in HbA1c at 6 months (29) and One Drop achieved a 1.36% HbA1c reduction at a median follow-up of approximately 4 months (31), both primarily through behavioral coaching.”
From Personalized nutrition in type 2 diabetes remission: application of digital twin technology for predictive glycemic control (2024) · cites this paper as [31]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Female percentage uses the wrong denominator
MinorThe stated 58/219 is 26.5%, not 22.7%. The reported 22.7% corresponds to 58/256.
Reported 22.7 · recomputed 26.484018
“were 22.7% (58/219) female”
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Type 2 Diabetes Remission and Role of Technology
Joshi, S., & Shamanna, P. (2026) · Springer eBooks · doi:10.1007/978-3-032-24854-1_13
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- Authors
- Osborn, C. Y., van Ginkel, J. R., Marrero, D. G., Rodbard, D., Huddleston, B., & Dachis, J.
- Affiliations
- University of Arizona (US)
- Corresponding author
- Osborn, Chandra Y
- ORCID
- Venue
- JMIR mHealth and uHealth
- Publisher
- JMIR Publications Inc.
- Published
- 2017-11-29
- Volume
- 5
- Issue
- 11
- Pages
- e179
- ISSN
- 2291-5222 (ISSN-L)
- PMC
- PMC5729227
- OpenAlex
- W2770842079
- Cited by
- 33
- References
- 20
- Citations by year
- 2026: 3 · 2025: 1 · 2024: 2 · 2023: 1 · 2022: 4 · 2021: 4 · 2020: 5 · 2019: 5 · 2018: 4
- FWCI
- 6.94
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- JMIR mhealth and uhealth (publishedVersion, cc-by)
- PubMed (publishedVersion)
- UA Campus Repository (The University of Arizona) (acceptedVersion, cc-by)
- PubMed Central (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Leiden Repository (Leiden University) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion, cc-by)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
- Keywords
- HbA1c, glycemic control, type 1 diabetes, type 2 diabetes, Apple Watch, HealthKit, mobile health apps, HbA1c reduction
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-09.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-09.
Cited sources are checked by gpt-6-sol.
Statistics and arithmetic are recomputed, not judged.
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