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. For the few that have, they significantly reduce glycated hemoglobin A_1c (HbA_1c) by an average 0.49% [4].

The HbA_1c measurement is the amount of hemoglobin in the blood with glucose attached to it. People are diagnosed with diabetes when their HbA_1c level is 6.5% or greater. An HbA_1c of 7.0% or greater puts people with diabetes at risk of developing macrovascular and microvascular complications, whereas a HbA_1c less than 7.0% or reducing HbA_1c by 1.0% prevents complications [5,6]. Diabetes self-care (eg, eating fewer carbohydrate grams, being more active, taking medications) improves HbA_1c levels.

Diabetes apps offer tracking of self-care and can educate and motivate people to better care for their health [1]. Together, the widely used diabetes apps rate highly in terms of functionality, aesthetics, and engagement [7]. Devices, sensors, wearables, and watches that passively collect data may bolster engagement. Passive data collection makes a more useful and less burdensome diabetes app [1,8]. Very few apps, however, offer manual and passive data collection from a mobile phone and a smartwatch, and no study to our knowledge has explored the health benefit of this type of digital solution.

The One Drop | Mobile app offers manual data entry, but also passive data collection via Apple’s HealthKit, Apple Watch, and the Bluetooth-enabled One Drop | Chrome glucose meter. We hypothesized that there would be a pre-post HbA_1c change among people with diabetes using the One Drop | Mobile app on an iPhone and Apple Watch. We also hypothesized self-care tracking with the app would be associated with HbA_1c change.

Users (N=256) had T1D (n=65) or T2D (n=191), and were 22.7% (58/219) female, diagnosed with diabetes for a mean 8.34 (SD 8.79) years, and tracked a mean 2176.35 (SD 3430.23) self-care activities in the app between HbA_1c entries. 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.

Table 1 presents median and interquartile ranges, n (%), or mean and standard deviation with P values for diabetes type differences on observed variables before multiple imputation. Compared to users with T2D, users with T1D had diabetes for more years and entered more self-care data in the app between HbA_1c measurements, particularly blood glucose readings. Self-reported HbA_1c 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). This is consistent with previous cohort studies reporting correlations varying from .71 to .86 [12].

In unadjusted and adjusted models, there was a significant 1.36% (14.9 mmol/mol) HbA_1c 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]). In the adjusted model, users with T1D had an average 0.41% (F=4.38, P=.04) higher HbA_1c than users with T2D, but there was no time by diabetes type interaction. After adjusting for a priori covariates and insulin status, users with T2D had a 1.27% (13.9 mmol/mol) HbA_1c reduction (F=364.50, P<.001; 8.16% [65.7 mmol/mol] to 6.89% [51.8 mmol/mol]).

Finally, using the app to track carbohydrates was associated with greater HbA_1c improvement even after adjusting for covariates and insulin status for users with T2D (all P<.01).

We assessed the HbA_1c change of 256 people with diabetes using the One Drop | Mobile app on an iPhone and Apple Watch for up to one year. HbA_1c decreased by 1.36% (14.9 mmol/mol) in a median of approximately 4 months. Using the app to track carbohydrates was independently associated with HbA_1c improvement.

To our knowledge, this study is the first to evaluate the HbA_1c benefit of a tethered diabetes mobile phone and smartwatch app. One study asked people with T1D to use a phone and smartwatch app and give qualitative feedback [16]. Users appreciated entering and viewing data from their watch, the watch’s connectivity to their phone, and viewing reminders on their watch. One Drop | Mobile on Apple Watch delivers all three benefits and, based on our findings, may improve glycemic control.

There are study limitations. This is not a randomized controlled trial, preventing causal conclusions. The sample was self-selected, limiting generalizability. HbA_1c measurements were self-reported rather than assessed with a laboratory assay. Passively collected data are less prone to social desirability biases, but have their own reliability and validity issues [17]. The One Drop | Mobile app has features we did not evaluate or adjust for in our analyses. Finally, we do not know users’ age or socioeconomic status (eg, income, education, insurance status), preventing generalizability to all ages and socioeconomic groups.

Despite these limitations, people of all ages [18], race/ethnicities, and socioeconomic backgrounds [19] increasingly want to use smart devices to assist in the management of diabetes [20]. Research needs to critically evaluate diabetes apps, trackers, and smartwatches, especially as new devices enter the marketplace. Findings must be disseminated directly to consumers and to physicians who can assess these tools and make recommendations accordingly.