Bober Timothy, Garvin Sophia, Krall Jodi, Zupa Margaret, Low Carissa, Rosland Ann-Marie
Caring for Complex Chronic Conditions Research Center, Department of Medicine, Division of General Internal Medicine, University of Pittsburgh, Pittsburgh, PA, United States.
VA Pittsburgh Center for Health Equity Research and Promotion, Pittsburgh, PA, United States.
JMIR Diabetes. 2025 Mar 25;10:e64505. doi: 10.2196/64505.
Technologies such as mobile apps, continuous glucose monitors (CGMs), and activity trackers are available to support adults with diabetes, but it is not clear how they are used together for diabetes self-management.
This study aims to understand how adults with diabetes with differing clinical profiles and digital health literacy levels integrate data from multiple behavior tracking technologies for diabetes self-management.
Adults with type 1 or 2 diabetes who used ≥1 diabetes medications responded to a web-based survey about health app and activity tracker use in 6 categories: blood glucose level, diet, exercise and activity, weight, sleep, and stress. Digital health literacy was assessed using the Digital Health Care Literacy Scale, and general health literacy was assessed using the Brief Health Literacy Screen. We analyzed descriptive statistics among respondents and compared health technology use using independent 2-tailed t tests for continuous variables, chi-square for categorical variables, and Fisher exact tests for digital health literacy levels. Semistructured interviews examined how these technologies were and could be used to support daily diabetes self-management. We summarized interview themes using content analysis.
Of the 61 survey respondents, 21 (34%) were Black, 23 (38%) were female, and 29 (48%) were aged ≥45 years; moreover, 44 (72%) had type 2 diabetes, 36 (59%) used insulin, and 34 (56%) currently or previously used a CGM. Respondents had high levels of digital and general health literacy: 87% (46/53) used at least 1 health app, 59% (36/61) had used an activity tracker, and 62% (33/53) used apps to track ≥1 health behaviors. CGM users and nonusers used non-CGM health apps at similar rates (16/28, 57% vs 12/20, 60%; P=.84). Activity tracker use was also similar between CGM users and nonusers (20/33, 61% vs 14/22, 64%; P=.82). Respondents reported sharing self-monitor data with health care providers at similar rates across age groups (17/32, 53% for those aged 18-44 y vs 16/29, 55% for those aged 45-70 y; P=.87). Combined activity tracker and health app use was higher among those with higher Digital Health Care Literacy Scale scores, but this difference was not statistically significant (P=.09). Interviewees (18/61, 30%) described using blood glucose level tracking apps to personalize dietary choices but less frequently used data from apps or activity trackers to meet other self-management goals. Interviewees desired data that were passively collected, easily integrated across data sources, visually presented, and tailorable to self-management priorities.
Adults with diabetes commonly used apps and activity trackers, often alongside CGMs, to track multiple behaviors that impact diabetes self-management but found it challenging to link tracked behaviors to glycemic and diabetes self-management goals. The findings indicate that there are untapped opportunities to integrate data from apps and activity trackers to support patient-centered diabetes self-management.
诸如移动应用程序、连续血糖监测仪（CGM）和活动追踪器等技术可用于支持糖尿病成人患者，但尚不清楚它们如何共同用于糖尿病自我管理。
本研究旨在了解具有不同临床特征和数字健康素养水平的糖尿病成人如何整合来自多种行为追踪技术的数据以进行糖尿病自我管理。
使用≥1种糖尿病药物的1型或2型糖尿病成人对一项基于网络的调查做出回应，该调查涉及健康应用程序和活动追踪器在6个类别中的使用情况：血糖水平、饮食、运动与活动、体重、睡眠和压力。使用数字医疗保健素养量表评估数字健康素养，使用简短健康素养筛查评估一般健康素养。我们分析了受访者的描述性统计数据，并使用独立双尾t检验比较连续变量的健康技术使用情况，使用卡方检验比较分类变量，使用费舍尔精确检验比较数字健康素养水平。半结构化访谈探讨了这些技术如何以及可以如何用于支持日常糖尿病自我管理。我们使用内容分析总结访谈主题。
在61名调查受访者中，21名（34%）为黑人，23名（38%）为女性，29名（48%）年龄≥45岁；此外，44名（72%）患有2型糖尿病，36名（59%）使用胰岛素，34名（56%）目前或以前使用过CGM。受访者具有较高的数字和一般健康素养：87%（46/53）使用至少1种健康应用程序，59%（36/61）使用过活动追踪器，62%（33/53）使用应用程序追踪≥1种健康行为。CGM使用者和非使用者使用非CGM健康应用程序的比例相似（16/28，57%对12/20，60%；P = 0.84）。CGM使用者和非使用者之间的活动追踪器使用情况也相似（20/33，61%对14/22，64%；P = 0.82）。受访者报告称，各年龄组与医疗保健提供者共享自我监测数据的比例相似（18 - 44岁组为17/32，53%；45 - 70岁组为16/29，55%；P = 0.87）。数字医疗保健素养量表得分较高者中，活动追踪器和健康应用程序的联合使用率较高，但这种差异无统计学意义（P = 0.09）。受访者（18/61，30%）描述使用血糖水平追踪应用程序来个性化饮食选择，但较少使用应用程序或活动追踪器的数据来实现其他自我管理目标。受访者希望获得被动收集的数据，这些数据能轻松跨数据源整合、以可视化方式呈现，并可根据自我管理优先级进行定制。
糖尿病成人通常使用应用程序和活动追踪器，且常与CGM一起使用，以追踪多种影响糖尿病自我管理的行为，但发现将追踪行为与血糖和糖尿病自我管理目标联系起来具有挑战性。研究结果表明，整合应用程序和活动追踪器的数据以支持以患者为中心的糖尿病自我管理存在尚未开发的机会。
