{"title":"Examining How Adults With Diabetes Use Technologies to Support Diabetes Self-Management: Mixed Methods Study.","authors":"Timothy Bober, Sophia Garvin, Jodi Krall, Margaret Zupa, Carissa Low, Ann-Marie Rosland","doi":"10.2196/64505","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Objective: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":52371,"journal":{"name":"JMIR Diabetes","volume":"10 ","pages":"e64505"},"PeriodicalIF":0.0000,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"JMIR Diabetes","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2196/64505","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0
摘要
背景:移动应用程序、连续血糖监测仪(CGM)和活动追踪器等技术可为成年糖尿病患者提供支持,但目前尚不清楚如何将这些技术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知识水平的成人糖尿病患者如何整合来自多种行为追踪技术的数据进行糖尿病自我管理:使用≥1种糖尿病药物的1型或2型糖尿病成人接受了一项基于网络的调查,内容涉及血糖水平、饮食、运动和活动、体重、睡眠和压力等6类健康应用程序和活动追踪器的使用情况。数字健康素养采用数字健康护理素养量表进行评估,一般健康素养采用简要健康素养筛查进行评估。我们对受访者进行了描述性统计分析,并使用独立的双尾 t 检验(连续变量)、卡方检验(分类变量)和费雪精确检验(数字健康素养水平)比较了健康技术的使用情况。半结构式访谈考察了这些技术是如何以及可以如何用于支持日常糖尿病自我管理的。我们使用内容分析法总结了访谈主题:在 61 名调查对象中,21 人(34%)为黑人,23 人(38%)为女性,29 人(48%)年龄≥45 岁;此外,44 人(72%)患有 2 型糖尿病,36 人(59%)使用胰岛素,34 人(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知识水平:87%(46/53)的受访者至少使用过一种健康应用程序,59%(36/61)的受访者使用过活动追踪器,62%(33/53)的受访者使用应用程序追踪≥一种健康行为。CGM 用户和非用户使用非 CGM 健康应用程序的比例相似(16/28,57% vs 12/20,60%;P=.84)。CGM 用户和非用户使用活动追踪器的情况也相似(20/33,61% vs 14/22,64%;P=.82)。不同年龄组的受访者报告与医疗服务提供者共享自我监测数据的比例相似(18-44 岁的受访者为 17/32,53%;45-70 岁的受访者为 16/29,55%;P=.87)。在数字保健素养量表得分较高的受访者中,活动追踪器和健康应用程序的综合使用率较高,但这一差异并无统计学意义(P=.09)。受访者(18/61,30%)描述了使用血糖水平追踪应用程序来个性化饮食选择的情况,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。受访者希望数据是被动收集的,易于跨数据源整合,可视化呈现,并适合自我管理的优先事项:成人糖尿病患者通常使用应用程序和活动追踪器(通常与血糖监测仪一起使用)来追踪影响糖尿病自我管理的多种行为,但他们发现将所追踪的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,在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方面还存在尚未开发的机会。
Examining How Adults With Diabetes Use Technologies to Support Diabetes Self-Management: Mixed Methods Study.
Background: 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.
Objective: 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.
Methods: 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.
Results: 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.
Conclusions: 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.