Mahmood Asos, Kedia Satish, Wyant David K, Ahn SangNam, Bhuyan Soumitra S
Division of Health Systems Management and Policy, School of Public Health, The University of Memphis, Memphis, TN, USA.
Division of Social and Behavioral Sciences, School of Public Health, The University of Memphis, Memphis, TN, USA.
Digit Health. 2019 Oct 10;5:2055207619882181. doi: 10.1177/2055207619882181. eCollection 2019 Jan-Dec.
Chronic medical conditions (CCs) are leading causes of morbidity and mortality in the United States. Strategies to control CCs include targeting unhealthy behaviors, often through the use of patient empowerment tools, such as mobile health (mHealth) technology. However, no conclusive evidence exists that mHealth applications (apps) are effective among individuals with CCs for chronic disease self-management.
We used data from the Health Information National Trends Survey (HINTS 5, Cycle 1, 2017). A sample of 1864 non-institutionalized US adults (≥18 years) who had a smartphone and/or a tablet computer and at least one CC was analyzed. Using multivariable logistic regressions, we assessed predisposing, enabling, and need predictors of three health-promoting behaviors (HPBs): tracking progress on a health-related goal, making a health-related decision, and health-related discussions with a care provider among smart device and mHealth apps owners.
Compared to those without mHealth apps, individuals with mHealth apps had significantly higher odds of using their smart devices to track progress on a health-related goal (adjusted odds ratio (aOR) 8.74, 95% confidence interval (CI): 5.66-13.50, <.001), to make a health-related decision (aOR 1.77, 95% CI: 1.16-2.71, <.01) and in health-related discussions with care providers (aOR 2.0, 95% CI: 1.26-3.19, <.01). Other significant factors of at least one type of HPB among smart device and mHealth apps users were age, gender, education, occupational status, having a regular provider, and self-rated general health.
mHealth apps are associated with increased rates of HPB among individuals with CCs. However, certain groups, like older adults, are most affected by a digital divide where they have lower access to mHealth apps and thus are not able to take advantage of these tools. Rigorous randomized clinical trials among various segments of the population and different health conditions are needed to establish the effectiveness of these mHealth apps. Healthcare providers should encourage validated mHealth apps for patients with CCs.
慢性疾病是美国发病和死亡的主要原因。控制慢性疾病的策略包括针对不健康行为,通常是通过使用患者赋权工具,如移动健康(mHealth)技术。然而,尚无确凿证据表明移动健康应用程序(应用)对患有慢性疾病的个体进行慢性病自我管理有效。
我们使用了来自健康信息国家趋势调查(HINTS 5,第1周期,2017年)的数据。对1864名拥有智能手机和/或平板电脑且至少患有一种慢性疾病的非机构化美国成年人(≥18岁)的样本进行了分析。我们使用多变量逻辑回归,评估了智能设备和移动健康应用程序所有者中三种健康促进行为(HPB)的诱发因素、促成因素和需求预测因素:跟踪与健康相关目标的进展、做出与健康相关的决定以及与医疗服务提供者进行与健康相关的讨论。
与没有移动健康应用程序的人相比,拥有移动健康应用程序的个体使用智能设备跟踪与健康相关目标进展的几率显著更高(调整后的优势比(aOR)8.74,95%置信区间(CI):5.66 - 13.50,<.001),做出与健康相关决定的几率(aOR 1.77,95% CI:1.16 - 2.71,<.01)以及与医疗服务提供者进行与健康相关讨论的几率(aOR 2.0,95% CI:1.26 - 3.19,<.01)。智能设备和移动健康应用程序用户中至少一种类型的健康促进行为的其他显著因素包括年龄、性别、教育程度、职业状况、有固定的医疗服务提供者以及自我评估的总体健康状况。
移动健康应用程序与患有慢性疾病的个体中健康促进行为发生率的增加相关。然而,某些群体,如老年人,受数字鸿沟影响最大,他们使用移动健康应用程序的机会较少,因此无法利用这些工具。需要在不同人群和不同健康状况下进行严格的随机临床试验,以确定这些移动健康应用程序的有效性。医疗服务提供者应鼓励为患有慢性疾病的患者使用经过验证的移动健康应用程序。