Health App Use Among US Mobile Phone Users: Analysis of Trends by Chronic Disease Status
Health App Use Among US Mobile Phone Users: Analysis of Trends by Chronic Disease Status
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DOI：
10.2196/mhealth.7832
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发表时间：
2017-12-01
影响因子：
5
通讯作者：
Duncan, Dustin T.
中科院分区：
文献类型：
--
作者：
Robbins, Rebecca;Krebs, Paul;Duncan, Dustin T.
背景：移动应用程序有望作为一种生活方式干预公共健康，以促进健康和缓解慢性病，但人们对慢性病患者如何使用或感知移动应用程序知之甚少。目的：本研究的目的是探索慢性病患者对基于手机应用程序的健康行为和感知。方法：数据来自对美国1604名手机用户的横断面调查，评估了mHealth的使用、信念和偏好。结果：在参与者中，38.9%(314/807)的无疾病受访者报告拥有1至5个应用程序，6.6%(24/364)的高血压患者报告拥有1至5个应用程序。据报道，21.3%(172/807)的无疾病受访者、2.7%(10/364)的高血压患者、13.1%(26/198)的肥胖患者、12.3%(20/163)的糖尿病患者、12.0%(32/267)的患者以及16.6%(53/319)的患者每天使用健康应用程序2次或以上。Logistic回归结果显示，慢性病患者和非慢性病患者在健康应用程序下载方面没有显著差异(P>；0.05)。与健康状况不佳的人相比，那些自我报告健康状况非常好(优势比3.80，95%可信区间2.38-6.09，P<；.001)和健康状况良好(OR 4.77，95%可信区间2.70-8.42，P<；.001)的人更有可能下载健康应用程序。同样，与从不或很少从事体力活动的人相比，每周锻炼1天(OR2.47，95%CI 1.6-3.83，P<；.001)、每周2天(OR 4.77，95%CI 3.27-6.94，P<；0.001)、每周3至4天(OR 5.00，95%CI 3.52-7.10，P<；)的人更有可能下载健康应用程序。.001)，每周5至7天(OR 4.64，95%CI 3.11-6.92，P<；.001)。所有Logistic回归结果都控制了年龄、性别和种族或民族。结论：这项研究的结果表明，自我报告健康状况较差和体力活动率较低的人，可以说是那些从健康应用程序中受益最大的人，最不可能报告下载和使用这些健康工具。
Background: Mobile apps hold promise for serving as a lifestyle intervention in public health to promote wellness and attenuate chronic conditions, yet little is known about how individuals with chronic illness use or perceive mobile apps.Objective: The objective of this study was to explore behaviors and perceptions about mobile phone-based apps for health among individuals with chronic conditions.Methods: Data were collected from a national cross-sectional survey of 1604 mobile phone users in the United States that assessed mHealth use, beliefs, and preferences. This study examined health app use, reason for download, and perceived efficacy by chronic condition.Results: Among participants, having between 1 and 5 apps was reported by 38.9% (314/807) of respondents without a condition and by 6.6% (24/364) of respondents with hypertension. Use of health apps was reported 2 times or more per day by 21.3% (172/807) of respondents without a condition, 2.7% (10/364) with hypertension, 13.1% (26/198) with obesity, 12.3% (20/163) with diabetes, 12.0% (32/267) with depression, and 16.6% (53/319) with high cholesterol. Results of the logistic regression did not indicate a significant difference in health app download between individuals with and without chronic conditions (P>.05). Compared with individuals with poor health, health app download was more likely among those with self-reported very good health (odds ratio [OR] 3.80, 95% CI 2.38-6.09, P < .001) and excellent health (OR 4.77, 95% CI 2.70-8.42, P < .001). Similarly, compared with individuals who report never or rarely engaging in physical activity, health app download was more likely among those who report exercise 1 day per week (OR 2.47, 95% CI 1.6-3.83, P < .001), 2 days per week (OR 4.77, 95% CI 3.27-6.94, P < .001), 3 to 4 days per week (OR 5.00, 95% CI 3.52-7.10, P < .001), and 5 to 7 days per week (OR 4.64, 95% CI 3.11-6.92, P < .001). All logistic regression results controlled for age, sex, and race or ethnicity.Conclusions: Results from this study suggest that individuals with poor self-reported health and low rates of physical activity, arguably those who stand to benefit most from health apps, were least likely to report download and use these health tools.