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Mobile Health Technology Knowledge and Practices Among Patients of Safety-Net Health Systems in Washington State and Washington, DC

机译:华盛顿州和华盛顿特区安全净健康系统患者的移动健康技术知识和实践

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Purpose: Mobile health technology (mHealth) can reduce health disparities, but research on the health behaviors of low-income patients is needed. This study evaluates mHealth knowledge and practices of low-resource safety-net patients. Methods: We administered a 47-item questionnaire to 164 low-income patients accessing services at community health centers in the state of Washington and Washington, DC. Predictor variables included demographic factors: age, race, ethnicity, income. Outcome variables were smartphone knowledge (smartphones as a wellness tool), medical app knowledge (availability of medical-based apps), smartphone practices (ever used smartphones for wellness), health apps practices (ever used health-based apps), and medical apps practices (ever used medical-based apps). Multivariate logistic regression assessed relationships between predictor and outcome variables. Results: Mean age was 35.2 years (median: 34), and study cohort (N = 159) consisted of mostly women (68%), white race (36%), and income of < $20,000/year (63%). Outcomes: 71% and 58% reported knowledge of using smartphones for wellness and knowledge of medical apps, respectively; 76% used smartphones for wellness, with adults 50+ years of age significantly less likely than younger adults (odds ratio [OR]: 0.94, 95% confidence interval [CI]: 0.88–0.99); 48% used health apps, with adults 50+ years of age less likely than younger adults (OR: 0.95, 95% CI: 0.91–0.99) and respondents earning < $20,000/year less likely than higher earners (OR: 3.13, 95% CI: 1.02–9.57); and 58% used medical apps, with Hispanics/Latinos significantly more likely than non-Hispanics/Latinos (OR: 6.38, 95% CI: 1.04–39.02). Conclusions: Safety-net patients use mobile devices for health promotion. Age and income are important predictive factors, suggesting a more tailored design of the technology is required for broad engagement and health equity.
机译:目的:移动健康技术(MHEALT)可以减少健康差异,但需要研究低收入患者的健康行为。本研究评估了低资源安全净患者的MHEATH知识和实践。方法:我们在华盛顿特区的华盛顿特区社区卫生中心提供了47件商品问卷到164件低收入患者的服务。预测变量包括人口因子:年龄,种族,种族,收入。结果变量是智能手机知识(智能手机作为健康工具),医疗应用知识(基于医疗的应用程序的可用性),智能手机实践(曾经使用的健康智能手机),Health Apps实践(曾经使用过的基于健康的应用程序)和医疗应用程序实践(曾经使用过基于医疗的应用程序)。多变量逻辑回归评估预测器与结果变量之间的关系。结果:平均年龄为35.2岁(中位数:34),研究队列(n = 159)由大多数女性(68%),白种类(36%),以及20,000 /年收入(63%)。结果:71%和58%报告了使用智能手机的知识分别用于医疗应用的健康和知识; 76%的健康用智能手机,成年人50多岁明显不太可能比较年轻人(差距[或]:0.94,95%置信区间[CI]:0.88-0.99); 48%的卫生应用程序,成年人比较年轻人(或:0.95,95%:0.91-0.99)和受访者比较高的收入者(或:3.13,95%,受访者(如:0.95,95%)和受访者(或:3.13,95%) CI:1.02-9.57);和58%使用的医疗应用程序,与非西班牙裔/拉丁裔人(或:6.38,95%CI:1.04-39.02)明显更可能。结论:安全网患者使用移动设备进行健康促销。年龄和收入是重要的预测因素,旨在为广泛参与和健康股权提供更量身定制的技术设计。

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