成人慢性疾病患者对COVID-19移动医疗工具的使用态度:卡塔尔世界杯8强波胆分析新冠肺炎影响调查二次数据分析%A Camacho-Rivera,Marlene %A Islam,Jessica Yasmine %A Rivera,Argelis %A Vidot,Denise Christina %+纽约州立大学下州健康科学大学社区健康科学系，纽约州布鲁克林克拉克森大道450号，MSC 43，纽约州，11203，美国，1 7182704386，marlene.camacho-rivera@downstate.edu %K智能手机%K移动健康%K COVID-19 %K慢性健康状况%K健康差距%K慢性疾病%K态度%K感知%K数据分析%K接触者追踪%K移动应用程序%K差距%D 2020 %7 17.12.2020 %9原始论文% JMIR移动健康Uhealth %G英语%X背景:成人慢性疾病患者因COVID-19发病率和死亡率而负担过重。尽管已经出现了COVID-19移动健康(mHealth)应用程序，但关于慢性病患者对使用COVID-19移动健康工具的态度的研究很少。目的:本研究旨在检查对COVID-19的态度，确定COVID-19移动健康工具使用的人口统计学和健康相关特征的决定因素，并评估慢性健康状况与使用COVID-19移动健康工具(例如，移动健康或基于网络的方法跟踪COVID-19暴露、症状和建议)的态度之间的关系。方法:我们使用2020年4月至6月收集的COVID-19影响调查中具有全国代表性的数据(n=10,760)。主要暴露是慢性病史，定义为自我报告的心脏代谢、呼吸、免疫相关、精神健康状况和超重/肥胖的诊断。主要结局是对COVID-19移动健康工具的态度，包括使用(1)手机应用程序跟踪COVID-19症状并接受建议的可能性;(2)一个跟踪COVID-19症状、跟踪位置并接收建议的网站;(3)使用位置数据跟踪潜在COVID-19暴露的应用程序。 Outcome response options for COVID-19 mHealth tool use were extremely/very likely, moderately likely, or not too likely/not likely at all. Multinomial logistic regression was used to compare the likelihood of COVID-19 mHealth tool use between people with different chronic health conditions, with not too likely/not likely at all responses used as the reference category for each outcome. We evaluated the determinants of each COVID-19 mHealth intervention using Poisson regression. Results: Of the 10,760 respondents, 21.8% of respondents were extremely/very likely to use a mobile phone app or a website to track their COVID-19 symptoms and receive recommendations. Additionally, 24.1% of respondents were extremely/very likely to use a mobile phone app to track their location and receive push notifications about whether they have been exposed to COVID-19. After adjusting for age, race/ethnicity, sex, socioeconomic status, and residence, adults with mental health conditions were the most likely to report being extremely/very or moderately likely to use each mHealth intervention compared to those without such conditions. Adults with respiratory-related chronic diseases were extremely/very (conditional odds ratio 1.16, 95% CI 1.00-1.35) and moderately likely (conditional odds ratio 1.23, 95% CI 1.04-1.45) to use a mobile phone app to track their location and receive push notifications about whether they have been exposed to COVID-19. Conclusions: Our study demonstrates that attitudes toward using COVID-19 mHealth tools vary widely across modalities (eg, web-based method vs app) and chronic health conditions. These findings may inform the adoption of long-term engagement with COVID-19 apps, which is crucial for determining their potential in reducing disparities in COVID-19 morbidity and mortality among individuals with chronic health conditions. %M 33301415 %R 10.2196/24693 %U http://mhealth.www.mybigtv.com/2020/12/e24693/ %U https://doi.org/10.2196/24693 %U http://www.ncbi.nlm.nih.gov/pubmed/33301415