mHealth Intervention Elements and User Characteristics Determine Utility: A Mixed-Methods Analysis.
mHealth Intervention Elements and User Characteristics Determine Utility: A Mixed-Methods Analysis.
复制标题
移动医疗干预要素和用户特征决定效用：混合方法分析。
DOI：
10.1089/dia.2016.0294
复制
发表时间：
2017
影响因子：
5.4
通讯作者：
Osborn,ChandraY
中科院分区：
文献类型：
--
作者：
Nelson,LyndsayA;Mulvaney,ShelaghA;Johnson,KevinB;Osborn,ChandraY
背景：移动的健康（mHealth）干预措施正在改善2型糖尿病（T2 DM）成人的药物依从性，但很少有研究探讨用户如何体验这些干预措施。因此，我们使用了混合方法的方法来了解T2 DM用户如何体验短信和交互式语音应答（IVR）提供的药物依从性干预称为MEssaging糖尿病（MED）.Methods：成人T2 DM使用MED作为一个为期3个月的试点研究的一部分。MED每天发送量身定制的短信，解决依从性障碍，每天发送评估短信，询问依从性，每周发送量身定制的IVR电话，提供依从性反馈，鼓励和问题，以促进问题的解决。60名参与者完成了反馈访谈。结果：完成反馈访谈的参与者平均年龄为50.0 ± 10.1岁; 65%为女性，62%为非白人; 15%的受教育程度低于高中，70%的年收入低于2万美元;平均血红蛋白A1 c为8.0% ± 1.9%。参与者对每个干预元素都给予了好评; MED帮助的常见原因包括接收有关糖尿病药物的新信息，情感支持和提醒服药。年轻人和最近诊断为T2 DM的人有更有利的经验，使用MED. In一般情况下，用户更重视短信比IVR calls.Conclusions：用户体验的考虑是至关重要的发展从事移动健康干预措施。用户反馈揭示了哪些mHealth元素具有最大价值及其原因，针对哪些用户，以及如何优化干预措施的效用和吸引力。
Background:Mobile health (mHealth) interventions are improving the medication adherence of adults with type 2 diabetes mellitus (T2DM), but few studies examine how users experience these interventions. Therefore, we used a mixed-methods approach to understand how T2DM users experience a text messaging and interactive voice response (IVR)-delivered medication adherence intervention called MEssaging for Diabetes (MED).Methods:Adults with T2DM used MED as part of a 3-month pilot study. MED sends daily tailored text messages addressing adherence barriers, daily assessment text messages asking about adherence, and weekly tailored IVR calls providing adherence feedback, encouragement, and questions to facilitate problem solving. Sixty participants completed feedback interviews. We used a mixed-methods approach to understand their experience, examining associations between participants' characteristics and their feedback.Results:Participants who completed feedback interviews were on average 50.0 ± 10.1 years old; 65% female, 62% non-white; 15% had less than a high school education, 70% had annual incomes less than $20K; and average hemoglobin A1c was 8.0% ± 1.9%. Participants rated each intervention element favorably; common reasons for MED's helpfulness included receiving novel information about diabetes medications, emotional support, and reminders to take medication. People who were younger and more recently diagnosed with T2DM had more favorable experiences using MED. In general, users valued text messages more than IVR calls.Conclusions:Consideration of the user experience is critical for developing engaging mHealth interventions. User feedback reveals what mHealth elements have the most value and why, which users to target, and how to optimize an intervention's utility and appeal.