VA Palo Alto Health Care System, 795 Willow Road (MPD-152), Menlo Park, CA, 94025, USA.
Department of Psychiatry, UMass Chan Medical School, 222 Maple Ave, Shrewsbury, MA, 01545, USA.
Int J Behav Med. 2024 Apr;31(2):284-291. doi: 10.1007/s12529-023-10182-1. Epub 2023 May 22.
Blended mHealth interventions (mHealth interventions including a facilitator) promote user engagement and increase effectiveness of health behavior change interventions. Little is known about how blended mHealth interventions are used outside the research context.
In the present work, we characterized patterns of app use among users of a blended mHealth intervention in real-world conditions. Program users were Veterans Health Administration (VHA) primary care patients (n = 56) who received an invite code for a blended mHealth intervention between 2019 and 2021. Cluster analysis was used to examine user engagement with health coach visits and program features.
Of patients who received an invite code, 34% initiated the program. Most users were men (63%) and white (57%). The mean number of health conditions was 5 (68% with obesity). The mean age was 55. Cluster analysis suggested that most users did sustain engagement at either moderate (57%) or very high levels (13%). The remaining 30% of users were low engaged users. Users completing any health coach visit (about half) reported more overall engagement than their counterparts who did not. Weight was the most frequently tracked metric. Of users entering weights in the first and last month of the program (n = 18), the mean percent body weight change was 4.0% (SD = 3.6).
A blended mHealth intervention may be a scalable option to extend the reach of health behavior change interventions for those that use it. However, a significant portion of users do not initiate these interventions, choose not to use the health coach feature, or engage at lower levels. Future research should examine the role of health coaching visits in promoting sustained engagement.
混合式移动医疗干预措施（包含促进者的移动医疗干预措施）可提高用户参与度并增强健康行为改变干预措施的效果。但对于混合式移动医疗干预措施在研究环境之外的使用情况，我们知之甚少。
在本研究中，我们描述了真实环境下混合式移动医疗干预措施使用者的应用程序使用模式。该项目的使用者为退伍军人事务部（VHA）初级保健患者（n=56），他们在 2019 年至 2021 年期间收到了混合式移动医疗干预措施的邀请码。使用聚类分析来检查健康教练访问和项目功能的用户参与情况。
在收到邀请码的患者中，有 34%的人启动了该项目。大多数使用者为男性（63%）和白人（57%）。平均患有 5 种疾病（68%的人患有肥胖症）。平均年龄为 55 岁。聚类分析表明，大多数使用者的参与度维持在中等（57%）或非常高（13%）水平。其余 30%的使用者为低参与度使用者。完成任何健康教练访问的使用者（约一半）比未完成访问的使用者报告的总体参与度更高。体重是最常跟踪的指标。在计划的第一个月和最后一个月输入体重的使用者中（n=18），体重百分比变化的平均值为 4.0%（SD=3.6）。
混合式移动医疗干预措施可能是扩大健康行为改变干预措施覆盖范围的一种可扩展选项，适用于使用这些措施的人群。但是，很大一部分使用者未启动这些干预措施，选择不使用健康教练功能，或者参与度较低。未来的研究应探讨健康教练访问在促进持续参与方面的作用。
