School of Computing, University of South Alabama, Mobile, AL, United States.
School of Nursing, University of Texas Health Science Center at San Antonio, San Antonio, TX, United States.
JMIR Mhealth Uhealth. 2020 Mar 16;8(3):e15927. doi: 10.2196/15927.
Although there is a rise in the use of mobile health (mHealth) tools to support chronic disease management, evidence derived from theory-driven design is lacking.
The objective of this study was to determine the impact of an mHealth app that incorporated theory-driven trigger messages. These messages took different forms following the Fogg behavior model (FBM) and targeted self-efficacy, knowledge, and self-care. We assess the feasibility of our app in modifying these behaviors in a pilot study involving individuals with diabetes.
The pilot randomized unblinded study comprised two cohorts recruited as employees from within a health care system. In total, 20 patients with type 2 diabetes were recruited for the study and a within-subjects design was utilized. Each participant interacted with an app called capABILITY. capABILITY and its affiliated trigger (text) messages integrate components from social cognitive theory (SCT), FBM, and persuasive technology into the interactive health communications framework. In this within-subjects design, participants interacted with the capABILITY app and received (or did not receive) text messages in alternative blocks. The capABILITY app alone was the control condition along with trigger messages including spark and facilitator messages. A repeated-measures analysis of variance (ANOVA) was used to compare adherence with behavioral measures and engagement with the mobile app across conditions. A paired sample t test was utilized on each health outcome to determine changes related to capABILITY intervention, as well as participants' classified usage of capABILITY.
Pre- and postintervention results indicated statistical significance on 3 of the 7 health survey measures (general diet: P=.03; exercise: P=.005; and blood glucose: P=.02). When only analyzing the high and midusers (n=14) of capABILITY, we found a statistically significant difference in both self-efficacy (P=.008) and exercise (P=.01). Although the ANOVA did not reveal any statistically significant differences across groups, there is a trend among spark conditions to respond more quickly (ie, shorter log-in lag) following the receipt of the message.
Our theory-driven mHealth app appears to be a feasible means of improving self-efficacy and health-related behaviors. Although our sample size is too small to draw conclusions about the differential impact of specific forms of trigger messages, our findings suggest that spark triggers may have the ability to cue engagement in mobile tools. This was demonstrated with the increased use of capABILITY at the beginning and conclusion of the study depending on spark timing. Our results suggest that theory-driven personalization of mobile tools is a viable form of intervention.
ClinicalTrials.gov NCT04132089; http://clinicaltrials.gov/ct2/show/NCT004122089.
虽然移动医疗（mHealth）工具的使用有所增加，可用于支持慢性病管理，但缺乏基于理论的设计证据。
本研究旨在确定一种包含基于理论的触发消息的 mHealth 应用程序的影响。这些消息采用了不同的形式，遵循 Fogg 行为模型（FBM），针对自我效能、知识和自我护理。我们评估了我们的应用程序在一项涉及糖尿病患者的试点研究中修改这些行为的可行性。
该试点随机非盲研究包括从医疗保健系统内招募的两个队列的 20 名 2 型糖尿病患者。总共招募了 20 名患者进行研究，并采用了自身对照设计。每位参与者都与一个名为 capABILITY 的应用程序进行了交互。capABILITY 和其相关的触发（文本）消息将社会认知理论（SCT）、FBM 和有说服力的技术集成到交互式健康通信框架中。在这个自身对照设计中，参与者与 capABILITY 应用程序进行交互，并以交替的方式接收（或不接收）文本消息。capABILITY 应用程序本身是控制条件，同时还包括触发消息，包括火花和促进器消息。使用重复测量方差（ANOVA）分析来比较在不同条件下的行为测量和移动应用程序的参与度。使用配对样本 t 检验对每个健康结果进行分析，以确定与 capABILITY 干预相关的变化，以及参与者对 capABILITY 的分类使用。
干预前后的结果表明，7 项健康调查测量中的 3 项具有统计学意义（一般饮食：P=.03；运动：P=.005；和血糖：P=.02）。当仅分析 capABILITY 的高和中用户（n=14）时，我们发现自我效能（P=.008）和运动（P=.01）方面有统计学上的显著差异。尽管方差分析没有显示出组间的任何统计学差异，但在收到消息后，火花条件有更快响应（即较短的登录滞后）的趋势。
我们的基于理论的移动医疗应用程序似乎是一种可行的改善自我效能和健康相关行为的方法。尽管我们的样本量太小，无法得出关于特定形式触发消息的差异影响的结论，但我们的发现表明，火花触发消息可能有能力提示移动工具的使用。这一点从研究开始和结束时 capABILITY 的使用增加中得到了证明，这取决于火花的时机。我们的结果表明，基于理论的移动工具个性化是一种可行的干预形式。
ClinicalTrials.gov NCT04132089；http://clinicaltrials.gov/ct2/show/NCT004122089。
