Incorporating Behavioral Trigger Messages Into a Mobile Health App for Chronic Disease Management: Randomized Clinical Feasibility Trial in Diabetes

BackgroundAlthough 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. ObjectiveThe objective of this study was to determine the impact of an mHealth app that inc...

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Main Authors: Sittig, Scott, Wang, Jing, Iyengar, Sriram, Myneni, Sahiti, Franklin, Amy
Format: Article
Language:English
Published: JMIR Publications 2020-03-01
Series:JMIR mHealth and uHealth
Online Access:http://mhealth.jmir.org/2020/3/e15927/
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spelling doaj-2868fe1cf14141e2abcabcfad207e0bc2021-05-02T19:28:33ZengJMIR PublicationsJMIR mHealth and uHealth2291-52222020-03-0183e1592710.2196/15927Incorporating Behavioral Trigger Messages Into a Mobile Health App for Chronic Disease Management: Randomized Clinical Feasibility Trial in DiabetesSittig, ScottWang, JingIyengar, SriramMyneni, SahitiFranklin, Amy BackgroundAlthough 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. ObjectiveThe 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. MethodsThe 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. ResultsPre- 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. ConclusionsOur 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. Trial RegistrationClinicalTrials.gov NCT04132089; http://clinicaltrials.gov/ct2/show/NCT004122089http://mhealth.jmir.org/2020/3/e15927/
collection DOAJ
language English
format Article
sources DOAJ
author Sittig, Scott
Wang, Jing
Iyengar, Sriram
Myneni, Sahiti
Franklin, Amy
spellingShingle Sittig, Scott
Wang, Jing
Iyengar, Sriram
Myneni, Sahiti
Franklin, Amy
Incorporating Behavioral Trigger Messages Into a Mobile Health App for Chronic Disease Management: Randomized Clinical Feasibility Trial in Diabetes
JMIR mHealth and uHealth
author_facet Sittig, Scott
Wang, Jing
Iyengar, Sriram
Myneni, Sahiti
Franklin, Amy
author_sort Sittig, Scott
title Incorporating Behavioral Trigger Messages Into a Mobile Health App for Chronic Disease Management: Randomized Clinical Feasibility Trial in Diabetes
title_short Incorporating Behavioral Trigger Messages Into a Mobile Health App for Chronic Disease Management: Randomized Clinical Feasibility Trial in Diabetes
title_full Incorporating Behavioral Trigger Messages Into a Mobile Health App for Chronic Disease Management: Randomized Clinical Feasibility Trial in Diabetes
title_fullStr Incorporating Behavioral Trigger Messages Into a Mobile Health App for Chronic Disease Management: Randomized Clinical Feasibility Trial in Diabetes
title_full_unstemmed Incorporating Behavioral Trigger Messages Into a Mobile Health App for Chronic Disease Management: Randomized Clinical Feasibility Trial in Diabetes
title_sort incorporating behavioral trigger messages into a mobile health app for chronic disease management: randomized clinical feasibility trial in diabetes
publisher JMIR Publications
series JMIR mHealth and uHealth
issn 2291-5222
publishDate 2020-03-01
description BackgroundAlthough 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. ObjectiveThe 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. MethodsThe 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. ResultsPre- 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. ConclusionsOur 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. Trial RegistrationClinicalTrials.gov NCT04132089; http://clinicaltrials.gov/ct2/show/NCT004122089
url http://mhealth.jmir.org/2020/3/e15927/
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