Evidence map›Paper›PMID 32175908›Full record

Trial reportJMIR mHealth and uHealth2020

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

Scott Sittig, Jing Wang, Sriram Iyengar, Sahiti Myneni, Amy Franklin

Registry-linked trialAbstract readRandomized Controlled Trial
In one paragraph

Trial report in JMIR mHealth and uHealth, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04132089 (Incorporating Behavioral Trigger Measures Into a Mobile Health), which is not on this map. Cited by 27 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT04132089 nacompletednot on this map

Incorporating Behavioral Trigger Measures Into a Mobile Health (mHealth) App Design for Chronic Disease Management: Pilot Study in Diabetes

TypeinterventionalSponsorUniversity of South AlabamaRan2015 to 2017Enrolled20ConditionsDiabetes Mellitus, Type 2ArmscapABILITY
3 · Its place in the literature

Who cites it

27 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Scott SittigSchool of Computing, University of South Alabama, Mobile, AL, United States.ORCID 0000-0002-7179-152X
Jing WangSchool of Nursing, University of Texas Health Science Center at San Antonio, San Antonio, TX, United States.ORCID 0000-0002-4012-0977
Sriram IyengarCollege of Medicine Phoenix, The University of Arizona, Phoenix, AZ, United States.ORCID 0000-0002-7242-430X
Sahiti MyneniSchool of Biomedical Informatics, University of Texas Health Science Center Houston, Houston, TX, United States.ORCID 0000-0002-9211-1626
Amy FranklinSchool of Biomedical Informatics, University of Texas Health Science Center Houston, Houston, TX, United States.ORCID 0000-0003-2227-7978

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Diabetes Mellitus, Type 2Mobile ApplicationsTelemedicineFeasibility StudiesHumansPilot ProjectsFogg behavior modelinteractive health communication applicationknowledgemessagesmHealthpersuasive technologyself-efficacyself-managementsocial cognitive theorytriggers

Identifiers

PMID32175908
PMCPMC7105932

What OpenQuestion holds

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.