Trial reportJMIR mHealth and uHealth2020
Incorporating Behavioral Trigger Messages Into a Mobile Health App for Chronic Disease Management: Randomized Clinical Feasibility Trial in Diabetes.
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.
What it found
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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.
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.
Incorporating Behavioral Trigger Measures Into a Mobile Health (mHealth) App Design for Chronic Disease Management: Pilot Study in Diabetes
Who cites it
27 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Tailoring for Health Literacy in the Design and Development of eHealth Interventions: Systematic Review.JMIR human factors · 2025Pooled it
- Factors Influencing Adherence to mHealth Apps for Prevention or Management of Noncommunicable Diseases: Systematic Review.Journal of medical Internet research · 2022Pooled it
- Engagement With a Smartphone-Delivered Dietary Education Intervention and Its Relation to Dietary Intake and Cardiometabolic Risk Markers in People With Type 2 Diabetes: Secondary Analysis of a Randomized Controlled Trial.JMIR formative research · 2025Trial
- Effects of Self-management Program as Adjunctive to Usual Rehabilitation Exercise on Pain and Functional Outcomes in Knee Osteoarthritis: A Randomized Controlled Trial.Journal of research in health sciences · 2023Trial
- Developing a Music-Based Mobile Health Intervention for Parents and Staff in Neonatal Care and Beyond: Online Focus Group Study.JMIR pediatrics and parenting · 2026Article
- Digital Health Interventions to Support Chronic Disease Management: Systematic Scoping Review.JMIR mHealth and uHealth · 2026Article
- Four night eating behavior subtypes in young and middle-aged adults with type 2 diabetes: insights for targeted public health interventions.Frontiers in public health · 2026Article
- Efficacy of FiberMore, an AI-Based mHealth Intervention to Increase Dietary Fiber Intake Among Type 2 Diabetes Patients: Protocol for a Pilot Randomized Controlled Trial.JMIR research protocols · 2025Article
- Behavioral science meets public health: a scoping review of the fogg behavior model in behavior change interventions.BMC public health · 2025Article
- Identifying and Reducing Stigmatizing Language in Home Health Care With a Natural Language Processing-Based System (ENGAGE): Protocol for a Mixed Methods Study.JMIR research protocols · 2025Article
- Exploring Perceptions, Barriers, and Facilitators of Participation in an Exercise Snack Intervention Among U.S. Office Workers: Findings From a Pilot Study.American journal of health promotion : AJHP · 2025Article
- A systematic review of strategies in digital technologies for motivating adherence to chronic illness self-care.npj health systems · 2025Article
- Intervention for physical activity in pregnant women with pre-pregnancy obesity or overweight based on the Fogg Behavior Model.Frontiers in sports and active living · 2025Article
- How Digital Solutions Might Provide a World of New Opportunities for Holistic and Empathic Support of Patients with Hidradenitis Suppurativa.Dermatology and therapy · 2024Article
- Nurses' Use of mHealth Apps for Chronic Conditions: Cross-Sectional Survey.JMIR nursing · 2024Article
- Development of a crowdsourcing- and gamification-based mobile application to collect epidemiological information and promote healthy lifestyles in Mexico.Scientific reports · 2024Article
- Effectiveness of Digital Health Interventions Containing Game Components for the Self-management of Type 2 Diabetes: Systematic Review.JMIR serious games · 2023Review
- Analyzing the Effectiveness of mHealth to Manage Diabetes Mellitus Among Adults Over 50: A Systematic Literature Review.Journal of multidisciplinary healthcare · 2023Review
- The effect of mHealth program on behavior modification and health outcomes among patients with diabetes: A randomized controlled trial study.Belitung nursing journal · 2023Article
- Strategies to improve the implementation of intensive lifestyle interventions for obesity.Frontiers in public health · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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