Real-world evaluation of a mobile health application in children with asthma
Abstract
Background Mobile health applications for asthma are increasingly being developed. However, there are no published randomized controlled trials evaluating efficacy in decreasing exacerbations.Objective To evaluate the impact of a mobile asthma application for asthma-related urgent health care usage.Methods We conducted a 6-month prospective randomized controlled trial for patients (6 months-21 years old) with persistent asthma presenting with an asthma exacerbation to the emergency department of a pediatric academic medical center. Participants were randomized to AsthmaCare (application providing medication and trigger reminders and treatment plan) or the control (online asthma information). Primary outcome measures were comparison of emergency department and urgent care visits and hospitalizations 6 months before and after randomization.Results AsthmaCare participants (n = 98) were slightly older (7.84 vs 6.24 years; P = .02) than controls (n = 95) but similar for sex (55% vs 62% boys), race (83% vs 77% African American), and insurer (89% vs 98% Medicaid). The 2 groups were similar in having more than 2 comorbidities (34% vs 32%) and receiving National Heart, Lung, and Blood Institute step 3 treatment or higher (69% vs 57%). There was no significant decrease in emergency department or urgent care visits or hospitalizations between the intervention and control groups. AsthmaCare participants were more likely to report improvement in asthma management 6 months after study enrollment (79% vs 64%; P = .06).Conclusion This randomized controlled trial did not demonstrate a significant decrease in asthma-related emergency department visits or hospitalizations among children who used a mobile health application.Trial registration ClinicalTrials.gov, Identifier NCT02333630.
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Due to absent or insufficient motivation strategies such as interactivity, proper incentives and rewards, and experiential value, the effects of digital interventions in asthma are prone to be negatively affected by the temporal decline in patients' engagement and motivation.
“Additionally, due to absent or insufficient motivation strategies such as interactivity, proper incentives and rewards [48], and experiential value [49-51], the effects of the previously reported digital interventions in asthma, such as the health condition of the young patients, are prone to be negatively affected by the temporal decline in the patients’ engagement and motivation [10,52-54].”
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- Authors
- Stukus, D. R., Farooqui, N., Strothman, K., Ryan, K., Zhao, S., Stevens, J. H., & Cohen, D. M.
- Affiliations
- Nationwide Children's Hospital (US)
- Corresponding author
- Stukus, David R.
- Venue
- Annals of Allergy, Asthma & Immunology
- Publisher
- Elsevier BV
- Published
- 2018-04
- Volume
- 120
- Issue
- 4
- Pages
- 395-400.e1
- ISSN
- 1081-1206 (ISSN-L)
- OpenAlex
- W2786208434
- Cited by
- 52
- References
- 32
- Citations by year
- 2026: 4 · 2025: 5 · 2024: 3 · 2023: 7 · 2022: 9 · 2021: 7 · 2020: 8 · 2019: 7 · 2018: 2
- FWCI
- 9.16
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Annals of Allergy Asthma & Immunology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Heffner Foundation
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Physiology › Asthma and respiratory diseases
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Keywords
- mobile health apps, childhood asthma, asthma exacerbations, emergency department visits, hospitalization, urgent care visits, medication reminders, asthma triggers, asthma management, persistent asthma
- MeSH terms
- Adolescent, Adult, Ambulatory Care, Asthma, Child, Child, Preschool, Emergency Service, Hospital, Female, Hospitalization, Humans, Infant, Male, Telemedicine, Young Adult, Mobile Applications
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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