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Cited by 156Mobile Health and mHealth ApplicationsDigital Mental Health InterventionsAsthma and respiratory diseases

The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.

The Potential of Mobile Apps for Improving Asthma Self-Management: A Review of Publicly Available and Well-Adopted Asthma Apps

Open access
Tinschert, Peter, Jakob, Robert, Barata, Filipe, Kramer, Jan-Niklas, Kowatsch, Tobias·2017·JMIR mHealth and uHealth
DOI 10.2196/mhealth.7177PMC PMC5559650
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Abstract

Background: Effective disease self-management lowers asthma’s burden of disease for both individual patients and health care systems. In principle, mobile health (mHealth) apps could enable effective asthma self-management interventions that improve a patient’s quality of life while simultaneously reducing the overall treatment costs for health care systems. However, prior reviews in this field have found that mHealth apps for asthma lack clinical evaluation and are often not based on medical guidelines. Yet, beyond the missing evidence for clinical efficacy, little is known about the potential apps might have for improving asthma self-management. Objective: The aim of this study was to assess the potential of publicly available and well-adopted mHealth apps for improving asthma self-management. Methods: The Apple App store and Google Play store were systematically searched for asthma apps. In total, 523 apps were identified, of which 38 apps matched the selection criteria to be included in the review. Four requirements of app potential were investigated: app functions, potential to change behavior (by means of a behavior change technique taxonomy), potential to promote app use (by means of a gamification components taxonomy), and app quality (by means of the Mobile Application Rating Scale [MARS]). Results: The most commonly implemented functions in the 38 reviewed asthma apps were tracking (30/38, 79%) and information (26/38, 68%) functions, followed by assessment (20/38, 53%) and notification (18/38, 47%) functions. On average, the reviewed apps applied 7.12 of 26 available behavior change techniques (standard deviation [SD]=4.46) and 4.89 of 31 available gamification components (SD=4.21). Average app quality was acceptable (mean=3.17/5, SD=0.58), whereas subjective app quality lied between poor and acceptable (mean=2.65/5, SD=0.87). Additionally, the sum scores of all review frameworks were significantly correlated (lowest correlation: r36=.33, P=.04 between number of functions and gamification components; highest correlation: r36=.80, P<.001 between number of behavior change techniques and gamification components), which suggests that an app’s potential tends to be consistent across review frameworks. Conclusions: Several apps were identified that performed consistently well across all applied review frameworks, thus indicating the potential mHealth apps offer for improving asthma self-management. However, many apps suffer from low quality. Therefore, app reviews should be considered as a decision support tool before deciding which app to integrate into a patient’s asthma self-management. Furthermore, several research-practice gaps were identified that app developers should consider addressing in future asthma apps.

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Crossref · 10.2196/mhealth.7177

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Figure 1 Systematic search and exclusion criteria.
Figure 1 Systematic search and exclusion criteria.CC BY · PubMed Central
Figure 2 Percentage of asthma apps fully applying the corresponding behavior change technique (B1-B26; N=38).
Figure 2 Percentage of asthma apps fully applying the corresponding behavior change technique (B1-B26; N=38).CC BY · PubMed Central
Figure 3 Percentage of asthma apps fully applying the corresponding gamification component (G1-G31; N=38).
Figure 3 Percentage of asthma apps fully applying the corresponding gamification component (G1-G31; N=38).CC BY · PubMed Central
Figure 4 Percentage of apps which applied at least one component fully from the corresponding gamification component category.
Figure 4 Percentage of apps which applied at least one component fully from the corresponding gamification component category.CC BY · PubMed Central

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Cites

Research works printed but not linked: 3

  1. Moorman, JE, 2012, Vital Health Stat 3, 1
  2. Ornstein, SM, 1991, J Fam Pract, 32, 82
  3. TinschertPBarataFKowatschTEnhancing asthma control through IT: design, implementation and planned evaluation of the mobile asthma companion201713th International Conference on WirtschaftsinformatikFebruary 12-15, 2017St Gallen, Switzerland

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Metadata

Authors
Tinschert, P., Jakob, R., Barata, F., Kramer, J.-N., & Kowatsch, T.
Affiliations
  • University of St.Gallen (CH)
  • Technical University of Munich (DE)
  • ETH Zurich (CH)
Corresponding author
Kowatsch, Tobias
ORCID
Venue
JMIR mHealth and uHealth
Publisher
JMIR Publications Inc.
Published
2017-08-02
Volume
5
Issue
8
Pages
e113
ISSN
2291-5222 (ISSN-L)
DOI
10.2196/mhealth.7177
PMC
PMC5559650
OpenAlex
W2739586802
Cited by
156
References
31
Citations by year
2026: 4 · 2025: 6 · 2024: 17 · 2023: 11 · 2022: 14 · 2021: 26 · 2020: 30 · 2019: 26 · 2018: 22
FWCI
34.58
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • JMIR mhealth and uhealth (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Alexandria (UniSG) (University of St.Gallen) (acceptedVersion)
  • Alexandria (UniSG) (University of St.Gallen) (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Repository for Publications and Research Data (ETH Zurich) (submittedVersion, cc-by)
  • ETH Zürich Research Collection (cc-by)
Topics
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
  • Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Asthma and respiratory diseases
Keywords
asthma, mobile health apps, asthma self-management, behaviour change techniques, gamification, app quality, Mobile App Rating Scale, digital health interventions, app adoption, quality of life, health care costs, clinical guidelines adherence, symptom monitoring, medication adherence

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